Seasonal variation of chemical composition and source apportionment of PM2.5 in Pune, India

Variations in the concentration, source activity, and atmospheric processing of PM2.5-associated water-soluble ionic species over Jammu, India

Concentrations, sources, and atmospheric processing of water-soluble ionic species associated with PM_2.5 collected from 2015 to 2017 were studied in Jammu, an urban location in the North-Western Himalayan Region (NWHR). Being ecologically sensitive and sparsely studied for dynamics in PM_2.5 and associated WSIS, the present study is important for developing robust air pollution abatement strategies for the air-shed of NWHR. Twenty-four hourly PM_2.5 samples were collected on weekly basis at a receptor site and analyzed for WSIS using ion chromatography system. On annual basis, total sum of WSIS (ΣWSIS) contributed about 28.5% of PM_2.5, where the contribution of sulfate-nitrate-ammonium, a proxy for secondary inorganic aerosols (SIA), was found to be 18.7% of PM_2.5. The ΣWSIS and PM_2.5 concentration showed a seasonal cycle with the maximum concentration during winters and the minimum in summers. Mass fraction of ΣWSIS in PM_2.5 showed an anti-phase seasonal pattern indicating more source activity during summers. Season-wise, dominant WSIS constituting PM_2.5 were NO₃^-, SO₄^2-, NH₄⁺, and K⁺ during winters; whereas summer was marked with dominant contributions from SO₄^2-, NH₄⁺, Ca²⁺, and K⁺. Seasonal variability exhibited among SIA constituents underscored the crucial role of air temperature and relative humidity regime. It was observed that nss-K⁺ + NH₄⁺ were sufficient to neutralize most of the acidic species arising from precursor gases (NO_x and SO_x). Using principal component analysis, five major sources and processes, viz. (a) biomass burning activities, (b) secondary inorganic aerosol formation, (c) input from re-suspended dust, (d) transported dust, and (e) fertilizer residue, were identified for the emissions of PM_2.5-associated WSIS over Jammu. In future studies, impacts of dry and/or wet deposition of aerosol-associated WSIS on the crop productivity in the region should be studied.

Property-activity relationship between physicochemical properties of PM2.5 and their activation of NLRP3 inflammasome

Air pollution is becoming severe environment factor affecting human health. More and more research has indicated that fine particulate matter (PM_2.5) plays a critical role in causing pulmonary inflammation or fibrosis, which potentially is ascribed to the activation of nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3) inflammasome. However, the underlying property-activity relationship between the physicochemical properties of PM_2.5 and their activation of NLRP3 inflammasome remains unclear. Herein, various ways, such as metal chelation, organic extraction, ROS consumption, charge neutralization and particle dispersion, were applied to interfere with the effects of metal ion, polycyclic aromatic hydrocarbons (PAHs), reactive oxygen species (ROS), charge and size. It was found that aggregated size and PAHs could activate the NLRP3 inflammasome through lysosome rupture and potassium efflux, respectively. Metal ion, PAHs and surface ROS could also activate the NLRP3 inflammasome through mitochondrial ROS production. However, neutralization of PM_2.5 with the negative surface charge could not relieve the activation of NLRP3 inflammasome. Furthermore, oropharyngeal aspiration of various modified PM_2.5 were adopted to explore their effects on lung fibrosis, which showed the consistent results with those in cellular levels. Removal of metal ion, PAHs and ROS as well as reduction of size of PM_2.5 could reduce collagen deposition in the lung tissue of mice, while the charge neutralization of PM_2.5 increased this collagen deposition. This study provides great insights to clarify the property-activity relationship of PM_2.5.

Chemical Characteristics of Major Inorganic Ions in PM2.5 Based on Year-Long Observations in Guiyang, Southwest China—Implications for Formation Pathways and the Influences of Regional Transport

Sulfate, nitrate and ammonium (SNA) are the dominant components of water-soluble ions (WSIs) in PM2.5, which are of great significance for understanding the sources and transformation mechanisms of PM2.5. In this study, daily PM2.5 samples were collected from September 2017 to August 2018 within the Guiyang urban area and the concentrations of the major WSIs in the PM2.5 samples were characterized. The results showed that the average concentration of SNA (SO42−, NO3−, NH4+) was 15.01 ± 9.35 μg m−3, accounting for 81.05% (48.71–93.76%) of the total WSIs and 45.33% (14.25–82.43%) of the PM2.5 and their possible chemical composition in PM2.5 was (NH4)2SO4 and NH4NO3. The highest SOR (sulfur oxidation ratio) was found in summer, which was mainly due to the higher temperature and O3 concentrations, while the lowest NOR (nitrogen oxidation ratio) found in summer may ascribe to the volatilization of nitrates being accelerated at higher temperature. Furthermore, the nitrate formation was more obvious in NH4+-rich environments so reducing NH3 emissions could effectively control the formation of nitrate. The results of the trajectory cluster analysis suggested that air pollutants can be easily enriched over short air mass trajectories from local emission sources, affecting the chemical composition of PM2.5.

Levels and sources of organic compounds in fine ambient aerosols over National Capital Region of India

The study presents the spatial and temporal variation of fine ambient aerosols (PM_2.5) over National Capital Region (NCR), India, during January to June 2016. The investigation includes three sampling sites, one in Delhi and two in the adjoining states of Delhi (Uttar Pradesh and Haryana), across NCR, India. The average PM_2.5 concentration was highest for Delhi (128.5 ± 51.5 μg m^-3) and lowest for Mahendragarh, Haryana (74.5 ± 28.7 μg m^-3), during the study period. Seasonal variation was similar for all the sites with highest concentration during winter and lowest in summer. PM_2.5 samples were analysed for organic compounds using gas chromatograph (GC). The concentration of three organic compound classes, n-alkanes (C11-C35), polycyclic aromatic hydrocarbons (PAHs), and phthalates, present in PM_2.5 samples has been reported. Diagnostic ratios for n-alkanes demonstrated that biogenic emissions were dominant over Mahendragarh while major contributions were observed from petrogenic emissions over Delhi and Modinagar, Uttar Pradesh. Molecular diagnostic ratios were calculated to distinguish between different sources of PAHs, which revealed that the fossil fuel combustion (diesel and gasoline emissions), traffic emissions, and biomass burning are the major source contributors. Health risk associated with human exposure of phthalates and PAHs was also assessed as daily intake (DI, ng kg^-1 day^-1) and lung cancer risk, respectively. Backward trajectory analysis explained the local, regional, and long-range transport routes of PM_2.5 for all sites. Principal component analysis (PCA) results summarized that the vehicular emissions, biomass burning, and plastic burning were the major sources of the PAHs and phthalates over the sampling sites.

The contribution of socioeconomic factors to PM2.5 pollution in urban China

PM_2.5 pollution poses severe health risks to urban residents in low and middle-income countries. Existing studies have shown that the problem is affected by multiple socioeconomic factors. However, the relative contribution of these factors is not well understood, which sometimes leads to controversial controlling measures. In this study, we quantified the relative contribution of different socioeconomic factors, including the city size, industrial activities, and residents' activities, to PM_2.5 pollution in urban China between 2014 and 2015 by using structural equation model (SEM). Our results showed that industrial activities contributed more to PM_2.5 pollution than other factors. The city size and residents' activities also had significant impacts on PM_2.5 pollution. The combined influence of all socioeconomic factors could explain between 44% and 48% of variation in PM_2.5 pollution, which indicated the existence of influences from other factors such as weather conditions and outside sources of pollutants. Findings from our study can contribute to a more comprehensive understanding of the socioeconomic causes of PM_2.5 pollution.