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16 pages, 4204 KiB

Open AccessArticle

Study on Improving the Air Quality with Emission Enhanced Control Measures in Beijing during a National Parade Event

by Bingbo Huang, Minjun Deng, Qingxian Gao, Zhanyun Ma and Mindong Chen

Atmosphere 2022, 13(7), 1019; https://doi.org/10.3390/atmos13071019 - 24 Jun 2022

Viewed by 1743

Abstract

Research on the enhanced control and emission-reduction measures to improve air quality during major events could provide data theory and scientific support for air-quality improvement during non-activities. Based on the air-quality data published by the China Environmental Monitoring Station and the meteorological elements [...] Read more.

Research on the enhanced control and emission-reduction measures to improve air quality during major events could provide data theory and scientific support for air-quality improvement during non-activities. Based on the air-quality data published by the China Environmental Monitoring Station and the meteorological elements and weather conditions released by the China Meteorological Administration, this paper explored the characteristics of air-quality evolution in Beijing from 5 August to 18 September 2015 and the weather situation during the Military Parade. The results showed that: (1) Emission-reduction measures implemented for air quality by Beijing and its surrounding area were induced, and we explored the contribution of these measures to pollutants or AQI in the locality. (2) During the 2015 Military Parade, Beijing was in the front or lower part of the high-pressure system. Due to the strong effect of North or Northeast winds, the weather situation was conducive to the diffusion of pollutants. When before or after the implementation, once the atmospheric diffusion was poor, the pollutants would accumulate gradually. Thus, it can be seen that the weather situation had a great impact on air quality. (3) During the implementation, PM_2.5, PM₁₀, NO₂ and other pollutants decreased significantly, of which the concentration of PM₁₀ decreased the most, from 109 μg·m⁻³ down to 34 μg·m⁻³, and the concentration of PM_2.5 decreased by 72.73%. According to the changes between before and during the implementation or during and after the implementation, the concentration of PM₁₀ and PM_2.5 increased when the implementation of the emission-reduction measures had been finished, indicating that the enhanced control measures made a great contribution to the emission reduction in particles. (4) In addition, the annual average of AQI in the three years is 87.49, and the average value of a normal year was the average value of 2013 and 2014. The average value of the normal year during the military parade is 64.63, which was 70.40% lower than the average value of AQI during the military parade. The goal of reaching the secondary standard of GB-3095-2012 was achieved, and there was still a long way to go from the primary standard. In a few words, in order to achieve the goal of better air quality throughout the year, all parties still needed to coordinate control and make joint efforts. Full article

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

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22 pages, 16169 KiB

Open AccessArticle

Restricted Anthropogenic Activities and Improved Urban Air Quality in China: Evidence from Real-Time and Remotely Sensed Datasets Using Air Quality Zonal Modeling

by Saidur Rahaman, Selim Jahangir, Ruishan Chen and Pankaj Kumar

Atmosphere 2022, 13(6), 961; https://doi.org/10.3390/atmos13060961 - 14 Jun 2022

Cited by 4 | Viewed by 2922

Abstract

The study aims to examine the major atmospheric air pollutants such as NO₂, CO, O₃, PM_2.5, PM₁₀, and SO₂ to assess the overall air quality using air quality zonal modeling of 15 major cities [...] Read more.

The study aims to examine the major atmospheric air pollutants such as NO₂, CO, O₃, PM_2.5, PM₁₀, and SO₂ to assess the overall air quality using air quality zonal modeling of 15 major cities of China before and after the COVID-19 pandemic period. The spatio-temporal changes in NO₂ and other atmospheric pollutants exhibited enormous reduction due to the imposition of a nationwide lockdown. The present study used a 10-day as well as 60-day tropospheric column time-average map of NO₂ with spatial resolution 0.25 × 0.25° obtained from the Global Modeling and Assimilation Office, NASA. The air quality zonal model was employed to assess the total NO₂ load and its change during the pandemic period for each specific region. Ground surface monitoring data for CO, NO₂, O₃, PM₁₀, PM_2.5, and SO₂ including Air Quality Index (AQI) were collected from the Ministry of Environmental Protection of China (MEPC). The results from both datasets demonstrated that NO₂ has drastically dropped in all the major cities across China. The concentration of CO, PM₁₀, PM_2.5, and SO₂ demonstrated a decreasing trend whereas the concentration of O₃ increased substantially in all cities after the lockdown effect as observed from real-time monitoring data. Because of the complete shutdown of all industrial activities and vehicular movements, the atmosphere experienced a lower concentration of major pollutants that improves the overall air quality. The regulation of anthropogenic activities due to the COVID-19 pandemic has not only contained the spread of the virus but also facilitated the improvement of the overall air quality. Guangzhou (43%), Harbin (42%), Jinan (33%), and Chengdu (32%) have experienced maximum air quality improving rates, whereas Anshan (7%), Lanzhou (17%), and Xian (25%) exhibited less improved AQI among 15 cities of China during the study period. The government needs to establish an environmental policy framework involving central, provincial, and local governments with stringent laws for environmental protection. Full article

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

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19 pages, 853 KiB

Open AccessArticle

Prediction of Air Pollutant Concentrations via RANDOM Forest Regressor Coupled with Uncertainty Analysis—A Case Study in Ningxia

by Weifu Ding and Xueping Qie

Atmosphere 2022, 13(6), 960; https://doi.org/10.3390/atmos13060960 - 14 Jun 2022

Cited by 13 | Viewed by 2773

Abstract

Air pollution has not received much attention until recent years when people started to understand its dreadful impacts on human health. According to air pollution and the meteorological monitoring data from 1 January 2016 to 31 December 2017 in Ningxia, we analyzed the [...] Read more.

Air pollution has not received much attention until recent years when people started to understand its dreadful impacts on human health. According to air pollution and the meteorological monitoring data from 1 January 2016 to 31 December 2017 in Ningxia, we analyzed the impact of ground surface temperature, air temperature, relative humidity and the power of wind on air pollutant concentrations. Meanwhile, we analyze the relationships between air pollutant concentrations and meteorological variables by using the mathematical model of decision tree regressor (DTR), feedforward artificial neural network with back-propagation algorithm (FFANN-BP) and random forest regressor (RFR) according to air-monitoring station data. For all pollutants, the RFR increases

R^{2}

of FFANN-BP and DTR by up to 0.53 and 0.42 respectively, reduces root mean square error (RMSE) by up to 68.7 and 41.2, and MAE by up to 25.2 and 17. The empirical results show that the proposed RFR displays the best forecasting performance and could provide local authorities with reliable and precise predictions of air pollutant concentrations. The RFR effectively establishes the relationships between the influential factors and air pollutant concentrations, and well suppresses the overfitting problem and improves the accuracy of prediction. Besides, the limitation of machine learning for single site prediction is also overcame. Full article

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

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14 pages, 3368 KiB

Open AccessArticle

Effects of Air Pollution on Sunshine Duration Trends in Typical Chinese Cities

by Wei Chong, Wenhua Lyu, Jian Zhang, Jing Liang, Xiaotong Yang and Guoyu Zhang

Atmosphere 2022, 13(6), 950; https://doi.org/10.3390/atmos13060950 - 10 Jun 2022

Cited by 3 | Viewed by 2199

Abstract

Long-term trends in sunshine duration in Chinese cities have been closely linked to factors caused by air pollution. To understand this impact on sunshine duration (SD), surface solar radiation from 1981 to 2020, annual PM_2.5 concentration from 2012 to 2020 and air [...] Read more.

