A review on advancements in atmospheric microplastics research: The pivotal role of machine learning.

Microplastics (MPs), recognized as emerging pollutants, pose significant potential impacts on the environment and human health. The investigation into atmospheric MPs is nascent due to the absence of effective characterization methods, leaving their concentration, distribution, sources, and impacts on human health largely undefined with evidence still emerging. This review compiles the latest literature on the sources, distribution, environmental behaviors, and toxicological effects of atmospheric MPs. It delves into the methodologies for source identification, distribution patterns, and the contemporary approaches to assess the toxicological effects of atmospheric MPs. Significantly, this review emphasizes the role of Machine Learning (ML) and Artificial Intelligence (AI) technologies as novel and promising tools in enhancing the precision and depth of research into atmospheric MPs, including but not limited to the spatiotemporal dynamics, source apportionment, and potential health impacts of atmospheric MPs. The integration of these advanced technologies facilitates a more nuanced understanding of MPs' behavior and effects, marking a pivotal advancement in the field. This review aims to deliver an in-depth view of atmospheric MPs, enhancing knowledge and awareness of their environmental and human health impacts. It calls upon scholars to focus on the research of atmospheric MPs based on new technologies of ML and AI, improving the database as well as offering fresh perspectives on this critical issue.

Gas Particle Partitioning of PAHs Emissions from Typical Solid Fuel Combustions as Well as Their Health Risk Assessment in Rural Guanzhong Plain, China.

Air pollutants from the incomplete combustion of rural solid fuels are seriously harmful to both air quality and human health. To quantify the health effects of different fuel-stove combinations, gas and particle partitioning of twenty-nine species of polycyclic aromatic hydrocarbons (PAHs) emitted from seven fuel-stove combinations were examined in this study, and the benzo (a) pyrene toxicity equivalent (BaPeq) and cancer risks were estimated accordingly. The results showed that the gas phase PAHs (accounting for 68-78% of the total PAHs) had higher emission factors (EFs) than particulate ones. For all combustion combinations, pPAHs accounted for the highest proportion (84.5% to 99.3%) in both the gas and particulate phases, followed by aPAHs (0.63-14.7%), while the proportions of nPAHs and oPAHs were much lower (2-4 orders of magnitude) than pPAHs. For BaPeq, particulate phase PAHs dominated the BaPeq rather than gas ones, which may be due to the greater abundance of 5-ring particle PAHs. Gas and particle pPAHs were both predominant in the BaPeq, with proportions of 95.2-98.6% for all combustion combinations. Cancer risk results showed a descending order of bituminous coal combustion (0.003-0.05), biomass burning (0.002-0.01), and clean briquette coal combustion (10-5-0.001), indicating that local residents caused a severe health threat by solid fuel combustion (the threshold: 10-4). The results also highlighted that clean briquette coal could reduce cancer risks by 1-2 orders of magnitude compared to bulk coal and biomass. For oPAH, BcdPQ (6H-benzo(c,d)pyrene-6-one) had the highest cancer risk, ranging from 4.83 × 10-5 to 2.45 × 10-4, which were even higher than the total of aPAHs and nPAHs. The dramatically high toxicity and cancer risk of PAHs from solid fuel combustion strengthened the necessity and urgency of clean heating innovation in Guanzhong Plain and in similar places.