Atmospheric Pollution Research最新文献

Water-soluble inorganic ions (WSIIs) in PM_2.5 play an important role in the formation of air pollution, which in turn affects climate change and human health. The formation pathways and factors influencing WSIIs have received extensive attention. Here, we analyzed the contents of nine WSIIs in PM_2.5, collected from 2015 to 2021 in Xi'an City, China, with the aim of investigating long-term atmospheric pollution changes. Sulfate (SO₄²⁻), nitrate (NO₃⁻), and ammonium (NH₄⁺) together contributed to 66.8%–88.1% and Ca²⁺ accounted for 5.1%–13.1% of total WSIIs. The relative content of SO₄²⁻ exhibited a gradually decreasing trend (from 49.80% in 2015 to 29.98% in 2021), whereas NO₃⁻ was increased in the same time period (from 13.96% in 2015 to 29.92% in 2021). In addition, the nitrogen oxidation rate showed an annual increase in this period, whereas the sulfur oxidation rate decreased, and their fitted curves intersected in 2019. The key finding of this study is that the air pollution pattern in Xi'an has changed from sulfate-dominated to nitrate-dominated particles, as evidenced by the feature importance results of the random forest model. We propose that more attention should be paid to vehicle emissions and road dust as pollution sources. Overall, the findings of this study serve as a useful reference to aid relevant authorities in devising more effective policies for controlling PM_2.5 pollution at its source.

Black carbon (BC), a component of atmospheric aerosols, strongly adsorbs solar radiation, thereby influencing atmospheric stability and air quality. In this study, the spatiotemporal distribution, historical trends, and influencing factors of BC concentration in China from 1980 to 2020 have been investigated using MERRA-2 (Modern-era Retrospective Analysis for Research and Applications, Vision2) reanalysis dataset, population distribution, and industrial statistics data. The annual total MERRA-2 BC concentration in China (averaging 1.08 μg/m³ over the study period) exhibited three distinct phases: slow growth (1980–1999, 0.02 μg/m³/year), rapid growth (2000–2007, 0.61 μg/m³/year), and gradual decline (2008–2020, -0.014 μg/m³/year). The BC concentration was consistently higher in autumn and winter than in spring and summer, being lowest in July (9.6 μg/m³) and highest in December (14 μg/m³). Spatially, the annual average BC concentration from 1980 to 2020 followed the order: central Yangtze River region (3.14 μg/m³) > eastern coastal region (2.72 μg/m³) > northeastern region (1.40 μg/m³) > western riverine region (0.69 μg/m³) > northwestern frontier region (0.31 μg/m³). High BC-concentration areas, mainly in the central and eastern regions, correlate with regions of vigorous human activities and high industrialization levels, confirming that human activity markedly influences BC pollution. Since 2013, the implementation of emission control strategies and adjustments in the energy structure in China had led to a significant decline in BC concentration. By revealing the spatiotemporal distribution and trends of BC concentration in China, this study provides valuable scientific insights for atmospheric science, environmental protection, and air pollution.

The aim of the present study is to assess the levels of dose rates and the potential risks of exposure to terrestrial gamma radiations in indoors and outdoors in houses in Tiru coal mining area. A highly sensitive portable micro-R gamma survey metre incorporated with a NaI (Tl) scintillator has been used for this study. Indoor and outdoor gamma dose rates (GDRs) have been estimated to be 58.5–178.3 nGy h⁻¹ and 55.5–81.9 nGy h⁻¹, respectively, with averages of 89.7 $\pm$ 7.4 nGy h⁻¹ and 65.7 $\pm$ 5.8 nGy h⁻¹, considerably higher than the reported global population-weighted averages. The annual effective doses (AEDs) for indoors and outdoors have been estimated to be in the ranges of 0.29–0.87 mSv y⁻¹ and 0.07–0.1 mSv y⁻¹, with averages of 0.44 $\pm$ 0.04 mSv y⁻¹ and 0.08 $\pm$ 0.01 mSv y⁻¹, which are marginally higher than the reported global averages. The excess lifetime cancer risk (ELCR) has been calculated and found to be in the range of 1.2 $\times$ 10⁻³-3.4 $\times$ 10⁻³ with an average of 1.8 $\times$ 10⁻³. This study contributes significantly to the scientific understanding of radiation exposure in an open-cast coal mining area as well as its potential impact on human health.

