Research

16 pages, 13271 KiB

Open AccessArticle

The Impact of Anthropogenic VOC Emissions on Atmospheric Pollution: A Case Study of a Typical Industrialized Area in China

by Xin Gao, Yanan Wang, Lin Wu, Fangyuan Zheng, Naixiu Sun, Guangxun Liu, Yongji Liu, Peng Meng, Luna Sun and Boyu Jing

Atmosphere 2023, 14(10), 1586; https://doi.org/10.3390/atmos14101586 - 20 Oct 2023

Viewed by 1330

Abstract

Volatile organic compounds (VOCs) are the main precursors of pollution from ground ozone (O₃) and PM_2.5, which cause the deterioration of urban air quality. The emissions of VOCs from industrialized areas are significant and their characteristics are complex, which [...] Read more.

Volatile organic compounds (VOCs) are the main precursors of pollution from ground ozone (O₃) and PM_2.5, which cause the deterioration of urban air quality. The emissions of VOCs from industrialized areas are significant and their characteristics are complex, which nowadays contribute significantly to the challenges of investigating the emission inventory. Taking a typical industrialized area in Tianjin as a case study, the anthropogenic VOCs emission inventory for 2020 was established in this study by using the activity data from a large-scale survey and the latest emission factors. The impact of VOCs on the environment was analyzed from the perspective of the combined control of PM_2.5 and O₃. The results showed that the total emission of VOCs in 2020 was about 1.68 Gg, mainly from industrial processes and mobile sources, which accounted for 38.4% and 36.5% of the total emissions, respectively. The top 10 emitted VOCs were toluene, acetone, ethylbenzene, m/p-xylene, i-pentane, n-hexane, formaldehyde, benzene, ethyl acetate and ethylene. The dominant species of O₃ formation potential (OFP) were almost all aromatic hydrocarbons and alkenes, with m/p-xylene contributing the most to the OFP emissions (8.90%). The top 10 secondary organic aerosols formation potential (SOAP) emission species were aromatic hydrocarbons and long-chain alkanes, and the largest emission came from toluene (39.9%). An analysis of an ADMS diffusion model showed that VOCs emitted from traffic-heavy main roads and industrialized central areas had the greatest impact on the air quality in the surrounding areas. The VOCs concentration was higher in winter due to unfavorable meteorological conditions. Our research updated the VOC inventory of industrialized areas and evaluated VOCs species reactivity and their impact on ambient air quality. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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16 pages, 7145 KiB

Open AccessArticle

Characteristics Analysis of Volatile Organic Compounds Pollution in Residential Buildings in Northeast China Based on Field Measurement

by Wen Sun, Weidong Yan, Kailiang Huang, Jiasen Song and Guoqi Liu

Atmosphere 2023, 14(10), 1543; https://doi.org/10.3390/atmos14101543 - 09 Oct 2023

Viewed by 755

Abstract

A total of 8 mechanically ventilated residential buildings and 8 naturally ventilated residential buildings were selected to analyze the pollution characteristics of indoor VOCs under different ventilation modes in the severe cold area of northeast China. On typical meteorological days in each season, [...] Read more.

A total of 8 mechanically ventilated residential buildings and 8 naturally ventilated residential buildings were selected to analyze the pollution characteristics of indoor VOCs under different ventilation modes in the severe cold area of northeast China. On typical meteorological days in each season, VOCs were detected on site, and ventilation modes were investigated by long-term online monitoring. The test results showed that the TVOC (total volatile organic compounds) concentrations varied greatly in different seasons or different functional rooms, and the TVOC concentration was the highest in winter, with a value of 0.994 mg/m³. The kitchen was the place with the most serious VOC pollution, and the TVOC concentration could reach 1.403 mg/m³. Benzene series and methylsiloxane had the highest detection rates, but the detected concentrations were low, and the average concentrations were 0.025 mg/m³ and 0.013 mg/m³ respectively. Among the VOC types with a detection rate greater than 50%, the average proportions of aldehydes, alkanes, and benzene series were 18.7%, 15.39%, and 14.38%, respectively. And their mass ratios were also high, which were 14.90%, 30.85%, and 15.70%, respectively. The annual daily average ventilation duration of mechanically ventilated residential buildings was 7.84 h longer than that of naturally ventilated residential buildings. The median TVOC concentrations of mechanically ventilated residential buildings and naturally ventilated residential buildings were 0.621 mg/m³ and 0.707 mg/m³, respectively. The fresh air system was applicable in the severe cold area of northeast China. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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18 pages, 2915 KiB

Open AccessArticle

An Ensemble Model for PM2.5 Concentration Prediction Based on Feature Selection and Two-Layer Clustering Algorithm

by Xiaoxuan Wu, Qiang Wen and Jun Zhu

Atmosphere 2023, 14(10), 1482; https://doi.org/10.3390/atmos14101482 - 25 Sep 2023

Viewed by 809

Abstract

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns are crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5-related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. [...] Read more.

