Evaluating air pollution exposure among cyclists: Real-time levels of PM2.5 and NO2 and POI impact.

Although cycling has numerous health benefits, the increased breathing volume and lack of protection from exposure to the environment while cycling poses health risks that cannot be disregarded. Previous studies evaluating the exposure of cyclists to air pollution have typically focused on assessing exposure to a single pollutant or exposure concentrations on specific urban routes, and have not performed a comprehensive assessment considering the distribution of cyclists. The present study used bicycle-sharing big data to conduct a more comprehensive and refined real-time population weighted exposure risk assessment of pileless bike sharing riders in Beijing. We quantified the spatial distribution of high exposure areas at different times and found that the exposure risk during the evening peak period was significantly higher than that during the morning peak and early morning periods, particularly in the city center and its environs. By establishing stepwise regression models, we identified the significant impact of various urban points of interest (POIs) on exposure risk, with sports venues, public toilets, educational institutions, scenic spots, and financial entities particularly influential at different time periods. Medical institutions and shopping venues have a significant negative impact on the exposure levels of PM2.5 and NO2 among cyclists in most cases. These findings emphasize the need for targeted pollution control strategies. The aim of this study is to mitigate the impact of air pollution on cyclists and create a healthier cycling environment. The research results can provide new ideas for urban health planning and support scientific decision-making for sustainable urban development.

Cooling Effect of Green Spaces on Urban Heat Island in a Chinese Megacity: Increasing Coverage versus Optimizing Spatial Distribution.

Enhancing the cooling effectiveness of green spaces (GSs) is crucial for improving urban thermal environments in the context of global warming. Increasing GS coverage and optimizing its spatial distribution individually proved to be effective urban cooling measures. However, their comparative cooling effectiveness and potential interaction remain unclear. Here, using the moving window approach and random forest algorithm, we established a robust model (R2 = 0.89 ± 0.01) to explore the relationship between GS and land surface temperature (LST) in the Chinese megacity of Guangzhou. Subsequently, the response of LST to varying GS coverage and its spatial distribution was simulated, both individually and in combination. The results indicate that GS with higher coverage and more equitable spatial distribution is conducive to urban heat mitigation. Increasing GS coverage was found to lower the city's average LST by up to 4.73 °C, while optimizing GS spatial distribution led to a decrease of 1.06 °C. Meanwhile, a synergistic cooling effect was observed when combining both measures, resulting in additional cooling benefits (0.034-0.341 °C). These findings provide valuable insights into the cooling potential of GS and crucial guidance for urban green planning aimed at heat mitigation in cities.

Controlling desertification brings positive socioeconomic benefits beyond regional environmental improvement: Evidence from China's Gonghe Basin.

Large-scale desertification combatting programs (DCPs) are crucial tools for addressing climate change and improving the ecological environment. Despite existing research having predominantly focused on assessing the ecological benefits of DCPs, the understanding of their impacts on surrounding socioeconomic aspects remains limited, particularly at the household level. To comprehensively evaluate the returns of DCPs, this study chose the representative desertification control area of the Gonghe Basin on the Qinghai-Tibet Plateau as the research region and identified the dual benefits in terms of ecological environment and socioeconomic gains. Firstly, two essential ecosystem services, carbon sequestration (CS) and wind erosion prevention (WEP), were assessed using the MODIS NPP dataset and the RWEQ model from 2001 to 2021. Household surveys were conducted in 36 villages across 14 townships within the Gonghe Basin to gain a deeper understanding of the residents' socioeconomic conditions. Through regression analysis, the study assessed the impact of DCPs on the regional ecological environment and household socioeconomic status. The research findings revealed significant improvements in CS and WEP across a significant portion of the study area from 2001 to 2021. Upon analyzing data from 401 household questionnaires, it was generally perceived by residents in the Gonghe Basin that the implementation of DCPs led to environmental improvements and increased their income levels. Further regression analysis revealed a significant impact of both natural factors and the extent of resident participation in the projects on the ecological environment surrounding the villages and on household socioeconomic aspects. With increased resident engagement in the projects, the likelihood of increased household income and life satisfaction was higher. The diverse array of DCPs implemented in the Gonghe Basin not only improved the regional ecological environment but also stimulated socioeconomic development. In future projects, it is imperative to consider regional characteristics, align ecological effects, ensure the sustainability of livelihoods, and maximize the role of social capital.