Long-term trends in sunshine duration in Chinese cities have been closely linked to factors caused by air pollution. To understand this impact on sunshine duration (SD), surface solar radiation from 1981 to 2020, annual PM_2.5 concentration from 2012 to 2020 and air pollution index (API) data from 2013 to 2020 collected in ten representative cities in China were investigated, and the long-term relationship of SD with diffuse fraction (DF), aerosol option depth (AOD), annual PM_2.5 concentration and API were analyzed. The results indicated that trends in SD varied across cities. SD decreased in seven of the ten selected cities’ stations in the past 40 years, and the annual mean SD decreased from −0.03 h d⁻¹ per decade to −0.36 h d⁻¹ per decade—particularly in the Beijing North China Plain, Shanghai and Wuhan stations in the Yangtze River delta, where the trend coefficients were lower than −0.5. Conversely, increases in varying degrees of SD were found in Kunming (0.38 h d⁻¹ per decade), Guangzhou and Shenyang in Southwest, South and Northeast China, respectively—with the biggest trend coefficient of 0.54 in Kunming. In addition to the SD variation, the DF in the ten city stations increased continuously from 1981 to 2010 and then declined after 2010, which is closely related to decreases in the annual PM2.5 concentration after 2012. The correlation coefficients between DF and SD ranged from −0.04 to −0.62, validating their negative relationship and the slight increasing trend in SD in recent ten years. The annual averages for SD and the DF plateaued in the 2010s due to the stringent pollution controls established by the Chinese government after 2010. Furthermore, the correlation coefficients between SD and the API ranged from −0.12 to −0.58, demonstrating a negative relationship between SD and the API. Full article

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

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16 pages, 9187 KiB

Open AccessArticle

How Sensitive Morphological Parameters Influence on the PM_2.5 Diffusion: An Empirical Study of Two Neighborhoods in Central Beijing

by Peihao Zhang, Haomiao Cheng, Zhiwen Jiang and Fanding Xiang

Atmosphere 2022, 13(6), 921; https://doi.org/10.3390/atmos13060921 - 6 Jun 2022

Cited by 2 | Viewed by 2010

Abstract

Air quality is highly related to the health of a human being. Urban morphology has a significant influence on air quality; however, the specific relationship between urban morphology characteristics and air quality at the neighborhood scale has yet to be investigated, especially the [...] Read more.

Air quality is highly related to the health of a human being. Urban morphology has a significant influence on air quality; however, the specific relationship between urban morphology characteristics and air quality at the neighborhood scale has yet to be investigated, especially the vegetation effect on PM_2.5 concentration and diffusion. The relevant morphological parameters based on the affected pathways of urban morphology on air quality were selected, and the sensitivity degree and laws of the selected morphological parameters to PM_2.5 were quantified by numerical simulation, bivariate correlation analysis, and regression analysis. The results showed that Building Density (BD), Block Envelope Degree (BED), Average Building Volume (ABV), Average Building Floors (ABF), Standard Deviation of Building Height (SDH) and Greenbelt Coverage Rate (GCR) were Sensitive Morphological Parameters (SMPs). A positive and cosine curve trend of BD and BED with PM_2.5 was observed. GCR was significant to dust retention along with vertical canopy height. When ABV = 40,000 m³ and ABF = 20F, the lowest PM_2.5 concentration was examined, while increased SDH could promote airflow and enhance the capacity of PM_2.5 diffusion. Finally, morphology-optimization strategies were proposed at the neighborhood scale: (1) Decreasing the BED along the street; (2) considering the species of vegetation with the appropriate height and increasing the GCR; (3) increasing the ABF of neighborhoods appropriately while controlling the ABV and distinguishing the internal SDH of neighborhoods. The study could apply the scientific basis for the planning and design of healthy and livable cities. Full article

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

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18 pages, 3352 KiB

Open AccessArticle

Characteristics and Source Apportionment of Size-Fractionated Particulate Matter at Ground and above the Urban Canopy (380 m) in Nanjing, China

by Hao Wu, Pulong Chen, Tijian Wang, Min Xie, Bingliang Zhuang, Shu Li and Mengmeng Li

Atmosphere 2022, 13(6), 883; https://doi.org/10.3390/atmos13060883 - 29 May 2022

Viewed by 1836

Abstract

In this study, the concentrations and chemical components of size-fractionated particulate matter (PM) in Nanjing at the ground (Gulou, 20 m) and above the urban canopy (Zifeng, 380 m) were sampled and analyzed from 16 November to 12 December in 2016. Higher concentrations [...] Read more.

In this study, the concentrations and chemical components of size-fractionated particulate matter (PM) in Nanjing at the ground (Gulou, 20 m) and above the urban canopy (Zifeng, 380 m) were sampled and analyzed from 16 November to 12 December in 2016. Higher concentrations of PM₁₀, PM_10-2.1, and PM_2.1 (108.3 ± 23.4 μg m⁻³, 47.3 ± 10.6 μg m⁻³, and 61.0 ± 18.8 μg m⁻³) were measured at Gulou than those (88.1 ± 21.1 μg m⁻³, 31.4 ± 6.7 μg m⁻³, and 56.7 ± 18.6 μg m⁻³) at Zifeng. The most abundant chemical components for size-fractionated PM were SO₄²⁻, NO₃⁻, organic carbon (OC), NH₄⁺, elemental carbon (EC), and crustal elements such as Al, Ca, Fe, and Mg, varying significantly on different particulate sizes. The concentrations of OC and EC were 7.46–19.60 μg m⁻³ and 3.44–5.96 μg m⁻³ at Gulou and were 8.34–18.62 μg m⁻³ and 2.86–4.11 μg m⁻³ at Zifeng, showing an equal importance in both fine and coarse particles. Nitrate, sulfate, and ammonium were more concentrated in PM_2.1, contributing 11.30–13.76 μg m⁻³, 8.91–9.40 μg m⁻³, and 5.78–6.81 μg m⁻³, which was more than in PM_10-2.1, which contributed 2.73–5.06 μg m⁻³, 2.16–3.81 μg m⁻³, and 0.85–0.87 μg m⁻³. In contrast, the crustal elements were larger in coarse particles and at the ground level, accounting for 18.6% and 15.3% of the total PM at Gulou and Zifeng. Source apportionment using the chemical mass balance (CMB) model EPA showed that the dominant three sources were secondary nitrate (18.2–24.9%), secondary sulfate (14.5–20.4%), and secondary organic aerosols (15.5–19.6%) for PM₁₀, PM_2.1, and PM_1.1 at both Gulou and Zifeng during the entire sampling period. However, for PM_10-2.1, the largest three contributors were secondary organic aerosols (18.3%), the coal-fired power plant (15.6%), and fugitive dust (14.4%), indicating dusts including construction dust, fugitive dust, and soil dust would contribute more at the ground. The results also showed that the concentrations of PM₁₀, PM_2.1, and PM_1.1 were lower than the work carried out in the winter of 2010 at the same sampling site by 41.4%, 26.3%, and 24.8%, confirming the improvement of the air quality and the efficient control of PM pollutants. Full article

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

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14 pages, 1152 KiB

Open AccessArticle

Can the Coal-to-Gas/Electricity Policy Improve Air Quality in the Beijing–Tianjin–Hebei Region?—Empirical Analysis Based on the PSM-DID

by Jingran Zhang, Wukui Wang, Lei Gao, Zhenzhu Deng and Yu Tian

Atmosphere 2022, 13(6), 879; https://doi.org/10.3390/atmos13060879 - 28 May 2022

Cited by 7 | Viewed by 2468

Abstract

Air pollution caused by coal burning not only increases the cost of environmental pollution but also harms human health. It is urgent for China to change the practice of coal-fired central heating. Therefore, the effectiveness and sustainability of the Coal to Gas and [...] Read more.

Air pollution caused by coal burning not only increases the cost of environmental pollution but also harms human health. It is urgent for China to change the practice of coal-fired central heating. Therefore, the effectiveness and sustainability of the Coal to Gas and Electricity policy have become the focus of all sectors of society. In this paper, eight cities in the Beijing–Tianjin–Hebei region were taken as the experimental groups and the other eleven cities as the control groups. Based on the PSM-DID model and the time-varying DID model, a quasi-natural experimental analysis was conducted to evaluate the effect of the policy of coal to gas and electricity to improve air quality in the Beijing–Tianjin–Hebei region from 2015 to 2020 and to test the sustainability of the policy. Three research conclusions are shown below: First, during the implementation of the policy, especially in 2019, the AQI index decreased significantly. Although there was a rebound thereafter, it was still lower than before. This shows that the Coal to Gas and Electricity policy has indeed improved the air quality in Beijing, Tianjin, and Hebei during its implementation. Second, the policy had a great impact on SO₂ and PM₁₀ but was relatively weak on PM_2.5 and CO. Therefore, there is an urgent need to formulate scientific and accurate policies to control different air pollutants. Third, the time-varying DID model was used to identify the dynamic sustainability effect of the Coal to Gas and Electricity policy. The results showed that the policy had a strong impact in the initial stage, but its effect was greatly reduced at the end of the implementation or near the end, when it was far less obvious than in the initial stage of the policy. Therefore, in formulating relevant measures to reduce air pollution, it is necessary to fully consider the sustainability of the policy. Full article

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

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17 pages, 9778 KiB

Open AccessArticle

The Extraordinary Trend of the Spatial Distribution of PM_2.5 Concentration and Its Meteorological Causes in Sichuan Basin

by Xing Xiang, Guangming Shi, Xiaodong Wu and Fumo Yang

Atmosphere 2022, 13(6), 853; https://doi.org/10.3390/atmos13060853 - 24 May 2022

Cited by 7 | Viewed by 1869

Abstract

Sichuan Basin is an area with some of the most serious PM_2.5 pollution, and it is also a key area for joint prevention and control of air pollution in China. Therefore, it is necessary to clarify the temporal and spatial distribution characteristics [...] Read more.

