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Landslides pose a devastating threat to human health, killing thousands of people annually. Human vulnerability is a crucial element of landslide risk reduction, yet up until now, all methods for estimating the human consequences of landslides rely on subjective, expert judgment. Furthermore, these methods do not explore the underlying causes of mortality or inform strategies to reduce landslide risk. In light of these issues, we develop a data‐driven tool to estimate an individual's probability of death based on landslide intensity, which can be used directly in landslide risk assessment. We find that between inundation depths of approximately 1–6 m, human behavior is the primary driver of mortality. Landslide vulnerability is strongly correlated with the economic development of a region, but landslide losses are not stratified by gender and age to the degree of other natural hazards. We observe that relatively simple actions, such as moving to an upper floor or a prepared refuge space, increase the odds of survival by up to a factor of 12. Additionally, community‐scale hazard awareness programs and training for citizen first responders offer a potent means to maximize survival rates in landslides. Key Points Many modern estimates of human vulnerability to landslides rely on subjective judgment and ignore the role of human behavior We present a human vulnerability curve that links an individual's probability of death to landslide inundation depth We find that human behavior drives vulnerability at inundation depths of 0.9–5.9 m and suggest practical actions to reduce personal risk

In this study, the variability and trends of the outdoor thermal discomfort index (DI) in the Kingdom of Saudi Arabia (KSA) were analyzed over the 39‐year period of 1980–2018. The hourly DI was estimated based on air temperature and relative humidity data obtained from the next‐generation global reanalysis from the European Center for Medium‐Range Weather Forecasts and in‐house high‐resolution regional reanalysis generated using an assimilative Weather Research Forecast (WRF) model. The DI exceeds 28°C, that is, the threshold for human discomfort, in all summer months (June to September) over most parts of the KSA due to a combination of consistently high temperatures and relative humidity. The DI is greater than 28°C for 8–16 h over the western parts of KSA and north of the central Red Sea. A DI of >28°C persistes for 7–9 h over the Red Sea and western KSA for 90% of summer days. The spatial extent and number of days with DI > 30°C, that is, the threshold for severe human discomfort, are significantly lower than those with DI > 28°C. Long‐term trends in the number of days with DI > 28°C indicate a reduced rate of increase or even a decrease over some parts of the southwestern KSA in recent decades (1999–2018). Areas with DI > 30°C, in particular the northwestern regions of the Arabian Gulf and its adjoining regions, also showed improved comfort levels during recent decades. Significant increases in population and urbanization have been reported throughout the KSA during the study period. Analysis of five‐years clinical data suggests a positive correlation between higher temperatures and humidity with heat‐related deaths during the Hajj pilgrimage. The information provided herein is expected to aid national authorities and policymakers in developing necessary strategies to mitigate the exposure of humans to high levels of thermal discomfort in the KSA. Plain Language Summary We analyzed the outdoor thermal discomfort using an in‐house high‐resolution reanalysis generated using an advanced Weather Research and Forecast modeling system and assimilating all available regional observations. We examined the spatiotemporal distribution of thermal discomfort from 1981 to 2018 over Kingdom of Saudi Arabia (KSA). Our results outline changes in livability conditions in terms of the trends of different thermal discomfort thresholds in the last four decades across KSA. Further, we investigate the possible reasons for the increase/decrease of thermal discomfort over different regions of KSA. Our study suggests improved living conditions over some parts of the northwestern Arabian Gulf and their adjoining regions in recent decades and worse conditions over the southeast regions. The detailed information provided here on the hotspots of improved or deteriorated human discomfort will be useful for decision makers to take efficient mitigation measures. Key Points Analyze and investigate variability and trends of the outdoor thermal discomfort index (DI) in the Kingdom of Saudi Arabia (KSA) Reduced rate of increase in DI was reported in the southwestern region during the last 20 years During this period, except Yanbu, Makkah, Madina, and Taif, most cities had an improved DI

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human‐caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future. Plain Language Summary Contaminants of emerging concern (CECs) are included in an ever‐evolving list of chemicals and microorganisms that are not currently regulated in drinking, recreational, or environmental waters but may be detrimental to human or ecological health. Advances in analytical technology have allowed the detection of these contaminants at ever decreasing concentrations. Additional techniques, such as nontargeted analyses and bioanalytical tools, have expanded our understanding on the occurrence of CECs both individually and in mixtures. Even with new analytical tools, little is known about the potentially tens of thousands of CECs that may be present in water. Models could be used to predict the fate and occurrence of these contaminants. Information on the toxicity to human and aquatic life, both for individual contaminants and mixtures, can follow environmental detection. Advancements in wastewater and drinking water treatment have increased the capacity for the reduction of contaminants in water. More research would be useful to determine human exposures that are occurring through all exposure routes to determine if, and where, additional treatment would be beneficial. If water resources become more limited due to population increases, climatic change, poor treatment performance, or other factors, CECs may become a larger concern for human and ecological health. Key Points Contaminants of emerging concern (CECs) are an ever‐evolving list of chemicals and microorganisms that are not currently regulated in water Advances in analytical technology have allowed the detection of individual and mixtures of CECs at ever decreasing concentrations Transdisciplinary research can be used to address science gaps in water monitoring, treatment optimization, and source water protection

