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Bailey R. Stevens and Walker S. Ashley

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.

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Jennifer Collins, Amy Polen, Elizabeth Dunn, Leslie Maas, Erik Ackerson, Janis Valmond, Ernesto Morales, and Delián Colón-Burgos

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.

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Jangho Lee and Andrew E. Dessler

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.

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William A. Yagatich, Eryn Campbell, Amanda C. Borth, Shaelyn M. Patzer, Kristin M. F. Timm, Susan Joy Hassol, Bernadette Woods Placky, and Edward W. Maibach

Abstract

Prior research suggests that climate stories are rarely reported by local news outlets in the United States. As part of the Climate Matters in the Newsroom project—a program for climate-reporting resources designed to help journalists report local climate stories—we conducted a series of local climate-reporting workshops for journalists to support such reporting. Here, we present the impacts of eight workshops conducted in 2018 and 2019—including participant assessments of the workshop, longitudinal changes in their climate-reporting self-efficacy, and the number and proportion of print and digital climate stories reported. We learned that participants found value in the workshops and experienced significant increases in their climate-reporting self-efficacy in response to the workshops, which were largely sustained over the next 6 months. We found only limited evidence that participants reported more frequently on climate change after the workshops—possibly, in part, due to the impact of coronavirus disease 2019 (COVID-19) on the news industry. These findings suggest that local climate-reporting workshops can be a useful but not necessarily sufficient strategy for supporting local climate change reporting. Further research is needed to illuminate how to support local climate reporting most effectively.

Significance Statement

As part of an NSF-funded project to support local climate change news reporting, we conducted a series of eight journalist workshops. Here we evaluate their impacts. Participants gave the workshops strong positive ratings and experienced significant increases in climate-reporting self-efficacy. There was only limited evidence, however, that the workshops led to more frequent reporting on climate change—a conclusion muddied by the impacts of coronavirus disease 2019 (COVID-19) on the news industry. These findings suggest that local climate-reporting workshops may be a useful strategy but that additional research is needed to strengthen the approach.

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Chris Vagasky

Abstract

Millions of people attend Major League Baseball games every year, during a season that is played primarily outdoors at the peak of the U.S. lightning season. In recent years, social media photographs and baseball game television broadcasts have revealed lightning within proximity of several baseball games without the game being delayed. Lightning data from the U.S. National Lightning Detection Network within 12.8 km of 9717 Major League Baseball games between 2016 and 2019 were examined to find the extent to which lightning is a threat to games, players, staff, and fans: 717 games were found to have lightning within 12.8 km, with more than 175 000 in-cloud and cloud-to-ground lightning discharges detected during those games. The distribution of games with lightning was not uniform and is related to the annual average lightning density of each ballpark. Despite the significant risk of a lightning-related incident at Major League Baseball games, existing work from other organizations like the National Collegiate Athletics Association and the National Athletics Trainers Association can be leveraged to improve lightning safety at professional baseball games.

Significance Statement

Nearly one of every 14 Major League Baseball games has lightning within what lightning safety experts would consider an unsafe distance. The potential for a lightning casualty incident is high because most games are played outdoors and millions of people are at baseball games every year. Although frameworks that can improve lightning safety at the thousands of professional baseball games that are played every year exist, it is unclear how frequently they are implemented.

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Sonu Mathew and Srinivas S. Pulugurtha

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.

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Andrea Suarez-Pardo, Clara Villegas-Palacio, and Lina Berrouet

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.

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Mark R. Jury and Jane Kerr

Abstract

We study how seasonal climate affects influenza–pneumonia (I-P) mortality using monthly health and climate data over the past 20 years, reduced to mean annual cycle and statistically correlated. Results show that I-P deaths are inversely related to temperature, humidity, and net solar radiation in the United States, South Africa, and Puerto Rico (r < −0.93) via transmission and immune system response. The I-P mortality is 3–10 times as high in winter as in summer, with sharp transitions in autumn and spring. Public health management can rely on seasonal climate-induced fluctuations of I-P mortality to promote healthy lifestyle choices and guide efforts to mitigate epidemic impacts.

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Katy Harris, Frida Lager, Marta K. Jansen, and Magnus Benzie

Abstract

Recent research has highlighted that adaptation tends to focus exclusively on the local and direct impacts of climate change and misses the crucial dimension of transboundary climate risk, which all countries are likely to face, irrespective of their level of development. This paper aims to improve the coverage of transboundary climate risk in case-study research for adaptation. It proposes a protocol to help researchers identify how their case studies can incorporate an analysis of transboundary climate risk, thereby supporting more holistic, effective and just approaches to adaptation. Existing climate risk assessment frameworks and supporting guidelines have significant strengths but also various challenges when applied to the novel context of transboundary climate risk. This is illustrated with reference to the Impact Chain framework. Its opportunities pertain to both its flexible form and systems-first focus while its constraints include an analytic emphasis on linear cause-effect relationships (that bely the complexity and uncertainty of systemic risk) and its limited applicability to fragmented governance landscapes (in the absence of an effective consideration of risk ownership). After critically examining the suitability of the Impact Chain framework, a new protocol is introduced, which builds on principles for managing complex risk and frameworks for assessing risk ownership. The protocol is designed to enable case-study researchers to better identify, assess and appraise transboundary climate risks, as well as enquire into appropriate risk owners and adaptation options across scales. The paper argues for more innovation in adaptation research, to better reflect the complexity and interdependency that characterise today’s world.

Open access
Michael A. Goldstein, Amanda H. Lynch, Ruitian Yan, Siri Veland, and William Talleri

Abstract

As Arctic open water increases, shipping activity to and from mid- and western- Russian Arctic ports to points south has notably increased. A number of Arctic municipalities hope increased vessel traffic will create opportunities to become a major transshipment hub. However, even with more traffic passing these ports, it might still be economically cheaper to offload cargo at a more southern port and also result in lower emissions; ultimately, the question of whether to use a transshipment in the Arctic vs. an established major European port is determined by the relative costs (or emissions) of sea vs. land travel.

This study calculates the relative competitiveness of six Norwegian coastal cities as multi-modal hubs for shipments. We quantify the relative prices and CO2 emissions for sea and land travel for routes starting at the Norwegian/Russian sea border with an ultimate destination in central Europe and find all existing routes are not competitive with routes using the major existing Port of Rotterdam; even with investments in port expansion and modernization, they would be underutilized regardless of an increase in vessel traffic destined for Central Europe. We then examine under what relative prices (emissions) these routes become economically viable or result in lower emissions than using existing southern ports. Notably, the cheapest routes generally produce the lowest emissions and the most expensive routes tend to have the largest emissions. Communities should consider relative competitiveness prior to making large infrastructure investments. While some choices are physically possible, they may not be economically viable.

Open access