Project description:Power outages threaten public health. While outages will likely increase with climate change, an aging electrical grid, and increased energy demand, little is known about their frequency and distribution within states. Here, we characterize 2018-2020 outages, finding an average of 520 million customer-hours total without power annually across 2447 US counties (73.7% of the US population). 17,484 8+ hour outages (a medically-relevant duration with potential health consequences) and 231,174 1+ hour outages took place, with greatest prevalence in Northeastern, Southern, and Appalachian counties. Arkansas, Louisiana, and Michigan counties experience a dual burden of frequent 8+ hour outages and high social vulnerability and prevalence of electricity-dependent durable medical equipment use. 62.1% of 8+ hour outages co-occur with extreme weather/climate events, particularly heavy precipitation, anomalous heat, and tropical cyclones. Results could support future large-scale epidemiology studies, inform equitable disaster preparedness and response, and prioritize geographic areas for resource allocation and interventions.
Project description:Purpose of reviewPower outages, a common and underappreciated consequence of natural disasters, are increasing in number and severity due to climate change and aging electricity grids. This narrative review synthesizes the literature on power outages and health in communities.Recent findingsWe searched Google Scholar and PubMed for English language studies with titles or abstracts containing "power outage" or "blackout." We limited papers to those that explicitly mentioned power outages or blackouts as the exposure of interest for health outcomes among individuals living in the community. We also used the reference list of these studies to identify additional studies. The final sample included 50 articles published between 2004 and 2020, with 17 (34%) appearing between 2016 and 2020. Exposure assessment remains basic and inconsistent, with 43 (86%) of studies evaluating single, large-scale power outages. Few studies used spatial and temporal control groups to assess changes in health outcomes attributable to power outages. Recent research linked data from electricity providers on power outages in space and time and included factors such as number of customers affected and duration to estimate exposure. The existing literature suggests that power outages have important health consequences ranging from carbon monoxide poisoning, temperature-related illness, gastrointestinal illness, and mortality to all-cause, cardiovascular, respiratory, and renal disease hospitalizations, especially for individuals relying on electricity-dependent medical equipment. Nonetheless the studies are limited, and more work is needed to better define and capture the relevant exposures and outcomes. Studies should consider modifying factors such as socioeconomic and other vulnerabilities as well as how community resiliency can minimize the adverse impacts of widespread major power outages.
Project description:In this paper, we simulate the economic loss resulting from supply chain disruptions triggered by the Great East Japan Earthquake (GEJE) in 2011, applying data from firm-level supply chains and establishment-level attributes to an agent-based model. To enhance the accuracy of the simulation, we extend data and models in previous studies in four ways. First, we identify the damage to production facilities in the disaster-hit regions more accurately by using establishment-level census and survey data and geographic information system (GIS) data on the damages caused by the GEJE and subsequent tsunami. Second, the use of establishment-level data enables us to capture supply chains between non-headquarter establishments in disaster-hit regions and establishments in other regions. Third, we incorporate the effect of power outages after the GEJE on production reduction, which exacerbated the effect of the supply chain disruption, particularly in the weeks immediately after the GEJE. Finally, our model incorporates sectoral heterogeneity by employing sector-specific parameters. Our findings indicate that the extended method can significantly improve the accuracy of predicting the domestic production after the GEJE, particularly due to the first three improvements utilizing various data sources, not because of the use of more sector-specific parameters. Our method can be applied to predict the economic effect of future disasters, such as the Nankai Trough earthquake, on each region more precisely.
Project description:Climate extremes, such as hurricanes, combined with large-scale integration of environment-sensitive renewables, could exacerbate the risk of widespread power outages. We introduce a coupled climate-energy model for cascading power outages, which comprehensively captures the impacts of climate extremes on renewable generation, and transmission and distribution networks. The model is validated with the 2022 Puerto Rico catastrophic blackout during Hurricane Fiona - a unique system-wide blackout event with complete records of weather-induced outages. The model reveals a resilience pattern that was not captured by the previous models: early failure of certain critical components enhances overall system resilience. Sensitivity analysis on various scenarios of behind-the-meter solar integration demonstrates that lower integration levels (below 45%, including the current level) exhibit minimal impact on system resilience in this event. However, surpassing this critical level without pairing it with energy storage can exacerbate the probability of catastrophic blackouts.
Project description:BackgroundPrevious studies investigated potential health effects of large-scale power outages, including the massive power failure that affected the northeastern United States and Ontario, Canada, in August 2003, and outages associated with major storms. However, information on localized outages is limited.ObjectiveThe study sought to examine potential health impacts of citywide and localized outages in New York City (NYC).MethodsAlong with the citywide 2003 outage, localized outages in July 1999 and July 2006 were identified. We additionally investigated localized, warm- and cold-weather outages that occurred in any of 66 NYC electric-grid networks during 2002–2014 using New York State Public Service Commission data. Mortality and hospitalizations were geocoded and linked to the networks. Associations were estimated using Poisson time-series regression, including examining distributed lags and adjusting for temperature and temporal trends. Network-specific estimates were pooled by season.ResultsRespiratory disease hospitalizations were associated with the 2006 localized outage [cumulative relative risk [CRR] over 0–1 lag day, lag01=2.26 (95% confidence interval [CI]: 1.08, 4.74)] and the 2003 citywide outage, but not with other localized, warm-weather outages. Renal disease hospitalizations were associated with the 2003 citywide outage, and with localized, warm-weather outages, pooled across networks [RR at lag3=1.16 (95% CI: 1.00, 1.34)], but not the 2006 localized outage. All-cause mortality was positively associated with the 1999, 2003, and 2006 outages (significant for the 2003 outage only), but not with other localized, warm-weather outages. Localized, cold-weather outages were associated with all-cause mortality [lag01 CRR=1.06 (95% CI: 1.01, 1.12)] and cardiovascular disease hospitalizations [lag01 CRR=1.14 (95% CI: 1.03, 1.26)], and fewer respiratory disease hospitalizations [lag03 CRR=0.77 (95% CI: 0.61, 0.97)].ConclusionsLocalized outages may affect health. This information can inform preparedness efforts and underscores the public health importance of ensuring electric grid resiliency to climate change. https://doi.org/10.1289/EHP2154.
