With the acceleration of global economic development and urbanization, the impacts of anthropogenic emissions on the Earth system have intensified. East Asia, as one of the most densely populated and economically active regions in the world, emits substantial amounts of particulate matter into the atmosphere. Influenced by the prevailing westerlies and the East Asian monsoon, these particles are transported downwind to the Northwest Pacific, exerting significant effects on marine atmospheric composition and ocean ecosystems in this region.Focusing on key marine atmospheric nutrients including iron (Fe) and nitrogen (N), this study employs a multi-platform approach encompassing satellite remote sensing, in situ Argo floats, shipborne observations, and atmospheric chemical transport modeling to investigate the contribution of East Asian continental aerosol outflow to nutrient supply and the subsequent ocean response. A central highlight of this work is quantifying anthropogenic contributions to atmospheric Fe and N over the Northwest Pacific in recent years.First, by integrating shipborne online measurements (2021–2022) of multiple atmospheric metals with a positive matrix factorization (PMF) model, we developed a high-time-resolution source apportionment framework for marine atmospheric metals including Fe. This approach provides the first observation-based quantification of contributions from several anthropogenic sources to marine atmospheric Fe and soluble Fe at hourly resolution. The results showed land anthropogenic emissions contributed substantially to atmospheric soluble Fe, accounting for 57% in the open Northwest Pacific during spring and increasing to 62% in summer. These results were further cross-validated against advanced Fe isotope–based source apportionment, yielding strong agreement (R2 = 0.94).Second, for atmospheric nitrogen, shipborne sampling combined with nitrogen isotope analysis revealed sharp spatial gradients in atmospheric nitrate concentrations and sources from the Chinese marginal seas to the open Northwest Pacific. Coupled with an atmospheric chemical transport model, we further quantified the flux and temporal variability of multiple nitrogen species transported from East Asia to the Northwest Pacific during 2005–2019 and assessed the response of marine atmospheric nitrogen deposition to emission reductions in recent years in East Asia. These findings provide novel insights into the important impacts of land-derived emissions on ocean ecosystems, particularly anthropogenic sources, in shaping biogeochemical processes in downwind oceanic regions and advance our understanding of land–ocean interactions under anthropogenic perturbations.

During long-range transport, dust aerosols mix with anthropogenic pollutants and undergo atmospheric aging, altering their chemical composition. However, observational data remain limited regarding how these changes affect health risks of dust to urban population and nutrient supply (e.g., iron) to marine ecosystem. This study examines two extreme Asian dust events with distinct transport pathways in March 2021 (Dust-1 and Dust-2), with observations at inland (Beijing) and island (Tuoji Island, Bohai Sea) sites. Chemical composition and toxicity analyses were integrated to assess changes in the oxidative potential and iron solubility (i.e., bioavailability) of dust during transport. The results reveal that Dust-1, which first arrived in Beijing on March 15, subsequently experienced a backflow to Beijing on March 16. During Dust-1 backflow, PM2.5 concentrations decreased by 79% compared to its first arrival, but the oxidative potential per PM2.5 mass (OPm) increased 5.3-fold, indicating elevated risks for human health. The mixing of dust with anthropogenic PM2.5, which accounted for 34% during the backflow, was a key factor in the elevated OPm. Regarding iron solubility, when Dust-1 backed flow over land, mixing with anthropogenic pollutants clearly enhanced iron solubility. However, during the land-to-sea transport of Dust-2, secondary acid formation played a more significant role, converting insoluble iron into soluble iron and resulting in a 173% increase in iron solubility over Tuoji Island compared to Beijing. This study provides new insights into how the aging of long-range transported dust increases oxidative potential, impacting human health on land, while enhancing iron solubility, benefiting marine ecosystem.

