Recently constructed hydropower dams were associated with reduced economic production, population, and greenness in nearby areas.

Hydropower dams produce huge impacts on renewable energy production, water resources, and economic development, particularly in the Global South, where accelerated dam construction has made it a global hotspot. We do not fully understand the multiple impacts that dams have in the nearby areas from a global perspective, including the spatial differentiations. In this study, we examined the impacts of hydropower dam construction in nearby areas. We first found that more than one-third of global gross domestic production (GDP) and almost one-third of global population fall within 50 km of the world's 7,155 hydropower dams (<10% of the global land area sans the Antarctic). We further analyzed impacts of 631 hydropower dams (≥1-megawatt capacity) constructed since 2001 and commissioned before 2015 for their effects on economy, population, and environment in nearby areas and examined the results in five regions (i.e., Africa, Asia, Europe, North America, and South America) and by different dam sizes. We found that recently constructed dams were associated with increased GDP in North America and urban areas in Europe but with decreased GDP, urban land, and population in the Global South and greenness in Africa in nearby areas. Globally, these dams were linked with reduced economic production, population, and greenness of areas within 50 km of the dams. While large dams were related with reduced GDP and greenness significantly, small and medium dams were coupled with lowered population and urban land substantially, and large and medium dams were connected to diminished nighttime light noticeably in nearby areas.

Spatiotemporal or temporal index to assess the association between temperature variability and mortality in China?

Epidemiological studies increasingly provide evidence about the adverse health effects of temperature variability (TV), which reflects short-term intra- and inter-day temperature change. However, calculation of TV only considers the temporal variability and lacks spatial variability. This study intends to investigate whether the lack of spatial variability in TV calculations has biased the health effect estimates. We collected daily data from the fine-gridded hourly temperatures and more than 2 million all-cause mortality counts in Zhejiang province in China from 2009 to 2015. A spatiotemporal TV index was developed by calculating the standard deviation of the hourly temperatures based on records from multiple sites. This new index could be compared to the two typical temporal TV indices that are calculated based on the hourly temperatures from one-site and area-average records. The three types of TV are compared using a three-stage analytical approach: district-specific time series Poisson regression, meta-analysis, and calculation of attributable mortality fraction. We observe that both spatiotemporal and temporal TVs produce very similar TV-mortality associations, attributable mortality fractions, and model fits at the district level. For example, the mortality increase associated for every increase of 1 °C during 0-7 exposure days is 1.53% (95% CI: 1.31, 1.73) in spatiotemporal TV, whereas it is 1.48% (95% CI: 1.27, 1.68) and 1.45% (95% CI: 1.24, 1.67) in the one-site and area-average temporal TV, respectively. Thus, time series models using temporal TV index are equally good at estimating the associations between TV and mortality as spatiotemporal TV at the district level in population-based epidemiological studies in China. Epidemiological studies using temperature from one site or the averages of multiple sites in TV calculation will not bias the effect estimates of TV. Our study could provide an important guidance method for future TV-related research in China and even in other countries.

Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China.

BACKGROUND: The increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales. METHODS: A human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level. RESULTS: High-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index. CONCLUSIONS: This study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

Spatially Explicit Mapping of Heat Health Risk Utilizing Environmental and Socioeconomic Data.

Extreme heat events, a leading cause of weather-related fatality worldwide, are expected to intensify, last longer, and occur more frequently in the near future. In heat health risk assessments, a spatiotemporal mismatch usually exists between hazard (heat stress) data and exposure (population distribution) data. Such mismatch is present because demographic data are generally updated every couple of years and unavailable at the subcensus unit level, which hinders the ability to diagnose human risks. In the present work, a human settlement index based on multisensor remote sensing data, including nighttime light, vegetation index, and digital elevation model data, was used for heat exposure assessment on a per-pixel basis. Moreover, the nighttime urban heat island effect was considered in heat hazard assessment. The heat-related health risk was spatially explicitly assessed and mapped at the 250 m × 250 m pixel level across Zhejiang Province in eastern China. The results showed that the accumulated heat risk estimates and the heat-related deaths were significantly correlated at the county level (Spearman's correlation coefficient = 0.76, P ≤ 0.01). Our analysis introduced a spatially specific methodology for the risk mapping of heat-related health outcomes, which is useful for decision support in preparation and mitigation of heat-related risk and potential adaptation.

