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Prolonged exposure to PM 2.5 is associated with increased mortality. However, reducing air pollution concentrations does not necessarily reduce the related burden of deaths. Here, we aim to estimate the variations in PM 2.5 -related mortality due to contributions from key factors - PM 2.5 concentration, population exposure, and healthcare levels - for 177 countries from 2000 to 2018 at the 1-km grid scale according to the Global Mortality Exposure Model (GEMM) model. We find that global reductions in PM 2.5 -related deaths mainly come from high and upper-middle income countries, where lowered air pollutant concentration and better healthcare can offset mortality burdens caused by increasing exposed populations. Changes in population exposure to PM 2.5 contribute the most (54 %) to change in global related deaths over the examined period, followed by changes in healthcare (-42 %) and pollution concentrations (4 %). The impacts vary across countries and regions within them due to other drivers, which are significantly influenced by development status. Policies aiming at reducing PM 2.5 associated health risks need to account for country-specific balances of these key socioeconomic drivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Many cities across the world face the challenge of severe fine particulate matter (PM 2.5 ) pollution. Among the many factors that affect PM 2.5 pollution, there is an increasing interest in the impacts of urban structure. However, quantifying these impacts in China has been difficult due to differences of study area and scale in existing research, as well as limited sample sizes. Here, we conducted a continental study focusing on 301 prefectural cities in mainland China to investigate the effects of urban structure, including urban size and urban compactness, on PM 2.5 concentrations. Based on PM 2.5 raster and land cover data, we used quantile regression and a general multilinear model to estimate the effects and relative contributions of urban size and urban compactness on urban PM 2.5 pollution, with explicit consideration for pollution level, urban size and geographical location. We found: (1) nationwide, the larger and more compact that cities were, the heavier the PM 2.5 pollution tended to be. Additionally, this relationship became stronger with increasing levels of pollution. (2) In general, urban size played a more important role than urban form, and there were no significant interactive effects between the two metrics on urban PM 2.5 concentrations at the national scale. (3) The impacts of urban size and form varied by city size and geographical location. The impacts of urban size were only significant for small or medium-large cities but not for large cities. Among large cities, only urban form had a significantly positive effect on urban PM 2.5 concentrations. The further north and west that cities were, the more dependent PM 2.5 pollution was on urban form, whereas the further south and east that cities were, the greater the impact of urban size. These results provide insights into how urban design and planning can be used to alleviate air pollution., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Ozone pollution has become a major environmental concern in China, especially in mega cities with intensified human activities, which can impact air quality and human health. This study explores the different characteristics of ozone and ozone weekend effect (OWE) in different seasons in places (e.g. urban center, inner urban areas, suburban areas and natural background areas) with different degree of urbanization and intensity of human activities and the effect of urbanization on ozone at different scales in Beijing. The annual daily average ozone concentration in Beijing was 56μg/m3, with the maximum of 98.0 μg/m3 occurred in summer and the minimum of 27 μg/m3 in winter. Spatially, annual daily average ozone concentration increased along the urban-rural gradient. The annual ozone concentration was 6% higher at weekend than that on weekdays. Seasonally, the ozone concentration on weekend was 18% higher than that on workdays in summer, 4% in autumn, and 10% in winter, but was 10% lower in spring, indicating that the ozone production regime in different seasons could be different. Influence of urbanization on OWE varied by scale. At the city scale, OWE was more pronounced in urban centers than suburban areas, but at the local scale, OWE tended to decrease with the increase degree of urbanization. Image 1 • Ozone concentration increased along the urban-rural gradient in Beijing. • The influence of urbanization on ozone weekend effect had scale effect. • The ozone production regime in different seasons could be different. [ABSTRACT FROM AUTHOR]

Many cities across the world face the challenge of severe fine particulate matter (PM 2.5) pollution. Among the many factors that affect PM 2.5 pollution, there is an increasing interest in the impacts of urban structure. However, quantifying these impacts in China has been difficult due to differences of study area and scale in existing research, as well as limited sample sizes. Here, we conducted a continental study focusing on 301 prefectural cities in mainland China to investigate the effects of urban structure, including urban size and urban compactness, on PM 2.5 concentrations. Based on PM 2.5 raster and land cover data, we used quantile regression and a general multilinear model to estimate the effects and relative contributions of urban size and urban compactness on urban PM 2.5 pollution, with explicit consideration for pollution level, urban size and geographical location. We found: (1) nationwide, the larger and more compact that cities were, the heavier the PM 2.5 pollution tended to be. Additionally, this relationship became stronger with increasing levels of pollution. (2) In general, urban size played a more important role than urban form, and there were no significant interactive effects between the two metrics on urban PM 2.5 concentrations at the national scale. (3) The impacts of urban size and form varied by city size and geographical location. The impacts of urban size were only significant for small or medium-large cities but not for large cities. Among large cities, only urban form had a significantly positive effect on urban PM 2.5 concentrations. The further north and west that cities were, the more dependent PM 2.5 pollution was on urban form, whereas the further south and east that cities were, the greater the impact of urban size. These results provide insights into how urban design and planning can be used to alleviate air pollution. [Display omitted] • The larger, more compact cities tend to have heavier PM 2.5 pollution in China. • Urban size played more important role than urban form on PM 2.5 pollution. • The effects of urban structure metrics on PM 2.5 varied by urban sizes and locations. [ABSTRACT FROM AUTHOR]

Cities in developing countries worldwide are facing severe fine particulate matter (PM 2.5) pollution. Numerous studies have been conducted to investigate how biophysical and socioeconomic factors affect PM 2.5 concentration. However, most of these studies have typically focused on biophysical and socioeconomic factors separately rather than taking an integrated social-ecological perspective. Cities are widely recognized social-ecological systems, and such an integrative perspective is crucially important for understanding the generation and mitigation of PM 2.5 pollutants. In this study, by considering socioeconomic, biophysical, and meteorological factors simultaneously, we took a comprehensive social-ecological perspective to assess the impacts of these factors on PM 2.5 concentrations. Correlation analysis and variance partitioning were used to quantify the impacts and relative importance of the factors. The analysis was conducted across mainland China focusing on 88 major cities based on socio-economic data, monitoring data of air quality and meteorological conditions, and land cover data. The statistical analysis results revealed that: (1) The biophysical structure and socio-economic factors significantly affect urban PM 2.5 levels year round, but the impacts of meteorological factors are significant only in winter. The biophysical structure factors and the socio-economic ones contribute equally to the variations in PM 2.5 concentration. (2) The effects of the factors vary by region. In northern China, the socio-economic factors together with meteorological factors contribute the most to the variation of PM 2.5 concentration. In southern China, however, the unique effect of meteorological factors is dominant in affecting the level of PM 2.5. (3) Air temperature has a positive relationship with the concentration of PM 2.5 in northern China, but a negative relationship in southern China, which might indicate the varied dominant precursors of PM 2.5 between the two regions. This study extends our understanding of the effects of social-ecological factors on urban PM 2.5 pollution and underscores the importance of differentiated strategies for air pollution mitigation in different regions, and in different seasons, which provides a scientific basis for sustainable development from the perspective of urban air pollution mitigation. [Display omitted] • Biophysical structure, socioeconomic and meteorological factors all affected PM 2.5 • In northern China, Social economy and meteorology together affected PM 2.5 • In southern China, the meteorological factors dominated the variation of PM 2.5 • Temperature had contradictory effects on PM 2.5 between Northern and Southern China. [ABSTRACT FROM AUTHOR]