Seasonal characteristics of aerosols (PM2.5 and PM10) and their source apportionment using PMF: A four year study over Delhi, India

Study of secondary organic aerosol formation and aging using ambient air in an oxidation flow reactor during high pollution events over Delhi

Secondary aerosols constitute a significant fraction of atmospheric aerosols, yet our understanding of their formation mechanism and fate is very limited. In this work, the secondary organic aerosol (SOA) formation and aging of ambient air of Delhi are studied using a potential aerosol mass (PAM) reactor, an oxidation flow reactor (OFR), coupled with aerosol chemical speciation monitor (ACSM), proton transfer reaction time of flight mass spectrometer (PTR-ToF-MS), and scanning mobility particle sizer with counter (SMPS + C). The setup mimics atmospheric aging of up to several days with the generation of OH radicals. Variations in primary volatile organic compounds (VOCs) and oxygenated volatile organic compounds (OVOCs) as a function of photochemical age were investigated. Primary VOCs such as benzene, toluene, xylene, trimethyl benzene, etc. decrease and OVOCs like formic acid, formaldehyde, acetone, ethanol, etc. increase substantially upon oxidation in OFR. The highest organic aerosol (OA) enhancement was observed for the 4.2 equivalent photochemical days of aging i.e., 1.84 times the ambient concentration, and net OA loss was observed at very high OH exposure, typically after 8.4 days of photochemical aging due to heterogeneous oxidation followed by fragmentation/evaporation. In ambient air, OA enhancement is highest during nighttime due to the high concentrations of precursor VOCs in the atmosphere. SMPS + C results demonstrated substantial new particle formation upon aging and decrement in preexisting aerosol mass. This is the first experimental study conducting an in-situ evaluation of potential SOA mass generated from the ambient aerosols in India.

Air quality challenges in Central Asian urban areas: a PM2.5 source apportionment analysis in Dushanbe, Tajikistan

This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM2.5 samples were collected during 2015-2016 and 2018-2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5 μg m-3. The PMF application identified eight sources of pollution that influenced PM2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018-2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons.

Comparative in vitro toxicological effects of water-soluble and insoluble components of atmospheric PM2.5 on human lung cells

Fine particulates in city air significantly impact human health, but the hazardous compositional mechanisms are still unclear. Besides the toxicity of environmental PM2.5 to in vitro human lung epithelial cells (A549), the independent cytotoxicity of PM2.5-bound water-soluble (WS-PM2.5) and water-insoluble (WIS-PM2.5) fractions were also compared by cell viability, oxidative stress (reactive oxygen species, ROS), and inflammatory injury (IL-6 and TNF-α). The cytotoxicity of PM2.5 varied significantly by sampling season and place, with degrees greater in winter and spring than in summer and autumn, related to corresponding trend of air PM2.5 level, and also higher in industrial than urban site, although their PM2.5 pollution levels were comparable. The PM2.5 bound metals (Ni, Cr, Fe, and Mn) may contribute to cellular injury. Both WS-PM2.5 and WIS-PM2.5 posed significant cytotoxicity, that WS-PM2.5 was more harmful than WIS-PM2.5 in terms of decreasing cell viability and increasing inflammatory cytokines production. In particular, industrial samples were usually more toxic than urban samples, and those from summer were generally less toxic than other seasons. Hence, in order to mitigate the health risks of PM2.5 pollution, the crucial targets might be components of heavy metals and soluble fractions, and sources in industrial areas, especially during the cold seasons.

Pollution characteristics, source apportionment, and health risk assessment of PM10 and PM2.5 in rooftop and kerbside environment of Lanzhou, NW China

To investigate air pollution in the kerbside environment and its associated human health risks, a study was conducted in Lanzhou during December 2018, as well as in April, June, and September 2019. The research aimed to characterize the composition of PM10 and PM2.5, including elements, ions, and carbonaceous components, at both rooftop and kerbside locations. Additionally, source apportionment and health risk assessment were conducted. The results showed that the average mass concentrations of PM10 on the rooftop were 176.01 ± 83.23 μg/m3, and for PM2.5, it was 94.07 ± 64.89 μg/m3. The PM10 and PM2.5 levels at the kerbside are 2.21 times and 1.79 times, respectively, greater than those on the rooftop. Moreover, the concentrations of elements, ions, and carbonaceous components in kerbside PM were higher than those at the rooftop location. Chemical mass closure analysis identified various sources, including organic matter, mineral dust, secondary ions, other ions, elements, and other components. In comparison to rooftop particulate matter (PM), mineral dust makes a more substantial contribution to kerbside PM. Secondary ions show an opposite trend, making a greater contribution to rooftop PM. The contribution of organic components within PM of the same particle size remains relatively consistent. The outcome of the health risk assessment indicates that Co, Cd, and As in PM within the kerbside and rooftop environments do not pose a notable carcinogenic risk. However, Al and Mn do present specific non-carcinogenic risks, particularly in the kerbside environment. Furthermore, children experience elevated non-carcinogenic risk compared to adults. These findings can serve as a scientific foundation for formulating policies within the local health department.

Insight Study of Trace Elements in PM2.5 During Nine Years in Delhi, India: Seasonal Variation, Source Apportionment, and Health Risks Assessment

This study investigated the concentrations, seasonal variations, sources, and human health risks associated with exposure to heavy elements (As, Al, Pb, Cr, Mn, Cu, Zn, and Ni) of PM2.5 at an urban location of Delhi (28° 38' N, 77° 10' E; 218 m amsl), India, from January 2013 to December 2021. The average mass concentration of PM2.5 throughout the study period was estimated as 127 ± 77 µg m-3, which is exceeding the National Ambient Air Quality Standards (NAAQS) limit (annual: 40 µg m-3; 24 h: 60 µg m-3). The seasonal mass concentrations of PM2.5 exhibited at the order of post-monsoon (192 ± 110 µgm-3) > winter (158 ± 70 µgm-3) > summer (92 ± 44 µgm-3) and > monsoon (67 ± 32 µgm-3). The heavy elements, Al (1.19 µg m-3), Zn (0.49 µg m-3), Pb (0.43 µg m-3), Cr (0.21 µg m-3), Cu (0.21 µg m-3), Mn (0.07 µg m-3), and Ni (0.14 µg m-3) exhibited varying concentrations in PM2.5, with the highest levels observed in the post-monsoon season, followed by winter, summer, and monsoon seasons. Six primary sources throughout the study period, contributing to PM2.5 were identified by positive matrix factorization (PMF), such as dust (paved/crustal/soil dust: 29.9%), vehicular emissions (17.2%), biomass burning (15.4%), combustion (14%), industrial emissions (14.2%), and Br-rich sources (9.2%). Health risk assessments, including hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR), were computed based on heavy elements concentrations in PM2.5. Elevated HQ values for Cr and Mn linked with adverse health impacts in both adults and children. High carcinogenic risk values were observed for Cr in both adults and children during the winter and post-monsoon seasons, as well as in adults during the summer and monsoon seasons. The combined HI value exceeding one suggests appreciable non-carcinogenic risks associated with the examined elements. The findings of this study provide valuable insights into the behaviour and risk mitigation of heavy elements in PM2.5, contributing to the understanding of air quality and public health in the urban environment of Delhi.

Atmospheric environment characteristic of severe dust storms and its impact on sulfate formation in downstream city

This study comprehensively investigated the impact of dust storms (DSs) on downstream cities, by selecting representative DS events. In this paper, we discussed the characteristics of meteorological conditions, air pollutants, PM2.5 components, and their influence on sulfate formation mechanisms. During DSs, strong winds, reaching speeds of up to 10 m/s, led to significant increases in PM10 and PM2.5, with maximum concentrations of 2684.5 and 429 μg/m3, respectively. Primary gaseous pollutants experienced substantial reductions, with decline rates of 48.1, 34.9, 36.8, and 9.0 % for SO2, NO2, NH3, and CO, respectively. Despite a notable increase in PM2.5 concentrations, only 7.6 % of the total mass of PM2.5 was attributed to ionic and carbonaceous components, a much lower value than observed before the DSs (77.3 %). Concentrations of Fe, Ti, and Mn exhibited increases by factors of 6.5-14.1, 10.4-17.0, and 1.6-4.7, respectively. In contrast to the significant decrease of >76.2 % in nitrogen oxidation ratio (NOR), sulfur oxidation ratio (SOR) remained at a relatively high level, displaying a strong positive correlation with high concentrations of Fe, Mn, and Ti. Quantitative analysis revealed an average increase of 0.187 and 0.045 μg/m3 in sulfate from natural sources and heterogeneous generation, respectively. The heterogeneous reaction on mineral dust was closely linked to atmospheric humidity, radiation intensity, the form of metal existence, and concentrations of it. High concentrations of titanium dioxide and iron‑manganese oxides in mineral dust promoted heterogeneous oxidation of SO2 through photocatalysis during the daytime and metal ion catalysis during the nighttime. This study establishes that the metal components in mineral dust promote heterogeneous sulfate formation, quantifies the yield of sulfate generated as a result, and provides possible mechanisms for heterogeneous sulfate formation.

