Fine Particulate Matter Research Articles

Association of Ambient Air Pollution Exposure With Incident Glaucoma: 12-Year Evidence From the UK Biobank Cohort.

Glaucoma is the leading cause of irreversible blindness worldwide. Despite growing concerns about air quality and its impact on ocular health, there remains a knowledge gap regarding the long-term association between air pollution and glaucoma risk. This study investigates the relationship between exposure to ambient air pollution and incidence of glaucoma. In this prospective study, we used land use regression models to estimate levels of various air pollutants, including fine particulate matter (PM2.5), PM2.5 absorbance, PM2.5-10, PM10, nitrogen dioxide (NO2), and nitrogen oxides (NOx). Incidents of glaucoma were ascertained through routinely collected hospital admission records. Multivariate Cox proportional hazards models were used to examine the associations between air pollution exposure and glaucoma incidence, adjusting for potential confounding sociodemographic, physical, and lifestyle factors. Data from 481,113 participants were included. Over a median follow-up of 12.8 years, 9224 incident cases of glaucoma were identified. In the maximally adjusted model, per interquartile range increase in PM2.5 was associated with a 3% greater risk of developing glaucoma (hazard ratio [HR] = 1.03, 95% confidence interval [CI] = 1.00 to 1.06, P = 0.048). Participants in the highest quartile had a 10% increased risk of developing glaucoma compared to those in the lowest quartile (HR = 1.10, 95% CI = 1.03 to 1.17, P = 0.005). Higher levels of exposure to ambient air pollutants, particularly PM2.5, are associated with an increased risk of developing glaucoma. These results highlight the potential public health impact of ambient air pollution on glaucoma risk and underscore the urgent need for further research into targeted environmental interventions in this domain.

Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth

Abstract. Ambient fine particulate matter (PM2.5) is the leading global environmental determinant of mortality. However, large gaps exist in ground-based PM2.5 monitoring. Satellite remote sensing of aerosol optical depth (AOD) offers information to help fill these gaps worldwide when augmented with a modeled PM2.5–AOD relationship. This study aims to understand the spatial pattern and driving factors of this relationship by examining η (PM2.5AOD) using both observations and modeling. A global observational estimate of η for the year 2019 is inferred from 6870 ground-based PM2.5 measurement sites and satellite-retrieved AOD. The global chemical transport model GEOS-Chem, in its high-performance configuration (GCHP), is used to interpret the observed spatial pattern of annual mean η. Measurements and the GCHP simulation consistently identify a global population-weighted mean η value of 96–98 µg m−3, with regional values ranging from 59.8 µg m−3 in North America to more than 190 µg m−3 in Africa. The highest η value is found in arid regions, where aerosols are less hygroscopic due to mineral dust, followed by regions strongly influenced by surface aerosol sources. Relatively low η values are found over regions distant from strong aerosol sources. The spatial correlation of observed η values with meteorological fields, aerosol vertical profiles, and aerosol chemical composition reveals that spatial variation in η is strongly influenced by aerosol composition and aerosol vertical profiles. Sensitivity tests with globally uniform parameters quantify the effects of aerosol composition and aerosol vertical profiles on spatial variability in η, exhibiting a population-weighted mean difference in aerosol composition of 12.3 µg m−3, which reflects the determinant effects of composition on aerosol hygroscopicity and aerosol optical properties, and a population-weighted mean difference in the aerosol vertical profile of 8.4 µg m−3, which reflects spatial variation in the column–surface relationship.