Hydro-dam - A nature-based solution or an ecological problem: The fate of the Tonlé Sap Lake.

Recent proliferation of hydro-dams was one of the nature-based solutions to meet the increasing demand for energy and food in the Lower Mekong River Basin (LMRB). While construction of these hydro-dams generated some hydropower and facilitated expansion of irrigated lands, it also significantly altered the basin-wide hydrology and subsequently impacted wetland ecosystems. Unintended adverse consequences of ecosystem services from lakes and wetlands offset the intended gains in hydroelectricity and irrigated agriculture. The trade-offs between gains in energy and food production and losses in aquatic ecosystem services were perceived to be significant but knowledge of the magnitude, spatial extent, and type of ecosystem services change is lacking and, therefore, the question whether the hydro-dam is an optimized solution or a potential ecological problem remains unanswered. In this study, as the first step to answer this question and using the Tonlé Sap Lake as an example, we quantified one of the impacts of hydro-dams on lake ecosystem's phenology in terms of open water area, a critical ecological characteristic that affects lake systems' fish production, biodiversity, and livelihoods of the local communities. We used the MODIS-NDVI time series, forecast function and the Mann-Kendall trend test method to first quantify the open water area, analyzed its changes over time, and then performed correlation analysis with climate variables to disentangle dam impacts. The results showed reduced hydro-periods, diminishing lake seasonality and a declining trend in Tonlé Sap Lake open water area over the past 15 years. These changes were insignificantly related to climatic influence during the same period. It is concluded that basin-wide hydro-dam construction and associated agricultural irrigation were deemed to be the primary cause of these ecological changes. Further analyses of changes in the lake's ecosystem services, including provision and cultural services, need to be carried out in order to have a holistic understanding of the trade-offs brought by the hydro-dam proliferation as a solution to the emerging energy and food demand in the LMRB.

Grassland productivity and carbon sequestration in Mongolian grasslands: The underlying mechanisms and nomadic implications.

BACKGROUND: Quantifying carbon (C) dioxide exchanges between ecosystems and the atmosphere and the underlying mechanism of biophysical regulations under similar environmental conditions is critical for an accurate understanding of C budgets and ecosystem functions. METHODS: For the first time, a cluster of four eddy covariance towers were set up to answer how C fluxes shift among four dominant ecosystems in Mongolia - meadow steppe (MDW), typical steppe (TPL), dry typical steppe (DRT) and shrubland (SHB) during two growing seasons (2014 and 2015). RESULTS: Large variations were observed for the annual net ecosystem exchange (NEE) from 59 to 193gCm-2, though all four sites acted as a C source. During the two growing seasons, MDW acted as a C sink, TPL and DRT were C neutral, while SHB acted as a C source. MDW to SHB and TPL conversions resulted in a 2.6- and 2.2-fold increase in C release, respectively, whereas the TPL to SHB conversion resulted in a 1.1-fold increase at the annual scale. C assimilation was higher at MDW than those at the other three ecosystems due to its greater C assimilation ability and longer C assimilation times during the day and growing period. On the other hand, C release was highest at SHB due to significantly lower photosynthetic production and relatively higher ecosystem respiration (ER). A stepwise multiple regression analysis showed that the seasonal variations in NEE, ER and gross ecosystem production (GEP) were controlled by air temperature at MDW, while they were controlled mainly by soil moisture at TPL, DRT and SHB. When air temperature increased, the NEE at MDW and TPL changed more dramatically than at DRT and SHB, suggesting not only a stronger C release ability but also a higher temperature sensitivity at MDW and TPL. CONCLUSIONS: The ongoing and predicted global changes in Mongolia likely impact the C exchange at MDW and TPL more than at DRT and SHB in Mongolia. Our results suggest that, with increasing drought and vegetation type succession, a clear trend for greater CO2 emissions may result in further global warming in the future. This study implies that diverse grassland ecosystems will respond differently to climate change in the future and can be seen as nature-based solutions (NBS) supporting climate change adaptation and mitigation strategies.

Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia.