Sichuan Basin is an area with some of the most serious PM_2.5 pollution, and it is also a key area for joint prevention and control of air pollution in China. Therefore, it is necessary to clarify the temporal and spatial distribution characteristics of PM_2.5 concentration in Sichuan Basin (SCB) and study the influence of meteorological conditions. In this study, the spatial disparity of PM_2.5 concentration in SCB and its variation trend from 1 December 2015 to 30 November 2019 were analyzed. The results showed that the spatial disparity of SCB was decreasing and distinct variation trends of PM_2.5 concentration were observed in different areas. The PM_2.5 concentrations declined rapidly in the western and southern basin (most severely polluted areas), decreased at a slower rate in the central and eastern basin, but unexpectedly increased slightly in the northern and northeastern basin. From the perspective of relative spatial anomalies (RAs), the decreasing (increasing) trend of RAs of PM_2.5 concentrations in the western and southern (northern and northeastern) parts of SCB were also prominent. The reduction in spatial disparity and the regionally extraordinary increasing trend could be partly explained by the variations in synoptic circulations. Specifically, the reasons for the decrease in wintertime spatial disparity and the increase in RAs in the northern basin were the reduction in synoptic pattern Type 2 (weak high-pressure system and uniform pressure fields) and Type 3 (high-pressure system to the north) and the growth of Type 6 (weak low-pressure system with high-pressure system to the north). In spring, the reasons were the reduction in Type 1 (weak low-pressure system) and Type 5 (weak low-pressure system to the southwest) and the growth of Type 2. The reduction in Type 2 and the growth in Type 4 (weak high-pressure system to the east) could explain the variation in PM_2.5 distribution in autumn. This study showed the importance of implementing more precise and effective emission control measures, especially in relatively cleaner areas, in which the impacts of meteorological conditions might cause fluctuation (even rebounding) in the PM_2.5 concentration. Full article

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

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18 pages, 4301 KiB

Open AccessArticle

Analysis of the Characteristics of Ozone Pollution in the North China Plain from 2016 to 2020

by Xinyu Wang, Wenhui Zhao, Tianyue Zhang, Yun Qiu, Pengfei Ma, Lingjun Li, Lili Wang, Mi Wang, Dongyang Zheng and Wenji Zhao

Atmosphere 2022, 13(5), 715; https://doi.org/10.3390/atmos13050715 - 30 Apr 2022

Cited by 15 | Viewed by 2958

Abstract

As a major gaseous pollutant, ozone (O₃) adversely affects human health and ecosystems. In recent years, ozone pollution in China has gradually become a prominent issue, especially in the North China Plain (NCP). To study the long-term spatio-temporal variation patterns of [...] Read more.

As a major gaseous pollutant, ozone (O₃) adversely affects human health and ecosystems. In recent years, ozone pollution in China has gradually become a prominent issue, especially in the North China Plain (NCP). To study the long-term spatio-temporal variation patterns of O₃ in the NCP, this study selected 230 monitoring stations in the NCP from 2016 to 2020 as research objects, used the Kriging interpolation method and global Moran’s index to discuss the spatial-temporal distribution of O₃, combining meteorological and social statistical data to analyze the causes underlying regional differences. The temporal analysis demonstrated that the O₃-8h average concentrations increased annually from 2016 to 2018 and decreased from 2019 to 2020. The O₃ concentrations were higher in spring and summer (117.89–154.20 μg/m³) and lower in autumn and winter (53.81–92.95 μg/m³). The spatial analysis revealed that O₃ concentrations were low in the north and south of the NCP but high in the central area. The spatial distribution of O₃ exhibited considerable cross-seasonal variability. Both meteorological conditions of high temperature and low pressure increased O₃ concentrations. The spatial distribution of O₃ varied depending on the period. However, the central and western regions of the Shandong Province were constantly characterized by high O₃ concentrations. This pattern has been likely formed by heavy industry in the Shandong Province, as large-scale industrial production and frequent traffic flows produce a large amount of precursors, thereby exacerbating regional O₃ pollution. These characteristics were attributed to emission reduction policies, meteorological conditions, the emission intensity of anthropogenic sources, and regional transport in the NCP. Overall, for cities with heavy industrial facilities in the central NCP, a timely adjustment of the energy and industrial structure, effectively controlling the emission of precursors, promoting new clean energy, and strengthening regional joint prevention and control are effective ways to alleviate O₃ pollution. Full article

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

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17 pages, 2420 KiB

Open AccessArticle

Impact of the Levels of COVID-19 Pandemic Prevention and Control Measures on Air Quality: A Case Study of Jiangsu Province, China

by Wenwen Ai, Xixi Yang, Duanyang Liu, Min Zhang, Yan Sun, Boni Wang and Xiaochun Luo

Atmosphere 2022, 13(5), 640; https://doi.org/10.3390/atmos13050640 - 19 Apr 2022

Cited by 4 | Viewed by 2424

Abstract

In order to control the spread of the COVID-19 pandemic, the prevention and control measures of public health emergencies were initiated in all provinces of China in early 2020, which had a certain impact on air quality. In this study, taking Jiangsu Province [...] Read more.

In order to control the spread of the COVID-19 pandemic, the prevention and control measures of public health emergencies were initiated in all provinces of China in early 2020, which had a certain impact on air quality. In this study, taking Jiangsu Province in China as an example, the air pollution levels in different regions under different levels of pandemic prevention and control (PPC) measures are evaluated. The implementation of the prevention and control policies of COVID-19 pandemic directly affected the concentration of air pollutants. No matter what level of PPC measures was implemented, the air quality index (AQI) and pollutant concentrations of NO₂, CO, PM₁₀ and PM_2.5 were all reduced by varied degrees. The higher the level of PPC measures, the greater the reduction was in air pollutant concentrations. Specifically, NO₂ was the most sensitive to PPC policies. The concentrations of CO and atmospheric particulate matter (PM₁₀ and PM_2.5) decreased most obviously under the first and second level of PPC. The response speed of air quality to different levels of PPC measures varied greatly among different cities. Southern Jiangsu, which has a higher level of economic development and is dominated by secondary and tertiary industries, had a faster response speed and a stronger responsiveness. The results of this study reflect the economic vitality of different cities in economically advanced regions (i.e., Jiangsu Province) in China. Furthermore, the results can provide references for the formulation of PPC policies and help the government make more scientific and reasonable strategies for air pollution prevention and control. Full article

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

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15 pages, 1285 KiB

Open AccessArticle

Pollution Characteristics and Health Risk Assessment of VOCs in Jinghong

by Jianwu Shi, Yuzhai Bao, Feng Xiang, Zhijun Wang, Liang Ren, Xiaochen Pang, Jian Wang, Xinyu Han and Ping Ning

Atmosphere 2022, 13(4), 613; https://doi.org/10.3390/atmos13040613 - 11 Apr 2022

Cited by 8 | Viewed by 2965

Abstract

In order to investigate the seasonal variation in chemical characteristics of VOCs in the urban and suburban areas of southwest China, we used SUMMA canister sampling in Jinghong city from October 2016 to June 2017. Forty-eight VOC species concentrations were analyzed using atmospheric [...] Read more.

