This study explored the interspecies and seasonal variation of polycyclic aromatic hydrocarbons (PAHs) in the extracted lipids of the leaves of seven local plants in an urban environment of Kolkata (22°33′N and 88°20′E), India. Based on the degree of toxicity and carcinogenicity (expressed in terms of their Benzo(a)pyrene equivalent (BaPeq) concentrations) the overall foliar-PAH accumulation during the study period (September 2018‒;August 2019) in the various plants showed the following order: Nerium oleander (80.96 ± 30.08 ng.gdw−1) > Mangifera indica (74.15 ± 20.34 ng.gdw−1) > Lantana aculeata (60.13 ± 21.71 ng.gdw−1) > Thevetia peruviana (40.97 ± 12.45 ng.gdw−1) > Ixora coccinea (38.11 ± 9.5 ng.gdw−1) > Murraya paniculata (37.1 ± 7.35 ng.gdw−1) > Polyalthia longifolia (25.72 ± 5.71 ng.gdw−1). The PAHs like phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)anthracene, chrysene, benzo (b+k)fluoranthene, benzo(a)pyrene, benzo [ghi]perylene and indeno [1,2,3-cd]pyrene were predominant during the study period over the PAHs like naphthalene, acynaphthylene, acenaphthene, fluorine and dibenz [a,h]anthracene in the extracted lipids. The temperature-dependent partitioning of the PAHs onto leaf-surface and photo-degradation could have affected the availability of the PAHs. The foliar PAH accumulation varied seasonally as winter (December–February) > postmonsoon (September–November) > premonsoon (March–May) > monsoon (June–August). The leaf epicuticular wax determined the PAH uptake and storage, which in turn was affected by the temperature and solar radiation. In consistence with the idea of “nature-based solutions” for deteriorated air quality remediation in an urban environment, this study could be a promising initiative to build up cost-effective biological filters to combat the airborne pollutants and improve urban air quality.

Aerosols have severe effects on climate, human health and ecosystems. The impact of aerosols on climate, ecosystems and human health can be better understood if the variability of optical properties of aerosols is accurately known. In this paper, we have used Moderate Resolution Imaging Spectroradiometer (MODIS) datasets of aerosol optical depth (AOD) at 550 nm, Angstrom exponent (440/870) (AE) and enhanced vegetation index (EVI) over Pakistan. We have also analyzed the relationship between meteorological variables (e.g., temperature, relative humidity (RH) and wind speed (WS)) and aerosol optical properties to acquire a deep knowledge of aerosol variability. The coefficients of determination (R²) between Aqua-AOD and AERONET-AOD are found to be 0.6724 over Lahore and 0.7678 over Karachi. Aqua-AOD has also been validated with AOD data from Terra, MISR and SeaWiFS. High AOD (0.8–1) and low AE (0.4–0.8) have been observed over south and southwestern Pakistan indicating the presence of dust aerosols. In northeastern Pakistan, EVI is negatively correlated with AOD. The northeastern Pakistan is characterized by high values of AOD (~1) during all seasons. AOD showed a significant interannual variation with the lowest values (0.22) in January and the highest (0.58) in July. AE is observed to be lower in spring and summer than in winter and autumn seasons in south and south-western Pakistan. A positive R (≥0.6) is observed between AOD and temperature over the southwestern Pakistan while a negative R (−0.4 ≤) is observed between AOD and RH over the southwestern Pakistan.

Based on the ground-level observed NO₂ concentration, satellite-observed NO₂ column concentration from the Ozone Monitoring Instrument (OMI) and meteorological parameters, we comprehensively consider the seasonal and regional differences in the relationship between NO₂ column concentration and measured NO₂ concentration and establish a two-stage combined ground NO₂ concentration estimation (TSCE-NO₂) model using a support vector machine for regression (SVR) and a genetic algorithm optimized back propagation neural network (GABP). On this basis, the spatial-temporal variation in the modelled ground-level NO₂ concentration over China during the period of 2005–2019 was analysed. The results show that the TSCE-NO₂ model proposed in this study provides a reliable estimation of the modelled ground-level NO₂ concentration over China, effectively filling the spatial and temporal gaps in China's air quality ground monitoring network (the model's correlation coefficient, R, is 0.92, the mean absolute error, MAE, is 3.62 μg/m³, the mean square percentage error, MSPE, is 0.72%, and the root-mean-square error, RMSE, is 5.93 μg/m³). The analysis results of the spatial and temporal variation indicate that (1) the perennial ground-level NO₂ concentration over China is high in the eastern area and low in the western area, and the high values are mainly distributed along the northern coast, the eastern coast, the middle reaches of the Yangtze River, the middle reaches of the Yellow River, the Pearl River Delta and the Sichuan Basin. (2) The modelled ground-level NO₂ concentrations over China are highest in winter, followed by those in autumn and spring, and they are lowest in summer. Before 2011, the ground-level NO₂ concentration over China increased at a rate of 0.348 ± 0.132 μg/(m³∙a) but decreased at a rate of 0.312 ± 0.188 μg/(m³∙a) after 2011. (3) From 2011 to 2019, measures such as energy savings and emission reductions alleviated NO₂ pollution on the premise of ensuring sustained China's GDP growth.

