Changes In PM2 Research Articles

Impact of COVID-19 restrictions liberalization on air quality: a case study of Chongqing, Southwest China.

To mitigate the societal impact of the COVID-19 pandemic, China implemented long-term restrictive measures. The sudden liberalization at the end of 2022 disrupted residents' daily routines, making it scientifically intriguing to explore its effect on air quality. Taking Chongqing City in Southwest China as an example, we examined the impact of restriction liberalization on air quality, identified potential sources of pollutants, simulated the effects of abrupt anthropogenic control relaxation using a Random Forest Model, and applied an optimized model to predict the post-liberalization pollutant concentrations. The results showed increases in PM2.5 (72.3%), PM10 (67.7%), and NO2 (21.9%) concentrations, while O3 concentration decreased by 20.5%. Although potential pollution source areas contracted, pollution levels intensified with northeastern Sichuan, interior Chongqing, and northern Guizhou being major contributors to pollutant emissions. Anthropogenic emissions accounted for 26.7 ~ 33% changes in PM2.5 and PM10 concentrations while meteorological conditions contributed to 40.2 ~ 43.3% variations observed during the period. The optimized model demonstrated a correlation between predicted and observed values with R2 ranging from 0.70 to 0.89, enabling accurate prediction of post-liberalization pollutant concentrations. This study can enhance our understanding regarding the impact of sudden social lockdown relaxation events on air quality while providing support for urban air pollution prevention.

Health impact of policies to reduce agriculture-related air pollutants in the UK: The relative contribution of change in PM2.5 exposure and diets to morbidity and mortality

Food systems can negatively impact health outcomes through unhealthy diets and indirectly through ammonia emissions originating from agricultural production, which contribute to air pollution and consequently cardiovascular and respiratory health outcomes. In the UK, ammonia emissions from agriculture have not declined in the same way as other air pollutants in recent years. We applied a novel integrated modelling framework to assess the health impacts from six ammonia reduction scenarios to 2030: two agriculture scenarios – a “Current trends” scenario projecting current mitigation measures to reflect a low ambition future, and “High ambition mitigation” based on measures included in the Climate Change Committee's Balanced Pathway to Net Zero; three dietary scenarios – a “Business as usual” based on past trajectories, “Fiscal” applying 20% tax on meat and dairy and 20% subsidy on fruit and vegetables, and “Innovation” applying a 30% switch to plant-based alternatives; one combination of “High ambition mitigation” and “Innovation”. Compared to “Current trends”, the “High ambition mitigation” scenario would result in a reduction in premature mortality of 13,000, increase life years by 90,000 and reduce incidence of respiratory diseases by 270,000 cases over a 30 year period. Compared to Business as Usual, the dietary scenarios would reduce the number of premature deaths by 65,000 and 550,000–600,000 life years gained over 30 years, with most of the benefits gained by reducing ischemic heart disease (incidence reduction: 190,000). The “High ambition combination” would lead to 67,000 deaths averted, 536,000 incidence reductions and 650,000 life-years gained. For all scenarios, older age groups and those living in lower income households would experience the greatest benefits, because of higher underlying mortality rates or higher levels of risk factors. Our study shows that combining mitigation policies targeting agricultural production systems with diet-related policies would lead to significant reductions in emissions and improvement in health outcomes.

The Influence of Three-Dimensional Building Morphology on PM2.5 Concentrations in the Yangtze River Delta

The rapid urbanization of urban areas in China has brought about great variation in the layout of cities and serious air pollution. Recently, the focus has been directed toward understanding the role of urban morphology in the generation and spread of atmospheric pollution, particularly in PM2.5 emissions. However, there have been limited investigations into the impact of three-dimensional (3D) features on changes in PM2.5 concentrations. By analyzing a wealth of data on building structures based on a mixed linear model and variance partition analysis in the Yangtze River Delta throughout 2018, this study sought to examine the associations between PM2.5 concentrations and urban building form, and further compared the contributions of two-dimensional (2D) and 3D building features. The findings revealed that both 2D and 3D building forms played an important role in PM2.5 concentrations. Notably, the greater contribution of 3D building forms on PM2.5 concentrations was observed, especially during the summer, where they accounted for 20% compared to 7% for 2D forms. In particular, the building height range emerged as a crucial local factor affecting PM2.5 concentrations, contributing up to 12%. Moreover, taller buildings with more variability in height were found to aid in the dispersion of pollution. These results underscore the substantial contribution of 3D building morphology to PM2.5 pollution, contrasting with previous studies. Furthermore, compact buildings were linked to lower pollution levels, and an urban landscape characterized by polycentric urban structures and lower fragmentation was deemed more favorable for sustainable urban development. This study is significant in investigating the contribution of 3D morphology to PM2.5 and its importance for pollution dispersion mechanisms. It suggests the adoption of a polycentric urban form with a broader range of building heights in urban planning for local governments in the Yangtze River Delta.

