Browse
Abstract
The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand on the basis of historical weather over the last two decades, thereby ignoring the effects of climate change and the possibility of weather variability outside the recent historical range. In this paper, we develop an empirical method to predict the impact of weather on energy demand. We use that with a large ensemble of climate model runs to construct a probability distribution of power demand on the ERCOT grid for summer and winter 2021. We find that the most severe weather events will use 100% of available power—if anything goes wrong, as it did during the 2021 winter, there will not be sufficient available power. More quantitatively, we estimate a 5% chance that maximum power demand would be within 4.3 and 7.9 GW of ERCOT’s estimate of best-case available resources during summer and winter 2021, respectively, and a 20% chance it would be within 7.1 and 17 GW. The shortage of power on the ERCOT grid is partially hidden by the fact that ERCOTs seasonal assessments, which are based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecast an extreme peak load of 67 GW. In reality, we estimate hourly peak demand was 82 GW, 22% above ERCOT’s most extreme forecast and about equal to the best-case available power. Given the high stakes, ERCOT should develop probabilistic estimates using modern scientific tools to predict the range of power demand more accurately.
Abstract
The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand on the basis of historical weather over the last two decades, thereby ignoring the effects of climate change and the possibility of weather variability outside the recent historical range. In this paper, we develop an empirical method to predict the impact of weather on energy demand. We use that with a large ensemble of climate model runs to construct a probability distribution of power demand on the ERCOT grid for summer and winter 2021. We find that the most severe weather events will use 100% of available power—if anything goes wrong, as it did during the 2021 winter, there will not be sufficient available power. More quantitatively, we estimate a 5% chance that maximum power demand would be within 4.3 and 7.9 GW of ERCOT’s estimate of best-case available resources during summer and winter 2021, respectively, and a 20% chance it would be within 7.1 and 17 GW. The shortage of power on the ERCOT grid is partially hidden by the fact that ERCOTs seasonal assessments, which are based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecast an extreme peak load of 67 GW. In reality, we estimate hourly peak demand was 82 GW, 22% above ERCOT’s most extreme forecast and about equal to the best-case available power. Given the high stakes, ERCOT should develop probabilistic estimates using modern scientific tools to predict the range of power demand more accurately.
Abstract
This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices.
Significance Statement
Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.
Abstract
This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices.
Significance Statement
Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.
Abstract
Climate information services can build the resilience of African farmers to address the increasing threats associated with climate change. This study used household surveys with 200 farmers and focus group discussions to identify the types of climate information services available to farming households in two selected districts (Tolon and Nanton) in the Northern Region of Ghana. The study also identified the dissemination channels and the barriers faced by farmers in their access and use of climate information services for building climate resilience in Ghanaian farming systems. Multinomial logistic regression analysis was used to evaluate the determinants of farmers’ access to climate information services. Results show that 70% of the surveyed farmers had access to varied forms of climate information services. The most prevalent meteorological variables accessible to them were rainfall, temperature, and windstorms in the form of daily and weekly weather forecasts, with only very limited availability and use of seasonal climate forecasts. Radio, television, and advice from extension agents were reported as the major dissemination channels by study respondents. A majority of the farmers reported lack of communication devices, mistrust in weather and climate forecasts, and lack of visual representations in the forecasts as major barriers to access and use of climate information services. The results highlight the importance of timely and reliable access to climate information services in enhancing farmers’ decision-making capacities and the need for training and recruitment of more extension agents to work with farmers on linking climate information services to targeted actions on crop and land management.
Abstract
Climate information services can build the resilience of African farmers to address the increasing threats associated with climate change. This study used household surveys with 200 farmers and focus group discussions to identify the types of climate information services available to farming households in two selected districts (Tolon and Nanton) in the Northern Region of Ghana. The study also identified the dissemination channels and the barriers faced by farmers in their access and use of climate information services for building climate resilience in Ghanaian farming systems. Multinomial logistic regression analysis was used to evaluate the determinants of farmers’ access to climate information services. Results show that 70% of the surveyed farmers had access to varied forms of climate information services. The most prevalent meteorological variables accessible to them were rainfall, temperature, and windstorms in the form of daily and weekly weather forecasts, with only very limited availability and use of seasonal climate forecasts. Radio, television, and advice from extension agents were reported as the major dissemination channels by study respondents. A majority of the farmers reported lack of communication devices, mistrust in weather and climate forecasts, and lack of visual representations in the forecasts as major barriers to access and use of climate information services. The results highlight the importance of timely and reliable access to climate information services in enhancing farmers’ decision-making capacities and the need for training and recruitment of more extension agents to work with farmers on linking climate information services to targeted actions on crop and land management.