The impact of exposure assessment on associations between air pollution and cardiovascular mortality risks in the city of Rio de Janeiro, Brazil

Despite a growing literature for complex air quality models, scientific evidence lacks of the influences of varying exposure assessments and air quality data sources on the estimated mortality risks. This case-crossover study estimated cardiovascular mortality risks from fine particulate matter (PM2.5) and ozone (O3) exposures, using varying exposure methods, to aid understanding of the impact of exposure methods in the health risk estimation. We used individual-level cardiovascular mortality data in the city of Rio de Janeiro, 2012–2016. PM2.5 and O3 exposure levels (from the date of death to seven prior days [lag0–7]) were estimated at the individual level or district level using either the WRF-Chem modeling data or monitoring data, resulting in a total of 10 exposure methods. The exposure-response relationships were estimated using multiple logistic regressions. The changes in cardiovascular mortality were represented as an odds ratio (OR) and 95% confidence intervals (CIs) for an interquartile range (IQR) increase in the exposures. Results showed that socioeconomically more advantaged populations had lower access to the stationary monitoring networks. Higher variance in the estimated exposure levels across the 10 exposure methods was found for PM2.5 than O3. PM2.5 exposure was not associated with mortality risk in any exposure methods. WRF-Chem-based O3 exposure estimated for each individual of the entire population found a significant mortality risk (OR = 1.06, 95% CI: 1.01, 1.11), but not the other exposure methods. Higher risks for females and older populations were suggested for O3 estimates estimated for each individual using the WRF-Chem data. Findings indicate that decisions on exposure methods and data sources can lead to substantially varying implications for air pollution risks and highlight the need for comprehensive exposure and health impact assessments to aid local decision-making for air pollution and public health.

Air pollution’s numerical, spatial, and temporal heterogeneous impacts on childhood hand, foot and mouth disease: a multi-model county-level study from China

BackgroundWhile stationary links between childhood hand, foot and mouth disease (HFMD) and air pollution are known, a comprehensive study on their heterogeneous relationships (nonstationarity), jointly considering numerical, temporal and spatial dimensions, has not been reported.MethodsMonthly HFMD incidence and air pollution data were collected at the county level from Sichuan-Chongqing, China (2009–2011), alongside meteorological and social environmental covariates. Key influential factors were identified using random forest (RF) under the stationary assumption. Factors’ numerically, temporally, and spatially heterogeneous relationships with HFMD were assessed using generalized additive model (GAM) and geographically and temporally weighted regression (GTWR).ResultsOur findings highlighted the relatively higher stationary contributions of fine particulate matter (PM2.5) and ozone (O3) to HFMD incidence across Sichuan-Chongqing counties. We further uncovered heterogeneous impacts of PM2.5 and O3 from three nonstationary perspectives. Numerically, PM2.5 showed an inverse ‘V’-shaped relationship with HFMD incidence, while O3 exhibited a complex pattern, with increased HFMD incidence at low PM2.5 and moderate O3 concentrations. Temporally, PM2.5’s impact peaked in autumn and was weakest in spring, whereas O3’s effect was strongest in summer. Spatially, hotspot mapping revealed high-risk clusters for PM2.5 impact across all seasons, with notable geographical variations, and for O3 in spring, summer, and autumn, concentrated in specific regions of Sichuan-Chongqing.ConclusionsThis study underscores the nuanced and three-perspective heterogeneous influences of air pollution on HFMD in small areas, emphasizing the need for differentiated, localized, and time-sensitive prevention and control strategies to enhance the precision of dynamic early warnings and predictive models for HFMD and other infectious diseases, particularly in the fields of environmental and spatial epidemiology.

Electrospun fine-diameter polyimide nanofiber membranes via metal wire-based needle-free technique for high-efficiency PM0.3 filtration at high-temperature

Polyimide (PI) nanofiber materials have garnered attention in the field of high-temperature filtration due to their exceptional thermal stability. Enhancing their filtration efficiency for fine particulate matter (PM2.5–0.3) and exploring their performance limits under high-temperature conditions are crucial for high-temperature filtration applications. In this study, a metal wire-based needle-free electrospinning technique was employed to electrospin polyimide (PI) material, successfully fabricating nanofiber membranes with an average fiber diameter of 122 nm within just 10 min at an elevated electrospinning voltage of 80 kV (electric field:333.33 kV/m). The Fine-diameter PI nanofiber membrane achieved a filtration efficiency of 99.99 % for PM0.3 and operated at a low resistance of 189.18 Pa. After continuous treatment at a high temperature of 390 °C for one hour, the Fine-diameter PI nanofiber membrane still maintained a filtration efficiency of 99.96 % for PM0.3 and was capable of completely filtering PM2.5. This demonstrates the excellent stability and reliability of the Fine-diameter PI nanofiber membrane under extreme temperature conditions. Additionally, the membrane exhibited outstanding hydrophobic properties, with a static contact angle of 130 ± 3°, aiding in maintaining its filtration performance in humid environments. The Fine-diameter PI nanofiber membrane developed in this study offers a novel fabrication strategy for PM filtration in high-temperature environments and provides new insights into its limit performance.

