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Case Study: When Heat Stress Hits an Entire Group

By Tod Schimelpfenig

Jul 23, 2019

The Setting

You’re the supervisor for several crews doing volunteer trail maintenance in a local national forest.

Since your crew leaders are new, you decide to head out to their work sites to check on their work. (Plus, it’s a good reason to get out of the office, away from email, and enjoy a hike in the hills.)

The weather has been unusually hot and humid, with daytime temperatures in the 90s °F (30s °C).

You find one of your crews around lunchtime resting under a few trees. They look lethargic and tired.

One crew member is lying on his back with his feet elevated and a wet bandanna on his forehead. Your crew leader gives you a SOAP report on the patient.

SOAP Report

The patient is a 19-year-old male who complains of weakness, dizziness, heat stress, and a headache.

The patient is supine with feet elevated. He denies any injuries and head to toe exam does not find any sign of injury.

Vital Signs

STOP READING!

What is your assessment and plan? Take a few minutes to figure out your own assessment and make a plan. Don’t cheat—no reading on without answering this first!

• Possible heat exhaustion and/or dehydration.
• Heat stroke is unlikely as patient is A+OX4 and has a measured oral temperature of 99°F (37.2°C).
• Move patient to shade and onto a pad to insulate him from the warm ground. Use cool, wet compresses to lessen heat stress.
• Hydrate and feed patient.
• Once he has time to recover, take patient back to camp to rest for the remainder of the day.

Anticipated problems

• Heat stroke, heat cramps or hyponatremia

The Story Continues...

After listening to the SOAP report and approving the assessment and plan, you check in on the other members of this trail crew. They are all tired and stressed by the heat.

You learn the crew members have been drinking water, but only about 3 liters on average rather than the minimum of 4 liters recommended by staff (the water has a brackish taste that no one likes). This is on the low end of their fluid needs.

The work days are long and run from 8:00 a.m. until 6:00 p.m. It’s been warm in the evenings, the camp is noisy, and most of the crew members are sleeping poorly.

You notice several of the crew members have bandannas on their heads, none are wearing long sleeved shirts or wide brimmed hats, and all are red and bronzed from sun exposure.

Matching Systems to the Needs of the Group 

You decide to meet with your crew leaders and make changes to manage this heat stress.

• First, you give everyone the afternoon off and take them to a lake where they can swim and cool off.
• You can’t improve the water source, so you offer some drink mixes to entice the crew members to drink more fluid.
• You encourage diligent monitoring of fluid intake by the crew leaders
• You change the work schedule to early morning and evening shifts so that people rest in the shade in the heat of the day.
• You require everyone to wear loose, long sleeved cotton shirts and hats to keep the sun at bay.
• Finally, you review strategies for preventing heat illness , predisposing factors, and the subtle signs and symptoms of heat stress.

Notes from NOLS: Injury/Illness Prevention is a Leadership Skill

The supervisor in this case study recognizes that preventing heat illness is a leadership task, and steps in to manage it before it becomes a broader medical problem.

When the weather heads up, leaders need to be alert for signs of developing heat illness in their groups. Environmental risk factors of high heat and humidity, coupled with dehydration, exertion, and overdressing, should raise caution flags. The vague symptoms of fatigue, headache, weakness, irritability, and malaise should be recognized as indicators of dehydration and heat illness.

Flagging and Preventing Heat Illness

Sources of heat stress.

• Environmental heat is an obvious source of stress that is increased when humidity lessens the efficiency of heat loss through sweat.
• Other factors include dehydration, age, general health, use of medications or alcohol, and fatigue.
• Heat illness can happen quickly if people have to work hard in very hot and humid conditions, or are not acclimatized to heat. It can also be cumulative and reveal itself after several days of heat stress have worn you down.

Higher-Risk Individuals & Conditions

• Patients with underlying health problems (illness or injury)
• Children, who have underdeveloped physical mechanisms that contribute to the incidence of heat illness.
• Individuals with compromised heart function are less able to adjust when stressed by heat.
• There is a correlation between lack of sleep, or fatigue, and the development of heat illness.
• Antihistamines, antipsychotic agents, thyroid hormone medications, amphetamines, and alcohol are among the drugs that have been implicated in the development of heat illness. Some interfere with thermoregulation; others increase metabolic activity or interfere with sweating.

Preventing Heat Illnesses

Acclimatizing to heat.

We can acclimatize to heat. When acclimatized, sweating happens faster and sooner and with the loss of fewer electrolytes in the sweat, and with improved physical and mental tolerance to heat.

Acclimating to heat requires one to two hours of exercise in the heat daily for approximately 10 to 14 days.

General Tips

• Stay hydrated, but avoid overhydration . Monitor urine output for color and quantity.
• Individual fluid needs can vary depending on the person, activity, and environment. 3-4 liters of fluid a day is a good reference point for many people in general outdoor activities in moderate environments.
• Exercise early or late in the day in hot environments. Rest often.
• Give yourself 10–14 days to acclimatize to hot environments before you begin heavy exercise.
• Wear well-ventilated, open weave clothing. Cover your head and wear sunglasses.
• The very young and older adults are less efficient at heat loss, as are people who are very muscular or overweight.
• Drugs that have been known to contribute to heat illnesses include: alcohol, antidepressants, antihistamines, some anesthetics, cocaine and amphetamines.

Keep your skills fresh: Recertify with NOLS Wilderness Medicine

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Tod Schimelpfenig

As a NOLS Instructor since 1973 and a WEMT, volunteer EMT on ambulance and search and rescue squads since the 70s, Tod Schimelpfenig has extensive experience with wilderness risk management. He has used this valuable experience to conduct safety reviews as well as serve as the NOLS Risk Management Director for eight years, the NOLS Rocky Mountain Director for six years, and three years on the board of directors of the Wilderness Medical Society, where he received the WMS Warren Bowman Award for lifetime contribution to the field of wilderness medicine. Tod is the founder of the Wilderness Risk Manager’s Committee, has spoken at numerous conferences on pre-hospital and wilderness medicine, including the Australian National Conference on Risk Management in Outdoor Recreation, and has taught wilderness medicine around the world. He has written numerous articles on educational program, risk management and wilderness medicine topics, and currently reviews articles for the Journal of Wilderness and Environmental Medicine. Additionally, he is the author of NOLS Wilderness Medicine and co-author of Risk Management for Outdoor Leaders, as well as multiple articles regarding wilderness medicine. Tod is the retired curriculum director for NOLS Wilderness Medicine and is an active wilderness medicine instructor

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You and three friends are hiking through a sandy wash in the desert. Even though it is fall, daytime high temperatures have been 100°F (37.7°C) with no clouds in the sky.

Your group encounters another party of two hikers, one of whom is lying on the ground under the only small juniper in the area. The other hiker seems worried. You ask if everything is ok. One hiker is fine but asks if you can help with the patient, who he worries is dehydrated or having a “heat stroke.”

Take Action Now to Prevent Heat-Related Illness at Work

Before we enter summer, we should plan ahead for work-related heat exposure and the potential for heat-related illness among workers. Exposure to heat combined with physical activity and other factors in the environment can increase the body’s temperature and cause heat stress . The body responds to heat stress by trying to stabilize body temperature, a process which can lead to heat strain. Many factors impact work-related heat stress and heat strain, including air temperature, humidity, clothing, personal protective equipment , and hydration. Heat stress that leads to unrelieved heat strain increases the risk for heat-related illness . Prevention of heat-related illness in workers may be needed year-round, depending on work duties and the environment.

Heat Stress Impacts Many Types of Workers

Workers in a wide variety of industries are exposed to hot environments during work and are at risk for heat-related illness. A recent study using California state-wide workers’ compensation data identified public administration (35% of the total cases); agriculture, forestry, fishing, and hunting (13%); and construction (8%) as industry groups with the highest number of heat-related illnesses. Industries with the highest rates were agriculture, forestry, fishing, and hunting; public administration; and mining. [3] Younger workers and male workers were at greater risk than other demographic groups. This study also found that 9% of heat-related illness cases happened to new workers within two weeks of hire.

Heat Stress at Work and Kidney Injury: An Emerging Issue

Emerging issues associated with occupational heat stress are acute kidney injury, the sudden loss of kidney function, and chronic kidney disease (the slow and gradual loss of kidney function). Kidney failure can lead to a range of illnesses and even death. The risk of acute kidney injury increases with high body temperatures and lack of water during physical work in the heat. [4] Researchers studying chronic kidney disease of nontraditional origin identified occupational heat stress as the strongest risk factor. [5]

A serious condition involving the kidneys is rhabdomyolysis , which is caused by high body temperature, physical exertion, overuse of muscles, and/or damage to muscles (e.g., crush injury from a fall). With rhabdomyolysis, damaged muscle breaks down and releases excess proteins and electrolytes into the blood, causing kidney damage and other severe medical problems.

Many occupations present an increased risk for workers for heat‐related acute and chronic kidney injury at work; for example, one study found that large numbers of mail and package delivery workers experience acute kidney injury. [6]  A recent science review of chronic kidney injury prevention among agricultural workers suggested that addressing several workplace factors including hyperthermia, hydration, and other factors at once is necessary. [7]

Plan Ahead: Address Workplace Heat Before Exposing Workers

Many workplace controls are available to minimize heat-related illness among workers. A complete heat stress program for the workplace should include assessing the risk, limiting heat exposure, reducing metabolic heat load, acclimating workers, encouraging hydration, and providing periodic training for heat stress and heat-related illness. Workplace-based educational programs have been shown to improve workers’ knowledge about heat illness; [8] training has been identified as a central part of a heat stress educational program to decrease heat-related illness among outdoor workers. [9]

When providing heat stress education and training, consider your workers and what delivery methods might work best. Small construction firms may face language and communication challenges when providing training to immigrant workers. [10] Small businesses often have fewer resources, greater time demands on managers, and fewer employees to address safety. [11] [12] [13] [14] As a result, small businesses are burdened with higher injury and fatality rates. [15] [16]

For many immigrant workers, a combination of factors can make them more vulnerable to heat-related illnesses, including seasonality, extreme work conditions, a lack of knowledge and safety training, poverty, cultural differences, and language barriers. [17] [18] [19] [20] [21] Delivery methods for education and training should consider length of time for trainings (for example, short trainings spaced out over a few days if a longer training does not fit work schedules) and formats of handouts and other shared educational materials (for example, concise, illustrated and available in multiple languages). The NIOSH Heat Stress topic page has a variety of materials, including guidance, posters, fact cards, infosheets, and a mobile app that may be used to supplement trainings. Train workers before hot outdoor work begins and tailor training to cover worksite-specific conditions.

NIOSH Recommended Heat Stress Training Program Elements

Employers should provide heat stress training for all workers and supervisors on the following:

• Recognizing the signs and symptoms of heat-related illnesses and administration of first aid. • Causes of heat-related illnesses and the procedures that will minimize the risk, such as drinking enough water and monitoring the color and amount of urine output. • Proper care and use of heat-protective clothing and equipment and the added heat load caused by exertion, clothing, and personal protective equipment. • Effects of non-work factors (such as drugs, alcohol, obesity, etc.) on ability to adapt to occupational heat stress. • The importance of acclimatization (see below). • The importance of immediately reporting to the supervisor any symptoms or signs of heat-related illness in themselves or in coworkers. • Procedures for responding to symptoms of possible heat-related illness and for contacting emergency medical services.

In addition, supervisors should also be trained on:

• How to implement appropriate acclimatization. • Procedures to follow when a worker has symptoms consistent with heat-related illness, including emergency response procedures. • Monitoring weather reports and responding to hot weather advisories. • Monitoring and encouraging adequate fluid intake and rest breaks.

Acclimatize Your Workforce

Over time, our bodies can often be trained to better tolerate heat exposure through a gradual process known as acclimatization . Heat strain occurs as the body attempts to maintain a safe and stable body temperature. Excessive heat strain can by identified by profuse sweating, rapid heart rate and elevated core body temperature. During acclimatization, the body becomes more efficient at maintaining a safe and stable core temperature.

Lack of work experience and acclimatization are well‐established risk factors for heat-related illness. [22] A 2018 case series of heat-related illnesses found that nearly 75% of fatal incidents occurred in the first week on the job. [23] Workers can become acclimatized to heat by steadily increasing their work time in hot environments over several days. Despite the evidence for needing acclimatization, a 2018 study of cleanup responders found that only about 1 in 4 reported using an acclimatization plan. [24]

Strategies for acclimatizing workers include gradually increasing workers’ time in hot conditions over 7 to 14 days; and planning for a range of schedules for new or returning workers to increase their exposure. Training for supervisors should include how to appropriately acclimatize and supervise new employees the first 14 days or until they are fully acclimatized.

The following resources will help you develop and implement a program to address hot working conditions and prevent heat-related illness.

• NIOSH Heat Stress
• NIOSH Criteria for a Recommended Standard: Occupational Exposure to Heat and Hot Environments
• NIOSH Heat Stress: Acclimatization Fact Sheet
• NIOSH Rhabdomyolysis
• NIOSH Science Blog: Heat Stress Imposed by PPE Worn in Hot and Humid Environments
• NIOSH Science Blog: Heat Stress in Construction
• NIOSH Science Blog: Adjusting to Work in the Heat: Why acclimatization Matters
• OSHA Safety and Health Topics: Heat
• OSHA Water. Rest. Shade. – Acclimatizing Workers
• CPWR Working in Hot Weather

We would love to hear from you

In the comment section below, please share your workplace heat stress prevention successes and challenges that you’ve faced.

• Has your workplace developed innovative or unique training materials or methods you feel may be helpful to others?
• What are the primary challenges your workplace faces in incorporating acclimatization as part of your overall workplace OSH plan related to excessive heat?

Douglas Trout, MD, MHS, is a medical officer at NIOSH.

Brenda Jacklitsch, PhD, MS, is Coordinator of the NIOSH Small Business Assistance Program and a research health scientist in the Division of Science Integration.

Scott Earnest, PhD, PE, CSP, is the Associate Director for Construction Safety and Health.

CDR Elizabeth Garza, MPH, CPH, is Assistant Coordinator for the Construction Sector in the NIOSH Office of Construction Safety and Health.

J’ette Novakovich, PhD, MS, is Assistant Coordinator of the Emergency Preparedness and Response, Core and Specialty Program and a Writer-Editor in the Division of Science Integration.

This blog has been translated into Spanish .

[1] Varghese BM, Hansen AL, Williams S, Bi P, Hanson-Easey S, Barnett AG, et al [2018]. Are workers at risk of occupational injuries due to heat exposure? A comprehensive literature review. Safety Science 110: 380–392. https://doi.org/10.1016/j.ssci.2018.04.027

[2] Calkins MM, Bonauto D, Hajat A, Lieblich M, Seixas N, Sheppard L, Spector JT [2019]. A case-crossover study of heat exposure and injury risk among outdoor construction workers in Washington State, 2019. Scand J Work Environ Health 45(6):588–599. https://doi.org/10.5271/sjweh.3814

[3] Heinzerling A, Laws RL, Frederick M, Jackson R, Windham G, Materna B, Harrison R [2020]. Risk factors for occupational heat‐related illness among California workers, 2000–2017. Am J Ind Med 63:1145–1154. DOI: 10.1002/ajim.23191

[4] Chapman CL, Johnson BD, Vargas NT, Hostler D, Parker MD, Schlader ZJ [2020]. Both hyperthermia and dehydration during physical work in the heat contribute to the risk of acute kidney injury. J Appl Physiol 128: 715–728.

[5] Wesseling C, Glaser J, Rodríguez-Guzmán J, Weiss I, Lucas R, Peraza S, et al [2020]. Chronic kidney disease of non-traditional origin in Mesoamerica: a disease primarily driven by occupational heat stress. Rev Panam Salud Publica. 2020;44:e15. https://doi.org/10.26633/RPSP.2020.15

[6] Tannis C [2020]. Letter to the editor: Heat illness and renal injury in mail and package delivery workers. Am J Ind Med 63:1059–1061. DOI: 10.1002/ajim.23169

[7] Hansson E, Glaser J, Jakobsson K, Weiss I, Wesseling C, Lucas RAI, et al [2020]. Pathophysiological mechanisms by which heat stress potentially induces kidney inflammation and chronic kidney disease in sugarcane workers. Nutrients 12: 1639. doi:10.3390/nu12061639

[8] El-Shafei DA, Bolbol SA, Awad Allah MB, Abdelsalam AE [2018]. Exertional heat illness: knowledge and behavior among construction Workers. Environ Sci Pollut Res 25:32269–32276

[9] McCarthy RB, Shofer F, Green-McKenzie J [2018]. Occupational heat illness in outdoor workers before and after the implementation of a heat stress awareness program. https://oem.bmj.com/content/75/Suppl_2/A505.1

[10] Cunningham TR, Guerin RJ, Keller BM, Flynn MA, Salgado C, Hudson D [2018]. Differences in safety training among smaller and larger construction firms with non-native workers: Evidence of overlapping vulnerabilities. Safety Science 103:62-69.

[11] De Kok JM [2005]. Precautionary actions within small and medium‐sized enterprises. J Journal of Small Business Management 43(4):498-516.

[12] Hasle P and Limborg HJ [2006]. A review of the literature on preventive occupational health and safety activities in small enterprises. Ind Health 44(1):6-12.

[13] Parker D, Brosseau L, Samant Y, Pan W, Xi M, Haugan D [2007]. A comparison of the perceptions and beliefs of workers and owners with regard to workplace safety in small metal fabrication businesses. Am J Ind Med. 50(12):999-1009.

[14] Sinclair RC and Cunningham TR [2014]. Safety activities in small businesses. Safety Science 64:32-38.

[15] Buckley JP, Sestito JP, Hunting KL [2008]. Fatalities in the landscape and horticultural services industry, 1992–2001. Am J Ind Med. 51(9):701-713.

[16] Mendeloff JM, Nelson C, Ko K, Haviland A [2006]. Small businesses and workplace fatality risk: an exploratory analysis. Vol. 371. Rand Corporation.

[17] Gany F, Dobslaw F, Ramirez J, Tonda J, Lobach I, and Leng J [2011]. Mexican urban occupational health in the US: A population at risk. Journal of community health 36(2):175-179.

[18] Gomberg‐Muñoz R [2010]. Willing to work: Agency and vulnerability in an undocumented immigrant network. J American Anthropologist 112(2):295-307.

[19] Flynn MA [2014]. Safety & the diverse workforce: lessons from NIOSH’s work with Latino immigrants. Professional Safety 59(6):p. 52.

[20] Brunette M [2005]. Development of educational and training materials on safety and health: Targeting Hispanic workers in the construction industry. J Family Community Health. 28(3):253-266.

[21] Stoecklin-Marois M, Hennessy-Burt T, Mitchell D, Schenker M. [2013]. Heat-related illness knowledge and practices among California hired farm workers in The MICASA Study. Ind Health 51(1): p. 47-55.

[22] Arbury S, Jacklitsch B, Farquah O, Hodgson M, Lamson G, Martin H, Profitt A; Office of Occupational Health Nursing, Occupational Safety and Health Administration (OSHA) [2014]. Heat illness and death among workers – United States, 2012-2013. MMWR Morb Mortal Wkly Rep. 63(31):661-665.

[23] Tustin AW, Cannon DL, Arbury SB, Thomas RJ, Hodgson MJ [2018]. Risk factors for heat-related illness in U.S. workers: an OSHA case series. JOEM 60 (8). DOI: 10.1097/JOM.0000000000001365

[24] Jacklitsch BL, King KA, Vidourek RA, Merianos AL [2018]. Heat-Related Training and Educational Material Needs among Oil Spill Cleanup Responders, Environmental Health Insights, 12: 1178630218802295. DOI: 10.1177/1178630218802295

4 comments on “Take Action Now to Prevent Heat-Related Illness at Work”

Comments listed below are posted by individuals not associated with CDC, unless otherwise stated. These comments do not represent the official views of CDC, and CDC does not guarantee that any information posted by individuals on this site is correct, and disclaims any liability for any loss or damage resulting from reliance on any such information. Read more about our comment policy » .

have developed and presnted training etc also have a spanish lang version of one; have worked with brown public health school who have done community based projects.. jc

It would be very helpful if NIOSH and OSHA would collect any fact sheets (especially Acclimatization, Hydration, Work/Rest) or public information that might be available in Spanish. Or provide links to those translations.

Below are some heat stress products available in Spanish:

– OSHA-NIOSH Heat App (if the user’s phone has Spanish enabled then content will load in Spanish) – NIOSH Fast Fact card – OSHA-NIOSH Infosheet – NIOSH Workplace Solution – OSHA Heat Illness Prevention

Thank you for this great update on heat illness however in my place of work I tried to create awareness program on heat stress to the supervisor and workers ,with knowledge on signs and symptoms, also provided cold water and hydralyte for rehydration, and maintain job rotation and frequent rest in refuge area and reporting procedures in case of emergency.

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Morbidity and Mortality Weekly Report ( MMWR )

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Heat Illness and Death Among Workers — United States, 2012–2013

Sheila Arbury , MPH 1 , Brenda Jacklitsch , MS 2 , Opeyemi Farquah 3 , Michael Hodgson , MD 4 , Glenn Lamson , MS 5 , Heather Martin , MSPH 3 , Audrey Profitt , MPH 6 (Author affiliations at end of text)

Exposure to heat and hot environments puts workers at risk for heat stress, which can result in heat illnesses and death. This report describes findings from a review of 2012‒2013 Occupational Safety and Health Administration (OSHA) federal enforcement cases (i.e., inspections) resulting in citations under paragraph 5(a)(1), the "general duty clause" of the Occupational Safety and Health Act of 1970. That clause requires that each employer "furnish to each of his employees employment and a place of employment which are free from recognized hazards that are causing or are likely to cause death or serious physical harm to his employees" ( 1 ). Because OSHA has not issued a heat standard, it must use 5(a)(1) citations in cases of heat illness or death to enforce employers' obligations to provide a safe and healthy workplace. During the 2-year period reviewed, 20 cases of heat illness or death were cited for federal enforcement under paragraph 5(a)(1) among 18 private employers and two federal agencies. In 13 cases, a worker died from heat exposure, and in seven cases, two or more employees experienced symptoms of heat illness. Most of the affected employees worked outdoors, and all performed heavy or moderate work, as defined by the American Conference of Governmental Industrial Hygienists ( 2 ). Nine of the deaths occurred in the first 3 days of working on the job, four of them occurring on the worker's first day. Heat illness prevention programs at these workplaces were found to be incomplete or absent, and no provision was made for the acclimatization of new workers. Acclimatization is the result of beneficial physiologic adaptations (e.g., increased sweating efficiency and stabilization of circulation) that occur after gradually increased exposure to heat or a hot environment ( 3 ). Whenever a potential exists for workers to be exposed to heat or hot environments, employers should implement heat illness prevention programs (including acclimatization requirements) at their workplaces.

To understand the effectiveness of existing heat illness prevention campaigns and tools, OSHA convened the Heat Illness Workgroup* to conduct a systematic review of cases of occupational heat illness or death cited for federal enforcement under paragraph 5(a)(1) during 2012–2013. Cases were identified by OSHA's Directorate of Enforcement Programs. For all cases reviewed, the workgroup established a list of program elements it considered important based on published literature and members' professional experience ( Table ). These included information on local weather conditions, work processes and workload, employer heat illness prevention program elements, health outcomes, numbers of persons affected, and individual risk factors. When needed, OSHA Compliance Safety and Health Officers were consulted for case clarification.