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns are crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5-related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components—feature selection, clustering, and integrated prediction—the model first employs the non-dominated sorting genetic algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the AdaBoost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model’s results were compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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23 pages, 1869 KiB

Open AccessArticle

Research on the Emission Reduction Effect of International Technology Import in China’s Key Industries

by Wenchao Li, Zhihao Wei, Lingyu Xu and Shumin Jiang

Atmosphere 2023, 14(7), 1146; https://doi.org/10.3390/atmos14071146 - 14 Jul 2023

Viewed by 829

Abstract

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction [...] Read more.

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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17 pages, 9197 KiB

Open AccessArticle

Spatio-Temporal Change Pattern Investigation of PM_2.5 in Jiangsu Province with MODIS Time Series Products

by Jieqiong Luo and Meiqin Che

Atmosphere 2023, 14(6), 943; https://doi.org/10.3390/atmos14060943 - 27 May 2023

Viewed by 1096

Abstract

In the last decade, the spatio-temporal patterns of PM_2.5 on various scales, ranging from global, continent, and country to regional levels, has been the focus of considerable studies. However, these studies on spatio-temporal variability have concentrated primarily on changes in the spatial [...] Read more.

In the last decade, the spatio-temporal patterns of PM_2.5 on various scales, ranging from global, continent, and country to regional levels, has been the focus of considerable studies. However, these studies on spatio-temporal variability have concentrated primarily on changes in the spatial distribution patterns of regional PM_2.5 concentrations and ignored temporal characteristics at a local site from a heterogeneous surface, such as local variability, persistence, and stability of PM_2.5 exposure. Understanding the temporal characteristics of PM_2.5 concentration changes at the local scale will help determine the local impacts of PM_2.5, such as local exposure risk and vulnerability to PM_2.5. This study aims to reveal the local characteristics of temporal variation at the scale of a prefecture-level city and its distinct-varying patterns from those at the provincial scale by using the annual satellite-derived PM_2.5 concentration product from 2000 to 2015. The evolutionary trends, stability, and persistence of annual changes were discovered with a set of time series analysis methods, such as linear regression analysis + F-test, coefficient of variation method, and Hurst index. This study uses PM_2.5 product data for a total of 16 years, from 2000 to 2015, and uses time series analysis methods, such as Theil–Sen median trend analysis + Mann–Kendall test, one-dimensional linear regression analysis + F-test, coefficient of variation method, and Hurst index, to reveal the temporal variation characteristics and spatial patterns of PM_2.5 in Jiangsu Province. The results show that the increasing trends or slopes of annual averaged PM_2.5 concentrations in Jiangsu Province are not consistent at the prefecture-level city scale, but they are consistent in northern, central and southern Jiangsu at a larger upward trend since 2000. The areas with significant increasing trends are concentrated in Xuzhou and Lianyungang and other northern cities. From the viewpoint of variability, the areas in medium and high variability are mainly aggregated in the areas north of the Yangtze River. According to the combination of persistence analysis and trend analysis, future variation in PM_2.5 concentrations indicates an inverse persistence for an increasing trend, meaning the air quality decline in Jiangsu will slow. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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20 pages, 23055 KiB

Open AccessArticle

Study on Spatial Changes in PM_2.5 before and after the COVID-19 Pandemic in Southwest China

by Xing Li, Jingchun Zhou, Jinliang Wang and Zhanyong Feng

Atmosphere 2023, 14(4), 671; https://doi.org/10.3390/atmos14040671 - 31 Mar 2023

Viewed by 1403

Abstract

Coronavirus disease 2019 (COVID-19) swept the world at the beginning of 2020, and strict activity control measures were adopted in China’s concentrated and local outbreak areas, which led to social shutdown. This study was conducted in southwest China from 2019 to 2021, and [...] Read more.

Coronavirus disease 2019 (COVID-19) swept the world at the beginning of 2020, and strict activity control measures were adopted in China’s concentrated and local outbreak areas, which led to social shutdown. This study was conducted in southwest China from 2019 to 2021, and was divided into the year before COVID-19 (2019), the year of COVID-19 outbreak (2020), and the year of normalization of COVID-19 prevention and control (2021). A geographically and temporally weighted regression (GTWR) model was used to invert the spatial distribution of PM_2.5 by combining PM_2.5 on-site monitoring data and related driving factors. At the same time, a multiple linear regression (MLR) model was constructed for comparison with the GTWR model. The results showed that: (1) The inversion accuracy of the GTWR model was higher than that of the MLR model. In comparison with the commonly used PM_2.5 datasets “CHAP” and “ACAG”, PM_2.5 inverted by the GTWR model had higher data accuracy in southwest China. (2) The average PM_2.5 concentrations in the entire southwest region were 32.1, 26.5, and 28.6 μg/m³ over the three years, indicating that the society stopped production and work and the atmospheric PM_2.5 concentration reduced when the pandemic control was highest in 2020. (3) The winter and spring of 2020 were the relatively strict periods for pandemic control when the PM_2.5 concentration showed the most significant drop. In the same period of 2021, the degree of control was weakened, and the PM_2.5 concentration showed an upward trend. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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17 pages, 2800 KiB

