Journal of Atmospheric Chemistry最新文献

Growing ambient air pollution in Lucknow is a menace to the monuments, urban dwellers, and the ecosystem. In view of the above, air pollution tolerance potential of dominant plants against air pollutants was assessed supported by indices and statistics. The study was conducted at three sampling sites in Lucknow city: commercial, industrial, and rural in the years 2021-22. PM_2.5 concentrations were 163.4 ± 25.3, 155.1 ± 14.6 and 113.2 ± 30.8 µg/m³ at commercial, industrial, and rural locations, respectively, breaching national ambient air quality standards (60 µg/m³) by 172.3, 158.5 and 88.7%. Eleven trace elements were associated with PM_2.5 and PM₁₀ out of which Sr, Al, Fe, and Zn were predominant owing to road dust entrainment and vehicular emission. Biochemical parameters were assessed for four native floral species Azadirachta indica, Mangifera indica, Ficus religiosa and Cascabela thevetia. For these species, pH ranged between 5.3-8.4, total chlorophyll 0.4–1.2 mg/g, carotenoids 0.15–0.34 mg/g, relative water content 32.1–89.9% and ascorbic acid 0.12–1.32 mg/g. Guaiacol peroxidase (19.5 ± 2.5 U/gm protein) was highest for C. thevetia, malondialdehyde (3.6 ± 1.4 nmol/gm FW) for A. indica, superoxide dismutase (339.4 ± 11.7 U/mg protein) for C. thevetia and catalase (688.7 ± 68 U/mg protein) for A. indica. Air pollution tolerance index (APTI) was higher for F. religiosa (17.53) followed by A. indica (13.34) showing their tolerance ability in response to particulate matter and heavy metals. Aforementioned plant species can be used to further investigate how plants and pollutants interact and for enhancing potential phyto-control methods for minimizing air pollution.

In this paper, the study focuses on the forecasting of the Air Quality Index (AQI) using linear regression, random forest, and decision tree regression models in Delhi City. The AQI is a crucial metric for monitoring air quality and provides information on the level of air pollution and its potential health risks. The main research aims to develop forecasting of AQI in three scenarios based on the air pollutants data. Monthly average Nitrogen dioxide (NO₂₎, Sulfur dioxide (SO₂), Oxygen (O₃), and Particle matter (PM_2.5) data from 1987 to 2020 were included. The research was executed in two steps: preprocessing datasets, plotting the datasets, and analyzing them in the first step, and training and testing the model's accuracy in the second step. The datasets were divided into training and testing sets also we forecasted the AQI in three scenarios based on the different input variables. Feature importance was used for the selection of model input variables. Results of the study area compared the Machine Learning (ML) models in three scenarios best performance models such as Decision Tree Regression (DT) (R² = 0.99, RMSE = 0.81), Random Forest (RF) (R² = 0.98, RMSE = 16.64), and RF (R² = 0.99, RMSE = 0.27), respectively. The results of DT and RF models showed high prediction performance compared to other models in the first, second, and third scenarios, respectively. The results of 10-fold cross-validation models are cross-validated to all models, which is the RF model is best other than the models in three scenarios. Hence, the cross-validation of all ML models so important for the selection of the best model for forecasting AQI in Delhi City. The results can be helpful to urban policy makers in the Delhi city.

Organic carbon (OC) and elemental carbon (EC) play a significant role in aerosol mass and atmospheric processes. This study is focused on the eastern part of the Great Northern Plains of India, namely the Brahmaputra Plains, to understand the influence of regional and local contribution on the carbonaceous fraction of PM_2.5. Mean annual PM_2.5 concentrations exceeded the National Ambient Air Quality Standards (NAAQS), with values of 46.6 ± 30.0 μg/m³ in the rural area and 50.4 ± 34.4 μg/m³ in the semi-urban area. The range in monsoon-winter was found to be 22.7–71.9 μg/m³. OC and EC contribute 44–50% of the PM_2.5 mass concentration. The OC/EC ratios ranged from 3.3 to 9.3 in the rural area and from 4.3 to 6.9 in the semi-urban area, indicating significant secondary organic aerosol (SOA) formation, especially during the high photochemical period of the pre-monsoon season. Lower δ13C values were observed during winter (-27.5‰ rural, -27.3‰ semi-urban), pre-monsoon (-28.1‰ rural, -27.6‰ semi-urban), and post-monsoon (-28.2‰ rural, -28.1‰ semi-urban) periods, suggesting influences from biomass burning, fossil fuel combustion, and aged aerosols. The study employs cluster analysis of air mass trajectory, and Moderate Resolution Imaging Spectroradiometer (MODIS) fire data to determine the influence of the hotspot Indo-Gangetic Plain (IGP) and long-range transport on aerosol carbonaceous content during most seasons except the monsoon period June–September in the Brahmaputra Plains.

