We investigated aerosol composition and sources and the interaction between secondary organic aerosol (SOA) and clouds at a regional mountain site in southeastern China. Clouds efficiently scavenge more oxidized SOA; however, cloud evaporation leads to the production of less oxidized SOA. The unexpectedly high presence of nitrate in aerosol particles indicates that nitrate formed in polluted areas has undergone interactions with clouds, significantly influencing the regional background site.

Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM_2.5, a typical air pollutant. The results will help to improve numerical models.

We investigated short-term source apportionment of PM_2.5 utilizing rolling positive matrix factorization (PMF) and online PM chemical speciation data, which included source-specific organic tracers collected over a period of 37 d during the winter of 2019–2020 in suburban Shanghai, China. The findings highlight that by imposing constraints on the primary source profiles, short-term PMF analysis successfully replicated both the individual primary sources and the total secondary sources.

Environmental conditions during dust are usually not favorable for secondary aerosol formation. However in this study, an unusual dust event was captured in a Chinese mega-city and showed “anomalous” meteorology and a special dust backflow transport pathway. The underlying formation mechanisms of secondary aerosols are probed in the context of this special dust event. This study shows significant implications for the varying dust aerosol chemistry in the future changing climate.

In this study, 130 OS species were quantified in ambient fine particulate matter (PM_2.5) collected in urban and suburban Shanghai (East China) in the summer of 2021. The daytime OS formation was concretized based on the interactions among OSs, ultraviolet (UV), ozone (O₃), and sulfate. Our finding provides field evidence for the influence of photochemical process and anthropogenic sulfate on OS formation and has important implications for the mitigation of organic particulate pollution.

Hourly elemental carbon (EC) and NO_x were continuously measured for 5 years (2016–2020) at a sampling site near a highway in western Shanghai. We use a machine learning model to rebuild the measured EC and NO_x, and a business-as-usual (BAU) scenario was assumed in 2020 and compared with the measured EC and NO_x.

Based on a field campaign in a suburban area of Shanghai during summer 2021, we calculated formaldehyde (HCHO) production rates from 24 volatile organic compounds (VOCs). In addition, HCHO photolysis, reactions with OH radicals, and dry deposition were considered for the estimation of HCHO loss rates. Our results reveal the key precursors of HCHO and suggest that HCHO wet deposition may be an important loss term on cloudy and rainy days, which needs to be further investigated.

Limited knowledge is available on volatile organic compound (VOC) multi-site research of different land-use types at city level. This study performed a concurrent multi-site observation campaign on the three typical land-use types of Shanghai, East China. The results showed that concentrations, sources and ozone and secondary organic aerosol formation potentials of VOCs varied with the land-use types.

The particle matter (PM_2.5) at the top of the 632 m high Shanghai Tower was found to be higher than the surface from June to October due to unexpected larger PM_2.5 levels during early to middle afternoon at Shanghai Tower. We suppose the significant chemical production of secondary species existed in the mid-upper planetary boundary layer. We found a high nitrate concentration at the tower site for both daytime and nighttime in winter, implying efficient gas-phase and heterogeneous formation.

Using artificial neural network modeling and an explainable analysis approach, natural surface emissions (NSEs) were identified as a main driver of gaseous elemental mercury (GEM) variations during the COVID-19 lockdown. A sharp drop in GEM concentrations due to a significant reduction in anthropogenic emissions may disrupt the surface–air exchange balance of Hg, leading to increases in NSEs. This implies that NSEs may pose challenges to the future control of Hg pollution.

We develop a new algorithm to get the vertical mass concentration profiles of fine aerosol components based on the synergy of ground-based remote sensing for the first time. The comparisons with in situ observations and chemistry transport models validate the performance of the algorithm. Uncertainties caused by input parameters are also assessed in this paper. We expected that the algorithm can provide a new idea for lidar inversion and promote the development of aerosol component profiles.

In this study, we report the long-term measurement of organic carbon (OC) and elementary carbon (EC) in PM_2.5 with hourly time resolution conducted at a regional site in Shanghai from 2016 to 2020. The results from this study provide critical information about the long-term trend of carbonaceous aerosol, in particular secondary OC, in one of the largest megacities in the world and are helpful for developing pollution control measures from a long-term planning perspective.

In this paper, we develop an online data coupled assimilation system (NAQPMS-PDAF) with the Eulerian atmospheric chemistry-transport model. NAQPMS-PDAF allows efficient use of large computational resources. The application and performance of the system are investigated by assimilating 1 month of vertical aerosol observations. The results show that NAQPMS-PDAF can significantly improve the performance of aerosol vertical structure simulation and reduce the uncertainty to a large extent.

Particulate nitrate plays an important role in wintertime haze pollution in eastern China, yet quantitative constraints on detailed nitrate formation mechanisms remain limited. Here we quantified the contributions of the heterogeneous N₂O₅ hydrolysis (66 %) and gas-phase OH + NO₂ reaction (32 %) to nitrate formation in this region and identified the atmospheric oxidation capacity (i.e., availability of O₃ and OH radicals) as the driving factor of nitrate formation from both processes.

Recently, high O₃ concentrations were frequently observed in rural areas of the Yangtze River Delta (YRD) region under stagnant conditions. Using an online measurement and observation-based model, we investigated the budget of RO_x radicals and the influence of isoprene chemistry on O₃ formation. Our results underline that isoprene chemistry in the rural atmosphere becomes important with the participation of anthropogenic NO_x.

The uncertainties in mercury emissions are much larger from natural sources than anthropogenic sources. A method was developed to quantify the contributions of natural surface emissions to ambient GEM based on PMF modeling. The annual GEM concentration in eastern China showed a decreasing trend from 2015 to 2018, while the relative contribution of natural surface emissions increased significantly from 41 % in 2015 to 57 % in 2018, gradually surpassing those from anthropogenic sources.