Open AccessArticle

Ozone Formation at a Suburban Site in the Pearl River Delta Region, China: Role of Biogenic Volatile Organic Compounds

by Jun Wang, Yanli Zhang, Shaoxuan Xiao, Zhenfeng Wu and Xinming Wang

Atmosphere 2023, 14(4), 609; https://doi.org/10.3390/atmos14040609 - 23 Mar 2023

Cited by 2 | Viewed by 1990

Abstract

Ozone (O₃) is becoming an increasingly concerning air quality problem in China, and previous O₃ control strategies focused primarily on reducing anthropogenic volatile organic compounds (AVOCs), while neglecting the role of biogenic VOCs (BVOCs) in O₃ formation. In this [...] Read more.

Ozone (O₃) is becoming an increasingly concerning air quality problem in China, and previous O₃ control strategies focused primarily on reducing anthropogenic volatile organic compounds (AVOCs), while neglecting the role of biogenic VOCs (BVOCs) in O₃ formation. In this study, a field campaign was conducted at a suburban site in the Pearl River Delta region of China with high BVOC emissions from 29 August to 3 September 2020. An empirical kinetic modelling approach (EKMA) showed that VOC-limited was the dominant feature for O₃ formation at the site. The relative incremental reactivity (RIR) values calculated by the box model (AtChem2-MCM) revealed that isoprene, formaldehyde, methylglyoxal and acetaldehyde had the highest RIRs. Simulation results from the box model also showed that isoprene played a substantial role in the formation of secondary carbonyls, especially contributing 32–92% to the formaldehyde production rate. Box model simulations further showed that during the O₃ pollution period with high BVOC emissions, only near zero AVOC emissions could prevent O₃ if the levels of nitrogen oxides (NO_x) remained unchanged. The results suggest that the presence of high BVOC emissions can greatly impact efforts to control O₃ by reducing AVOCs, particularly in regions with relatively high NO_x levels (up to 51 ppbv in this study). In the long term, it may be essential to control NO_x and choose low BVOC-emitting tree species in urban planning to address this issue, particularly as BVOC emissions are projected to become a more significant source of reactive VOCs with enhanced control of AVOCs. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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16 pages, 3058 KiB

Open AccessArticle

Changes in Air Pollution Control Policy Instruments: Based on a Textual Analysis for Southwest China 2010–2021

by Ting Yan, Min Wu, Yong Zhan and Zihan Hu

Atmosphere 2023, 14(2), 414; https://doi.org/10.3390/atmos14020414 - 20 Feb 2023

Cited by 1 | Viewed by 1213

Abstract

An important task in the construction of China’s ecological civilization, the selection and implementation of policy instruments fully reflect the actual effectiveness of the government’s efforts to control air pollution. Based on the content analysis method, this study examines the changing process of [...] Read more.

An important task in the construction of China’s ecological civilization, the selection and implementation of policy instruments fully reflect the actual effectiveness of the government’s efforts to control air pollution. Based on the content analysis method, this study examines the changing process of air pollution control policy instruments in southwest China from 2010 to 2021 in terms of implementation, synergy, and integration of policy instruments. The results show that, in terms of the degree of mandatory, the frequency of using policy instruments generally increased with time, but the overall balance of the instrument portfolio was poor. In terms of the degree of synergy, a gradual shift occurred from government-led to government-society governance. However, the concept and modes of inter-governmental linkage and cross-regional collaborative governance need to be improved. As for the degree of systemic, a clear trend of instrument integration and more frequent information interaction was found. Emergency-oriented characteristics appear strong, but a regular governance mechanism is lacking. Therefore, this paper provides policy suggestions and academic considerations for further improving the effectiveness of air pollution management in southwest China from three aspects: optimizing the policy tool system, deepening the regional joint prevention and control mechanism of air pollution, and promoting intelligent air pollution management. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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16 pages, 638 KiB

Open AccessArticle

Perception of Air Pollution and the Evaluation of Local Governments’ Environmental Governance: An Empirical Study on China

by Jie Zhu, Chuntian Lu and Zihao Wei

Atmosphere 2023, 14(2), 212; https://doi.org/10.3390/atmos14020212 - 19 Jan 2023

Cited by 6 | Viewed by 2377

Abstract

In China, blue sky defense is a crucial part of ecological environment governance. Objective environmental governance performance needs to be perceived by the public to more truly affect the public’s evaluation of the government’s environmental governance. This paper focuses on the public’s subjective [...] Read more.

