Heatwaves cause excess mortality and physiological impacts on humans throughout the world, and climate change will intensify and increase the frequency of heat events. Many adaptation and mitigation studies use spatial distribution of highly vulnerable local populations to inform heat reduction and response plans. However, most available heat vulnerability studies focus on urban areas with high heat intensification by Urban Heat Islands (UHIs). Rural areas encompass different environmental and socioeconomic issues that require alternate analyses of vulnerability. We categorized Nebraska census tracts into four urbanization levels, then conducted factor analyses on each group and captured different patterns of socioeconomic vulnerabilities among resultant Heat Vulnerability Indices (HVIs). While disability is the major component of HVI in two urbanized classes, lower education, and races other than white have higher contributions in HVI for the two rural classes. To account for environmental vulnerability of HVI, we considered different land type combinations for each urban class based on their percentage areas and their differences in heat intensifications. Our results demonstrate different combinations of initial variables in heat vulnerability among urban classes of Nebraska and clustering of high and low heat vulnerable areas within the highest urbanized sections. Less urbanized areas show no spatial clustering of HVI. More studies with separation on urbanization level of residence can give insights into different socioeconomic vulnerability patterns in rural and urban areas, while also identifying changes in environmental variables that better capture heat intensification in rural settings.

The outcomes of drought can be difficult to assess due to the complexity of its effects. While most risk assessments of drought are developed for agriculture or water resources, the associations with human health are not well studied due to unclear and complex pathways. This study is the first to assess potential changes in health risk from droughts during the last decade in the contiguous United States. To assess the risk, we spatially superimposed vulnerability variables associated with drought on historical drought exposure over the last decade. Different variations in Local Moran’s I statistics were used to assess the spatial distribution of health vulnerability, risk of drought, and changes in the two five-year study periods (2010–2014 and 2015–2019). Our results show large clusters of the western United States had a significant increase in risk during the latter part of the study period due to increases in vulnerability and hazard. In addition, southern areas of the United States were consistently above the national average in drought risk. Since our vulnerability variables include agriculture, drinking water, and sociodemographic indicators, the results of this study can help various experts interested in drought preparedness efforts associated with human health.

Advances in artificial intelligence (AI), particularly agentic AI, have created opportunities to enhance global sustainability by improving the efficiency and accuracy of environmental monitoring and response systems. Agentic AIs autonomously plan and execute towards specific goals with minimal or no human intervention; however, accessing environmental data is challenging and requires expertise due to inherent fragmentation and the diversity of data formats. The Model Context Protocol (MCP) is an open standard that allows AI systems to securely access and interact with diverse software tools and data sources through unified interfaces, reducing the need for custom integrations while enabling more accurate, context-aware assistance. This study introduces WeatherInfo_MCP, an interface that provides the required expertise for AI agents to access National Weather Service (NWS) data. Built on a service-oriented architecture, the system uses a centralized engine to handle robust geocoding and data extraction while providing AI agents with simple, independent tools to retrieve weather data from the NWS API. The system was validated through 14 unit tests and 23 comprehensive protocol compliance tests against the MCP 2025-06-18 specification, achieving a 100% pass rate across all categories, demonstrating its reliability when working with AI agents. We also successfully tested our model alongside a memory MCP to showcase its performance in a multi-MCP environment. While in its earliest version, WeatherInfo_MCP connects to the NWS API, its modular design and compliance with software development and MCP standards facilitate immediate expansion to additional environmental data and tools. WeatherInfo_MCP is released as an open-source tool to support the sustainable development community, enabling broad adoption of AI agents for environmental use cases.