The spatio-temporal characteristics of remote sensing are considered to be the primary advantage in environmental studies. With long-term and frequent satellite observations, it is possible to monitor changes in key biophysical attributes such as phenological characteristics, and relate them to climate change by examining their correlations. Although a number of remote sensing methods have been developed to quantify vegetation seasonal cycles using time-series of vegetation indices, there is limited effort to explore and monitor changes and trends of vegetation phenology in the Monsoon Southeast Asia, which is adversely affected by changes in the Asian monsoon climate. In this study, MODIS EVI and TRMM time series data, along with field survey data, were analyzed to quantify phenological patterns and trends in the Monsoon Southeast Asia during 2001-2010 period and assess their relationship with climate change in the region. The results revealed a great regional variability and inter-annual fluctuation in vegetation phenology. The phenological patterns varied spatially across the region and they were strongly correlated with climate variations and land use patterns. The overall phenological trends appeared to shift towards a later and slightly longer growing season up to 14 days from 2001 to 2010. Interestingly, the corresponding rainy season seemed to have started earlier and ended later, resulting in a slightly longer wet season extending up to 7 days, while the total amount of rainfall in the region decreased during the same time period. The phenological shifts and changes in vegetation growth appeared to be associated with climate events such as EL Niño in 2005. Furthermore, rainfall seemed to be the dominant force driving the phenological changes in naturally vegetated areas and rainfed croplands, whereas land use management was the key factor in irrigated agricultural areas.

Demand Potential for Agricultural Trade between China and Countries along the "Belt and Road".

International agricultural markets are an important part of the global food resource chain. Tapping into the potential of agricultural trade between China and countries along the "Belt and Road" (B&R) is conducive to safeguarding China's and the world's food security, but there is less literature on the potential of bilateral trade demand. This paper ranks the B&R countries according to the scale of imports and exports, and calculates the elasticity of demand for imports, the elasticity of substitution for exports, and, finally, the potential of elasticity of demand for trade between China and the major B&R countries. The results show that China's agricultural export potential to major B&R countries is ranked as follows: Indonesia, Thailand, Russia, Poland, Turkey, Vietnam, Malaysia, Ukraine, India, and Singapore. The major B&R countries are also ranked in terms of their export potential to China: Vietnam, India, Ukraine, Russia, Malaysia, Thailand, Indonesia, Poland, Singapore, and Turkey. The findings of this paper provide a decision-making basis for promoting agricultural trade between China and B&R countries.

Anthropogenic and climate impacts on carbon stocks of grassland ecosystems in Inner Mongolia and adjacent region.

Up to date, most studies reported that degradation is worsened in the grassland ecosystems of Inner Mongolia and adjacent regions as a result of intensified grazing. This seems to be scientific when considering the total forage or total above-ground biomass as a degradation indicator, but it does not hold true in terms of soil organic carbon density (SOCD). In this study, we quantified the changes of grassland ecosystem carbon stock in Inner Mongolia and adjacent regions from the 1980s to 2000s and identified the major drivers influencing these variations, using the National Grassland Resource Inventory and Soil Survey Dataset in 1980s and the Inventory data during 2002 to 2009 covering 624 sampling plots concerned vegetal traits and edaphic properties across the study region. The result indicated that the above-, below-ground and total vegetation biomass declined from the 1980s to 2000s by ∼ 10 %. However, total forage production increased by 6.72 % when considering livestock intake. SOCD remained stable despite a 67 % increase in grazing intensity. A generalized linear model (GLIM) analysis suggested that an increase in grazing intensity from the 1980s to 2000s could only explain 1.04 % of the total biomass change, while changes in precipitation and temperature explained 17.7 % (p < 0.05) of total vegetation biomass (TVB) change. Meanwhile, SOCD change during 1980s - 2000s could be explained 10.08 % by the soil texture (p < 0.05) and <1.6 % by changes in climate and livestock. This implies that the impacts of climate change on grassland biomass are more significant than those of grazing utilization, and SOCD was resistant to both climate change and intensified grazing. Overall, intensified grazing did not result in significant negative impacts on the grassland carbon stocks in the study region during the 1980s and 2000s. The grassland ecosystems possess a mechanism to adjust their root-shoot ratio, enabling them to maintain resilience against grazing utilization.

Characterization of the impacts of hydro-dams on wetland inundations in Southeast Asia.

