Air Quality Atmosphere and Health最新文献

Surface ozone observations in Doon Valley (Dehradun: 30.3^oN, 78.0^oE, 700 m), which acts as a bridge between the Himalayas and the Indo-Gangetic Plain, showed daytime higher values, suggesting a typical urban behaviour in proximity of the Himalayas. Ozone exhibited a maximum in spring (49.2 ± 24.8 ppbv in May) with an hourly average of more than 110 ppbv, followed by a secondary maximum in autumn and the lowest level occurring in the summer-monsoon (~ 13 ppbv in July-August). Ozone levels exceeded the 8-hour National Air Quality Standard limit (50 ppbv) throughout the year, except in July-September. The observed spring maximum was found to be triggered by biomass burning, leading to 9–50% enhancement in ozone during the high-fire activity period (April-May). Using a box model, in-situ photochemical ozone production and loss were estimated at ~ 41 ppbv and ~ 8 ppbv, respectively. The model highlighted the dominant role of the HO₂ + NO reaction (85.6%) in ozone production and the O₃ + HO₂ reaction (56.2%) in ozone loss. Exposure metrics analysis (M7 and AOT40) estimated an annual loss of 27–37 kilotons of wheat and 14–32 kilotons of rice production due to elevated ozone levels. Furthermore, hazard ratios for non-methane hydrocarbons and lifetime cancer risk values for benzene and ethylbenzene exceeded the standard limits (USEPA and WHO), indicating significant health risks to the population. Model and satellite-based studies demonstrated the NO_x-sensitive behaviour of ozone production in this Himalayan region, where aromatics exhibited the maximum ozone formation potential among different NMHCs.

Urban green space can effectively alleviate air pollution, in which vegetation structure plays an important role. However, these green spaces with varying vegetation structures exist in different environmental backgrounds of the city. By analyzing the influence of the different environmental backgrounds on the dust retention effect of green spaces with varying vegetation structures, green spaces can be truly utilized as a solution in alleviating air pollution. Therefore, according to the typical characteristics of landscape patterns and different coverage ratios of green areas in Xi’an city, China, the matrices of urban landscape were divided into three types, which include "green space", "grey-green mixed space" and "gray space." In each environmental background, urban green space was divided into three levels: horizontal structure, species composition and vertical structure. Subsequently, 13 types of green spaces with different vegetation structures and three hard (no vegetation present) squares as control groups were selected. A one-year on-site monitoring was conducted on urban green spaces and concentrations of TSP, PM₁₀, PM_2.5 and PM₁. The results showed that: (1) In the green space, the concentrations of PM₁ and PM_2.5 were relatively higher. In the grey-green mixed space, the average concentration of air particle of all four particle sizes was the lowest. In the gray space, the concentrations of PM₁₀ and TSP were more concentrated. (2) Under the same matrices, due to the different locations of the plots, the concentration of air particles of different sizes was significantly different. Under the different urban environmental backgrounds, temperature, relative humidity, wind speed and air pressure all showed the same trend in the change of air particle concentration. (3) The one-layer green space structure was most suitable for planting. Considering the green space, the coniferous one-layered green space (CO) structure was recommended. The partly-closed broad-leaved one-layered green space (P-CBO) was found to be more suitable for the grey-green mixed space. Considering the gray space in the city center, it was suggested to plant the closed mixed coniferous and broad-leaved one-layered green space (CMO) structure. The findings provide empirical support for the future collocation of urban green vegetation structure and the improvement of urban air quality.