During 2012‒2013, a total of 20 cases were cited for federal enforcement under paragraph 5(a)(1). Thirteen cases involved a worker death attributed to heat exposure, and seven involved two or more workers with symptoms of heat illness. Thirteen worksites were outdoors. In eight cases, workers performed heavy work, and in 12 cases they performed moderate work per American Conference of Governmental Industrial Hygienists workload definitions ( 2 ). Seven cases occurred in indoor facilities with a local heat source, such as laundry equipment or combustion engines. The cases occurred in various workplaces, including two in solid waste collection, two in mail delivery, nine in outdoor worksites (e.g., ship repair, landscaping, roofing, and oil servicing), two in laundries, and five in indoor worksites with machinery or other heat sources. All heat illnesses and deaths occurred on days with a heat index in the range of 84.0°F–105.7°F (29.0°C–41.0°C), although those working in direct sunlight might have experienced a heat index that was up to 15.0°F (8.3°C) higher than reported ( 3 ).

Thirteen employers had not incorporated an approach to identifying heat illness risk (e.g., heat index), as described by the National Oceanic and Atmospheric Administration, into their heat illness prevention program ( 4 ). None of the employer heat illness prevention programs were complete. Twelve had no program at all, seven provided inadequate water management, and 13 failed to provide shaded rest areas. Only one of the employers used work-rest cycles (i.e., scheduled periods of rest between periods of work based on temperature, humidity, and the intensity of the work activity), and none had an acclimatization program ( Table ). Four of the 13 deaths occurred on the first day at work in a new job or after returning from time away from the job, three on the second day, and two on the third day; four deaths occurred among long-time employees. In the cases that involved heat illness but not a death, the number of days on the job did not appear to contribute to any of the heat-related incidents.

Heat-related deaths often occur in occupations in which workers are performing tasks in hot environments, causing them to build metabolic heat faster than their bodies can release heat and cool down. In North Carolina, during 2008–2010, work-related heat illnesses resulting in emergency department visits were more common than work-related emergency department visits with any other cause among persons aged 19–45 years ( 5 ). In Maricopa County, Arizona, during 2002–2009, outdoor work in construction and agriculture accounted for 35% of heat-related deaths in men ( 6 ). A total of 68 crop production worker deaths were reported in the United States during 1992–2006, resulting in an annual average death rate of 0.39 deaths per 100,000 crop workers ( 7 ). Particularly in agriculture, estimates of heat illness cases are likely to be undercounts because some surveys exclude workers on small farms ( 8 ).

Although OSHA's Heat Illness Prevention Campaign's core message "Water. Rest. Shade." has been widely disseminated and reflects many similar public health messages ( 9 ), this review shows that some employers have not developed complete heat illness prevention programs. Strikingly, in the cases reviewed, the failure to support acclimatization appears to be the most common deficiency and the factor most clearly associated with death. Employers need to provide time to acclimatize for workers absent from the job for more than a few days, new employees, and those working outdoors during an extreme heat event or heat wave. Employers must ensure that all workers acclimatize to hot environments by gradually increasing duration of work in the hot environment. In addition, health care providers should be aware of the loss of acclimatization in their patients who have been out of work for a week or more and counsel them that they will need time to regain acclimatization once they return to their job. New workers and all workers returning from an absence of more than a week should begin with 20% of the usual duration of work in the hot environment on the first day, increasing incrementally by no more than 20% each subsequent day ( 3 ). During a rapid change leading to excessively hot weather or conditions such as a heat wave, even experienced workers should begin on the first day of work in excessive heat with 50% of the usual duration of work, 60% on the second day, 80% on the third, and 100% on the fourth day ( 9 ). Full acclimatization might take up to 14 days or longer to attain, depending on individual or environmental factors.

Employers should be aware of the importance of all elements, including acclimatization, in their heat illness prevention programs. They should be diligent about 1) designating a person to develop, implement, and manage the program, 2) monitoring the temperature (e.g., heat index and wet bulb globe temperature † ) of their worksite, 3) providing water and rest breaks in a shaded, cool area, 4) acclimatizing workers by gradually increasing the exposure to heat or a hot environment, 5) modifying work schedules as necessary to reduce workers' exposure to heat, 6) training workers on the signs and symptoms of heat illness, 7) monitoring workers for signs of heat stress, and 8) planning for emergencies and response. Guidance provided by CDC's National Institute for Occupational Safety and Health includes information on acclimatization, work-rest schedules, adequate hydration, indices for monitoring environmental heat stress (including wet bulb globe temperature), and other recommendations that can be used for developing a heat illness prevention program ( 9,10 ).

The findings in this report are subject to at least three limitations. First, information collected retrospectively might fail to identify important elements such as individual prior acclimatization that might have been missed by OSHA Compliance Safety and Health Officers. Second, information from weather websites regarding past weather conditions relatively close to the worksite under consideration might not accurately represent conditions at the worksite itself (especially because at least one of the weather stations was more than 100 miles from the worksite) and thus might fail to identify the actual impact of weather. Finally, OSHA Compliance Safety and Health Officers performing workplace inspections might have missed program elements identified by the Heat Illness Workgroup because these elements were not part of routine information collection.

Additional information and resources regarding heat stress are available from CDC at http://www.cdc.gov/niosh/topics/heatstress and from OSHA at https://www.osha.gov/SLTC/heatillness/edresources.html .

1 Office of Occupational Health Nursing, Occupational Safety and Health Administration (OSHA); 2 Education and Information Division, National Institute for Occupational Safety and Health, CDC; 3 Office of Science and Technology Assessment, OSHA; 4 Office of Occupational Medicine, OSHA; 5 Salt Lake Technical Center, Directorate of Technical Support and Emergency Management, OSHA; 6 Office of Health Enforcement, OSHA (Corresponding author: Michael J. Hodgson, [email protected] , 202-693-1768)

• Section 5(a)(1) of the Occupational Safety and Health Act of 1970 (29 U.S.C.654) and 29 CFR 1960.8(a) for federal agencies. Available at https://www.osha.gov/pls/oshaweb/owadisp.show_document?p_id=3359&p_table=oshact .
• American Conference of Governmental Industrial Hygienists. TLVs and BEIs: threshold limit values for chemical substances and physical agents of biological exposure indices. Heat stress and strain. Cincinnati, OH: American Conference of Governmental Industrial Hygienists; 2007.
• Occupational Safety and Health Administration. Campaign to prevent heat illness in outdoor workers. Washington, DC: US Department of Labor, Occupational Safety and Health Administration; 2014. Available at https://www.osha.gov/SLTC/heatillness .
• National Oceanic and Atmospheric Administration. Heat: a major killer. Silver Spring, MD: National Oceanic and Atmospheric Administration; 2014. Available at http://www.nws.noaa.gov/os/heat/index.shtml .
• Rhea S, Ising A, Fleischauer AT, Deyneka L, Vaughan-Batten H, Waller A. Using near real-time morbidity data to identify heat-related illness prevention strategies in North Carolina. J Community Health 2012;37:495–500.
• Petitti DB, Harlan SL, Chowell-Puente G, Ruddell D. Occupation and environmental heat-associated deaths in Maricopa County, Arizona: a case-control study. PLoS One 2013;8(5).
• CDC. Heat-related deaths among crop workers—United States, 1992–2006. MMWR 2008;57:649–53 .
• Leigh JP, Du J, McCurdy SA. An estimate of the U.S. government's undercount of nonfatal occupational injuries and illnesses in agriculture. Ann Epidemiol 2014;24:254–9.
• CDC. Criteria for a recommended standard: occupational exposure to hot environments (revised criteria 1986). Cincinnati, OH: US Department of Health and Human Services, CDC, National Institute for Occupational Safety and Health; 1986. DHHS (NIOSH) publication no. 86-113. Available at http://www.cdc.gov/niosh/docs/86-113 .
• CDC. OSHA-NIOSH infosheet: protecting workers from heat illness. Cincinnati, OH: US Department of Health and Human Services, CDC, National Institute for Occupational Safety and Health; 2011. DHHS (NIOSH) publication no. 2011-174. Available at http://www.cdc.gov/niosh/docs/2011-174 .

* The Heat Illness Workgroup was created in 2014 after an informal internal review of OSHA's Heat Illness Campaign and consisted of representatives from the various offices (all listed as coauthors in this report) involved in campaign materials development. The group invited a representative from CDC's National Institute for Occupational Safety and Health when they became aware of the CDC/NIOSH document revision, Criteria for a Recommended Standard: Occupational Exposure to Heat and Hot Environments that was underway.

† Wet bulb globe temperature is the measure of heat stress in direct sunlight that takes into account temperature, humidity, wind speed, sun angle, and cloud cover. This differs from the heat index, which takes into account temperature and humidity and is calculated for shady areas. Additional information available at http://www.srh.noaa.gov/tsa/?n=wbgt .

What is already known on this topic?

Exposure to heat and hot environments puts workers at risk for heat stress, which can result in heat illness and death. Guidance for prevention exists, but heat illness prevention programs are not formally implemented by most employers.

What is added by this report?

A review of 2012–2013 Occupational Safety and Health Administration federal enforcement cases (i.e., inspections) resulting in citations under paragraph 5(a)(1), the "general duty clause" of the Occupational Safety and Health Act of 1970, indicated a total of 20 cases involving heat illness and death among workers (13 cases of worker deaths and seven cases in which two or more employees experienced symptoms of heat illness). Most of the affected workers were outdoors and performing heavy or moderate work. In addition, most deaths occurred in the first 3 days of working, with four of them occurring on the worker's first day. Many employers had no heat illness prevention program. Among those with such programs, many lacked basic program elements, such as water management, shaded rest areas, work-rest cycles, and acclimatization protocols. Employers' failure to support acclimatization appears to be the most common deficiency and the factor most clearly associated with death.

What are the implications for public health practice?

Heat illness prevention recommendations include the provision of water and rest breaks in a shaded, cool area to employees. Guidance from regulatory and public/occupational health agencies should include acclimatization of workers as an essential element of employer heat illness prevention programs.

Use of trade names and commercial sources is for identification only and does not imply endorsement by the U.S. Department of Health and Human Services. References to non-CDC sites on the Internet are provided as a service to MMWR readers and do not constitute or imply endorsement of these organizations or their programs by CDC or the U.S. Department of Health and Human Services. CDC is not responsible for the content of pages found at these sites. URL addresses listed in MMWR were current as of the date of publication.

All MMWR HTML versions of articles are electronic conversions from typeset documents. This conversion might result in character translation or format errors in the HTML version. Users are referred to the electronic PDF version ( http://www.cdc.gov/mmwr ) and/or the original MMWR paper copy for printable versions of official text, figures, and tables. An original paper copy of this issue can be obtained from the Superintendent of Documents, U.S. Government Printing Office (GPO), Washington, DC 20402-9371; telephone: (202) 512-1800. Contact GPO for current prices. **Questions or messages regarding errors in formatting should be addressed to [email protected] .

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• Published: 25 May 2021

Disproportionate exposure to urban heat island intensity across major US cities

• Angel Hsu   ORCID: orcid.org/0000-0003-4913-9479 1 , 2 , 3 ,
• Glenn Sheriff 4 ,
• Tirthankar Chakraborty   ORCID: orcid.org/0000-0003-1338-3525 3 , 5 &
• Diego Manya 5  

Nature Communications volume  12 , Article number:  2721 ( 2021 ) Cite this article

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A Publisher Correction to this article was published on 28 June 2021

This article has been updated

Urban heat stress poses a major risk to public health. Case studies of individual cities suggest that heat exposure, like other environmental stressors, may be unequally distributed across income groups. There is little evidence, however, as to whether such disparities are pervasive. We combine surface urban heat island (SUHI) data, a proxy for isolating the urban contribution to additional heat exposure in built environments, with census tract-level demographic data to answer these questions for summer days, when heat exposure is likely to be at a maximum. We find that the average person of color lives in a census tract with higher SUHI intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line.

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Introduction.

Built environments are commonly hotter than their neighboring rural counterparts 1 . This phenomenon, commonly referred to as the urban heat island effect, contributes to a range of public health issues. Heat-related mortality in the USA, for example, causes more deaths (around 1500 per year) than other severe weather events 2 , 3 , 4 . Heat exposure is also associated with several non-fatal health outcomes, including heat strokes, dehydration, loss of labor productivity, and decreased learning 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 . Characteristics of the built environment (e.g., green space, urban form, city size, spectral reflectance) not only create temperature differentials between urban and surrounding rural areas 13 , 14 , 15 , 16 but also contribute to intracity temperature variation 17 , 18 , 19 , 20 . This variation has the potential to cause disparities in the distribution of the burden of adverse heat-related outcomes across sociodemographic groups.

Like other environmental stressors, such as air pollution 21 , low-income or otherwise marginalized communities may experience disproportionately higher levels of heat intensity 22 . Small-scale case studies have found disparities in the distribution of urban heat island intensity within single cities 23 or differences in exposure among population groups within a few cities in different countries 24 , 25 , 26 . Although evidence suggests that extreme heat-related morbidity and mortality in cities disproportionately affect marginalized groups 27 , 28 , 29 , 30 , there has been little research showing whether these groups have systematic disproportionately high exposure to the heat island effect.

Instead, research linking intracity differences in heat exposure to sociodemographic factors has typically been done in an ad hoc manner for a small number of individual cities 23 , 29 , 30 , 31 , 32 . Examining the relationship between the distribution of annual urban heat island exposure and income at the neighborhood level, ref. 25 find that the distribution tended to favor those with higher incomes in 18 out of 25 selected global cities. While illustrative, these results are difficult to generalize since the sociodemographic information comes from a variety of sources with distinct definitions and methods, and the sample of global cities was chosen in response to data constraints rather than random sampling. It also does not convey information about potential disparities for other US cities.

In 108 US cities, ref. 26 find that neighborhoods that were redlined in the 1930s have summer surface temperature profiles that are significantly higher than other coded residential areas (“redlining” refers to the historical practice of denying home loans or insurance based on an area’s racial composition). In light of substantial demographic changes and urban growth patterns over the past 90 years, however, the extent to which this finding translates into current racial or income disparities remains unclear.

While these studies are suggestive, it is difficult to extrapolate their results to a widespread or national level for several reasons. Varying methodological approaches to quantifying urban heat island intensity may lead to different conclusions, or analyses may not be representative. One obstacle to a more uniform approach has been the lack of consistent multicity delineations of urban and rural areas that are also comparable with the administrative areas of aggregation for which socioeconomic data are collected. Case studies may also reflect selection bias. Prior beliefs regarding inequitable distributions of heat exposure may have motivated such scientific inquiry for particular locations, such that the chosen cities may not be representative of the nation as a whole.

Combining high-resolution satellite-based temperature data with sociodemographic data from the US Census, we find that the average person of color lives in a census tract with higher summer daytime surface urban heat island (SUHI) intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line. In nearly half the urbanized areas, the average person of color faces a higher summer daytime SUHI intensity than the average person living below poverty, despite the fact that, on average, only 10% of people of color live below the poverty line. This last finding suggests that widespread inequalities in heat exposure by race and ethnicity may not be well explained by differences in income alone. While we do not observe major differences in SUHI intensity for very young or elderly populations in most major cities, when compared to the total population, we find that the same racial and ethnic disparities in SUHI for specific populations of color compared to non-Hispanic whites are also consistent for these age demographics.

Conceptually, an environmental risk analysis typically includes three components: hazard—measures of the spatial distribution of a potential harm; exposure—the intersection of the spatial distribution of human populations with the hazard; and vulnerability—the propensity to suffer damage when exposed to the hazard (see, for example, refs. 33 , 34 ). We calculate harm on the basis of the census tract level database of SUHI intensity for the USA we developed in ref. 35 . During summer months, relatively large SUHI intensity is associated with increased local warming and extreme heat events in urban areas 13 , 36 , 37 . For exposure, we use census tract level demographic information from the 2017 5-year American Community Survey (ACS).

A comprehensive vulnerability assessment would require detailed information, not only about sociodemographic variables but also about other elements such as household resources, social capital, community resources, comorbidities, etc. that could be obtained at an individual or community level through localized fieldwork 38 , 39 . Although such an assessment is beyond the scope of this study, we consider one salient aspect, age, to evaluate whether differences in exposure by sensitive age groups affect conclusions drawn regarding exposure for the general population. In both very young and older populations, the body’s ability to thermoregulate is compromised, and many older individuals have comorbidities or predispositions that increase the likelihood of heat-related illness and death 40 , 41 . Between 2004 and 2018, 39% of heat-related deaths in the USA occurred in ages 65 years or older 42 . Our framework is thus consistent with several studies using heat exposure to represent climate-related hazards and age to represent vulnerability to analyze the risk of heat stress in urban areas in Brazil, China, Finland, the Philippines, and the USA 34 , 43 , 44 , 45 , 46 .

These combined data allow us to evaluate the relationship between race, income, age, and mean summer daytime SUHI intensity for all major urbanized areas in the USA (see “Methods” for the US Census definition of an urbanized area). These 175 largest US cities cover ~65% of the total population (see Supplementary Fig.  1 ) and are also where most US heat-related deaths have occurred in the last 15 years 42 . We narrow our analysis to the summer months of June, July, and August when the SUHI intensity is most pronounced during the day and when mean temperatures are generally higher than other periods through the year 47 (see Supplementary Fig.  2 ).

Recognizing that health impacts of summer heat exposure are likely to be nonlinear 48 , 49 , 50 , 51 , i.e., incremental increases in environmental heat load may lead to disproportionately higher risk 47 , we also consider environmental inequality metrics that evaluate the importance of within-group inequalities with respect to SUHI spatial distribution and exposure for different sociodemographic groups. We discuss our findings in three parts: first, comparing mean SUHI intensity across racial and income groups; second, using an inequality index to measure intragroup variation in SUHI intensity; and third, considering vulnerability according to age and race/ethnicity.

Mean SUHI intensity across sociodemographic groups

Table  1 (a) describes differences in exposure to SUHI by population groups defined by race/ethnicity and income (see “Methods” for demographic group definitions). We group urbanized areas by Köppen–Geiger 52 climate zones: arid, snow, warm temperate (henceforth referred to as temperate), and equatorial. For total population, summer day SUHI intensity is lowest (0.40 ± 1.75 °C) in arid zones, potentially due to the presence of more vegetation in urban areas compared to their rural references, which moderates the urban–rural temperature differentials 15 , 35 . Most cities are in snow and temperate zones, with a mean SUHI intensity of about 2.2 °C.

These population averages mask differences across population groups. With respect to race/ethnicity, in each climate zone, Black residents have the highest average SUHI exposure, for an overall average (±standard deviation) of 3.12 ± 2.67 °C, with Hispanics experiencing the second highest level (2.70 ± 2.64 °C). Non-Hispanic whites have the lowest exposure in each climate zone, with an overall average of 1.47 ± 2.60 °C. A similar pattern emerges across income groups: people living below the poverty line have the highest exposure in each zone (national average 2.70 ± 2.64 °C), while people living at above twice the poverty line have the lowest (1.80 ± 2.69 °C).

Figure  1 illustrates these sociodemographic differences in exposure, comparing kernel density plots of the distribution of mean SUHI across the 175 cities for different population groups. The starkest differences appear between race, Fig. 1 a, and income, Fig. 1 b. In only a few cities ( n  = 17) are white populations exposed to a mean SUHI intensity greater than 2 °C, while the corresponding number of cities for people of color is 83. A similar number of cities ( n  = 82) expose below-poverty populations to more than 2 °C SUHI. Figure 1 c shows that distributions for those below poverty and for people of color are practically identical. As shown in Fig. 1 d, e, there are not large differences in the distributions for the very young (less than 5) or the elderly (greater than 65) and the rest of the general population. Slightly more cities expose populations under 5 to higher SUHI intensity, while populations over 65 are exposed to lower mean SUHI intensity. Restricting attention to the most vulnerable age groups in Fig. 1 g does not alter the conclusion drawn from Fig. 1 a; for both age groups people of color appear to have a worse SUHI distribution than non-Hispanic whites.

Each panel compares kernel density estimates for two sociodemographic groups. Diagrams are normalized so that the area under each curve equals 175 cities. Hispanic is defined as all who report “Hispanic, Latino, or Spanish origin” as their ethnicity, regardless of race. People of color includes all Hispanic and all who do not identify as white alone. a Non-Hispanic white vs. all people of color. b 2× above poverty vs. below poverty. c Below poverty vs. all people of color. d Over 5 vs. under 5. e Under 65 vs. over 65. f Over 65: non-Hispanic white vs. all people of color. g Under 5: non-Hispanic white vs. all people of color. a illustrates that people of color have an average SUHI exposure greater than 2 °C in more cities than non-Hispanic whites.

Table  1 (b) tests hypotheses that mean exposure is equal across selected groups. We reject ( p  < 0.01) both the null hypothesis of equal means for people of color and non-Hispanic whites in each climate zone, and the null hypothesis of equal means for people below and above two times the poverty line. Perhaps unsurprisingly, the average exposure of non-Hispanic whites is also significantly lower than the average exposure of people below poverty. Interestingly however, outside of arid climates, the average exposure of people of color is not significantly lower than the average exposure of people below poverty despite the fact that only 10% of people of color live below the poverty line.

The values in Table  1 are weighted by population, thus raising the possibility that a few exceptionally large urbanized areas may be driving the results. By illustrating the spatial distribution of significant city-level racial and income disparities in SUHI exposure, the maps in Fig.  2 visualize the geographic scope of the phenomenon presented in the table. For each comparison, circles and triangles identify which group has the higher average SUHI exposure in each city. Symbols with black outlines indicate cities for which the differences in means are statistically significant ( p  < 0.05). (Supplementary Table  1 displays city-level results used to generate these maps). In Fig. 2 a, map shows that people of color have higher SUHI exposure than non-Hispanic whites in 97% of cities nationally, and that this difference is significant in three quarters of cities. By zone, this proportion ranges from 42% in arid climates to almost 90% in snow. In contrast, non-Hispanic whites have a significantly higher exposure in only a single city, McAllen, TX. In Fig. 2 b, the map shows a similar pattern for income. For over 70% of cities people below poverty have a significantly higher exposure than people above twice the poverty line (and in no city do they have a significantly lower exposure). In only 7% of cities nationwide does the average person of color have a lower exposure than the average person living below the poverty line (Fig. 2 c).

Symbols outlined in black depict statistically significant differences in mean exposures ( p  < 0.05). Tables embedded in the lower left-hand corners indicate proportion of cities in each category (e.g., worse for ▵ or worse for ◦) by climate zone. Supplementary Table 1 provides detailed results for each city. Hispanic is defined as all who report “Hispanic, Latino, or Spanish origin” as their ethnicity, regardless of race. People of color includes all Hispanic and all who do not identify as white alone. a Non-Hispanic white (◦) and people of color ( ▵ ). b Above 2 × poverty (◦) and below poverty ( ▵ ). c Below poverty (◦) and people of color ( ▵ ). d Below 65 (◦) and above 65 ( ▵ ).

Intragroup variation in SUHI intensity

A potential drawback to focusing on average exposures by demographic group is it can mask the existence of potential hotspots, geographic areas in which individuals are exposed to elevated levels of the hazard. Hotspots are particularly problematic when comparing exposures across groups if the additional damage caused by an incremental temperature increase grows as temperatures rise. In such cases, even if two groups were to hypothetically face the same average exposure, a group in which half of individuals were exposed to a temperature of, say, 38 °C and half were exposed to 32 °C, would suffer higher adverse effects than a group in which all individuals were exposed to 35 °C.

