Air Quality Atmosphere and Health最新文献

Trace metals (TMs) pose significant environmental and health risks due to their tendency to bioaccumulate and exhibit toxicity. This study investigates TM contamination within a university environment using cobwebs (CBWs) as passive samplers. CBWs were collected from various campus locations, including laboratories, student hostels, cafeterias, lecture halls, and roadways, to assess TM concentrations and their potential sources. Eight TMs (Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn) were quantified using inductively coupled plasma optical emission spectrophotometry (ICP-OES). Across all samples, the ∑TMs concentrations (µg/g) ranged from 0.01 to 0.19, 0.47–7.92, 0.04–4.46, 0.13–4.07, 0.03–4.64, 0.31–7.23, 0.05–3.39, and 0.14–22.24 for Cd, Cr, Co, Cu, Mn, Ni, Pb and Zn, respectively. The results revealed significant spatial variations, with laboratories exhibiting the highest TM concentrations, followed by student hostels and roadways. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) identified laboratory emissions, vehicular sources, and infrastructural materials as major contributors to TM pollution. Health risk assessments based on inhalation and dermal exposure routes indicated that non-carcinogenic and carcinogenic risks remained within acceptable limits; however, certain metals, such as Cr, Cd, and Co, showed elevated potential risks. The findings highlight the necessity for stringent waste management and continuous environmental monitoring in academic institutions and highlight the effectiveness of CBW as a cost-efficient bioindicator for air quality assessment, advocating for their broader application in environmental monitoring.

The thoracic fraction of atmospheric particulate matter (PM₁₀) from road dust was collected with an on-site resuspension chamber on the pavements of the access roads to three quarries (limestone, granite and clay-sand). The PM₁₀ dust loads on the roads at the entrances to these facilities (160–524 mg m⁻²) were up to 5–6 times higher than those obtained on the nearby arteries (37.6–102 mg m⁻²). The PM₁₀ emission factors were much higher than the values ​​obtained on urban roads, reaching 893–1932 mg km⁻¹ veh⁻¹ on the main roads and 2798–7299 mg km⁻¹ veh⁻¹ at the quarry entrances. Carbonaceous constituents represented PM₁₀ mass fractions lower than 2.3%. Carbonates constituted 8.3% of the PM₁₀ mass from the limestone quarry access road, compared to 2.3% in road dust from the granite and clay sand quarries. The elemental composition of PM₁₀ from the limestone quarry access road was dominated by Ca and a much more moderate contribution from Al, Fe, K and Mg, while the abundances of K, Al, Ca and Fe were more balanced in dust samples from the roads to the other two quarries. Mineralogical analysis by XRD showed that road dust from the limestone quarry was dominated by rock minerals such as calcite (95–97%), while its presence in PM₁₀ of roads in the vicinity of other quarries fell below 16%. Phyllosilicates and quartz were the dominant minerals in PM₁₀ of the access roads to the granite and clay-sand quarries, respectively, with lower contributions from K-feldspar, plagioclase, calcite and dolomite. While total cancer risks remained below the generally accepted threshold, hazard index (HI) values exceeding the safety threshold of 1 were observed in most areas, particularly around granite and clay quarries, where children face an elevated non-carcinogenic risk. The ingestion route was identified as the primary contributor to these risks, with zirconium (Zr) being the dominant element influencing the HI.

Indoor and outdoor PM (particulate matter) air pollution is a major environmental problem due to its potential impact on human health. To understand the exchange relationship between indoor and outdoor PM composition, the compositional data analysis technique has been applied to data obtained from a previous study. In this study, PM levels measured both indoors and outdoors in two California dwelling units during Fall were analysed. The results revealed two distinct scenarios. In unit 933, indoor PM contained approximately 22% fewer coarse particles than outdoor PM. This difference was attributed to both the lack of indoor PM sources and limited air exchange due to residents’ habit of keeping windows and doors closed. This likely induced gravitational settling of the coarser indoor PM fractions, enriching the finer ones. In this unit, no evidence of a direct link between indoor and outdoor PM was found, suggesting that outdoor PM did not influence indoor PM. Conversely, in unit 921, indoor PM contained approximately 72% fewer fine particles than outdoor PM. This result was attributed to the absence of indoor PM sources and continuous air exchange, as occupants routinely left windows and doors open during the day. Statistical analysis indicated a relationship between indoor and outdoor PM, suggesting that outdoor PM influenced indoor PM. The proposed method sheds light on the possible mechanism that influences the coarse and fine size fraction of indoor and outdoor PM, providing a useful technique for studying their complex relationship.