Rural Roads to Cognitive Resilience (RRR): A prospective cohort study protocol.

Ambient air pollution, detrimental built and social environments, social isolation (SI), low socioeconomic status (SES), and rural (versus urban) residence have been associated with cognitive decline and risk of Alzheimer's disease and related dementias (ADRD). Research is needed to investigate the influence of ambient air pollution and built and social environments on SI and cognitive decline among rural, disadvantaged, ethnic minority communities. To address this gap, this cohort study will recruit an ethnoracially diverse, rural Florida sample in geographic proximity to seasonal agricultural burning. We will (1) examine contributions of smoke-related fine particulate matter (PM2.5) exposures to SI and cognitive function; (2) determine effects of built and social environments on SI and cognitive function; and (3) contextualize SI and cognitive function among residents from different ethnoracial groups during burn and non-burn seasons. Methods: We will recruit 1,087 community-dwelling, dementia-free, >=45-year-olds from five communities in Florida's Lake Okeechobee region. Over 36 months, participants will complete baseline visits to collect demographics, health history, and health measurements (e.g., blood pressure, body mass index) and 6-month follow-ups assessing cognitive function and social isolation at each visit. A subsample of 120 participants representative of each community will wear smartwatches to collect sensor data (e.g., heart rate) and daily routine and predefined activities (e.g., GPS-captured travel, frequent destinations) over two months. Ecological momentary assessments (EMA) (e.g., whether smoke has bothered participant in last 30 minutes) will occur over two months during agricultural burning and non-burning months. PurpleAir monitors (36 total) will be installed in each community to continuously monitor outdoor PM2.5 levels. Ethics and expected impact: This study received Florida Atlantic University's Institutional Review Board approval and will require participant informed consent. We expect to identify individual- and community-level factors that increase the risk for SI and cognitive decline in a vulnerable rural population.

Evidence for global increases in urban ammonia pollution and their drivers

Ammonia (NH3) affects air quality, human health, and life expectancy through its important role in forming fine particulate matter. However, the spatial patterns and trends of NH3 concentrations in the urban environment remain unknown worldwide. Here we use satellite measurements to produce a global distribution of NH3 at fine resolution, and then identify, categorize and quantify NH3 air concentrations in urban clusters throughout the world, as well as explore associated trends and drivers. Based on satellite records, a significant increase is evident in global urban NH3 concentrations between 2008 and 2019, with an annual increase of 1.2 % yr−1. Our results show that the decline of acidic gas (NOx/SO2) explains the largest part of the increasing NH3 concentrations (42 %), exceeding the contribution of local NH3 emissions. Our results also show that increasing temperature can explain 20 % of the increase in urban NH3 concentrations implying that efforts to reduce NH3 emissions need to be greatly strengthened to compensate for increases in urban NH3 pollution induced by global warming and so improve the urban environment.

The Protective Effect against Lung Injury of Phytosome Containing the Extract of Purple Waxy Corn Tassel in an Animal Model of PM2.5-Induced Lung Inflammation.