Changes in PM2.5 toxicity in three large US cities during 2005-2019

Changes in PM2.5 toxicity in three large US cities during 2005-2019

Reduction in polycyclic aromatic hydrocarbon exposure in Beijing following China’s clean air actions

Exposure to polycyclic aromatic hydrocarbons (PAHs) in the Chinese population was among the highest globally and associated with various adverse effects. This study examines the impact of China’s two-phase clean air initiatives, namely the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013–2017 and the Blue-Sky Defense War (BSDW) in 2018–2020, on PAH levels and human exposures in Beijing. To evaluate the effects of APPCAP, we measured 16 PAHs in 287 PM2.5 samples collected in Beijing and 9 PAH metabolites in 358 urine samples obtained from 54 individuals who traveled from Los Angeles to Beijing between 2014 and 2018. The concentration of PM2.5-bound benzo[a]pyrene equivalents (BaPeq) decreased by 88.5% in 2014–2018 due to reduced traffic, coal, and biomass emissions. PAH metabolite concentrations in travelers’ urine decreased by 52.3% in Beijing, correlated with changes in PM2.5 and NO2 levels. In contrast, no significant changes were observed in Los Angeles. To evaluate BSDW’s effects, we collected 123 additional PM2.5 samples for PAH measurements in 2019–2021. We observed sustained reductions in BaPeq concentrations attributable to reductions in coal and biomass emissions during the BSDW phase, but those from traffic sources remained unchanged. After accounting for meteorological factors, China’s two-phase clean air initiatives jointly reduced Beijing’s PM2.5-bound BaPeq concentrations by 96.6% from 2014 to 2021. These findings provide compelling evidence for the effectiveness of China’s clean air actions in mitigating population exposure to PAHs in Beijing.

Spatial and temporal variation of PM2.5 and the influence of vegetation in the Yangtze River Delta region

With rapid urbanisation in China, PM2.5 has become a limiting factor for the sustainable development of cities. Taking the Yangtze River Delta as the experimental area, this study analysed the spatial and temporal changes of PM2.5 concentrations from 2001 to 2020. It also examined the variations, dispersion, and correlation with NDVI of PM2.5 concentrations in different vegetation zones at different temporal and spatial scales. The results showed that: (1) The PM2.5 concentration in the Yangtze River Delta showed an overall decreasing trend during 2001–2020, and the change was divided into two phases, starting with an increasing phase and entering a decreasing phase after 2013. (2) In terms of spatial distribution, PM2.5 concentrations in the Yangtze River Delta show a pattern of low in the south and high in the north, with the spatial focus shifting to the north over time. There is a concentration of high levels of particulate matter in the Hefei-Nanjing-Wuxi area. (3) The effect of natural vegetation on the reduction and stabilization of atmospheric particulate matter concentration is better than that of artificial vegetation. (4) Needleleaf forests, broadleaf forests, and shrubs in natural vegetation are more capable of reducing and stabilizing atmospheric particulate matter than grasses. The study can provide a reference for regional air pollution control and regional plant system construction.