Achieving both “livability” and “business-friendliness” represents people’s aspiration toward a region’s economic, social, and ecological well-being. In recent years, numerous local governments in China have introduced various “business-friendliness” policies aimed at guiding labor migration backflows for entrepreneurship. However, whether these policies adequately address the equally important attribute of “livability” has emerged as a crucial issue deserving profound contemplation. This paper employs panel data from 1775 counties in China from2011-2021 and a Double/Debiased Machine Learning (DML) method to evaluate the impact of the Return-to-Hometown Entrepreneurship Pilot Policy (RHEPP, a proxy for “business-friendliness”) on air quality (AQ, a proxy for “livability”). The study found that: Firstly, implementing RHEPP is conducive to improving AQ. Heterogeneity assessment suggests that the improving impact of RHEPP on AQ is long-term and increases annually, whereas the spillover effect of RHEPP is only significant in a specific range and decays spatially. Secondly, RHEPP achieves this positive impact on AQ through the effects of economies of scale, industrial structural adjustment, and technological innovation. Thirdly, the influence of RHEPP on AQ is heterogeneous in industry and region This paper can provide valuable policy recommendations for achieving sustainable development in entrepreneurship and county-level economies.

Currently, within the framework of China’s “dual carbon” goals—aiming to reach a carbon peak by 2030 and achieve carbon neutrality by 2060—agriculture plays a dual role as both a carbon source and a carbon sink. It holds significant potential for carbon sequestration and emission reduction. Therefore, studying the spatial and temporal evolution patterns and driving factors of regional agricultural carbon emission efficiency (ACEE) is crucial for advancing low-carbon agricultural development. This study analyzes agricultural carbon emission data from the Yangtze River Delta (YRD) region spanning the years 2001 to 2020. It utilizes the Super-SBM model and the Global Malmquist-Luenberger (GML) index to investigate the temporal and spatial characteristics of ACEE from both static and dynamic perspectives. Furthermore, the Tobit model is employed to identify the key factors influencing ACEE. The results confirmed that: (1) From the perspective of static efficiency, the average ACEE value from 2001 to 2020 was 0.83, with the ACEE values ranked from highest to lowest as follows: Jiangsu, Shanghai, Zhejiang, and Anhui. (2) From the perspective of dynamic efficiency, the ACEE exhibits an upward trend, with an average annual growth rate of 2.10%. Technological advancements can enhance the improvement of the GML index. (3) The use of pesticides, rural electricity consumption, agricultural industrial structure, and the level of rural economic development all significantly contribute to the enhancement of ACEE. Hence, the government should develop policies that reflect the current state of regional agricultural carbon emissions, tailored to local conditions. By optimizing agricultural production structures and regional layouts, introducing innovative green technologies, and implementing a range of additional measures, it can collaboratively enhance the improvement of ACEE in the YRD region, thereby contributing to China “dual carbon” goals.

Sustained urbanization and industrialization have exacerbated PM_2.5 pollution, posing severe threats to public health and the quality of life. The imperative need for balancing urban development and environmental protection underscores the significance of understanding how built-up landscape patterns affect PM_2.5 concentrations. Using 21-year time-series data (2000–2020) for Anhui Province, we applied piecewise linear regression to detect turning points in PM_2.5 concentrations and quantified their multi-scale spatiotemporal dynamics during the increasing and decreasing phases. Furthermore, bivariate spatial autocorrelation and geographically weighted regression models are employed to explore how built-up landscape patterns influence PM_2.5 concentrations across different spatial scales and seasons. The key findings are as follows: (1) 2013 was the turning point for PM_2.5 concentration in Anhui during 2000-2020. Before 2013, changes in built-up landscape patterns were predominantly positively correlated with rising PM_2.5 levels, while after 2013, this relationship generally became negative. (2) The impact of built-up landscape patterns on PM_2.5 concentrations in different regions is closely related to the topography. Effects are more pronounced in mountainous regions than in the plains. Spatial scale analysis showed that correlations strengthened with larger grids in plains but weakened in mountainous areas. (3) The influence of built-up landscape patterns on PM_2.5 concentration was significantly stronger in winter than in summer. This study elucidates the spatiotemporal heterogeneity of how built-up landscapes affect PM_2.5, providing critical insights for optimizing urban spatial planning to improve air quality.

Air pollution stands out as a major problem that threatens the environment and public health in urban environmets. In a densely populated megacity like İstanbul, the concentration and distribution of pollutants are greatly affected by meteorological conditions and local environmental factors. In this study, hourly air quality data (PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂ and O₃), meteorological variables (temperature, relative humidity, wind speed and direction) and cloud base height (CBH) data measured with a ceilometer were analyzed between January 1, 2023 and December 31, 2023 in İstanbul. Pearson correlation coefficient, Mann-Kendall trend test and time series analysis methods were used to evaluate the data. The findings revealed seasonal variations in air pollutant levels and reach high concentrations in the winter months. It was determined that particulate pollutants such as PM₁₀ and PM_2.5 tend to accumulate especially in low temperature and high relative humidity (RH) conditions. A positive correlation was observed between RH and particulate pollutants, and a negative relationship with temperature and wind speed. For example, it was observed that particulate matter (PM) concentrations increased when the temperature decreased, and dispersion was facilitated during periods when wind speed was high. In addition, a strong relationship was found between CBH and air pollutants. Analyses showed that PM and gaseous pollutants tended to accumulate in the atmosphere during periods when CBH was low. This situation, combined with the decrease in atmospheric stability and the effect of high RH in winter months, further deteriorated air quality. Seasonal analyses showed that meteorological variables such as temperature, RH and wind had varying impacts on on air quality. In particular, it was determined that gaseous pollutants such as NO_x and SO₂ increased during winter months, and this was associated with low atmospheric mixing and high stability conditions. Additionally, winds originating from certain directions were found to contribute to elevated pollutant concentrations.