Sources appointment and health risks of PM2.5-bound trace elements in a coastal city of southeastern China

To gain a comprehensive understanding of sources and health risks of trace elements in an area of China with high population densities and low PM2.5 concentrations, 15 trace elements (Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Sn, Ba, Pb) in PM2.5 were monitored from December 2020 to November 2021 in a representative city, Xiamen. The concentrations of trace elements in Xiamen displayed an obvious seasonal variation and were dominated by K, Fe, Al, Ca and Zn. Based on Positive Matrix Factorization analysis, source appointment revealed that the major sources of trace elements in Xiamen were traffic, dust, biomass and firework combustion, industrial manufacture and shipping emission. According to health risk assessment combined with the source appointment results, it indicated that the average noncarcinogenic risk was below the threshold and cancer risk of four hazardous metals (Cr, Ni, As, Pb) exceeded the threshold (10-6). Traffic-related source had almost half amount of contribution to the health risk induced by PM2.5-bound trace elements. During the dust transport period or Spring Festival period, the health risks exceeded an acceptable threshold even an order of magnitude higher, suggesting that the serious health risks still existed in low PM2.5 environment at certain times. Health risk assessment reminded that the health risk reduction in PM2.5 at southeastern China should prioritize traffic-related hazardous trace elements and highlighted the importance of controlling vehicles emissions in the future.

Sewage treatment plant dust: An emerging concern for heavy metals-induced health risks in urban area

Metal-related pollution from dust is a significant source of toxic elements in urban areas. The present study aimed to assess the health risk posed by heavy metals present in dust samples to the people residing near the Sewage Treatment Plant (STP). Dust samples were collected from an STP with a capacity of 130 mega litres per day (MLD). Data analysis indicated highly contaminated STP dust with Enrichment Factor (EF) suggesting an anthropogenic origin of selected metals (As, Co, Al, Cu, Cr, Cd, Ba, Pb, Ni, Mn). The contamination factor values of metals highlighted a greater degree of contamination in the selected area. Notably, a strong correlation (>0.5) was observed between metals. The EF value was found to be >40 indicating high enrichment for all the metals except Fe. In-depth chemical analysis and health risk assessments were conducted, revealing an Excess Lifetime Cancer Risk (ELCR) value of 1 × 10-6 and HQ (Hazard Quotient) value of 1. These values are significantly exceeding the safe limits for both children and adults which could develop cancerous properties in human beings. In an effort to reduce toxicity, dust samples were also subjected to vermicomposting treatment to assess the potential effectiveness of the earthworms. The EF value of vermicomposted dust came out to be lower than the untreated one. The Hazard Quotient (HQ) values for adults exhibited the following pattern of HQing > HQder > HQinh (indicating that the Hazard Quotient from ingestion is greater than that from dermal contact, which is in turn greater than inhalation). This investigation offers crucial insights into the increased risks of cancerous and non-cancerous ailments for individuals living or working in proximity to STPs. This research also highlights the pressing need to implement effective measures for safeguarding public health and mitigating environmental pollution in urban areas.

Identifying urban emission sources and their contribution to the oxidative potential of fine particulate matter (PM2.5) in Kuwait

In this study, we investigated the seasonal variations, chemical composition, sources, and oxidative potential of ambient PM2.5 (particles with a diameter of less than 2.5 μm) in Kuwait City. The sampling campaign was conducted within the premises of Kuwait Institute for Scientific Research from June 2022 to May 2023, covering different seasons throughout the year. The personal cascade impactor sampler (PCIS) operated at flow rate of 9 L/min was employed to collect weekly PM2.5 samples on PTFE and quarts filters. These collected samples were analyzed for carbonaceous species (i.e., elemental and organic carbon), metals and transition elements, inorganic ions, and DTT (dithiothreitol) redox activity. Furthermore, principal component analysis (PCA) and multi-linear regression (MLR) were used to identify the predominant emission sources and their percentage contribution to the redox activity of PM2.5 in Kuwait. The results of this study highlighted that the annual-averaged ambient PM2.5 mass concentrations in Kuwait (59.9 μg/m3) substantially exceeded the World Health Organization (WHO) guideline of 10 μg/m3. Additionally, the summer season displayed the highest PM2.5 mass concentration (75.2 μg/m3) compared to other seasons, primarily due to frequent dust events exacerbated by high-speed winds. The PCA identified four primary PM2.5 sources: mineral dust, fossil fuel combustion, road traffic, and secondary aerosols. The mineral dust was found to be the predominant source, contributing 36.1% to the PM2.5 mass, followed by fossil fuel combustion and traffic emissions with contributions of 23.7% and 20.3%, respectively. The findings of MLR revealed that road traffic was the most significant contributor to PM2.5 oxidative potential, accounting for 47% of the total DTT activity. In conclusion, this comprehensive investigation provides essential insights into the sources and health implications of PM2.5 in Kuwait, underscoring the critical need for effective air quality management strategies to mitigate the impacts of particulate pollution in the region.

Source apportionment of PM2.5 using PMF combined online bulk and single-particle measurements: Contribution of fireworks and biomass burning

Fireworks (FW) could significantly worsen air quality in short term during celebrations. Due to similar tracers with biomass burning (BB), the fast and precise qualification of FW and BB is still challenging. In this study, online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM2.5 and specific chemical species by positive matrix factorization (PMF) during the Chinese New Year in Hong Kong in February 2013. With combined information, fresh/aged FW (abundant 140K2NO3+ and 213K3SO4+ formed from 113K2Cl+ discharged by fresh FW) can be extracted from the fresh/aged BB sources, in addition to the Second Aerosol, Vehicles + Road Dust, and Sea Salt factors. The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region. The fresh BB/FW contributed 39.2% and 19.6% to PM2.5 during the Lunar Chinese New Year case. However, the contributions of aged FW/BB enhanced in the last two episodes due to the aging process, evidenced by high contributions from secondary aerosols. Generally, the fresh BB/FW showed more significant contributions to nitrate (35.1% and 15.0%, respectively) compared with sulfate (25.1% and 5.9%, respectively) and OC (14.8% and 11.1%, respectively) on average. In comparison, the aged FW contributed more to sulfate (13.4%). Overall, combining online bulk and single-particle measurement data can combine both instruments' advantages and provide a new perspective for applying source apportionment of aerosols using PMF.

Source identification and health risk assessment of PM2.5 in urban districts of Hanoi using PCA/APCS and UNMIX

Comparing results obtained by different models with different physical assumptions and constraints for source apportionment is important for better understanding the sources of pollutants. Source apportionment of PM2.5 measured at three sites located in inner urban districts of Hanoi was performed using two receptor models, UNMIX and principal component analysis with absolute principle component score (PCA/APCS). A total of 78 daily samples were collected consecutively during the dry and wet seasons in 2019 and 2020. The average PM2.5 concentration (66.26 µg/m3 ± 29.70 µg/m3 with a range from 23.57 to 169.04 µg/m3) observed in Hanoi metropolitan exceeded the National Ambient Air Quality standard QCVN 05:2013/BTNMT (50 µg/m3). Both UNMIX and PCA/APCS expressed comparable ability to reproduce measured PM2.5 concentrations. Additionally, both models identified similar potential sources of PM2.5 including traffic-related emissions, scrap metal recycling villages, crustal mixed with construction sources, coal combustion mixed with industry, and biomass burning. Both UNMIX and PCA/APCS confirmed that traffic-related emission was the most influential PM2.5 with a high percentage contribution of 59% and 55.97%, respectively. All the HQ and Cr values for both children and adults of toxic elements apportioned by both UNMIX and PCA/APCS in every source were within the acceptable range.

Identification of sources of coarse mode aerosol particles (PM10) using ATR-FTIR and SEM-EDX spectroscopy over the Himalayan Region of India

This study attempts to examine the morphological, elemental and physical characteristics of PM10 over the Indian Himalayan Region (IHR) using FTIR and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis. The study aimed at source identification of PM10 by exploring the inorganic ions, organic functional groups, morphology and elemental characteristics. The pollution load of PM10 was estimated as 63 ± 22 μg m-3; 53 ± 16 μg m-3; 67 ± 26 μg m-3 and 55 ± 11 μg m-3 over Mohal-Kullu, Almora, Nainital and Darjeeling, respectively. ATR-FTIR spectrum analysis revealed the existence of inorganic ions (SiO44-, TiO2, SO42-, SO3-, NO3-, NO2-, CO32-, HCO3-, NH4+) and organic functional groups (C-C, C-H, C=C, C≡C, C=O, N-H, C≡N, C=N, O-H, cyclic rings, aromatic compounds and some heterogeneous groups) in PM10 which may arise from geogenic, biogenic and anthropogenic sources. The morphological and elemental characterization was performed by SEM-EDX, inferring for geogenic origin (Al, Na, K, Ca, Mg and Fe) due to the presence of different morphologies (irregular, spherical, cluster, sheet-like solid deposition and columnar). In contrast, particles having biogenic and anthropogenic origins (K, S and Ba) have primarily spherical with few irregular particles at all the study sites. Also, the statistical analysis ANOVA depicts that among all the detected elements, Na, Al, Si, S and K are site-specific in nature as their mean of aw% significantly varied for all the sites. The trajectory analysis revealed that the Uttarakhand, Jammu and Kashmir, the Thar Desert, Himachal Pradesh, Pakistan, Afghanistan, Nepal, Sikkim, the Indo-Gangetic Plain (IGP) and the Bay of Bengal (BoB) contribute to the increased loading of atmospheric pollutants in various locations within the IHR.