In order to investigate the seasonal variation in chemical characteristics of VOCs in the urban and suburban areas of southwest China, we used SUMMA canister sampling in Jinghong city from October 2016 to June 2017. Forty-eight VOC species concentrations were analyzed using atmospheric preconcentration gas chromatography–mass spectrometry (GC–MS), Then, regional VOC pollution characteristics, ozone formation potentials (OFP), source identity, and health risk assessments were studied. The results showed that the average concentration of total mass was 144.34 μg·m⁻³ in the urban area and 47.81 μg·m⁻³ in the suburban area. Alkanes accounted for the highest proportion of VOC groups at 38.11%, followed by olefins (36.60%) and aromatic hydrocarbons (25.28%). Propane and isoprene were the species with the highest mass concentrations in urban and suburban sampling sites. The calculation of OFP showed that the contributions of olefins and aromatic hydrocarbons were higher than those of alkanes. Through the ratio of specific species, the VOCs were mainly affected by motor vehicle exhaust emissions, fuel volatilization, vegetation emissions, and biomass combustion. Combined with the analysis of the backward trajectory model, biomass burning activities in Myanmar influenced the concentration of VOCs in Jinghong. Health risk assessments have shown that the noncarcinogenic risk and hazard index of atmospheric VOCs in Jinghong were low (less than 1). However, the value of the benzene cancer risk to the human body was higher than the safety threshold of 1 × 10⁻⁶, showing that benzene has carcinogenic risk. This study provides effective support for local governments formulating air pollution control policies. Full article

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

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15 pages, 2722 KiB

Open AccessArticle

Haze Grading Using the Convolutional Neural Networks

by Lirong Yin, Lei Wang, Weizheng Huang, Jiawei Tian, Shan Liu, Bo Yang and Wenfeng Zheng

Atmosphere 2022, 13(4), 522; https://doi.org/10.3390/atmos13040522 - 25 Mar 2022

Cited by 67 | Viewed by 3346

Abstract

As an air pollution phenomenon, haze has become one of the focuses of social discussion. Research into the causes and concentration prediction of haze is significant, forming the basis of haze prevention. The inversion of Aerosol Optical Depth (AOD) based on remote sensing [...] Read more.

As an air pollution phenomenon, haze has become one of the focuses of social discussion. Research into the causes and concentration prediction of haze is significant, forming the basis of haze prevention. The inversion of Aerosol Optical Depth (AOD) based on remote sensing satellite imagery can provide a reference for the concentration of major pollutants in a haze, such as PM2.5 concentration and PM10 concentration. This paper used satellite imagery to study haze problems and chose PM2.5, one of the primary haze pollutants, as the research object. First, we used conventional methods to perform the inversion of AOD on remote sensing images, verifying the correlation between AOD and PM2.5. Subsequently, to simplify the parameter complexity of the traditional inversion method, we proposed using the convolutional neural network instead of the traditional inversion method and constructing a haze level prediction model. Compared with traditional aerosol depth inversion, we found that convolutional neural networks can provide a higher correlation between PM2.5 concentration and satellite imagery through a more simplified satellite image processing process. Thus, it offers the possibility of researching and managing haze problems based on neural networks. Full article

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

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22 pages, 5088 KiB

Open AccessArticle

Spatio-Temporal Characteristics of Air Quality Index (AQI) over Northwest China

by Shah Zaib, Jianjiang Lu and Muhammad Bilal

Atmosphere 2022, 13(3), 375; https://doi.org/10.3390/atmos13030375 - 23 Feb 2022

Cited by 19 | Viewed by 5108

Abstract

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and [...] Read more.

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and Qinghai (QH)) of northwest China (NWC) from January 2015 to December 2018. For this purpose, surface-level aerosol pollutants, including particulate matter (PMx, x = 2.5 and 10) and gaseous pollutants (sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃)) were obtained from China National Environmental Monitoring Center (CNEMC). The results showed that fine particulate matter (PM_2.5), coarse particulate matter (PM₁₀), SO₂, NO₂, and CO decreased by 28.2%, 32.7%, 41.9%, 6.2%, and 27.3%, respectively, while O₃ increased by 3.96% in NWC during 2018 as compared with 2015. The particulate matter (PM_2.5 and PM₁₀) levels exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II standards as well as the WHO recommended Air Quality Guidelines, while SO₂ and NO₂ complied with the CAAQS Grade II standards in NWC. In addition, the average air quality index (AQI), calculated from ground-based data, improved by 21.3%, the proportion of air quality Class I (0–50) improved by 114.1%, and the number of pollution days decreased by 61.8% in NWC. All the pollutants’ (except ozone) AQI and PM_2.5/PM₁₀ ratios showed the highest pollution levels in winter and lowest in summer. AQI was strongly positively correlated with PM_2.5, PM₁₀, SO₂, NO₂, and CO, while negatively correlated with O₃. PM₁₀ was the primary pollutant, followed by O₃, PM_2.5, NO₂, CO, and SO₂, with different spatial and temporal variations. The proportion of days with PM_2.5, PM₁₀, SO₂, and CO as the primary pollutants decreased but increased for NO₂ and O₃. This study provides useful information and a valuable reference for future research on air quality in northwest China. Full article

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

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13 pages, 3306 KiB

Open AccessArticle

Variation and Driving Factor of Aerosol Optical Depth over the South China Sea from 1980 to 2020

by Enwei Sun, Chuanbo Fu, Wei Yu, Ying Xie, Yiwen Lu and Chunsong Lu

Atmosphere 2022, 13(3), 372; https://doi.org/10.3390/atmos13030372 - 23 Feb 2022

Cited by 4 | Viewed by 2532

Abstract

Spatial and temporal variation of aerosol optical depth (AOD) and optical depth of different aerosol types derived from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) over the South China Sea (SCS) between 1980 and 2020 were studied. AOD distribution showed [...] Read more.

Spatial and temporal variation of aerosol optical depth (AOD) and optical depth of different aerosol types derived from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) over the South China Sea (SCS) between 1980 and 2020 were studied. AOD distribution showed different characteristics throughout the entire SCS. Sulfate Aerosol Optical Depth (SO₄AOD) and Sea Salt Aerosol Optical Depth (SSAOD) mainly contributed to the spatial and temporal variation of AOD over the SCS. A significant increasing trend followed by a decreasing trend of AOD could be observed in the north of the SCS from 1980 to 2020. Mean MERRA-2 AOD between 1980 and 2020 showed that AOD was high in the north and low in the south and that AOD gradually decreased from north to south over the SCS. AOD after 2000 was obviously higher than that of the 1980s and 1990s. Higher AOD appeared in the spring and winter, and low AOD appeared in the summer. The spatial distribution of scattering aerosol optical depth (SAOD) was similar to AOD distribution over the SCS. SO₄AOD and SSAOD were obviously higher than black carbon aerosol optical depth (BCAOD), organic carbon aerosol optical depth (OCAOD), and dust aerosol optical depth (DUAOD) over the SCS. SO₄AOD accounted for over 50% of total AOD (TAOD) over the north of the SCS, while BCAOD and DUAOD accounted for less than 10% of TAOD over the entire SCS. An obvious annual mean TAOD increase between 1980 and 2007 could be observed over the northern part of the SCS (NSCS), while a TAOD decrease happened from 2008 to 2020 in this region. The correlation coefficient between TAOD and SO₄AOD over NSCS from 1980 to 2020 was about 0.93, indicating SO₄AOD was the driving factor of TAOD variation in this area. Different AOD variation trends over the different areas of the SCS could be observed during the two periods including 1980–2007 and 2008–2020. AOD increase appeared over most of the SCS during the period from 1980 to 2007, while AOD decrease could be observed over most of the SCS from 2008 to 2020. Full article

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

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15 pages, 4038 KiB

Open AccessArticle

Effect of Combustion Boundary Conditions and n-Butanol on Surrogate Diesel Fuel HCCI Combustion and Emission Based on Two-Stroke Diesel Engine

by Shiye Wang, Jundong Zhang and Li Yao

Atmosphere 2022, 13(2), 303; https://doi.org/10.3390/atmos13020303 - 10 Feb 2022

Cited by 3 | Viewed by 2040

Abstract

The combustion and emission characteristics of surrogate diesel fuel homogeneous charge compression ignition (HCCI) with different combustion boundary conditions and n-butanol (NB) mixing ratios are studied in this work. Engine data of a two-stroke low-speed direct-injection marine diesel engine were selected for the [...] Read more.