Vehicle emission is a major source of urban ultrafine particles (UFPs), yet measurement and emission control for UFP lags significantly behind that of other pollutants. The China VI emission standard, one of the strictest globally, introduced the nation’s first particle number (PN) limits. This study focused on real-world PN emissions in the capital city Beijing, which adopted China VI ahead of the national schedule in 2019. Based on long-term particle number size distribution measurements and online UFP composition analysis, a pronounced decline in emission rates of vehicle-attributed PN from 2019 to 2023 was found, resulting in decreases of 70

The direct aerosol radiative effect (DARE) remains one of the largest uncertainties in Earth’s climate system, partly because global estimates rely on polar-orbiting satellites with limited daily sampling. Here, we combine observations from eight geostationary satellites (the GEO-Ring constellation) with an integrated Transformer and transfer learning framework to retrieve global, hourly aerosol optical depth (AOD) at 550 nm and 2 km resolution over land. The resulting dataset agrees well with independent random-sample-based cross-validation (CV-R2 = 0.86; RMSE = 0.085) and enables robust characterization of diurnal AOD variability. We find pronounced diurnal cycles, with a mean amplitude of 46% ± 29% relative to a global mean land AOD of 0.17 ± 0.13 during 2021–2023, alongside strong regional contrasts. Instantaneous polar-orbiting observations yield systematically higher aerosol loadings by 7–48% across 60–80% of global land areas relative to GEO-Ring estimates, reflecting unresolved diurnal variability and retrieval differences. These discrepancies lead to a 35–79% overestimation of global annual mean DARE over land (−3.8 W m-2), implying an inflated estimate of aerosol-induced cooling and consequently a greater challenge for mitigating global warming. Our results highlight the importance of resolving diurnal aerosol variability for robust quantification of aerosol radiative effects and their climate impacts.

In recent years, with the continuous advancement of atmospheric pollution control efforts, the health effects arising from the complex sources and diverse physicochemical properties of particulate matter have garnered increasing attention from scholars. The oxidative potential (OP) of atmospheric particulate matter has gradually emerged as a key indicator for assessing air quality and health risks in the field of environmental health, becoming one of the major research focuses in recent years. OP effectively reflects the capacity of particulate matter to induce the generation of reactive oxygen species and trigger oxidative stress responses, which is closely linked to a range of adverse health outcomes, including cardiovascular and respiratory diseases. Therefore, accurate measurement of the OP of particulate matter is of paramount importance for the in-depth evaluation of its health impacts, the refinement of air quality standards, and the formulation of precise public health intervention strategies. Traditionally, the measurement of OP has relied primarily on offline filter sampling and laboratory analysis techniques. Such methods are often limited by low temporal resolution, notable analytical delays, high economic costs, and the potential loss of short-lived, highly reactive oxidative components during the detection processes. These limitations present challenges for studies based on offline measurements to capture the rapid dynamic changes in atmospheric OP or to enable real-time warning and source apportionment during pollution events. To overcome the bottlenecks associated with conventional offline measurement techniques, researchers have dedicated considerable efforts in recent years to developing rapid and automated detection techniques based on various principles, aiming to achieve real-time online assessment of the OP of atmospheric aerosols. The advancement of such techniques: (1) reveals the diurnal variation patterns of atmospheric OP and its dynamic linkages with pollutant source emissions, meteorological conditions, and chemical processes, and (2) provides novel technical approaches for evaluating real-time air quality from a biologically relevant perspective and for assessing population exposure risks. This review systematically summarizes research progress in the field of online detection of atmospheric aerosol OP over the past 25 years. It elaborates on the technical principles of automated online monitoring systems and provides a comprehensive overview of the development history and current status of various detection devices and methods. Specifically, the study categorizes, introduces, and compares six major types of online monitoring systems, including: (1) systems based on the 2',7'- dichlorofluorescin (DCFH) assay; (2) particle into Nitroxide Quencher (PINQ) technology, (3) the ascorbic acid redox system (AA-only), (4) automated dithiothreitol (DTT) assay platforms, (5) online hydroxyl radical monitoring systems, and (6) online monitoring systems coupling OP measurement with cytotoxicity assessment. These approaches are further compared from multiple perspectives, such as detection sensitivity, measurement specificity, temporal resolution, operational complexity, economic cost, and physiological relevance. Finally, the review thoroughly analyzes the advantages and challenges faced by these automated technologies in practical monitoring scenarios. Looking ahead, future research directions in online OP monitoring technology should focus on promoting the standardization and mutual recognition of measurement methods, developing probe systems with higher sensitivity and greater specificity, achieving multi-parameter synchronous online monitoring and comprehensive data integration, as well as expanding their applications in areas such as individual exposure assessment and rapid evaluation of the effectiveness of air pollution control measures. This paper aims to provide systematic scientific references for methodological innovation, technological advancement, and the formulation of health effect-based environmental policies.