In China, blue sky defense is a crucial part of ecological environment governance. Objective environmental governance performance needs to be perceived by the public to more truly affect the public’s evaluation of the government’s environmental governance. This paper focuses on the public’s subjective perception of air pollution and evaluation of the local government’s environmental governance. Based on the Chinese General Social Survey data, the matched economic indicators, and air pollution data, we conduct a diachronic study on the public’s evaluation of local governments’ environmental protection work, and we analyze the relationship between the subjective perception of air pollution, the objective air pollution data, and the evaluation of local governments’ environmental protection work. The results showed the following: (1) People’s evaluation of local governments’ environmental protection work significantly improved from 2013 to 2021. The objective indicator improved, while the subjective perception declined. (2) The subjective perception of air pollution has a significant negative impact on the evaluation of local governments’ environmental protection work and needs to be better considered to improve air quality. At the same time, the effect of the objective indicator is insignificant. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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20 pages, 8403 KiB

Open AccessArticle

Spatial Identification, Prevention and Control of Epidemics in High-Rise Residential Areas Based on Wind Environments

by Jianxin Zhang, Shenqiang Jiang, Jingyuan Zhao and Xuan Ma

Atmosphere 2023, 14(2), 205; https://doi.org/10.3390/atmos14020205 - 19 Jan 2023

Cited by 1 | Viewed by 1319

Abstract

The wind environment in residential areas can exert a direct or indirect influence on the spread of epidemics, with some scholars paying particular attention to the epidemic prevention and control of residential areas from the perspective of wind environments. As a result, it [...] Read more.

The wind environment in residential areas can exert a direct or indirect influence on the spread of epidemics, with some scholars paying particular attention to the epidemic prevention and control of residential areas from the perspective of wind environments. As a result, it is urgent to re-examine the epidemic prevention response of residential spaces. Taking high-rise residential areas in Xi’an as an example, the article defines the air flow field area based on on-site wind environment measurements, crowd behavior annotation, and CFD simulation. Using the double-effect superposition of crowd behavior and risk space, the paper undertook a multiple identification strategy of epidemic prevention space. The identification methods and management and control strategies of epidemic prevention in high-rise residential areas are proposed. Additionally, the living environment of residential areas is optimized, and a healthy residential space is created. The transformation from concept and calls for action to space implementation is made to provide a reference for improving the space management and control capabilities in high-rise residential areas in China. The results of this study can be used as a guideline for future residential planning and design from the perspective of preventing airborne diseases. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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14 pages, 2810 KiB

Open AccessArticle

Analysis of the PM_2.5–O₃ Pollution Characteristics and Its Potential Sources in Major Cities in the Central Plains Urban Agglomeration from 2014 to 2020

by Shu Quan, Miaohan Liu, Boxuan Chen, Yuehua Huang, Meijuan Wang, Qingxia Ma and Yan Han

Atmosphere 2023, 14(1), 92; https://doi.org/10.3390/atmos14010092 - 31 Dec 2022

Viewed by 1393

Abstract

To highlight the characteristics of PM_2.5–O₃ pollution in the Central Plains Urban Agglomeration, spatial and temporal characteristics, key meteorological factors, and source pollution data for the area were analyzed. These data from the period 2014–2020 were obtained from state-controlled environmental [...] Read more.

To highlight the characteristics of PM_2.5–O₃ pollution in the Central Plains Urban Agglomeration, spatial and temporal characteristics, key meteorological factors, and source pollution data for the area were analyzed. These data from the period 2014–2020 were obtained from state-controlled environmental monitoring stations in seven major cities of the agglomeration. The results revealed the following: (1) Spatially, the PM_2.5–O₃ pollution days were aggregated in the central area of Xinxiang and decreased toward the north and south. Temporally, during the 2014–2020 period, 50 days of PM_2.5–O₃ pollution were observed in the major cities of the Central Plains Urban Agglomeration, with an overall decreasing trend. (2) A low-temperature, high-pressure environment appeared unfavorable for the occurrence of PM_2.5–O₃ pollution days. Wind speeds of 2.14–2.19 m/s and a southerly direction increased the incidence of PM_2.5–O₃ pollution days. (3) The external transport range in summer was smaller and mainly originated from within Henan Province. These results can provide important reference information for achieving a synergistic control of PM_2.5–O₃ pollution, determining the meteorological causes, as well as the potential sources, of PM_2.5–O₃ pollution in polluted areas and promoting air pollution control. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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14 pages, 10345 KiB

Open AccessArticle

Quantifying the Source Contributions to Poor Atmospheric Visibility in Winter over the Central Plains Economic Region in China

by Huiyun Du, Jie Li, Xueshun Chen, Wenyi Yang, Zhe Wang and Zifa Wang

Atmosphere 2022, 13(12), 2075; https://doi.org/10.3390/atmos13122075 - 09 Dec 2022

Viewed by 1045

Abstract

The Central Plains Economic Region (CPER) is one of the most polluted regions in China. Air pollution has caused visibility degradation due to the light extinction of fine particles (PM_2.5). However, the source of light extinction and visibility degradation is still [...] Read more.