The Kolm–Pollak (KP) inequality index (see “Methods”) is a tool for ranking group distributions of exposures when there are potential differences in dispersion of outcomes within each group (e.g., hotspots). Table  2 (a) summarizes the average KP inequality index values for each city by population group and climate zone. A higher value corresponds to a less equal distribution of SUHI exposures within each group, with zero indicating a perfectly equal exposure (i.e., no within-group variation).

In general, cities in arid climates tend to have the lowest intragroup variation, and cities in snow and temperate zones have the highest. Within a given zone, however, index values are remarkably similar across population groups. Table 2 (b) evaluates the hypothesis that index values vary significantly by demographic groups. Differences, measured in °C, are small in magnitude and not generally significant. Taken together, results in Table  2 suggest that the group means presented in Table  1 do not mask significant differences in variation within demographic groups. That is, the presence of relative hotspots is not likely to be higher among people living below the poverty line, for example, than people living at more than twice the poverty line. Consequently, for the remainder of this analysis we focus on average exposure levels for each group.

Vulnerability

Analyzing vulnerability is a relevant factor in considering the implications of the difference in mean exposures presented in Table  1 . Since SUHI intensity is more damaging to people over the age of 65 years, the fact that all people of color might be exposed to higher average SUHI than non-Hispanic whites may not be problematic, for example, if its vulnerable (over 65) subpopulations are not exposed in the same way. Map in Fig.  2 d indicates that people over 65 have lower SUHI exposures than those under 65 in 86% of US cities. While this difference is significant for only 16% of cities, there are no cities in which they have a significantly higher exposure. Table  3 (a) presents mean SUHI exposure levels by race and ethnicity, restricting attention to two particularly vulnerable subpopulations: those over 65 years old and those below the age of 5 years. Comparing the exposure levels of these ages in Table  3 (a) with group-wide exposure in Table  1 (a), we see that for people of color exposure levels are nationally the same or higher for these vulnerable groups: 2.76 ± 2.64 °C for those below 5 and 2.88 ± 2.77 °C for those above 65, compared to 2.77 ± 2.70 °C for all people of color. For non-Hispanic whites, however, these vulnerable populations have slightly lower exposures: 1.45 ± 2.53 °C for those below 5 and 1.44 ± 2.60 °C for those above 65, compared to 1.47 ± 2.60 °C for the entire white population. Table 3 (b) compares mean exposures of these vulnerable ages across racial/ethnic groups. The patterns are almost identical to results in Table  1 (b): people of color in each age group have significantly higher exposure levels than their white peers in each climate zone.

Framework for understanding inequalities in SUHI

This analysis provides a framework for quantifying the intercity and intracity distribution of SUHI intensity by race, income, and age that considers both the intensity of the exposure as well as the inequality of distribution for different population subgroups. We find that the distributions of summer daytime SUHI intensity, taking into account both the mean and dispersion, is worse for both people of color and the poor, compared to white and wealthier populations in nearly all major US cities. As illustrated in Fig.  2 , this pattern holds not only at the national level, but in almost all major urban areas regardless of geographical location or climate zones, with a particularly intense difference in the Northeast and upper Midwest of the continental United States. These findings provide comprehensive evidence supporting the narrative presented by earlier case studies that minority and low-income communities bear the brunt of the urban heat island effect 23 , 25 , 26 , 29 , 30 , 31 , 32 , 35 , air temperature 23 , and heat stress 31 in individual or multicity studies.

Although age presents a vulnerability to SUHI, and elderly individuals aged 65 and older comprise a substantial percentage (39%) of heat-related deaths in the USA 42 , our finding that populations over 65 are on average slightly less exposed (1.84 °C versus 2.06 °C for those under 65) could have several explanations. Because SUHI intensity and greenness (as measured by normalized difference vegetation index) are negatively correlated 35 , cooler areas tend to be greener. There is evidence that populations over the age of 65 tend to live in suburban areas in the USA. Approximately half live in rural areas or in urban areas with less than 1 housing unit per acre, and 28% live in suburban areas 53 , which are typically greener than denser urban areas, except in arid climates 15 , 54 , 55 . Considering the intersection of race and age demographics, however, the same racial and ethnic disparities in SUHI intensity for specific populations of color compared to non-Hispanic whites are also consistent for both very young and elder populations 3 , meaning non-white populations over the age of 65 or less than 5 are still exposed to higher levels of SUHI than their white counterparts. The fact that older people of color have a slightly higher SUHI exposure than all people of color suggests that they may be less able to escape the heat by changing location than their white counterparts.

The Intergovernmental Panel on Climate Change has identified the “increasing frequency and intensity of extreme heat, including the urban heat island effect” as a relevant hazard for certain age groups (i.e., elderly, the very young, people with chronic health problems), which creates a risk of increased morbidity or mortality during extreme heat periods 37 . Relating intercity SUHI disparities to health outcomes is challenging due to both prevalence of confounding factors in the populations groups, as well as the differences between land surface temperature (LST) and more comprehensive metrics of heat stress 56 . There is, however, evidence of disparities in heat-related health outcomes across the USA and for individual cities 42 , 57 . For example, ref. 57 finds positive correlations between heat-related mortality rates and poverty for neighborhoods in New York City. More recently, ref. 42 found higher heat-related mortality rates among non-Hispanic American Indians/Alaska Natives and Blacks than for non-Hispanic whites at the national level.

Locally-tailored SUHI mitigation strategies

In addition to evaluating the general scope of potential heat-related environmental inequality concerns, the metrics developed in our study can identify precisely in which cities specific sociodemographic groups are most adversely exposed to SUHI intensity and to potential heat-related health effects for vulnerable groups. These data can thereby assist policy makers in designing interventions to address this exposure differential, as well as facilitate analysis of different scenarios to select the most appropriate strategy to mitigate exposure in an equitable manner. According to ref. 47 , many cities do not take into consideration the spatial location of the most exposed populations in climate mitigation planning and whether areas that present increased sociodemographic vulnerabilities, such as age or high minority populations, are coincident with areas exposed to higher temperatures.

Consideration of background climate differences, which have been found to strongly modulate the thermodynamics of SUHI intensity 15 , 16 , are critical for adapting city-specific intervention strategies to reduce both total exposure and disparities in its distribution 58 . Because we use a globally consistent dataset derived from satellite remote sensing 35 , our data allow for comparison of SUHI given differences in background climates and sociodemographics. Decision-makers and urban planners can utilize this information as a starting point to identify best practices and strategies for mitigating the overall SUHI as well as inequalities in its distribution, although there are certainly localized, context-specific factors that must be considered when determining SUHI management strategies. Studies have demonstrated the importance of coproduction (i.e., involving citizens in the production of knowledge and planning decisions) in developing tailored urban environmental policies 59 . Manoli et al. 60 , who used similar globally consistent satellite-derived data to evaluate drivers of SUHI in 30,000 cities around the world, acknowledge that these data can provide a first-order analysis to understand base-level SUHI exposures and differences to complement more fine-grained data on local factors that influence the SUHI (see “Study limitations” section for more discussion on data issues).

For example, the presence (or absence) of urban vegetation is often proposed as a strategy to reduce the urban heat island effect 13 , 16 , 20 , 61 , climate change more generally 62 , and for their other cobenefits 63 , 64 , 65 , 66 . Access to green space has been found to be inversely correlated with median income 67 . Actions such as planting trees in low-income and minority neighborhoods, which has been shown to reduce summertime afternoon temperatures by as much 1.5 °C 68 , can increase property values and housing costs. Previous work indicates that these housing price effects may displace minority residents the policies were designed to help 69 , 70 . Evidence suggests that homeowners value cooler temperatures and that local temperature differentials are capitalized into housing prices 71 . It is therefore unsurprising that people living below the poverty line have higher average temperature exposures than those at over two times above the poverty line in 94% of major urbanized areas in our study.

Complexity in disentangling race, income, and SUHI

The effect of historical practices of real estate, urban development, and planning policies that promoted spatial and racial segregation in US cities 26 , 72 , as well as the fact that people of color tend to have lower income than white populations in the USA makes it difficult to disentangle purely economic reasons for the unequal distribution of SUHI intensity exposure to those based upon racial factors. We can, however, shed light on the complex relationships between race, poverty, and urban heat by comparing the SUHI distributions faced by people of color to those faced by people living below the poverty line.

While there is some overlap of individuals belonging to both groups, such individuals are a minority; according to the 2017 5-year ACS, only about 10% (ranging from 0.4 to 18.9%) of people of color live below the poverty line in these major urbanized areas. If income were to determine local summer daytime SUHI intensity exposure, one would expect that the typical person of color would have a lower exposure than the typical person living below poverty. Table  1 shows that this hypothesis is unsupported: across the entire sample the mean SUHI exposure of a person of color (2.77 ± 2.70 °C) is practically identical to that of a person living below poverty (2.77 ± 2.73 °C). The distribution of temperature differentials across cities is also similar for these two groups (Fig.  1 ). Nationally, we observe few cities (about 10%) with statistically significant differences between the mean SUHI intensities for these groups (Fig.  2 c).

Illustrative examples

While the SUHI distributions for below poverty and people of color are nearly identical (Fig.  1 ), patterns of exposure by sociodemographic group are not all the same between cities. Figure  3 provides an illustrative example, contrasting the cases of Baltimore, MD, and Greenville, SC. In Baltimore, the temperature exposure of the average person of color is about 0.7° cooler than the average person in poverty, whereas the opposite is true for Greenville. Figure  3 a, b shows that in Greenville, the Black population is highly concentrated in the warmest census tracts, while the poor population is more widely dispersed to cooler areas away from the city center. In Baltimore by contrast, Fig.  3 c, d indicates that the poorest census tracts tend to be the warmest, while the Black population is much more evenly spread through the city.

The correlation between SUHI intensity (dark orange and red) and census tracts that are predominantly non-Hispanic Black (in dark purple) and low-income areas (in dark teal) differs across cities. Hispanic is defined as all who report “Hispanic, Latino, or Spanish origin” as their ethnicity, regardless of race. a Greenville, SC: SUHI and race. b Greenville, SC: SUHI and income. c Baltimore, MD: SUHI and race. d Baltimore, MD: SUHI and income.

As these illustrative examples of Greenville, SC, and Baltimore, MD, show, while many factors might explain our observed difference in below poverty and minority populations’ SUHI exposure in these two cities, prior research on residential housing markets in the USA has shown that racial and ethnic segregation, among factors other than consumer preference alone, determine where certain groups live 73 , 74 .

Future challenges

The patterns of systematically higher SUHI exposure for low-income populations and communities of color in nearly all major US cities may lead to further inequality if these disparities persist or worsen. Currently disadvantaged groups suffer more from greater heat exposure that can further exacerbate existing inequities in health outcomes and associated economic burdens, leaving them with fewer resources to adapt to increasing temperature 75 . Increasing trends of urbanization, demographic shifts with aging populations, and the projected rise in extreme heat-related events due to climate change 37 , may compound certain groups’ vulnerability to extreme heat in the future 29 , 38 . From an environmental equity and justice perspective, understanding where these disparities in heat exposure exist today can inform future efforts to design policy interventions to ameliorate them.

Study limitations

While the SUHI database used in this study has been validated against other published estimates 35 , we recognize limitations of its use as a metric to identify which groups may be more vulnerable to heat stress within cities. Our environmental equity analysis assumes that SUHI intensity is harmful. While this assumption is likely to be justified in the summer periods evaluated in this study, the effect may be beneficial in cities exposed to extreme winter cold 76 . Although in theory the association between SUHI intensity and income and race could imply less extreme cold-related stress in poorer and predominantly non-white neighborhoods, other research suggests that these winter benefits may not materialize 35 . Nonetheless, intracity variation should be taken into account while planning strategies both to reduce mean SUHI and to address environmental disparities in its exposure within cities.

Heat stress also depends on factors other than LST and air temperature, including humidity, wind speed, and radiation 77 . SUHI intensity, however, is still a useful proxy for the urban contribution to local heat stress 35 . Our analysis relies on satellite-based estimates, which could overestimate UHI magnitude compared to in situ weather stations, particularly during daytime 78 , when shade from tree canopies or buildings reduce air temperature in a way that is not captured from a satellite’s vantage point. Our estimates, therefore, likely slightly overestimate the absolute measures of UHI (in °C), but in lieu of dense, widely accessible ground-based air temperature networks, satellite-derived estimates represent the best available data source.

We assume every individual residing in a census tract has the same temperature exposure. In reality, temperatures and demographic characteristics may vary within a tract, and exposures can depend on individual behavior or conditions (home air conditioning, time spent outdoors, etc.). Our analysis also assumes that people pass the entire day in their census tract, abstracting from the possibility that they spend work or leisure time in other locations with distinct SUHI profiles.

The choice to use census tract as the unit of analysis is a compromise based on the relative precision of demographic and satellite data. Precise demographic data are publicly available at the smaller census block group level, and aggregating to larger tracts implies a loss of information. In other contexts, the environmental justice literature suggests that such aggregation can underestimate racial disparities due to the “ecological fallacy” 79 . In contrast, although satellite data are available at a resolution of 1 km, this pixel-level data have a relatively high degree of uncertainty, particularly for urban areas 80 . Since census tracts, unlike block groups, typically contain more than one pixel, averaging the satellite data to this level of aggregation provides more reliable surface temperature estimates.

We also do not evaluate inequities in SUHI among demographic groups over time. Future research could evaluate whether disparities in SUHI exposure have improved or worsened in time. A recent study examining inequality in fine particulate air pollution (PM 2.5 ) found that between 1981 and 2016, absolute disparities between more and less polluted census tracts in the USA declined but that relative disparities have persisted, meaning the most exposed subpopulations in 1981 remained the most exposed in 2016 81 . Incorporating a time-series panel dataset on SUHI intensity and sociodemographic characteristics would allow for future understanding of the role climate change and increasing temperatures may have on worsening heat exposure disparities over time.

SUHI intensity database

Existing maps of SUHI intensity use physical boundaries (e.g., boundary based on built-up, impervious land cover usually measured through satellite remote sensing) as the units of calculations for delineating both urban areas and their corresponding rural references, making them unsuitable for use with socioeconomic data without significant uncertainties. To deal with this scale mismatch between administrative and physical boundaries, we use summertime (June, July, and August; Supplementary Fig.  1 ) values from our recently created SUHI database for the USA that is consistent with census tract delineations 35 .

This dataset uses global LST products from NASA’s MODIS sensor 82 and the land cover product from the European Space Agency 83 . It calculates SUHI intensity at the census tract level by combining the land cover data with the census tracts that intersect US urbanized areas, as defined by the US Census Bureau 84 .

We use the simplified urban extent method 15 to define the SUHI intensity of an urban census tract t as the difference between the tract’s mean LST and the mean temperature of the rural reference r , the nonurban, nonwater land cover pixels within the tract’s urbanized area

Urbanized area boundaries do not necessarily coincide with those of census tracts. In such cases, we adjust the approach to include only pixels within the urbanized area of a census tract to calculate LST t . For more details, see ref. 35 . The distributional analysis thus implicitly assumes no one resides in the nonurbanized portions of those outlying tracts.

Since previous studies have demonstrated the importance of background climate in modulating the SUHI intensity 15 , 16 , we also examine the relationship between disparities in SUHI exposure and the Köppen–Geiger climate zone 85 . The possible impact of background climate has policy implications, since it constrains what city planners can do to mitigate the city-specific SUHI and its distributional impacts.

Demographic data

We assign the same SUHI intensity to every individual living in a given census tract. Demographic group averages are calculated as weighted means across census tracts, in which the weights correspond to the number of people of a given group residing in a tract. Census tract level demographic data come from the 2017 ACS 5-year Data Profile 86 , 87 . We collect data on race, ethnicity, poverty status, age, and age by race for all 46,346 census tracts in the 175 census-defined urbanized areas that contain more than 250,000 residents (Supplementary Fig.  2 ). Our set of urbanized areas ranges from 43 to 4470 tracts, with a median of 582 (Supplementary Table  2 ). Responses to race include options for single race (e.g., Black only) as well as multiple races. Hispanic is an ethnicity reported in addition to race (e.g., Black only and Hispanic). Regardless of race, it is defined as any who respond “yes” to the Census question asking whether the person is “of Hispanic, Latino, or Spanish origin” 88 . For the total population, we generate categories for two non-Hispanic single race groups (Black, white), Hispanic of any race, and “Other”. Other includes non-Hispanics of other single races, including Black or African American, Asian, American Indian and Alaska Native, Native Hawaiian and other Pacific Islander, and non-Hispanics reporting two or more races. We also create a People of Color category that includes all Hispanic and all who do not identify as white alone. For age categories, we use the same race and ethnicity groupings to develop under 5 and over age 65 categories. Since ACS age data do not differentiate Black by Hispanic ethnicity, however, Black Hispanics appear in both the Black and Hispanic categories in Table  3 only.

The ACS reports poverty status as household income relative to the poverty line. This income is not measured in dollars since the poverty line depends on the number of individuals in the household. We use these data to generate three income categories: at or below the poverty line, from one to two times the poverty line, and at or above two times the poverty line (the highest recorded category). While results for each of these income categories are provided in our tables, for the ease of exposition, we focus our discussion on the tails of the income distribution: the poor (those below poverty) and the relatively rich (above two times).

Inequality metrics

The goal of comparing exposure levels across population groups is to determine whether a distribution of SUHI intensities for a given group is preferable in some sense to that of another. In contrast to approaches identifying correlations between summer temperatures and neighborhood characteristics such as historical redlining 26 or percentage poor or low income, e.g., ref. 23 , we place the unit of analysis on the individual to better understand human welfare implications of SUHI exposure.

There is no clear link between what individuals find desirable and the significance of statistical correlations between neighborhood attributes. It is theoretically possible, for example, for the average individual in a demographic group to be better off with a positive (versus negative) correlation between summer heat and their group’s majority status in a neighborhood if most members of the group happen to live in neighborhoods in which they are a minority.

A simple individual-based metric such as mean exposure is potentially misleading due to nonlinear adverse health impacts of summer heat. Evidence suggests that above a moderate threshold damage is an increasing convex function of temperature, i.e., a 1° temperature increase causes more damage at higher temperatures 48 , 49 , 50 , 51 . In such cases, Jensen’s inequality implies that, all else equal, the average health damage for a population in which everyone faces an identical summer heat exposure will be lower than that of a population with the same mean exposure but an unequal temperature distribution. It follows that for any unequal temperature distribution there exists a more desirable (from a health perspective) distribution characterized by a higher mean and no inequality. That is, a perfectly equal summer temperature distribution is generally preferable to an unequal distribution with the same mean.

Using this principle, we adapt an ethical framework commonly used to study income distributions to compare distributions of environmental harm 89 . Under this framework, a distribution is considered more desirable than another if it would be chosen by an impartial agent who knows only that she will receive an outcome from that distribution but is ignorant regarding what that outcome will be. Reframing the problem of ranking SUHI exposure distributions as one of rational choice made behind a “veil of ignorance” 90 , 91 , provides an intuitive approach founded on explicitly specified individual preferences.

To implement this method, we transform distributions of SUHI intensity across individuals in a demographic group to “lotteries” in which the probability of receiving a given exposure corresponds to the proportion of people in the group receiving that exposure. The more desirable distribution is the lottery that would be chosen ex ante by an impartial representative agent who only knows that her ex post exposure will be randomly drawn from that lottery. This choice in turn depends on assumptions made about the agent’s tastes regarding the harm caused by different levels of exposure.

The equally distributed equivalent (EDE) 92 , 93 is a construct for cardinally ranking all possible lotteries. It represents the value of the outcome (in our case, SUHI intensity) that, if experienced by everyone in the group, would make the impartial agent indifferent between the actual unequal distribution and the hypothetical equal distribution.

In summer, the EDE is generally higher than the mean of the actual distribution, i.e., the agent would be willing to bear a higher average intensity if she knew that she were guaranteed not to randomly draw a value higher than the mean 89 . The gap between the EDE and the mean is an index of inequality within a given group, indicating the maximum additional SUHI intensity per person that would make the representative agent indifferent between the actual distribution and the hypothetical equal distribution.

As described in ref. 89 and Supplementary Note  1 , the KP inequality index has several desirable features relevant to characterizing distributions of environmental harm. For an N -dimensional vector of SUHI intensities x , with each element corresponding to the exposure of individual n in a given urbanized area, the KP inequality index can be expressed

Here, \(\bar{x}\) is the mean outcome and κ is a parameter indicating the degree to which inequality in the distribution is undesirable due to increasing marginal damage. The KP EDE is simply \(I({\bf{x}})+\bar{x}\) . As is standard in the literature, we present results for a range of possible values for κ (see Supplementary Tables  3 – 5 ).

All statistical analyses were conducted in Stata (Version 15) and R(Version 3.6.3). Figures were made using ggplot2 94 and tmap 95 , 96 packages in R. The SUHI dataset was created using the Google Earth Engine platform 97 .

Reporting summary

Further information on research design is available in the  Nature Research Reporting Summary linked to this article.

Data availability

SUHI intensity data are available for exploration on an interactive Google Earth Engine platform tool, available at https://datadrivenlab.users.earthengine.app/view/usuhiapp and also for download at https://data.mendeley.com/datasets/x9mv4krnm2/2 . Sociodemographic data were collected from the US Census Bureau 2017 5-year ACS via the API at https://api.census.gov/data/2017/acs/acs5/variables.html .

Code availability

Code to reproduce the figures is available upon reasonable request.

Change history

28 june 2021.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23972-6

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Acknowledgements

The authors would like to thank Nicholas Chin of Yale-NUS College for assistance in extracting US census data, and Barkley Dai of Yale College for compiling an early version of the SUHI United States SUHI Explorer tool in Google Earth Engine. This work was supported by a National University of Singapore Early Career Award to A.H. (Grant Number: NUS_ECRA_FY18_P15) and Samuel Centre for Social Connectedness (Grant number: AWDR14157).

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Hsu, A., Sheriff, G., Chakraborty, T. et al. Disproportionate exposure to urban heat island intensity across major US cities. Nat Commun 12 , 2721 (2021). https://doi.org/10.1038/s41467-021-22799-5

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Assessing Heat Stress and Health among Construction Workers in a Changing Climate: A Review

Payel acharya.

1 Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; moc.liamg@60ayrahcap (P.A.); moc.liamg@sseggobcb (B.B.)

Bethany Boggess

2 Workers Defense Project, Austin, TX 78753, USA

3 Southwest Center for Occupational and Environmental Health, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA

Construction workers are at an elevated risk of heat stress, due to the strenuous nature of the work, high temperature work condition, and a changing climate. An increasing number of workers are at risk, as the industry’s growth has been fueled by high demand and vast numbers of immigrant workers entering into the U.S., the Middle East and Asia to meet the demand. The risk of heat-related illnesses is increased by the fact that little to no regulations are present and/or enforced to protect these workers. This review recognizes the issues by summarizing epidemiological studies both in the U.S. and internationally. These studies have assessed the severity with which construction workers are affected by heat stress, risk factors and co-morbidities associated with heat-related illnesses in the construction industry, vulnerable populations, and efforts in implementing preventive measures.

1. Introduction

Heat stress poses a substantial risk to construction workers worldwide in a changing climate. Construction workers are vulnerable to heat stress because the majority (e.g., 73% in the U.S.) [ 1 ] engage in heavy work outdoors. Construction workers in the southern United States, the Middle East, Asia, Latin America, and Africa are regularly exposed to extremely high temperatures with long working hours, yet may have limited or no access to shade or water [ 2 ]. Previous studies have shown that construction workers in the U.S. are 13 times more likely to die from a heat-related illness (HRI) compared to workers in other industries, and within the industry, roofers and road construction workers face a particularly high risk of HRIs [ 3 , 4 ].