Heatwaves cause excess mortality and physiological impacts on humans throughout the world, and climate change will intensify and increase the frequency of heat events. Many adaptation and mitigation studies use spatial distribution of highly vulnerable local populations to inform heat reduction and response plans. However, most available heat vulnerability studies focus on urban areas with high heat intensification by Urban Heat Islands (UHIs). Rural areas encompass different environmental and socioeconomic issues that require alternative analyses of vulnerability. We categorized Nebraska census tracts into four urbanization levels, then conducted factor analyses on each group and captured different patterns of socioeconomic vulnerabilities among resulted Heat Vulnerability Indices (HVIs). While disability is the major component of HVI in two urbanized classes, lower education and races other than white have higher contributions in HVI for the two rural classes. To account for environmental vulnerability of HVI, we considered different land type combinations for each urban class based on their percentage areas and their differences in heat intensifications. Our results demonstrate different combination of initial variables in heat vulnerability among urban classes of Nebraska and clustering of high and low heat vulnerable areas within the highest urbanized section. Less urbanized areas show no spatial clustering of HVI. More studies with separation on urbanization level of residence can give insights into different socioeconomic vulnerability patterns in rural and urban areas, while also identifying changes in environmental variables that better capture heat intensification in rural settings.

Drought is considered among the most devastating climate hazards impacting civilizations, including human health, throughout history. It causes cumulative damages based on the five generally categorized meteorological, hydrological, agricultural, socioeconomic, and ecological droughts. Reducing damages at the local, regional, and global levels requires a better understanding of human (health) vulnerability to drought. While there are different studies to distinguish and measure vulnerabilities for the five aforementioned conditions, there is minimal effort to identify vulnerabilities to health impacts from drought. Our study aims to develop an analysis of vulnerability for Nebraska based on the established health effects associated with drought. We considered vulnerability as the interaction between exposure to drought and different sensitivity measures for a timespan, including the highest drought levels in the 21st century. To calculate the total sensitivities, we extracted ten initial variables and applied two well-known methods of dimensionality reduction and (Weighted) Additive Overlays of percentile-ranked values. The result showed the inadequacy of the former method for our study. We also grouped the sensitivity variables into socioeconomic, environmental, and water-related intervention categories and developed related intensity maps showing different spatial patterns. We calculated the drought exposure levels by adding the intensity, duration, and frequency of drought over the study period (2012–2016) and developed total vulnerability maps to determine the ten most vulnerable counties, of which nine are rural. The resulting three intervention category maps can help related experts find priority areas within Nebraska, and the final vulnerability maps can help distinguish the areas of concern for general state-wide planning. While the results and some sensitivity variables are unique to Nebraska, the provided framework and the inclusion of two different methods can guide other regions in similar studies.

Drought is one of the most widespread and disruptive natural hazards globally, with environmental and societal effects that may increase psychological distress. Yet, its association with suicide in the U.S. remains understudied. We examined the relationship between drought and suicide mortality across the contiguous U.S. Drought severity was measured using the Evaporative Demand Drought Index, and suicide data from the National Center for Health Statistics. We used Generalized Additive Models (GAMs) to estimate incidence rate ratios (IRRs) and absolute risk differences (ARDs), with 95% confidence intervals. Analyses were stratified by age, sex, and urbanicity. From 2000 to 2018, the U.S. recorded 350,434 firearm‐related and 323,225 non‐firearm suicide deaths. Drought affected 37.4% of county‐months, and both suicide types were positively associated with drought—especially under severe conditions. For firearm suicides, worsening drought was linked to an IRR of 1.109 (95% CI: 1.091–1.128) and ARD of 0.704 (95% CI: 0.595–0.811); improving drought had an IRR of 1.094 (95% CI: 1.076–1.112) and ARD of 0.608 (95% CI: 0.501–0.715). For non‐firearm suicides, worsening drought was associated with an IRR of 1.057 (95% CI: 1.037–1.077) and ARD of 0.347 (95% CI: 0.232–0.461), while improving drought had an IRR of 1.073 (95% CI: 1.054–1.093) and ARD of 0.456 (95% CI: 0.344–0.568). Severe drought was associated with higher suicide mortality, including firearm‐related deaths, across several subgroups such as older adults, women, and individuals living in non‐metro areas; these subgroup‐specific findings were not statistically compared.