The Central Plains Economic Region (CPER) is one of the most polluted regions in China. Air pollution has caused visibility degradation due to the light extinction of fine particles (PM_2.5). However, the source of light extinction and visibility degradation is still unclear. In this study, the nested air quality prediction model system coupled with an online tracer-tagging module has been used to quantify the contribution of emission sectors and regions to visibility degradation. The light extinction coefficients were well reproduced over CPER. The results showed that resident-related emissions, traffic and industry were the main sectors of visibility degradation over CPER, contributing 55~62%, 10~28%, and 9~19%, respectively. The contribution of local emissions and regional transport was also investigated, and the results showed that regional transport dominated the light extinction (56~68%), among which transport within Henan province contributes significantly (12~45%). Sensitivity tests showed that the reduction in the resident-related sector was more effective than that of the industry sector. Emission control of 40% in resident-related, industry, and traffic sectors over the whole region can achieve the goal of good visibility. This study will provide scientific suggestions for the control strategies development to mitigate visibility degradation over CPER. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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14 pages, 1297 KiB

Open AccessArticle

Air Pollution and Tear Lactoferrin among Dry Eye Disease Modifications by Stress and Allergy: A Case–Control Study of Taxi Drivers

by Wei Hao, Fanxue Kong, Wei Song, Lei Zhang, Xueying Xu, Zhongjuan Ren, Jing Li and Fei Yu

Atmosphere 2022, 13(12), 2003; https://doi.org/10.3390/atmos13122003 - 29 Nov 2022

Viewed by 1210

Abstract

Few studies have explored the possible associations between air pollution and tear lactoferrin (Lf) levels, a non-invasive biological marker of ocular surface diseases, among taxi drivers, while none have explored the modifications by stress and allergic tendencies in the relationship. We recruited 1905 [...] Read more.

Few studies have explored the possible associations between air pollution and tear lactoferrin (Lf) levels, a non-invasive biological marker of ocular surface diseases, among taxi drivers, while none have explored the modifications by stress and allergic tendencies in the relationship. We recruited 1905 taxi drivers with dry eye disease (DED) and 3803 non-DED controls in Liaoning, China, in 2012–2014. After physical examination and questionnaires were recorded, ocular surface was measured and tear Lf was determined by electrophoresis. Air pollutants and humidity were estimated by measured concentrations from monitoring stations. Conditional logistic regression models were employed to examine the associations of air pollutants and humidity with tear Lf levels. Among taxi drivers with stress or allergic tendencies, an IQR (26 μg/m³, 10 μg/m³) increase in PM₁₀ and NO₂ levels elevated the adjusted odds ratio by 1.89 (95% CI, 1.19 to 3.08) or 1.77 (95% CI, 1.06 to 2.90); and 2.87 (95% CI, 1.60 to 3.58) or 2.93 (95% CI, 1.64 to 3.83), respectively. In contrast, humidity was inversely associated for taxi drivers with stress [0.51 (95% CI, 0.38 to 0.64)] or allergic tendencies [0.49 (95% CI, 0.11 to 0.84)]; and for taxi drivers without stress [0.33 (95% CI: 0.17, 0.39)] or without allergic tendencies [0.39 (95% CI, 0.19 to 0.59)]. Tear Lf was negatively associated with each quartile of PM₁₀ or NO₂ exposure, and low humidity. PM₁₀, NO₂, and low humidity were inversely associated with Lf levels, especially for DED taxi drivers with stress and allergic tendencies. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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13 pages, 1693 KiB

Open AccessArticle

Variations of Secondary PM_2.5 in an Urban Area over Central China during 2015–2020 of Air Pollutant Mitigation

by Dingyuan Liang, Tianliang Zhao, Yan Zhu, Yongqing Bai, Weikang Fu, Yuqing Zhang, Zijun Liu and Yafei Wang

Atmosphere 2022, 13(12), 1962; https://doi.org/10.3390/atmos13121962 - 24 Nov 2022

Cited by 1 | Viewed by 1052

Abstract

The lack of long-term observational data on secondary PM_2.5 (SPM) has limited our comprehensive understanding of atmospheric environment change. This study develops an SPM estimation method, named Single-Tracer Approximate Envelope Algorithm (STAEA), to assess the long-term changes of SPM under different PM [...] Read more.

The lack of long-term observational data on secondary PM_2.5 (SPM) has limited our comprehensive understanding of atmospheric environment change. This study develops an SPM estimation method, named Single-Tracer Approximate Envelope Algorithm (STAEA), to assess the long-term changes of SPM under different PM_2.5 levels and in all seasons in Wuhan, Central China, over the period of anthropogenic pollutant mitigation in 2015–2020. The results show that: (1) the average proportions of SPM in ambient PM_2.5 is 59.61% in a clean air environment, rising significantly to 71.60%, 73.73%, and 75.55%, respectively, in light, moderate, and heavy PM_2.5 pollution, indicating the dominant role of SPM in air quality deterioration; (2) there are increasing trends of interannual changes of SPM at the light and moderate pollution levels of 1.95 and 3.11 μg·m⁻³·a⁻¹ with extending SPM proportions in PM_2.5 pollution, raising a challenge for further improvement in ambient air quality with mitigating light and moderate PM_2.5 pollution; (3) the high SPM contributions ranging from 55.63% to 68.65% on a seasonal average and the large amplitude of seasonal SPM changes could dominate the seasonality of air quality; (4) the wintertime SPM contribution present a consistent increasing trend compared with the declining trends in spring, summer, and autumn, suggesting underlying mechanisms of SPM change for further deciphering the evolution of the atmospheric environment. Our results highlight the effects of air pollutant mitigation on long-term variations in SPM and its contributions with implications for atmospheric environment change. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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14 pages, 2963 KiB