DNN model reveals sharp decline in PM2.5 concentration in the Yangtze River Delta during COVID-19 lockdown and lift lockdown

The COVID-19 lockdown in early 2020 and subsequent lifting in late 2022 had a significant impact on air pollution levels in the Yangtze River Delta (YRD). Previous studies have not provided a clear understanding of the detailed spatiotemporal characteristics of PM2.5 concentrations in various functional areas of cities during different periods before and after the outbreak of the epidemic. However, by employing a deep neural network (DNN) model and integrating satellite data, meteorological reanalysis, and PM2.5 observations, established an estimation of high-resolution PM2.5 distribution during the period from 2019 to 2022. The DNN model performed well (R2 = 0.78). During the lockdown, PM2.5 concentrations in 14 YRD cities were over 50% lower than in previous years. Interestingly, even after the lockdown was lifted, PM2.5 levels remained relatively low due to reduced human activities caused by widespread infections. Found that PM2.5 reductions varied across different intra-city functional regions during both the lockdown and lift lockdown periods. Overall, the changes in PM2.5 levels during the 2022 lift lockdown were smaller than during the 2020 lockdown. These findings emphasize the need for tailored government policies to address COVID-19's impact on air pollution, considering diverse functional areas within the region.

Moderating effect of a sodium-rich diet on the association between long-term exposure to fine particulate matter and blood lipids in children and adolescents

BackgroundSeveral studies reported that exposure to higher levels of fine particulate matter (PM2.5) was associated with deteriorated lipid profiles in children and adolescents. However, whether a sodium-rich diet could modify the associations remains unknown. We aimed to examine the associations of long-term exposure to PM2.5 with blood lipids in children and adolescents, and further examine the effect modification by dietary and urinary sodium levels based on a multi-community population in China.MethodsThe 3711 study participants were from a cross-sectional study, which interviewed children and adolescents aged 6 to 17 years across Sichuan Province, China between 2015 and 2017. Blood lipid outcomes including blood total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were assessed. Information on daily dietary sodium consumption was estimated with a semi-quantitative food frequency questionnaire (FFQ), and urinary sodium was used as an internal exposure biomarker. A linear regression model was applied to estimate the associations of prior 2-years’ average exposure to ambient PM2.5 with blood lipids. The effect modification by dietary and urinary sodium was examined by stratified analyses.ResultsThe participants from rural areas had higher levels of daily sodium consumptions. The results of multivariable regression analysis indicated that per 10 μg/m3 incremental change in PM2.5 was associated with a 1.56% (95% confidence interval 0.90%—2.23%) and a 2.26% (1.15%—3.38%) higher blood TC and LDL-C levels, respectively. Among the study participants with higher levels of dietary sodium or urinary sodium, exposure to higher levels of PM2.5 was significantly associated with deteriorated lipid profiles. For example, each 10 μg/m3 incremental change in exposure to PM2.5 was correlated with a 2.83 (-4.65 to -0.97) lower percentage decrease in blood HDL-C levels among the participants who were from the highest quartile of urinary sodium levels. While, these associations changed to be nonsignificant in the participants who were from the lowest quartile of dietary sodium levels.ConclusionExposure to higher levels of PM2.5 was associated with deteriorated blood lipid levels in children and adolescents. It is noteworthy that these associations might be ameliorated through the adoption of a low-sodium dietary regimen.

Responses of fine particulate matter (PM2.5) air quality to future climate, land use, and emission changes: Insights from modeling across shared socioeconomic pathways

Air pollution induced by fine particulate matter with diameter ≤ 2.5 μm (PM2.5) poses a significant challenge for global air quality management. Understanding how factors such as climate change, land use and land cover change (LULCC), and changing emissions interact to impact PM2.5 remains limited. To address this gap, we employed the Community Earth System Model and examined both the individual and combined effects of these factors on global surface PM2.5 in 2010 and projected scenarios for 2050 under different Shared Socioeconomic Pathways (SSPs). Our results reveal biomass-burning and anthropogenic emissions as the primary drivers of surface PM2.5 across all SSPs. Less polluted regions like the US and Europe are expected to experience substantial PM2.5 reduction in all future scenarios, reaching up to ~5 μg m−3 (70 %) in SSP1. However, heavily polluted regions like India and China may experience varied outcomes, with a potential decrease in SSP1 and increase under SSP3. Eastern China witness ~20 % rise in PM2.5 under SSP3, while northern India may experience ~70 % increase under same scenario. Depending on the region, climate change alone is expected to change PM2.5 up to ±5 μg m−3, while the influence of LULCC appears even weaker. The modest changes in PM2.5 attributable to LULCC and climate change are associated with aerosol chemistry and meteorological effects, including biogenic volatile organic compound emissions, SO2 oxidation, and NH4NO3 formation. Despite their comparatively minor role, LULCC and climate change can still significantly shape future air quality in specific regions, potentially counteracting the benefits of emission control initiatives. This study underscores the pivotal role of changes in anthropogenic emissions in shaping future PM2.5 across all SSP scenarios. Thus, addressing all contributing factors, with a primary focus on reducing anthropogenic emissions, is crucial for achieving sustainable reduction in surface PM2.5 levels and meeting sustainable pollution mitigation goals.