Chemical characteristics, morphology and source apportionment of PM10 over National Capital Region (NCR) of India

The present study frames the physico-chemical characteristics and the source apportionment of PM10 over National Capital Region (NCR) of India using the receptor model's Positive Matrix Factorization (PMF) and Principal Momponent Mnalysis/Absolute Principal Component Score-Multilinear Regression (PCA/APCS-MLR). The annual average mass concentration of PM10 over the urban site of Faridabad, IGDTUW-Delhi and CSIR-NPL of NCR-Delhi were observed to be 195 ± 121, 275 ± 141 and 209 ± 81 µg m-3, respectively. Carbonaceous species (organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC)), elemental constituents (Al, Ti, Na, Mg, Cr, Mn, Fe, Cu, Zn, Br, Ba, Mo Pb) and water-soluble ionic components (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) of PM10 were entrenched to the receptor models to comprehend the possible sources of PM10. The PMF assorted sources over Faridabad were soil dust (SD 15%), industrial emission (IE 14%), vehicular emission (VE 19%), secondary aerosol (SA 23%) and sodium magnesium salt (SMS 17%). For IGDTUW-Delhi, the sources were SD (16%), VE (19%), SMS (18%), IE (11%), SA (27%) and VE + IE (9%). Emission sources like SD (24%), IE (8%), SMS (20%), VE + IE (12%), VE (15%) and SA + BB (21%) were extracted over CSIR-NPL, New Delhi, which are quite obvious towards the sites. PCA/APCS-MLR quantified the similar sources with varied percentage contribution. Additionally, catalogue the Conditional Bivariate Probability Function (CBPF) for directionality of the local source regions and morphology as spherical, flocculent and irregular were imaged using a Field Emission-Scanning Electron Microscope (FE-SEM).

Wintertime investigation of PM10 concentrations, sources, and relationship with different meteorological parameters

Meteorological factors play a crucial role in affecting air quality in the urban environment. Peshawar is the capital city of the Khyber Pakhtunkhwa province in Pakistan and is a pollution hotspot. Sources of PM10 and the influence of meteorological factors on PM10 in this megacity have yet to be studied. The current study aims to investigate PM10 mass concentration levels and composition, identify PM10 sources, and quantify links between PM10 and various meteorological parameters like temperature, relative humidity (RH), wind speed (WS), and rainfall (RF) during the winter months from December 2017 to February 2018. PM10 mass concentrations vary from 180 - 1071 µg m-3, with a mean value of 586 ± 217 µg m-3. The highest concentration is observed in December, followed by January and February. The average values of the mass concentration of carbonaceous species (i.e., total carbon, organic carbon, and elemental carbon) are 102.41, 91.56, and 6.72 μgm-3, respectively. Water-soluble ions adhere to the following concentration order: Ca2+  > Na+  > K+  > NH4+  > Mg2+. Twenty-four elements (Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Co, Zn, Ga, Ge, As, Se, Kr, Ag, Pb, Cu, and Cd) are detected in the current study by PIXE analysis. Five sources based on Positive Matrix Factorization (PMF) modeling include industrial emissions, soil and re-suspended dust, household combustion, metallurgic industries, and vehicular emission. A positive relationship of PM10 with temperature and relative humidity is observed (r = 0.46 and r = 0.56, respectively). A negative correlation of PM10 is recorded with WS (r =  - 0.27) and RF (r =  - 0.46). This study's results motivate routine air quality monitoring owing to the high levels of pollution in this region. For this purpose, the establishment of air monitoring stations is highly suggested for both PM and meteorology. Air quality standards and legislation need to be revised and implemented. Moreover, the development of effective control strategies for air pollution is highly suggested.

Variation of PM2.5 and PM10 in emissions and chemical compositions in different seasons from a manure-belt laying hen house

Particulate matter (PM) emissions from animal houses and the corresponding hazard have raised increasing attention during recent years. In this study, a large-scale manure-belt laying hen house located in Beijing, China was selected as the experimental site for the study of the emission rates (ER) and chemical compositions of PM2.5 and PM10 in 3 seasons, namely, summer, autumn, and winter, to investigate their possible influences on ambient air quality and human health. The results showed that the mean ER from the hen house in summer, autumn, and winter were 9.0 ± 1.7, 2.4 ± 0.7, and 1.9 ± 0.7 mg hen-1 d-1 for PM2.5 (P < 0.05), and 30.7 ± 1.1, 12.8 ± 1.5, and 10.9 ± 0.9 mg hen-1 d-1 for PM10 (P < 0.05), respectively. Moreover, large amounts of secondary inorganic aerosols (SIA) were observed inside the house in summer, accounting for 11.4 and 9.6% of indoor PM2.5 and PM10 mass, respectively, compared with the value of <1.4% in autumn and winter. Among the 31 detected elements in indoor PM, arsenic concentration exceeded the threshold set in legislation. Zn had a notably high concentration of 3,403 to 4,432 ng m-3 in indoor PM10, which was 28 to 71 times higher than that in ambient PM10. The findings suggest that the poultry-raising house emit PM2.5 and PM10 containing SIA and toxic heavy-metal elements such as As and Zn to the ambient with much more emissions in summer than in autumn and winter. Considering the increasing development of poultry-raising farming in China, the potential hazard derived from the exhaust of PM2.5 and PM10 should be focused on, especially during summer.

Application of machine learning (individual vs stacking) models on MERRA-2 data to predict surface PM2.5 concentrations over India

The spatial coverage of PM2.5 monitoring is non-uniform across India due to the limited number of ground monitoring stations. Alternatively, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), is an atmospheric reanalysis data used for estimating PM2.5. MERRA-2 does not explicitly measure PM2.5 but rather follows an empirical model. MERRA-2 data were spatiotemporally collocated with ground observation for validation across India. Significant underestimation in MERRA-2 prediction of PM2.5 was observed over many monitoring stations ranging from -20 to 60 μg m-3. The utility of Machine Learning (ML) models to overcome this challenge was assessed. MERRA-2 aerosol and meteorological parameters were the input features used to train and test the individual ML models and compare them with the stacking technique. Initially, with 10% of randomly selected data, individual model performance was assessed to identify the best model. XGBoost (XGB) was the best model (r2 = 0.73) compared to Random Forest (RF) and LightGBM (LGBM). Stacking was then applied by keeping XGB as a meta-regressor. Stacked model results (r2 = 0.77) outperformed the best standalone estimate of XGB. Stacking technique was used to predict hourly and daily PM2.5 in different regions across India and each monitoring station. The eastern region exhibited the best hourly prediction (r2 = 0.80) and substantial reduction in Mean Bias (MB = -0.03 μg m-3), followed by the northern region (r2 = 0.63 and MB = -0.10 μg m-3), which showed better output due to the frequent observation of PM2.5 >100 μg m-3. Due to sparse data availability to train the ML models, the lowest performance was for the central region (r2 = 0.46 and MB = -0.60 μg m-3). Overall, India's PM2.5 prediction was good on an hourly basis compared to a daily basis using the ML stacking technique.

Molecular distribution, sources and potential health risks of fine particulate-bound polycyclic aromatic hydrocarbons during high pollution episodes in a subtropical urban city

Abundance of fine particulate-bound 16 priority polycyclic aromatic hydrocarbons (PAHs) was investigated to ascertain its sources and potential carcinogenic health risks in Varanasi, India. The city represents a typical urban settlement of South Asia having particulate exposure manyfold higher than standard with reports of pollution induced mortalities and morbidities. Fine particulates (PM2.5) were monitored from October 2019 to May 2020, with 32% of monitoring days accounting ≥100 μgm-3 of PM2.5 concentration, frequently from November to January (99% of monitoring days). The concentration of 16 priority PAHs varied from 24.1 to 44.6 ngm-3 (mean: 33.1 ± 3.2 ngm-3) without much seasonal deviations. Both low (LMW, 56%) and high molecular weight (HMW, 44%) PAHs were abundant, with Fluoranthene (3.9 ± 0.4ngm-3) and Fluorene (3.5 ± 0.3ngm-3) emerged as most dominating PAHs. Concentration of Benzo(a)pyrene (B(a)P, 0.5 ± 0.1ngm-3) was lower than the national standard as it contributed 13% of total PAHs mass. Diagnostic ratios of PAH isomers indicate predominance of pyrogenic sources including emissions from biomass burning, and both from diesel and petrol-driven vehicles. Source apportionment using receptor model revealed similar observation of major PAHs contribution from biomass burning and fuel combustion (54% of source contribution) followed by coal combustion for residential heating and cooking purposes (44%). Potential toxicity of B[a]P equivalence ranged from 0.003 to 1.365 with cumulative toxicity of 2.13ngm-3. Among the PAH species, dibenzo[h]anthracene contributed maximum toxicity followed by B[a]P, together accounting 86% of PAH induced carcinogenicity. Incremental risk of developing cancer through lifetime exposure (ILCR) of PAHs was higher in children (3.3 × 10-4) with 56% contribution from LMW PAHs, primarily through ingestion and dermal contact. Adults in contrast, were more exposed to inhale airborne PAHs with cumulative ILCR of 2.2 × 10-4. However, ILCR to PM2.5 exposure is probably underestimated considering unaccounted metal abundance thus, require source-specific control measures.