Representation of irrigation in Earth System Models has advanced over the past decade, yet large uncertainties persist in the effective simulation of irrigation practices, particularly over locations where the on-ground practices and climate impacts are less reliably known. Here we investigate the utility of assimilating remotely sensed vegetation data for improving irrigation water use and associated fluxes within a land surface model. We show that assimilating optical sensor-based leaf area index estimates significantly improves the simulation of irrigation water use when compared to the USGS ground reports. For heavily irrigated areas, assimilation improves the evaporative fluxes and gross primary production (GPP) simulations, with the median correlation increasing by 0.1–1.1 and 0.3–0.6, respectively, as compared to the reference datasets. Further, bias improvements in the range of 14–35 mm mo^(−1) and 10–82 g m^(-2)mo^(−1) are obtained in evaporative fluxes and GPP as a result of incorporating vegetation constraints, respectively. These results demonstrate that the use of remotely sensed vegetation data is an effective, observation-informed, globally applicable approach for simulating irrigation and characterizing its impacts on water and carbon states.

Emissions of particulate matter from fires associated with land management practices in Indonesia contribute to regional air pollution and mortality. We assess the public health benefits in Indonesia, Malaysia, and Singapore from policies to reduce fires by integrating information on fire emissions, atmospheric transport patterns, and population exposure to fine particulate matter (PM2.5). We use adjoint sensitivities to relate fire emissions to PM2.5 for a range of meteorological conditions and find that a Business‐As‐Usual scenario of land use change leads, on average, to 36,000 excess deaths per year into the foreseeable future (the next several decades) across the region. These deaths are largely preventable with fire reduction strategies, such as blocking fires in peatlands, industrial concessions, or protected areas, which reduce the health burden by 66, 45, and 14%, respectively. The effectiveness of these different strategies in mitigating human health impacts depends on the location of fires relative to the population distribution. For example, protecting peatlands through eliminating all fires on such lands would prevent on average 24,000 excess deaths per year into the foreseeable future across the region because, in addition to storing large amounts of fuel, many peatlands are located directly upwind of densely populated areas. We also demonstrate how this framework can be used to prioritize restoration locations for the Indonesian Peatland Restoration Agency based on their ability to reduce pollution exposure and health burden. This scientific framework is publicly available through an online decision support tool that allows stakeholders to readily determine the public health benefits of different land management strategies. Plain Language Summary Regularly occurring fires in Indonesia are associated with drought conditions and agricultural practices. These fires contribute to dangerous levels of particulate matter pollution that are harmful to public health throughout the region. We develop an interdisciplinary scientific framework to connect land use decisions with fire activity and public health outcomes. Our estimates find that if current trends continue, exposure to air pollution from Indonesian fires would cause, on average, 36,000 excess deaths per year across Indonesia, Malaysia, and Singapore. These deaths can be prevented through land management strategies, which would reduce the number of deaths attributable to air pollution from fires. Current plans to restore peatlands would reduce regional fire emissions‐related mortality by approximately 66% if fully implemented. Key Points Current trends in Indonesia's fire activity would lead to 37,000 excess deaths per year across the region from air pollution exposure Restoring peatlands could reduce fire‐related mortality by nearly 70% Our integrative scientific tool can be used to support land management strategies most beneficial for public health

In the United States, citizens and policymakers heavily rely upon Environmental Protection Agency mandated regulatory networks to monitor air pollution; increasingly they also depend on low-cost sensor networks to supplement spatial gaps in regulatory monitor networks coverage. Although these regulatory and low-cost networks in tandem provide enhanced spatiotemporal coverage in urban areas, low-cost sensors are located often in higher income, predominantly White areas. Such disparity in coverage may exacerbate existing inequalities and impact the ability of different communities to respond to the threat of air pollution. Here we present a study using cost-constrained multiresolution dynamic mode decomposition (mrDMDcc) to identify the optimal and equitable placement of fine particulate matter (PM2.5) sensors in four U.S. cities with histories of racial or income segregation: St. Louis, Houston, Boston, and Buffalo. This novel approach incorporates the variation of PM2.5 on timescales ranging from 1 day to over a decade to capture air pollution variability. We also introduce a cost function into the sensor placement optimization that represents the balance between our objectives of capturing PM2.5 extremes and increasing pollution monitoring in low-income and nonwhite areas. We find that the mrDMDcc algorithm places a greater number of sensors in historically low-income and nonwhite neighborhoods with known environmental pollution problems compared to networks using PM2.5 information alone. Our work provides a roadmap for the creation of equitable sensor networks in U.S. cities and offers a guide for democratizing air pollution data through increasing spatial coverage of low-cost sensors in less privileged communities.