Effects of " Air Pollution Prevention and Control Action Plan " on PM2.5 and Chemical Compositions in Zhengzhou in Polluted Winters

The Air Pollution Prevention and Control Action Plan （APPCAP） was promulgated in China in 2013. To explore the effectiveness of APPCAP on PM2.5 in winter in Zhengzhou, PM2.5 samples were collected in Zhengzhou Monitoring Center during December 2013 and December 2018. The chemical composition of PM2.5 was analyzed, including EC, OC, water soluble ions, and metal elements. Pollution episodes under different stages were selected to investigate the changes in PM2.5 concentration and composition. The results showed that： ① The average concentration of PM2.5 in winter in Zhengzhou decreased from （215.38 ±107.28） μg·m-3 in 2013 to （77.45 ±49.81） μg·m-3 in 2018, with a decrease rate of 64%. ② The concentrations of EC, K+, SO42-, and Cl- decreased by 85%, 80%, 78%, and 72%, respectively, and the decrease rate in OC, NH4+, and NO3- was 50%, 41%, and 32%, respectively. ③ Compared with those in winter of 2013, the ratios of OC/EC in winter of 2018 increased by 2.6 times, and the proportion of secondary organic carbon in OC increased to 57%； meanwhile, values of sulfur oxidation rate and nitrogen oxidation rate increased by 1.5 and 1.0 times, respectively, indicating heavy secondary pollution in Zhengzhou. ④ The mass ratios of NO3-/SO42-increased from 0.8 ±0.2 in 2013 to 2.5 ±1.0 in 2018, indicating that the contribution of mobile sources increased and surpassed fixed sources as the main source in Zhengzhou. ⑤The comparison results of different stages of the heavy pollution process showed that ρ（PM2.5） decreased significantly in 2018 compared with that in 2013, with the peak concentration decreasing by 61%. The main chemical composition changed from OC, NO3-, SO42-, and NH4+ to OC, NO3-, and NH4+. The results indicated that the primary emission source control in Zhengzhou had achieved remarkable effects, but the contribution of secondary generation to PM2.5 showed an elevated trend； thus, the influence of secondary generation requires further attention in the future.

The joint impact of PM2.5, O3, and CO2 on the East Asian Summer Monsoon in 2013 and 2018 due to contrasting emission reduction

With the rapid urbanization and the implementation of a series of air pollution control measures, significant changes have occurred in the emission of fine particulate matter (PM2.5), ozone (O3) precursors, and CO2 in China. In this study, we comprehensively assess the impact of emission variations on the East Asian Summer Monsoon (EASM) climate from 2008 to 2018 using a regional-chemistry-ecology model RegCM-Chem-YIBs. The investigations indicated a strengthening of the EASM from 2008 to 2018, with all four EASM Indices exhibiting an increase trend ranging from 0.08 to 1.09 per year based on the simulations. Since 2008, alterations in the emissions of PM2.5 and O3 precursors in 2013 and 2018 led to a rise in near-surface temperatures in China by 0.5–1.5 K, thereby enhancing the EASM. Conversely, the changed CO2 emissions, through its influence on radiative balance and altering BVOCs (Biogenic Volatile Organic Compounds) emissions via its effect on vegetation growth, decreased temperatures by 0.5–1.5 K, thus weakening the EASM. However, when considering the combined effects of total emissions changes in PM2.5, O3 precursors, and CO2, surface temperatures increased by 0.5–2 K, ultimately strengthening the EASM. In addition, compared to 2013, EASM was strongly enhanced in 2018 due to the notable increase in CO2 and significant reduction of PM2.5 and O3 precursors. Our study underscores the significant influence of variations in PM2.5, O3 precursors, and CO2 emissions on EASM climate and emphasizes the importance of coordinated governance of air pollution and climate change.