Graphical Abstract

Understanding the pollution levels, potential sources, and chemical reactivity of atmospheric volatile organic compounds (VOCs), the key precursors of ozone (O₃) and fine particulate matter (PM_2.5), is important for emission control and air pollution abatement. This study presents a systematic VOCs analysis in a less studied heavy industrial urban agglomeration located in Northeast China. Using a cruising platform, we conducted real-time monitoring of VOC concentrations and components at Changchun (CC), Jilin (JL), Siping (SP), and Liaoyuan (LY) in Jilin Province. During the observation period, the average VOC concentrations at CC, JL, SP, and LY were 63.38 ± 127.03, 260.39 ± 855.76, 18.06 ± 17.17, and 10.12 ± 17.48 µg/m³, respectively. Halocarbons were predominant with a high percentage of contribution (22.4–31.1%) to the total observed VOCs for all cities. Combined with 2020-based anthropogenic VOCs emission inventory of Jilin Province, we concluded that industrial processes had the largest contribution to VOCs concentration in CC, whereas petrochemical emission was the major source of VOCs in JL. The assessment of atmospheric photochemical reactivity indicates the dominant role of aromatics and alkenes in O₃ formation potential (OFP). As the second-most abundant species in CC and JL, aromatics contributed over 50% of the OFPs. Alkenes played a dominant role in O₃ formation in SP and LY, accounting for nearly half of the total OFPs. Considering the VOC emission characteristics and OFP results, we suggest that reducing aromatics emissions, particularly benzene, toluene, ethylbenzene, and xylene, should be given higher priority to mitigate O₃ pollution and prevent health risks. Moreover, industrial-related, and petrochemical sources are crucial in the evolution of O₃ pollution, which should be incorporated into heavy industrial urban air quality management and targeted control of O₃ pollution in Northeast China.

The escalation of PM_2.5 pollution in the Zhengzhou Metropolitan Area (ZMA) underscores the pressing need for air pollution mitigation measures. We utilized high-resolution PM_2.5 data from 2020, with a 1 km spatial resolution, to identify and comprehend the factors influencing PM_2.5 concentration across the urban–rural continuum. This extensive dataset, inclusive of terrain, meteorological data, vegetation cover, population density, GDP, nighttime light data, and land use categories, facilitated our analysis of PM_2.5 trends across the urban–rural spectrum in nine ZMA cities. Our results demonstrate that there is no consistent correlation between city size and classification with PM_2.5 pollution levels. However, urban and suburban regions demonstrated higher pollution levels compared to rural areas. The PM_2.5 concentrations exhibited considerable variance along the urban–rural continuum. Spring and summer exhibited rising concentrations along the continuum, while autumn witnessed a decrease. Spatially, the PM_2.5 concentration demonstrated higher trends in the eastern and southern regions compared to the western and northern areas, indicating distinctive urban–rural gradient patterns. The influencing factors displayed a scale effect: metropolitan areas showed a stronger correlation with natural elements such as elevation and wind speed; suburban regions correlated with meteorological factors; urban areas were notably impacted by socio-economic factors. Effective collaboration among cities for emission reduction and pollution control is crucial, irrespective of meteorological conditions.

This first key study examines the influence of functional residue capacity (FRC) associated with Body Mass Index (BMI) on PM_2.5 regional and lobar deposition. Size-segregated particulate matter (PM) was collected using the cascade impactor and multiple path particle dosimetry (MPPD) model is used to simulate the regional and lobar deposition in males and females aged 19–49, with various BMI categories. Morning and evening commutes exhibited a mean PM_2.5 of 127.89 ± 38.42 µg m⁻³ and 157.2 ± 58.84 µg m⁻³, respectively. The elemental analysis indicated the prevalence of elements in the order of B > Ca > Fe > Pb > Al > Hg > TI > Mg > Cu > K > Na > Mn > Cr during commuting. Regardless of age and gender, the pulmonary region exhibited the highest PM_2.5 deposition levels in comparison to both the head and tracheobronchial regions. Females aged 19 and 49 exhibited a higher incidence of pulmonary accumulation of PM_2.5 than males of about 41% and 43.3% respectively. Among individuals aged 19 to 49, lobar deposition patterns of PM_2.5 revealed higher prevalence among females than males, showcasing relative variations across different BMI categories: 17 (3.1%), 18 (3.2%), 19 (3.12%), 22 (3.24%), 25 (3.21%), 27 (3.1%), and 30 (3.25%). Fine particles showcased maximum deposition in the right upper (25%), right lower (27%) and left lower lobes (26%). These findings emphasize the urgent need for extensive and meticulous research on BMI-based, gender-specific impacts on particle deposition and lung health within this critical bodily system.