Inundations of wetlands play a significant role in wetland ecosystems, but they are vulnerable to hydrological alterations. In Southeast Asia, many hydro-dams, which significantly alter the hydrology, have been built, but little is known about the influences of dams on wetland inundations. In this study, we quantified the characteristics of inundations and related the alterations to the dams by distinguishing them from influences of climate variabilities and local human activities. A multi-sensor approach using Landsat 8, Sentinel-1, and MODIS was devised to delineate the weekly inundations of 362 Southeast Asian wetlands from 2014 to 2021. The four hydrological characteristics (cyclical patterns, trends, intra-annual variability, and amplitude of inundations) were quantified, and the alteration of the characteristics caused by dams was separated from climate variabilities and local human activities using correlation analysis and logistic regression models. The results found that cyclical patterns, trends, intra-annual variability, and amplitude of wetland inundations changed significantly over the period, but the magnitudes vary significantly depending on their geographic locations with respect to the dams. Findings showed that dams critically affect the wetlands even though dams are located distantly from the dams. This indicates that wetlands should be monitored and conserved for reducing the influences of dams. This study advances our understanding of the effects of dams on wetlands by using the multi-sensor approach and distinguishing them from climate variabilities and local human activities.

A synthesis of hydroclimatic, ecological, and socioeconomic data for transdisciplinary research in the Mekong.

The Mekong River basin (MRB) is a transboundary basin that supports livelihoods of over 70 million inhabitants and diverse terrestrial-aquatic ecosystems. This critical lifeline for people and ecosystems is under transformation due to climatic stressors and human activities (e.g., land use change and dam construction). Thus, there is an urgent need to better understand the changing hydrological and ecological systems in the MRB and develop improved adaptation strategies. This, however, is hampered partly by lack of sufficient, reliable, and accessible observational data across the basin. Here, we fill this long-standing gap for MRB by synthesizing climate, hydrological, ecological, and socioeconomic data from various disparate sources. The data- including groundwater records digitized from the literature-provide crucial insights into surface water systems, groundwater dynamics, land use patterns, and socioeconomic changes. The analyses presented also shed light on uncertainties associated with various datasets and the most appropriate choices. These datasets are expected to advance socio-hydrological research and inform science-based management decisions and policymaking for sustainable food-energy-water, livelihood, and ecological systems in the MRB.

Urbanization, economic development, and environmental changes in transitional economies in the global south: a case of Yangon.

Background: Transitional economies in Southeast Asia-a distinct group of developing countries-have experienced rapid urbanization in the past several decades due to the economic transition that fundamentally changed the function of their economies, societies and the environment. Myanmar, one of the least developed transitional economies in Southeast Asia, increased urbanization substantially from 25% in 1990 to 31% in 2019. However, major knowledge gaps exist in understanding the changes in urban land use and land cover and environment and their drivers in its cities. Methods: We studied Yangon, the largest city in Myanmar, for the urbanization, environmental changes, and the underlying driving forces in a radically transitioned economy in the developing world. Based on satellite imagery and historic land use maps, we quantified the expansion of urban built-up land and constructed the land conversion matrix from 1990 through 2020. We also used three air pollutants to illustrate the changes in environmental conditions. We analyzed the coupled dynamics among urbanization, economic development, and environmental changes. Through conducting a workshop with 20 local experts, we further analyzed the influence of human systems and natural systems on Yangon's urbanization and sustainability. Results: The city of Yangon expanded urban built-up land rapidly from 1990 to 2000, slowed down from 2000 to 2010, but gained momentum again from 2010 to 2020, with most newly added urban built-up land appearing to be converted from farmland and green land in both 1990-2000 and 2010-2020. Furthermore, the air pollutant concentration of CO decreased, but that of NO2 and PM2.5 increased in recent years. A positive correlation exists between population and economic development and the concentration of PM2.5 is highly associated with population, the economy, and the number of vehicles. Finally, the expert panel also identified other potential drivers for urbanization, including the extreme climate event of Cyclone Nargis, capital relocation, and globalization. Conclusions: Our research highlights the dramatic expansion of urban land and degradation of urban environment measured by air pollutants and interdependent changes between urbanization, economic development, and environmental changes.

Quantifying the effect of ecological restoration on soil erosion in China's Loess Plateau region: an application of the MMF approach.