Black carbon (BC) is an important air pollutant that poses serious risks to human health. However, previous studies have largely focused on total BC mass concentrations, while the health risks associated with source-specific BC remain poorly understood, limiting the development of effective health-oriented control strategies. To address this issue, long-term source-specific BC mortality analyses were conducted in Beijing during 2016-2019 by integrating an hourly-resolution dataset of 19 PM2.5 components, Positive Matrix Factorization (PMF) source apportionment, and high-quality mortality records. The findings indicated that the health risk of BC could vary by source, with traffic BC posing the highest non-accidental mortality risk (RR: 1.014, 95% CI: 1.003, 1.025), followed by biomass burning and atmospherically aged BC. During the study period, the stringent coal control policies implemented in northern China led to a drastic reduction in coal BC concentration, accounting for 40% of the reduction in BC-attributable mortality burden. Consequently, the three non-coal sources (traffic, biomass burning, and aged BC) became the dominant contributors in 2019, collectively accounting for 86% of the BC-attributable mortality burden. These findings highlight substantial source-specific differences in BC mortality risks and provide evidence for developing health-oriented policies to better protect public health through clean air initiatives.

Understanding the changes in atmospheric composition is essential for accurately assessing their impacts on climate, air quality, and human health. In China, long-term and high-quality datasets are very useful and critical for evaluating the effectiveness of air pollution control measures. Over the past decade, many researchers have conducted extensive field measurements and developed new emission inventories and datasets for various air pollutants in China, generating a large volume of valuable but fragmented data. With support from the National Natural Science Foundation of China (NSFC), we have successfully established the China Air Pollution Data Center (CAPDC; https://www.capdatabase.cn), integrating multi-type data from 76 NSFC-funded projects, including emission inventories, field observations, laboratory measurements, chemical reanalysis products, and emerging technologies. The CAPDC provides open, bilingual access for domestic and international users, and enables quick data download and online visualization, which could support scientists in conducting further analyses for air quality management and climate change.This presentation provides an overview of this data center and examples of how data products from CAPDC are applied to study atmospheric composition changes and trends in China, with reasons for such changes. The data product for studying trends is based on a chemical reanalysis dataset named High-resolution Air Quality Reanalysis Dataset over China (CAQRA-aerosol), which provides concentrations of sulfate, nitrate, ammonium, black carbon, and organic carbon over China from 2013 to 2022 at 1-h and 15-km resolutions. This dataset allows assessment of diurnal to decadal variability and regional contrasts in aerosol composition. Results show a pronounced decline in annual mean PM2.5 concentrations in major urban regions, particularly in winter, primarily driven by reductions in sulfate and organic matter, reflecting the effectiveness of recent emission control policies. In contrast, PM2.5 concentration trends at remote sites on the Tibetan Plateau do not show significant change, very different from many major cities. Our study illustrates how high-quality long-term datasets can be used to attribute observed atmospheric composition changes to specific drivers and to document atmospheric responses to policy interventions

