Changes in Long-Term PM2.5 Pollution in the Urban and Suburban Areas of China’s Three Largest Urban Agglomerations from 2000 to 2020

Incentivizing emission controls toward clean air and carbon neutrality in China: Perspectives from a risk-based approach for air quality management

Air Quality Standards (AQSs) worldwide have continued to employ concentration-based approaches since their first implementation under the 1970 Clean Air Act in the United States. The primary objective of establishing these AQSs is widely recognized as protecting public health. With the significantly improved understanding of the health risks associated with air pollutants today, it is an opportune time to reassess air pollution management from a fundamental risk perspective. This study applied a risk-based AQS system to assess the overall mortality risks associated with both long- and short-term exposure to air pollution in China between 2015 and 2022. The analyses revealed that the health benefits resulting from reductions in concentrations of non-ozone (O3) pollutants exceeded the health risks associated with increasing O3 concentrations. As a result, the overall mortality risk across China showed a significant descending trend. During the initial phase of decarbonization, emission reductions may unintentionally lead to increased O3 concentrations in China due to the non-linear response of O3 to its precursors. Nevertheless, the overall health benefits derived from emission controls incentivize governments to implement stringent measures toward achieving carbon neutrality. These findings highlight the substantial benefits of applying the risk-based AQS system for synergistic health and carbon management.

Synergistic PM2.5 and O3 control to address the emerging global PM2.5-O3 compound pollution challenges

In recent years, the issue of PM2.5-O3 compound pollution has become a significant global environmental concern. This study examines the spatial and temporal patterns of global PM2.5-O3 compound pollution and exposure risks, firstly at the global and urban scale, using spatial statistical regression, exposure risk assessment, and trend analyses based on the datasets of daily PM2.5 and surface O3 concentrations monitored in 120 cities around the world from 2019 to 2022. Additionally, on the basis of the common emission sources, spatial heterogeneity, interacting chemical mechanisms, and synergistic exposure risk levels between PM2.5 and O3 pollution, we proposed a synergistic PM2.5-O3 control framework for the joint control of PM2.5 and O3. The results indicated that: (1) Nearly 50% of cities worldwide were affected by PM2.5-O3 compound pollution, with China, South Korea, Japan, and India being the global hotspots for PM2.5-O3 compound pollution; (2) Cities with PM2.5-O3 compound pollution have exposure risk levels dominated by ST + ST (Stabilization) and ST + HR (High Risk). Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries, with unequal exposure characteristics; (3) The selected cities showed significant positive spatial correlations between PM2.5 and O3 concentrations, which were consistent with the spatial distribution of the precursors NOx and VOCs; (4) During the study period, 52.5% of cities worldwide achieved synergistic reductions in annual average PM2.5 and O3 concentrations. The average PM2.5 concentration in these cities decreased by 13.97%, while the average O3 concentration decreased by 19.18%. This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low-carbon transition.

Long-term variations of air pollutants and public exposure in China during 2000-2020

Since 2000, China has faced severe air pollution challenges，prompting the initiation of comprehensive emission control measures post-2013. The subsequent implementation of these measures has led to remarkable enhancements in air quality. This study aims to enhance our understanding of the long-term trends in fine particulate matter (PM2.5) and gaseous pollutants of ozone (O3) and nitrogen dioxide (NO2) across China from 2000 to 2020. Utilizing the Community Multiscale Air Quality (CMAQ) model, we conducted a nationwide analysis of air quality, systematically quantifying model predictions against observations for pollutants. The CMAQ model effectively captured the trends of air pollutants, meeting recommended performance benchmarks. The findings reveal variations in pollutant concentrations, with initial increases in PM2.5 followed by a decline after 2013. The proportion of the population living in high PM2.5 concentrations (>75 μg/m3) decreased to <5 % after 2015. However, during the period from 2017 to 2020, around 40 % of the population continued to live in regions that did not meet the criteria for Chinese air quality standards (35 μg/m3). From 2000 to 2019, fewer than 20 % of the population met the WHO standard (100 μg/m3) for MDA8 O3. In 2000, 77 % of the population met the NO2 standard (<20 μg/m3), a figure that declined to 60 % between 2005 and 2014, nearly reaching 70 % in 2020. This study offers a comprehensive analysis of the changes in pollutants and public exposure in 2000-2020. It serves as a foundational resource for future efforts in air pollution control and health research.