Global and regional observations of air temperature (AT) and specific atmospheric greenhouse gases (GHGs) such as methane (CH₄) and carbon dioxide (CO₂) are required for a variety of applications, including constraining global or regional estimates of their significant impacts on the climate system. The present study employs Atmospheric Infrared Sounder (AIRS) -Level3 monthly products for AT, CH₄, and CO₂, at two standard pressure levels (925 and 500 hPa) over Iraq during 2010–2016. Both CO₂ and CH₄ shows significant seasonal variation, with maximum (minimum) CO₂ observed in June (October), while CH₄ recorded three maximum peaks during April, August, and November, and a minimum in February. CH₄ shows a negative correlation during winter (DJF), spring (MAM), summer (JJA), and autumn (SON) with correlation coefficients (R) −0.627, −0.734, −0.491, and −0.688, respectively. The P-value is below 0.05 (4.14 × 10⁻¹⁵, 2.13 × 10⁻²², 1.1 × 10⁻⁸, and 5.2 × 10⁻¹⁹) for the four seasons, indicating a negative linear relationship. CO₂ shows a low negative correlation in DJF and SON, and a low positive correlation in MAM and JJA seasons, with R values equal to −0.315, −0.221, 0.059, and 0.079, for DJF, SON, MAM and JJA seasons, respectively. The P-value was greater than 0.05 (0.061, 0.728, 0.647, and 0.195) for the four seasons, respectively, indicating a nonlinear relationship with AT. The monthly averaged time-series for CH₄ and CO₂ shows an evident increase, with an annual average increase of 1.81% (4.75) ppbv/year and 3.31% (1.84) ppm/year, respectively. Analysis reveals that the major sink and sources for CH₄ are the presence of hydroxyl (OH) radicals and vegetation, whereas the major sources for CO₂ are anthropogenic emissions, burning fossil fuels, and land-use change. The satellite observations of AIRS can efficiently show the spatiotemporal variations of air temperature versus CH₄ and CO₂ for the study area.

Tropospheric profiles of HCHO, NO₂, and O₃ are important for analyzing ozone formation mechanism. In this study, ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS), light detection and ranging (LIDAR), and in-situ measurements were simultaneously performed to diagnose ozone formation sensitivity at the Heshan Observatory in the Pearl River Delta (PRD) region from September to end October 2019. The profiles of tropospheric HCHO and NO₂ were retrieved from MAX-DOAS measurements using an optimal estimation method. The retrieved surface HCHO and NO₂ results were validated with 2,4-dinitrophenylhydrazine (DNPH) and Thermo 42i measurements, and the correlation coefficients (R) were 0.78 and 0.81, respectively. The retrieved tropospheric vertical column densities (VCDs) of HCHO and NO₂ were compared with TROPOMI measurements, and the correlation coefficients (R) were 0.68 and 0.87, respectively. In addition, MAX-DOAS and LIDAR measurements were combined to diagnose a typical planetary boundary layer (PBL) ozone pollution episode from September 28 to October 10, 2019; this episode was analyzed using HCHO/NO₂ ratio as an indicator and was found to be dominated by the VOC-sensitive regime. Moreover, the regime transition of ozone formation sensitivity was calculated using the surface HCHO/NO₂ ratio and increased O₃ from the MAX-DOAS and Thermo 49i measurements, with transition thresholds of 1.43 and 1.78, respectively. Based on this definition, the ozone formation sensitivity at Heshan Observatory varied from VOC-sensitive ($<$ 0.2 km and $>$ 0.8 km) to NO_x-sensitive (0.3–0.7 km) to VOC-NO_x-sensitive (0.2–0.3 km and 0.7–0.8 km). The results improve our understanding of ozone formation sensitivity in the PRD region.

Surface ozone (O₃) pollution triggered by extreme weather conditions is attracting increasing attention. Heat waves in summer of 2022 were chosen to explore the photochemical and meteorological impacts on O₃ formation in the southeastern coastal industrial city of Quanzhou in China. The machine-learning (ML)-based weather normalization showed that the de-weathered O₃ concentrations (increased by 6.69 μg m⁻³) in 2022 were higher than those from 2015 to 2021. Temperature is the most important variable (33.5%), followed by solar radiation (23.5%) and RH (10.1%), differing from the O₃ pollution in inland cities. The Observation-Based Model (OBM) analysis results showed that hydroxyl radical (OH) was the predominant oxidant for daytime atmospheric oxidation capacity (AOC). And oxygenated volatile organic compounds (OVOCs), NO₂, and CO were the dominant contributors to OH reactivity, accelerating the recycling of ROx radicals and O₃ formation. The daytime reaction rate of HO₂+NO during the O₃ pollution episodes was 20.0 ppb h⁻¹, accounting for 65% of the total O₃ production. The contribution of RO₂+NO to the O₃ production enhanced the possibility of the MDA8h O₃ exceeding the Air Quality Standard of China. This study improves the understanding of O₃ formation mechanisms in a coastal industrial city during heat waves, and the elevated contributions of meteorological conditions to O₃ pollution become more challenge for the reduction of anthropogenic emissions controll.