Abstract
Probabilistic forecast information is rapidly spreading in the weather enterprise. Many scientists agree that this is a positive development, but incorporating probability information into risk communication can be challenging because communicators have little guidance about the most effective way to present it. This project endeavors to create such guidance by initiating a “living systematic review” of research studies that empirically examine the impact of risk messages that use probability information on protective action decision-making, intentions, and behaviors. In this article, we explain how we began the review, map the current state of the literature, synthesize core findings, provide actionable recommendations to assist forecasters in risk communication, and introduce an online platform that scholars and forecasters can use to interact with the data from the review. We conclude with two key points from the review that necessitate emphasis: the research literature strongly suggests that 1) average people can make sense of and use probability information if consideration is given to information presentation and 2) assuming appropriate presentation, probability information generally improves decision quality.
Significance Statement
Probability information is increasingly common in weather forecasts, but forecasters have relatively little guidance on the most effective way to communicate this information to members of the public. This project synthesizes the research literature to provide actionable recommendations to assist forecasters who are working to include probability information in risk communication messages.
Abstract
Probabilistic forecast information is rapidly spreading in the weather enterprise. Many scientists agree that this is a positive development, but incorporating probability information into risk communication can be challenging because communicators have little guidance about the most effective way to present it. This project endeavors to create such guidance by initiating a “living systematic review” of research studies that empirically examine the impact of risk messages that use probability information on protective action decision-making, intentions, and behaviors. In this article, we explain how we began the review, map the current state of the literature, synthesize core findings, provide actionable recommendations to assist forecasters in risk communication, and introduce an online platform that scholars and forecasters can use to interact with the data from the review. We conclude with two key points from the review that necessitate emphasis: the research literature strongly suggests that 1) average people can make sense of and use probability information if consideration is given to information presentation and 2) assuming appropriate presentation, probability information generally improves decision quality.
Significance Statement
Probability information is increasingly common in weather forecasts, but forecasters have relatively little guidance on the most effective way to communicate this information to members of the public. This project synthesizes the research literature to provide actionable recommendations to assist forecasters who are working to include probability information in risk communication messages.
Abstract
Although research relating to hurricane evacuation behavior and perceptions of risk has grown throughout the years, there is very little understanding of how these risks compound during a pandemic. Utilizing the U.S. territories of Puerto Rico and the U.S. Virgin Islands (PRVI) as a study region, this work examines risk perceptions and evacuation planning during the first hurricane season following the coronavirus disease 2019 (COVID-19) pandemic before vaccines were widely available. Analyses of how people view public shelters and whether evacuation choices will change in light of COVID-19 concerns were conducted, and results reflect major changes in anticipated evacuation behavior during the 2020 hurricane season. Key findings include that over one-half of the sample considered themselves vulnerable to COVID-19. When asked about their intended actions for the 2020 hurricane season, a significant number of individuals who would have previously evacuated to a shelter said that they would choose not to during the pandemic, reflecting that public shelter usage has the potential to decrease when the decision is coupled with COVID-19 threats. In addition, individuals were shown to have a negative perception of public shelter options. Approximately one-half of the respondents had little faith in shelters’ ability to protect them, and three-quarters of respondents found the risks of enduring a hurricane to be less than those posed by public shelters. These results will inform future hazard mitigation planning during a disease outbreak or pandemic.
Abstract
Although research relating to hurricane evacuation behavior and perceptions of risk has grown throughout the years, there is very little understanding of how these risks compound during a pandemic. Utilizing the U.S. territories of Puerto Rico and the U.S. Virgin Islands (PRVI) as a study region, this work examines risk perceptions and evacuation planning during the first hurricane season following the coronavirus disease 2019 (COVID-19) pandemic before vaccines were widely available. Analyses of how people view public shelters and whether evacuation choices will change in light of COVID-19 concerns were conducted, and results reflect major changes in anticipated evacuation behavior during the 2020 hurricane season. Key findings include that over one-half of the sample considered themselves vulnerable to COVID-19. When asked about their intended actions for the 2020 hurricane season, a significant number of individuals who would have previously evacuated to a shelter said that they would choose not to during the pandemic, reflecting that public shelter usage has the potential to decrease when the decision is coupled with COVID-19 threats. In addition, individuals were shown to have a negative perception of public shelter options. Approximately one-half of the respondents had little faith in shelters’ ability to protect them, and three-quarters of respondents found the risks of enduring a hurricane to be less than those posed by public shelters. These results will inform future hazard mitigation planning during a disease outbreak or pandemic.
