Mass Concentration, Chemical Composition, and Source Characteristics of PM2.5 in a Plateau Slope City in Southwest China

Shi, Jianwu; Feng, Yin-Chuan; Ren, Liang; Lu, Xiuqing; Zhong, Yaoqian; Han, Xinyu; Ning, Ping

doi:10.3390/atmos12050611

Cited by 8 publications

(6 citation statements)

References 62 publications

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“…In comparison to other Chinese studies, most of the ionic species identified in the research are found to be on the lower side. Compared with Kunming [30] and Wenshan [40], the concentration of SO 4 2− was lowest, which is consistent with the lagged industrial development of Baoshan. These results show that the WSII concentrations in Baoshan were impacted more by local pollution sources (e.g., biomass burning, agricultural dust, construction dust, etc.)…”

Section: Characteristics Of Pm 25supporting

confidence: 69%

“…These values are lower than those of developed cities in the plains of China, such as Beijing and Tianjing [38]. Furthermore, the concentration of PM 2.5 in Baoshan was lower than that in some plateau cities, such as Guiyang, Wenshan, and Kunming [30,39,40]. At the same time, it can be seen in Figure 2 that although the air quality in Baoshan was better than that in domestic cities, there is still a certain gap in comparison to foreign cities, such as New York [41].…”

Section: Characteristics Of Pm 25mentioning

confidence: 99%

“…The dominant compounds were secondary inorganic aerosols (SIAs, including NO 3 − , SO 4 2− , and NH 4 + ), with concentrations accounting for more than 55% of the total WSII mass of PM 2.5 . The concentrations of WSIIs in Baoshan are shown in Table 2 and compared to other typical cities, such as Kunming [30] and Wenshan [40] on the plateau, and Huanggang [42] and Delhi [43] on the plain. In comparison to other Chinese studies, most of the ionic species identified in the research are found to be on the lower side.…”

Section: Characteristics Of Pm 25mentioning

confidence: 99%

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Chemical Composition and Source Apportionment of PM2.5 in a Border City in Southwest China

et al. 2021

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This paper studied the chemical characteristics and seasonal changes of PM2.5 in plateau cities on the southwest border of China. Urban air was sampled in Baoshan City during the rainy and dry seasons. Finally, 174 PM2.5 filters were collected (including 87 quartz and 87 Teflon samples for PM2.5). The mass concentrations, water-soluble inorganic ions, organic and inorganic carbon concentrations, and inorganic elements constituting PM2.5 were determined. Positive definite matrix factorization was used to identify potential sources of PM2.5, 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 PM2.5 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 PM2.5 in Baoshan. Using combined data from three measurement sites provides a focus on the common sources affecting all locations.

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Section: Characteristics Of Pm 25supporting

confidence: 69%

Section: Characteristics Of Pm 25mentioning

confidence: 99%

Section: Characteristics Of Pm 25mentioning

confidence: 99%

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Chemical Composition and Source Apportionment of PM2.5 in a Border City in Southwest China

et al. 2021

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“…The average concentration of the four water-soluble ions and two gases during the sampling period was 6.855 µg/m 3 , with SO 4 2− , NO 3 − , and NH 4 + (collectively referred to as SNA) being the most abundant. These results are consistent with those of Shi et al [22]. During the sampling period, the ratio of the mass concentration of SNA to the total water-soluble ion content in Wuhan (excluding HCl, HNO 2 , HNO 3 , SO 2 , and NH 3 ) was 88.37%.…”

Section: Concentration Of Water-soluble Ions Over Timesupporting

confidence: 92%

Analysis of the Diurnal Changes in the Water-Soluble Ion Concentration in Wuhan between 2016 and 2019