The Minamata Convention proposes to reduce mercury (Hg) emissions from non-ferrous metal smelting. According to the Global Mercury Assessment report 2018, Hg emissions from non-ferrous smelting reach 14.9% of global Hg emissions. Existing air pollution control devices (APCDs) can effectively remove oxidized Hg (Hg²⁺) and particle-bound Hg (Hg^P) from non-ferrous smelting flue gases, but are less effective in removing elemental Hg (Hg⁰), so deep removal of Hg⁰ is needed. This paper comprehensively introduces the methods for the deep removal of Hg⁰ from non-ferrous metal smelting flue gas, including absorption (Boliden-Norzink scrubbing, thiourea solution scrubbing, predesulfurization-coabsorption method), adsorption (selenium filter adsorption, carbon filter adsorption, ultrafine nano-sulfur adsorption, metal sulfide adsorption) and other methods (condensation, catalytic oxidation, bioprocessing). The latest research progress of these techniques, including the technical principles, influencing factors and applicable conditions, is reviewed. We also compare the advantages and disadvantages of different methods. Finally, the challenges and research perspectives of these technologies are proposed. This review aims to provide some valuable guidance for the subsequent use and development of Hg removal technologies in the non-ferrous metal smelting industry.

In this contribution, we applied a multi-stage machine learning (ML) framework to map daily values of nitrogen dioxide (NO₂) and particulate matter (PM₁₀ and PM_2.5) at a 1 km² resolution over Great Britain for the period 2003–2021. The process combined ground monitoring observations, satellite-derived products, climate reanalyses and chemical transport model datasets, and traffic and land-use data. Each feature was harmonized to 1 km resolution and extracted at monitoring sites. Models used single and ensemble-based algorithms featuring random forests (RF), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), as well as lasso and ridge regression. The various stages focused on augmenting PM_2.5 using co-occurring PM₁₀ values, gap-filling aerosol optical depth and columnar NO₂ data obtained from satellite instruments, and finally the training of an ensemble model and the prediction of daily values across the whole geographical domain (2003–2021). Results show a good ensemble model performance, calculated through a ten-fold monitor-based cross-validation procedure, with an average R² of 0.690 (range 0.611–0.792) for NO₂, 0.704 (0.609–0.786) for PM₁₀, and 0.802 (0.746–0.888) for PM_2.5. Reconstructed pollution levels decreased markedly within the study period, with a stronger reduction in the latter eight years. The pollutants exhibited different spatial patterns, while NO₂ rose in close proximity to high-traffic areas, PM demonstrated variation at a larger scale. The resulting 1 km² spatially resolved daily datasets allow for linkage with health data across Great Britain over nearly two decades, thus contributing to extensive, extended, and detailed research on the long-and short-term health effects of air pollution.

Urban green space (UGS) landscape patterns can alter the spatial and temporal distributions of PM_2.5 and O₃ concentrations by affecting the source‒sink functions of pollutants. However, the role of UGS landscape patterns in the synergistic prevention of O₃ and PM_2.5 pollution has not been adequately studied, especially at the different scales. This study describes the temporal changes in PM_2.5 and O₃ concentrations in Shenyang city via long-term monitoring data from 2015 to 2020. Ridge regression and PCA were used to explore the relationships among the PM_2.5, O₃, and UGS landscape patterns across the four seasons at six scales. The results show that the PM_2.5 concentration significantly decreased as the UGS area increased (r = −0.57, p < 0.05), but the O₃ concentrations showed a nonsignificant increasing trend (r = 0.22, p = 0.51). Landscape patch index and aggregation index significantly negatively affected the PM_2.5 and O₃ concentrations in summer. In contrast, the patch density had a significantly positive effect. Our results suggest that increasing patch homogeneity and aggregation, increasing the proportion of largest patch, and reducing patch fragmentation in the UGS landscapes at 1500–2000 m scales are more favorable for the synergistic prevention of O₃ and PM_2.5 pollution. These findings provide important insights that can help urban planners mitigate air pollution.