Abstract
It is increasingly evident that climate sustainability depends not only on societal actions and responses, but also on ecosystem functioning and responses. The capacity of global ecosystems to provide services such as sequestering carbon and regulating hydrology is being strongly reduced both by climate change itself and by unprecedented rates of ecosystem degradation. These services rely on functional aspects of ecosystems that are causally linked—the same ecosystem components that efficiently sequester and store carbon also regulate hydrology by sequestering and storing water. This means that climate change adaptation and mitigation must involve not only preparing for a future with temperature and precipitation anomalies, but also actively minimizing climate hazards and risks by conserving and managing ecosystems and their fundamental supporting and regulating ecosystem services. We summarize general climate–nature feedback processes relating to carbon and water cycling on a broad global scale before focusing on Norway to exemplify the crucial role of ecosystem regulatory services for both carbon sequestration and hydrological processes and the common neglect of this ecosystem–climate link in policy and landscape management. We argue that a key instrument for both climate change mitigation and adaptation policy is to take advantage of the climate buffering and regulative abilities of a well-functioning natural ecosystem. This will enable shared benefits to nature, climate, and human well-being. To meet the global climate and nature crises, we must capitalize on the importance of nature for buffering climate change effects, combat short-term perspectives and the discounting of future costs, and maintain or even strengthen whole-ecosystem functioning at the landscape level.
Significance Statement
Natural ecosystems such as forests, wetlands, and heaths are key for the cycling and storage of water and carbon. Preserving these systems is essential for climate mitigation and adaptation and will also secure biodiversity and associated ecosystem services. Systematic failure to recognize the links between nature and human well-being underlies the current trend of accelerating loss of nature and thereby nature’s ability to buffer climate changes and their impacts. Society needs a new perspective on spatial planning that values nature as a sink and store of carbon and a regulator of hydrological processes, as well as for its biodiversity. We need policies that fully encompass the role of nature in preventing climate-induced disasters, along with many other benefits for human well-being.
Abstract
It is increasingly evident that climate sustainability depends not only on societal actions and responses, but also on ecosystem functioning and responses. The capacity of global ecosystems to provide services such as sequestering carbon and regulating hydrology is being strongly reduced both by climate change itself and by unprecedented rates of ecosystem degradation. These services rely on functional aspects of ecosystems that are causally linked—the same ecosystem components that efficiently sequester and store carbon also regulate hydrology by sequestering and storing water. This means that climate change adaptation and mitigation must involve not only preparing for a future with temperature and precipitation anomalies, but also actively minimizing climate hazards and risks by conserving and managing ecosystems and their fundamental supporting and regulating ecosystem services. We summarize general climate–nature feedback processes relating to carbon and water cycling on a broad global scale before focusing on Norway to exemplify the crucial role of ecosystem regulatory services for both carbon sequestration and hydrological processes and the common neglect of this ecosystem–climate link in policy and landscape management. We argue that a key instrument for both climate change mitigation and adaptation policy is to take advantage of the climate buffering and regulative abilities of a well-functioning natural ecosystem. This will enable shared benefits to nature, climate, and human well-being. To meet the global climate and nature crises, we must capitalize on the importance of nature for buffering climate change effects, combat short-term perspectives and the discounting of future costs, and maintain or even strengthen whole-ecosystem functioning at the landscape level.
Significance Statement
Natural ecosystems such as forests, wetlands, and heaths are key for the cycling and storage of water and carbon. Preserving these systems is essential for climate mitigation and adaptation and will also secure biodiversity and associated ecosystem services. Systematic failure to recognize the links between nature and human well-being underlies the current trend of accelerating loss of nature and thereby nature’s ability to buffer climate changes and their impacts. Society needs a new perspective on spatial planning that values nature as a sink and store of carbon and a regulator of hydrological processes, as well as for its biodiversity. We need policies that fully encompass the role of nature in preventing climate-induced disasters, along with many other benefits for human well-being.