Metals are key toxic components of PM2.5, but their personal exposure levels and health effects remain unclear, due to their high spatiotemporal heterogeneity and large differences in individual behaviors. This study proposed a "personal PM2.5-bound metal exposome" framework to (1) systematically characterize personal metal exposure profiles and their variability, (2) comprehensively evaluate the health effects of multimetal exposures, and (3) explore interactions among metals. Using data from the SCOPE (Study Comparing the cardiO-metabolic and respiratory effects of air Pollution Exposure) panel study, we analyzed personal samples and data from 588 follow-up visits of 120 elders in Beijing, China. Personal 23.5-h PM2.5 samples were collected using portable devices, and concentrations of 15 metals were quantified by micro-synchrotron radiation X-ray fluorescence (μ-SRXRF). Linear mixed-effects models were applied to assess the impacts of transportation modes and personal exposure sources on personal PM2.5-bound metal exposure profiles. A Bayesian Kernel Machine Regression (BKMR) model was applied to examine the associations between metals and inflammatory biomarkers and evaluate interactions among metals. The results indicated that participants exposed to the subway microenvironment had elevated exposure levels of iron (Fe), manganese (Mn), and copper (Cu). This suggests that even when metal exposure is accumulated over only a short period in the subway, the enclosed environment may still lead to potentially pronounced health impacts. An interquartile range increase in arsenic (As) was associated with an increase of 6.2% in IFNγ (95% CI: 0.0-12.4%), 20.2% in sCD40L (95% CI: 7.1-33.3%), 2.9% in MCP-1 (95%CI: 1.0-5.5%), 1.8% in white blood cells (95% CI: 0.3-3.2%), and 3.3% in monocytes (95% CI: 1.0-5.4%). Suggestive evidence indicated that transition metals (Fe, Cu, Mn) may have synergistic pro-inflammatory effects. Based on a "personal PM2.5-bound metal exposome" analytical framework, this study has improved scientific understanding of personal metal exposure profiles and their health effects.

The atmospheric environment of the Tibetan Plateau is significantly sensitive to pollutants transported from regions with intensive anthropogenic activity. It is therefore critical to identify source regions and transported air pollutants on the Tibetan Plateau. The present study developed a method to link multiple pollutants measured at receptor sites on the Tibetan Plateau to their source regions by integrating measurements and modeling. Ground-based measurements of over 150 species in fine particulate matter (PM2.5) at the Nam Co Station were conducted for one year. Meanwhile, contributions from different source regions to PM2.5 in each sample were quantified by using an emission inventory-coupled Lagrangian box model. The findings indicated that specific source regions were associated with distinct chemical species and sources. In the premonsoon season, transport from the northwestern South Asia was related to enhanced concentrations of black carbon, organic carbon, K+, anhydrosugars, Pb, and Zn. This suggested a strong influence from intensive biomass burning and industrial activities. However, increased contribution from the northwestern China to PM2.5 was associated with increased concentrations of low-molecular-weight polycyclic aromatic hydrocarbons, Cl-, and several anthropogenic metals, reflecting impacts from mixed industrial and residential sources. During the monsoon season, concentrations of highly oxidized secondary organic aerosol (SOA) species increased with contribution from regions south of the receptor site, highlighting the importance of aged SOA in this season. The findings in this study not only improve our understanding of how transport from different regions shapes atmospheric composition in the Tibetan Plateau but also offer a new approach to investigate impacts of long-range transport on remote environments.

The atmospheric environment of the Tibetan Plateau is significantly sensitive to pollutants transported from regions with intensive anthropogenic activity. It is therefore critical to identify source regions and transported air pollutants on the Tibetan Plateau. The present study developed a method to link multiple pollutants measured at receptor sites on the Tibetan Plateau to their source regions by integrating measurements and modeling. Ground-based measurements of over 150 species in fine particulate matter (PM2.5) at the Nam Co Station were conducted for one year. Meanwhile, contributions from different source regions to PM2.5 in each sample were quantified by using an emission inventory-coupled Lagrangian box model. The findings indicated that specific source regions were associated with distinct chemical species and sources. In the premonsoon season, transport from the northwestern South Asia was related to enhanced concentrations of black carbon, organic carbon, K+, anhydrosugars, Pb, and Zn. This suggested a strong influence from intensive biomass burning and industrial activities. However, increased contribution from the northwestern China to PM2.5 was associated with increased concentrations of low-molecular-weight polycyclic aromatic hydrocarbons, Cl-, and several anthropogenic metals, reflecting impacts from mixed industrial and residential sources. During the monsoon season, concentrations of highly oxidized secondary organic aerosol (SOA) species increased with contribution from regions south of the receptor site, highlighting the importance of aged SOA in this season. The findings in this study not only improve our understanding of how transport from different regions shapes atmospheric composition in the Tibetan Plateau but also offer a new approach to investigate impacts of long-range transport on remote environments.