Project description:BackgroundPosttraumatic stress symptoms (PTSS) are common after acute coronary syndrome (ACS) and predict increased morbidity and mortality. Climate change contributes to worse mental and cardiovascular health outcomes, thus, PTSS represent a potential mechanism linking climate change to adverse cardiovascular outcomes. Because people living in areas with lower socioeconomic status (SES) experience greater climate vulnerability, have worse cardiovascular health, and may be more susceptible to PTSS, any effect of temperature on PTSS could be amplified in this population.MethodsSpatial regression models were estimated to test the association of temperature and temperature variability (within-day variability, directed change over time, and absolute change over time), census tract-level SES, and their interaction with PTSS 1 month post-hospital discharge in a longitudinal cohort study comprising 956 patients evaluated for ACS at an urban U.S. academic medical center between November 2013-May 2017. PTSS were self-reported in relation to the ACS event that brought the patient to the hospital. Census tract-level was computed as a composite score from the CDC Social Vulnerability Index, with higher values indicating lower SES.ResultsNo temperature or temperature variability metrics were associated with PTSS. Lower census tract-level SES was associated with greater PTSS at 1 month. There was a marginally significant interaction of SES with ACS status, such that we only observed evidence of an association among those with ACS.ConclusionTemperature exposures were not associated with acute CVD-induced PTSS, which could be a result of a small sample size, mismatched timescale, or lack of a true effect. Conversely, lower census tract-level SES was associated with developing worse PTSS 1 month after evaluation for an ACS. This association appeared stronger in individuals with a true ACS. Early interventions to prevent PTSS could promote better mental and CVD outcomes in this at-risk population.
Project description:Exposure to extreme events is a major concern in coastal regions where growing human populations and stressed natural ecosystems are at significant risk to such phenomena. However, the complex sequence of processes that transform an event from notable to extreme can be challenging to identify and hence, limit forecast abilities. Here, we show an extreme heat content event (i.e., a marine heatwave) in coastal waters of the northern Gulf of Mexico resulted from compounding effects of a tropical storm followed by an atmospheric heatwave. This newly identified process of generating extreme ocean temperatures occurred prior to landfall of Hurricane Michael during October of 2018 and, as critical contributor to storm intensity, likely contributed to the subsequent extreme hurricane. This pattern of compounding processes will also exacerbate other environmental problems in temperature-sensitive ecosystems (e.g., coral bleaching, hypoxia) and is expected to have expanding impacts under global warming predictions.
Project description:Access to therapeutic oxygen remains a challenge in the effort to reduce pneumonia mortality among children in low- and middle-income countries. The use of oxygen concentrators is common, but their effectiveness in delivering uninterrupted oxygen is gated by reliability of the power grid. Often cylinders are employed to provide continuous coverage, but these can present other logistical challenges. In this study, we examined the use of a novel, low-pressure oxygen storage system to capture excess oxygen from a concentrator to be delivered to patients during an outage. A prototype was built and tested in a non-clinical trial in Jinja, Uganda. The trial was carried out at Jinja Regional Referral Hospital over a 75-day period. The flow rate of the unit was adjusted once per week between 0.5 and 5 liters per minute. Over the trial period, 1284 power failure episodes with a mean duration of 3.1 minutes (range 0.08 to 1720 minutes) were recorded. The low-pressure system was able to deliver oxygen over 56% of the 4,295 power outage minutes and cover over 99% of power outage events over the course of the study. These results demonstrate the technical feasibility of a method to extend oxygen availability and provide a basis for clinical trials.
Project description:The clinical responses to targeted drugs are often transient and do not always translate into meaningful overall survival due to the development of resistance. We discuss here that the greater power of drug resistant cells can be associated with significant newly-acquired vulnerabilities that can be exploited therapeutically.
Project description:We estimate the effect of heightened temperature sensitivity on electricity demand in Texas during the February 2021 blackout event. Using 20 years of hourly data, we estimate the relationship between temperature and electricity demand; finding demand has become more responsive to cold temperatures over time. This is consistent with the fact electric heating has similarly increased over the past 20 years in Texas. We find during the February 2021 event, average electricity demand was 8% higher, and approximately 10,000 MW higher during the peak hour, than it would have been had temperature sensitivity remained unchanged at early 2000s levels. Our results highlight that Texas's increased sensitivity to cold weather extremes is not limited to the supply side, but the demand side as well. These findings have implications to other regions that are seeking to reduce carbon emissions through the electrification of heating.