Lung inflammation caused by fine particulate matter (PM), particularly PM2.5, poses a significant public health challenge, with oxidative stress and inflammation playing central roles in its pathophysiology. This study evaluates the protective effects of phytosome-encapsulated extract of purple waxy corn tassel (PPT) against PM2.5-induced lung inflammation. Male Wistar rats received PPT at doses of 100, 200, and 400 mg/kg BW for 21 days prior to exposure and continued to receive the same doses for 27 days during PM2.5 exposure. Significant reductions in inflammatory markers, including cyclooxygenase-2 (COX-II), various interleukins (IL-1β, IL-6, IL-8), tumor necrosis factor-alpha (TNF-α), and nuclear factor kappa B (NF-κB), were observed, indicating that PPT effectively regulates the inflammatory response. Additionally, PPT improved oxidative stress markers by reducing malondialdehyde (MDA) levels and enhancing antioxidant enzyme activities such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px), thereby restoring lung antioxidant defenses. Notably, the study revealed that PPT modulates epigenetic mechanisms, as evidenced by decreased histone deacetylase (HDAC) activity and upregulation of sirtuins in lung tissue. These epigenetic modifications likely contribute to the reduction in inflammation and oxidative stress, suggesting a multifaceted protective role of PPT that involves both direct biochemical pathways and epigenetic regulation. The interplay between reduced inflammatory signaling, enhanced antioxidant capacity, and epigenetic modulation underscores PPT's potential as a therapeutic agent for managing respiratory inflammation-related diseases and its promise for the development of future functional food products.

Involvement of autophagy and gut dysbiosis in ambient particulate matter-induced colonic inflammation

Ambient fine particulate matter (PM2.5), a vital environmental toxicant, not only adversely affects the cardiovascular and respiratory systems but also potentially exhibits an association with intestinal inflammation and colorectal cancer (CRC). The underlying molecular mechanisms of PM2.5 impacts on CRC are still unclear. In this study, we utilized collected ambient PM2.5 and standard reference material SRM2786 to investigate the toxic effects on the colon through in vivo chronic exposure mouse and in vitro cell culture models. We employed a chronic mouse exposure model to clarify the colonic injury and gut microbiome biomarkers. Prolonged exposure to PM2.5 via oropharyngeal aspiration led to a significant rise in colonic epithelial proliferation and reduced colon length in mice. It triggered characteristics indicative of gut microbiota dysbiosis linked to inflammatory bowel disease. The gut microbiome alternations may serve as a biomarker indicating the colonic health impacts of PM2.5 exposure. PM2.5 and SRM2786-induced cytotoxicity manifested as autophagy dysregulation-mediated abnormal proliferation, IL-8 production, p62/SQSTM1 accumulation, and lysosomal membrane damage in human colon cells WiDr and Caco-2. Both PM2.5 and SRM2786 exposures led to the accumulation of p62/SQSTM1 and compromised lysosomal membrane integrity, showing impaired autophagic flux in WiDr and Caco-2 cells. Finally, we examined the correlations between atmospheric PM2.5 data and biomarkers of colonic inflammation in human population. The serum level of IL-8 was significantly correlated with regional anthropogenic pollutants. In conclusion, our findings elucidate that ambient PM2.5 exhibits adverse effects on colon health manifested as inflammation, aberrant proliferation, and gut dysbiosis, potentially mediated through autophagy dysregulation, thereby highlighting the importance of further research on the impact of environmental pollutants on gastrointestinal health.

Prenatal Exposure to Source-Specific Fine Particulate Matter and Autism Spectrum Disorder.

In this study, associations between prenatal exposure to fine particulate matter (PM2.5) from 9 sources and development of autism spectrum disorder (ASD) were assessed in a population-based retrospective pregnancy cohort in southern California. The cohort included 318,750 mother-child singleton pairs. ASD cases (N = 4559) were identified by ICD codes. Source-specific PM2.5 concentrations were estimated from a chemical transport model with a 4 × 4 km2 resolution and assigned to maternal pregnancy residential addresses. Cox proportional hazard models were used to estimate the hazard ratios (HR) of ASD development for each individual source. We also adjusted for total PM2.5 mass and in a separate model for all other sources simultaneously. Increased ASD risk was observed with on-road gasoline (HR [CI]: 1.18 [1.13, 1.24]), off-road gasoline (1.15 [1.12, 1.19]), off-road diesel (1.08 [1.05, 1.10]), food cooking (1.05 [1.02, 1.08]), aircraft (1.04 [1.01, 1.06]), and natural gas combustion (1.09 [1.06, 1.11]), each scaled to standard deviation increases in concentration. On-road gasoline and off-road gasoline were robust for other pollutant groups. PM2.5 emitted from different sources may have different impacts on ASD. The results also identify PM source mixtures for toxicological investigations that may provide evidence for future public health policies.