Impact of electric and clean-fuel vehicles on future PM2.5 and ozone pollution over Delhi

We investigate the impact of adoption of electric vehicles and cleaner fuels on future surface levels of PM2.5 and ozone over Delhi for two contrasting seasons, pre-monsoon and post-monsoon. We run the WRF-Chem atmospheric transport model at high resolution (4 km) with two transport emission scenarios for year 2030: (1) a scenario with electrification of two- and three-wheelers and light commercial vehicles, and (2) a scenario which also includes conversion of diesel vehicles to compressed natural gas (CNG). Compared to the baseline values in 2019, the scenario with both electrification and conversion of diesel vehicles to CNG has a greater reduction in PM2.5 concentrations (up to 5%) than the electrification of two- and three-wheelers and light commercial vehicles alone (within 1%), mainly due to the the greater reduction in primary emissions of PM2.5 and black carbon from diesel conversion to CNG. Vehicles electrification could result in an increase in the daily maximum 8-hours ozone concentrations, which are partially offset by additionally converting to CNG—by −1.9% and +2.4% during pre-monsoon and post-monsoon seasons. This reflects higher NOx emissions from the CNG vehicle scenario compared to electrification-alone scenario, which limits the increase of surface ozone in the VOC-limited chemical environment over Delhi. Our findings highlight the importance of a coordinated strategy for PM2.5 and ozone when considering traffic emission controls, and highlight that the transition to electric vehicles should be accompanied by the conversion of diesel vehicles to CNG to limit surface ozone increase and achieve greater reduction in PM2.5 concentrations over Delhi. However, the small changes in PM2.5 and in ozone compared to the baseline scenario highlight the importance of joint emissions reduction from other sectors to achieve substantial progress in PM2.5 and ozone air quality in Delhi.

Quantifying the effect of driving restrictions on fine particulate matter concentrations with WRF-Chem model: A case study in Kaifeng, China

One of the significant sources of urban air particulate matter (PM2.5 and PM10) has been found to be vehicle exhaust emission. Vehicle restriction measures have been taken to alleviate particulate matter pollution in the world. Here, we quantified the impact of vehicle restriction measures on the PM2.5 concentrations using the Weather Research and Forecasting model with Chemistry (WRF-Chem) in Kaifeng, China. This study set up three different scenarios to simulate the spatiotemporal changes of PM2.5 concentrations in four seasons in 2020. They were no emission reduction (S0), the restriction of two tailing license plate numbers (S1), and the restriction of odd–even tailing numbers of license plates (S2), respectively. In general, the odd–even license plate restriction policy has proven to be more effective than restricting two specific license plate numbers. In scenario S1, the range of PM2.5 concentrations reduction in Kaifeng City was between 0.2% and 1.28%. In scenario S2, the range of PM2.5 concentrations reduction was between 0.98% and 14.42%. The results showed that the effectiveness of vehicle restriction measures varies from season to season, and the effect in summer and winter is better than that in spring and autumn. We suggest that it may be difficult to reduce the PM2.5 concentrations to a great extent if simply reducing the traffic exhaust emissions through motor vehicle restrictions, on the contrary, would lead to the increase of O3 concentration, bringing some other effects. This study can serve as a foundation for the rational development of motor vehicle control strategies and help advance the ongoing improvement of air quality.

Varying Drivers of 2013–2017 Trends in PM2.5 Pollution over Different Regions in China

