Jianwu Shi

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.

In order to study the characteristics and causes of ozone (O₃) pollution in 16 cities of Yunnan Plateau, the methods of COD, backward trajectory and potential source contribution function (PSCF) were used to analyze the O₃ concentrations from 2015 to 2020 of all state-controlled environmental monitoring stations in 16 cities of Yunnan. The results show that the O₃ concentrations in Yunnan gradually increased from 2015 to 2019, and the concentration in 2020 was the lowest due to the COVID-19 pandemic. The peak O₃ concentration appears in spring. The daily change trend is a typical single peak shape, the lowest value appears around 8: 00, and the highest value is between 15:00 and 16:00. High concentrations of O₃ are from the cities of Zhaotong and Kunming in northeastern Yunnan, while low concentrations of O₃ mainly occur in the southwest and northwest border areas. Temperature and relative humidity are two meteorological parameters that have significant effect on O₃ concentration. Temperature has the best correlation with O₃ in winter, and relative humidity has a better correlation with O₃ in autumn and winter than in spring and summer. Finally, source analysis of O₃ showed that local ozone precursor emission sources and long-distance transmission from South and Southeast Asia constituted the major contributions of O₃ in Yunnan.

The contents of potentially toxic elements (V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb) and emission characteristics of PM_2.5 in soil fugitive dust (SFD) in six Yunnan cities (Baoshan, Kunming, Wenshan, Honghe, Yuxi, and Zhaotong) were investigated in this research. The results showed that the contents of Zn and Pb in PM_2.5 of SFD were the highest around Honghe and Yuxi, respectively, while the contents of Mn were the highest in PM_2.5 of SFD around the other four cities. The enrichment factor and correlation indicated that the potentially toxic elements’ pollution degrees of PM_2.5 of SFD around Kunming, Yuxi, and Honghe were higher than those around the other three cities and that potentially toxic elements were generally affected by metal smelting activities, and in Zhaotong, were affected by coal burning activities, while in Wenshan and Baoshan were less affected by human activities. The total emission of PM_2.5 of SFD in the six cities was 7705.49 t in 2018. The total emission factor of PM_2.5 of SFD reached the highest level from January to May and the lowest level from July to October. The health risk assessment showed that the potentially toxic elements in PM_2.5 of SFD for children in the six cities and for adults in Baoshan, Kunming, Honghe, and Zhaotong had non-carcinogenic risk (non-carcinogenic risk thresholds were greater than 1), and As contributes most to non-carcinogenic risk. The carcinogenic risk value of Cr in PM_2.5 of SFD in Kunming and Zhaotong was between 1 × 10⁻⁶ and 1 × 10⁻⁴, which had a certain carcinogenic risk. More attention should be paid to alleviate health risks posed by particle-bound potentially toxic elements through SFD.

From April 2008 to July 2009, ambient measurements of 58 volatile organic compounds (VOCs), including alkanes, alkenes, and aromatics, were conducted in nine industrial cities (Shenyang, Fushun, Changchun, Jilin, Harbin, Daqing, Huludao, Anshan and Tianjin) of the Northeast Region, China (NRC). Daqing had the highest concentration of VOCs (519.68 ± 309.88 μg/m³), followed by Changchun (345.01 ± 170.52 μg/m³), Harbin (231.14 ± 46.69 μg/m³), Jilin (221.63 ± 34.32 μg/m³), Huludao (195.92 ± 103.26 μg/m³), Fushun (135.43 ± 46.01 μg/m³), Anshan (109.68 ± 23.27 μg/m³), Tianjin (104.31 ± 46.04 μg/m³), Shenyang (75.2 ± 40.09 μg/m³). Alkanes constituted the largest percentage (>40%) in concentrations of the quantified VOCs in NRC, and the exception was Tianjin dominated by aromatics (about 52.34%). Although alkanes were the most abundant VOCs at the cities, the most important VOCs contributing to ozone formation potential (OFP) were alkenes and aromatics. Changchun had the highest OFP (537.3 μg/m³), Tianjin had the lowest OFP (111.7 μg/m³). The main active species contributing to OFP in the nine cities were C2~C6 alkanes, C7~C8 aromatic hydrocarbons, individual cities (Daqing) contained n-hexane, propane and other alkane species. Correlation between individual hydrocarbons, B/T ratio and principal component analysis model (PCA) were deployed to explore the source contributions. The results showed that the source of vehicle exhausts was one of the primary sources of VOCs in all nine cities. Additionally, individual cities, such as Daqing, petrochemical industry was founded to be an important source of VOCs. The results gained from this study provided a large of useful information for better understanding the characteristics and sources of ambient VOCs incities of NRC. The non-carcinogenic risk values of the nine cities were within the safe range recognized by the U.S. Environmental Protection Agency (HQ < 1), and the lifetime carcinogenic risk values of benzene were 3.82 × 10⁻⁵~1.28 × 10⁻⁴, which were higher than the safety range specified by the US Environmental Protection Agency (R < 1.00 × 10⁻⁶). The results of risk values indicated that there was a risk of cancer in these cities.

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.

This paper studied the chemical characteristics and seasonal changes of PM_2.5 in plateau cities on the southwest border of China. Urban air was sampled in Baoshan City during the rainy and dry seasons. Finally, 174 PM_2.5 filters were collected (including 87 quartz and 87 Teflon samples for PM_2.5). The mass concentrations, water-soluble inorganic ions, organic and inorganic carbon concentrations, and inorganic elements constituting PM_2.5 were determined. Positive definite matrix factorization 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 Baoshan area. It was found that in the wet season, most of the air masses come from the Indian Ocean and Myanmar. In the dry season, the air mass mainly comes from the China and Myanmar border area. The average concentration of PM_2.5 in the wet and dry seasons was 23.17 ± 12.23 μg/m³. 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 (Na, Mg, Al, Si, P, K, Ca, Ti, Fe, Cu, Zn, Sb, Ba, and Pb) accounted for 99.51% and 99.40% of the total inorganic elements in the wet season and dry season, respectively. Finally, source apportionment showed that SIA, dust, industry, biomass burning, motor vehicle emissions, and copper smelting emissions constituted the major contributions of PM_2.5 in Baoshan. Using combined data from three measurement sites provides a focus on the common sources affecting all locations.

To explore the mass concentration levels and health risks of heavy metals in the air in dense traffic environments, PM_2.5 samples were collected at three sites in the city of Kunming in April and October 2013, and January and May 2014. Ten heavy metals––V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb––were analyzed by ICP–MS, and the results showed PM_2.5 concentrations significantly higher in spring and winter than in summer and autumn, especially for Zn and Pb. The concentration of heavy metals on working days is significantly higher, indicating that vehicle emissions are significant contributors. An enrichment factor analysis showed that Cr, Mn, Ni, Cu, Zn, As, Cd and Pb come mainly from anthropogenic sources, while V and Co may be both anthropogenic and natural. The correlation and principal component analysis (PCA) showed that Ni, Cu, Zn, Cd and Pb mainly come from vehicles emissions and metallurgical industries; Cr and Mn, from vehicles emissions and road dust; and As, mainly from coal combustion. The health risk assessment shows that the non-carcinogenic risk thresholds of the heavy metals in PM_2.5 to children and adult men and women are all less than 1. The carcinogenic risk of Cr for men and women in traffic-intensive areas exceeds 10⁻⁴, reaching 1.64 × 10⁻⁴ and 1.4 × 10⁻⁴, respectively.

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.