The combustion and emission characteristics of surrogate diesel fuel homogeneous charge compression ignition (HCCI) with different combustion boundary conditions and n-butanol (NB) mixing ratios are studied in this work. Engine data of a two-stroke low-speed direct-injection marine diesel engine were selected for the reactor. HCCI combustion was achieved by compressing a completely homogeneous mixture of fuel and air. The results show that NO emissions decrease slightly with the increase of initial boundary pressure at a constant equivalence ratio and initial temperature. In addition, the different initial boundary temperature has little effect on NO emission. The results also indicate that the ignition delay time of the mixed fuel rises with the increase of n-butanol mixing ratio. The emissions and reaction rate of NO_x reduce significantly with the increase of n-butanol percentage in surrogate diesel fuel and n-butanol mixing combustion at a constant equivalence ratio and total mole fraction. Meanwhile, CO₂ emissions also decrease significantly with the increase of n-butanol mixing ratio. Full article

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

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25 pages, 1046 KiB

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Effects of Carbon Emission Trading on Companies’ Market Value: Evidence from Listed Companies in China

by Maogang Tang, Silu Cheng, Wenqing Guo, Weibiao Ma and Fengxia Hu

Atmosphere 2022, 13(2), 240; https://doi.org/10.3390/atmos13020240 - 30 Jan 2022

Cited by 13 | Viewed by 5451

Abstract

Emissions trading schemes (ETSs) are effective measures that facilitate economic growth and carbon mitigation, especially for developing countries such as China. These schemes can further affect the cash flow, production, and investment decisions of regulated companies. However, few empirical studies have explored how [...] Read more.

Emissions trading schemes (ETSs) are effective measures that facilitate economic growth and carbon mitigation, especially for developing countries such as China. These schemes can further affect the cash flow, production, and investment decisions of regulated companies. However, few empirical studies have explored how ETSs promote companies’ market value. We systematically evaluate the influence of the carbon emission trading (CET) policy on companies’ market value and explore the influential mechanism. We use the data of listed companies from the Chinese stock “A” markets and employ the difference-in-difference method to account for the unobserved cause of the CET policy regarding companies’ market value. Robust benchmark regression results reveal that the CET policy promotes companies’ market value significantly. The mechanism analysis reveals that the CET policy can improve the market value of listed companies by influencing the carbon price, innovative activities, and carbon disclosure. The results of the heterogeneity analysis show that the CET policy’s impact on companies’ market value is heterogeneous in terms of marketization degree, industry, firm ownership, and different regions. We suggest that the carbon pricing mechanism, degree of market perfection, carbon disclosure policy, and carbon finance should be optimized to improve the efficiency of ETSs. Full article

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

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17 pages, 6489 KiB

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Research on the Growth Mechanism of PM_2.5 in Central and Eastern China during Autumn and Winter from 2013–2020

by Qi Jiang, Hengde Zhang, Fei Wang and Fei Wang

Atmosphere 2022, 13(1), 134; https://doi.org/10.3390/atmos13010134 - 14 Jan 2022

Cited by 7 | Viewed by 2227

Abstract

Haze is a majorly disastrous type of weather in China, especially central and eastern of China. The development of haze is mainly caused by highly concentrated fine particles (PM_2.5) on a regional scale. Here, we present the results from an autumn [...] Read more.

Haze is a majorly disastrous type of weather in China, especially central and eastern of China. The development of haze is mainly caused by highly concentrated fine particles (PM_2.5) on a regional scale. Here, we present the results from an autumn and winter study conducted from 2013 to 2020 in seven highly polluted areas (27 representative stations) in central and eastern China to analyze the growth mechanism of PM_2.5. At the same time, taking Beijing Station as an example, the characteristics of aerosol composition and particle size in the growth phase are analyzed. Taking into account the regional and inter-annual differences of fine particles (PM_2.5) distribution, the local average PM_2.5 growth value of the year is used as the boundary value for dividing slow, rapid, and explosive growth (only focuses on the hourly growth rate greater than 0). The average value of PM_2.5 in the autumn and winter of each regional representative station shows a decreasing trend as a whole, especially after 2017, whereby the decreasing trend was significant. The distribution value of +ΔPM_2.5 (PM_2.5 hourly growth rate) in the north of the Huai River is lower than that in the south of the Huai River, and both of the +ΔPM_2.5 after 2017 showed a significant decreasing trend. The average PM_2.5 threshold before the explosive growth is 70.8 µg m⁻³, and the threshold that is extremely prone to explosive growth is 156 µg m⁻³ to 277 µg m⁻³ in north of the Huai River. For the area south of the Huai River, the threshold for PM_2.5 explosive growth is relatively low, as a more stringent threshold also puts forward stricter requirements on atmospheric environmental governance. For example, in Beijing, the peak diameters gradually shift to larger sizes when the growth rate increases. The number concentration increasing mainly distributed in Aitken mode (AIM) and Accumulation mode (ACM) during explosive growth. Among the various components of submicron particulate matter (PM₁), organic aerosol (OA), especially primary OA (POA), have become one of the most critical components for the PM_2.5 explosive growth in Beijing. During the growth period, the contribution of secondary particulate matter (SPM) to the accumulated pollutants is significantly higher than that of primary particulate matter (PPM). However, the proportion of SPM gradually decreases when the growth rate increases. The contribution of the PPM can reach 48% in explosive growth. Compared to slow and rapid growth, explosive growth mainly occurs in the stable atmosphere of higher humidity, lower pressure, lower temperature, small winds, and low mixed layers. Full article

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

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13 pages, 3203 KiB

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PCA-Based Identification of Built Environment Factors Reducing PM_2.5 Pollution in Neighborhoods of Five Chinese Megacities

by Ming Chen and Fei Dai

Atmosphere 2022, 13(1), 115; https://doi.org/10.3390/atmos13010115 - 12 Jan 2022

Cited by 3 | Viewed by 2431

Abstract

Air pollution, especially PM_2.5 pollution, still seriously endangers the health of urban residents in China. The built environment is an important factor affecting PM_2.5; however, the key factors remain unclear. Based on 37 neighborhoods located in five Chinese megacities, three [...] Read more.

Air pollution, especially PM_2.5 pollution, still seriously endangers the health of urban residents in China. The built environment is an important factor affecting PM_2.5; however, the key factors remain unclear. Based on 37 neighborhoods located in five Chinese megacities, three relative indicators (the range, duration, and rate of change in PM_2.5 concentration) at four pollution levels were calculated as dependent variables to exclude the background levels of PM_2.5 in different cities. Nineteen built environment factors extracted from green space and gray space and three meteorological factors were used as independent variables. Principal component analysis was adopted to reveal the relationship between built environment factors, meteorological factors, and PM_2.5. Accordingly, 24 models were built using 32 training neighborhood samples. The results showed that the adj_R² of most models was between 0.6 and 0.8, and the highest adj_R² was 0.813. Four principal factors were the most important factors that significantly affected the growth and reduction of PM_2.5, reflecting the differences in green and gray spaces, building height and its differences, relative humidity, openness, and other characteristics of the neighborhood. Furthermore, the relative error was used to test the error of the predicted values of five verification neighborhood samples, finding that these models had a high fitting degree and can better predict the growth and reduction of PM_2.5 based on these built environment factors. Full article

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

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9 pages, 1261 KiB

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The Impact of Air Pollution (PM2.5) on Atherogenesis in Modernizing Southern versus Northern China

by Kamsang Woo, Changqing Lin, Yuehui Yin, Dongshuang Guo, Ping Chook, Timothy C. Y. Kwok and David S. Celermajer

Atmosphere 2021, 12(12), 1552; https://doi.org/10.3390/atmos12121552 - 24 Nov 2021

Cited by 3 | Viewed by 2064

Abstract

To evaluate the impact of PM2.5 air pollution on atherogenic processes in modernizing Southern versus Northern China, we studied 1323 asymptomatic Chinese in Southern and Northern China in 1996–2007. PM2.5 exposure and metabolic syndrome (MS) were noted. Brachial flow-mediated dilation (endothelial function FMD) [...] Read more.