Abstract
This article presents an agroecosystem resilience index (ARI) relative to two types of exogenous drivers: biophysical and socioeconomic threats. The ARI is based on a theoretical framework of socioecological systems and draws upon multicriteria analysis. The multicriteria consist of variables related to natural, productive, socioeconomic, and institutional systems that are weighted and grouped through expert judgment. The index was operationalized in the Rio Grande basin (RGB), in the Colombian Andes. The ARI was evaluated at the household level using information from 99 RGB households obtained through workshops, individual semistructured interviews, and surveys. The ARI is a continuous variable that ranges between 0 and 1 and results in five categories of resilience: very low, low, medium, high, and very high. When faced with climate change impacts, 19% of households showed low resilience, 64% showed medium resilience, and 16% showed high resilience according to the ARI. When faced with price fluctuations, 23% of households showed low resilience, 65% showed medium resilience, and 11% showed high resilience. Key variables associated with high resilience include the diversity of vegetation cover, households that have forests on their properties, a high degree of connectivity with other patches of forest, diversification of household economic activities, profitability of economic activities, availability of water sources, and good relationships with local institutions.
Abstract
This article presents an agroecosystem resilience index (ARI) relative to two types of exogenous drivers: biophysical and socioeconomic threats. The ARI is based on a theoretical framework of socioecological systems and draws upon multicriteria analysis. The multicriteria consist of variables related to natural, productive, socioeconomic, and institutional systems that are weighted and grouped through expert judgment. The index was operationalized in the Rio Grande basin (RGB), in the Colombian Andes. The ARI was evaluated at the household level using information from 99 RGB households obtained through workshops, individual semistructured interviews, and surveys. The ARI is a continuous variable that ranges between 0 and 1 and results in five categories of resilience: very low, low, medium, high, and very high. When faced with climate change impacts, 19% of households showed low resilience, 64% showed medium resilience, and 16% showed high resilience according to the ARI. When faced with price fluctuations, 23% of households showed low resilience, 65% showed medium resilience, and 11% showed high resilience. Key variables associated with high resilience include the diversity of vegetation cover, households that have forests on their properties, a high degree of connectivity with other patches of forest, diversification of household economic activities, profitability of economic activities, availability of water sources, and good relationships with local institutions.
Abstract
To reach the 1.5°–2° goal of the Paris Agreement, the speed of transition to a renewable energy society must increase significantly. Applying Perrow’s theory of societal risk, we argue that switching from a fossil-based energy system to a future 100% renewable energy system may increase climate risks. Reviewing policy and research literature, and interviewing key energy policy actors in Norway, we find that there is limited knowledge on this topic and that the knowledge that does exist suffers from several shortcomings. Climate risks are generally discussed by applying future climate to the current energy system and thus failing to consider climate vulnerabilities caused by the ongoing energy transition. Also, discussions are frequently limited to subsystem reflections as opposed to system reflections and mostly present supply-side perspectives as opposed to demand-side perspectives. Most of the policy actors conclude that a future 100% renewable energy system will mainly benefit from climate change and reduce rather than increase climate risks. A research agenda is proposed to gain a better understanding of how the ongoing energy transitions can affect climate risks, especially to address the potential that reducing the level of energy consumption, diversifying energy sources, and prioritizing short-traveled energy can have to reduce climate risk in high-consuming countries.
Significance Statement
Switching from a fossil-based to a mostly “climate driven” renewable energy system may increase climate risks, and rapid transitions may increase risks even more. Still, knowledge of such risks is limited and suffers from several shortcomings. Studies are generally applying future climate to current energy system conditions and thus failing to consider vulnerabilities caused by the ongoing transformation of the energy system. Studies so far are also often limited to analyzing only parts of the system and not the energy system as a whole, and they are aiming at the production side rather than the consumption side. Thus, they tend to conclude that the energy system will mainly benefit from climate change. To reduce climate risks, we claim the need to focus on energy consumption and short-traveled energy.