The COVID‐19 pandemic has profoundly influenced urban lifestyles, particularly the utilization of green spaces. While existing studies have primarily focused on the immediate effects of COVID‐19‐induced isolation, less attention has been given to the enduring impacts on green space usage patterns. This study addresses this gap by conducting three comprehensive surveys in Dezhou, China—before, during, and after the first wave of social isolation (December 2019, March 2020, December 2020). These surveys assessed socioeconomic conditions, commuting habits, green space usage habits, and landscape preferences, specifically focusing on usage frequency, duration of stays, and activities undertaken. Using Mann‐Whitney U tests and Spearman's rho correlations, we identified significant long‐term changes, including an increase in the frequency of visits by previously infrequent users, a reduction in visit durations, and a rise in high‐intensity activities. These trends persisted 9 months post‐isolation, highlighting the pandemic's lasting impact on green space usage and its critical role in enhancing public health and pandemic preparedness through thoughtful urban environmental design. This study not only sheds light on behavioral adaptations during a public health crisis but also offers evidence‐based strategies for urban planning to bolster societal resilience in the face of future pandemics. Plain Language Summary During the COVID‐19 pandemic, how people used parks and green areas changed significantly because of social distancing rules. To understand these changes, we asked people about their green space usage habits before, during, and after the first major outbreak in Dezhou, China. We were interested in how often they visited these spaces, how long they stayed, and why they went there. Our research showed that, with the pandemic's social rules, fewer people went to these spaces, and when they did, they stayed for shorter periods but were more likely to engage in intense activities. These patterns were still noticeable 9 months later. This study suggests that designing our green spaces thoughtfully can help communities better handle the challenges of pandemics, making us healthier and more prepared for future crises. Key Points Immediate and lasting effects of COVID‐19‐induced isolation on green space usage habits were distinguished Three surveys were conducted before, during, and after the first wave of the COVID‐19 pandemic's social isolation Effects of isolation on usage habits were identified and these effects remained significant 9 months after the social isolation

The concept of resilience has been evolving over the past decade as a way to address the current and future challenges nations, states, and cities face from a changing climate. Understanding how the environment (natural and built), climate event risk, societal interactions, and governance reflect community resilience for adaptive management is critical for envisioning urban and natural environments that can persist through extreme weather events and longer‐term shifts in climate. To be successful, this interaction of these five domains must result in maintaining quality of life and ensuring equal access to the benefits or the protection from harm for all segments of the population. An exhaustive literature review of climate resilience approaches was conducted examining the two primary elements of resilience—vulnerability and recoverability. The results of this review were examined to determine if any existing frameworks addressed the above five major areas in an integrated manner. While some aspects of a resilience model were available for existing sources, no comprehensive approach was available. A new conceptual model for resilience to climate events is proposed that incorporates some available structures and addresses these five domains at a national, regional, state, and county spatial scale for a variety of climate‐induced events ranging from superstorms to droughts and their concomitant events such as wildfires, floods, and pest invasions. This conceptual model will be developed in a manner that will permit comparisons among governance units (e.g., counties) and permit an examination of best reliance practices. Key Points Conceptual model of community resilience to climate events Climate event resilience must be holistic and include vulnerability and recoverability This conceptual model is being populated for application for the U.S. at the county level