To evaluate the impact of PM2.5 air pollution on atherogenic processes in modernizing Southern versus Northern China, we studied 1323 asymptomatic Chinese in Southern and Northern China in 1996–2007. PM2.5 exposure and metabolic syndrome (MS) were noted. Brachial flow-mediated dilation (endothelial function FMD) and carotid intima-media thickness (IMT) were measured by ultrasound. Although age and gender were similar, PM2.5 was higher in Northern China than in Southern China. The Northern Chinese were characterized by lower lipids, folate and vitamin B12, but higher age, blood pressures, MS and homocysteine (HC) (p = 0.0015). Brachial FMD was significantly lower and carotid IMT was significantly greater (0.68 ± 0.13) in Northern Chinese, compared with FMD and IMT (0.57 ± 0.13, p < 0.0001) in Southern Chinese. On multivariate regression, for the overall cohort, carotid IMT was significantly related to PM2.5, independent of location and traditional risk factors (Model R² = 0.352, F = 27.1, p < 0.0001), while FMD was inversely related to gender, age, and northern location, but not to PM2.5. In Southern Chinese, brachial FMD was inversely correlated to PM2.5, independent of age, whereas carotid IMT was significantly related to PM2.5, independent of age and gender. In Northern Chinese, brachial FMD was inversely related to gender only, but not to PM2.5, while carotid IMT was related to traditional risk factors. Despite a higher PM2.5 pollution in Northern China, PM2.5 pollution was more significantly associated with atherogenic surrogates in Southern compared to Northern Chinese. This has potential implications for atherosclerosis prevention. Full article

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

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14 pages, 8191 KiB

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Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

by Chunsheng Fang, Hanbo Gao, Zhuoqiong Li and Ju Wang

Atmosphere 2021, 12(11), 1519; https://doi.org/10.3390/atmos12111519 - 18 Nov 2021

Cited by 4 | Viewed by 2089

Abstract

This study systematically investigated the pollution characteristics of atmospheric O₃ and PM_2.5, regional transport, and their health risks in three provincial capitals in northeast China during 2016–2020. The results show that O₃ concentrations showed a trend of high summer [...] Read more.

This study systematically investigated the pollution characteristics of atmospheric O₃ and PM_2.5, regional transport, and their health risks in three provincial capitals in northeast China during 2016–2020. The results show that O₃ concentrations showed a trend of high summer and low winter, while PM_2.5 concentrations showed a trend of high winter and low summer during these five years. The results of the correlation analysis indicate that external sources contribute more O₃, while PM_2.5 is more from local sources. The backward trajectory clustering analysis results showed that Changchun had the highest share of northwest trajectory with a five-year average value of 67.89%, and the city with the highest percentage of southwest trajectory was Shenyang with a five-year average value of 23.95%. The backward trajectory clustering analysis results showed that the share of the northwest trajectory decreased and the share of the southwest trajectory increased for all three cities in 2020 compared to 2016. The results of the potential source contribution function (PSCF) and concentration weighting trajectory (CWT) analysis showed that the main potential source areas and high concentration contribution areas for PM_2.5 in the northeast were concentrated in Mongolia, Inner Mongolia, Shandong Province, and the northeast, and for O₃ were mainly located in Shandong, Anhui, and Jiangsu Provinces, and the Yellow Sea and Bohai Sea. The non-carcinogenic risk of PM_2.5 in Harbin was high with a HQ of 2.04, while the other cities were at acceptable levels (HQ < 0.69) and the non-carcinogenic risk of O₃ was acceptable in all three cities (HQ < 0.22). However, PM_2.5 had a high carcinogenic risk (4 × 10⁻⁴ < CR < 0.44) and further treatment is needed to reduce the risk. Full article

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

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17 pages, 4804 KiB

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Research on the Temporal and Spatial Characteristics of Air Pollutants in Sichuan Basin

by Chunsheng Fang, Xiaodong Tan, Yue Zhong and Ju Wang

Atmosphere 2021, 12(11), 1504; https://doi.org/10.3390/atmos12111504 - 15 Nov 2021

Cited by 11 | Viewed by 2520

Abstract

Sichuan Basin is one of the most densely populated areas in China and the world. Human activities have great impact on the air quality. In order to understand the characteristics of overall air pollutants in Sichuan Basin in recent years, we analyzed the [...] Read more.

Sichuan Basin is one of the most densely populated areas in China and the world. Human activities have great impact on the air quality. In order to understand the characteristics of overall air pollutants in Sichuan Basin in recent years, we analyzed the concentrations of six air pollutants monitored in 22 cities during the period from January 2015 to December 2020. During the study period, the annual average concentrations of CO, NO₂, SO₂, PM_2.5 and PM₁₀ all showed a clear downward trend, while the ozone concentration was slowly increasing. The spatial patterns of CO and SO₂ were similar. High-concentration areas were mainly located in the western plateau of Sichuan Basin, while the concentrations of NO₂ and particulate matter were more prominent in the urban agglomerations inside the basin. During the study period, changes of the monthly average concentrations for pollutants (except for O₃) conformed to the U-shaped pattern, with the highest in winter and the lowest in summer. In the southern cities of the basin, secondary sources had a higher contribution to the generation of fine particulate matter, while in large cities inside the basin, such as Chengdu and Chongqing, air pollution had a strong correlation with automobile exhaust emissions. The heavy pollution incidents observed in the winter of 2017 were mainly caused by the surrounding plateau terrain with typical stagnant weather conditions. This finding was also supported by the backward trajectory analysis, which showed that the air masses arrived in Chengdu were mainly from the western plateau area of the basin. The results of this study will provide a basis for the government to take measures to improve the air quality in Sichuan Basin. Full article

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

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11 pages, 5904 KiB

Open AccessArticle

A Haze Prediction Model in Chengdu Based on LSTM

by Xinyi Wu, Zhixin Liu, Lirong Yin, Wenfeng Zheng, Lihong Song, Jiawei Tian, Bo Yang and Shan Liu

Atmosphere 2021, 12(11), 1479; https://doi.org/10.3390/atmos12111479 - 9 Nov 2021

Cited by 76 | Viewed by 3931

Abstract

Air pollution with fluidity can influence a large area for a long time and can be harmful to the ecological environment and human health. Haze, one form of air pollution, has been a critical problem since the industrial revolution. Though the actual cause [...] Read more.

Air pollution with fluidity can influence a large area for a long time and can be harmful to the ecological environment and human health. Haze, one form of air pollution, has been a critical problem since the industrial revolution. Though the actual cause of haze could be various and complicated, in this paper, we have found out that many gases’ distributions and wind power or temperature are related to PM2.5/10’s concentration. Thus, based on the correlation between PM2.5/PM10 and other gaseous pollutants and the timing continuity of PM2.5/PM10, we propose a multilayer long short-term memory haze prediction model. This model utilizes the concentration of O₃, CO, NO₂, SO₂, and PM2.5/PM10 in the last 24 h as inputs to predict PM2.5/PM10 concentrations in the future. Besides pre-processing the data, the primary approach to boost the prediction performance is adding layers above a single-layer long short-term memory model. Moreover, it is proved that by doing so, we could let the network make predictions more accurately and efficiently. Furthermore, by comparison, in general, we have obtained a more accurate prediction. Full article

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

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16 pages, 2479 KiB

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Spatiotemporal Analysis of Haze in Beijing Based on the Multi-Convolution Model

by Lirong Yin, Lei Wang, Weizheng Huang, Shan Liu, Bo Yang and Wenfeng Zheng

Atmosphere 2021, 12(11), 1408; https://doi.org/10.3390/atmos12111408 - 26 Oct 2021

Cited by 102 | Viewed by 4286

Abstract

As a kind of air pollution, haze has complex temporal and spatial characteristics. From the perspective of time, haze has different causes and levels of pollution in different seasons. From the perspective of space, the concentration of haze in adjacent areas will affect [...] Read more.