Projected increases in extreme heat due to changing climate, along with other factors, are expected to increase the vulnerability of construction workers to heat stress [ 2 ]. The global construction industry generates 12% of the world’s gross domestic product and is expected to grow rapidly as populations in China, southern Asia, and the U.S. continue to expand [ 5 ]. As construction workers comprise an increasingly large and critical part of the global economy, special attention needs to be paid to the risks faced by the global construction workforce from occupational heat stress. In addition, greenhouse gas emissions are increasing mainly driven by human activities, and the scientific community has a consensus that climate change is taking place with a general trend of rising temperatures [ 6 ]. As a result, the number of extreme hot days are projected to last longer with more frequency and intensity in the future [ 7 ]. Additional factors such as long working hours compounded by heavy workloads, impediments in regulating small construction businesses, and vulnerabilities due to an immigrant worker status that limits access to healthcare resources further worsen construction workers’ vulnerability to heat stress.

In this paper, we will first review the existing epidemiological research about occupational heat stress in the construction industry, both in the U.S. and internationally. Then we investigate the risk factors for heat-related illnesses in construction, as well as populations most vulnerable to experiencing heat-related illness. Additionally, we review preventive measures and existing worker protection policies enacted by local and national governments.

We conducted a general scoping review [ 8 ] to identify the scientific papers published and other relevant information available, including governmental and non-governmental organization (NGO) reports. The databases that were searched included PubMed, Web of Science, references of relevant peer-reviewed literature, and web-based searches (including Google Scholar and documents published by occupational-health organizations). Key words and phrases that were used to search the databases included “construction workers”, “heat stress”, “heat-related illness”, “construction industry”, “work rest cycles”, “regulations” and derivatives of the words “heat”, “temperature”, “hot”, “morbidity”, “risk factors”, “mortality”, “injury”. Due to the limited number of scientific articles available, the search was broad and was not limited by study type. However, studies published after March 2017 were not included. For sources other than scientific literature, reports and conference papers from governmental, non-governmental and inter-governmental organizations were included. Material written in languages other than English were not included ( N = 2). Search results that addressed or analyzed heat stress exposure, risk of HRIs, or interventions for HRIs among construction workers were selected for this review.

3.1. Types of Metrics for Heat Exposure

Heat stress depends on many variables such as temperature, humidity, wind, clothing, shade, physical activities, and other factors. These factors can vary greatly depending on the environment, the occupation, and the individual worker. Workers felt more uncomfortable in a hot and humid environment than in a hot and dry environment, with heat stress further exacerbated by heavy workload, personal protective equipment (PPE), among other factors [ 9 ]. Therefore, a variety of measures have been used to characterize heat stress, including simple temperature metrics (e.g., daily maximum or minimum temperatures), composite indices accounting for temperature and other weather parameters such as humidity (e.g., heat index), core body temperature, and skin temperature. This is mainly due to the fact that heat stress is the heat load brought about by many factors such as weather conditions, physical activities, metabolic heat and thermal effects of clothing [ 10 , 11 ]. Wet Bulb Globe Temperature (WBGT) is a commonly used measure in occupational settings that incorporates air temperature, humidity, radiant heat and wind speed [ 11 ]. The WBGT also serves as the metric upon which heat stress standard ISO 7243 (International Organization for Standardization) for determining ergonomic effects of thermal environments is based [ 12 ], and it is a widely used heat index that underlies measurement of the Threshold Limit Values (TLVs) by the American Conference of Governmental and Industrial Hygienists (ACGIH) [ 10 ]. Despite limitations of WBGT in measuring the effects of metabolic rate and effect of wind speed [ 12 ], WBGT is still an important index to measure heat effects. Another index of heat stress relevant to construction workers and workers laboring in the outdoors is the Thermal Work Limit (TWL), a commonly used measure in occupational settings that incorporates environmental parameters into single index as the equivalent metabolic rate [ 11 ]. Although core body temperature and skin temperature are better measures than other indicators of environmental heat, they have not been used very often because of safety and logistical issues and because they require individuals to ingest or attach a temperature sensor [ 13 ]. Several studies in environmental epidemiology that have examined the associations between heat and mortality concluded that the ‘best measure to heat stress varied with populations and regions’ [ 9 ]. Other heat indices are the Humidex (used in Canada) and the National Weather Service (NWS) Heat Index in the U.S., both describing how hot the weather feels by combining the effects of heat and humidity [ 11 ].

3.2. Epidemiological Studies

Table 1 summarized 16 epidemiological studies included in this review, including study design, study location/period, study population, heat exposure metrics, outcomes and major conclusions.

Summary of heat-related epidemiological studies among construction workers.

3.2.1. Construction Industry is Severely Affected by Heat Stress

According to the study by Xiang et al. (2014) [ 14 ], workers in the construction industry are one of the most affected by heat stress, second only to agricultural workers. The percentage change in daily injury claims per °C increase in daily maximum temperature (T max ) below the threshold temperature (37.7 °C) resulted in an incidence rate ratio (IRR) of 1.006 (95% confidence interval CI: 1.002–1.011). Washington State Accepted State Fund (SF) Workers’ Compensation data from 1995 to 2005 showed that the construction industry was responsible for 33.1% of all HRI claims, and that the construction industry had the highest HRI claim rate (12.1 per 100,000 Full-time Equivalent, FTE) [ 3 ]. Research conducted in Taiwan between 2004 and 2007 by Lin and Chan (2009) [ 15 ] found that the perceived risk of excessive heat in the workplace was highest among the workers from the construction industry. A small study of 16 rebar workers in Beijing found that labor productivity decreased with increasing temperatures, and that older or less-experienced workers had greater productivity losses [ 16 ].

Among studies investigating heat-related mortality outcomes among workers, it was found that the construction industry had consistently higher fatality rates related to heat stress as compared to other industries. For example, in a case-control study conducted in the state of Arizona in the U.S., the odds of heat-related mortality were highest among construction/extraction workers ( N = 76; OR = 2.32; 95% CI 1.55–3.48, age-adjusted) [ 17 ]. In the U.S., the construction industry accounted for 36.8% of the occupational heat-related mortality nationwide. The U.S. construction workers, over a 10-year period, had 13 times (RR = 13.0; 95% CI 10.1–16.7) higher risk of a heat-related fatality compared to workers in other industries [ 4 ]. Sett and Sahu (2014) [ 18 ] studied the effects of heat exposure on female brick workers in India, where construction is heavily reliant on bricks, and it was found that the weekly productivity among those workers declined under increased exposure to outdoor heat, and their physiological stress parameters such as peak heart rate and cardiac strain, as measured by Net Cardiac Cost and Relative Cardiac Cost, were significantly higher in elevated temperatures.

3.2.2. Pattern of Heat Stress Injuries

The number of daily HRIs increase as the ambient temperature increases beyond a certain range. The morbidity effects of rising temperatures are slow at first, but they rise steadily as the temperature continues to increase [ 19 ]. In the study conducted by Xiang et al. (2014) [ 14 ] in Adelaide, Australia, an inverse U-shaped relationship was found between T max and the number of workers’ injury claims reported between July 2001 and June 2010. Until the threshold temperature of up to 37.7 °C, ambient temperature was positively associated with the risk of work injury for all the outdoor industries, including the construction industry, whereas a negative association was observed between the workers’ injuries and temperature beyond this point. This may be due to workers halting work at higher temperatures and thus leading to small sample size of reported claims. The threshold temperature was determined by choosing a single cut-off point from the range of recorded temperatures using the hockey-stick model. A threshold temperature of 37.7 °C was ascertained and associations between temperature and daily injury claims were quantified above and below the threshold temperature.

3.3. Policies, Regulations, and Recommendations

Few regulations exist to prevent HRIs in the construction industry, even though construction workers are among the most likely to experience them. Heat-related illnesses and fatalities are easily prevented with appropriate rest, shade, and rehydration. The U.S. Occupational Safety and Health Administration (OSHA) (2011) [ 20 ] has published guideline for employers, and it recommend that preventive activities increase as the heat index increases. In brief, according to the range of heat index values, OSHA defined four risk categories: Lower; Moderate; High; and Very High/Extreme. Recommendations include providing rest, shade and water; training; acclimatization; developing a monitor system for HRI signs; limiting physical tasks; rescheduling non-essential work; and closely monitoring workers’ vital signs and strictly enforcing work/rest cycles, and the choice of these recommendations depends on risk categories. It is also important to note that working in direct sunlight or unventilated buildings can increase the ambient temperature to a greater degree. Suggestions have been made by a number of agencies, including the ACGIH and the UK Health and Safety Executive (HSE), regarding upper limit of heart rate. The ACGIH recommends upper limit of 120 beats per minute for one-minute recovery heart rate, whereas the HSE suggests the heart rate threshold at workplace to be calculated from the age of individual workers. Further, ISO 7933 sets limits for body mass loss as a measurement of heat strain as 5% for 95% of the working population [ 10 , 11 ].

3.3.1. Public Education Campaigns and Governmental Guidelines

Few construction workers globally are protected from the risks of occupational HRIs by enforceable policies, but many countries have implemented educational campaigns. Some countries have issued strong recommendations for employers, but these recommendations are generally not enforceable. The European Union, the U.S., India, and many other countries recommend that employers follow such guidelines, but they do not enforce them strictly [ 21 ]. Some municipalities, such as Ahmedabad in Gujarat, India, have acted to prevent HRIs by issuing high temperature warnings and distributing educational pamphlets to the public on heat stress prevention [ 22 , 23 ]. However, the efficacy of such guidelines or public education campaigns to prevent or reduce HRIs among construction workers is unknown.

3.3.2. Limited Work Hours

Qatar, the United Arab Emirates, and other Middle Eastern countries limit work hours in summer by requiring all work to stop between 11:30 a.m. and 3:00 p.m. [ 24 ]. However, this regulation is irregularly enforced and temperatures can still be extremely high during non-restricted hours. Investigations by the Amnesty International [ 25 ] found that migratory construction workers were still laboring during limited work hours in Qatar. Nepalese and Indian embassies have reported dozens of young men who have died from heart attacks triggered by heat stress while working in the Middle East [ 25 ], indicating that the regulatory standard is ineffective. The national guidelines for heat stress management in China delineated in the document entitled “Notice for administering guidelines on climatic heat stress prevention measures” were issued in 2012, and regulate work hours based on environmental threshold of forecasted daily maximum air temperature [ 26 ]. Information about the efficacy of these regulations was not found.

3.3.3. Required Rest Breaks

In 2015, Costa Rica introduced legislation requiring employers of agricultural workers who labor outdoors to provide shade, water, rest breaks, and protective clothing [ 27 ]. The legislation is modeled on the US, OSHA guidelines for protecting workers at various heat index levels, with increased protections as the heat index increases [ 20 ]. It was created in response to a growing epidemic of chronic kidney disease linked to occupational heat stress and chronic dehydration among young men in Costa Rica, Nicaragua and El Salvador [ 28 ]. Although this legislation was not specifically applied to construction workers, globally this is the only comprehensive, enforceable legislation implemented at a national level to protect a subset of outdoor workers from HRIs. While other countries, such as the United Arab Emirates (UAE), have adopted policies to protect outdoor workers from heat stress, these policies may be insufficient or poorly enforced. For example, in 2005 the Ministry of Labor of UAE banned work between 12:30 and 4:30 p.m. in July and August, but the duration was restricted a year later to 12:30 to 3:00 p.m. from lobbying by construction companies [ 29 ].

The state of California in the United States [ 30 ] requires employers to provide rest, shade and potable water to agricultural workers, and when temperatures exceed 95 °F (35 °C) monitoring for signs of HRIs must be conducted by designated co-workers or a supervisor. Agricultural workers must receive at least ten minutes of rest every two hours when temperatures are at or above 95 °F (35 °C); however, no other outdoor workers are included in this provision. In 2010 and 2015, the municipalities of Austin [ 31 ] and Dallas [ 32 ], Texas in the U.S. adopted mandatory rest breaks for construction workers of at least ten minutes for every four hours of work. Heat indices often average over 110 °F in these cities from May to September. Prior to the enactment of these regulations, repeated surveys of Texas construction workers found that nearly 40% of them were unable to take rest or water breaks during those days [ 33 ].

3.4. Risk Factors

3.4.1. physiological effects of heat stress.

HRIs occurs when the body retains more heat than it can release, which can then lead to a range of symptoms including heat stroke and death. The effects of heat stress were classified according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) that is used to assign codes following hospital utilization in the United States [ 34 ]: 992.0—heat stroke and sunstroke; 992.1—heat syncope; 992.2—heat cramps; 992.3—heat exhaustion, anhydrotic; 992.4—heat exhaustion due to salt depletion; 992.5—heat exhaustion, unspecified; 992.6—heat fatigue, transient; 992.7—heat edema; 992.8—other specified heat effects; or 992.9—effects of heat and light, unspecified; and/or an ANSI Z16.2 type code 151 (contact with general heat—atmosphere or environment) [ 3 ]. In ambient heat at or above 34–37 °C (93–99 °F), the only method of heat loss from the body is through evaporation of sweat. Accompanied by high humidity, sweat evaporation is greatly reduced resulting in the rising of the core body temperature to potentially dangerous levels (>39 °C or 102 °F) [ 35 , 36 ]. Kjellstrom (2016) [ 35 ] reports many such direct impacts of heat on workers performing heavy labor, such as in the construction industry, including mortality due to cardiovascular conditions. Additionally, in labor-intensive and outdoor occupations, increased environmental heat has been found to be associated with chronic kidney disease, teratogenic effects and poor clinical status, in addition to reduced work performance resulting in loss of income.

Heat stress can also lead to issues with a worker’s hydration status. Hydration status is dependent upon factors such as perspiration rate, the amount of water intake [ 37 ], working conditions, choices such as clothing types [ 38 ], and personal behaviors such as alcohol consumption [ 39 ]. Urine Specific Gravity (USG) is considered as a good indicator of absolute hydration status of the body. The maximum concentrating capacity of the renal system is 1.050, as represented by ascertainment of acutely dehydrated state at Urine Specific Gravity (USG) value of >1.030. On the other hand, a USG value of <1.015 is considered an euhydrated state [ 40 ]. In a comparative study aimed at measuring hydration status among construction workers working under sunlight versus non-exposed conditions in Iran, a significant correlation was found between thermal work limit (TWL) and the USG measures. The exposed group of workers had significantly higher ( p value 0.001) mean USG level (1.026 ± 0.005) than the non-exposed group (mean USG of 1.021 ± 0.005), indicating a hypo-hydrated to clinically dehydrated status in the heat-exposed group [ 41 ]. Contrarily, in a study conducted by Bates (2008) [ 42 ] in the United Arab Emirates, the construction workers studied were not found to have dehydrated status (average water intake was 5.44 liters per 12-h shift). However, in another study conducted by Bates et al. (2010) [ 43 ] among expatriate construction workers working in outdoor and/or in significant heat-generating industrial conditions in the Middle East, the workers were hypo-hydrated as measured by Urine Specific Gravity (USG) values that were elevated during midday and afternoon [ 3 ]. Additional discrepancies in assessing extent of heat stress is addressed by Basagana (2014) [ 19 ] who commented that time-series studies on mortality and morbidity due to heat stress often do not take into consideration other external causes of outcomes.

3.4.2. Seasonal Aspect of HRIs

According to Bonauto (2007) [ 3 ], most of the HRI claims ( N = 456; 95% of total claims) across all the industries in Washington State of the U.S. were made between May through September, which were the area’s hottest months. Similarly, a vast majority of days that recorded multiple HRI claims were between June and August. Among all the HRI claims made in the third quarter of July–September, the construction industry remained highest in terms of number (%) of HRI claims at 121 out of 351 claims (34.5%).

3.4.3. Co-Morbid Risk Factors for Heat-Related Stress

A number of co-morbid risk factors for HRIs have been identified in the literature. According to Bonauto et al. (2007) [ 3 ], use of medications, illicit drugs or alcohol were seen in about 22% of the HRI claims, and other physiological co-morbid conditions to HRIs may arise due to lack/loss of sleep, fatigue and disease. A multiple regression analysis showed that the rate of perceived exertion (RPE) of the construction workers was related to alcohol consumption (standardized coefficient = 0.62, rank = 1), as was duration of work and smoking habit. Also, among construction workers in Hong Kong, smokers represented a higher rate of heat disorder cases (17.8%) than non-smokers (15.2%) [ 44 ]. However, as mentioned by the authors, a lack of set standard of drug use history and medical record collection among workers indicate that these data simply represent a crude estimate, and similar caution should be exercised in interpreting the regression analysis rankings. Body Mass Index (BMI) measurements of obesity (21.4%) and underweight (30.0%) groups had higher percentage of HRI cases [ 44 ]. Institutional factors contributing to HRIs have also been identified at the ecosystem level (weather and climate), society level (e.g., policy and culture), industry level (e.g., workers’ training), organization level (e.g., business model), and individual level (e.g., work skills, risk perception) [ 45 ].

3.4.4. Business Size and Skill Levels

According to Xiang et al. (2014) [ 14 ] who studied workers’ compensation claims in Adelaide, Australia between 2001 and 2010, business size was found to be inversely associated with daily injury claims of the workers. Injury claims increased by 0.7% (IRR = 1.007, 95% CI 1.003–1.011) for small businesses and 0.4% (IRR = 1.004, 95% CI 1.002–1.006) for medium-sized businesses per 1 °C increase in maximum temperature below threshold (37.7 °C). Moreover, in the study conducted by Bates et al. (2010) [ 43 ] among expatriate workers in hot conditions in the Middle East, it was found that among the different working conditions and skill levels studied, the unskilled and semi-skilled workers (island development and city development) had higher USG compared to skilled tradesmen, indicating poorer hydration status [ 43 ].

3.4.5. Vulnerable Age Ranges

Varying results were identified from the literature regarding vulnerable age groups. For example, Xiang et al. (2014) [ 14 ] found that in Adelaide, Australia, young male workers across all industries were at most risk of heat stress, where the incidence rate ratios (IRRs) for male workers and young workers aged ≤24 were IRR = 1.004 (95% CI 1.002–1.006) and IRR = 1.005 (95% CI 1.002–1.008), respectively. In Washington State in the U.S., Bonauto (2007) [ 3 ] found the most vulnerable age group for HRI claims as 25–34, closely followed by 18–24 and 35–44-year-old male workers. It can be concluded from the paper that the workers between ages 18 and 44 comprised the group with the most HRI claims (about 75% of the claims). Interestingly, as the temperature exceeded T max the injury claims decreased, except for the age group 55 years and older. Similar findings were reported by Jia et al. (2016) [ 44 ] where the highest percentage of HRI cases were found among construction workers in the 26 to 35-year-old group (23.7%). The number of cases decreased with age.

Older workers may also be at higher risk of experiencing HRIs and heat-related mortalities. In the state of Arizona, U.S., Petitti et al. (2013) [ 17 ] found that the proportion of heat-related mortality was higher for workers aged 35–49 (112, 25.2% of cases) and 50–65 (114, 25.7% of cases) among construction and agricultural workers. Similar to this finding, occupational heat-related mortality data from the Bureau of Labor Statistics (BLS) in the US between 2000 and 2010 shows that mortality among workers aged 35–54 accounted for 53% (27.3% for ages 35–44; 25.9% for ages 45–54) of all heat-related mortalities. Among the older U.S. workers (ages ≥ 65 years) the average rate of occupational heat-related fatalities per million workers per year was found to be the higher at 0.32, versus that of workers <55 years at 0.22 [ 34 ]. Xiang et al. (2014) [ 14 ] found that in Australia, the injury claims of the ≥55 years age-group continued to increase when the T max exceeded threshold temperature, contrary to the other age groups, where injuries decreased beyond the threshold temperature.

3.4.6. Sex and Racial Differences

Differences in heat stress risk by sex and race among construction workers is not well documented in the literature, but such disparities have been documented among workers in other industries. Among U.S. workers in all industries, Hispanic men were found to have significantly higher age-adjusted odds ratio for heat-related mortality (OR = 2.69; 95% CI 1.79–4.05), along with Native-American men (OR = 2.43; 95% CI 1.79–4.05), compared to non-Hispanic white male workers. A similar trend was observed in female workers when non-Hispanic white women were used as the reference group (Hispanic women; OR = 2.79; 95% CI 1.56–7.0), but an even higher odds ratio for heat-related deaths was observed among Native-American female workers (OR = 3.81; 95% CI 1.51–9.57) [ 17 ]. A number of studies have reported significantly lower number of HRI claims among female workers compared to male workers [ 3 , 14 , 17 ]. For every degree rise in temperature below the threshold temperature of 37.7 °C, daily HRI claims by male workers in Australia increased by 0.4% (IRR 1.004, 95% CI 1.002–1.006). However, no such effect was observed by the study among the female workers whose IRR for both above and below threshold temperature remained insignificant ( p value of 0.550 and 0.206) [ 14 ]. Jia et al. (2016) [ 44 ] reported a similar finding in their study among construction workers in Hong Kong where men had a higher number of heat disorder cases than females (out of 36 HRI cases, 35 were male workers). The authors commented that the result might be due to lighter workload of females than the males in the construction industry [ 44 ]. The Bureau of Labor Statistics (BLS) data for the U.S. heat-related mortality between 2000 and 2010 found that Blacks were at elevated risk of heat-related occupational mortality than the non-Hispanic Whites (RR = 1.5; 95% CI 1.1–2.0). Also, Hispanics were found to be at higher risk (RR = 3.2; 95% CI 2.5–4.0) compared to non-Hispanics. Hispanic workers also had a significantly high average yearly HRI mortality rate of 0.54 per 1 million workers [ 44 ]. Overall, racial minorities were found to have a higher risk of heat-related mortality in the U.S.

4. Prevention

4.1. effects of acclimatization to heat.

Human beings subjected to repeated exposure to hot environments over a period of time undergo physiological responses to heat changes such as an increased and quicker onset of sweating in response to increased heat. This phenomenon is termed as acclimatization, which is characterized by increased blood volume, a decrease in internal body temperature, and a decrease in sodium chloride content of sweat and urine, along with better coping of hot conditions as internal body temperature and heart rate remain within acceptable limits in response to heat stress. Lack of acclimatization has been attributed to heatstroke, heat syncope, heat exhaustion and heat cramps [ 36 ].

Bonauto et al. (2007) [ 3 ] suggests that workers who were not physiologically well adjusted to a high workplace ambient temperature and higher exertion levels had greater heat-related stress. In this study, the author used the ‘length of time employed’ as a measure of acclimatization. For all workers’ claims, it was observed that within a period of one week or less of employment, workers sustained higher HRIs (14%), as compared to other general health-related claims (3.3%). Poor acclimatization was also reflected by the fact that regardless of the length of employment (considered as a measure of acclimatization), a sudden and significant increase in daily maximum temperature (of 10 °F or 5.5 °C) was associated with approximately 42% of the HRI claims. Morioka et al. (2006) [ 37 ] points out that among construction workers, physiological adaptation to heat stress begins within three to four days of working in hot conditions but the hormonal regulation process of acclimatization starts three to four weeks later. This delayed response may mean that the workers are at an increased risk for experiencing HRIs if heat stress prevention measures are not provided or adequately used.

