An overview of atmospheric aerosol and their effects on human health

Understanding secondary particles in a regional site of Yangtze River Delta: Insights from mass spectrometric measurement

Submicron particulate matter (PM1) poses significant risks to health risks and global climate. In this study, secondary organic aerosols (SOA) and inorganic compositions were examined for their physicochemical characteristics and evolution using high-resolution aerosol instruments in Changzhou over one-month period. The results showed that transport accompanied by regional static conditions leaded to the occurrence of heavy pollution. In addition, regional generation and local emissions also leaded to the occurrence of light and moderate pollution during the observation period in Changzhou. Organic aerosols (OA) and nitrate (NO3-) accounted for 45 % and 23 % of PM1, respectively. The increase in PM1 was dominated by the contribution of NO3- and OA. SOA was dominance in OA (63 % with 40 % MO-OOA), which was higher than primary organic aerosols (POA). Besides, photochemical reactions and the high oxidizing nature of the urban atmosphere promoted the production of OA, especially MO-OOA in Changzhou. Our results highlight that secondary particles contribute significantly to PM pollution in Changzhou, underlining the importance of controlling emissions of gaseous precursors, especially under high oxidation conditions.

Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China

BACKGROUND

The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome.

METHODS AND RESULTS

A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05).

CONCLUSIONS

Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.

Unveiling global land fine- and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data

Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode Aerosol Optical Depth (FAOD) and Coarse-Mode Aerosol Optical Depth (CAOD) methods have drawbacks including inaccuracies, low spatial coverage, and limited temporal duration. To overcome these issues, we developed new global-scale FAOD and CAOD from 2005 to 2020 using a novel deep learning model capable of the synergistic retrieval of two aerosol sizes. After validation with the aerosol robotic network (AERONET) and sky radiometer network (SKYNET), the new monthly FAOD and CAOD showed significant improvements in accuracy and spatial coverage. From 2005 to 2020, the new data showed that China had the greatest decrease in FAOD and CAOD. In contrast, India and South Latin America had a significant increase in FAOD versus North Africa in CAOD. FAOD in the regions of Argentina, Paraguay, and Uruguay in South America have shown an upward trend. The results reveal that FAOD and CAOD display distinct patterns of change in the same regions, particularly on the west coast of the United States where FAOD is increasing, while CAOD is decreasing. Aside from the year 2020 due to the global COVID-19 pandemic, the analysis showed that although China has seen at least an +85% increase in energy consumption and urban expansion in 2019 compared to 2005 due to the needs of development and construction, the implementation of China's air pollution control policies has led to a significant decrease in FAOD (-46%) and CAOD (-65%) after 2013. This research enriches our comprehension of global fine and coarse aerosol patterns, additional investigations are needed to determine the potential global implications of these changes.