Non-dust emissions have been increasingly recognized as important contributors to atmospheric iron (Fe), influencing marine productivity through enhanced bioavailable Fe inputs. However, accurately quantifying the contributions and spatiotemporal variability of non-dust sources remains challenging due to relatively low time-resolution of traditional filter-based analytical methods. In this study, the contributions of non-dust emissions to atmospheric total and soluble Fe in the Northwest Pacific were quantified based on online measurements from three ship-based observation campaigns in 2021-2022. A Positive Matrix Factorization (PMF) model was applied for source apportionment. Results showed non-dust emissions were notable contributors to atmospheric total Fe, representing 24 %-41 % of total Fe in PM10 and 30 %-56 % in PM2.5 samples across different cruise legs. Importantly, their contributions to soluble Fe were significantly higher, reaching 88 %-97 % in PM10 and 85 %-98 % in PM2.5 samples. Among non-dust sources, land anthropogenic emissions contributed substantially to both total and soluble Fe, whereas ship emission contributed a small portion to total Fe but was a major source of soluble Fe, particularly in summer, when its contribution reached 79 % of soluble Fe in PM10 samples in coastal regions. Additionally, Fe from non-dust sources exhibited stronger spatial variability than dust source. The concentrations of land anthropogenic Fe differed by 3-5 times between coastal and open-ocean areas during the same cruises, while ship-derived Fe varied by an order of magnitude or more. This study offers critical observational evidence to advance understanding of how diverse emission sources shape atmospheric composition in Asian continental outflow regions.

Air pollution levels monitored at fixed sites, known as ambient concentrations, are often used as surrogate indicators of individual exposure levels. However, this could lead to exposure misclassification, a major challenge in environmental epidemiology research. Discrepancies between ambient concentrations and personal exposure characteristics, their underlying causes, and their potential impacts on health effect assessments remain unclear, particularly for the metals in fine particulate matter (PM2.5). Based on a panel study conducted in Beijing, we investigated the discrepancies in daily average concentrations of nine metals in personal and ambient PM2.5 samples. Specific personal exposure sources and outdoor activity time can impact personal PM2.5 metal exposure levels. Indoor sources were found to be the primary contributors to these discrepancies when ambient concentrations were low, while infiltration factors became the dominant influence at higher ambient concentrations. Using inflammatory biomarkers as examples, we further explored the impacts of ambient concentration and personal exposure as indicators for health effect assessment. The confidence intervals for associations between single metals and inflammatory biomarkers were wider for ambient concentration, but narrower for personal exposure. An overall increase of one IQR in the concentrations of nine metals in personal exposure was significantly associated with the following increases in inflammatory biomarkers: 0.16 [95 % CI: 0.04-0.28] in MCP-1, 0.13 [95 % CI: 0.05-0.21] in MDC, 0.49 [95 % CI: 0.41-0.76] in MIP-1β, 0.32 [95 % CI: 0.07-0.57] in sCD40L, and 0.22 [95 % CI: 0.0-0.44] in TNF-α. In contrast, no such significant associations were found for ambient concentrations. Taken together, indoor sources and infiltration factors largely determine the discrepancies between ambient concentrations and personal exposure levels, which can further affect the accuracy of health effect assessments. Personal exposure is a better indicator for characterizing metal exposure levels.

Based on the satellite aerosol optical thickness (AOD) data from MODIS/Terra (2001-2022) and MODIS/Aqua (2002-2022), we investigated the temporal-spatial distribution and trends of AOD in East Asia and the Northwest Pacific. An increasing trend, ranging from 0.002 to 0.02/year with 95% confidence, was observed across all seven sub-regions from 2001 to 2013. The highest increase rates were found in North China and South China, both at 0.02/year. Following the implementation of China's Air Pollution Prevention and Control Action Plan in 2013, AOD levels in Northeast China, North China, South China, the East China Sea, and the Northwest Pacific significantly decreased, ranging from -0.002 to -0.02/year. The results indicate that the Air Pollution Prevention and Control Action Plan has been effective in reducing aerosol emissions in China, thereby decreasing the aerosol loading transported to downwind areas.

