Introduction There is scarce information about the allocation of health resources in Syria. Pre-existing inequalities were further intensified after the 2011 conflict which displaced over 50% of the population. This study provides an analysis of health inequalities in Syria focusing on spatial access to public hospitals and employs data from 2010, just prior to the outbreak of conflict. Establishing a preconflict snapshot of the health system could serve as a helpful baseline assessment for future studies to measure the impact of the conflict on the health system. Such information could also offer systematic data to guide postconflict reconstruction efforts. Methods We compared two methods to quantify the inpatient bed access: provider to population ratio (PPR) and two-step floating catchment area (2SFCA) method. We compared PPR calculated at the governorate level with population weighted 2SFCA score calculated at a resolution of 2 km by 2 km. We then aggregated at the governorate level, tested multiple catchment sizes and calculated Gini coefficient for each governorate. Results We found high inequality in access to public hospitals across and within governorates, especially in the north and eastern regions, where all governorates ranked in the lowest two quintiles using both PPR and 2SFCA. Relatively small governorates in the west and the south had higher spatial access and less inequality. Testing variability in catchment size showed that even at 125 km catchment, 65% of the country had accessibility below national average. Conclusion Methodologically, the use of 2SFCA provided more nuanced insights about hospital bed allocation than PPR. 2SFCA was able to account for the cross-boundary effect and road network quality. Realistic representation of health accessibility is possible in data-scarce settings such as Syria and could be adapted to assess health access inequalities in conflict and postconflict settings.

Despite sustained global efforts to avoid, reduce, and reverse land degradation, estimates of land degradation nationally and regionally vary considerably. Land degradation reduces agricultural productivity, impacts the provision of vital ecosystem services, and disproportionately affects vulnerable populations. The 2030 Agenda for Sustainable Development, through Sustainable Development Goal 15.3, sets out to achieve land degradation neutrality (LDN) by improving the livelihoods of those most affected and building resilience in areas affected by or at risk from degradation. The United Nations Convention to Combat Desertification (UNCCD) leads the charge in creating a spatially explicit framework for monitoring and reporting on LDN goals that countries can integrate into their land planning policies. However, it remains difficult to operationalize the integration of biophysical indicators of land degradation with climatic and socio‐economic indicators to assess the impact of land degradation on vulnerable populations. We present an integrative framework that demonstrates how freely available global geospatial data sets can be leveraged through an open‐source platform (Trends.Earth) to simplify and operationalize monitoring and reporting on progress towards achieving LDN. Then, we summarize a suite of data sets and approaches that can be used to understand and quantify the socio‐ecological interactions between drought, land degradation and population exposed to desertification, land degradation and drought. We discuss how improvements in Earth observation data sets and algorithms will allow UNCCD land‐based progress sub‐indicators (changes in primary productivity, land cover, soil organic carbon, drought, and population exposure) to be computed at enhanced spatial resolutions.

Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM₁₀) concentrations to lung cancer rates in New Hampshire, USA. First, Pearson correlation analysis and geographically weighted regression were used to investigate spatial relationships between outdoor PM₁₀ and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM₁₀ to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and secondhand smoke to the risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed.

Addressing the global challenges of desertification, land degradation, and drought (DLDD), and their impacts on achieving sustainable development goals for coupled human-environmental systems is a key component of the 2030 Agenda for Sustainable Development. In particular, Sustainable Development Goal (SDG) 15.3 aims to, “by 2030, combat desertification, restore degraded land and soil, including land affected by desertification, drought and floods, and strive to achieve a land degradation-neutral world”. Addressing this challenge is essential for improving the livelihoods of those most affected by DLDD and for safeguarding against the most extreme effects of climate change. This paper introduces a conceptual framework for improved monitoring of DLDD in the context of United Nations Convention to Combat Desertification (UNCCD) Strategic Objective 2 (SO2) and its expected impacts: food security and adequate access to water for people in affected areas are improved; the livelihoods of people in affected areas are improved and diversified; local people, especially women and youth, are empowered and participate in decision-making processes in combating DLDD; and migration forced by desertification and land degradation is substantially reduced. While it is critical to develop methods and tools for assessing DLDD, work is needed first to provide a conceptual roadmap of the human dimensions of vulnerability in relation to DLDD, especially when attempting to create a globally standardized monitoring approach.

Measuring destination attractivity and finding the determinants of attractivity at the county scale can finely reveal migration flows and explain what kinds of counties have higher attractivity. Such understanding can help local governors make better policies to enhance county attractivity and attract more migrants for regional development. In this study, the county-scale relative intrinsic attractivity (RIA) of Guangdong Province is computed using the number of migrants and the corresponding distances between origins and destinations. The results show that the RIA has a higher positive correlation with the flows of migrants to destination and demonstrates an obvious phenomenon of distance decay. The RIA decreases faster when the distance between origins and destinations increases. Spatially, the RIA reveals a core-periphery belt pattern in Guangdong Province. The center of the Pearl River Delta is the highest core of RIA and the outside areas of the delta represent the low-RIA belt. The highest RIA is 6811 in Dongguan City and the lowest RIA is 1 in Yangshan County. The core area includes Dongguan, Shenzhen City and the southern regions of Guangzhou, Foshan and Zhongshan City where the RIA value is higher than 1000. The second belt is mainly composed of the periphery districts of the Pearl River Delta, which include Shunde, Nanhai, Luohu, Tianhe Huicheng, Panyu, Haizhu, Huiyang, Huadu, Yuexiu, Xiangzhou and the Yuexiu, Huangpu and Boluo, where the RIA values are higher than 100 and lower than 1000. The third belt includes the western wing, eastern wing and northern area. Most of these RIA values range from 1 to 2. In this belt, there are three areas with relatively higher RIA attractivity scattered in the ring: the downtowns of Zhanjiang City, Chaozhou and Shantou Cities and Shaoguan City. The areas farther away from the core have a lower RIA score. Determinants analysis indicates that the RIA is positively determined by destination economic development level, social service and living standard level and destination population quality. A region will be more attractive if it has higher per capital GDP, tertiary industry level, investment and number of industrial enterprises involved in economic development. A region with a high annual average wage of employees and high social service and living standards will be more attractive, while a region with low destination population quality, including aspects such as the adult illiteracy rate, will be less attractive.

Adverse exposure to noise pollution is increasingly recognized as a significant public health concern. Strong evidence links noise exposure with negative health outcomes such as cardiovascular disease, mental disorders, stress, and sleep disturbance. The presence of noise in parks, which are environmental settings associated with health promotion, recreation, and restoration, presents a paradox that warrants further exploration. The United States offers a distinct context for exploring this paradox, given its vast public park system and a wide array of anthropogenic and environmental noise sources. Our scoping review synthesized findings from fifteen research studies that investigated noise exposure and noise levels in United States public parks. The review examined how studies measured noise, the integration of subjective perceptions with objective assessments, and the role of park characteristics in shaping park visitor noise experiences. Results highlighted varying methodological approaches, with some studies employing sound level meters or modeling techniques, while others also incorporated surveys to capture visitor perceptions. Despite this variety, evidence on the direct health impacts of park noise exposure remains limited, and longitudinal studies are largely absent. Notably, few studies evaluated how noise interacts with other environmental exposures, such as air pollution or greenness, to influence visitor perception and wellness. By synthesizing the current evidence base, this review suggests knowledge gaps and few methodological inconsistencies that limit the field. Findings call for future research mobilizing standardized, multimodal noise assessment methods, and considerations for health outcome measures. Such advancements are important for informing public health interventions and guiding urban planning strategies to improve the acoustic quality and restorative potential of US parks.