Evaluation of air quality and health risks associated with trace elements in respirable particulates (PM2.5) from Islamabad, Pakistan

Fine atmospheric particulates are associated with numerous environmental and health issues as they can penetrate deeply in the respiratory tract thereby adversely affecting the human health. This study aimed to investigate the concentrations of trace elements in the respirable (PM2.5) fraction of the atmospheric particulates and to understand their pollution status and health risks. The samples were collected from Islamabad, and the metals were extracted using HNO3 and HCl based extraction method. Atomic absorption spectroscopy was employed to quantify the concentrations of selected trace elements. PM2.5 exhibited considerable variations in their minimum (4.737 µg/m3) and maximum (108.1 µg/m3) levels. The significant contributors among the selected elements bound to PM2.5 were Ca (1016 ng/m3), K (759.8 ng/m3), Mg (483.0 ng/m3), Fe (469.7 ng/m3), and Zn (341.1 ng/m3), while Ag (0.578 ng/m3) was found at the lowest levels with an overall descending order: Ca > K > Mg > Fe > Zn > Cu > Pb > Ni > Cd > Mn > Sr > Cr > Co > Li > Ag. Multivariate PCA and CA identified industrial activities, combustion processes and automobile emissions as the main anthropogenic contributors to particulate pollution. Enrichment factors and geoaccumulation indices were computed to assess the pollution status. The results also revealed that among the trace elements, Cd showed extremely high contamination, followed by Ag, Zn, and Pb, which showed moderate to high contamination in the atmospheric particulates. Carcinogenic health risks from Pb and Ni were found to be within the safe limit (1.0 × 10-6); however, Cr, Co, and Cd exposure was linked to significant cancer risks. The present elemental levels in PM2.5 were also compared with the reported levels from other regions around the world.

Is there an EKC between economic growth and air pollutant emissions in SAARC countries? Evidence from disaggregated analysis

The manufacturing and construction (M&C) sector not only plays a vital role in promoting economic growth, but is also a significant contributor to global air pollution. Growing concerns regarding air pollutant emissions necessitate a more disaggregated (i.e., sectoral) investigation in order to identify the major contributors. This study employs aggregated and disaggregated data to determine the fundamental effects of economic growth (i.e., overall growth and sectoral growth) on air pollutant emissions (APE) (specifically, PM2.5 and PM10 released by the M&C sector) in SAARC economies between 1995 and 2018. It assesses the environmental Kuznets curve (i.e., inverted U-shaped and N-shaped) using the feasible generalized least squares (FGLS), panel-corrected standard errors (PCSE), and generalized method of moments (GMM) techniques. The sectoral analysis reveals the presence of an N-shaped EKC while the overall analysis indicates an inverted U-shaped EKC. Population, financial development (FD), and merchandise exports (MX) have no influence on the estimates. Population and FD increase APE in all models, whereas the effects of MX vary between models. As SAARC economies are capital-deficient, these economies can adopt unbalanced environmental protection policies. First, focus on major contributing sectors (e.g., M&C sector) to curb APE, then focus on less emitting sectors in turn. By implementing pollution reduction strategies on M&C sector activities, governments may reach their threshold (peak) points earlier than expected. A reduction in APE is impossible without rigorous monitoring and application. Being capital-deficient nations and given the collective nature of the problem, a Transboundary Haze/Pollution agreement is required to solve this issue.

Spatiotemporal variability and health risk assessment of PM2.5 and NO2 over the Indo-Gangetic Plain: A three years long study (2019-21)

Studying the spatiotemporal variability of pollutants is necessary to identify the pollution hotspots with high health risk and enable the agencies to implement pollution abatement strategies in a targeted manner. Present study reports the spatio-temporal variability and health risk assessment (HRA) of PM2.5 (Particulate matter with aerodynamic diameter <2.5μm) and NO2 over IGP from 2019-2021. The HRA is expressed as passively smoked cigarettes (PSC) for four different health outcomes i.e., low birth weight (LBW), percentage decreased lung function (DLF) in school aged children, lung cancer (LC), and cardiovascular mortality (CM). The findings confirm very high PM2.5 and NO2 mass concentrations and high health risk over middle IGP and Delhi as compared to upper and lower IGP. Within Delhi, north Delhi region is the most polluted and at highest risk as compared to central and south Delhi. The health risk associated with PM2.5 over IGP is highest for DLF, equivalent to 21.63 PSCs daily, followed by CM (11.69), LBW (8.27) and LC (6.94). For NO2, the health risk is highest for DLF (3.09 PSCs) and CM (2.95), followed by LC (1.47) and LBW (1.04). PM2.5 and NO2 concentrations, along with the associated health risks, are highest during the post-monsoon and winter seasons and lowest during the monsoon season.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM_2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM_2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM_2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM_2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM_2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM_2.5 (>95 μg/m³). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM_2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Stubble-burning activities in north-western India in 2021: Contribution to air pollution in Delhi

Stubble-burning in northern India is an important source of atmospheric particulate matter (PM) and trace gases, which significantly impact local and regional climate, in addition to causing severe health risks. Scientific research on assessing the impact of these burnings on the air quality over Delhi is still relatively sparse. The present study analyzes the satellite-retrieved stubble-burning activities in the year 2021, using the MODIS active fire count data for Punjab and Haryana, and assesses the contribution of CO and PM_2.5 from such biomass-burning activities to the pollution load in Delhi. The analysis suggests that the satellite-retrieved fire counts in Punjab and Haryana were the highest among the last five years (2016-2021). Further, we note that the stubble-burning fires in the year 2021 are delayed by ∼1 week compared to that in the year 2016. To quantify the contribution of the fires to the air pollution in Delhi, we use tagged tracers for CO and PM_2.5 emissions from fire emissions in the regional air quality forecasting system. The modeling framework suggests a maximum daily mean contribution of the stubble-burning fires to the air pollution in Delhi in the months of October-November 2021 to be around 30-35%. We find that the contribution from stubble burning activities to the air quality in Delhi is maximum (minimum) during the turbulent hours of late morning to afternoon (calmer hours of evening to early morning). The quantification of this contribution is critical from the crop-residue and air-quality management perspective for policymakers in the source and the receptors regions, respectively.

Chemical composition, oxidative potential and identifying the sources of outdoor PM2.5 after the improvement of air quality in Beijing

Air pollution poses a serious threat to human health. The implementation of air pollution prevention and control policies has gradually reduced the level of atmospheric fine particles in Beijing. Exploring the latest characteristics of PM_2.5 has become the key to further improving pollution reduction measures. In the current study, outdoor PM_2.5 samples were collected in the spring and summer of Beijing, and the chemical species, oxidative potential (OP), and sources of PM_2.5 were characterized. The mean PM_2.5 concentration during the entire study period was 41.6 ± 30.9 μg m^-3. Although the PM_2.5 level in summer was lower, its OP level was significantly higher than that in spring. SO₄^2-, NH₄⁺, EC, NO^3-, and OC correlated well with volume-normalized OP (OP_v). Strong positive correlations were found between OP_v and the following elements: Cu, Pb, Zn, Ni, As, Cr, Sn, Cd, Al, and Mn. Seven sources of PM_2.5 were identified, including traffic, soil dust, secondary sulfate, coal and biomass burning, oil combustion, secondary nitrate, and industry. Multiple regression analysis indicated that coal and biomass combustion, industry, and traffic were the main contributors to the OP_v in spring, while secondary sulfate, oil combustion, and industry played a leading role in summer. The source region analysis revealed that different pollution sources were related to specific geographic distributions. In addition to local emission reduction policies, multi-provincial cooperation is necessary to further improve Beijing's air quality and reduce the adverse health effects of PM_2.5.

Mass, composition, and sources of particulate matter in residential and traffic sites of an urban environment

Present study aims to assess the mass, composition, and sources of PM₁₀ and PM_2.5 (particulate matter having aerodynamic diameter less than or equal to 10 and 2.5 µm aerodynamic diameter, respectively) in Vellore city. Seasonal samples collected in traffic and residential sites were analyzed for ions, elements, organic carbon (OC), and elemental carbon (EC). Source apportionment of PM₁₀ and PM_2.5 is carried out using Chemical Mass Balance, Unmix, Positive Matrix Factorization and Principal Component Analysis receptor models. Results showed that traffic site had higher annual concentration (PM_2.5 = 62 ± 32 and PM₁₀ = 112 ± 23 µg m^-3) when compared to residential site (PM_2.5 = 54 ± 22 and PM₁₀ = 98 ± 20 µg m^-3). Al, Ca, Fe, K, and Mg known to have crustal origin dominated the element composition irrespective of PM size and sampling site. Among ions, SO₄^2- accounted highest in both sites with an average of 70 and 60% to PM_2.5 and PM₁₀ ionic mass. Elemental carbon contribution to PM mass was found highest in traffic site (PM_2.5 = 17 to 23% and PM₁₀ = 8 to 10%) than residential site (PM_2.5 = 9 to 17% and PM₁₀ = 4 to 8%). Elements, ions, OC, and EC accounted 12, 28, 34, and 16% of PM_2.5 mass and 12, 21, 20, and 8% of PM₁₀ mass, respectively. Different sources identified by the receptor models are resuspended road dust, crustal material, secondary aerosol, traffic, non-exhaust vehicular emissions, secondary nitrate, construction, cooking, and biomass burning. Since Vellore is aspiring to be a smart city, this study can help the policymakers in effectively curbing PM.