INTRODUCTION:Long-term exposure to fine particulate matter (PM2.5) has been linked to many adverse health outcomes, which can vary significantly depending on the chemical profile of the PM2.5. However, many meta-analyses of the health effects of a specific component of PM2.5 have ignored the effects of other components, leading to omitted variable bias (OVB). This study developed a new method to address this problem and conducted a simulation using black carbon (BC) as an example. METHOD:We used data from two published meta-analyses as input for our model, with supplementary information obtained from a reanalysis product of PM2.5 components. Based on the classical OVB formula, we developed a post hoc adjusted model and verified its performance via a simulation study. We obtained pooled estimates of the effect of BC on all-cause mortality, with adjustment for the effect of non-black carbon (NBC) components. Finally, based on the estimated effects of BC and NBC, we investigated global patterns in PM2.5 toxicity (i.e., the per-unit effect of PM2.5) and the degree of OVB associated with ignoring the differential effects of BC and NBC. RESULTS:The post hoc adjusted model included 46 individual estimates of the effects of BC or NBC on all-cause mortality. Results from the model indicate that a 10 μg/m³ increase in BC and NBC was associated with a 49 % (95 % confidence interval [CI]: 26 - 76 %) and 6 % (95 % CI: 3 - 10 %) increase in mortality risk, respectively. Based on global average total PM2.5 mass composition values (6.1 % and 93.9 % for BC and NBC, respectively), we estimated that the relative risk of all-cause mortality increased by 1.09 (95 % CI: 1.06 - 1.12) per 10 μg/m3 increment in long-term PM2.5 exposure. Estimation of the effects of BC on mortality based on observations obtained within one city yielded a median OVB of 147 % (95 % CI: -151 - 700) when using a single-pollutant model. CONCLUSION:In meta-analyses on the health impacts of PM2.5 components, ignoring the differential effects of BC and NBC causes significant biases in estimating associations with all-cause mortality. Our study presents a novel method to adjust for OVB in meta-analyses, and we find that BC more harmful than NBC components of PM2.5 by using the novel method.

Scientific knowledge on the chemical compositions of fine particulate matter (PM2.5) is essential for properly assessing its health and climate effects, and for decisionmakers to develop efficient mitigation strategies. A high-resolution PM2.5 chemical composition dataset (CAQRA-aerosol) is developed in this study, which provides hourly maps of organic carbon, black carbon, ammonium, nitrate, and sulfate in China from 2013 to 2020 with a horizontal resolution of 15 km. This paper describes the method, access, and validation results of this dataset. It shows that CAQRA-aerosol has good consistency with observations and achieves higher or comparable accuracy with previous PM2.5 composition datasets. Based on CAQRA-aerosol, spatiotemporal changes of different PM2.5 compositions were investigated from a national viewpoint, which emphasizes different changes of nitrate from other compositions. The estimated annual rate of population-weighted concentrations of nitrate is 0.23 µg m−3 yr−1 from 2015 to 2020, compared with −0.19 to −1.1 µg m−3 yr−1 for other compositions. The whole dataset is freely available from the China Air Pollution Data Center ( https://doi.org/10.12423/capdb_PKU.2023.DA ).

Atmospheric iron (Fe) impacts atmospheric chemistry and marine ecosystems. However, the scarcity of long-term observations limits insights into its source variations that may reflect emission controls. From September 2016 to December 2019, Fe in atmospheric fine particles (PM2.5) was measured in Beijing. Positive Matrix Factorization was used to apportion Fe sources. Results showed nearly 50% of Fe originated from anthropogenic sources, primarily industrial processes (30%) and coal combustion (17%). Although PM2.5 concentrations decreased significantly, the Fe component of PM2.5 did not show a significant decline. Instead, annual source contributions changed with dust source rising from 45% to 61%, while combustion sources decreased from 27% to 12%. Dust Fe aligned better with monthly MERRA-2 dust extinction coefficients than hourly data, suggesting the limitations of MERRA-2 in resolving hourly changes in dust. Anthropogenic Fe correlated with labile Fe, indicating anthropogenic emission reductions in Asia could decrease labile Fe supply to downwind oceans.