As a kind of air pollution, haze has complex temporal and spatial characteristics. From the perspective of time, haze has different causes and levels of pollution in different seasons. From the perspective of space, the concentration of haze in adjacent areas will affect each other, showing some correlation. In this paper, we construct a multi-convolution haze-level prediction model for predicting haze levels in different areas of Beijing, which uses the remote sensing satellite image of the Beijing divided into nine regions as input and the haze pollution level as output. We categorize the predictions into four seasons in chronological order and use frequency histograms to analyze haze levels in different regions in different seasons. The results show that the haze pollution in the southern regions is significantly different from that in the northern regions. In addition, the haze tends to be clustered in adjacent areas. We use Global Moran’s I to analyze the predictions and find that haze is related to the geographical location in summer and autumn. We also use Local Moran’s I, Moran scatter plot, and Local Indicators of Spatial Association (LISA) to study the spatial characteristics of haze in adjacent areas. The results show, for the spatial distribution of haze in Beijing, that the southern regions present a high-high agglomeration, while the northern regions exhibit a ‘low-low agglomeration. The temporal evolution of haze on the seasonal scale, according to the chronological order of winter, spring, and summer to autumn, shows that the haze gradually becomes agglomerated. The main finding is that the haze pollution in southern Beijing is significantly different from that of northern regions, and haze tends to be clustered in adjacent areas. Full article

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

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14 pages, 1943 KiB

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Analysis of Spatio-Temporal Heterogeneity and Socioeconomic driving Factors of PM_2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

by Ju Wang, Ran Li, Kexin Xue and Chunsheng Fang

Atmosphere 2021, 12(10), 1324; https://doi.org/10.3390/atmos12101324 - 10 Oct 2021

Cited by 9 | Viewed by 2277

Abstract

Due to rapid urbanization and socio-economic development, fine particulate matter (PM_2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may [...] Read more.

Due to rapid urbanization and socio-economic development, fine particulate matter (PM_2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM_2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM_2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM_2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM_2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of “high–high” and “low–low”. The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM_2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM_2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM_2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM_2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM_2.5 pollutions from a socio-economic perspective. Full article

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

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14 pages, 287 KiB

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New Urbanization, Energy-Intensive Industries Agglomeration and Analysis of Nitrogen Oxides Emissions Reduction Mechanisms

by Yang Yu and Tianchang Wang

Atmosphere 2021, 12(10), 1244; https://doi.org/10.3390/atmos12101244 - 24 Sep 2021

Cited by 6 | Viewed by 2287

Abstract

With the deepening of urbanization and industrialization, as well as the exacerbation of energy consumption, China is facing a severe situation in which nitrogen oxide (NOx) emissions reduction is imperative. In this study, it is aimed to put forward countermeasures and suggestions to [...] Read more.

With the deepening of urbanization and industrialization, as well as the exacerbation of energy consumption, China is facing a severe situation in which nitrogen oxide (NOx) emissions reduction is imperative. In this study, it is aimed to put forward countermeasures and suggestions to reduce NOx emissions by analyzing the impact and mechanism of new urbanization, the agglomeration of energy-intensive industries and mutual interactions on China’s NOx emissions. By analyzing the data of 30 provinces in China from 2006 to 2017, this paper adopted the system generalized method of moments (SYS-GMM) and intermediary effect model to introduce four variables, such as: energy efficiency, human capital, industrial structure and energy structure, which were for empirical analysis. From the results, it was shown that: (1) NOx emissions in China have an accumulated effect; (2) new urbanization inhibits NOx emissions, whilst the agglomeration of energy-intensive industries intensifies NOx emissions. New urbanization weakens the negative impact of the agglomeration of energy-intensive industries on NOx emissions reduction and, (3) among the impacts of new urbanization on NOx emissions, the energy efficiency and human capital reflect the intermediary effect mechanism. At the same time, in the impact of the agglomeration of energy-intensive industries on NOx emissions, the industrial structure and energy structure show the mechanisms of the intermediary effect and masking effect, respectively. Full article

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

14 pages, 2798 KiB

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Concentration Characteristics and Photochemical Reactivities of VOCs in Shenyang, China

by Ningwei Liu, Xiaolan Li, Wanhui Ren, Liguang Li, Congcong Su and Chuang Wang

Atmosphere 2021, 12(10), 1240; https://doi.org/10.3390/atmos12101240 - 23 Sep 2021

Cited by 10 | Viewed by 3109

Abstract

We investigated the seasonal and diurnal characteristics of volatile organic compound (VOC) concentrations in Shenyang, China, using the whole-year hourly data of 52 types of VOC at three sites over the year 2019. The photochemical reactivities of VOCs were also studied by analyzing [...] Read more.

We investigated the seasonal and diurnal characteristics of volatile organic compound (VOC) concentrations in Shenyang, China, using the whole-year hourly data of 52 types of VOC at three sites over the year 2019. The photochemical reactivities of VOCs were also studied by analyzing the influence of VOCs on ozone and secondary organic aerosol (SOA) formation potential and the hydroxyl radical consumption rate. It is shown that the order of VOC concentrations from high to low is alkanes, alkynes, alkenes, and aromatic hydrocarbons. For various types of VOCs, the maximum appeared in the morning and at night, whereas the minimum appeared in the afternoon. The contributions of VOCs to ozone formation potential are highest for aromatic hydrocarbons with a value of 78%, followed by alkenes and alkanes, among which toluene and isoprene contributed the most. The contributions of VOCs to SOA formation potential are also highest for aromatic hydrocarbons with a value of 94%, followed by alkanes and alkenes, among which the contributions of toluene and benzene add up to over 70%. Being the most active type of VOCs in atmospheric chemical reactions, aromatic hydrocarbons are the dominant contributor to the formation of both ozone and SOA, and therefore being able to control of the use of a large number of solvents and vehicle exhaust emissions would be an effective way to regulate the formation of ozone and SOA in Shenyang. Full article

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

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12 pages, 1983 KiB

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Temporal and Spatial Trends in Particulate Matter and the Responses to Meteorological Conditions and Environmental Management in Xi’an, China

by Yulu Tian, Lingnan Zhang, Yang Wang, Jinxi Song and Haotian Sun

Atmosphere 2021, 12(9), 1112; https://doi.org/10.3390/atmos12091112 - 30 Aug 2021

Cited by 9 | Viewed by 2751

Abstract

Particulate matter contributes much to the haze pollution in China. Meteorological conditions and environmental management significantly influenced the accumulation, deposition, transportation, diffusion, and emission intensity of particulate matter. In this study, temporal and spatial variations of PM10 and PM2.5—and the responses to meteorological [...] Read more.

Particulate matter contributes much to the haze pollution in China. Meteorological conditions and environmental management significantly influenced the accumulation, deposition, transportation, diffusion, and emission intensity of particulate matter. In this study, temporal and spatial variations of PM10 and PM2.5—and the responses to meteorological factors and environmental regulation intensity—were explored in Xi’an, China. The concentrations of PM10 were higher than those of PM2.5, especially in spring and winter. The mean annual concentrations of PM10 and PM2.5 markedly decreased from 2013 to 2017, but the decreasing trend has plateaued since 2015. The concentrations of PM10 and PM2.5 exhibited seasonal differences, with winter being the highest and summer the lowest. Air quality monitoring stations did not reveal significant spatial variability in PM10 and PM2.5 concentrations. The concentrations of PM10 and PM2.5 were significantly influenced by precipitation, relative humidity, and atmospheric temperature. The impact of wind speed was prominent in autumn and winter, while in spring and summer the impact of wind direction was obvious. Additionally, the emission intensity of SO₂, smoke and dust could be effectively decreased with the increasing environmental regulation intensity, but not the concentrations of particulate matter. This study could provide a scientific framework for atmospheric pollution management. Full article

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

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19 pages, 13554 KiB

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Analysis of the Interactions between the 200 hPa Jet and Air Pollutants in the Near-Surface Layer over East Asia in Summer

by Wen Wei, Bingliang Zhuang, Huijuan Lin, Yu Shu, Tijian Wang, Huimin Chen and Yiman Gao

Atmosphere 2021, 12(7), 886; https://doi.org/10.3390/atmos12070886 - 8 Jul 2021

Cited by 2 | Viewed by 2434

Abstract

The rapid economic development in East Asia has led to serious air pollution problems in the near-surface layer. Studies have shown that there is an interaction between air pollution and the East Asian upper-level jet, which is an important weather system controlling the [...] Read more.