Associations of polycyclic aromatic hydrocarbons, water-soluble ions and metals in PM2.5 with liver function: Evidence from schizophrenia cohort

BACKGROUND

Fine particulate matter (PM_2.5) was reported to impact liver function, but the roles of specific PM_2.5 chemical components remained to be explored. Besides, severe liver dysfunction in schizophrenia patients deserves attention.

OBJECTIVE

To investigate the associations of short-term PM_2.5 components with liver function in schizophrenia patients.

METHODS

A repeated-measures study based on schizophrenia cohort including 1023 visits (n = 446) was conducted during 2017-2020. Liver function was reflected by 10 indicators including liver enzymes, proteins and bilirubin et al. Monitoring data of PM_2.5 and its components, including 16 polycyclic aromatic hydrocarbons (PAHs), 4 water-soluble ions and 10 metals were collected. Linear mixed effect and Bayesian kernel machine regression (BKMR) models were used to evaluate the single and combined effects of PM_2.5 components (0-3 day) on liver function in schizophrenia patients.

RESULTS

Several PAHs were significantly associated with liver enzymes, while water-soluble ions and metal components had almost no association. Specifically, with per interquartile range (IQR) increased in Fluoranthene, levels of alkaline phosphatase (ALP), alanine transaminase (ALT), aspartate transaminase (AST) and gamma-glutamyl transpeptidase (GGT) increased by 2.06 %, 5.07 %, 4.94 % and 5.56 %, respectively. An IQR increases in Benzo[a]pyrene was significantly associated with 6.62 %, 3.67 % and 7.83 % increase in ALT, AST and GGT. Almost all PAHs, sulfate, nitrate, ammonium, Sb, Al, As, Pb, Mn and Tl were positively associated with albumin (ALB). Phenanthrene was associated with increased levels of direct bilirubin (DBIL) and total bilirubin (TBIL). The combined effects of significant PM_2.5 components on ALP, GGT, ALB, globulin (GLOB), ratio of albumin to globulin (A/G), TBIL and total bile acid (TBA) were found by BKMR, respectively.

CONCLUSIONS

Findings highlight the short-term combined effects of PM_2.5 components, especially PAHs, on liver function in schizophrenia patients, which contribute to the management of PM_2.5 sources including combustion activities and traffic emissions as well as improving schizophrenia comorbidities.

Elemental Composition and Sources of Fine Particulate Matter (PM2.5) in Delhi, India

In this study we have analysed the elemental composition of fine particulate matter (PM_2.5) to examine the seasonal changes and sources of the elements in Delhi, India from January, 2017 to December, 2021. During the entire sampling period, 19 elements (Al, Fe, Ti, Cu, Zn, Cr, Ni, As, Mo, Cl, P, S, K, Pb, Na, Mg, Ca, Mn, and Br) of PM_2.5 were identified by Wavelength Dispersive X-ray Fluorescence Spectrometer. The higher annual mean concentrations of S (2.29 µg m^-3), Cl (2.26 µg m^-3), K (2.05 µg m^-3), Ca (0.96 µg m^-3) and Fe (0.93 µg m^-3) were recorded during post-monsoon season followed by Zn > Pb > Al > Na > Cu > Ti > As > Cr > Mo > Br > Mg > Ni > Mn > and P. The annual mean concentrations of elemental composition of PM_2.5 accounted for 10% of PM_2.5 (pooled estimate of 5 year). Principal Component Analysis (PCA) identified the five main sources [crustal/soil/road dust, combustion (BB + FFC), vehicular emissions (VE), industrial emissions (IE) and mixed source (Ti, Cr and Mo rich-source)] of PM_2.5 in Delhi, India.

Seasonal variation of driving factors of ambient PM2.5 oxidative potential in Shenzhen, China

Reactive oxygen species (ROS) play a central role in health effects of ambient fine particulate matter (PM_2.5). In this work, we screened for efficient and complementary oxidative potential (OP) measurements by comparing the response values of multiple chemical probes (OP^DTT, OP^OH, OP^GSH) to ambient PM_2.5 in Shenzhen, China. Combined with meteorological condition and PM_2.5 chemical composition analysis, we explored the effects of different chemical components and emission sources on the ambient PM_2.5 OP and analyzed their seasonal variations. The results show that OP_m^DTT(mass-normalized) and OP_m^GSH-SLF were highly correlated (r = 0.77). OP^DTT was mainly influenced by organic carbon, while OP^OH was highly dominated by heavy metals. The combination of OP^DTT and OP^OH provides an efficient and comprehensive measurement of OP. Temporally, the OPs were substantially higher in winter than in summer (1.4 and 4 times higher for OP_m^DTT and OP_m^OH, respectively). The long-distance transported biomass burning sources from the north dominated the OP^DTT in winter, while the ship emissions mainly influenced the summer OP. The OP_m^DTT increased sharply with the decrease of PM_2.5 mass concentration, especially when the PM_2.5 concentration was lower than 30 μg/m³. The huge differences in wind fields between the winter and summer cause considerable variations in PM_2.5 concentrations, components, and OP. Our work emphasizes the necessity of long-term, multi-method, multi-component assessment of the OP of PM_2.5.

Chemical Characteristics and Cytotoxicity to GC-2spd(ts) Cells of PM2.5 in Nanjing Jiangbei New Area from 2015 to 2019

PM_2.5 is an air pollutant with complex components. After entering the body through respiration, PM_2.5 can not only cause respiratory diseases, but also break through the blood-testis barrier and influence the reproductive system. PM_2.5 with different components may result in different toxic effects. In the first five years of Nanjing Jiangbei New Area, industrial transformation would change the concentration and chemical fraction of PM_2.5 in the local environment to a certain extent. In this study, PM_2.5 collected in Nanjing Jiangbei New Area every autumn and winter from 2015 to 2019 was analyzed. PM_2.5 concentration generally decreased year by year. The large proportion of secondary inorganic ions indicated the presence of secondary pollution at the sampling site. PM_2.5 was mainly emitted from fossil fuel combustion and vehicle exhaust. The cytotoxicity of PM_2.5 samples was evaluated by PM_2.5 exposure to mouse spermatocytes (GC-2spd(ts) cells). Cell viability was relatively low in 2016 and 2018, and relatively high in 2017 and 2019. Reactive oxygen species levels and DNA damage levels followed similar trends, with an overall annual decrease. The cytotoxicity of PM_2.5 on GC-2spd(ts) cells was significantly correlated with water-soluble ions, water-soluble organic carbon, heavy metals and polycyclic aromatic hydrocarbons (p < 0.01). According to principal component analysis and multiple linear regression, fossil fuel combustion, secondary transformation of pollutants and construction dust were identified as the major contributors to cytotoxic effects, contributing more than 50%.

Investigating the association between air pollutants' concentration and meteorological parameters in a rapidly growing urban center of West Bengal, India: a statistical modeling-based approach

The ambient air quality in a city is heavily influenced by meteorological conditions. The city of Siliguri, known as the "Gateway of Northeast India", is a major hotspot of air pollution in the Indian state of West Bengal. Yet almost no research has been done on the possible impacts of meteorological factors on criterion air pollutants in this rapidly growing urban area. From March 2018 to September 2022, the present study aimed to determine the correlations between meteorological factors, including daily mean temperature (℃), relative humidity (%), rainfall (mm), wind speed (m/s) with the concentration of criterion air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, CO, O₃, and NH₃). For this research, the trend of all air pollutants over time was also investigated. The Spearman correlation approach was used to correlate the concentration of air pollutants with the effect of meteorological variables on these pollutants. Comparing the multiple linear regression (MLR) and non-linear regression (MLNR) models permitted to examine the potential influence of meteorological factors on concentrations of air pollutants. According to the trend analysis, the concentration of NH3 in the air of Siliguri is rising, while the concentration of other pollutants is declining. Most pollutants showed a negative correlation with meteorological variables; however, the seasons impacted on how they responded. The comparative regression research results showed that although the linear and non-linear models performed well in predicting particulate matter concentrations, they performed poorly in predicting gaseous contaminants. When considering seasonal fluctuations and meteorological parameters, the results of this research will definitely help to increase the accuracy of air pollution forecasting near future.

Composition and sources of heavy metals in aerosol at a remote site of Southeast Tibetan Plateau, China

Knowledge of the elemental composition of aerosols at remote sites is important for evaluating the influence of anthropogenic activities. In this study, the elemental composition and sources of total suspended particles (TSP) at Yaze, a remote site in the southeastern Tibetan Plateau (TP), were investigated. The results showed that the mean elemental concentrations at Yaze were relatively low compared with those in other areas of the TP. Seasonal variations in the studied elements was characterized by low and high concentrations during the monsoon and non-monsoon periods, respectively. The enrichment factors (EFs) for some heavy metals at Yaze were slightly higher than those at Nam Co station (inland TP) but much lower than those at Mt. Yulong (southeastern TP) and in the Indian megacity of Delhi, indicating fewer anthropogenic influences at the study site relative to sites close to severely polluted regions. For the studied elements, three major sources were identified: crustal origins (e.g., Al and Fe), anthropogenic origins (e.g., Zn and Cd) and mixed origins (e.g., As and Bi). Further analysis by potential source contribution functions showed that the local TP was the primary source for elements of crustal origins. Correspondingly, the typical heavy metals were mainly attributed to pollution emitted from anthropogenic activities and transported over long-range from both South and Southeast Asia. This work demonstrates the transport of heavy metals from external sources to remote sites in the southeastern TP. These results are also useful for interpreting the historical profiles of heavy metals in the ice cores of the TP.