Sun

Zhao

et al. 2022

Atmosphere

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This study uses online monitoring data from the Hubei Environmental Monitoring Center’s Atmospheric Compound Pollution Automatic Monitoring Station from 2016 to 2019 to analyze the diurnal changes in the concentration of water-soluble ions in particulate matter in Wuhan. During the study period, the concentrations of SO2, NO3−, and SO42− changed significantly, while those of NH4+, NH3, and Ca2+ exhibited minimal differences. SO2 and NO3− showed an annually increasing trend, while NH4+ and SO42− exhibited an annually decreasing trend. The ion concentration was generally higher in the winter and spring and lower in the summer and autumn. The concentration of water-soluble ions was generally higher during the day than at night. However, the “weekend effect” on the change in ion concentrations was substantial and higher during the day than at night. This effect was the strongest for NO3− and the weakest for NH3. These changes in the weekend effect of water-soluble ions in particulate matter clearly revealed the impact of periodic human activities on atmospheric pollution. Taken together, the results of this novel study reveal the diurnal pollution characteristics and “weekend effect” of water-soluble ions with high concentrations in atmospheric aerosols in Wuhan over a four-year period, thus providing relevant insights for Wuhan’s atmospheric mitigation plan.

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“…more significant between Harbin and Qiqihar. Consequently, it is apparent that PM2.5 has weak transmission capacity [43][44][45], with a relatively limited spatial distribution range, especially under static and stable weather conditions, predominantly affected by local regional pollution sources.…”

Section: Spatial Variation Characteristics Of O 3 and Pm 25mentioning

confidence: 99%

Characteristics of Temporal and Spatial Changes in Ozone and PM2.5 and Correlation Analysis in Heilongjiang Province

Xuan,

Li,

Wang

et al. 2023

Atmosphere

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The escalating ambient ozone (O3) pollution in China has garnered significant attention, necessitating an intensified focus on O3 pollution control and the coordinated management of PM2.5 and O3. This study reviews and analyzes the spatiotemporal characteristics of O3 and PM2.5 concentrations in 13 cities within Heilongjiang Province from 2019 to 2021. The analysis is based on data sourced from the ecological environment monitoring network. In addition to this, correlation analyses were executed to explore the interaction between the two pollutants. The findings reveal a declining trajectory in PM2.5 concentration over the past three years, while O3 concentration has exhibited an upward trend. Temporally, both O3 and PM2.5 concentrations display pronounced seasonal variations, with peaks evident during the spring and summer (May to July), as well as in the winter (January, February, and December). From a spatial standpoint, elevated O3 concentrations were identified in the southwestern cities of Harbin, Daqing, and Suihua, while the northwestern cities of Daxinganling and Heihe exhibited comparatively lower O3 concentrations, but the difference was not significant. Conversely, PM2.5 concentrations demonstrated substantial variation among the 13 cities (districts). Regarding their correlation, a noteworthy positive correlation between the two pollutants was observed in April and May, contrasted by a negative correlation in November and December. Weather categories such as excellent, good, lightly polluted, moderately polluted, and other weather showed a lower correlation, whereas heavily polluted and severely polluted categories demonstrated a stronger correlation. Furthermore, the correlation with severe pollution is greater than that with heavily polluted, further indicating that heavier air pollution is more conducive to the coexistence of O3 and PM2.5 to form composite pollution. On a provincial scale, the correlation between the two pollutants is progressively increasing annually. This signifies a closely intertwined and intricate interaction and transformation relationship between O3 and PM2.5, accentuating the urgency for synergistic control measures.

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Mass Concentration, Chemical Composition, and Source Characteristics of PM2.5 in a Plateau Slope City in Southwest China

Cited by 8 publications

References 62 publications

Chemical Composition and Source Apportionment of PM2.5 in a Border City in Southwest China

Chemical Composition and Source Apportionment of PM2.5 in a Border City in Southwest China

Analysis of the Diurnal Changes in the Water-Soluble Ion Concentration in Wuhan between 2016 and 2019

Characteristics of Temporal and Spatial Changes in Ozone and PM2.5 and Correlation Analysis in Heilongjiang Province

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