PM_2.5 samples were collected in Suncheon during the summer (June 2–11, 2023) and winter (January 15–21, 2024). The chemical composition analysis included carbonaceous components (OC, EC), secondary ionic components (NH₄⁺, NO₃⁻, SO₄²⁻), dithiothreitol - oxidative potential (QDTT-OP), and volatile organic compounds. Results showed higher summer PM_2.5 concentrations due to photochemical reactions and higher winter concentrations from heating and stable atmospheric conditions. The OC/EC ratio indicated greater secondary organic aerosol formation in summer. Oxidative potential (QDTT-OP_v) was higher in summer (0.12 µM/m³) than winter (0.09 µM/m³), correlating strongly with OC in summer. Health risk assessment of BTEX revealed higher concentrations in winter, with benzene as the primary contributor to lifetime cancer risk (LTCR). The cumulative hazard quotient (HQ) was higher in winter, indicating increased non-carcinogenic risk. The study highlighted that oxidative potential is more influenced by chemical composition than physical characteristics, suggesting that regulating PM_2.5 concentration alone may be insufficient. VOCs, as precursors of SOA, showed a positive correlation with QDTT-OP_v, with benzene exhibiting the strongest correlation in winter. These findings emphasize the need for targeted management of specific PM_2.5 components to mitigate health risks effectively.

Graphical Abstract

High levels of particulate matters in the air are a major health issue in Middle East leading to adverse health effects. In this study, we have simultaneously investigated (i) the spatio-temporal distribution of ambient particulate matters in a city located in the Middle East (Khorramabad) over the time period 2021–2022; and (ii) PM_2.5 and PM₁₀-related carcinogenic and non-carcinogenic risk assessment to exposure. For the risk assessment, hourly PM_2.5 and PM₁₀ data were obtained from three monitoring stations located in the city. A methodology for risk assessment recommended by the United State Environmental Protection Agency was used for all age groups. The excess lifetime cancer risk (ELCR) and the hazard quotient (HQ) were estimated, and the backward trajectories were assessed by the Hybrid Single-Particle Lagrangian Integrated Trajectory model. The Aerosol Optical Depth from 0 to 1000 nm was applied to observe the variations of atmospheric aerosols. The results showed that the annual PM_2.5 and PM₁₀ mean concentrations during 2021 and 2022 were exceeded the World Health Organization limit value for human health protection. In 2021 and 2022, 2.2-148.3 and 1.3-134.4 cancers per 1,000,000 inhabitants can be related to ambient PM_2.5 exposure. The HQ values for PM_2.5 and PM₁₀ were 4.7 and 1.3 in 2021, and 3.8 and 1.1 in 2022, i.e., the risk for human health is expected. To reduce the adverse health effects related to particulate matters, air emissions control strategies are required.

The composition of aerosols influenced by regional pollution sources during a post-monsoon haze event was studied including the isotopic, bulk, and molecular signatures. The air mass back trajectory and fire spot analysis revealed that the Delhi aerosols were influenced by the regional post-harvest crop (rice plant) residue-burning activities during the sampling period. To better understand the atmospheric processes during such an event, three samples of 4 h duration each (Period I: from 06:00–10:00, Period II: 10:00–14:00, and Period III: 14:00–18:00 h local time) were collected during the sampling period (8th -17th November, 2019) in the daytime. The average mass concentration of PM_2.5, molecular compounds including the inorganic and carbonaceous components (dicarboxylic acid class compounds), along with the stable isotopes of C and N were observed to be elevated during Period I of the study. NH₄⁺ and SO₄²⁻ were found to be the most abundant inorganic ions during Period II and III with Cl⁻ being the dominant ion during Period I. The OC/EC, WSOC/EC ratios indicated the influence of biomass burning on Delhi aerosols with little influence of local ageing processes evident from the minimal variation observed between the three periods of study during the day. High concentrations of dicarboxylic acids than previous studies are reported with oxalic and succinic acid being the most abundant diacids, a typical behaviour observed in biomass-burning influenced aerosols with an interesting observation of terephthalic acid to be found in an appreciable amount. The δ¹⁵ N of TN and δ¹³ C of TC signatures clearly indicated the influence of emissions from the burning of a C3 plant on the aerosols. The results strongly suggested that the aerosols were influenced by biomass-burning activities in the neighbouring regions and were aged during the atmospheric transport over to the city of Delhi with minimal effect of local ageing processes during the study period.