Air pollution potential is a measure of the inability of the atmosphere to disperse pollutants away from the source. It depends on Planetary Boundary Layer Height (PBLH) and wind speed. Global air pollution potential Index (APPI) maps have been generated for the first time using 40 years (1980–2019) of PBLH and wind speed data available from ECMWF Reanalysis v5 (ERA5) data. These are useful for identifying ventilation corridors and for sustainable development. The seasonal climatology of APPI is also analyzed. Long-term trends in Ventilation coefficient (VC), PBLH, Wind speed, PM_2.5, and Aerosol Optical Thickness (AOT) were analyzed globally and in over 30 cities to understand their future impact on climate change scenarios. High APPI is observed in the South Asian regions, giving rise to PM_2.5 and AOT hot spots, and are naturally disadvantageous. Long-term trends in VC and associated trends in PBLH and Wind speed suggest that the PBLH is decreasing at the rate of 1–3 m per year over south Asia, and wind speed is decreasing at the rate of 0.01–0.02 m·s^− 1per year, resulting in the decrease of VC of about 1–25 m²·s^− 1per year. If this trend continues, South Asia will have more air pollution potential, causing severe stagnation of air pollutants in the coming years and putting health risks to 1.8 billion people. The surface PM_2.5 and AOT are increasing at 0.5–1.5 µg·m^− 3 per year and 0.005–0.01 per year for South Asia cities. Sustainable development goals and climate policies/negotiations should consider global air pollution potential as an essential variable in planning and mitigation.

This study targets to determine the oxidative potential (OP) of fine aerosols in an urban-industrial area of the Lisbon Metropolitan Area (Portugal) and, in addition, to identify which pollution sources may have an impact on the OP levels of fine aerosols. For this purpose, thirty samples were selected from a set of 128 samples collected over one year (Dec 2019-Nov 2020), based on the highest load for each source (both mass and %) previously assessed by source apportionment studies (using Positive Matrix Factorisation, a total of 7 different sources were identified: soil, secondary sulphate, fuel-oil combustion, sea, vehicle non-exhaust, vehicle exhaust and industry). The OP associated with the water-soluble components of PM_2.5 was assessed using the dithiothreitol (DTT) method. The samples had a mean DTT activity (normalised to the mass) of 12.9 ± 6.6 pmol min^− 1 µg^− 1, ranging from 3.5 to 31.8 pmol min^− 1 µg^− 1. The DTT activity (normalised to the volume, ({text{O}text{P}}_{text{V}}^{text{D}text{T}text{T}})) showed to have a significant positive association with PM_2.5 levels (R² = 0.714). Considering that the mass contributions of the different sources to the PM_2.5 levels were known, Spearman correlations were assessed and significant correlations were found between ({text{O}text{P}}_{text{V}}^{text{D}text{T}text{T}}) and three different sources: vehicle exhaust (ρ = 0.647, p-value = 0.001), fuel-oil combustion (ρ = 0.523, p-value = 0.012) and industry (ρ = 0.463, p-value = 0.018). Using a multiple linear regression analysis, these three sources were found to explain 82% of the variability in ({text{O}text{P}}_{text{V}}^{text{D}text{T}text{T}}), with vehicle exhaust being the most influential source.

Anthropogenic pollution impacts human and environmental health, climate change, and air quality. Elbasan, an industrial town about 50 km from the capital city of Tirana, is susceptible to environmental contamination as a result of the outdated technology applied in metal processing and metallurgy. Environmental biomonitoring was conducted to provide a comprehensive view of contamination levels in atmospheric deposition as a result of anthropogenic influences. The aim of this study is to evaluate the distribution of toxic metals in the atmospheric deposits in this area. Concentrations of thirteen trace metals were studied by using the passive method of moss biomonitoring. The ground-growing moss samples, Hypnium cupressiforme, were collected during the dry season of June 2021 from 12 sampling sites evenly distributed over the study area. Statistical analysis was used to assess the spatial distribution, concentration levels, variances, and relationships of the trace metals. The knowledge and the obtained statistical data harmonization made it possible to discuss the most probable sources of contaminants. Very strong and significant inter-element correlations were found between Cr, Ni, Co, and Fe. It looks like an anthropogenic association, which is mostly characteristic of air particles emitted from iron-chromium and iron-smelter plants. Together with cement factories, those are the primary emitters of trace metals in the Elbasan area and the primary sources of the deposition of Cr, Ni, Co, and Fe in this area. Substantial impacts were also found from soil dust emissions.