Assessing the performance of an atmospheric dispersion model to estimate nitrogen dioxide (NO₂) remains challenging in regions with limited monitoring, where observations are scarce and key variables like ozone (O₃) are often unavailable. In this study, we explore different methodologies to assess the influence of chemistry on modelled high NO₂ concentrations using DAUMOD-GRS, an urban atmospheric dispersion model with a simplified chemical scheme, applied to the Metropolitan Area of Buenos Aires (MABA) over four years of hourly simulations. We evaluate three complementary approaches: (i) clustering of input/output conditions associated with NO₂ exceedances; (ii) analysis of the NO₂/NOx concentration ratio; and (iii) sensitivity simulations to key parameters in the chemical scheme, such as reaction time and background O₃. Clustering proved useful for detecting metadata issues and identifying consistent conditions associated with exceedances. Our results highlight that, although the NO₂/NOx ratio is widely used as a chemical diagnostic, its value depends strongly on the accuracy of NOx estimates, which can limit its applicability for evaluating chemical processes in practice. A bivariate analysis of modelled-to-observed concentration fractions of NO₂ vs NOx proved useful for quickly visualizing the distribution of errors in NO₂, NOx, and their ratio, along with associated input data conditions. Sensitivity tests revealed that the fraction of NO₂ in NOx emissions had greater impact on hourly exceedances, while background O₃ had a larger influence on annual means. These methods offer complementary insights and are particularly valuable in data-scarce contexts. Future work may benefit from incorporating O₃ observations and comparisons with chemical transport models to further support chemical evaluations and to explore additional reactions beyond those included in simplified schemes.

The aerosol subtypes and their distinct aerosol radiative effects are highly uncertain components in the global climate model due to the lack of observations at the required spatiotemporal scales, especially the vertical variation. In this study, the radiative effects of dust and smoke aerosols and their responses to boundary layer processes using Micro Pulse Lidar (MPL) observations conducted at Solapur (17.6°N, 75.9°E, 510 m a.m.s.l.), a rain-shadow region, India, during June 2023, are reported. Three important events characterized by the presence of an elevated aerosol layer (EAL), intrusions of dust and smoke aerosols, and fumigation with associated radiative forcing and heating rates were explored. The EAL observed during 17–19 June 2023 at ~ 1.5–4.0 km is mainly attributed to dust aerosols (~ 90%) with a depolarization ratio > 0.2. The event with intrusion of smoke plumes, constituted mainly of black carbon, with a depolarization ratio < 0.1. The strong fumigation event revealed that the heating rate within the boundary layer (below ~ 1.0 km) was nearly double that observed on weak fumigation days. The heating rates varied between 0.43 ± 0.04 K/day on weak fumigation days and 0.79 ± 0.07 K/day on strong fumigation days. The enhanced atmospheric heating rates are also observed at the dust/smoke residing altitudes. The average aerosol extinction within the boundary layer is ~ 0.30 ± 0.06 km⁻¹, while ~ 0.24 ± 0.08 km⁻¹ from the free troposphere indicates a significant contribution from elevated aerosol layers. During the campaign period, an overall radiative forcing was estimated to be 20.65 ± 6.18 Wm⁻² in the atmosphere, and at the surface − 31.38 ± 5.40 Wm⁻², at the top of the atmosphere is about − 10.72 ± 2.40 Wm⁻².

Indoor air quality (IAQ) is critical to human health, given the considerable amount of time spent indoors. Volatile Organic Compounds (VOCs) contribute substantially to IAQ degradation and potential health risks. VOCs significantly contribute to the degradation of IAQ and pose potential health risks. This study assessed VOC concentrations in the Instituto Nacional de Silicosis (INS) building, (which includes laboratories, offices, and common areas), according to ISO 16000-5 guidelines. Sampling was carried out using P-type pumps with Tenax^® TA sorbent tubes and analysed via thermal desorption and Gas Chromatography–Mass Spectrometry (GC-MS), in compliance with UNE-EN 14,662 standards. Of the 49 targeted VOCs, 29 were detected across several chemical classes. Toluene was the most abundant compound, while benzene, a Group 1 human carcinogen, was found both indoors and outdoors, with concentrations reaching up to 0.89 µg/m³. All individual VOCs were below 1% of the Spanish Occupational Exposure Limit Values (OELVs), and total VOC (TVOC) levels remained consistently below the recommended threshold of 200 µg/m³. Certain areas, such as the cleaning room and the library, exhibited comparatively higher concentrations and a broader range of compounds. In the library, this was likely due to books containing thin slices of real lungs, preserved with varnish. Although the results indicate no immediate health risk, the detection of hazardous substances such as benzene, even at low concentrations, emphasises the importance of continuous monitoring. The study recommends potential mitigation strategies including improved ventilation and the use of indoor plants for biofiltration. These findings support the need for proactive IAQ management and further research into the long-term health implications of occupational exposure.