Seasonal Changes in the Oxidative Potential of Urban Air Pollutants: The Influence of Emission Sources and Proton- and Ligand-Mediated Dissolution of Transition Metals.

The inhalation of fine particulate matter (PM2.5) is a major contributor to adverse health effects from air pollution worldwide. An important toxicity pathway is thought to follow oxidative stress from the formation of exogenous reactive oxygen species (ROS) in the body, a proxy of which is oxidative potential (OP). As redox-active transition metals and organic species are important drivers of OP in urban environments, we investigate how seasonal changes in emission sources, aerosol chemical composition, acidity, and metal dissolution influence OP dynamics. Using a kinetic model of the lung redox chemistry, we predicted ROS (O2 •-, H2O2, •OH) formation with input parameters comprising the ambient concentrations of PM2.5, water-soluble Fe and Cu, secondary organic matter, nitrogen dioxide, and ozone across two years and two urban sites in Canada. Particulate species were the largest contributors to ROS production. Soluble Fe and Cu had their highest and lowest values in summer and winter, and changes in Fe solubility were closely linked to seasonal variations in chemical aging, the acidity of aerosol, and organic ligand levels. The results indicate three conditions that influence OP across various seasons: (a) low aerosol pH and high organic ligand levels leading to the highest OP in summer, (b) opposite trends leading to the lowest OP in winter, and (c) intermediate conditions corresponding to moderate OP in spring and fall. This study highlights how atmospheric chemical aging modifies the oxidative burden of urban air pollutants, resulting in a seasonal cycle with a potential effect on population health.

Ratios of organic mass to organic carbon in fine particulate matter at urban sites in China and Korea during winter and summer.

This study evaluates the composition and seasonal characteristics of fine particulate matter (PM2.5) during winter and summer through simultaneous measurements conducted at the Gwangju Institute of Science and Technology in South Korea and the Changping campus of Peking University in China. PM2.5 samples were concurrently collected at both sites, and chemical analyses were conducted to quantify various components, including carbonaceous materials, ionic species, and metals. Although the average PM2.5 concentrations were comparable between the two sites, there were distinct differences in the concentrations of major components. Organic indicator compounds were analyzed to discern the contributions of primary and secondary pollution sources. Changping displayed a mix of primary and secondary pollution, characterized by higher concentrations of primary organic carbon (POC) such as polycyclic aromatic hydrocarbons and hopanes, compared to Gwangju. In contrast, Gwangju demonstrated a higher prevalence of secondary organic carbon (SOC), particularly water-soluble organic carbon not related to biomass burning (WSOCnbb) and various polar organic compounds. The organic mass to organic carbon (OM/OC) ratios estimated using the mass balance method revealed significant differences, with Gwangju showing a higher ratio of 2.3 compared to 1.9 at Changping, indicating a greater influence of secondary pollutants at Gwangju. Additionally, both Changping and Gwangju exhibited higher OM/OC ratios in summer (Changping: 2.0, Gwangju: 2.5) compared to winter (Changping: 1.8, Gwangju: 2.2), indicating seasonal differences in organic mass contributions to PM2.5. These findings underscore the importance of accounting for spatial and seasonal variations in air pollution studies and suggest that updating commonly used OM/OC ratios could enhance the reliability of research outcomes.

Impact of elevated fine particulate matter (PM2.5) during landscape fire events on cardiorespiratory hospital admissions in Perth, Western Australia

BackgroundAustralia has experienced extreme fire weather in recent years. Information on the impact of fine particulate matter (PM2.5) from landscape fires (LFs) on cardiorespiratory hospital admissions is limited.MethodsWe conducted a...