Concentration and sources of PM2.5 components especially black carbon (BC) in Beijing have changed significantly in recent years under the influence of numerous air pollution prevention and control policies. To evaluate the influence of control policies as well as the long-term variation of BC sources, hourly time-resolution BC measurements, with simultaneous measurements of multiple chemical species of PM2.5, were performed continuously from 2016 to 2019 in Beijing. Here, six major sources of BC including aged BC were resolved by Positive Matrix Factorization (PMF) with BC and other 18 species of PM2.5. The aged BC source resolved by PMF was validated by BC data from single-particle soot photometer (SP2) and single particle aerosol mass spectrometer (SPAMS) for the first time in Beijing. The results showed that BC concentration decreased significantly from 2016 to 2019 with approximately 46 % of the decrease attributed to coal burning reduction. The sources of BC apportioned by PMF were compared to the emission inventory of BC and the best correlation was found between coal BC from PMF and residential BC from emission inventory. However, the contribution of traffic BC (from 40 % to 53 %) and aged BC (from 12 % to 15 %) increased during the study period. The major source of BC pollution episodes has shifted from coal combustion to traffic source. This study provided observation-based evidence for the effectiveness of air pollution control policies on BC, and provided guidance for future BC source control in Beijing.

Ship emissions can significantly exacerbate air pollution in coastal cities, threatening public health; however, a low-sulfur fuel oil policy, which restricts sulfur content in marine fuels, can effectively mitigate such pollution-driven challenges. This study employed a high-resolution ship emission inventory to assess the impacts of the fuel oil switch on air quality and public health in Shanghai from 2017 to 2021. Results showed a 37.3 % reduction in primary PM2.5 emissions from ships, with even steeper declines of 46.7 and 91.6 % in Ni and V emissions, respectively, leading to notable air quality improvements. Health assessments revealed a reduction in premature mortality attributable to long-term exposure to the contribution of ships to atmospheric PM2.5 concentrations, with deaths decreasing from 630 cases in 2017 to 481 in 2021. Similarly, short-term exposure-related deaths fell from 43 to 29. The port and waterfront areas experienced the most pronounced health benefits. The non-carcinogenic risks posed by trace metals (Ni and V), which were detected along the Huangpu River in 2017, dropped to 0.1 by 2021. Nonetheless, the carcinogenic risk from V persisted as a concern for adults in 2021. An analysis of ship-influenced episodes showed that population-weighted concentrations and short-term premature mortality decreased by over 50 % in densely populated areas and key ports. Despite the low population density in port areas such as Wusongkou and Waigaoqiao, the human health risks linked to ship emissions remained significant. This study demonstrates the effectiveness of low-sulfur fuel oil policy in reducing emissions and health risks, providing a scientific basis for refined pollution control strategies in port cities.

Hourly-resolution chemical characterization of PM2.5 exposure remains a significant challenge in exposure science, despite its critical importance for accurate health impact assessment. Current literature predominantly focuses on daily or annual PM2.5 metrics, as conventional sampling methods typically require extended collection periods to accumulate sufficient mass for chemical analysis. This study introduces the Personal Exposure Sampler (PES), a compact and portable device for personal PM2.5 exposure assessment. It enables high-temporal resolution measurements and chemical speciation. This innovative sampler employs a sequential sampling mechanism that alternates among six sampling spots on a single 47 mm filter, enhancing particle collection efficiency for analysis while maintaining portability for personal exposure studies. Laboratory validation confirmed the impactor effectively achieved a 2.5  μm aerodynamic cut off. In parallel, chamber tests using nebulized NaCl particles showed strong agreement between the PES and a federal reference method (FRM) sampler, with a correlation coefficient of R2 = 0.99. Field tests demonstrated excellent agreement with FRM samplers, with micro-synchrotron radiation X-ray fluorescence analysis for six metals (R2 = 0.88) and gas chromatography (GC) coupled with a temperature-programmable inlet and time-of-flight mass spectrometry (ToF-MS) for five polycyclic aromatic hydrocarbons (PAHs) (R2 = 0.85). A pilot study with participants following different activity patterns revealed distinct exposure profiles across various microenvironments at hourly resolution, which conventional personal exposure sampling cannot achieve. This technology addresses a critical gap in personal exposure instrumentation, improving our understanding of the health impacts of specific PM constituents and their temporal variability.