A significant decrease in surface PM2.5 concentrations has been reported since the implementation of the Air Pollution Prevention and Control Action Plan in 2013. In this study, we use the GEOS-Chem model to simulate the trend in surface PM2.5 pollution in China from 2013 to 2017, as well as the relative contributions of emission reduction and meteorology. The simulated decline rate averaged over monitoring sites in China is around −4.7 μg m−3 yr−1 in comparison with the value of −6.4 μg m−3 yr−1 from observations. The model also captures the variations over different regions, with r in the range of 0.85–0.95. Based on the sensitivity tests against emissions and meteorology, the study finds that the decline in PM2.5 concentrations is mainly driven by the reduction in anthropogenic emissions. The variation in open biomass burning (OBB) is not significant, except in Northeast China (NEC) and Pearl River Delta (PRD), where the changes originated from OBB are 40% and 30% of those associated with anthropogenic emission reductions. Changes in meteorology from 2013 to 2017 led to significant increases in PM2.5 concentrations in most areas in China, except in NEC. The increase attributed to meteorology, to a large extent, could be explained by the significant decrease in surface wind speed (WS) and planetary boundary layer height (PBLH) between 2013 and 2017, combined with their negative correlation with PM2.5. The decrease in PM2.5 concentrations in NEC, on the other hand, could be explained by the significant decrease in relative humidity (RH) there combined with the positive correlation of RH with PM2.5, while the changes in WS and PBLH there are relatively small compared with other areas. The change in meteorology, therefore, hinders the improvement of air quality via emission controls in most of China. In Sichuan Basin (SCB), the increase due to meteorology almost compensates for the decrease associated with emission reduction, leading to the least change in PM2.5 concentrations, although the decrease due to emission controls is the largest compared with other areas.

Time series analysis of PM2.5 pollution risk based on the supply and demand of PM2.5 removal service: a case study of the urban areas of Beijing.

Demonstrating the temporal changes in PM2.5 pollution risk in regions facing serious PM2.5 pollution problems can provide scientific evidence for the air pollution control of the region. However, research on the variation of PM2.5 pollution risk on a fine temporal scale is very limited. Therefore, we developed a method for quantitative characterizing PM2.5 pollution risk based on the supply and demand of PM2.5 removal services, analyzed the time series characteristics of PM2.5 pollution risk, and explored the reasons for the temporal changes using the urban areas of Beijing as the case study area. The results show that the PM2.5 pollution risk in the urban areas of Beijing was close between 2008 and 2012, decreased by approximately 16.3% in 2016 compared to 2012, and further decreased by approximately 13.2% in 2021 compared to 2016. The temporal variation pattern of the PM2.5 pollution risk in 2016 and 2021 showed significant differences, including an increase in the number of risk-free days, a decrease in the number of heavily polluted days, and an increase in the stability of the risk day sequence. The significant reduction in risk level was mainly attributed to Beijing's air pollution control measures, supplemented by the impact of COVID-19 control measures in 2021. The results of PM2.5 pollution risk decomposition indicate that compared to the previous 2years, the stability and predictability of the risk variation in 2016 increased, but the overall characteristics of high risk from November to February and low risk from April to September did not change. The high risk from November to February was mainly due to the demand for coal heating during this period, a decrease in PM2.5 removal service supply caused by plant leaf fall, and the common occurrence of temperature inversions in winter, which hinders the diffusion of air pollutants. This study provides a method for the analysis of PM2.5 pollution risk on fine temporal scales and may provide a reference for the PM2.5 pollution control in the urban areas of Beijing.

Using the Multicomponent Aerosol FORmation Model (MAFOR) to Determine Improved VOC Emission Factors in Ship Plumes.

International shipping's particulate matter primary emissions have a share in global anthropogenic emissions of between 3% and 4%. Ship emissions of volatile organic compounds (VOCs) can play an important role in the formation of fine particulate matter. Using an aerosol box model for the near-plume scale, this study investigated how the changing VOC emission factor (EF) for ship engines impacts the formation of secondary PM2.5 in ship exhaust plumes that were detected during a measurement campaign. The agreement between measured and modeled particle number size distribution was improved by adjusting VOC emissions, in particular of intermediate-, low-, and extremely low-volatility compounds. The scaling of the VOC emission factor showed that the initial emission factor, based on literature data, had to be multiplied by 3.6 for all VOCs. Information obtained from the box model was integrated into a regional-scale chemistry transport model (CTM) to study the influence of changed VOC ship emissions over the Mediterranean Sea. The regional-scale CTM run with adjusted ship emissions indicated a change in PM2.5 of up to 5% at the main shipping routes and harbor cities in summer. Nevertheless, overall changes due to a change in the VOC EF were rather small, indicating that the size of grid cells in CTMs leads to a fast dilution.