4.2. Optimizing Work–Rest Cycles

Heat strain can be reduced by regular and frequent periods of rest when workers are experiencing heat stress. Yi and Chan (2013) [ 46 ] used Monte Carlo simulation to estimate the probability distribution of physiological conditions and behavioral factors (e.g., heart rate, blood pressure, percentage of body fat, and smoking habits) and environmental conditions (e.g., WBGT, air pollution index (API) of rebar workers) to calculate optimum break schedule. It was found that a 15-min break after working constantly for 120 min (WBGT = 28.9 ± 1.3 °C) would be optimum. A slightly increased rest period and lowered working period were recommended. The Physiological Strain Index (PSI), which is based on heart rate and core temperature and is used to measure heat strain during exercise, was used to measure the rates of recovery after heat stress in 19 rebar workers. It was found that 94% of the recovery occurred within 40 min of rest, 84% in 20 min, and 58% in 5 min, when workers were allowed to work to exhaustion [ 47 ]. Further, based on Time-Weighted Average (TWA), recovery time for heavy workload has been summarized by Rowlinson and Jia (2014) [ 13 ] as follows:

• 28.5 °C-WBGT: 120 min of work followed by a 5-min break
• 28.9 °C-WBGT: 90 min of work followed by a 10-min break
• 29.7 °C-WBGT: 60 min of work followed by a 15-min break
• 31.6 °C-WBGT: Self pace

For ordinary work, self-paced work was suggested from temperatures of 31.7 °C-WBGT or higher, up to the sustainable work limit of 240 min [ 13 ]. These suggestions may be used for designing work–rest cycles. The continuous work time (CWT) reference values were, in turn, calculated from the maximum allowable exposure duration (D lim ) [ 11 ].

4.3. Other Preventive Actions

A number of workplace recommendations have been made by the National Institute for Occupational Safety and Health (NIOSH) for hot environments, including engineering controls and heat alert program [ 36 ]. In a study on Japanese construction workers, Morioka et al. (2006) [ 37 ] and [ 36 ] has found that preventive heat stress measures like the provision of electric fans for ventilation, cool water dispensers, ice machines and structured rest periods were crucial in reducing heat stress. Proper breakfast and electrolyte supplements are recommended as well.

5. Climate Change

According to the Intergovernmental Panel on Climate Change’s Fifth Assessment Report, greenhouse gas emissions have been increasing since the pre-industrial era and are mainly driven by human activities. The scientific community has a consensus that climate change is taking place with a general trend of increasing temperatures [ 48 ]. Available weather observations indicate that the period 1983–2012 ranked the highest in the 30-year period in the Northern Hemisphere, and the linear slope of the global average surface temperature was calculated as 0.85 °C during the period 1880–2012. In fact, growing evidence has suggested that greenhouse gas emissions attributed to anthropogenic activities account for more than half of the increase in the globally averaged surface temperature during the period 1951–2010 [ 48 ].

As a consequence of the changing climate, heat waves are projected to last longer and occur more frequently and intensely [ 7 ]. This has been generally confirmed by many studies using a variety of climate models and scenarios. Moreover, the trend of increasing heat wave days in many regions in recent years is in the agreement of climate change projections [ 49 ]. Globally, the heat wave in Europe in 2003 caused 14,802 deaths in France alone and the heat waves in the future were estimated to occur at least twice as frequently as the 2003 European heat waves [ 50 ]. The chance of a 2010 Russian heat wave that was associated with 55,000 deaths is estimated to become 5 to 10 times more likely by 2050 [ 49 , 51 ]. In the U.S., high summertime temperatures and heat waves are projected to increase in most regions, particularly in the western and central U.S. [ 52 ]. If greenhouse gas emissions continue to grow globally, the hottest 5% of the summertime temperatures during the period 1950–1979 are projected to occur at least 70% of the time in 2035–2064; and the chance of previous once-in-20-year heat wave days are projected to happen up to 10 times in most of the US in the late 21st century [ 52 ].

6. Conclusions

In summary, heat-related health effects among construction workers are a significant but understudied public health topic. This is a critical omission given the trend of the generally increasing global temperatures. Adverse heat-related health effects can be reduced readily through low-cost interventions (e.g., more breaks and the provision of shade and drinking water). Lundgren et al. (2013) [ 53 ] summarized the research needs for all working populations in regard to climate change. The latest assessment of the impacts of climate change on human health [ 7 ] also highlights research needs for general populations. Some of these research needs are particularly appropriate and important for construction workers. They include: (1) the role of genetic and epigenetic factors and social determinants in developing heat-related health effects; (2) exposure–response associations under a large range of temperatures and across locations; (3) the combined effects of heat stress and other stressors (e.g., air pollution): and (4) developing more effective intervention and prevention action plans.

Acknowledgments

The research described in this paper was supported through the start-up funds provided by The University of Texas Health Science Center at Houston (UTHealth) School of Public Health. BB was partly funded by the Southwest Center for Occupational and Environmental Health (SWCOEH), a NIOSH Education and Research Center, and awardee of Grant No. T420H008421 from the National Institute for Occupational Safety and Health (NIOSH)/Centers for Disease Control and Prevention. This paper does not necessarily reflect the views of the UTHealth School of Public Health.

Author Contributions

Kai Zhang conceived and designed the study; Payel Acharya and Bethany Boggess conducted the review; Payel Acharya, Bethany Boggess and Kai Zhang wrote the paper.

Conflicts of Interest

The authors declare no conflict of interest.

Furnace Repair - Heat Stress Case Study

Background: The following case study involves a company with operations in chemical manufacturing. The unit of focus was a furnace that was 22 feet across, 12 burners long and 60 feet high.

Hazard Identification

The hazard identified with this particular chemical manufacturing operation involved heat stress for employees completing heavy work on the furnace. Weather conditions involving 100° F temperatures for completing this type of work were not optimal. Problems with the furnace first began in late April of 2007. Unsupported bricks inside the furnace were in need of maintenance because they were falling apart and collecting on the furnace floor. If no action was taken, complete failure of the furnace would result. Furnace failure would lead to an inevitable shutdown. The operation involved high air temperatures, extreme heat sources, high humidity, direct physical contact with hot objects, and strenuous physical activities, which had a high potential for inducing heat stress in employees engaged in the work. The goal was to complete the repair job flawlessly and on time.

Hazard Intervention

The company identified the heat stress hazard as a physical hazard to employees. The abatement plan was developed by the Joint Safe Operations Committee (JSOC). The abatement approaches involved changes in the PPE, administrative controls, and engineering controls, although the latter was the more effective level of control. The method used to repair the furnace involved fixed equipment engineering, where the repair would take place from the outside. A slot 16 feet wide and 6 inches long was cut on the outside of the furnace to hold the bricks in place. Then a steel shelf (expanded metal plate) was inserted on the top edge of the furnace. Finally, ceramic fiber refractory was injected to fill in the hole. The furnace was under negative pressure. The team also conducted a “what if” analysis to anticipate all the hazards. Once the analysis was complete the team recognized that setting up a hot zone and cool-down tent was important for maintaining a safe environment.

Impacts of the Intervention

There were many positive health, business, and risk management results due to the implementation of the hazard abatement intervention. Employees were protected from exposure to heat stress, as heat stress management was used to control potential health risks. This included development of a work-rest schedule where 25% of time was spent working and 75% of the time employees were resting. There was also a very positive impact on employee morale.

The business process was improved since there was no shutdown of the process, which would have caused an $8-10 million loss. If the unit had been shutdown other units would have to be shutdown as well. A total shutdown for 10 days would cost approximately $15 million. The knock-off effect (2:1) was included in the estimation. If the wall inside the furnace had failed, a shutdown of 10 days would have occurred.

Many positive benefits resulted from the intervention. There was no impact on production rates during the repair process. The amount of time spent on planning was significantly shortened. Risk management was greatly improved because the intervention provided many opportunities for heat stress reduction throughout other areas within the plant.

Financial Metrics

The lost production parameter is the most important parameter. Additional process staff costs were minimal with approximately 12 hours of additional work required. The total cost for mechanical repair would be $150,000 if a shutdown occurred for 7 days.

Lessons Learned

Integrating industrial hygienists into the planning of operations at the right time is of key importance. Early communication of the hazards by industrial hygienists to the management level will allow for the interventions to be more efficient and less risky. Management needs to learn where industrial hygienists fit in the process and where they can be most effective. There is great value in having properly allocated resources. The Safety and Health Group was a core part of the team from the beginning of the intervention to the end. Completing the project the way it was could have been seen as inherently dangerous, but involving the IH and safety points of view allowed for the approach to work. The intervention was broken down into components, which were then analyzed to determine how to manage them.

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The factor affecting heat stress in industrial workers exposed to extreme heat: A case study of methodology

Ahmad Rasdan Ismail 1,2 , Norfadzilah Jusoh 1 , Mohd Amin Mahd Asri 1 , Raemy Md Zein 3 , Ismail Abdul Rahman 3 , Nor Kamilah Makhtar 4 and Darliana Mohamed 1

Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series , Volume 1630 , International Conference on Thermal Sciences and Fluid Flow (ICTSFF) 2020 17-18 April 2020, Penang, Malaysia Citation Ahmad Rasdan Ismail et al 2020 J. Phys.: Conf. Ser. 1630 012001 DOI 10.1088/1742-6596/1630/1/012001

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1 Faculty of Creative Technology & Heritage, Universiti Malaysia Kelantan, 16300 Bachok, Kelantan, Malaysia

2 Centre of Management Environment, Occupational Safety and Health (CMeOSH), Universiti Malaysia Kelantan, 16300 Bachok, Kelantan, Malaysia

3 National Institute of Occupational Safety and Health, Malaysia

4 Department of Educational Planning and Research, Institute of Teacher Education, Campus Kota Bharu, Kota Bharu, Kelantan, Malaysia

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Excessive heat during work creates occupational health risks; it restricts a worker's physical functions and capabilities, work capacity and productivity. Temperatures above 24–26 °C are associated with reduced labour productivity. Exposure to excessive heat levels can lead to heatstroke, sometimes even with a fatal outcome. The aim of this study is to discuss the methodology in experimental of the factor affecting heat stress in industrial workers exposed to extreme heat. The experiment will be conducted in an environmental chamber which simulates the same environment of the manufacturing industry and another arrangement which simulates the environment of a construction industry. The environmental parameters will be recorded such as the temperature, relative humidity and also the physiological parameters such as the volume oxygen uptake level and the heart rate. The heart rate and the volume of oxygen uptake will be recorded for a 15-minute interval for one shift (2 shift-manufacturing and construction). This study is conducted based on two tasks in two different conditions, outdoor and indoor. It simulates the lifting work at both manufacturing and construction industry. For manufacturing industry, the subjects are demanded to lift boxes (10kg). Meanwhile, for the construction industry, the subjects are demanded to lift a sand bag (10kg). From this study, the optimum values of temperature and humidity can be obtained which can lead to the optimum workers' performance. The increase of performance will ensure the production level at the manufacturing industries at its best and will lead to monetary gain. Besides, this can ensure that a construction project can be delivered at the right time while reducing the cost lost and the accidents at the site.

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Case studies on heat stress related perceptions in different industrial sectors in southern India

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• https://doi.org/10.3402/gha.v3i0.5635

Introduction

Materials and methods, conclusions, conflict of interest and funding, acknowledgements.

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Linkages between thermal loads and its physiological consequences have been widely studied in non-tropical developed country settings. In many developing countries like India, despite the widespread recognition of the problem, limited attempts have been made to estimate health impacts related to occupational heat stress and fewer yet to link heat stress with potential productivity losses. This is reflected in the ubiquity of workplaces with limited or no controls to reduce exposures. As a prelude to understanding the feasibility of alternative interventions in different industrial sectors, we present case studies from 10 different industrial units in Tamil Nadu, Chennai, which describe perceptions of occupational heat stress among the workers and supervisors/management.

Units were selected from among those who had previously requested an assessment of workplace heat stress exposure at select locations as part of routine industrial hygiene services provided by the investigators. Since the earlier measurements were performed in response to a management request, all units were revisited to generate a simple job and process profile using checklists in order to understand the overall heat exposure situation in the concerned unit. This was followed by a simple questionnaire administration to a small subsample of employees to evaluate the perceptions of workers and supervisors/management. Finally, we retrieved available quantitative data from previous measurements of heat stress at these units to correlate prevalence of exposures with respective perceptions.

Results indicate that the existing level of controls may not be sufficient for managing work-related heat stress in any of the sectors studied, with wide variations in perceived risks. There was a noticeable disconnect between worker's perceptions and their ability to secure workplace improvements related to heat stress from the management. Wider availability of engineering and administrative controls in the industries may be facilitated by monitoring worker discomfort, disability, and performance in more intensive ways so that the top management is able to justify the associated cost benefits.

Given the potential implications of future climate change related increases in ambient heat stress that are likely to translate into workplace exposures in developing country settings, concerted efforts are needed to integrate exposure assessments with assessments of productivity as well as health impacts. This will likely build the momentum for much needed interventions for large worker populations in the developing world.

• heat stress
• perceptions on heat stress
• productivity loss
• health effects of heat stress

Heat stress has been identified as a widely prevalent health risk in many industrial sectors in India Citation 1 Citation 2 Citation 3 Citation 4 Citation 5 Citation 6 . Combined effects due to excessive heat stress and ergonomic hazards (like heavy lifting, physical exertion, and others) pose great challenges for workers in being able to optimize their productivity, with the potential risk of ensuing heat-related disorders like heat stroke, heat exhaustion, heat cramps, and heat syncope. However, limited attempts have been made to create detailed job exposure profiles for various sectors that may facilitate such hazard recognition. With most workplace settings in developing countries being heavily influenced by outdoor temperatures (in the absence of mechanical cooling), it can be expected that both indoor and outdoor work may contribute to greater than recommended levels of heat exposure. Inadequate recognition of this hazard potential has hampered efforts to assess health impacts related to heat stress and/or implement controls to reduce exposures.

Building on earlier efforts in single industrial units to control heat stress exposures Citation 7 , an assessment of risk perceptions among workers and management across different sectors was conceptualized to provide a deeper understanding of factors that influence the investment in heat stress reduction strategies in individual companies. Such an exercise would also provide insights into how health risks and/or productivity losses in relation to heat stress may be assessed on a routine basis to facilitate risk communication and subsequent management. Finally, heat stress associated with climate change has been most often examined in relation to heat wave effects on the general population and have overlooked working populations. Recognition that climate change may precipitate occupational heat-related health risks with related impacts on productivity especially in developing countries is yet to develop. The need for the design of effective intervention strategies thus becomes even more important in the face of current and future climate change.

With a view to capturing perceptions that may play an important role in determining the availability/accessibility of control (preventive) measures for management of occupational heat stress, we present case studies from 10 different industrial sectors in Tamil Nadu in India that describe a range of perceptions on occupational heat stress. These case studies describe the nature of the job processes, available exposure information, an overview of the available control measures, and perceptions of workers and supervisors/management on heat stress in these sectors.

Perceptions were assessed among workers, managers, and other health and safety professionals in area industries where heat stress measurements had been previously made as part of routine industrial hygiene monitoring by the same investigators. Ten such companies that were involved in automobile assembly, automobile parts manufacturing, heavy truck manufacturing, heavy vehicle (lorry) manufacturing, automobile parts (wheel) manufacturing, leather manufacturing, glass manufacturing, textiles, fertilizer, and electricity (power) generation were selected for the present assessment.

A simple job and process profile was first generated for all facilities to allow an overall understanding of the prevalence of heat exposure situations in companies. A small subsample of workers (∼1–5% of the total worker strength) from select work locations where heat stress monitoring had been performed were first selected for administration of a questionnaire to assess perceptions (some of the units assessed have had a long history of routine heat stress monitoring while others have been assessed only on a single time basis). In addition, select workers from other locations, the safety and/or medical officer (if available), and work supervisors/senior management were included for the assessment. The selection of the participants from other categories was based on the premise that they would be able to respond to management relevant questions and would be aware of company policy on the issue. The response rate ranged from 60% among workers to 95% among other categories. The questionnaire elicited responses pertaining to how workers perceived the heat stress problem in terms of symptoms experienced, productivity/performance changes, the availability of controls, their awareness on heat stress management, and the availability of specific company policies for management of heat stress.

Heat stress exposure was assessed (during previous visits to the same companies) through measurements of the Wet Bulb Globe Temperature (WBGT) index. The WBGT index primarily estimates the environmental contribution to heat stress and is influenced by air temperature, radiant heat, air movement, and humidity. Since the WBGT index primarily reflects environmental contributions, recommended exposure criteria are adjusted for the contributions of work demands and clothing.

Measurements for WBGT were carried out using an area heat stress monitor (Model QuesTemp°34, manufactured by Quest Technologies, USA). The instruments used for the measurements comply with the standards set out by the American Conference of Governmental Industrial Hygienists (ACGIH). Additional information on workload, clothing worn, worker's time-activity pattern, and acclimatization were collected on-site by the trained industrial hygienists and occupational health specialists to make appropriate adjustments to the measured WBGT value.

A total of 242 questionnaires were administered and heat stress measurement data on nearly 80 work locations were retrieved to assess perceptions in relation to prevalent exposure situations and generate initial recommendations for next steps. All questionnaires were administered by research assistants with experience/special training on occupational hazard recognition and control.

Results of quantitative and qualitative assessments conducted at the 10 facilities are furnished in Table 1 .

Table 1. Results on worker's and management's perceptions

The results described in the previous section clearly convey the wide variation in the nature of perception prevalent among workers and management across multiple industrial sectors. Despite the range of differences, listed below are some summary observations that convey the overall results of the assessment.

All companies (with the exception of one) assessed were in possession of some form of environmental or occupational health certification indicating a general awareness among local companies for occupational safety issues (especially since such certifications are not required for local legal compliance). However, the importance accorded for heat stress as an occupational health issue was rather low. Although in many cases measurements were requested to satisfy certification requirements, there was little correlation between the prevalence of the problem and the level of follow-up of recommendations for implementation of appropriate exposure mitigation strategies.

The levels wherever and whenever measured usually exceeded recommended exposure levels, but there was little or no integration with either control or health surveillance efforts. This was despite the availability of a well-equipped health center being available at many facilities.

Most locations where heat stress was measured were indoors with no process generated heat components indicating that heat stress exposure may be a facility wide problem and not limited to the locations monitored (as a result of primary contributions from high ambient temperatures). This has important implications for the scale of expected exposures and related impacts that could be grossly underestimated by including only industrial processes with process generated heat as sources of occupational heat stress. There were also a few cases of personal protective equipments (PPEs) not being used to avoid excess heat indicating potential for risks from heat stress spilling over to additional risks from chemical exposures.

Most workers recognized the problem and wanted some improvements but had limited abilities to influence their management. Some workers in fact felt this would allow them to maintain/enhance their productivity. Management often felt that the levels of controls in place were adequate and that in the absence of extreme health events (such as heat stroke or exhaustion) there was little need for additional measures to reduce exposures. There were few facilities that despite several heat stress related incidents did not engage in additional exposure controls but instead were satisfied with their health center being able to manage the episodes. Possible links to productivity losses were not recognized until prompted. While many workers felt they were not able to slow down, management was either unaware or surprised at the possibilities of such impacts on productivity as opposed to health.

Finally, heat was perceived to a ‘common’ and a ‘general’ problem, an issue of special concern for risk management in tropical settings. High levels of ambient heat are encountered in occupational and non-occupational settings. Since in many work locations this heat is not process generated, management does not feel obligated to control an exposure that the workplace did not generate. The linkages to health and welfare remain distal and it seems to be expected that workers would need to bear the heat and maintain productivity.

A summary that consolidates the main results and the ensuing discussion are provided in Table 2 .

Table 2. Results on the status of heat stress exposure in different industrial sectors

While many previous studies Citation 1 Citation 2 Citation 3 Citation 4 Citation 5 Citation 6 Citation 7 have reported prevailing heat exposure levels in India, to our knowledge a perception survey has not been carried out thus far. The preceding discussion emphasizes the fact that the existing levels of exposure mitigation do not appear to be sufficient for managing work-related heat stress in any of the sectors studied. Limited awareness on the need for preventive measures for heat stress seemed to be prevalent among management despite widespread reported discomfort by workers. There was a noticeable disconnect between worker's perceptions and their ability to secure workplace improvements related to heat stress from the management. Wider availability of engineering and administrative controls in the industries may be facilitated by monitoring worker discomfort, disability, and performance in more intensive ways so that the top management is able to justify the associated cost benefits. In some sectors, management did express interest in collecting data relevant to absenteeism and examining its relationship with heat stress especially during peak summer and this may afford an important opportunity to establish linkages to productivity. Linkages to productivity have been recently demonstrated in other countries Citation 8 Citation 9 Citation 10 . Similar quantification of such productivity losses may allow leveraging of worker interests with that of the management in feasible ways.

It needs to be emphasized that this assessment was carried out in large organized manufacturing units, a work environment setting that eludes millions of workers who are largely employed in the unorganized or small and medium enterprise (SME) units within industrial and non-industrial sectors. The magnitude of the problem as presented here may thus just represent the tip of the iceberg for a much larger and deeper impact. It is in this context that examination of this issue from a climate change point of view becomes important. Even relatively modest increases in ambient temperatures (such as the current lower end projections of 2–3°C) could be expected to tip large worker populations exposed to ‘near limit values’ of heat stress over the threshold into the realm of experiencing heat stress related health risks. The reduction of physical ‘work ability’ due to increasing heat exposure has been well documented in international guidelines such as ISO, 1989. Pilot studies have shown that there is not much work ability left between the hours of 10:00 and 17:00 during typical May days for construction workers in New Delhi, who often have to take 5 h rest breaks to cope with the heat Citation 8 . It could be easily expected that many workers are already losing substantial hours to reduced or no productivity and this would only worsen if ambient temperatures were to rise.

The National Institute of Occupational Health in India has undertaken extensive research on the physiology of heat exposure and preventive approaches of relevance for Indian work settings. Using experimental exposure chambers, their studies quantify the ‘tolerance time’ of work at different intensities until core body temperature reaches 39°C. At a WBGT of 34°C, the tolerance time for heavy work goes below 1 h and it reduces by 4–5 min per 1°C increase of WBGT Citation 2 . Given the propensity of workplaces at this or in excess of this threshold of exposures, any increases that climate change may precipitate could be expected to have serious impacts on workers health and productivity.

Concerted efforts would thus be needed to profile exposures in multiple work settings and link it with potential impacts on productivity and health. It is hoped that the results of this exercise serves as a pilot to scope larger efforts that can build the momentum for much needed interventions for large worker populations in the developing world.

The authors have not received any funding or benefits from industry or elsewhere to conduct this study.

We thank Professor Tord Kjellstrom for his technical guidance in presenting the case studies in the form of this manuscript. His insights in interpreting the results in the context of implications for efforts to control this pervasive and yet largely unrecognized occupational health hazard as well as potential linkages to future climate change mediated impacts on worker productivity were immensely useful. The authors are grateful for his patient involvement. Source(s) of support: Sri Ramachandra University, Chennai.

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Protecting people from a changing climate: The case for resilience

About the authors.

This article is a collaborative effort by Harry Bowcott , Lori Fomenko, Alastair Hamilton , Mekala Krishnan , Mihir Mysore , Alexis Trittipo, and Oliver Walker.

The United Nations’ 2021 Intergovernmental Panel on Climate Change (IPCC) report stated —with higher confidence than ever before—that, without meaningful decarbonization, global temperatures will rise to at least 1.5°C above preindustrial levels within the next two decades. 1 Climate change 2021: The physical science basis , Intergovernmental Panel on Climate Change (IPCC), August 2021, ipcc.ch. This could have potentially dangerous and irreversible effects. A better understanding of how a changing climate could affect people around the world is a necessary first step toward defining solutions for protecting communities and building resilience. 2 For further details on how a changing climate will impact a range of socioeconomic systems, see “ Climate risk and response: Physical hazards and socioeconomic impacts ,” McKinsey Global Institute, January 16, 2020.