Land-use and land-cover changes due to urban expansion is recognized as one of the crucial factors affecting carbon dioxide emissions. In this study, the land conversion effects on soil CO₂ fluxes associated with temperate re-established grasslands within the Forest Botanical Garden found on an anthropogenic landform were investigated. The present work analyses the capabilities and requirements of the CALPUFF Lagrangian puff air quality modelling system to simulate the spatial distribution of ecosystem respired CO₂ in the urban domain. The results are validated against the available observations of CO₂ fluxes in the urban environment using the closed-chamber method with the measurements of the stable carbon isotope ratio (δ¹³C) of daytime soil-respired CO₂. The isotope mass balance partitioning approach was applied to distinguish biogenic portions of CO₂ from the admixture of atmospheric air.The spatial and temporal amplitude of the simulated CO₂ concentrations from the CALPUFF model showed considerable agreement with the tracer measurements of the biogenic CO₂ component in the near-ground air (0.25 m). In most cases, however, the CALPUFF predictions of ecosystem-derived CO₂ showed a general tendency toward considerable underestimation of real concentration levels. Such discrepancies are related to the difficulties associated with the optimization of biospheric CO₂ flux and uptake from ecosystems by means of local-scale modelling. The modelled results implied that the CALPUFF performance in the dispersion simulation of CO₂ concentrations within the urban ecosystems is very sensitive to the initial meteorological conditions, grid resolution, measurement timescale, and the calculated gas flux rate from soils. A significant negative correlation was found between hourly values of the average modelled CO₂ and observed wind speed during the entire study campaign (r = −0.58 and ρ = −0.82 for Pearson and Spearman statistics, respectively, p < 0.05). Moreover, analysis of the impact of the deposition parameters on changes in the atmospheric concentration of carbon dioxide indicated significant dependency of the temporal CO₂ distribution patterns on the precipitation-based events. According to the obtained estimates, the wet deposition rate during rain events was approximately two orders higher than the average dry deposition flux.Overall, the present case study indicates that the CALPUFF model has a rather acceptable predictive ability. A better agreement of model predictions and all field measurements, however, require further studies of CO₂ exchange between the ecosystem and atmosphere and understanding where they need to be improved.

With increasing atmospheric pollution and health issues associated with size of the particulate matter, it has become important to look for techniques that may improve the monitoring resolution. Magnetic bio-monitoring of particulate matter has been used in recent years in some countries as an approach for better spatial resolution that provides proxy indicators for the measurements over large areas. Delhi, which is one of the most polluted cities of not just India, but the whole world, is still probing to understand the possible sources. The present magnetic biomonitoring study was therefore, carried across different land use areas in some air pollution hotspots of Delhi, using common roadside tree species Morus alba, Ficus religiosa, Ficus virens and Ficus benghalensis to understand the magnitude and nature of the particulate pollution, and possible sources by studying magnetic properties (Magnetic susceptibility, Frequency-dependent susceptibility, S-ratio, and SIRM) of the dust deposited on leaves. Mass specific magnetic susceptibility (10⁻⁸ m³ kg⁻¹) values were found to follow the order: Traffic intersection area (25.6–66.5) > Industrial area (25.4–41.3) > Residential area (13.2–30.1) > Institutional area serving as control (2.7–6.6). High magnetic susceptibility values indicated particulates with ferrimagnetic grains of anthropogenic or technogenic origin. Frequency-dependent Susceptibility indicated dominance of coarse multidomain (MD) and Pseudo Single Domain (PSD) +MD grains in industrial area and major traffic intersection. Average S ratio across all study sites ranged from 0.92 to 0.99 indicating presence of soft magnetic mineral with low coercivity. High SIRM values (10⁻⁵Am² kg⁻¹) from 58.1 to 862.3 suggested prevalence of magnetite dominating atmospheric particulates particularly in traffic intersection and industrial area, and to some extent in residential area. Morus alba and Ficus religiosa were found more suitable bio-monitors and the technique provided useful information on size, mineralogy and possible source of the particulates.