Effect of Biomass Burning, Diwali Fireworks, and Polluted Fog Events on the Oxidative Potential of Fine Ambient Particulate Matter in Delhi, India

We investigated the influence of biomass burning (BURN), Diwali fireworks, and fog events on the ambient fine particulate matter (PM_2.5) oxidative potential (OP) during the postmonsoon (PMON) and winter season in Delhi, India. The real-time hourly averaged OP (based on a dithiothreitol assay) and PM_2.5 chemical composition were measured intermittently from October 2019 to January 2020. The peak extrinsic OP (OP_v: normalized by the volume of air) was observed during the winter fog (WFOG) (5.23 ± 4.6 nmol·min^-1·m^-3), whereas the intrinsic OP (OP_m; normalized by the PM_2.5 mass) was the highest during the Diwali firework-influenced period (29.4 ± 18.48 pmol·min^-1·μg^-1). Source apportionment analysis using positive matrix factorization revealed that traffic + resuspended dust-related emissions (39%) and secondary sulfate + oxidized organic aerosols (38%) were driving the OP_v during the PMON period, whereas BURN aerosols dominated (37%) the OP_v during the WFOG period. Firework-related emissions became a significant contributor (∼32%) to the OP_v during the Diwali period (4 day period from October 26 to 29), and its contribution peaked (72%) on the night of Diwali. Discerning the influence of seasonal and episodic sources on health-relevant properties of PM_2.5, such as OP, could help better understand the causal relationships between PM_2.5 and health effects in India.

The Predominant Sources of Heavy Metals in Different Types of Fugitive Dust Determined by Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) Modeling in Southeast Hubei: A Typical Mining and Metallurgy Area in Central China

To develop accurate air pollution control policies, it is necessary to determine the sources of different types of fugitive dust in mining and metallurgy areas. A method integrating principal component analysis and a positive matrix factorization model was used to identify the potential sources of heavy metals (HMs) in five different types of fugitive dust. The results showed accumulation of Mn, Fe, and Cu can be caused by natural geological processes, which contributed 38.55% of HMs. The Ni and Co can be released from multiple transport pathways and accumulated through local deposition, which contributed 29.27%. Mining-related activities contributed 20.11% of the HMs and showed a relatively high accumulation of As, Sn, Zn, and Cr, while traffic-related emissions contributed the rest of the HMs and were responsible for the enrichment in Pb and Cd. The co-applied source-identification models improved the precision of the identification of sources, which revealed that the local geological background and mining-related activities were mainly responsible for the accumulation of HMs in the area. The findings can help the government develop targeted control strategies for HM dispersion efficiency.

Seasonal variations in aerosol acidity and its driving factors in the eastern Indo-Gangetic Plain: A quantitative analysis

This study employs ISORROPIA-II for the evaluation of aerosol acidity and quantification of contributions from chemical species and meteorological parameters to acidity variation in the Indian context. PM_2.5 samples collected during summer (April-July 2018), post-monsoon (September-November 2018), and winter (December 2018-January 2019) from a rural receptor location in the eastern Indo-Gangetic Plain (IGP) were analyzed for ionic species, water-soluble organic carbon (WSOC), and organic and elemental carbon (OC, EC) fractions. This was followed by estimation of the in situ aerosol pH and liquid water content (LWC) using the forward mode of ISORROPIA-II, which is less sensitive to measurement uncertainty compared to the reverse mode, for a K⁺-Ca²⁺-Mg²⁺-NH₄⁺-Na⁺-SO₄^2--NO₃^--Cl^--H₂O system. Aerosol pH was moderately acidic (summer: 2.93 ± 0.67; post-monsoon: 2.67 ± 0.23; winter: 3.15 ± 0.34) and was most sensitive to SO₄^2- and total ammonium (TNH₃) variation. The LWC of aerosol showed an increasing trend from summer (16.6 ± 13.6 μg m^-3) through winter (32.9 ± 10.4 μg m^-3). With summer as the baseline, the largest changes in aerosol pH during the other seasons was driven by SO₄^2- (ΔpH: -0.70 to -0.82 units), followed by TNH₃ (ΔpH: +0.25 to +0.38 units) with K⁺ and temperature being significant only during winter (ΔpH: +0.51 and + 0.46 units, respectively). The prevalent acidity regime provided three major insights: i) positive summertime Cl^- depletion (49 ± 20%) as a consequence of SO₄^2- substitution increased aerosol pH by 0.03 ± 0.20 units and decreased LWC by 2.4 ± 5.9 μg m^-3; ii) the rate of strong acidity (H⁺_str) neutralization and the [H⁺_str]/[SO₄^2-] molar ratio suggested the existence of bounded acidity in ammonium-rich (winter) conditions; and iii) significant correlations between LWC, WSOC, and secondary organics during post-monsoon and winter pointed towards a possible indirect role of WSOC in enhancing LWC of aerosol, thereby increasing pH. Given the inability of proxies such as H⁺_str and charge ratios to accurately represent aerosol pH as demonstrated here, this study emphasizes the need for rigorous thermodynamic model-based evaluation of aerosol acidity in the Indian scenario.

Chemical characterization of water-soluble ions in highly time-resolved atmospheric fine particles in Istanbul megacity

The diurnal and seasonal variations of water-soluble ions (WSIs) in fine particles were investigated in an area predominantly affected by traffic emissions in Beşiktaş, Istanbul between 2017 and 2018. PM_2.5 samples were collected at high time resolutions of 2 h during the daytime and 12 h during the nighttime for six sampling campaigns over all seasons. Five inorganic water-soluble ions (SO₄^2-, NH₄⁺, NO₃^-, PO₄^-3, and NO₂^-) were determined using ion chromatography. Source analysis was investigated with principal component analysis (PCA) and bivariate polar plots. In descending order, WSIs concentrations were SO₄^2->NH₄⁺> NO₃^-> PO₄^-3>NO₂^- during the different seasons. The high time-resolved concentrations ranged as follows: sulfate 1.2-1118.1, ammonium 0.3-289.9, phosphate 2.9-107.6, nitrate 4.6-179.7, and nitrite 0.8-9.0 ng/m³, with yearly averages of 226.5, 59.0, 58.4, 37.9, and 3.3 ng/m³, respectively. Except for phosphate, all WSIs had strong seasonal variations with high concentrations during the winter and low concentrations during the summer. Molar ratios revealed that the formation of ammonium sulfate was less likely than ammonium nitrate. Principal component analysis resolved secondary aerosols (43.9%), residential heating (34.6%), shipping emissions (8.7%), and vehicle emissions (6.7%) as the major sources of WSIs, OC, EC, and PM_2.5 in Beşiktaş, Istanbul. Sulfate aerosol originated mainly from two nearby areas, SW and NE, of the sampling site tentatively due to residential heating and shipping emissions, respectively.

Inter-annual variability of source contributions to PM10, PM2.5, and oxidative potential in an urban background site in the central mediterranean

Airborne particulate matter (PM) is studied because of its effects on human health and climate change. PM long-term characterisation allows identifying trends and evaluating the outcomes of environmental protection policies. This work is aimed to study the inter-annual variability of PM_2.5 and PM₁₀ concentrations and chemical composition in an urban background site (Italy). A dataset of daily PM_2.5 and PM₁₀ was collected in the period 2016-2017, including the content of OC, EC, major water-soluble ions, main metals, and compared to a similar dataset collected in the period 2013-2014. Oxidative potential using DTT assay (dithiothreitol) was evaluated and expressed in DTT_V as 0.39 nmol/min·m³ in PM₁₀ and 0.29 in PM_2.5 nmol/min·m³. PM source apportionment was computed using the EPA PMF5.0 model and source contributions compared with those of a previous dataset collected between 2013 and 2014. Multi linear regression analysis identified which source contributed (p < 0.05) to the oxidative potential of each size fraction. Inter-annual trends were more evident on PM_2.5 with reductions of biomass burning contribution and increases in traffic contribution in the 2016-2017 period. Crustal contributions were similar for the two periods, in both size fractions. Carbonates were comparable in PM₁₀ with a slight increase in PM_2.5. Sea spray decreased in PM₁₀. The DTT_V of PM_2.5 peaked during cold periods, while, the DTT_V of the PM_10-2.5 fraction peaked in summer, suggesting that different sources, with different seasonality, influence OP in the PM_2.5 and PM_10-2.5 fractions. Analysis showed that sea spray, crustal, and carbonates sources contribute ∼13.6% to DTT_V in PM_2.5 and ∼62.4% to DTT_V in PM_10-2.5. Combustion sources (biomass burning and traffic) contribute to the majority of DTT_V (50.6%) in PM_2.5 and contribute for ∼26% to DTT_V in PM_10-2.5. Secondary nitrate contributes to DTT_V in both fine and coarse fraction; secondary sulphate contribute to DTT_V in PM_2.5 with negligible contributions to DTT_V in PM_10-2.5.