As part of our knowledge partnership with Race to Resilience at the UN Climate Change Conference of the Parties (COP26) in Glasgow, we have built a detailed, global assessment of the number of people exposed to four key physical climate hazards, primarily under two different warming scenarios. This paper lays out our methodology and our conclusions from this independent assessment.

A climate risk analysis focused on people: Our methodology in brief

Our research consists of a global analysis of the exposure of people’s lives and livelihoods to multiple hazards related to a changing climate. This analysis identifies people who are potentially vulnerable to four core climate hazards—heat stress, urban water stress, agricultural drought, and riverine and coastal flooding—even if warming is kept within 2.0°C above preindustrial levels.

Our methodology

The study integrates climate and socioeconomic data sources at a granular level to evaluate exposure to climate hazards. We used an ensemble mean of a selection of Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models under Representative Concentration Pathway (RCP) 8.5 —using a Shared Socioeconomic Pathway (SSP2) for urban water stress—with analysis conducted under two potential warming scenarios: global mean temperature increases above preindustrial levels of 1.5°C and 2.0°C. We sometimes use the shorthand of “1.5°C warming scenario” and “2.0°C warming scenario” to describe these scenarios. Our modeling of temperatures in 2030 refers to a multidecadal average between 2021 and 2040. When we say 2050, we refer to a multidecadal average between 2041 and 2060. These are considered relative to a reference period, which is dependent on hazard basis data availability (which we sometimes refer to as “today”).

We built our analysis by applying 2030 and 2050 population-growth projections to our 1.5°C and 2.0°C warming scenarios, respectively. This amount of warming by those time periods is consistent with an RCP 8.5 scenario, relative to the preindustrial average. Climate science makes extensive use of scenarios. We chose a higher emissions scenario of RCP 8.5 to measure the full inherent risk from a changing climate. Research also suggests that cumulative historical emissions, which indicate the actual degree of warming, have been in line with RCP 8.5. 1 For further details, see “ Climate risk and response ,” January 16, 2020, appendix; see also Philip B. Duffy, Spencer Glendon, and Christopher R. Schwalm, “RCP8.5 tracks cumulative CO2 emissions,” Proceedings of the National Academy of Sciences of the United States of America (PNAS) , August 2020, Volume 117, Number 33, pp. 19656–7, pnas.org. In some instances, we have also considered a scenario in which decarbonization actions limit warming and 1.5°C of warming relative to the preindustrial levels is only achieved in 2050, rather than in 2030. For our analysis we used models which differ to some extent on their exact amount of warming and timing, even across the same emissions scenario (RCP 8.5). Naturally, all forward-looking climate models are subject to uncertainty, and taking such an ensemble approach to our model allows us to account for some of that model uncertainty and error. 2 For a more detailed discussion of these uncertainties, see chapter 1 of “ Climate risk and response: Physical hazards and socioeconomic impacts ,” McKinsey Global Institute, January 16, 2020. However, the mean amount of warming typically seen across our ensemble of models is approximately 1.5°C by 2030 and 2.0°C by 2050.

Our analysis consisted of three major steps (see technical appendix for details on our methodology):

First, we divided the surface of the planet into a grid composed of five-kilometer cells, with climate hazards and socioeconomic data mapped for each cell.

Second, in each of those cells, we combined climate and socioeconomic data to estimate the number and vulnerability of people likely to be exposed to climate hazards. These data were categorized on the basis of severity and classified on the basis of exposure to one or more hazards at the grid-cell level.

Third, taking into account people’s vulnerability, we examined the potential impact of our four core hazards on the current and future global population. To do this, we assessed, globally, the number and vulnerability of people affected by different types and severities of hazards. We then aggregated the data from each cell up to the subnational, national, subcontinental, continental, and global levels to allow for comparison across countries.

It’s important to note that we carefully selected these four hazards because they capture the bulk of hazards likely to affect populations on a global scale. We did not account for a range of other hazards such as wildfires, extreme cold, and snow events. Further, our analysis accounts only for first-order effects of climate hazards and does not take into account secondary or indirect effects, which can have meaningful impact. Drought, for example, can lead to higher food prices and even migration—none of which are included in our analysis. Thus, the number of people affected by climate hazards is potentially underestimated in this work.

A focus on four main climate hazards

For our study, we used global data sets covering four key hazards: heat stress, urban water stress, agricultural drought, and riverine and coastal flooding. We relied on data from a selection of CMIP5 climate models, unless otherwise specified. For further details, see the technical appendix.

Heat stress

Heat stress can have meaningful impacts on lives and livelihoods as the climate changes. Heat stress is measured using wet-bulb temperature, which combines heat and humidity. We assess heat stress in the form of acute exposure to humid heat-wave occurrence as well as potential chronic loss in effective working hours, both of which depend on daily wet-bulb temperatures. Above a wet-bulb temperature of 35°C, heat stress can be fatal.

Acute humid heat waves are defined by the average wet-bulb temperature of the hottest six-hour period during a rolling three-day period in which the daily maximum wet-bulb temperature exceeds 34°C for three consecutive days. 3 Analysis of lethal heat waves in our previous McKinsey Global Institute report (see “ Climate risk and response ,” January 16, 2020) was limited to urban populations, and the temperature threshold was set to 34°C wet-bulb temperature under the assumption that the true wet-bulb temperature would actually be 35°C due to an additional 1°C from the urban heat-island effect. Heat-wave occurrence was calculated for each year for both a reference time period 4 The reference period for heat stress refers to the average between 1998 and 2017. and our two future time periods and translated into annual probabilities. Exposure was defined as anyone living in either an urban or rural location with at least a 2 percent annual probability of experiencing such a humid heat wave in any given year. Acute humid heat waves of 34°C or higher can be detrimental to health, even for a healthy and well-hydrated human resting in the shade, because the body begins to struggle with core body-temperature regulation and the likelihood of experiencing a heat stroke increases.

Chronic heat stress was assessed for select livelihoods and defined by processing daily mean air temperature and relative humidity data into a heat index and translating that into the fraction of average annual effective working hours lost due to heat exposure. This calculation was conducted following the methods of John P. Dunne et al., 5 John P. Dunne, Ronald J. Stouffer, and Jasmin G. John, “Reductions in labour capacity from heat stress under climate warming,” Nature Climate Change , 2013, Volume 3, Number 6, pp. 563–6, nature.com. using empirically corrected International Organization for Standardization (ISO) heat-exposure standards from Josh Foster et al. 6 Josh Foster et al., “A new paradigm to quantify the reduction of physical work capacity in the heat,” Medicine and Science in Sports and Exercise , 2019, Volume 51, Number 6S, p. 15, journals.lww.com.

We combined groups of people who were exposed to both chronic and acute heat stress to assess the aggregate number of people exposed. Heat stress can affect livelihoods, particularly for those employed in outdoor occupations, most prominently because an increased need for rest and a reduction in the body’s efficiency reduce effective working hours. Therefore, our analysis of potential exposure to chronic heat stress was limited to people estimated to be working in agriculture, crafts and trades, elementary, factory-based, and manufacturing occupations likely to experience at least a 5 percent loss of effective working hours on average annually. We excluded managers, professional staff, and others who are more likely to work indoors, in offices, or in other cooled environments from this analysis.

Urban water stress

Urban water stress 7 The reference period for water stress refers to the average between 1950 and 2010. often occurs in areas in which demand for water from residents, local industries, municipalities, and others exceeds the available supply. This issue can become progressively worse over time as demand for water continues to increase and supply either remains constant, decreases due to a changing climate, or even increases but not quickly enough to match demand. This can reduce urban residents’ access to drinking water or slow production in urban industry and agriculture.

Our analysis of water stress is limited to urban areas partially because water stress is primarily a demand-driven issue that is more influenced by socioeconomic factors than by changes in climate. We also wanted to avoid methodological overlap with our agricultural drought analysis, which mostly focused on rural areas.

We define urban water stress as the ratio of water demand to supply for urban areas globally. We used World Resources Institute (WRI) data for baseline water stress today and the SSP2 scenario for future water stress outlooks, where 2030 represents the 1.5°C warming scenario and 2040 represents the 2.0°C warming scenario. We only considered severe water stress, defined as withdrawals of 80 percent or more of the total supply, which WRI classifies as “extremely high” water stress.

We make a distinction for “most severe” urban water stress, defined as withdrawals of more than 100 percent of the total supply, to show how many people could be affected by water running out—a situation that will require meaningful interventions to avoid. However, for the sake of the overall exposure analysis, people exposed to the most severe category are considered to be exposed to “severe” water stress unless otherwise noted (exhibit).

Agricultural drought

Agricultural drought 8 The reference period for agricultural drought refers to the average between 1986 and 2005. is a slow-onset hazard defined by a period of months or years that is dry relative to a region’s normal precipitation and soil-moisture conditions, specifically, anomalously dry soils in areas where crops are grown. Drought can inhibit plant growth and reduce plant production, potentially leading to poor yields and crop failures. For more details, see the technical appendix.

Riverine and coastal flooding

We define flooding as the presence of water at least one centimeter deep on normally dry land. We analyze two types of flooding here: riverine flooding from rivers bursting their banks and coastal flooding from storm surges and rising sea levels pushing water onto coastal land. Both coastal and riverine flooding can damage property and infrastructure. In severe cases, they could lead to loss of life. 9 The reference period for riverine flooding refers to the average between 1960 and 1999; the reference period for coastal flooding refers to the average between 1979 and 2014. For more details, see the technical appendix.

Based on a combination of frequency and intensity metrics, we estimated three severity levels of each climate hazard: mild, moderate, and severe (exhibit).

Even when we only look at first-order effects, it is clear that building resilience and protecting people from climate hazards are critical. Our analysis provides data that may be used to identify the areas of highest potential exposure and vulnerability and to help build a case for investing in climate resilience on a global scale.

Our findings suggest the following conclusions:

• Under a scenario with 1.5°C of warming above preindustrial levels by 2030, almost half of the world’s population could be exposed to a climate hazard related to heat stress, drought, flood, or water stress in the next decade, up from 43 percent today 3 Climate science makes extensive use of scenarios; we have chosen Representative Concentration Pathway (RCP) 8.5 and a multimodel ensemble to best model the full inherent risk absent mitigation and adaption. Scenario 1 consists of a mean global temperature rise of 1.5°C above preindustrial levels, which is reached by about 2030 under this RCP; Scenario 2 consists of a mean global temperature rise of 2.0°C above preindustrial levels, reached around 2050 under this RCP. Following standard practice, future estimates for 2030 and 2050 represent average climatic behavior over multidecadal periods: 2030 represents the average of the 2021–2040 period, and 2050 represents the average of the 2041–2060 period. We also compare results with today, also based on multidecadal averages, which differ by hazard. For further details, see technical appendix. —and almost a quarter of the world’s population would be exposed to severe hazards. (For detailed explanations of these hazards and how we define “severe,” see sidebar “A climate risk analysis focused on people: Our methodology in brief.”)
• Indeed, as severe climate events become more common, even in a scenario where the world reaches 1.5°C of warming above preindustrial levels by 2050 rather than 2030, nearly one in four people could be exposed to a severe climate hazard that could affect their lives or livelihoods.
• Climate hazards are unevenly distributed. On average, lower-income countries are more likely to be exposed to certain climate hazards compared with many upper-income countries, primarily due to their geographical location but also to the nature of their economies. (That said, both warming scenarios outlined here are likely to expose a larger share of people in nearly all nations to one of the four modeled climate hazards compared with today.) Those who fall within the most vulnerable categories are also more likely to be exposed to a physical climate hazard.

These human-centric data can help leaders identify the best areas of focus and the scale of response needed to help people—particularly the most vulnerable—build their climate resilience.

A larger proportion of the global population could be exposed to a severe climate hazard compared with today

Under a scenario with 1.5°C of warming above preindustrial levels by 2030, almost half of the world’s population—approximately 5.0 billion people—could be exposed to a climate hazard related to heat stress, drought, flood, or water stress in the next decade, up from 43 percent (3.3 billion people) today.

In much of the discussion below, we focus on severe climate hazards to highlight the most significant effects from a changing climate. We find that regardless of whether warming is limited to 1.5°C or reaches 2.0°C above preindustrial levels by 2050, severe hazard occurrence is likely to increase, and a much larger proportion of the global population could be exposed compared with today (Exhibit 1).

This proportion could more than double, with approximately one in three people likely to be exposed to a severe hazard under a 2.0°C warming scenario by 2050, compared with an estimated one in six exposed today. This amounts to about 2.0 billion additional people likely to be exposed by 2050. Even in a scenario where aggressive decarbonization results in just 1.5°C of warming above preindustrial levels by 2050, the number of people exposed to severe climate hazards could still increase to nearly one in four of the total projected global population, compared with one in six today.

One-sixth of the total projected global population, or about 1.4 billion people, could be exposed to severe heat stress, either acute (humid heat waves) or chronic (lost effective working hours), under a 2.0°C warming scenario above preindustrial levels by 2050, compared with less than 1 percent, or about 0.1 billion people, likely to be exposed today (Exhibit 2).

Our results suggest that both the severity and the geographic reach of severe heat stress may increase to affect more people globally, despite modeled projections of population growth, population shifts from rural to urban areas, and economic migration. Our analysis does not attempt to account for climate-change-related migration or resilience interventions, which could decrease exposure by either forcing people to move away from hot spots or mitigating impacts from severe heat stress.

For those with livelihoods affected by severe chronic heat stress, it could become too hot to work outside during at least 25 percent of effective working hours in any given year. This would likely affect incomes and might even require certain industries to rethink their operations and the nature of workers’ roles. For outdoor workers, extreme heat exposure could also result in chronic exhaustion and other long-term health issues. Heat stress can cause reductions in worker productivity and hours worked due to physiological limits on the human body, as well as an increased need for rest.

We have already seen some of the impacts of acute heat stress in recent years. In the summer of 2010 in Russia, tens of thousands of people died of respiratory illness or heat stress during a large heat-wave event in which temperatures rose to more than 10°C (50°F) higher than average temperatures for those dates. One academic study claims “an approximate 80 percent probability” that the new record high temperature “would not have occurred without climate warming.” 4 Dim Coumou and Stefan Rahmstorf, “Increase of extreme events in a warming world,” Proceedings of the National Academy of Sciences of the United States of America (PNAS) , November 2011, Volume 108, Number 44, pp. 17905–9, pnas.org. To date these impacts have been isolated events, but the potential impact of heat stress on a much broader scale is possible in a 1.5°C or 2.0°C warming scenario in the coming decades.

While we did not assess second-order impacts, they could also be meaningful. Secondary impacts from heat stress may include loss of power, and therefore air conditioning, due to greater stress on electrical grids during acute heat waves, 5 Sofia Aivalioti, Electricity sector adaptation to heat waves , Sabin Center for Climate Change Law, Columbia University, 2015, academiccommons.columbia.edu. increased stress on hospitals due to increased emergency room visits and admission rates primarily during acute heat-stress events, 6 Climate change and extreme heat events , Centers for Disease Control and Prevention, 2015, cdc.gov. and migration driven primarily by impacts from chronic heat stress. 7 Mariam Traore Chazalnoël, Dina Ionesco, and Eva Mach, Extreme heat and migration , International Organization for Migration, United Nations, 2017, environmentalmigration.iom.int.

The rate of growth in global urban water demand is highly likely to outpace that of urban water supply under future warming and socioeconomic pathway scenarios, compared with the overall historical baseline period (1950–2010). In most geographies, this problem is primarily caused not by climate change but by population growth and a corresponding growth in demand for water. However, in some geographies, urban water stress can be exacerbated by the impact of climate change on water supply. In a 2.0°C warming scenario above preindustrial levels by 2050, about 800 million additional people could be living in urban areas under severe water stress compared with today (Exhibit 3). This could result in lack of access to water supplies for drinking, washing and cleaning, and maintaining industrial operations. In some areas, this could make a case for investment in infrastructure such as pipes and desalination plants to make up for the deficit.

Agricultural drought is most likely to directly affect people employed in the agricultural sector: in conditions of anomalously dry soils, plants do not have an adequate water supply, which inhibits plant growth and reduces production. This in turn could have adverse impacts on agricultural livelihoods.

In a scenario with warming 2.0°C above preindustrial levels by 2050, nearly 100 million people—or approximately one in seven of the total global rural population projected to be employed in the agricultural sector by 2050—could be exposed to a severe level of drought, defined as an average of seven to eight drought years per decade. This could severely diminish people’s ability to maintain a livelihood in rainfed agriculture. Additional irrigation would be required, placing further strain on water demand, and yields could still be reduced if exposed to other heat-related hazards.

While our analysis focused on the first-order effects of agricultural drought, the real-world impact could be much larger. Meaningful second-order effects of agricultural drought include reduced access to drinking water and widespread malnutrition. In addition, drought in regions with insufficient aid can cause infectious disease to spread.

Further, although our analysis did not cover food security, many other studies have posited that if people are unable to appropriately adapt, this level of warming would raise the risk of breadbasket failures and could lead to higher food prices. 8 For more on how a changing climate might affect global breadbaskets, see “ Will the world’s breadbaskets become less reliable? ,” McKinsey Global Institute, May 18, 2020.

Primarily as a result of surging demand exacerbated by climate change, 9 Salvatore Pascale et al., “Increasing risk of another Cape Town ‘Day Zero’ drought in the 21st century, Proceedings of the National Academy of Sciences of the United States of America (PNAS) , November 2020, Volume 117, Number 47, pp. 29495–503, pnas.org. Cape Town, South Africa, a semi-arid country, recently experienced a water shortage. From 2015 to 2018, unusually high temperatures contributed to higher rates of evaporation with less refresh due to low rainfall, contributing to decline in water reserves which fell to the point of emergency 10 “Cape Town’s Water is Running Out,” NASA Earth Observatory, January 14, 2018, earthobservatory.nasa.gov. —by January 2018, about 4.3 million residents of South Africa had endured years of constant restrictions on water use in both urban and agricultural settings. Area farmers recorded losses, and many agricultural workers lost their jobs. In the city, businesses were hit with steep water tariffs, jobs were lost, and residents had to ration water.

Under a scenario with warming 2.0°C above preindustrial levels by 2050, about 400 million people could be exposed to severe riverine or coastal flooding, which may breach existing defenses in place today. As the planet warms, patterns of flooding are likely to shift. This could lead to decreased flood depth in some regions and increases likely beyond the capacity of existing defenses in others.

Riverine floods can disrupt travel and supply chains, damage homes and infrastructure, and even lead to loss of life in extreme cases. The most vulnerable are likely to be disproportionately affected—fragile homes in informal coastal settlements are highly vulnerable to flood-related damages.

This analysis does not account for the secondary impacts of floods that may affect people. In rural areas, floods could cause the salinity of soil to increase, which in turn could damage agricultural productivity. Flooding could also make rural roads impassable, limiting residents’ ability to evacuate and their access to emergency response. Major floods sometimes lead to widespread impacts caused by population displacement, healthcare disruptions, food supply disruptions, drinking-water contamination, psychological trauma, and the spread of respiratory and insect-borne disease. 11 Christopher Ohl and Sue Tapsell, “Flooding and human health: The dangers posed are not always obvious,” British Medical Journal (BMJ) , 2000, Volume 321, Number 7270, pp. 1167–8, bmj.com; Shuili Du, C.B. Bhattacharya, and Sankar Sen, “Maximizing business returns to corporate social responsibility (CSR): The role of CSR communication,” International Journal of Management Reviews (IJMR) , 2010, Volume 12, Number 1, pp. 8–19, onlinelibrary.wiley.com. The severity of these impacts varies meaningfully across geographic and socioeconomic factors. 12 Roger Few et al., Floods, health and climate change: A strategic review , Tyndall Centre working paper, number 63, November 2004, unisdr.org.

People in lower-income countries tend to have higher levels of exposure to hazards

Our analysis suggests that exposure to climate hazards is unevenly distributed. Overall, a greater proportion of people living in lower-income countries are likely to be exposed to one or more climate hazards (Exhibit 4). Under a scenario with warming 2.0°C above preindustrial levels by 2050, more than half the total projected global population could be affected by a climate hazard. On the other hand, only 10 percent of the total population in high-income countries is likely to be exposed. That said, there could also be meaningful increases in overall exposure in developed nations. For example, based on 2050 population projections, about 160 million people in the United States—almost forty percent of the US population—could be exposed to at least one of the four climate hazards in a 2.0°C warming scenario by 2050.

In all, our analysis suggests that nearly twice as many highly vulnerable people (those estimated to have lower income and who may also have inadequate shelter, transportation, skills, or funds to protect themselves from climate risks) could be exposed to a climate hazard (Exhibit 5).

One of the implications of these findings is that certain countries are likely to be disproportionately affected. Two-thirds of the people who could be exposed to a climate hazard in a 2.0°C warming scenario by 2050 are concentrated in just ten countries. In two of these, Bangladesh and Pakistan, more than 90 percent of the population could be exposed to at least one climate hazard.

India’s vulnerability to climate hazards

Today, India accounts for more than 17 percent of the world’s population. In a scenario with 2.0°C warming above preindustrial levels by 2050, nearly 70 percent of India’s projected population, or 1.2 billion people, is likely to be exposed to one of the four climate hazards analyzed in this report, compared with the current exposure of nearly half of India’s population (0.7 billion). India could account for about 25 percent of the total global population likely to be exposed to a climate hazard under a 2.0°C warming scenario by 2050, relative to today.

Just as the absolute number of people likely to be exposed to hazards is increasing, so too is the proportion of people likely to be exposed to a severe climate hazard. Today, approximately one in six people in India are likely to be exposed to a severe climate hazard that puts lives and livelihoods at risk. Using 2050 population estimates and a scenario with 2.0°C warming above preindustrial levels by 2050, we estimate that this proportion could increase to nearly one in two people.

Severe heat stress is the primary culprit of severe climate hazard exposure, potentially affecting approximately 650 million residents of India by 2050 in the 2.0°C warming scenario, compared with just under ten million today (exhibit).

A vast number of people in India could also be exposed. Under a scenario with warming 2.0°C above preindustrial levels by 2050, nearly half of India’s projected population—approximately 850 million—could be exposed to a severe climate hazard. This equates to nearly one-quarter of the estimated 3.1 billion people likely to be exposed to a severe climate hazard globally by 2050 under a 2.0°C warming scenario (see sidebar “India’s vulnerability to climate hazards”).

Between now and 2050, population models 13 “Spatial Population Scenarios,” City University of New York and NCAR, updated August 2018, cgd.ucar.edu. project that the world could gain an additional 1.6 billion people, a proportion of whom are likely to be more exposed, more vulnerable, and less resilient to climate impacts.

For example, much of this population growth is likely to come from urban areas. Urbanization is likely to exacerbate the urban heat-island effect—in which human activities cause cities to be warmer than outlying areas—and humid heat waves could take an even greater toll. Urbanization is likely a driver in increased exposure of populations in coastal and riverine cities.

In India and other less developed economies, water stress is less of a climate problem and more of a socioeconomic problem. Our work and previous work on the topic has shown that increased water stress is mostly due to increases in demand—which is primarily driven by population growth in urban areas.

As labor shifts away from agriculture and other outdoor occupations toward indoor work, fewer people may be exposed to the effects of agricultural drought and heat stress. But on balance, many more people will likely be exposed to climate hazards by 2050 than today under either a 1.5°C or a 2.0°C warming scenario above preindustrial levels.