Open AccessArticle

Variation Characteristics and Source Analysis of Pollutants in Jinghong before and after the COVID-19 Pandemic

by Zengchun Zhou, Zhijun Wang, Jianwu Shi, Yunhong Zhong and Yinhu Ding

Atmosphere 2022, 13(11), 1846; https://doi.org/10.3390/atmos13111846 - 07 Nov 2022

Cited by 1 | Viewed by 1236

Abstract

With the outbreak of COVID-19 in early 2020, China’s urban epidemic prevention and control policies have caused significant changes in air pollution sources. In order to clarify the change characteristics of urban air pollution in Yunnan Province before and after the epidemic, using [...] Read more.

With the outbreak of COVID-19 in early 2020, China’s urban epidemic prevention and control policies have caused significant changes in air pollution sources. In order to clarify the change characteristics of urban air pollution in Yunnan Province before and after the epidemic, using statistics and correlation analysis methods, Jinghong city was selected as the research object, and based on the ambient air quality monitoring data (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) and meteorological data from 2017 to 2021, the concentration characteristics of air pollutants in Jinghong in the past five years were analyzed, and the sources of air pollutants were analyzed using the local emission source inventory and HYSPLIT model. The results show that: ① The air quality in Jinghong was the worst in 2019 before the outbreak of the epidemic, and then gradually improved, with an average 5-year excellent and good rate of 91.8%. The pollutants are mainly particulate matter and O₃. ② Except for SO₂, the concentrations of other pollutants have similar seasonal changes, with the highest in spring and the lowest in summer. ③ The air quality in Jinghong is mainly affected by the combined effects of local emissions and external transportation. According to the local emission inventory, biomass combustion sources have the largest contribution to CO, PM_2.5, and PM₁₀, mobile sources have the highest share rate of NOx, and industrial enterprises are the largest emission sources of SO₂. Air mass backward trajectory research shows that the westward and southerly airflow are the main transport direction of pollutants entering Jinghong, especially in spring, which significantly affects the local pollutant concentration level. In addition, meteorological conditions such as temperature, precipitation, and wind speed also have a great impact on the dilution, diffusion, and transfer of air pollutants in Jinghong. The results of this study further improve the characteristics of the spatial and temporal distribution of air pollutants and pollutant sources in the border areas of China and before and after the epidemic, and also provide a theoretical basis for air environment management in the border areas. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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23 pages, 8756 KiB

Open AccessArticle

Characteristics of Ozone Pollution and the Impacts of Related Meteorological Factors in Shanxi Province, China

by Ling Chen, Hui Xiao, Lingyun Zhu, Xue Guo, Wenya Wang, Li Ma, Wei Guo, Jieying He, Yan Wang, Mingming Li, Erping Chen, Jie Lan and Ruixian Nan

Atmosphere 2022, 13(10), 1729; https://doi.org/10.3390/atmos13101729 - 20 Oct 2022

Cited by 7 | Viewed by 1871

Abstract

Based on environmental monitoring data and meteorological observation data of the Chinese major energy province, Shanxi, from 2015 to 2020, using the satellite remote sensing data of Atmospheric Infrared Sounder Instrument (AIRS) and Ozone Monitoring Instrument (OMI) in 2017, we analyzed the characteristics [...] Read more.

Based on environmental monitoring data and meteorological observation data of the Chinese major energy province, Shanxi, from 2015 to 2020, using the satellite remote sensing data of Atmospheric Infrared Sounder Instrument (AIRS) and Ozone Monitoring Instrument (OMI) in 2017, we analyzed the characteristics of surface ozone (O₃) pollution and its correlation with meteorological factors, as well as the vertical distribution of O₃ in typical pollution cities in Shanxi Province. The results showed that surface O₃ became the primary pollutant in Shanxi. Surface O₃ has shown a zonal distribution with a high level in the south and a low level in the north region since 2017. Surface O₃ pollution was severe in 2019, and the maximum daily 8 h running average of O₃ (MDA8 O₃) decreased, but annual mean O₃ in northern and central regions showed a slow rising trend in 2020. Comprehensive analyses of the influence of meteorological factors on surface O₃ indicated that O₃ pollution in Linfen, Yuncheng and Taiyuan was mainly caused by local photochemical reactions, while that in Jincheng, Xinzhou, Lvliang and Yangquan resulted from regional transports. O₃ volume mixing ratios (VMR) in the middle and lower troposphere generally increased with altitude, peaking at 120 ppbv at approximately 400 hPa. The positive vertical gradient of O₃ in the boundary layer was obvious in Taiyuan in summer and significant in the surface layer in Taiyuan and Linfen during winter and spring, which was associated with greater atmospheric dynamic stability and suppressed vertical mixing. Due to the lack of direct detection of O₃ in the lower troposphere in this region, O₃ vertical distribution retrieved by satellite observation is critical for the study of vertical mixing and transport of local O₃, as well as its regional transport characteristics. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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11 pages, 3932 KiB