The two versions of the reference method of sulphur dioxide (SO₂) measurement in ambient air (pararosaniline method) available as the Environment Protection Agency (EPA) USA (CFR 40 Part 50, Appendix A) and Bureau of Indian Standards (BIS) India (IS 5182 (Part 2):2001) standard methods were analytically studied. For accuracy and precision of the data obtained, a certain set of specifications should be ascertained before using the method for sample analysis as per the guidelines. On comparing the two methods of operation, the stated set of specifications are fulfilled for the EPA method but not for the BIS method. A different set of specifications were observed for the BIS method (absorbance blank: 0.012 ± 0.001 abs units, slope of calibration curve: 0.014 ± 0.001 abs units/µg SO₂, intercept of calibration curve: 0.003 ± 0.002, calibration factor:72.0 ± 4.2). The absorption efficiency as well as the method efficiency of both methods were tested using three different concentrations (0.3 ppm, 0.5 ppm, and 0.8 ppm) of standard SO₂ gas. The absorption efficiency of both the methods was found to be 100%. The average method efficiency of the EPA method at 0.3 ppm, 0.5 ppm and 0.8 ppm were found to be 81 ± 8%, 81 ± 6% and 87 ± 1% while that of BIS method was observed to be 91 ± 5%, 93 ± 2%, 89 ± 4% at the respective concentrations. An uncertainty estimation study was also performed considering factors involved in sampling and analysis. A combined uncertainty < 9% and < 7% was observed for EPA and BIS method, respectively. This study presents a comprehensive examination of the operational aspects of two versions of pararosaniline method employed for measuring SO₂ in ambient air. The results indicate a need for redefining the specifications outlined in the BIS method. Notably, the BIS method displays greater sensitivity to low blank values compared to the EPA method. Additionally, the study introduces, for the first time, working factors and specifications associated with the BIS method for SO₂ measurement. These findings suggest their potential inclusion in the standard method as a means to enhance data quality and reliability in the assessment of SO₂ levels in ambient air.

The Maptaphut industrial area, one of the largest petrochemical complexes in Thailand, is the major cause of the various air pollutants. The larger concern is that a significant volume of air pollution is emitted and that air quality management needs to be improved. This is in part due to a lack of deeper understanding of how anthropogenic emissions are emitted from different sources in this area— especially volatile organic compounds (VOCs). Moreover, it has complicated relationship results of air pollution, disease mechanisms, and health effects. As a result, its available data can only give a rough indication of them. These factors are often assumed to be associated with economic consequences, but assessing the health-related economic losses caused by air pollution remains limited in many ways.

Four targeted VOCs were analyzed, including benzene, 1,3-butadiene, 1,2-dichloroethane, and vinyl chloride from industrial and non-industrial sources, namely stacks, flares, storage tanks, wastewater treatment plants, transportation and marketing, fugitive losses, slurry/open equipment/vessel, and on-road mobile emissions. Source apportionment can be conducted using emissions inventory (EI) to establish pollution source databases, the dispersion model, and then imported on the risk model by determining receptors. The AERMOD dispersion model coupled with the IRAP-h view model was used to predict the spatial distribution of the ground-level concentration and analyze the inhalation health risk covering cancer and non-cancer risks— as well as the prioritization of pollutants.

The risk assessment results indicated that the highest risk occurred most from 1,3-butadiene for cancer and chronic non-cancer risks contributed to fugitive sources, about 83% and 94%, and most benzenes for acute non-cancer risk contributed to on-road mobile sources, at about 56%.

Consequently, the benzene classified as the most important priority depending on its risk results, comprehensive epidemiological studies, and discharge volumes.

With the economic benefits assessment, BenMAP-CE was further utilized to estimate the health impacts and economic value of multiple scenarios to facilitate decision-making for benzene reduction. Overall, the 10% rollback policy for benzene concentration, monetized value of about 13.13 billion US dollars for all mortalities, gave the best practical scenario for the most economically viable option based on the B/C (benefit/cost) ratio results in Maptaphut. Ultimately, policymakers need to take additional measures to improve air quality and reduce health impacts while also considering economic benefits, especially benzene reduction.