Physical, chemical and optical properties of PM2.5 and gaseous emissions from cooking with biomass fuel in the Indo-Gangetic Plain

The current study was designed to capture real-world cooking process-wise emissions generated by the combustion of mixed biomass fuel in traditional mud cookstoves in rural kitchens of the north Indian state of Uttar-Pradesh during regular meal preparations. Combustion characteristics, including modified combustion efficiency, thermal efficiency and burn rate, were examined to understand their relationship with emissions. Variations were observed in emission factors (EFs) of PM_2.5, trace gases, namely CO, CO₂, NO_x and SO_2, for different cooking processes. While the highest emission of PM_2.5, CO and SO₂ were observed for boiling (7.0 ± 2.7, 68 ± 29.3, 1.0 ± 1.7 gkg^-1, respectively), CO₂ and NO_x recorded the highest EFs for frying (1537 ± 278.2 & 1.6 ± 0.9 gkg^-1 respectively). Although the study reported similar carbon content emissions for different processes, high EC emissions were observed for baking (1.1 ± 0.3 gkg^-1). A high concentration of K⁺ (indicating biomass burning) and toxic trace metals including Al, Cu, Sr, Ti, Mo & Cd has been reported in the present study. EFs of black carbon and brown carbon from mixed fuel burning during uncontrolled cooking have been discussed for different cooking processes which are critical inputs to emission inventories and radiative forcing calculation. The processes of frying and sautéing were found to be more consistent in emissions of pollutants than boiling and baking (variability- 13 %-167 %). Overall, this study emphasizes that a measurement of combustion characteristics and cooking method type should also be contemplated along with fuel and stove types during field emission studies.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM_2.5 in typical industrial areas of North China, manual sampling and analysis of PM_2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM_2.5 was 53.4 ± 43.9 μg·m^-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO₃^- ion, at 14.6 ± 14.2 μg·m^-3, followed by organic carbon (OC), SO₄^2-, and NH₄⁺, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m^-3, respectively. The concentrations of OC, NO₃^-, and SO₄^2- were highest in winter and lowest in summer, whereas the NH₄⁺ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO₂ emission and conversion rates in winter, resulting in the SO₄^2- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m^-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m^-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM_2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM_2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Long-Term Variation in Carbonaceous Components of PM2.5 from 2012 to 2021 in Delhi

Carbonaceous species [organic carbon (OC), elemental carbon (EC), elemental matter (EM), primary organic carbon (POC), secondary organic carbon (SOC), total carbon (TC), and total carbonaceous matter (TCM)] of PM_2.5 were analyzed to study the seasonal variability and long-term trend of carbonaceous aerosols (CAs) in megacity Delhi, India from January, 2012 to April, 2021. The average concentrations (± standard deviation) of PM_2.5, OC, EC, TC, EM, TCM, POC and SOC were 127 ± 77, 15.7 ± 11.6, 7.4 ± 5.1, 23.1 ± 16.5, 8.2 ± 5.6, 33.3 ± 23.9, 9.3 ± 6.3 and 6.5 ± 5.3 µg m^-3, respectively during the sampling period (10-year average). The average CAs accounted for 26% of PM_2.5 concentration during the entire sampling period. In addition, the seasonal variations in PM_2.5, OC, EC, POC, SOC, and TCM levels were recorded with maxima in post-monsoon and minima in monsoon seasons. The linear relationship of OC and EC, OC/EC and EC/TC ratios suggested that the vehicular emissions (VE), fossil fuel combustion (FFC) and biomass burning (BB) are the major sources of CAs at megacity Delhi, India.

The seasonal variation, characteristics and secondary generation of PM2.5 in Xi'an, China, especially during pollution events

As an important central city in western China, Xi'an has the worst atmospheric pollution record in China and many measures have been taken to improve the air quality in the past few years. In this study, PM_2.5 samples were collected across four seasons from 2017 to 2018 in Xi'an. Organic carbon and elemental carbon, water soluble ions, and elements were monitored to assess the air quality. The average annual PM_2.5 concentration was (134.9 ± 48.1 μg/m³), with the highest concentration in winter (188.8 ± 93.2 μg/m³), and lowest concentration in summer (71.2 ± 12.1 μg/m³). The secondary generation of sulfate (SO₄^2-) and nitrate (NO₃^-) was strong in spring, and secondary organic carbon (SOC) was formed in all seasons. The compositions of PM_2.5 changed greatly during a sandstorm occurred and the Spring Festival. The sandstorm played a positive role in removing local pollutant NO₃^-, but also increased the concentration of SO₄^2-, however both the concentration of SO₄^2- and NO₃^- greatly increased by secondary generation during Spring Festival. Potential source analysis showed that during the sandstorm, pollutants were transported over a long distance from the northwest of China, whereas it was mainly from the local and surrounded emissions during the Spring Festival. Except Ca²⁺ and geological dust (GM), the other components in PM_2.5 increased significantly on the day of the Spring Festival. During sampling time in Xi'an, the positive matrix factorization (PMF) model analysis showed that PM_2.5 mainly came from vehicle emission, coal combustion, and biomass burning.

Estimation of the fraction of soil-borne particulates in indoor air by PMF and its impact on health risk assessment of soil contamination in Guangzhou, China

The fraction of soil-borne particulates in indoor air (fspi), a principal exposure factor in health risk assessment of soil, is used to calculate the inhaled dose of contaminants in air particulates (PM₁₀) from soil. To investigate the fspi, consecutive 24-h PM₁₀ samples (n = 180) of indoor ambient were collected from September 2019 to January 2020 in Guangzhou main urban areas, China. The concentrations of twenty-six metal elements, five anions, organic carbon (OC) and elemental carbon (EC) in samples were measured. The sources of indoor ambient PM₁₀ and the value of fspi were identified by the method of Positive Matrix Factor analysis (PMF). Results showed that the main sources contributing to indoor PM₁₀ content were combustion sources (50.53%) and vehicular sources (28.17%). The soil sources (the local fspi) were 19.96%. The soil contents of indoor PM₁₀ in Guangzhou main urban areas were in accordance with those in similar monsoon climate regions, such as Malaysia. The health risks of the inhalation route were dropped by about 62% for some common brownfield contaminants (Cr (VI), Ni, Be and Cd) with the investigated local fspi in Guangzhou main urban areas, compared with using the fspi (0.8) recommended by the C-RAG model in China. The results supplied a new effective methodology for estimation of the local fspi value in health risk assessment of soil contamination in urban areas.

Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India

The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM_2.5 concentrations and an enhancement in the O₃ concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O₃ formation, comprising 89.4%, 83.1%, and 88.9% of the O₃ sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O₃ concentrations at the surface layer. Compared with the Pre1 period, the O₃ enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O₃ removal rate by horizontal transport. During the Tri period, a slower consumption of O₃ by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O₃. Emission and aerosol processes constituted the major positive contributions to the net surface PM_2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM_2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM_2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM_2.5 production from emission and aerosol processes. The increased vertical transport rate of PM_2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM_2.5 during the Lock periods.

Seasonal variation of dissolved bioaccessibility for potentially toxic elements in size-resolved PM: Impacts of bioaccessibility on inhalable risk and uncertainty

The health effects of potentially toxic elements (PTEs) in airborne particulate matter (PM) are strongly dependent on their size distribution and dissolution. This study examined PTEs within nine distinct sizes of PM in a Chinese megacity, with a focus on their deposited and dissolved bioaccessibility in the human pulmonary region. A Multiple Path Particle Dosimetry (MPPD) model was used to estimate the deposited bioaccessibility, and an in-vitro experiment with simulated lung fluid was conducted for dissolved bioaccessibility. During the non-heating season, the dissolved bioaccessible fraction (DBF) of As, Cd, Co, Cr, Mn, Pb and V were greater in fine PM (aerodynamics less than 2.1 μm) than in coarse PM (aerodynamics between 2.1 and 10 μm), and vice versa for Ni. With the increased demand of heating, the DBF of Pb and As decreased in fine particle sizes, probably due to the presence of oxide/silicate compounds from coal combustion. Inhalation health risks based on the bioaccessible concentrations of PTEs displayed the peaks in <0.43 μm and 2.1-3.3 μm particulate sizes. The non-cancer risk was at an acceptable level (95th percentiles of hazard index (HI) was 0.49), but the cancer risk exceeded the threshold value (95th percentiles of total incremental lifetime cancer risk (TCR) was 8.91 × 10^-5). Based on the results of uncertainty analysis, except for the exposure frequency, the total concentrations and DBF of As and Cr in <0.43 μm particle size segment have a greater influence on the uncertainty of probabilistic risk.

Source apportionment of PM2.5 in Seoul, South Korea and Beijing, China using dispersion normalized PMF

East Asian countries experience severe air pollution owing to their rapid development and urbanization induced by substantial economic activities. South Korea and China are among the most polluted East Asian countries with high mass concentrations of PM_2.5. Although the occurrence of transboundary air pollution among neighboring countries has been recognized for a long time, studies involving simultaneous ground-based PM_2.5 monitoring and source apportionment in South Korea and China have not been conducted to date. This study performed simultaneous daily ground-based monitoring of PM_2.5 in Seoul and Beijing from January to December 2019. The mass concentrations of PM_2.5 and its major chemical components were analyzed simultaneously during 2019. Positive matrix factorization (PMF) as well as dispersion normalized PMF (DN-PMF) were utilized for the source apportionment of ambient PM_2.5 at the two sites. 23 h average ventilation coefficients were applied for daily PM_2.5 chemical constituents' data. Nine sources were identified at both sites. While secondary nitrate, secondary sulfate, mobile, oil combustion, biomass burning, soil, and aged sea salt were commonly found at both sites, industry/coal combustion and incinerator were identified only at Seoul and incinerator/industry and coal combustion were identified only at Beijing. Reduction of the meteorological influences were found in DN-PMF compare to C-PMF but the effects of DN on mobile source were reduced by averaging over the 23 h sampling period. The DN-PMF results showed that Secondary nitrate (Seoul: 25.5%; Beijing: 31.7%) and secondary sulfate (Seoul: 20.5%; Beijing: 17.6%) were most dominant contributors to PM_2.5 at both sites. Decreasing secondary sulfate contributions and increasing secondary nitrate contributions were observed at both sites.