Chronic atmospheric nitrogen (N) deposition could influence the functioning of ecosystems as well as their biodiversity. However, N deposition in urban forest ecosystems, especially natural evergreen broad-leaved forests, is not well known. In this study, the concentrations and fluxes of dissolved inorganic N (DIN) and dissolved organic N (DON) in bulk deposition, throughfall, and stemflow were assessed in an urban evergreen broad-leaved forest site over three years, in order to clarify the characteristics of N deposition. At the study site, bulk DIN deposition was 3.7 kg N ha⁻¹ year⁻¹ (1.5 kg N ha⁻¹ year⁻¹ for NH₄–N and 2.2 kg N ha⁻¹ year⁻¹ for NO₃ + NO₂–N), which is the same level as that found in rural areas. In contrast, 6.5 kg N ha⁻¹ year⁻¹ for bulk DON deposition contributed to 66% of the bulk N deposition, which suggests the importance of bulk DON deposition in Japanese forest ecosystems. Passing through the tree canopy, DIN was enriched by 8.8 kg N ha⁻¹ year⁻¹ (3.7 kg N ha⁻¹ year⁻¹ for NH₄–N and 5.1 kg N ha⁻¹ year⁻¹ for NO₃ + NO₂–N) and DON was enriched by 1.5 kg N ha⁻¹ year⁻¹ as net throughfall in the evergreen broad-leaved forest. This reveals that dry deposition of DIN dominates the total DIN deposition onto the urban forest floor, compared to that found in the rural areas, due to the non-negligible N emissions from outside and possibly because of the evergreen broad-leaved forest's greater ability to capture N.

The concentration of ions, metals, and metalloids in hailstone samples was evaluated for the first time in South America. The samples were previously cleaned with ultrapure water to eliminate potential contaminants. The ions concentrations in the samples showed a general pattern according to the following sequence: Ca²⁺ >NO3-> K⁺ > CHOO⁻ > Mg²⁺ > Cl⁻ >SO 42_> Na⁺ >NH4+ > F⁻. Regarding the metals and metalloids concentrations, the order was of Zn > Al > Fe > Mn > Sr > Ba > Cu > Ni > Cr > Pb > Co > V. Ca²⁺ was the most abundant and agricultural activity, one of the sources due to long-distance transport. Concentrations of K⁺ and Cl⁻ may originate from fires that occur every year in the North and Center-West regions of Brazil. Local sources also contributed to the chemical composition, such as soil resuspension contributing mainly to the species and elements Al, Fe, Na⁺, K⁺, SO 42_, and F⁻. Besides that, the region is an agricultural area with unpaved roads and use of fertilizer; therefore, the species and elements NH4+, Mg²⁺, K⁺, Cl⁻, Cu, and Zn, were also associated with local sources, including emissions from vegetation. A possible vehicular contribution was also observed. Among the few existing studies, this is the first to evaluate the hailstones cleaning procedure's efficiency. The findings also support the previous studies' conclusion that the concentration of chemical species varies considerably according to the region of study's characteristics. This work contributes to improve the understanding of local and remote natural and anthropic emissions in this complex atmospheric phenomenon.