Fine simulation of PM2.5 combined with NPP-VIIRS night light remote sensing and mobile monitoring data

Human activity plays a crucial role in influencing PM2.5 concentration and can be assessed through nighttime light remote sensing. Therefore, it is important to investigate whether the nighttime light brightness can enhance the accuracy of PM2.5 simulation in different stages. Utilizing PM2.5 mobile monitoring data, this study introduces nighttime lighting brightness as an additional factor in the PM2.5 simulation model across various time periods. It compares the differences in simulation accuracy, explores the impact of nocturnal human activities on PM2.5 concentrations at different periods of the following day, and analyzes the spatial and temporal pollution pattern of PM2.5 in urban functional areas. The results show that (1) the incorporation of nighttime lighting brightness effectively enhances the model's accuracy (R2), with an improvement ranging from 0.04 to 0.12 for different periods ranges. (2) the model's accuracy improves more prominently during 8:00-12:00 on the following day, and less so during 12:00-18:00, as the PM2.5 from human activities during the night experiences a strong aggregation effect in the morning of the next day, with the effect on PM2.5 concentration declining after diffusion until the afternoon. (3) PM2.5 is primarily concentrated in urban functional areas including construction sites, roads, and industrial areas during each period. But in the period of 8:00-12:00, there is a significant level of PM2.5 pollution observed in commercial and residential areas, due to the human activities that occurred the previous night.

Examination of air pollutants and their risk for human health in urban and suburban environments for two Romanian cities: Brasov and Iasi

To detect the spatial differences of atmospheric pollutants in urban and suburban areas is important for observing their aspects on regional air quality, climate, and human health. This study is focused on the evolution of PM2.5, PM10, NOx and SO2, concentrations, and meteorological parameters from 2010 to 2022, at urban and suburban area in the two Romanian city: Brasov and Iasi. The daily patterns of most pollutants in urban and suburban areas, are strongly linked to land-traffic emissions. The seasonal differences were observation of the studied air pollutants displays visible decreasing in warm period and increased concentrations in cold period. Significant higher (25%- Brasov, 28%- Iasi) PM10 were found in urban area concentration probably caused by enhanced vehicular emissions over these areas induced by urban planning and mobility policies. The average relative risk caused by PM10 for all-cause mortality in the urban region was 1.021 (±0.004) in Brasov, and significantly higher in Iasi 1.030 (±0.005). In suburban regions this risk was lower with 33 % 1.014 (±0.006) in Brasov and 30 % 1.021 (±0.003) in Iasi. The main objective of this research was to identify the difference of air pollutants and meteorological parameters in the urban and suburban region of the studied city.

Chronic and acute health effects of PM2.5 exposure and the basis of pollution control targets

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

The dynamics of cardiovascular and respiratory deaths attributed to long-term PM2.5 exposures in global megacities

Exposure to ambient fine particulate matter (PM_2.5) air pollution is a significant driver of premature deaths. We estimate the number of cardiovascular and respiratory (CR) premature deaths attributed to long-term exposure to PM_2.5 in 33 global megacities based on long-term remotely sensed observations from 2000 to 2019. Our analysis uses high-resolution (0.01 degree) PM_2.5 concentration data and cause-specific integrated exposure-response (IER) functions developed for the Global Burden of Disease Project. From 2000 to 2019, PM_2.5-related CR death rates per 1000 people increased in 6 of 33 megacities, decreased in 9, and remained constant in 18 megacities. The increase in PM_2.5-related CR mortality in 11 megacities located in South and East Asia during the period 2000-2019 can be attributed to the increases in PM_2.5 concentrations. All 33 megacities could avoid 30,248 (9 %), 62,989 (20 %), 128,457 (40 %), 198,462 (62 %) and all of the estimated 322,515 CR deaths attributed to PM_2.5 pollution in 2019 if they were to attain the World Health Organization's four interim PM_2.5 targets (IT-1, IT-2, IT-3, and IT-4) and the new air quality guideline (AQG), respectively. Major improvements in air quality are needed to reduce the number of CR deaths attributed to PM_2.5 in South and East Asia, in addition to ny reductions that would likely follow shifts in the population structures of these megacities moving forward.

Lidar- and UAV-Based Vertical Observation of Spring Ozone and Particulate Matter in Nanjing, China

The rapid urbanization in China is accompanied by increasingly serious air pollution. Particulate matter and ozone are the main air pollutants, and the study of their vertical distribution and correlation plays an important role in the synergistic air pollution control. In this study, we performed Lidar- and UAV-based observations in spring in Nanjing, China. The average concentrations of surface ozone and PM2.5 during the observation period are 87.78 µg m−3 and 43.48 µg m−3, respectively. Vertically, ozone reaches a maximum in the upper boundary layer, while the aerosol extinction coefficient decreases with height. Generally, ozone and aerosol are negatively correlated below 650 m. The correlation coefficient increases with altitude and reaches a maximum of 0.379 at 1875 m. Within the boundary layer, ozone and aerosols are negatively correlated on days with particulate pollution (PM2.5 > 35 μg m−3), while on clean days they are positively correlated. Above the boundary layer, the correlation coefficient is usually positive, regardless of the presence of particulate pollution. The UAV study compensates for Lidar detections below 500 m. We found that ozone concentration is higher in the upper layers than in the near-surface layers, and that ozone depletion is faster in the near-surface layers after sunset.