In this study, we have reported spatial and temporal variation in particulate matter (PM), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO) and ozone (O₃) over five provincial capital cities in northwestern China during 2013–2020. Regarding the seasonal variation, all pollutants (except ozone) exhibited the lowest concentration during summer and the highest concentration during winter, which could be attributed to increased anthropogenic activities (like coal burning) and conducive meteorological features. The highest monthly mean concentrations were primarily observed during December-February, whereas ozone exhibited the highest concentration during April-August, with different cities experiencing the highest concentration during different seasons. Regarding the diurnal variation exhibited by the pollutants, the lowest concentration of pollutants (except O₃) was observed during the late afternoon (17:00–18:00) period. Ozone posed the urban site diurnal variation characteristic (peak during afternoon hour) over all sites. Urumqi had the highest PM_2.5/PM₁₀ ratio during November-March and the lowest ratio during April-October. Compared to the WHO revised guideline, the annual mean PM_2.5 concentration was about 8–12 times higher, whereas the annual PM₁₀ concentration was exceeded by a factor of up to 7. Most pollutants exhibited reduced concentration during the spring festival period. Analysis using HYSPLIT back trajectories indicated that the air masses affecting the five sites primarily originated from the northwestern area of China, although the impact of long-range pollution transport from remote regions should not be overlooked.

Sequential Extraction Procedure (SEP) is a method widely used to extract metals and metalloids from Particulate Matter (PM) based on their solubility in different reaction media. This extraction procedure is used to determine the actual mobility of metals present in the environment. A detailed discussion on the significance of sequential extraction analysis is also being given in this scientific document. This review includes different aspects related to the fractions obtained (exchangeable: F1, reducible: F2, oxidizable: F3, bound to organic matter: F4, and residual fraction: F5) during the SEP. The use of each reagent involved in the fractionation process of PM is also discussed briefly. Finally, the present up-to-date information given by different researchers in various fields of atmospheric chemistry along with the possible future developments is also part of this scientific review. The current review also focuses on the relation between SEP and mathematical expressions (bioavailability, source apportionment, and health risk assessment by the USEPA method). It is revealed from the previous studies that Cd and Zn are highly enriched, mobile as well as highly bioavailable in the environment and poses more risk to the human being. The Cr and As showed carcinogenic nature and hence pose carcinogenic diseases in humans. Whereas, Mn and As are non-carcinogenic in nature for children and adults and thereby both pose a non-carcinogenic disease threat to the population.

India, one of the most dynamic ancient civilizations, possesses a multitude of historical artifacts, with 37 of its notable architectural structures recognized as UNESCO World Heritage Sites. Yet, the ever-changing climate, especially air pollution, expedites the natural deterioration of historic sites and diminishes their aesthetic appeal, causing socio-economic damage. With this in mind, the current study aims to offer a logical scientific foundation for the implications of air pollution, seasonal shifts, and COVID-19 on 14 significant historical places in India during the year 2019-20. Delhi, among the cities most severely affected by atmospheric pollution, recorded an alarming air quality index (AQI) of 102–141, which can intensify the risk of cultural sites to corrode and deteriorate. Analysis reveals that the winter season had elevated levels of NO₂ and particle pollution (PM_2.5, PM₁₀), whereas summer had the higher levels of O₃. Throughout the 5-month lockdown period, ozone levels exhibited an elevation, contrasting with the reduction observed in other air parameters. Notably, there was a substantial 70% decrease in particulate matter concentration, which had previously remained stable over the course of the year. Variations in geographic locales and anthropogenic influences contribute significantly to the dose-response statistics, revealing an unprecedented elevation in corrosion risks to historical limestone and sandstone structures across target sites. Moreover, the research addresses available Governmental initiatives, and effective strategies designed to safeguard heritage sites against the corrosion and material degradation, offering a comprehensive exploration of protective measures. Thereby, the current research is centred on establishing a foundational understanding of the impact of air pollution on cultural heritage, utilizing a comparison to the year with the lowest air pollution levels, which can aid policymakers in enhancing risk management and implementing a robust national mandate for the preservation of cultural heritage sites against corrosion.