Land degradation due to erosion is one of the most serious environmental problems in China. To reduce land degradation, the government has taken a number of conservation and restoration measures, including the Sloping Land Conversion Program (SLCP), which was launched in 1999. A logical question is whether these measures have reduced soil erosion at the regional level. The objective of this article is to answer this question by assessing soil erosion dynamics in the Zuli River basin in the Loess Plateau of China from 1999 to 2006. The MMF (Morgan, Morgan and Finney) model was used to simulate changes in runoff and soil erosion over the period of time during which ecological restoration projects were implemented. Some model variables were derived from remotely sensed images to provide improved land surface representation. With an overall accuracy rate of 0.67, our simulations show that increased ground vegetation cover, especially in forestlands and grasslands, has reduced soil erosion by 38.8% on average from 1999 to 2006. During the same time period, however, the change in rainfall pattern has caused a 13.1% +/- 4.3% increase in soil erosion, resulting in a net 25.7% +/- 8.5% reduction in soil erosion. This suggests that China's various ecological restoration efforts have been effective in reducing soil loss.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, upper Yangtze, China from 1975 to 2000.

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975-2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.

[Study on relationship between on-the-go near-infrared spectroscopy and soil texture].

Near infrared spectroscopy (NIRS) is a rapid, pioximal-sensed method that has proven useful in quantifying soil constituents mainly in laboratory. However, very little is known about how NIRS performs in a field setting by newly developed on-the-go NIRS measurements. The objective of the present study was to evaluate the relationship between on-the-go field NIRS measurements and soil texture in a glacial till soil. It was found that NIRS band combination based on difference, normalized difference and ratio could apparently improve the coefficient of relationship between NIRS and soil texture, and this might be a new and effective analytical procedure for field NIRS measurements.

Temperature variability and mortality in rural and urban areas in Zhejiang province, China: An application of a spatiotemporal index.

BACKGROUND: Temperature variability (TV) is a potential trigger for death in urban areas, but there is little evidence of this in rural areas. In addition, a typical TV index only considers the temporal variability of temperature and ignores its spatial variability, which should be considered due to the effects of human mobility. Here this study aimed to 1) develop a novel spatiotemporal TV index accounting for human mobility; and 2) based on this index, explore the urban-rural differences in TV-mortality associations in China. METHODS: We collected daily data on fine-gridded hourly temperatures and >2 million deaths that occurred in Zhejiang province, China from 2009 to 2015. A spatiotemporal TV index was developed by calculating the standard deviation of the hourly temperatures from multi-site records over the course of several exposure days. A three-stage analysis was performed to estimate the mortality risks and mortality burdens of TV. Stratified analyses were performed by cause-specific mortality, urban/rural district, age and gender. RESULTS: Significant associations were found between TV and all types of targeted diseases, age groups, and genders. Percentage increase in mortality associated with a 1 °C increase in TV at 0-7 exposure days were found to be higher for rural dwellers than urban dwellers in the warm season [for all-cause mortality, 2.07% (95% CI: 1.49%, 2.64%) vs. 1.16% (95%CI: 0.70%, 1.62%)]. An estimated all-cause mortality fraction of 5.33% was attributable to TV, with 4.99% in urban areas and 6.02% in rural areas. The elderly (aged 65+ years) and females were more sensitive to TV than young people and males, respectively. CONCLUSIONS: A spatiotemporal TV index was developed, considering both the temporal and spatial variability of temperatures. TV is an independent health risk factor. In China, rural areas generally suffer greater TV-related mortality risks than urban areas in the warm season. Our findings have important implications for developing area-, cause-, and group-specific adaptation strategies and emergency planning to reduce TV-related mortality.

Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model.

Remote sensing image products (e.g. brightness of nighttime lights and land cover/land use types) have been widely used to disaggregate census data to produce gridded population maps for large geographic areas. The advent of the geospatial big data revolution has created additional opportunities to map population distributions at fine resolutions with high accuracy. A considerable proportion of the geospatial data contains semantic information that indicates different categories of human activities occurring at exact geographic locations. Such information is often lacking in remote sensing data. In addition, the remarkable progress in machine learning provides toolkits for demographers to model complex nonlinear correlations between population and heterogeneous geographic covariates. In this study, a typical type of geospatial big data, points-of-interest (POIs), was combined with multi-source remote sensing data in a random forests model to disaggregate the 2010 county-level census population data to 100 × 100 m grids. Compared with the WorldPop population dataset, our population map showed higher accuracy. The root mean square error for population estimates in Beijing, Shanghai, Guangzhou, and Chongqing for this method and WorldPop were 27,829 and 34,193, respectively. The large under-allocation of the population in urban areas and over-allocation in rural areas in the WorldPop dataset was greatly reduced in this new population map. Apart from revealing the effectiveness of POIs in improving population mapping, this study promises the potential of geospatial big data for mapping other socioeconomic parameters in the future.