Open AccessArticle

Atmospheric Mercury Concentrations in Guangzhou City, Measured by Spectroscopic Techniques

by Guoping Chen, Yuting Sun, Qiang Zhang, Zheng Duan and Sune Svanberg

Atmosphere 2022, 13(10), 1650; https://doi.org/10.3390/atmos13101650 - 10 Oct 2022

Cited by 1 | Viewed by 1226

Abstract

Atmospheric levels of atomic mercury pollution were measured using spectroscopic techniques in the city of Guangzhou, Guangdong Province, China. Assessments were mainly performed at ground level using a portable (vehicle mounted or hand carried) Zeeman modulation correlation spectrometer (Lumex RA-915M), and the results [...] Read more.

Atmospheric levels of atomic mercury pollution were measured using spectroscopic techniques in the city of Guangzhou, Guangdong Province, China. Assessments were mainly performed at ground level using a portable (vehicle mounted or hand carried) Zeeman modulation correlation spectrometer (Lumex RA-915M), and the results are given in easily comprehensible diagrams. Measurements were made with continuous recording in car traverses along major roads which cross the city, but also at selected spots, such as at a university campus with laboratory buildings. Further, pollution levels at different locations were recorded when walking through a major and a small hospital. While concentrations in the city in the range 3–10 ng/m³ were typical, and strongly dependent on the traffic situation, very high concentrations (up to 1300 ng/m³) were found at certain indoor hospital locations, again drawing attention to the fact that high mercury levels due to inadequate handling routines can remain undetected but could readily be eliminated by adequate measurements and subsequent sanitation. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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16 pages, 14564 KiB

Open AccessArticle

Ozone-Induced Lung and Bronchial Injury: A Mouse Model Study

by Shi Liang, Yan Sha, Chuanhong Yang, Huangwen Lai, Chong Sun, Weisen Zhao, An Zhang, Qingwen Qi and Ying Xie

Atmosphere 2022, 13(10), 1562; https://doi.org/10.3390/atmos13101562 - 24 Sep 2022

Cited by 1 | Viewed by 1642

Abstract

Ozone pollution is a prominent public health issue, but there are few studies on the effect of ozone on the ultrastructure of respiratory system; we conducted this research. Exposed to 1.1 ppm O₃ 4 h per day, the mice lungs and bronchi [...] Read more.

Ozone pollution is a prominent public health issue, but there are few studies on the effect of ozone on the ultrastructure of respiratory system; we conducted this research. Exposed to 1.1 ppm O₃ 4 h per day, the mice lungs and bronchi were taken on the 15th or 30th day. The sections stained with HE and immunohistochemical streptavidin–peroxidase methods for NQO1, Nrf2, and Keap1 were observed and measured under the optical microscope. TEM was used for ultrastructure observation. The animals’ serums were detected for CRP and IL-6 levels. The HE-stained sections showed no obvious micromorphological changes in the O₃ exposure, but the NQO1 average optical density was higher than the control on the 15th day (p < 0.05). The ultrastructural changes were found in the O₃ exposure group, such as bulges and vacuoles in type I alveolar cells, the increased evacuation of substance from lamellar bodies in the type II alveolar cells, the increased space around the goblet nucleus, binuclear goblet, and columnar cells. CRP and IL-6 levels increased compared with the control (p < 0.05). Although inhaling 1.1 ppm O₃ had no significant effect on the micromorphology of the mice lungs and bronchi, it did affect the ultrastructure with oxidative stress and inflammatory responses. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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18 pages, 4623 KiB

Open AccessArticle

Prediction of PM_2.5 Concentration in Ningxia Hui Autonomous Region Based on PCA-Attention-LSTM

by Weifu Ding and Yaqian Zhu

Atmosphere 2022, 13(9), 1444; https://doi.org/10.3390/atmos13091444 - 08 Sep 2022

Cited by 8 | Viewed by 1675

Abstract

The problem of air pollution has attracted more and more attention. PM_2.5 is a key factor affecting air quality. In order to improve the prediction accuracy of PM_2.5 concentration and make people effectively control the generation and propagation of atmospheric pollutants, [...] Read more.