The rapid economic development in East Asia has led to serious air pollution problems in the near-surface layer. Studies have shown that there is an interaction between air pollution and the East Asian upper-level jet, which is an important weather system controlling the climate in East Asia. Therefore, it is of great significance to study the relationship between the surface layer air pollutants and the upper-level jet stream in East Asia. Based on the daily wind and vertical velocity data provided by the National Centers for Environmental Prediction/National Center for Atmospheric Research as well as the surface pollutant and meteorological variable data provided by the Science Data Bank, we use statistical analysis methods to study the relationship between the East Asian upper-level jet and the high-concentration area of near-surface air pollutants in summer. Meanwhile, the mechanisms of the interaction are preliminarily discussed. The results show that the North China Plain and the Tarim Basin are the high-value areas of the particulate matter (PM) in summer during 2013–2018, and the ozone (O₃) concentration in the near-surface atmospheric layer in the North China Plain is also high. The average concentrations of the PM_2.5, PM₁₀ and O₃ in the North China Plain are 45.09, 70.28 and 131.27 μg·m⁻³, respectively, and the days with the concentration exceeding the standard reach 401, 461 and 488, respectively. During this period, there is an increasing trend in the O₃ concentration and a decreasing trend in the PM concentration. The average ratio of the PM_2.5 to PM₁₀ is approximately 0.65 with a decreasing trend. The air pollutant concentration in this region has a significant relationship with the location of the East Asian upper-level jet. The low wind speed at the surface level under the control of the upper-level jet is the main reason for the high pollutant concentration besides the pollutant emission. They relate to each other through the surface humidity and the meridional and zonal wind. Meanwhile, the concentrations of the PM_2.5 and PM₁₀ are high in the near-surface layer in the Tarim Basin, and the average concentrations are 45.19 and 49.08 μg·m⁻³, respectively. The days with the concentration exceeding the standard are 265 and 193, respectively. The interannual variation in the PM concentration shows an increasing trend first and then a decreasing trend. The average ratio of PM_2.5 to PM₁₀ in this region reaches approximately 0.9. The ratio reaches the highest in 2013 and 2014 and then decreases to and maintains at approximately 0.85. The concentration of air pollutants in the basin has a significant relationship with the intensity of the upper-level jet in East Asia. The weakening of the upper-level jet will lead to a decrease in the surface humidity in the northern part of the basin, an increase in the surface temperature in the western part of the basin and a decrease in the surface zonal wind in the eastern part of the basin, which will result in a higher PM concentration. Full article

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

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12 pages, 3691 KiB

Open AccessArticle

A Simple New Method for Calculating Precipitation Scavenging Effect on Particulate Matter: Based on Five-Year Data in Eastern China

by Bin Zhou, Duanyang Liu and Wenlian Yan

Atmosphere 2021, 12(6), 759; https://doi.org/10.3390/atmos12060759 - 11 Jun 2021

Cited by 16 | Viewed by 3303

Abstract

A “rain-only” method is proposed to find out the precipitation effect on particle aerosol removal from the atmosphere, and this method is not only unique and novel but also very simple and can be easily adapted to predict aerosol particle scavenging over any [...] Read more.

A “rain-only” method is proposed to find out the precipitation effect on particle aerosol removal from the atmosphere, and this method is not only unique and novel but also very simple and can be easily adapted to predict aerosol particle scavenging over any region across the world irrespective of the topographical, orographical, and climatic features. By using this simple method, the influences of the rain intensity and particle mass concentration on the aerosol scavenging efficiency are discussed. The results show that a higher concentration, a higher rain intensity, and a larger particle size lead to a higher scavenging efficiency and a higher scavenging rate. The greater the rain intensity, the higher the scavenging efficiency. The scavenging efficiency of PM₁₀ by precipitation is better than that of PM_2.5. When the rain intensity is 10 mm h⁻¹, the scavenging efficiency of PM_2.5 reaches 5.1 μg m⁻³ h⁻¹, and the scavenging efficiency of PM₁₀ reaches 15.8 μg m⁻³ h⁻¹. The scavenging rate increases faster when accumulative precipitation is below 15 mm. The scavenging rate has obvious monthly variation, and the scavenging rate of coastal areas is less than that of inland Jiangsu. The growth of the particle mass concentration after precipitation is divided into two stages: the rapid growth stage after precipitation ends, and the slow growth stage about 24 h after precipitation ends. Full article

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

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16 pages, 2434 KiB

Open AccessArticle

Mass Concentration, Chemical Composition, and Source Characteristics of PM_2.5 in a Plateau Slope City in Southwest China

by Jianwu Shi, Yinchuan Feng, Liang Ren, Xiuqing Lu, Yaoqian Zhong, Xinyu Han and Ping Ning

Atmosphere 2021, 12(5), 611; https://doi.org/10.3390/atmos12050611 - 8 May 2021

Cited by 7 | Viewed by 3095

Abstract

In order to investigate the seasonal variations in the chemical characteristics of PM_2.5 at the plateau slope of a mountain city in southwest China, 178 PM_2.5 filters (89 quartz and 89 Teflon samples for PM_2.5) were collected to sample [...] Read more.

In order to investigate the seasonal variations in the chemical characteristics of PM_2.5 at the plateau slope of a mountain city in southwest China, 178 PM_2.5 filters (89 quartz and 89 Teflon samples for PM_2.5) were collected to sample the urban air of Wenshan in spring and autumn 2016 at three sites. The mass concentrations, water-soluble inorganic ions, organic and inorganic carbon concentrations, and inorganic elements constituting PM_2.5 were determined, principal component analysis was used to identify potential sources of PM_2.5, and the backward trajectory model was used to calculate the contribution of the long-distance transmission of air particles to the Wenshan area. The average concentration of PM_2.5 in spring and autumn was 44.85 ± 10.99 μg/m³. Secondary inorganic aerosols contributed 21.82% and 16.50% of the total PM_2.5 in spring and autumn, respectively. The daily mean value of OC/EC indicated that the measured SOC content was generated by the photochemical processes active during the sampling days. However, elements from anthropogenic sources (Ti, Si, Ca, Fe, Al, K, Mg, Na, Sb, Zn, P, Pb, Mn, As and Cu) accounted for 99.38% and 99.24% of the total inorganic elements in spring and autumn, respectively. Finally, source apportionment showed that SIA, dust, industry, biomass burning, motor vehicle emissions and copper smelting emissions constituted the major components in Wenshan. This study is the first to investigate the chemical characterizations and sources of PM_2.5 in Wenshan, and it provides effective support for local governments formulating air pollution control policies. Full article

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

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Review

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18 pages, 888 KiB

Open AccessReview

Review on Atmospheric Ozone Pollution in China: Formation, Spatiotemporal Distribution, Precursors and Affecting Factors

by Ruilian Yu, Yiling Lin, Jiahui Zou, Yangbin Dan and Chen Cheng

Atmosphere 2021, 12(12), 1675; https://doi.org/10.3390/atmos12121675 - 13 Dec 2021

Cited by 37 | Viewed by 5316

Abstract

In recent years, atmospheric ozone pollution has become more and more serious in many areas of China due to the rapid development of industrialization and urbanization. The increase in atmospheric ozone concentration will not only cause harm to the human respiratory tract, nervous [...] Read more.

In recent years, atmospheric ozone pollution has become more and more serious in many areas of China due to the rapid development of industrialization and urbanization. The increase in atmospheric ozone concentration will not only cause harm to the human respiratory tract, nervous system and immune system, but also cause obvious harm to crops, which will lead to reductions in crop production. Therefore, the study of atmospheric ozone pollution should not be ignored in research on the atmospheric environment. In this paper, we summarized the formation mechanisms of atmospheric ozone, the spatiotemporal distribution characteristics of atmospheric ozone in some areas of China, the relationship between atmospheric ozone and its precursors, and the main factors affecting the concentration of atmospheric ozone. Then, the control countermeasures against atmospheric ozone pollution were put forward in combination with the actual situation in China. Full article

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

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