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes

La Oroya is a city in the Peruvian Andes that has suffered a serious deterioration in its air quality, especially due to the high rate of sulfur dioxide (SO2) emissions, which underlines the importance of knowing its sources of contamination and variation over the years. In this sense, this study aimed to evaluate the immission levels and determine the sources of SO2 contamination in La Oroya. This analysis was performed using the hourly concentration data of SO2, and meteorological variables (wind speed and direction), which were analyzed for a period of three years (2018-2020). Graphs of time series, wind and pollutant roses, bivariate polar graphs, clustering k-means, nonparametric statistical tests, and the application of the conditional bivariate probability function were performed to analyze the data and identify the emission sources. The mean concentration of SO2 was 264.2 μg m-3 for the study period, where 55.66 and 2.37% of the evaluated days exceeded the guideline values recommended by the World Health Organization and the Peruvian Environmental Quality Standard for air for 24 h, respectively. The results showed a defined pattern for the daily and monthly variations, with peaks in the morning hours (0900-1000 h LT) and at the end of the year (December), respectively. The main sources of SO2 emissions identified were light and heavy vehicles that travel through the Central Highway, the La Oroya Metallurgical Complex, the transit of vehicles within the city, and the diesel-electric locomotives that provide cargo transportation services and tourism passenger transportation. The article attempts to contribute to the development of adequate air quality management policies.

On the techniques and standards of particulate matter sampling

Air pollution and its limits are regulated by the environmental protection agency of an individual country according to their National Ambient Air Quality Standards (NAAQS). Particulate matter (e.g., TSP, PM₁₀, and PM_2.5) is one of the important criteria pollutants of NAAQS. Their measurement methods are specified in NAAQS, and detailed technical descriptions are given in standards. This review focuses on the sampling and analysis techniques and methods in the context of PM samplers' design mentioned in countries specific PM measuring standards (e.g., EPA Part 50, CEN 12341, IS 5182(23), etc.) and their comparison wherever is necessary. It discusses, different designs of PM samplers mentioned in standards and its important components, e.g., size fractionators cutoff efficiency, PM sampler head design, flow measurement, and calibration, and also addresses the important issues that are the limitation of present standards. Our review reveals that most of the country-specific standards show common practice in measuring PM_2.5 using WINS impactor and VSCC cyclone as mentioned in EPA Part 50, except European Union (EU) standards, which has different design and parameters. For PM₁₀ measurement, sampler design is different in EU and Indian standards than that of U.S. EPA and other countries' standards, which is discussed in length here. All standards lack in pointing some inherent problems like change in D₅₀ cutoff of size fractionator of sampler under a high particle mass loading condition, which is common in countries like China and India. Other important issues where most of the standards lack include PM head design and specification, a key component of PM sampler on which the mass measurement results are largely dependent.Implications: The review paper discusses the air quality standards compliances of different countries and their comparisons. It focuses on the sampling and analysis techniques in context of PM samplers' design mentioned in countries specific PM measuring standards, and also addresses the important issues that are not mentioned in standards. Therefore, the discussions and findings of the review may be very useful while revising the existing air quality standards of different countries and to fill the research gap in this domain. Further, we have discussed several technical issues described in standards related to PM sampling which may be very helpful for PM sampler designing or modification in current designs as per the prevailing ambient conditions of a country.

DESA: a novel hybrid decomposing-ensemble and spatiotemporal attention model for PM2.5 forecasting

Exposure to fine particulate matter can easily lead to health issues. PM_2.5 concentrations are associated with various spatiotemporal factors, which makes the prediction of PM_2.5 concentrations still a challenging task. One of the reasons that makes the accurate prediction by statistical learning method difficult is severe fluctuations in input data. In addition, the abstraction method of space will also affect the prediction results. To address these important issues, a novel hybrid decomposing-ensemble and spatiotemporal attention (DESA) model is proposed to improve the prediction accuracy by decomposing the mode-mixed time series into single-mode series and automatically assign weights to the spatiotemporal factors. In our proposed framework, raw PM_2.5 series are firstly decomposed into simple sub-series via the complete ensemble empirical mode decomposition (CEEMD) method. Then, to keep the results independent of the spatial abstraction method, a data-driven approach called multiscale spatiotemporal attention network is employed to extract spatiotemporal features from the sub-series. Finally, the predictions of each sub-series are processed separately and combined to obtain the final prediction results. The experimental results indicate that the proposed model achieved the better performance with RMSE of 11.15, 17.49, 24.84, and 26.93 for 6-, 12-, 24-, and 36-h forecasting, respectively. The proposed method is expected to be applied in fine prediction of air pollution and controlling programs and therefore provide decision support or useful guidance.

The relationship between greenspace and personal exposure to PM2.5 during walking trips in Delhi, India

The presence of urban greenspace may lead to reduced personal exposure to air pollution via several mechanisms, for example, increased dispersion of airborne particulates; however, there is a lack of real-time evidence across different urban contexts. Study participants were 79 adolescents with asthma who lived in Delhi, India and were recruited to the Delhi Air Pollution and Health Effects (DAPHNE) study. Participants were monitored continuously for exposure to PM_2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) for 48 h. We isolated normal day-to-day walking journeys (n = 199) from the personal monitoring dataset and assessed the relationship between greenspace and personal PM_2.5 using different spatial scales of the mean Normalised Difference Vegetation Index (NDVI), mean tree cover (TC), and proportion of surrounding green land use (GLU) and parks or forests (PF). The journeys had a mean duration of 12.7 (range 5, 53) min and mean PM_2.5 personal exposure of 133.9 (standard deviation = 114.8) μg/m³. The within-trip analysis showed weak inverse associations between greenspace markers and PM_2.5 concentrations only in the spring/summer/monsoon season, with statistically significant associations for TC at the 25 and 50 m buffers in adjusted models. Between-trip analysis also indicated inverse associations for NDVI and TC, but suggested positive associations for GLU and PF in the spring/summer/monsoon season; no overall patterns of association were evident in the autumn/winter season. Associations between greenspace and personal PM_2.5 during walking trips in Delhi varied across metrics, spatial scales, and season, but were most consistent for TC. These mixed findings may partly relate to journeys being dominated by walking along roads and small effects on PM_2.5 of small pockets of greenspace. Larger areas of greenspace may, however, give rise to observable spatial effects on PM_2.5, which vary by season.

Identification of Carbonaceous Species and FTIR Profiling of PM2.5 Aerosols for Source Estimation in Old Delhi Region of India

In this study, PM_2.5 samples from a traffic-influenced site in old Delhi were collected from January 2021 to June 2021 (January–March, 2021: months with regular activities; April–June, 2021: partially restricted months due to second wave of pandemic) and analysed to assess noteworthy effect on their infrared (IR) spectral features and carbonaceous content viz., organic carbon (OC) and elemental carbon (EC) and their sub-fractions with their link to major sources in the vicinity of the sampling site of Delhi. Absorbance peaks for the structural and functional groups for previously identified compounds associated with vehicular/combustion/biogenic emissions at the site were notable. Intensive peaks for C=C, C–H, O–H and NH₄NO₃ were observed on certain days pointing towards enhanced emission of the related compounds. Lower spectral peaks were observed for March and first half of April probably due to transitioning meteorological variables and imposed restrictions. Monthly variation in ratios, such as OC/EC, EC/TC and OM/OC, revealed about the probable emission sources. Comparatively higher peaks/values were observed during January, February and June. The overall results followed a general pattern of variation for regular days.

Association between Acute Exposure to PM2.5 Chemical Species and Mortality in Megacity Delhi, India

The association between daily all-cause mortality and short-term fine particulate matter (PM_2.5) exposure is well established in the literature. However, association between acute exposure to PM_2.5 chemical species and mortality is not well known, especially in developing countries like India. Here we examined associations between mortality and acute exposure to PM_2.5 mass concentration and their 15 chemical components using data from 2013 to 2016 in megacity Delhi using a semiparametric quasi-Poisson regression model, adjusting for mean temperature, relative humidity, and long-term time trend as the major potential confounders. Mortality estimates were further checked for effect modification by sex, age group, and season. The subspecies of NO₃^-, NH₄NO₃, Cr, NH₄⁺, EC, and OC showed a higher mortality impact than the total PM_2.5 mass. Males were at higher risk from NO₃^-, SO₄^2-, and their NH₄⁺ compounds along with carcinogen Cr, whereas female group was at higher risk from EC and OC. Among all age groups, the elderly above 65 years were the most vulnerable group prone to mortality effects from maximum species. The major mortality risk from all hazardous species arose from their winter exposures. Our study provides the first evidence of association between acute exposure to PM_2.5 chemical species and mortality anywhere in India and recommends similar studies in other regions so that sectoral mitigation emitting the most toxic species can be prioritized to maximize the health benefits.