Climate change may alter access to safe drinking water, with important implications for health. We assessed the relationship between temperature and rainfall and utilization of basic drinking water (BDW) in The Gambia, Mozambique, Pakistan, and Kenya. The outcomes of interest were (a) whether the reported drinking water source used in the past 2 weeks met the World Health Organization definition of BDW and (b) use of a BDW source that was always available. Temperature and precipitation data were compiled from weather stations and satellite data and summarized to account for long‐ and short‐term weather patterns and lags. We utilized random forests and logistic regression to identify key weather variables that predicted outcomes by site and the association between important weather variables and BDW use. Higher temperatures were associated with decreased BDW use at three of four sites and decreased use of BDW that is always available at all four sites. Increasing rainfall, both in the long‐ and short‐term, was associated with increased BDW use in three sites. We found evidence for interactions between household wealth and weather variables at two sites, suggesting lower wealth populations may be more sensitive to weather‐driven changes in water access. Changes in temperature and precipitation can alter safe water use in low‐resource settings—investigating drivers for these relationships can inform efforts to build climate resilience. Plain Language Summary This manuscript examines the association between temperature, precipitation and the use of safe drinking water sources in four low and middle‐income countries. Climate is known to impact the risk of diarrheal disease, but the potential mechanisms driving this relationship are poorly described. We hypothesized that both short and long‐term trends in temperature and precipitation may affect both improved water source availability and usage in low‐resource settings. We utilized data from a case‐control study on diarrheal disease with data on household water source use and availability. Machine learning was used to identify the most important weather predictors of households using “basic drinking water” (BDW) as defined by the World Health Organization. We found higher temperatures and decreasing rainfall were associated with decreased BDW use overall at three of the four sites. Notably, we also found evidence of resilience to climate impacts linked to safe drinking water availability and household wealth. Our findings have broad‐reaching implications for climate resilient infrastructure development and provide critical evidence that increasing prevalence of drought and rising temperatures can lead to use of less‐safe water sources. Key Points Access to and reported use of basic drinking water (BDW) is dependent on rainfall and temperature in The Gambia, Mozambique, Pakistan, and Kenya Higher temperatures are associated with decreased access to and use of BDW Climate change threatens access to safe drinking water in settings where infrastructure is vulnerable to rainfall and temperature

The popular beaches of the San Diego‐Tijuana (US/MX) border region are often impacted by untreated wastewater sourced from Mexico—via the Tijuana River Estuary (TJRE) and San Antonio de los Buenos outfall at the Pt. Bandera (SAB/PTB) shoreline, leading to impacted beaches and human illness. The US‐Mexico‐Canada trade agreement will fund border infrastructure projects reducing untreated wastewater discharges. However, estimating project benefits such as reduced human illness and beach impacts is challenging. We develop a coupled hydrodynamic, norovirus (NoV) pathogen, and swimmer illness risk model with the wastewater sources for the year 2017. The model is used to evaluate the reduction in human illness and beach impacts under baseline conditions and three infrastructure diversion scenarios which (Scenario A) reduce SAB/PTB discharges and moderately reduce TJRE inflows or (Scenarios B, C) strongly reduce TJRE in inflows only. The model estimates shoreline untreated wastewater and NoV concentrations, and the number of NoV ill swimmers at Imperial Beach CA. In the Baseline, the percentage of swimmers becoming ill is 3.8% over 2017, increasing to 4.5% during the tourist season (Memorial to Labor Day) due to south‐swell driven SAB/PTB plumes. Overall, Scenario A provides the largest reduction in ill swimmers and beach impacts for the tourist season and full year. The 2017 tourist season TJRE inflows were not representative of those in 2020, yet, Scenario A likely still provides the greatest benefit in other years. This methodology can be applied to other coastal regions with wastewater inputs. Plain Language Summary The popular beaches of the San Diego‐Tijuana border region are often impacted by Mexican‐sourced untreated wastewater leading to beach advisories and human health impacts. There are two principal ocean sources: the Tijuana River Estuary (TJRE) and San Antonio de los Buenos outfall at Pt. Bandera (SAB/PTB). The recent US‐Mexico‐Canada trade agreement will fund infrastructure projects to reduce untreated wastewater flowing into the ocean. Estimating project benefits requires coupling models, which is challenging and has not previously been performed. We develop such a model to estimate shoreline pathogen concentration and swimmer illness risk for the year 2017 for four scenarios of baseline conditions and three infrastructure diversion scenarios which (Scenario A) reduce SAB/PTB discharges and moderately reduce TJRE inflows or (Scenarios B, C) strongly reduce TJRE inflows only. In the Baseline, the percentage of swimmers becoming ill is 3.8% over the year, increasing to 4.5% for the tourist season (Memorial to Labor Day) due to south‐swell driven SAB/PTB plumes. Overall, Scenario A provides the largest reduction in ill swimmers both for the tourist season and full year relative to Scenarios B and C that only reduce TJRE inflows. This methodology can be applied to other regions where wastewater enters the ocean. Key Points We develop a coupled hydrodynamic, a pathogen, and swimmer illness model to evaluate US/MX border region shoreline wastewater impacts Year 2017 model simulations quantitatively assess the benefits of four infrastructure scenarios that reduce regional wastewater inputs Tourist season has the most ill swimmers from plumes advecting north from MX, and mitigating this source yields the largest benefit