Abstract
To reach the 1.5°–2° goal of the Paris Agreement, the speed of transition to a renewable energy society must increase significantly. Applying Perrow’s theory of societal risk, we argue that switching from a fossil-based energy system to a future 100% renewable energy system may increase climate risks. Reviewing policy and research literature, and interviewing key energy policy actors in Norway, we find that there is limited knowledge on this topic and that the knowledge that does exist suffers from several shortcomings. Climate risks are generally discussed by applying future climate to the current energy system and thus failing to consider climate vulnerabilities caused by the ongoing energy transition. Also, discussions are frequently limited to subsystem reflections as opposed to system reflections and mostly present supply-side perspectives as opposed to demand-side perspectives. Most of the policy actors conclude that a future 100% renewable energy system will mainly benefit from climate change and reduce rather than increase climate risks. A research agenda is proposed to gain a better understanding of how the ongoing energy transitions can affect climate risks, especially to address the potential that reducing the level of energy consumption, diversifying energy sources, and prioritizing short-traveled energy can have to reduce climate risk in high-consuming countries.
Significance Statement
Switching from a fossil-based to a mostly “climate driven” renewable energy system may increase climate risks, and rapid transitions may increase risks even more. Still, knowledge of such risks is limited and suffers from several shortcomings. Studies are generally applying future climate to current energy system conditions and thus failing to consider vulnerabilities caused by the ongoing transformation of the energy system. Studies so far are also often limited to analyzing only parts of the system and not the energy system as a whole, and they are aiming at the production side rather than the consumption side. Thus, they tend to conclude that the energy system will mainly benefit from climate change. To reduce climate risks, we claim the need to focus on energy consumption and short-traveled energy.
Abstract
Forecasts of sea ice evolution in the Arctic region for several months ahead can be of considerable socioeconomic value for a diverse range of marine sectors and for local community supply logistics. However, subseasonal-to-seasonal (S2S) forecasts represent a significant technical challenge, and translating user needs into scientifically manageable procedures and robust user confidence requires collaboration among a range of stakeholders. We developed and tested a novel, transdisciplinary coproduction approach that combined socioeconomic scenarios and participatory, research-driven simulation gaming to test a new S2S sea ice forecast system with experienced mariners in the cruise tourism sector. Our custom-developed computerized simulation game known as “ICEWISE” integrated sea ice parameters, forecast technology, and human factors as a participatory environment for stakeholder engagement. We explored the value of applications-relevant S2S sea ice prediction and linked uncertainty information. Results suggest that the usefulness of S2S services is currently most evident in schedule-dependent sectors but is expected to increase as a result of anticipated changes in the physical environment and continued growth in Arctic operations. Reliable communication of uncertainty information in sea ice forecasts must be demonstrated and trialed before users gain confidence in emerging services and technologies. Mariners’ own intuition, experience, and familiarity with forecast service provider reputation impact the extent to which sea ice information may reduce uncertainties and risks for Arctic mariners. Our insights into the performance of the combined foresight/simulation coproduction model in brokering knowledge across a range of domains demonstrates promise. We conclude with an overview of the potential contributions from S2S sea ice predictions and from experiential coproduction models to the development of decision-driven and science-informed climate services.
Abstract
Forecasts of sea ice evolution in the Arctic region for several months ahead can be of considerable socioeconomic value for a diverse range of marine sectors and for local community supply logistics. However, subseasonal-to-seasonal (S2S) forecasts represent a significant technical challenge, and translating user needs into scientifically manageable procedures and robust user confidence requires collaboration among a range of stakeholders. We developed and tested a novel, transdisciplinary coproduction approach that combined socioeconomic scenarios and participatory, research-driven simulation gaming to test a new S2S sea ice forecast system with experienced mariners in the cruise tourism sector. Our custom-developed computerized simulation game known as “ICEWISE” integrated sea ice parameters, forecast technology, and human factors as a participatory environment for stakeholder engagement. We explored the value of applications-relevant S2S sea ice prediction and linked uncertainty information. Results suggest that the usefulness of S2S services is currently most evident in schedule-dependent sectors but is expected to increase as a result of anticipated changes in the physical environment and continued growth in Arctic operations. Reliable communication of uncertainty information in sea ice forecasts must be demonstrated and trialed before users gain confidence in emerging services and technologies. Mariners’ own intuition, experience, and familiarity with forecast service provider reputation impact the extent to which sea ice information may reduce uncertainties and risks for Arctic mariners. Our insights into the performance of the combined foresight/simulation coproduction model in brokering knowledge across a range of domains demonstrates promise. We conclude with an overview of the potential contributions from S2S sea ice predictions and from experiential coproduction models to the development of decision-driven and science-informed climate services.
Abstract
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities.
Significance Statement
Carbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
Abstract
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities.
Significance Statement
Carbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