How does PM2.5 affect forest phenology? Integrating PM2.5 into phenology models for warm-temperate forests in China

Vegetation can regulate particulate matter (PM) through various mechanisms, such as facilitating the deposition of gases and particulates and purifying the air via photosynthesis. Conversely, PM directly damages leaves through dry deposition, while it also indirectly affects plant growth by altering weather conditions. However, the ways in which PM influence vegetation growth patterns, and the driving factors behind these impacts, remain unclear. In this study, we primarily focused on the start of the growing season (SOS) of warm-temperate zone forests in China with severe PM. SOS exhibited a trend of advancing at a rate of 0.15 days/yr during the study period from 2004 to 2022. We assessed the impact of satellite-derived fine PM (PM2.5) and coarser PM (PM10) on forest SOS across warm temperate forest regions in China using partial correlation analysis methods. After removing the effects of PM, we found that the correlation between temperature and SOS weakened. Additionally, PM exhibited a positive correlation with SOS in most pixels. Linear regression analysis revealed a significant negative correlation between relative humidity (RH) and the relationship between PM2.5 and SOS. However, in areas where RH exceeds 60.38%, this effect becomes unstable, presumably due to increased aerosol hygroscopicity or the saturation of aerosol particles. We also found that as road network density increased, the relationship between PM2.5 and SOS strengthened, whereas the impact of nightlight on this relationship was relatively weak. It is important to note that while the observed correlations reveal mechanisms by which PM2.5 affects SOS, they do not directly imply causation, as the complex interactions between environmental factors may influence these relationships. Finally, we incorporated PM2.5 into the phenology model and optimized its parameters using the least squares method, which improved the accuracy of SOS simulations and provided insights for predicting vegetation phenology in areas with severe PM pollution.

Temperature variability and influenza incidence in China: Effect modification by ambient fine particulate matter

This study aims to examine the association between temperature variabilit (TV) exposure and influenza incidence in China, and the modification effect of PM2.5 levels. Data on daily influenza cases, weather conditions, and PM2.5 concentrations were collected from 339 cities across mainland China from 2014 to 2019. TV was computed as the standard deviation of daily maximum and minimum temperatures for the current day and the previous several days (i.e., TV0–1 to TV0–7). A space-time-stratified case-crossover design with conditional Poisson regression was employed. Overall, each 1 °C increase in TV0–6 was linked to 3.3 % (95 % CI: 3.1 %, 3.5 %) rise in influenza incidence, potentially attributing 14.73 % (95 % CI: 14.08 %, 15.37 %) of cases to this exposure. PM2.5 concentration showed substantial modification effect on the association, such that the relative risk (RR) of influenza incidence grew from 1.027 (95 % CI: 1.025, 1.029) to 1.040 (95 % CI: 1.038, 1.042) as PM2.5 levels increased from 15 to 75 μg/m³ . Females and individuals over 65 years old were more susceptible to TV exposure and the PM2.5 modification. Stronger effects were observed during cold season and in North region. The findings highlight the integrating considerations of TV and PM2.5 exposures into public health measures for influenza prevention and control.

Estimation of nighttime PM2.5 concentrations over Seoul using Suomi NPP/VIIRS Day/Night Band