The problem of air pollution has attracted more and more attention. PM_2.5 is a key factor affecting air quality. In order to improve the prediction accuracy of PM_2.5 concentration and make people effectively control the generation and propagation of atmospheric pollutants, in this paper, a long short-term memory neural network (LSTM) model based on principal component analysis (PCA) and attention mechanism (attention) is constructed, which first uses PCA to reduce the dimension of data, eliminate the correlation effect between indicators, and reduce model complexity, and then uses the extracted principal components to establish a PCA-attention-LSTM model. Simulation experiments were conducted on the air pollutant data, meteorological element data, and working day data of five cities in Ningxia from 2018 to 2020 to predict the PM_2.5 concentration. The PCA-attention-LSTM model is compared with the support vector regression model (SVR), AdaBoost model, random forest model (RF), BP neural network model (BPNN), and long short-term memory neural network (LSTM). The results show that the PCA-attention-LSTM model is optimal; the correlation coefficients of the PCA-attention-LSTM model in Wuzhong, Yinchuan, Zhongwei, Shizuishan, and Guyuan are 0.91, 0.93, 0.91, 0.91, and 0.90, respectively, and the SVR model is the worst. The addition of variables such as a week, precipitation, and temperature can better predict PM_2.5 concentration. The concentration of PM_2.5 was significantly correlated with the geographical location of the municipal area, and the overall air quality of the southern mountainous area was better than that in the northern Yellow River irrigation area. PM_2.5 concentration shows a clear seasonal change trend, with the lowest in summer and the highest in winter, which is closely related to the climate environment of Ningxia. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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16 pages, 516 KiB

Open AccessArticle

The Impact of Low-Carbon City Pilot Policies on Air Quality: Quasi-Natural Experimental Evidence from China

by Jingran Zhang, Lei Gao, Wukui Wang, Zhenzhu Deng and Xi Zhang

Atmosphere 2022, 13(9), 1355; https://doi.org/10.3390/atmos13091355 - 25 Aug 2022

Cited by 5 | Viewed by 1480

Abstract

Low-carbon cities have become a new trend in regional development around the world. Whether they can improve the environment in China, especially the air quality, remains to be tested. In this paper we take low-carbon city construction as a quasi-natural experiment and empirically [...] Read more.

Low-carbon cities have become a new trend in regional development around the world. Whether they can improve the environment in China, especially the air quality, remains to be tested. In this paper we take low-carbon city construction as a quasi-natural experiment and empirically test the net effects, influencing factors, and dynamic effects of low-carbon city construction on air quality by constructing a multistage propensity score matching and Difference-in-Differences model. After a series of robustness tests, the following conclusions are drawn: first, low-carbon city construction reduces the regional Air Quality Index, inhalable particulate matter, fine particulate matter, and NO₂ concentrations. Among them, the construction effect in 2017 was the most significant. Therefore, it is necessary to continue to promote low-carbon city policies and accurately identify different types of air pollutants to improve the overall effectiveness of low-carbon city policies. Second, temperature, humidity, wind level, and other meteorological factors, as well as gross domestic product for the proportion of secondary industry, will affect air quality. Therefore, it is necessary to comprehensively consider meteorological, economic, social, and other influencing factors in an early stage of the construction of the next batch of low-carbon cities, so as to avoid falling into the trap of “building first and managing later”. Third, the impact of secondary industry on air quality is significantly greater than that of tertiary industry. Therefore, the upgrading of industrial structure promoted by low-carbon city policy is effective in improving air quality. Fourth, the construction of low-carbon cities in western China has the most significant impact on air quality improvement. Therefore, the joint prevention and control mechanism of air pollution control in urban agglomeration should be established. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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20 pages, 11389 KiB

Open AccessArticle

Has COVID-19 Altered the Air Quality Conduction Relationship in Beijing and Neighboring Cities?—A Test Based on Dynamic Periodic Conformance

by Min Zhang, Jianbo Dong, Gang Diao and Qiaomei Lan

Atmosphere 2022, 13(8), 1188; https://doi.org/10.3390/atmos13081188 - 27 Jul 2022

Viewed by 1133

Abstract

The Beijing–Tianjin–Hebei region is the most dynamic region and largest economy in northern China; however, the air quality is the worst in the country. The study of the air quality in the cities around Beijing is of great significance for air pollution control. [...] Read more.

The Beijing–Tianjin–Hebei region is the most dynamic region and largest economy in northern China; however, the air quality is the worst in the country. The study of the air quality in the cities around Beijing is of great significance for air pollution control. Therefore, this study analyzed whether the COVID-19 pandemic altered the periodic pattern of the air quality in Beijing and its neighboring cities. The study employed continuous wavelet transform to examine the impact of the COVID-19 pandemic on the air quality of Beijing and its neighboring cities. This method reveals the changes in the air quality from a periodic pattern perspective. The results showed that COVID-19 weakened the periodic changes in air quality in Beijing and five neighboring cities, and this effect was most pronounced during the outbreak of the pandemic in early 2020. The cycle synchronization analysis showed that the pandemic weakened the cycle synchronization of air quality of the cities in the north of Beijing, while less impact was found on the cities to the south of Beijing. Moreover, the periodic patterns in 2020 and 2021 were compared with that in 2019 (before the outbreak of the pandemic), and it was found that the periodic patterns during the outbreak of the pandemic in 2020 and 2021 were significantly different from that in the same period in 2019. Therefore, COVID-19 weakened the periodic pattern of air quality in the cities around Beijing and altered the connection to air quality among them. The changes reveal the connections of inter-city air pollutants caused by human economic and social activities in cities around Beijing. Full article

(This article belongs to the Special Issue Air Pollution in China (2nd Edition))

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