Downscaling of environmental indicators: A review.

Environmental indicators at different scales are important for environmental management, daily life, and scientific research. Because of the lack of statistics below a national scale for many environmental indicators, scholars have developed various downscaling methods to obtain finer-scale and diverse forms of data for different environmental indicators. However, the existing downscaling methods for environmental indicators are diverse and fragmented. Here, we reviewed the downscaling methods by reclassifying the environmental indicators from a life cycle perspective into five categories: natural resources use and related attributes; material and energy consumption; environmental discharge; climate change; and environmental footprints. We first provide a general introduction to downscaling theory in the environmental field, including definitions, techniques, and evolution. We then elaborate on downscaling methods and make an inventory of the five categories of environmental indicators. We summarize the downscaling methods commonly applied to specific indicators, scale transformation, the strengths and limitations of corresponding methods, and provide specific examples. Next, we discuss ways to select or construct downscaling methods based on four principles: objective orientation, data accessibility, model feasibility, and model adjustment. Finally, we explore the future direction of downscaling and provide insights for improving downscaling for environmental indicators. In this review, we generalize and clarify the downscaling techniques for environmental indicators, which will help facilitate the appropriate selection of downscaling methods by researchers.

Heterogeneous effects of the availability and spatial configuration of urban green spaces on their cooling effects in China.

The impacts of the availability and spatial configuration of urban green spaces (UGS) on their cooling effects can vary with background climate conditions. However, large-scale studies that assess the potential heterogeneous relationships of UGS availability and spatial configuration with urban thermal environment are still lacking. In this study, we investigated the impacts of UGS availability and spatial configuration on urban land surface temperature (LST) taking 306 cities in China as a case study covering a multi-biome-scale. We first calculated the availability of surrounding UGS for urban built-up pixels in each city using a distance-weighted approach, and its spatial configuration was quantified through the Gini coefficient. Then, we employed various regression models to explore how the impacts of UGS availability and the Gini coefficient on LST varies across different LST quantiles and between day- and nighttime. The results revealed that UGS availability was negatively associated with both daytime and nighttime LST, while the Gini coefficient showed a positive impact solely on daytime LST, indicating that an adequate and equally distributed UGS contributes to lower environmental temperatures during the daytime. Furthermore, the impact of UGS availability on LST decreased during both day- and nighttime with increased background LST quantiles. Whereas the impact of the Gini coefficient increased only with daytime LST quantile levels, with its effect remaining almost insignificant during the night. Our findings provide new insights into the impacts of UGS on urban thermal environment, offering significant implications for urban green infrastructure planning aiming at lowering the urban heat island.

The tradeoffs between food supply and demand from the perspective of ecosystem service flows: A case study in the Pearl River Delta, China.

Ecosystem service flows are a research topic of significant interest, and exploring this topic may mitigate the shortcomings related to the spatial mismatches between supply and demand in the current ecosystem services studies. The Pearl River Delta (PRD) experiences a serious spatial mismatch in ecosystem services in particular the food supply, between the supply areas (hilly areas) and demand areas (central areas). Therefore, this study focused on the PRD as a case study to analyze change trends of food supply-demand ratio (FSDR) at city level, and depict the spatial flow path within and between cities from the perspective of ecosystem service flow with different threshold distance, using an enhanced two-step floating catchment area accessibility method. The results showed that the food demand significantly exceeded the supply, the budget was 3.58 million tons and FSDR was 0.49 in 2015. There were large discrepancies in the FSDR at the city level before and after when considering the ecosystem service flows. The FSDR of cities in the central areas increased 0.1%-30%, due to the ecosystem service flow from the low hilly areas. As delivery distances increased, the size of food flow decreased within cities and increased among cities. This led to a significant decline in the population living in severe undersupplied areas (FSDR＜0.1) and oversupplied areas (FSDR＞1), and an increase in undersupplied areas (0.1＜FSDR＜0.9). Our findings indicate that local governments would benefit from enhancing connections between supply and demand areas to meet the food demand of big cities. This study offers a comprehensive and realistic understanding of the physical situation of ecosystem service consumption by human beings, and provides decision-making information for optimize land use allocation.