Evidence for Urban-Rural Disparity in Temperature-Mortality Relationships in Zhejiang Province, China.

BACKGROUND: Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban-rural differences in the temperature impacts on health outcomes. OBJECTIVES: We investigated whether temperature-mortality relationships vary between urban and rural counties in China. METHODS: We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban-rural differences were explored using meta-regression with county-level characteristics. RESULTS: Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban-rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban-rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types. CONCLUSIONS: Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure-response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban-rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban-rural disparity in mortality risks. https://doi.org/10.1289/EHP3556.

Buruli ulcer disease prevalence in Benin, West Africa: associations with land use/cover and the identification of disease clusters.

BACKGROUND: Buruli ulcer (BU) disease, caused by infection with the environmental mycobacterium M. ulcerans, is an emerging infectious disease in many tropical and sub-tropical countries. Although vectors and modes of transmission remain unknown, it is hypothesized that the transmission of BU disease is associated with human activities in or around aquatic environments, and that characteristics of the landscape (e.g., land use/cover) play a role in mediating BU disease. Several studies performed at relatively small spatial scales (e.g., within a single village or region of a country) support these hypotheses; however, if BU disease is associated with land use/cover characteristics, either through spatial constraints on vector-host dynamics or by mediating human activities, then large-scale (i.e., country-wide) associations should also emerge. The objectives of this study were to (1) investigate associations between BU disease prevalence in villages in Benin, West Africa and surrounding land use/cover patterns and other map-based characteristics, and (2) identify areas with greater and lower than expected prevalence rates (i.e., disease clusters) to assist with the development of prevention and control programs. RESULTS: Our landscape-based models identified low elevation, rural villages surrounded by forest land cover, and located in drainage basins with variable wetness patterns as being associated with higher BU disease prevalence rates. We also identified five spatial disease clusters. Three of the five clusters contained villages with greater than expected prevalence rates and two clusters contained villages with lower than expected prevalence rates. Those villages with greater than expected BU disease prevalence rates spanned a fairly narrow region of south-central Benin. CONCLUSION: Our analyses suggest that interactions between natural land cover and human alterations to the landscape likely play a role in the dynamics of BU disease. For example, urbanization, potentially by providing access to protected water sources, may reduce the likelihood of becoming infected with BU disease. Villages located at low elevations may have higher BU disease prevalence rates due to their close spatial proximity to high risk environments. In addition, forest land cover and drainage basins with variable wetness patterns may be important for providing suitable growth conditions for M. ulcerans, influencing the distribution and abundance of vectors, or mediating vector-human interactions. The identification of disease clusters in this study provides direction for future research aimed at better understanding these and other environmental and social determinants involved in BU disease outbreaks.

Spatial and Seasonal Dynamics of Water Environmental Capacity in Mountainous Rivers of the Southeastern Coast, China.

The south-east littoral is one of the most populous and developed regions in China suffering from serious water pollution problems, and the Xian-Jiang Basin in the mid of this region is among the most polluted watersheds. Critical information is needed but lacking for improved pollution control and water quality assessment, among which water environmental capacity (WEC) is the most important variable but is difficult to calculate. In this study, a one-dimensional water quality model combined with a matrix calculation algorithm was first developed and calibrated with in-situ observations in the Xian-Jiang basin. Then, the model was applied to analyze the spatial and temporal patterns of WEC of the entire basin. The results indicated that, in 2015, the total pollutant discharges into the river reached 6719.68 t/yr, 488.12 t/yr, and 128.57 t/yr for COD, NH3-N and TP, respectively. The spatial pattern suggested a strong correlation between these water contaminants and industrial enterprises, residential areas, and land-use types in the basin. Furthermore, it was noticed that there was a significant seasonal pattern in WEC that the dry season pollution is much greater than that in the plum season, while that in the typhoon season appears to be the weakest among all seasons. The WEC differed significantly among the 24 sub-basins during the dry season but varied to a smaller extent in other seasons, suggesting differential complex spatial-temporal dependency of the WEC.