Many regions of the world are already experiencing elevated warming on a regional scale. It is estimated that 20 to 40 percent of today’s global population (depending on the temperature data set used) has experienced mean temperatures of at least 1.5°C higher than the preindustrial average in at least one season. 14 “Chapter 1: Framing and context,” Special report: Global warming of 1.5°C , International Panel on Climate Change (IPCC), 2018, ipcc.ch.

Mitigation will be critical to minimizing risk. However, much of the warming likely to occur in the next decade has already been “locked in” based on past emissions and physical inertia in the climate system. 15 H. Damon Matthews et al., “Focus on cumulative emissions, global carbon budgets, and the implications for climate mitigation targets,” Environmental Research Letters, January 2018, Volume 13, Number 1. Therefore, in addition to accelerating a path to lower emissions, leaders need to build resilience against climate events into their plans.

Around the world, there are examples of innovative ways to build resilience against climate hazards. For example, the regional government of Quintana Roo on Mexico’s Yucatán Peninsula insured its coral reefs in an arrangement with an insurance firm, providing incentives for the insurer to manage any degradation, 16 “World’s first coral reef insurance policy triggered by Hurricane Delta,” Nature Conservancy, December 7, 2020, nature.org. and a redesigned levee system put in place after Hurricane Katrina may have mitigated the worst effects of Hurricane Ida for the citizens of New Orleans. 17 Sarah McQuate, “UW engineer explains how the redesigned levee system in New Orleans helped mitigate the impact of Hurricane Ida,” University of Washington, September 2, 2021, washington.edu.

Nonstate actors may have particular opportunities to help build resilience. For instance, insurance companies may be in a position to encourage institutions to build resilience by offering insurance products for those that make the right investments. This can lower reliance on public money as the first source of funding for recovery from climate events. Civil-engineering companies can participate in innovative public–private partnerships to accelerate infrastructure projects. Companies in the agricultural and food sectors can help farmers around the world mitigate the effects that climate hazards can have on food production—for example, offers of financing can encourage farmers to make investments in resilience. The financial-services sector can get involved by offering better financing rates to borrowers who agree to disclose and reduce emissions and make progress on sustainability goals. And, among other actions, all companies can work to make their own operations and supply chains more resilient.

Accelerating this innovation, and scaling solutions that work quickly, could help us build resilience ahead of the most severe climate hazards.

Harry Bowcott is a senior partner in McKinsey’s London office, Lori Fomenko is a consultant in the Denver office, Alastair Hamilton is a partner in the London office, Mekala Krishnan is a partner at the McKinsey Global Institute (MGI) and a partner in the Boston office, Mihir Mysore is a partner in the Houston office, Alexis Trittipo is an associate partner in the New York office, and Oliver Walker is a director at Vivid Economics, part of McKinsey’s Sustainability Practice.

The authors wish to thank Shruti Badri, Riley Brady, Zach Bruick, Hauke Engel, Meredith Fish, Fabian Franzini, Kelly Kochanski, Romain Paniagua, Hamid Samandari, Humayun Tai, and Kasia Torkarska for their contributions to this article. They also wish to thank external adviser Guiling Wang and the Woodwell Climate Research Center.

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Watch CBS News

Heat stress can turn deadly even sooner than experts thought. Are new warnings needed?

By David Schechter , Chance Horner , Aparna Zalani , Grace Manthey , Tracy J. Wholf

June 11, 2024 / 8:00 AM EDT / CBS News

Gwen Osborne, a 72-year-old retired newspaper reporter in Chicago, liked to spend long hours in her apartment reading her Bible and writing. It's also where she died, overcome by the temperatures of a Midwestern heat wave. 

Osborne was one of three residents who died in the same building in May 2022. The building had a policy of not turning on the air conditioner until June. 

"After three consecutive days of above-average temperatures ... they decided to do health checks. And when they did the health check of her unit, she had passed," said her son, Ken Rye.  

In the era of climate change and warming temperatures , the impact of extreme heat on people over the age of 65, like Osborne, is a serious public health issue because they are the most vulnerable to heat illness and death.  

New research from Penn State University found that extreme heat can begin to stress the human body at much lower levels of heat and humidity than previously thought.  

"Heat stress is what kills," said Dr. Larry Kenney, a Penn State professor of physiology and kinesiology who specializes in how the body regulates temperature, particularly for seniors. 

Heat index vs. wet bulb temperatures: What's the difference? 

Weather forecasters and government agencies like the National Weather Service frequently use a measurement called the  heat index to determine how dangerous temperatures may be. It combines heat and humidity to give a "feels like" temperature.  

And while the heat index does tell us what temperatures feel like, Kenney is concerned that it does not tell us the damage that heat and humidity do to the human body. 

"When our body temperature goes up and we can't get rid of that heat, it puts a strain on the cardiovascular system," he said. 

A better measurement, according to Kenney, is the wet bulb temperature , which is a way to measure heat stress. Like the heat index, wet bulb measurements consider temperature and humidity. But wet bulb  temperatures also include wind speed, sun angle and cloud cover. It's a measurement frequently used by the military and sporting events to assess danger. 

For the last two decades, scientists have worked under the theory that prolonged exposure to a wet bulb temperature of 95 degrees — which is 95 degrees Fahrenheit and 100% humidity — was the upper limit of the human body to compensate for heat. 

But until Kenney looked deeper, that theory was never tested on human subjects. He and his colleagues at Penn State found that those upper limits start far lower, at a wet bulb temperature of around 87 degrees, which is 87 degrees F and 100% humidity. 

Consequently, the risk of heat illness is greatly enhanced for far more people, and sooner than anticipated, under the lower theoretical standard. 

Those results were on test subjects doing "minimal" activities like fidgeting or brushing teeth, according to Kenney's study. If the researchers increased test subjects' activity to "light ambulatory activities" like gardening, washing dishes or gentle walks, the critical limit decreased even further, to a wet bulb temperature around 82 degrees, or 82 degrees F and 100% humidity. 

Very hot and humid places around the world, like South Asia and the Middle East, will be first to hit these kinds of conditions.  

But in the United States, as summer gets hotter and more humid from climate change, cities across the Midwest and East Coat will begin to breach that lower danger zone, at about 5.5 degrees F of warming.  

If the Earth warms more — 7 degrees F — places like Chicago and Houston could see up to 30 hours or more a year of temperatures above critical limits. 

Creating new standards 

As those threats loom, Kenney says we need to move away from the "feels like" temperatures of the heat index. 

"I think we need to look more inward at the human body in terms of how we respond to conditions of high heat and humidity, and then base new standards on those sorts of physiological responses," said Kenney. 

One of the few places that's happening is the Australian Open tennis tournament.  

Starting in 2019, the Australian Open started using a heat stress scale with number from 1 to 5 that is based on wet bulb temperatures but is simpler to understand. 

Each level of the scale has a specific recommendation, like taking extended breaks or suspending play.  

Kenney said a similar scale could be tuned to the vulnerabilities of seniors. 

"That, I think, would be more valuable, more valid, and more reliable in alerting the public," he said. 

And Kenney hopes it could give us a better understanding of how truly damaging heat and humidity can be, instead of learning that the hard way, like Ken Rye had to with his mother. 

"We can do better for our seniors," Rye said. 

• Climate Change

David Schechter is a national environmental correspondent and the host of "On the Dot with David Schechter," a guided journey to explore how we're changing the earth and earth is changing us.

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Heat exposure poses the most risk to older adults with heart disease, a new study suggests.

Even when people are young and healthy, heat exposure that causes a spike in body temperature can put stress on the heart, a new study suggests.

“During heat exposure, the body sends blood to the skin surface to exchange heat with the environment. This causes an increase in the work of the heart, by increasing heart rate and contractility (or the force of contractions) to maintain a stable blood pressure,” says senior study author  Daniel Gagnon, PhD , an associate professor at the Montreal Heart Institute and the University of Montreal.

The fact that the heart works harder is not necessarily a problem in and of itself, Dr. Gagnon says. It’s actually part of the body’s normal response to heat exposure. The problem is that conditions like coronary artery disease reduce the ability of the arteries to widen when the heart needs to receive more blood, which can make it harder for enough oxygen to reach everywhere in the heart where it’s needed for the muscle to work effectively.

This type of oxygen deficit in the heart causes a condition known as myocardial ischemia, which can lead to chest pain, an irregular heart rhythm, or a heart attack , Gagnon says.

Symptoms of Myocardial Ischemia

Even though study participants didn’t exhibit symptoms of myocardial ischemia, seven of the older adults with coronary artery disease showed evidence of this on imaging scans of their hearts taken after heat exposure.

It’s possible that some people may have experienced subtle symptoms like mild chest discomfort or shortness of breath, says Sameed Khatana, MD, MPH , an assistant professor of medicine at the University of Pennsylvania in Philadelphia and a cardiologist at the Philadelphia Veterans Affairs Medical Center.

“If the ischemia gets more severe, it could result in ever more serious consequences, such as a heart attack or abnormal heart rhythms,” says Dr. Khatana, who wasn’t involved in the new study. “It is difficult to say how long this would take, as it depends on the level of heat, clothing, humidity levels, activity levels, and overall fitness.”

However, the lab conditions weren’t the same as what people might encounter outdoors or inside a building without air conditioning on a hot day. Participants were required to stop taking any medications — including drugs prescribed to manage coronary artery disease. They were also exposed to heat by wearing a special suit that prevented them from sweating, the body’s natural cooling system, and they weren’t allowed to drink water during the experiment.

What Happens to the Heart on Hot Days?

“However, when heat is extreme and the humidity is high, the risks of elevated body temperatures and heat stroke increase, and these conditions could cause severe symptoms with exposures as short as 30 minutes,” says Dr. Ferrari. “Be aware that symptoms such as dizziness, lightheadedness, and thirst can precede the more severe symptoms of heat stroke , such as slurred speech, disorientation, confusion, and passing out.”

When heat is extreme, people with heart disease should avoid going outdoors during the hottest parts of the day, if possible, Ferrari advises. He also suggests the following precautions:

• Stay hydrated. Drink lots of water, and consider electrolyte-replenishing drinks if you don’t have heart failure.
• Stick to the shade. Carry an umbrella to shield yourself from the sun if it’s not shady.
• Carry a fan. Hand-held personal fans can help you cool down, especially if it has a mister or you wipe your face, arms, and legs with a moist cloth.

Beyond this, people need to know what symptoms to watch out for, and seek medical help immediately if these symptoms develop.

“The main symptoms to look out for would be chest pain, shortness of breath, a squeezing feeling on the chest, and dizziness or nausea,” Gagnon says. “If someone feels these symptoms, they should call 911.”

Editorial Sources and Fact-Checking

Everyday Health follows strict sourcing guidelines to ensure the accuracy of its content, outlined in our editorial policy . We use only trustworthy sources, including peer-reviewed studies, board-certified medical experts, patients with lived experience, and information from top institutions.

• Barry H et al. The Effect of Heat Exposure on Myocardial Blood Flow and Cardiovascular Function. Annals of Internal Medicine . June 11, 2024.
• Guallar E et al. Feeling the Heat: Cardiovascular Consequences of Heat Exposure Under Controlled Experimental Conditions. Annals of Internal Medicine . June 11, 2024.

Unlocking Wheat's Heat Stress Survival Secrets: A Comprehensive Study of Spike Development’s Metabolic Responses

• Published: 05 March 2024
• Volume 43 , pages 1875–1890, ( 2024 )

Cite this article

• Junjie Han 1 ,
• Wenjing Wang 2 ,
• Yichen Liu 1 ,
• Yiting Shen 1 &
• Weihua Li   ORCID: orcid.org/0009-0009-2384-1199 1  

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Wheat exhibits a heightened sensitivity to heat during spike differentiation, and varietal characteristics and the duration of exposure influence its ability to withstand such stress. Wheat can enhance its resistance to heat stress by regulating the synthesis of endogenous "stress hormones," but understanding the precise molecular mechanisms involved has remained a formidable challenge. This study focused on the Xinjiang spring wheat variety "Xinchun 9" during the period spanning from 2020 to 2021. We subjected the wheat to heat stress treatments at three critical stages of spike differentiation. We utilized RNA-seq and DIA techniques to analyze wheat spikes' transcriptome and proteome comprehensively. In summary, we conducted quantitative analyses on 105,200 transcripts and 19,503 proteins. Remarkably, we observed significant enrichment of differentially expressed genes (DEGs) and proteins (DEPs) associated with secondary metabolite synthesis, plant hormone signaling, and metabolic pathways. Hierarchical clustering analysis further unveiled the distinct stage-specificity of these DEGs/DEPs, emphasizing their rapid response to short-term heat stress. Of particular interest, essential genes/proteins involved in abscisic acid (ABA) synthesis and proline metabolism pathways exhibited significant upregulation or downregulation. It suggests the activation of ABA and proline-mediated heat tolerance pathways. Furthermore, the swift activation of arginase and ornithine aminotransferase (OAT) underscores the pivotal role of proline synthesis through the ornithine pathway. Our study offers a clearer panoramic perspective, illuminating wheat spikes' genetic and proteomic changes under heat stress conditions. It provides novel insights into the genetic regulation of heat stress at various stages of wheat spike differentiation.

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Changes of transcriptome and proteome are associated with the enhanced post-anthesis high temperature tolerance induced by pre-anthesis heat priming in wheat.

Transcriptome profiling reveals the genes and pathways involved in thermo-tolerance in wheat (Triticum aestivum L.) genotype Raj 3765

Data availability.

Data sets generated and/or analyzed during the current study are available from the corresponding authors upon reasonable request.

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Acknowledgements

We thank lab colleagues from the Oasis Eco-agriculture, University of Shihezi, China, for providing seed stocks. This work was partially supported by the National Natural Science Foundation of China 31260357 and the Science and Technology Bureau of Xinjiang Production and Construction Corps 2016AC027 Project Support

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Han, J., Wang, W., Liu, Y. et al. Unlocking Wheat's Heat Stress Survival Secrets: A Comprehensive Study of Spike Development’s Metabolic Responses. J Plant Growth Regul 43 , 1875–1890 (2024). https://doi.org/10.1007/s00344-023-11227-1

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Lab experiment shows exactly how heat waves can put hearts into ‘oxygen debt’

By Elizabeth Cooney June 10, 2024

W hen temperatures soar, so do heart attacks. Now, a lab experiment explains just how temperatures climbing into Fahrenheit’s three-digits can cause ischemia and potential heart attacks, all while international efforts to limit long-term warming seem like they’re running out of time.

The experiment, which gradually exposed participants to higher temperatures, showed that exposure to heat even while resting made participants’ hearts work harder, ramping up blood flow through the hearts of healthy young and old people, but hitting narrowed passages in one-third of older trial participants who had existing coronary artery disease.

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“Older people with heart disease are vulnerable to changes in weather — both extreme heat as well as extreme cold pose a risk for chest pain, heart attacks, and sudden death,” Erica Spatz, a Yale cardiologist and epidemiologist not involved in the study, told STAT via email. “One-third of older people with heart disease developed ischemia to rises in body temperature — this is huge. This study not only provides clues about the mechanisms of this risk but also a warning that with climate change we need to be prepared to better protect our most vulnerable populations.”

For the experiment, three groups of people donned tube-equipped wetsuits originally designed by NASA to cool down astronauts, senior author Daniel Gagnon, an associate professor at the Université de Montréal and the Montreal Heart Institute, told STAT. In this case, progressively warmer water was infused into the suits after a 30-minute rest period. Core body temperature as measured by rectal thermometers was pushed up by three notches: 0.5 degree, 1 degree, then 1.5 degrees Celsius while PET scans revealed how blood was flowing through participants’ hearts.

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What would that feel like in real life? Those temperatures were chosen to approximate what a very hot environment outside the body would be over three hours, climbing from 38 to 47 degrees C (100 to 116 Fahrenheit) with 10% to 60% humidity. Once rare, temperatures that high are becoming more common and more frequent around the world, from Arizona to India but also in Canada and northern Europe .

Taking part in the experiment were 20 healthy people 18 to 40 years old, 21 healthy counterparts age 60 to 80, and 20 participants also age 60 to 80, but with coronary artery disease. During the trial, which took about an hour and 40 minutes, no one could drink water and those who were on heart drugs like beta-blockers skipped their doses.

All of the people had increased blood flow, a sign that their hearts were working harder, in part to cool their bodies. Blood flow rose twice as much in the youngest, healthiest group compared to the oldest, least healthy group. One-third of that oldest, least healthy group — 7 out of 20 — had blood flow blockages, despite feeling no angina symptoms during the experiment. Their imaging looked like what’s seen in a stress test.

“Our hypothesis was that the reason why heat exposure might be bad is because it makes the heart work harder,” Gagnon said. “We didn’t know to what extent does it work harder, and does it work sufficiently hard to think that it could lead to something, especially something like a heart attack.”

The participants’ hearts were in fact working harder, and sooner than the researchers expected. Almost half of the increase in myocardial blood flow occurred when body temperature went up by 0.5 degree C, which was the first bump up. That’s a mild increase, one that might happen normally over the course of a day without high heat, Gagnon said.

As the experiment progressed, the hearts of those with coronary artery disease had impaired ability to open up their vessels to allow more oxygen-carrying blood to sustain the work. Their myocardial blood flow did not increase proportionately to the amount of work that the heart needed to do during the experiment. It’s like their engines were running out of fuel, he said.

Related: What we know about extreme heat’s health impacts after the hottest summer on record

“It’s almost like oxygen debt,” Gagnon said. “It’s spending more energy than it’s bringing in.”

They were never in danger over the experiment’s less than two hours, Gagnon said, but the implications for longer heat exposure are clear.

“If we can imagine during an actual heat wave when it’s hot for a day, two days, three days, and if somebody has myocardial ischemia for several hours or days, then that could potentially lead to something like a heart attack,” he said.

Among the seven people with coronary artery disease whose arteries were closing enough to be called ischemic, there were some differences. Blockages were mild for three participants, moderate for three participants, and severe for one. For three of the seven, the narrowing got progressively worse, climbing in sync with their core temperature. Two participants whose imaging showed heat-induced ischemia also had abnormal electrocardiograms.

The small study defines a mechanism for what large studies have been able to show only as a correlation between high heat and heart problems, said Joel Kaufman, a primary care doctor and professor of environmental and occupational sciences at the University of Washington in Seattle.

“I think the value of this study and the importance of this study is showing physiologically that in individuals with established coronary artery disease, clearly ischemia can be induced by heat,” he told STAT. Also an editor of the NIH-supported journal Environmental Health Perspectives, he was not involved in the new study, published Monday in the Annals of Internal Medicine . “That provides us an explanation for the risk of triggering myocardial infarction during an extreme heat event.”

Gagnon suggested it might be time to widen attention to include not just making sure people don’t get too hot, but also finding ways to reduce the work of the heart when it’s hot outside.

“A lot of times when we talk about heat waves, we say, OK, we need to make sure we don’t get too hot,” he said. “We don’t need to get that hot to potentially have other health problems that might occur because of the heat without necessarily being extremely hot.”

Spatz echoed that concern.

“We need to do a better job about counseling older people with heart disease about heat exposure. Heat poses an increased stress to the heart, and this may lead to ischemia with chest pain or even a heart attack,” she said. “Knowing this information can empower individuals to hydrate, wear cool clothing, seek out air conditioning, and stay indoors when there is extreme heat. Our public health and social systems need to ensure that older people with heart disease have the protection they need.”

Those health problems could affect a large swath of the world’s population, Kaufman pointed out.

“If you’re able to observe ischemia in a small group of people with an experimental intervention, you can assume that there’s a lot of people affected by this when you’re talking about millions of people who might have coronary artery disease who are going to experience heat,” he said. “People with established coronary artery disease are a vulnerable population during a heat wave that should be thinking about cool environments to get to during a heat wave, even in the absence of symptoms.”

STAT’s coverage of chronic health issues is supported by a grant from Bloomberg Philanthropies . Our financial supporters are not involved in any decisions about our journalism.

About the Author Reprints

Elizabeth cooney.

Cardiovascular Disease Reporter

Elizabeth Cooney is a cardiovascular disease reporter at STAT, covering heart, stroke, and metabolic conditions.

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Net Zero by 2050

A Roadmap for the Global Energy Sector

This report is part of Net Zero Emissions

About this report

The number of countries announcing pledges to achieve net zero emissions over the coming decades continues to grow. But the pledges by governments to date – even if fully achieved – fall well short of what is required to bring global energy-related carbon dioxide emissions to net zero by 2050 and give the world an even chance of limiting the global temperature rise to 1.5 °C. This special report is the world’s first comprehensive study of how to transition to a net zero energy system by 2050 while ensuring stable and affordable energy supplies, providing universal energy access, and enabling robust economic growth. It sets out a cost-effective and economically productive pathway, resulting in a clean, dynamic and resilient energy economy dominated by renewables like solar and wind instead of fossil fuels. The report also examines key uncertainties, such as the roles of bioenergy, carbon capture and behavioural changes in reaching net zero.

Summary for policy makers

Reaching net zero emissions globally by 2050 is a critical and formidable goal.

The energy sector is the source of around three-quarters of greenhouse gas emissions today and holds the key to averting the worst effects of climate change, perhaps the greatest challenge humankind has faced. Reducing global carbon dioxide (CO 2 ) emissions to net zero by 2050 is consistent with efforts to limit the long-term increase in average global temperatures to 1.5˚C. This calls for nothing less than a complete transformation of how we produce, transport and consume energy. The growing political consensus on reaching net zero is cause for considerable optimism about the progress the world can make, but the changes required to reach net zero emissions globally by 2050 are poorly understood. A huge amount of work is needed to turn today’s impressive ambitions into reality, especially given the range of different situations among countries and their differing capacities to make the necessary changes. This special IEA report sets out a pathway for achieving this goal, resulting in a clean and resilient energy system that would bring major benefits for human prosperity and well-being.

The global pathway to net zero emissions by 2050 detailed in this report requires all governments to significantly strengthen and then successfully implement their energy and climate policies. Commitments made to date fall far short of what is required by that pathway. The number of countries that have pledged to achieve net zero emissions has grown rapidly over the last year and now covers around 70% of global emissions of CO 2 . This is a huge step forward. However, most pledges are not yet underpinned by near-term policies and measures. Moreover, even if successfully fulfilled, the pledges to date would still leave around 22 billion tonnes of CO 2 emissions worldwide in 2050. The continuation of that trend would be consistent with a temperature rise in 2100 of around 2.1 °C. Global emissions fell in 2020 because of the Covid-19 crisis but are already rebounding strongly as economies recover. Further delay in acting to reverse that trend will put net zero by 2050 out of reach.

In this Summary for Policy Makers, we outline the essential conditions for the global energy sector to reach net zero CO 2 emissions by 2050. The pathway described in depth in this report achieves this objective with no offsets from outside the energy sector, and with low reliance on negative emissions technologies. It is designed to maximise technical feasibility, cost-effectiveness and social acceptance while ensuring continued economic growth and secure energy supplies. We highlight the priority actions that are needed today to ensure the opportunity of net zero by 2050 – narrow but still achievable – is not lost. The report provides a global view, but countries do not start in the same place or finish at the same time: advanced economies have to reach net zero before emerging markets and developing economies, and assist others in getting there. We also recognise that the route mapped out here is a path, not necessarily the path, and so we examine some key uncertainties, notably concerning the roles played by bioenergy, carbon capture and behavioural changes. Getting to net zero will involve countless decisions by people across the world, but our primary aim is to inform the decisions made by policy makers, who have the greatest scope to move the world closer to its climate goals.