With rapid economic development and urban growth, Seoul experiences severe air pollution due to fine particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), which is detrimental to human health. Although recent studies have extensively focused on estimating daytime PM2.5 concentrations using various types of satellite data, there remains a significant lack of research on nighttime PM2.5 estimations. This study estimated nighttime PM2.5 in Seoul from December 2018 to November 2019 using multiple linear regression (MLR) and random forest (RF) models. These models, which incorporated data on radiance, moon illumination fraction, and terrain height from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi National Polar-orbiting Partnership satellite covering all moon phases, also utilized meteorological data from the ERA5 reanalysis by the European Centre for Medium-Range Weather Forecasts (ECMWF). To address multicollinearity, seasonal models were developed using forward stepwise regression and variance inflation factor analysis. DNB radiance analysis indicates that the high intensity of artificial light sources in Seoul significantly reduces the impact of moonlight, leading to notable changes in the DNB radiation associated with PM2.5 concentrations. Consequently, this study estimated nighttime PM2.5 over Seoul across all moon phases. These estimates were then validated through 10-fold cross-validation. The RF model exhibited superior accuracy, with a coefficient of determination (R2) of 0.65–0.90, compared to MLR, with R2 of 0.15–0.50, reflecting seasonal fluctuations in the model performance. The developed models can be applied to estimate reliable nighttime PM2.5 concentrations in megacities with strong artificial light sources, utilizing a comprehensive dataset from satellite observations for all moon phases. Additionally, our findings can serve as scientific data for establishing environmental policies by providing valuable insights into understanding air pollution primarily caused by PM2.5.

Spatiotemporal Characterization and Driving Factors of Fine Particulate Matter and Its Chemical Components in the Huaihe River Basin

According to the data sets of fine particulate matter （PM2.5） and its components in 35 cities in the Huaihe River Basin from 2015 to 2021, the temporal and spatial distribution patterns of pollutants were analyzed. The influence of meteorological factors on PM2.5 concentrations was examined using a random forest model. The original series of PM2.5, sulfate （SO42-）, nitrate （NO3-）, ammonium salt （NH4+）, organic matter （OM）, and black carbon （BC） were rebuilt using KZ （Kolmogorov-Zurbenko） filtering and multiple linear regression （MLR） to quantify the effects of meteorological conditions. The results demonstrated that from 2015 to 2021, the declining rates of PM2.5, SO42-, NO3-, NH4+, OM, and BC in the Huaihe River Basin were 4.71, 0.99, 1.05, 0.77, 1.01, and 0.19 μg·（m3·a）-1, respectively. The high mass concentrations of PM2.5 and its components were concentrated in the central and western regions of the HRB, whereas those in coastal and southern cities were lower. The variance contributions of the short-term, seasonal, and long-term components of PM2.5 to the original PM2.5 sequences in 35 cities were 51.6%, 35.9%, and 7.0%, respectively. The PM2.5 in coastal cities were more affected by the short-term components. The meteorological conditions were unfavorable for PM2.5 reduction in the HRB from 2015 to 2018, whereas the meteorological conditions supported the PM2.5 decrease from 2019 to 2021. From 2015 to 2021, the contribution rates of meteorological conditions to the long-term component reductions of PM2.5, SO42-, NO3-, NH4+, OM, and BC were 28.3%, 29.1%, 31.0%, 29.3%, 27.8%, and 28.6%, respectively. The contribution rates of meteorological conditions to the long-term PM2.5 reduction were 43.4%, 25.6%, 25.5%, and 20.6% in the HRB cities in Anhui, Shandong, Jiangsu, and Henan Provinces, respectively. With the decrease in PM2.5 concentration in the HRB, the sulfur oxidation rate （SOR） increased significantly, while the nitrogen oxide oxidation rate （NOR） changed little.

Evolution Characteristics and Typical Pollution Episodes of PM2.5 and O3 Complex Pollution in Bozhou City from 2017 to 2022

In China, atmospheric pollution exhibits a complex pattern, with simultaneous exceedances of fine particulate matter （PM2.5） and ozone （O3） levels becoming evident. To understand the complex pollution characteristics and evolution patterns of PM2.5 and O3 in Bozhou City, various methods such as weather classification, analysis of typical pollution processes, and investigation of precursor sources were employed to explore the pollution and variations of PM2.5 and O3 in Bozhou City from 2017 to 2022 and subsequently analyze their causes and precursor sources. The results indicated that： ① PM2.5-O3 complex pollution in Bozhou City mostly occurred under high-pressure weather conditions, with daytime high temperatures and low humidity promoting the formation of O3 pollution, whereas nighttime high humidity and atmospheric oxidative conditions promoted the generation of secondary components such as nitrates and ammonium salts in PM2.5. ② During the pollution process, PM2.5 in Bozhou City mainly originated from biomass burning, secondary generation, traffic pollution, coal combustion, and dust sources. Volatile organic compounds （VOCs） primarily emerged from plant sources, traffic pollution, oil and gas evaporation, solvent use, fossil fuel combustion, residential emissions, and industrial emissions. Biomass burning and traffic pollution made significant contributions to the pollution process. ③ Analysis of air mass trajectories and regional pollution situations indicated that the overlay of northern and southern air masses, along with local generation, were the main causes of the PM2.5-O3 complex pollution in Bozhou from October 18th to 27th, 2022.