The mass concentrations and content of water-soluble anions (Cl⁻, NO₃⁻, SO₄²⁻) and cations (Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺) in the PM₂.₅ particle fraction were measured, and an investigation of their relationship and their contribution to the total PM₂.₅ mass measured was conducted at an urban background site as part of the Croatian monitoring network for air quality located in Rijeka, Croatia. Daily samples of PM₂.₅ particle fraction were collected over 2017 on PTFE filters using a low volume sampler Sven Leckel SEQ 47/50. Mass concentrations of the PM₂.₅ particle fraction were determined by gravimetry according to the standard HRN EN 12341:2014 (EN 12341:2014). The content of water-soluble inorganic anions and cations were determined using a Thermo Scientific ICS-5000 capillary ion chromatograph. Results show that the annual average PM₂.₅ mass concentration was 9.65 μg m⁻³ and did not exceed the limit value of 25 μg m⁻³ given by the Regulation on the level of pollutants in air (OG No. 117/12). The annual average mass concentrations of ions in PM₂.₅ particle fraction was SO₄²⁻> NH₄⁺> NO₃⁻ > Ca²⁺> K⁺> Na⁺> Cl⁻ > Mg²⁺. The contributions of total anion mass and total cation mass to the total PM₂.₅ mass were 25.4% and 12.8%, respectively. The acidic property of PM₂.₅ was obtained in spring and winter and slightly acidic in summer and autumn. For a prediction of the pollutant sources, we ran a factor analysis which was performed using the statistical packages STATISTICA 13.0. After varimax rotation, the obtained four principal component factors were found to account for 86% of the variance. Factor loadings > 0.7 were considered significant.

Precipitation chemistry is important for understanding atmospheric chemistry and transportation mechanism for a region. Therefore, 6-h rain samples were collected manually on the Black Sea Region of Turkey between March 2019 and May 2019. Totally, 21 wet deposition samples were collected in 12 rainy days. The collected rain samples were analyzed by ion chromatography for ions, including Cl⁻, NO₂⁻, NO₃⁻, SO₄²⁻, Na⁺, Ca²⁺, Mg²⁺, K⁺, NH₄⁺. Volume weighted mean (VWM) concentrations of ions were calculated and were in the order of Na⁺ > Ca²⁺ > Cl⁻ > SO₄²⁻ > NO₃⁻ > Mg²⁺ > K⁺ > NH₄⁺> NO₂⁻. The pH values of individual precipitation varied from 4.70 to 8.07. Anion to cation ratio was 0.74 ± 0.34 thus it was an indication of anion deficiency. A strong correlation between NH₄⁺ and SO₄²⁻, NH₄⁺ and NO₃⁻, Ca²⁺ and SO₄²⁻, Ca²⁺, and NO₃⁻ was found in the samples due to the neutralization process. The back trajectory model was used to find the long-range sources and the influence of air masses coming from Saharan, Europe, and the Black Sea. Calcium ion was found to be an effective ion in the neutralization processes by analysis of multiple linear regression and neutralization factor calculation. Approximately 79.5% of SO₄²⁻ and 59.7% of NO₃⁻ were neutralized by Ca²⁺ and NH₄⁺. The washout mechanism for Na⁺, Mg²⁺, Ca²⁺, and K⁺ was dominantly observed on the March 12, 2019. Rainout mechanism was seen on the April 13, 2019 rain event due to the long-range transportation from Saharan Dust.

The daily concentrations of 15 polycyclic aromatic hydrocarbons (PAHs) in PM₁ aerosol samples, including 7 carcinogenic PAHs, were determined in six urban/rural areas in the Czech Republic in winter seasons between 2013 and 2017. The PM₁ aerosol was collected on quartz fibre filters using high-volume samplers for 24 h and PAHs were analysed by GC-MS. The highest concentrations of PAHs were found in the industrial city Ostrava (60.8 ng m⁻³), which is one of the most polluted areas in the Czech Republic, while the lowest concentrations were obtained in the small town Čelákovice (11.7 ng m⁻³) and in the background rural area Košetice (12.3 ng m⁻³). Carcinogenic PAHs formed 43.9%–57.8% of total analysed PAHs.The toxic equivalence factors for individual PAHs adopted from literature and two unit risks (Cal-EPA and WHO) were used for the evaluation of carcinogenic risk of PAHs exposure. The inhalation cancer risk models assume a lifetime exposure (70 years), whereas our measurement was realized for a relatively short duration in winters where concentrations of PAHs are usually high. The average of PAHs concentrations will be lower for the whole year resulting in lower lung cancer risk values. The calculated lifetime lung cancer risk of PAHs exposure for the measured winter periods suggested 1545 cases per 1 million people in Ostrava (industrial area), 192–456 cases per 1 million people in other four investigated cities/towns and 182 cases per 1 million people in Košetice (rural area). The calculated lifetime lung cancer risk values are related only to ambient concentrations of PAHs in atmospheric aerosols. Nevertheless, other factors can influence and increase the lung cancer risk, e.g., occupation, smoking, indoor emissions of coal/wood combustion in stoves or genetic factors of individuals. Our results can also be underestimated due to the determination of PAHs only in PM₁ aerosol.