Net zero by 2050 hinges on an unprecedented clean technology push to 2030

The path to net zero emissions is narrow: staying on it requires immediate and massive deployment of all available clean and efficient energy technologies. In the net zero emissions pathway presented in this report, the world economy in 2030 is some 40% larger than today but uses 7% less energy. A major worldwide push to increase energy efficiency is an essential part of these efforts, resulting in the annual rate of energy intensity improvements averaging 4% to 2030 – about three-times the average rate achieved over the last two decades. Emissions reductions from the energy sector are not limited to CO 2 : in our pathway, methane emissions from fossil fuel supply fall by 75% over the next ten years as a result of a global, concerted effort to deploy all available abatement measures and technologies.

Ever-cheaper renewable energy technologies give electricity the edge in the race to zero. Our pathway calls for scaling up solar and wind rapidly this decade, reaching annual additions of 630 gigawatts (GW) of solar photovoltaics (PV) and 390 GW of wind by 2030, four-times the record levels set in 2020. For solar PV, this is equivalent to installing the world’s current largest solar park roughly every day. Hydropower and nuclear, the two largest sources of low-carbon electricity today, provide an essential foundation for transitions. As the electricity sector becomes cleaner, electrification emerges as a crucial economy-wide tool for reducing emissions. Electric vehicles (EVs) go from around 5% of global car sales to more than 60% by 2030.  

Priority action: Make the 2020s the decade of massive clean energy expansion

All the technologies needed to achieve the necessary deep cuts in global emissions by 2030 already exist, and the policies that can drive their deployment are already proven.

As the world continues to grapple with the impacts of the Covid-19 pandemic, it is essential that the resulting wave of investment and spending to support economic recovery is aligned with the net zero pathway. Policies should be strengthened to speed the deployment of clean and efficient energy technologies. Mandates and standards are vital to drive consumer spending and industry investment into the most efficient technologies. Targets and competitive auctions can enable wind and solar to accelerate the electricity sector transition. Fossil fuel subsidy phase-outs, carbon pricing and other market reforms can ensure appropriate price signals. Policies should limit or provide disincentives for the use of certain fuels and technologies, such as unabated coal-fired power stations, gas boilers and conventional internal combustion engine vehicles. Governments must lead the planning and incentivising of the massive infrastructure investment, including in smart transmission and distribution grids.

Electric car sales in the net zero pathway, 2020-2030

Capacity additions of solar pv and wind in the net zero pathway, 2020-2030, energy intensity of gdp in the net zero pathway, 2020-2030, net zero by 2050 requires huge leaps in clean energy innovation.

Reaching net zero by 2050 requires further rapid deployment of available technologies as well as widespread use of technologies that are not on the market yet. Major innovation efforts must occur over this decade in order to bring these new technologies to market in time. Most of the global reductions in CO 2 emissions through 2030 in our pathway come from technologies readily available today. But in 2050, almost half the reductions come from technologies that are currently at the demonstration or prototype phase. In heavy industry and long-distance transport, the share of emissions reductions from technologies that are still under development today is even higher.

The biggest innovation opportunities concern advanced batteries, hydrogen electrolysers, and direct air capture and storage. Together, these three technology areas make vital contributions the reductions in CO 2 emissions between 2030 and 2050 in our pathway. Innovation over the next ten years – not only through research and development (R&D) and demonstration but also through deployment – needs to be accompanied by the large-scale construction of the infrastructure the technologies will need. This includes new pipelines to transport captured CO 2 emissions and systems to move hydrogen around and between ports and industrial zones.

Priority action: Prepare for the next phase of the transition by boosting innovation

Clean energy innovation must accelerate rapidly, with governments putting R&D, demonstration and deployment at the core of energy and climate policy.

Government R&D spending needs to be increased and reprioritised. Critical areas such as electrification, hydrogen, bioenergy and carbon capture, utilisation and storage (CCUS) today receive only around one-third of the level of public R&D funding of the more established low-carbon electricity generation and energy efficiency technologies. Support is also needed to accelerate the roll-out of demonstration projects, to leverage private investment in R&D, and to boost overall deployment levels to help reduce costs. Around USD 90 billion of public money needs to be mobilised globally as soon as possible to complete a portfolio of demonstration projects before 2030. Currently, only roughly USD 25 billion is budgeted for that period. Developing and deploying these technologies would create major new industries, as well as commercial and employment opportunities.

Annual CO2 emissions savings in the net zero pathway, 2030 and 2050, relative to 2020

The transition to net zero is for and about people.

A transition of the scale and speed described by the net zero pathway cannot be achieved without sustained support and participation from citizens. The changes will affect multiple aspects of people’s lives – from transport, heating and cooking to urban planning and jobs. We estimate that around 55% of the cumulative emissions reductions in the pathway are linked to consumer choices such as purchasing an EV, retrofitting a house with energy-efficient technologies or installing a heat pump. Behavioural changes, particularly in advanced economies – such as replacing car trips with walking, cycling or public transport, or foregoing a long-haul flight – also provide around 4% of the cumulative emissions reductions.

Providing electricity to around 785 million people that have no access and clean cooking solutions to 2.6 billion people that lack those options is an integral part of our pathway. Emissions reductions have to go hand-in-hand with efforts to ensure energy access for all by 2030. This costs around USD 40 billion a year, equal to around 1% of average annual energy sector investment, while also bringing major co-benefits from reduced indoor air pollution.

Some of the changes brought by the clean energy transformation may be challenging to implement, so decisions must be transparent, just and cost-effective. Governments need to ensure that clean energy transitions are people-centred and inclusive. Household energy expenditure as a share of disposable income – including purchases of efficient appliances and fuel bills – rises modestly in emerging market and developing economies in our net zero pathway as more people gain access to energy and demand for modern energy services increases rapidly. Ensuring the affordability of energy for households demands close attention: policy tools that can direct support to the poorest include tax credits, loans and targeted subsidies.

Priority action: Clean energy jobs will grow strongly but must be spread widely

Energy transitions have to take account of the social and economic impacts on individuals and communities, and treat people as active participants.

The transition to net zero brings substantial new opportunities for employment, with 14 million jobs created by 2030 in our pathway thanks to new activities and investment in clean energy. Spending on more efficient appliances, electric and fuel cell vehicles, and building retrofits and energy-efficient construction would require a further 16 million workers. But these opportunities are often in different locations, skill sets and sectors than the jobs that will be lost as fossil fuels decline. In our pathway, around 5 million jobs are lost. Most of those jobs are located close to fossil fuel resources, and many are well paid, meaning structural changes can cause shocks for communities with impacts that persist over time. This requires careful policy attention to address the employment losses. It will be vital to minimise hardships associated with these disruptions, such as by retraining workers, locating new clean energy facilities in heavily affected areas wherever possible, and providing regional aid.

Global employment in energy supply in the Net Zero Scenario, 2019-2030

An energy sector dominated by renewables.

In the net zero pathway, global energy demand in 2050 is around 8% smaller than today, but it serves an economy more than twice as big and a population with 2 billion more people. More efficient use of energy, resource efficiency and behavioural changes combine to offset increases in demand for energy services as the world economy grows and access to energy is extended to all.

Instead of fossil fuels, the energy sector is based largely on renewable energy. Two-thirds of total energy supply in 2050 is from wind, solar, bioenergy, geothermal and hydro energy. Solar becomes the largest source, accounting for one-fifth of energy supplies. Solar PV capacity increases 20-fold between now and 2050, and wind power 11-fold.

Net zero means a huge decline in the use of fossil fuels. They fall from almost four-fifths of total energy supply today to slightly over one-fifth by 2050. Fossil fuels that remain in 2050 are used in goods where the carbon is embodied in the product such as plastics, in facilities fitted with CCUS, and in sectors where low-emissions technology options are scarce.

Electricity accounts for almost 50% of total energy consumption in 2050. It plays a key role across all sectors – from transport and buildings to industry – and is essential to produce low-emissions fuels such as hydrogen. To achieve this, total electricity generation increases over two-and-a-half-times between today and 2050. At the same time, no additional new final investment decisions should be taken for new unabated coal plants, the least efficient coal plants are phased out by 2030, and the remaining coal plants still in use by 2040 are retrofitted. By 2050, almost 90% of electricity generation comes from renewable sources, with wind and solar PV together accounting for nearly 70%. Most of the remainder comes from nuclear.    

Emissions from industry, transport and buildings take longer to reduce. Cutting industry emissions by 95% by 2050 involves major efforts to build new infrastructure. After rapid innovation progress through R&D, demonstration and initial deployment between now and 2030 to bring new clean technologies to market, the world then has to put them into action. Every month from 2030 onwards, ten heavy industrial plants are equipped with CCUS, three new hydrogen-based industrial plants are built, and 2 GW of electrolyser capacity are added at industrial sites. Policies that end sales of new internal combustion engine cars by 2035 and boost electrification underpin the massive reduction in transport emissions. In 2050, cars on the road worldwide run on electricity or fuel cells. Low-emissions fuels are essential where energy needs cannot easily or economically be met by electricity. For example, aviation relies largely on biofuels and synthetic fuels, and ammonia is vital for shipping. In buildings, bans on new fossil fuel boilers need to start being introduced globally in 2025, driving up sales of electric heat pumps. Most old buildings and all new ones comply with zero-carbon-ready building energy codes. 1

Priority action: Set near-term milestones to get on track for long-term targets

Governments need to provide credible step-by-step plans to reach their net zero goals, building confidence among investors, industry, citizens and other countries.

Governments must put in place long-term policy frameworks to allow all branches of government and stakeholders to plan for change and facilitate an orderly transition. Long-term national low-emissions strategies, called for by the Paris Agreement, can set out a vision for national transitions, as this report has done on a global level. These long-term objectives need to be linked to measurable short-term targets and policies. Our pathway details more than 400 sectoral and technology milestones to guide the global journey to net zero by 2050.  

There is no need for investment in new fossil fuel supply in our net zero pathway

Beyond projects already committed as of 2021, there are no new oil and gas fields approved for development in our pathway, and no new coal mines or mine extensions are required. The unwavering policy focus on climate change in the net zero pathway results in a sharp decline in fossil fuel demand, meaning that the focus for oil and gas producers switches entirely to output – and emissions reductions – from the operation of existing assets. Unabated coal demand declines by 98% to just less than 1% of total energy use in 2050. Gas demand declines by 55% to 1 750 billion cubic metres and oil declines by 75% to 24 million barrels per day (mb/d), from around 90 mb/d in 2020.

Clean electricity generation, network infrastructure and end-use sectors are key areas for increased investment. Enabling infrastructure and technologies are vital for transforming the energy system. Annual investment in transmission and distribution grids expands from USD 260 billion today to USD 820 billion in 2030. The number of public charging points for EVs rises from around 1 million today to 40 million in 2030, requiring annual investment of almost USD 90 billion in 2030. Annual battery production for EVs leaps from 160 gigawatt-hours (GWh) today to 6 600 GWh in 2030 – the equivalent of adding almost 20 gigafactories 2  each year for the next ten years. And the required roll-out of hydrogen and CCUS after 2030 means laying the groundwork now: annual investment in CO 2 pipelines and hydrogen-enabling infrastructure increases from USD 1 billion today to around USD 40 billion in 2030.

Priority action: Drive a historic surge in clean energy investment

Policies need to be designed to send market signals that unlock new business models and mobilise private spending, especially in emerging economies.

Accelerated delivery of international public finance will be critical to energy transitions, especially in developing economies, but ultimately the private sector will need to finance most of the extra investment required. Mobilising the capital for large-scale infrastructure calls for closer co operation between developers, investors, public financial institutions and governments. Reducing risks for investors will be essential to ensure successful and affordable clean energy transitions. Many emerging market and developing economies, which rely mainly on public funding for new energy projects and industrial facilities, will need to reform their policy and regulatory frameworks to attract more private finance. International flows of long-term capital to these economies will be needed to support the development of both existing and emerging clean energy technologies.

Clean energy investment in the net zero pathway, 2016-2050

An unparalleled clean energy investment boom lifts global economic growth.

Total annual energy investment surges to USD 5 trillion by 2030, adding an extra 0.4 percentage point a year to annual global GDP growth, based on our joint analysis with the International Monetary Fund. This unparalleled increase – with investment in clean energy and energy infrastructure more than tripling already by 2030 – brings significant economic benefits as the world emerges from the Covid-19 crisis. The jump in private and government spending creates millions of jobs in clean energy, including energy efficiency, as well as in the engineering, manufacturing and construction industries. All of this puts global GDP 4% higher in 2030 than it would be based on current trends.

Governments have a key role in enabling investment-led growth and ensuring that the benefits are shared by all. There are large differences in macroeconomic impacts between regions. But government investment and public policies are essential to attract large amounts of private capital and to help offset the declines in fossil fuel income that many countries will experience. The major innovation efforts needed to bring new clean energy technologies to market could boost productivity and create entirely new industries, providing opportunities to locate them in areas that see job losses in incumbent industries. Improvements in air quality provide major health benefits, with 2 million fewer premature deaths globally from air pollution in 2030 than today in our net zero pathway. Achieving universal energy access by 2030 would provide a major boost to well-being and productivity in developing economies.

New energy security concerns emerge, and old ones remain

The contraction of oil and natural gas production will have far-reaching implications for all the countries and companies that produce these fuels. No new oil and natural gas fields are needed in our pathway, and oil and natural gas supplies become increasingly concentrated in a small number of low-cost producers. For oil, the OPEC share of a much-reduced global oil supply increases from around 37% in recent years to 52% in 2050, a level higher than at any point in the history of oil markets. Yet annual per capita income from oil and natural gas in producer economies falls by about 75%, from USD 1 800 in recent years to USD 450 by the 2030s, which could have knock-on societal effects. Structural reforms and new sources of revenue are needed, even though these are unlikely to compensate fully for the drop in oil and gas income. While traditional supply activities decline, the expertise of the oil and natural gas industry fits well with technologies such as hydrogen, CCUS and offshore wind that are needed to tackle emissions in sectors where reductions are likely to be most challenging.

The energy transition requires substantial quantities of critical minerals, and their supply emerges as a significant growth area. The total market size of critical minerals like copper, cobalt, manganese and various rare earth metals grows almost sevenfold between 2020 and 2030 in the net zero pathway. Revenues from those minerals are larger than revenues from coal well before 2030. This creates substantial new opportunities for mining companies. It also creates new energy security concerns, including price volatility and additional costs for transitions, if supply cannot keep up with burgeoning demand.

The rapid electrification of all sectors makes electricity even more central to energy security around the world than it is today. Electricity system flexibility – needed to balance wind and solar with evolving demand patterns – quadruples by 2050 even as retirements of fossil fuel capacity reduce conventional sources of flexibility. The transition calls for major increases in all sources of flexibility: batteries, demand response and low-carbon flexible power plants, supported by smarter and more digital electricity networks. The resilience of electricity systems to cyberattacks and other emerging threats needs to be enhanced.

Priority action: Address emerging energy security risks now

Ensuring uninterrupted and reliable supplies of energy and critical energy-related commodities at affordable prices will only rise in importance on the way to net zero.

The focus of energy security will evolve as reliance on renewable electricity grows and the role of oil and gas diminishes. Potential vulnerabilities from the increasing importance of electricity include the variability of supply and cybersecurity risks. Governments need to create markets for investment in batteries, digital solutions and electricity grids that reward flexibility and enable adequate and reliable supplies of electricity. The growing dependence on critical minerals required for key clean energy technologies calls for new international mechanisms to ensure both the timely availability of supplies and sustainable production. At the same time, traditional energy security concerns will not disappear, as oil production will become more concentrated.

Critical minerals demand in the net zero pathway, 2020-2050

Oil supply in the net zero pathway, 2020-2050, international co-operation is pivotal for achieving net zero emissions by 2050.

Making net zero emissions a reality hinges on a singular, unwavering focus from all governments – working together with one another, and with businesses, investors and citizens. All stakeholders need to play their part. The wide-ranging measures adopted by governments at all levels in the net zero pathway help to frame, influence and incentivise the purchase by consumers and investment by businesses. This includes how energy companies invest in new ways of producing and supplying energy services, how businesses invest in equipment, and how consumers cool and heat their homes, power their devices and travel.

Underpinning all these changes are policy decisions made by governments. Devising cost-effective national and regional net zero roadmaps demands co-operation among all parts of government that breaks down silos and integrates energy into every country’s policy making on finance, labour, taxation, transport and industry. Energy or environment ministries alone cannot carry out the policy actions needed to reach net zero by 2050.

Changes in energy consumption result in a significant decline in fossil fuel tax revenues. In many countries today, taxes on diesel, gasoline and other fossil fuel consumption are an important source of public revenues, providing as much as 10% in some cases. In the net zero pathway, tax revenue from oil and gas retail sales falls by about 40% between 2020 and 2030. Managing this decline will require long-term fiscal planning and budget reforms.

The net zero pathway relies on unprecedented international co-operation among governments, especially on innovation and investment. The IEA stands ready to support governments in preparing national and regional net zero roadmaps, to provide guidance and assistance in implementing them, and to promote international co-operation to accelerate the energy transition worldwide. 

Priority action: Take international co-operation to new heights

This is not simply a matter of all governments seeking to bring their national emissions to net zero – it means tackling global challenges through co-ordinated actions.

Governments must work together in an effective and mutually beneficial manner to implement coherent measures that cross borders. This includes carefully managing domestic job creation and local commercial advantages with the collective global need for clean energy technology deployment. Accelerating innovation, developing international standards and co-ordinating to scale up clean technologies needs to be done in a way that links national markets. Co-operation must recognise differences in the stages of development of different countries and the varying situations of different parts of society. For many rich countries, achieving net zero emissions will be more difficult and costly without international co-operation. For many developing countries, the pathway to net zero without international assistance is not clear. Technical and financial support is needed to ensure deployment of key technologies and infrastructure. Without greater international co-operation, global CO 2 emissions will not fall to net zero by 2050. 

Global energy-related CO2 emissions in the net zero pathway and Low International Cooperation Case, 2010-2090

A zero-carbon-ready building is highly energy efficient and either uses renewable energy directly or uses an energy supply that will be fully decarbonised by 2050, such as electricity or district heat.

Battery gigafactory capacity assumption = 35 gigawatt-hours per year.

Reference 1

Reference 2, related net zero reports.

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To gauge whether people are engaged or withdrawn, researchers study a brainwave pattern known as frontal alpha asymmetry (the difference between right and left alpha wave activity in the frontal area of the brain). In Microsoft’s study, those taking breaks showed positive asymmetry, which is associated with higher engagement. Those who didn’t take breaks showed negative asymmetry, which is associated with being more withdrawn.

3. Transitioning between meetings can be a source of high stress.

For the participants deprived of breaks, researchers also noticed that the transition period between calls caused beta activity, or stress levels, to spike.

That might be because “you’re coming to the end of the meeting, knowing you have another one coming right up, and you’re going to have to switch gears and use your brain to think hard about something else,” Bohan says.

For those participants, beta wave activity jumped again when new check ins started. When people took meditation breaks, by contrast, the increase in beta activity dropped between meetings, and the increase at the start of the next meeting was much gentler and smoother.

Jumping directly from one meeting to another can cause spikes of stress

Taking breaks between conversations eases that stress.

An infographic shows how—without breaks—beta wave activity in the brain can rise sharply at the beginning and end of meetings, suggesting heightened stress.

Without breaks, beta wave activity in the brain can rise sharply at the beginning and end of meetings, suggesting heightened stress. Taking breaks not only prevents those spikes but causes a dip in beta activity—which correlates with less stress.

Illustration by Valerio Pellegrini

The takeaway: Breaks, even short ones, are important to make the transitions between meetings feel less stressful.

“What makes this study so powerful and relatable is that we’re effectively visualizing for people what they experience phenomenologically inside,” Bohan says. “It’s not an abstraction—quite the opposite. It's a scientific expression of the stress and fatigue people feel during back-to-backs.”

How we are adapting our products—and practices

These findings helped inform settings in Outlook that allow individuals or organizations to set defaults that shave five, 10, or 15 minutes off Microsoft Teams meetings to carve out breaks between conversations.

For example, an individual or company might decide to start its meetings five minutes after the hour or half-hour, so that 30-minute check ins drop to 25 minutes and hour-long conversations shorten to 55 minutes. That means a half-hour meeting that would have started at 11 a.m. will become a 25-minute meeting beginning at 11:05 a.m.

It’s not just the brain research that supports this change. Digital overload has become an urgent issue in the new era of remote and hybrid work. In Microsoft’s 2021 Work Trend Index published in March, 54 percent of respondents in a global external survey said they feel overworked, while 39 percent described themselves as outright exhausted.

Over the past year, we have introduced several new capabilities to foster wellbeing in this time of rapid change. Together mode in Microsoft Teams helps combat meeting fatigue; a virtual commute helps reestablish boundaries between work and home; and a Headspace integration coming with the Microsoft Viva Insights app promotes mindfulness. This new Outlook setting is a next step in this wellbeing journey, with more to come.

One final note: If you’re using the new setting in Outlook to build in break times between meetings, consider stepping away from your computer. “Try not to use that five or 10 minutes to squeeze in some other kind of work,” Bohan says. “Catch your breath and take a break away from your screen.”

Strategies for making breaks successful—and beating meeting fatigue

Because we know making space for breaks is easier said than done, we've pulled together some research-backed tips on carving out time to pause, getting the most from moments of respite, and making meetings more effective and energizing.

Shift your mindset. While it might feel more productive to power through back-to-backs, research shows the opposite is true. View breaks away from your computer as an essential part of your workday.

Find break activities that calm your mind. Meditation is one effective way to relax and recharge between meetings, but other studies show that physical activity such as walking is also beneficial. Past Microsoft studies suggest that doodling or reading something enjoyable also bring benefits. “It can be anything that takes your mind away from work-related things and focuses it on something that you feel is relaxing,” Bohan says. That will help you be refreshed and recharged when you start your next meeting.

Create even more time for breaks by considering other modes of communication. Before scheduling a video call, pause and ask yourself: Do we really need a meeting on this issue? More dynamic, creative, or emotional topics may require a meeting, while status check ins and informational subjects may benefit from document collaboration, a Teams channel, or email. Other simple tasks may be handled via chat. Read more about creating time for breaks.

Make meetings more intentional. The best—and often shortest—meetings are more intentional. Best practices like creating and sending an agenda ahead of time, being thoughtful about who attends, starting and stopping on time, and transitioning to a recap for the final five minutes will make it easier to accomplish your goals in less time. Read more about intentional meetings.

Keep participants engaged and energized. In virtual meetings, it can be hard to chime in remotely. A moderator can help ensure remote participants are included. Features like Raise your hand, Whiteboard, and Breakout Rooms in Microsoft Teams are great ways to use technology to elicit creative and strategic conversations.

Methodology

Study conducted from March 8-18, 2021, by Microsoft Human Factors Lab with 14 people participating in video meetings while wearing electroencephalogram (EEG) equipment to monitor the electrical activity in their brains. Participants consisted of Microsoft and non-Microsoft employees who are US-based information workers and who typically work remotely. Volunteers each participated in two different session blocks of meetings. In the first session, half the participants attended a stretch of four half-hour meetings back-to-back (two continuous hours), with each call devoted to different tasks (designing an office layout, for example, or creating a marketing plan). For the others, the four half-hour meetings were interspersed with 10-minute breaks, during which participants meditated with the Headspace app. The following week, the groups switched; those who had done back-to-backs had breaks, and vice versa. Three to four additional non-EEG-measured volunteers participated in each 30-minute meeting to create variation of attendees collaborating to complete the assigned tasks. Note: Headspace was not involved in the design or execution of the study.

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