Dominant influence of biomass combustion and cross-border transport on nitrogen-containing organic compound levels in the southeastern Tibetan Plateau

Abstract. The Tibetan Plateau (TP) is highly susceptible to climate change, and nitrogen-containing organic compounds (NOCs) in fine particulate matter (PM2.5) represent one of the largest uncertainties with respect to their impact on the climate in high-altitude areas. Previous studies have shown that NOCs play a vital role in the nitrogen budget of PM2.5. However, our understanding of the composition and sources of NOCs in PM2.5, particularly in the TP, is limited. Here, we aim to enhance our understanding of NOCs in the TP region by examining their identification, concentration levels, sources, and origins. We conducted field sampling at a regional background sampling site in Gaomeigu, in the southeastern margin of the TP from 11 March to 13 May 2017, followed by laboratory analysis of the NOCs collected on the filters. The daily mass concentrations of NOCs ranged from 714.4 to 3887.1 ng m−3, with an average of 2119.4 ± 875.0 ng m−3 during the campaign. This average concentration was approximately 40 % higher than that reported at a typical regional site in the North China Plain (NCP), highlighting a more significant presence of NOCs in the Tibetan area. Biomass burning and secondary sources were identified as the major contributors to total NOCs. This was further substantiated by a regional air quality model, which indicated that over 80 % of the aerosol in the southeast of the TP originated from neighboring countries. This study improves our understanding of NOCs' contribution to PM2.5 in the TP and their potential impacts on climate stability in high-altitude areas.

Simultaneous comparison of the chemical composition and attributable source of PM2.5 during 2014–2018 in major metropolitan cities in South Korea: impacts of policy interventions

Abstract Ambient fine particulate matter (PM2.5) is one of the most concerning pollutants, characterized by its diverse chemical composition. Although various studies have revealed PM2.5 chemical components, there is limited knowledge on how to reduce PM2.5 concentrations through administrative policies focusing on source management. We compared PM2.5 compositional characteristics and performed source apportionment using the positive matrix factorization in four metropolitan cities (Seoul, Daejeon, Gwangju, and Ulsan) in South Korea from 2014 to 2018. The annual average of PM2.5 concentrations exceeded the annual national ambient air quality standard of 15 μg m−3 in all areas while secondary inorganic aerosols constituted the largest fraction of PM2.5. This implies that secondary formation from gaseous precursors in the atmosphere was the main factor contributing to ambient PM2.5. However, the concentrations of PM2.5 constituents varied significantly across cities, suggesting that PM2.5 is a heterogeneous pollutant considerably influenced by region-specific conditions. In line with the chemical composition, secondary nitrate, secondary sulfate, and mobile-related sources were found to be significant contributors of PM2.5. Additionally, the extent of contribution from each source varied across the study regions. We also evaluated the impacts of policy interventions by comparing the PM2.5 composition and source apportionment before and after the policies for improving air quality. Intensive programs focused on the vehicle sector in Seoul led to a considerable decrease in the concentrations of carbonaceous compounds and mobile-related sources. In addition, strengthened regulations on coal-fired power plants (CFPPs) since 2016 have influenced the contributions of coal combustion sources in two cities adjacent to the west coastal area, where approximately half of the CFPPs of the country are densely distributed. Overall, the study’s findings indicate that region-specific PM2.5 chemical constituents and source contributions should be considered for establishing PM2.5-related policies, considering the high heterogeneity of PM2.5.