Long-term exposure to ambient fine particulate matter (PM2.5) and attributable pulmonary tuberculosis notifications in Ningxia Hui Autonomous Region, China: a health impact assessment

IntroductionLong-term exposure to fine particulate matter (≤2.5 µm (PM2.5)) has been associated with pulmonary tuberculosis (TB) notifications or incidence in recent publications. Studies quantifying the relative contribution of long-term PM2.5...

Changes of PM2.5 and O3 and their impact on human health in the Guangdong-Hong Kong-Macao Greater Bay Area.

In recent years, the combined pollution of PM2.5 and O3 in China, particularly in economically developed regions such as the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), has garnered significant attention due to its potential implications. This study systematically investigated the changes of PM2.5 and O3 and their associated human health effects in the GBA, utilizing observational data spanning from 2015 to 2019. The findings revealed a spatial trend indicating a gradual decrease in PM2.5 levels from the northwest to the southeast, while the spatial distribution of MDA8 O3 demonstrated an opposing pattern to that of PM2.5. The monthly fluctuations of PM2.5 and MDA8 O3 exhibited V-shaped and M-shaped patterns, respectively. Higher MDA8 O3 concentrations were observed in autumn, followed by summer and spring. Over the five-year period, PM2.5 concentrations exhibited a general decline, with an annual reduction rate of 1.7μgm-3/year, while MDA8 O3 concentrations displayed an annual increase of 3.2μgm-3. Among the GBA regions, Macao, Foshan, Guangzhou, and Jiangmen demonstrated notable decreases in PM2.5, whereas Jiangmen, Zhongshan, and Guangzhou experienced substantial increases in MDA8 O3 levels. Long-term exposure to PM2.5 in 2019 was associated with 21,113 (95% CI 4968-31,048) all-cause deaths (AD), 1333 (95% CI 762-1714) cardiovascular deaths (CD), and 1424 (95% CI 0-2848) respiratory deaths (RD), respectively, reflecting declines of 27.6%, 28.0%, and 28.4%, respectively, compared to 2015. Conversely, in 2019, estimated AD, CD, and RD attributable to O3 were 16,286 (95% CI 8143-32,572), 7321 (95% CI 2440-14,155), and 6314 (95% CI 0-13,576), respectively, representing increases of 45.9%, 46.2%, and 44.2% over 2015, respectively. Taken together, these findings underscored a shifting focus in air pollution control in the GBA, emphasizing the imperative for coordinated control strategies targeting both PM2.5 and O3.

A panel study of exposure to fine particulate matter and modeled respiratory deposition on biomarkers of inflammation, blood coagulation, and oxidative stress in healthy young adults in Hefei, China

Evidence is scarce on the acute cardiovascular health effects of fine particulate matter (PM2.5) and its respiratory tract depositions. We performed a panel study in Hefei, China to explore the relations of PM2.5 and its depositions in 3 respiratory tract regions over different lag times with a range of cardiovascular biomarkers among 40 college students and the potential mediating effects of inflammation. We found significant effects of PM2.5 exposure on the alterations of biomarkers at specific lag days, in a concentration-response manner, even at PM2.5 level below Chinese Ambient Air Quality Standard (CAAQS) Grade I (35 μg/m3). For example, per 10 μg/m3 increase in PM2.5 concentration was associated with −9.33% increase in ADAMTS13 on lag 0-1d. The corresponding increases in D-Dimer, GM-CSF, and MCP-1 for the same change in PM2.5 concentration on lag 5-6d were 30.51%, 11.43%, and 20.05%. Besides, tracheobronchial region (TB) deposition presented more evident effects on these biomarkers than that in PM2.5. Additionally, we observed greater associations of PM2.5-biomarkers among females, those with abnormal body mass index (BMI), and those with physical activity. The results indicated that short-term PM2.5 exposure and its respiratory tract depositions were concentration-responsive associated with damaged cardiovascular health via inducing blood coagulation, oxidative stress and inflammation among healthy young adults even at concentration below CAAQS Grade I. Elevated serum levels of systemic inflammation may be partly responsible for the effects of PM2.5 and its respiratory tract depositions on coagulation function.

Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM2.5 exposure and cardiovascular emergency department visits in Missouri

IntroductionAmbient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures...