Gaseous and Particulate Pollution in the Wu-Chang-Shi Urban Agglomeration on the Northern Slope of Tianshan Mountains from 2017 to 2021
Abstract
:1. Introduction
2. Data and Methods
2.1. Studying urban
2.2. Data Collection and Data Analyses
2.2.1. Data Collection
2.2.2. Data Analyses
HYSPLIT Model and Backward Trajectory
Cluster Analysis
Potential Source Contribution Function
Concentration Weighted Trajectory Analysis
3. Results and Discussions
3.1. Urban Gaseous and Particulate Pollutants Profiles
3.2. Seasonal Variation
3.3. Influence of Meteorological Factor on Pollutants Concentration
3.4. Backward Trajectory Clustering Analysis during Winter
3.5. Potential Source Area Analysis
3.5.1. PSCF Analysis
3.5.2. CWT Analyse
3.6. Comparisons with Other Chinese Cities
3.7. Characteristics of Changes in Air Pollutant Concentrations before and after the New Coronary Pneumonia Outbreak
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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City | Pollutants Species | 2017 | 2018 | 2019 | 2020 | 2021 |
---|---|---|---|---|---|---|
Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | ||
Changji | AQI | 103.52 ± 60.30 | 105.03 ± 53.81 | 95.28 ± 47.29 | 96.52 ± 54.49 | 97.66 ± 45.90 |
SO2 | 18.09 ± 12.98 | 14.41 ± 5.63 | 10.52 ± 3.01 | 8.48 ± 2.39 | 10.60 ± 2.47 | |
NO2 | 45.24 ± 13.27 | 43.29 ± 11.67 | 37.36 ± 7.23 | 32.61 ± 16.56 | 35.72 ± 12.83 | |
CO | 1.33 ± 0.68 | 1.16 ± 0.64 | 0.97 ± 0.50 | 0.93 ± 0.64 | 1.08 ± 0.56 | |
O3 | 83.43 ± 30.38 | 82.03 ± 32.77 | 77.85 ± 32.06 | 89.28 ± 31.39 | 91.86 ± 32.58 | |
PM10 | 98.49 ± 68.39 | 114.52 ± 67.07 | 98.87 ± 64.66 | 91.45 ± 64.53 | 92.19 ± 53.93 | |
PM2.5 | 67.29 ± 57.62 | 61.45 ± 52. 48 | 57.66 ± 48.00 | 52.79 ± 55.22 | 51.75 ± 49.60 | |
Shihezi | AQI | 109.27 ± 53.17 | 105.32 ± 55.21 | 103.73 ± 53.31 | 97.82 ± 59.02 | 96.97 ± 47.57 |
SO2 | 15.25 ± 4.86 | 11.84 ± 2.64 | 11.88 ± 2.21 | 9.63 ± 2.20 | 9.25 ± 1.98 | |
NO2 | 42.80 ± 17.71 | 33.71 ± 13.62 | 36.53 ± 9.94 | 32.87 ± 12.72 | 35.88 ± 11.87 | |
CO | 1.15 ± 0.63 | 0.99 ± 0.52 | 0.91 ± 0.51 | 0.85 ± 0.45 | 0.86 ± 0.42 | |
O3 | 101.39 ± 42.04 | 86.78 ± 35.31 | 84.50 ± 32.94 | 84.40 ± 30.06 | 84.07 ± 33.25 | |
PM10 | 102.14 ± 74.29 | 101.42 ± 62.59 | 99.87 ± 57.79 | 94.29 ± 59.88 | 91.72 ± 53.78 | |
PM2.5 | 61.87 ± 56.71 | 61.23 ± 55.00 | 61.44 ± 55.81 | 55.44 ± 59.06 | 53.43 ± 48.88 | |
Urumqi | AQI | 108.14 ± 64.97 | 97.98 ± 36.85 | 90.03 ± 34. 82 | 87.68 ± 41.98 | 81.59 ± 24.97 |
SO2 | 13.26 ± 6.42 | 10.54 ± 2.31 | 8.31 ± 1.17 | 8.52 ± 0.91 | 7.21 ± 1.08 | |
NO2 | 48.69 ± 17.83 | 42.83 ± 12.80 | 41.22 ± 12.65 | 35.52 ± 16.37 | 37.34 ± 12.11 | |
CO | 1.38 ± 0.76 | 1.20 ± 0.64 | 1.04 ± 0.56 | 0.94 ± 0.52 | 0.81 ± 0.39 | |
O3 | 71.77 ± 30.82 | 79.70 ± 34. 28 | 79.09 ± 34.23 | 80.45 ± 30.05 | 84.58 ± 30.83 | |
PM10 | 112.80 ± 59.41 | 113.37 ± 45.76 | 86.87 ± 33.65 | 79.00 ± 31.81 | 71.87 ± 21.90 | |
PM2.5 | 68.99 ± 63.54 | 52.65 ± 39.92 | 49.01 ± 39.38 | 47.34 ± 43.30 | 39.74 ± 30.98 |
City | Pollutant Species (Annually Average ± SD) | ||||||
---|---|---|---|---|---|---|---|
AQI | SO2 | NO2 | CO | O3 | PM10 | PM2.5 | |
Changji | 99.60 ± 52.76 | 12.42 ± 7.48 | 38.48 ± 13.53 | 1.09 ± 0.62 | 84.89 ± 32.25 | 99.10 ± 64.46 | 58.19 ± 53.01 |
Shihezi | 102.62 ± 53.98 | 11.57 ± 3.66 | 36.36 ± 13.87 | 0.95 ± 0.52 | 88.23 ± 35.63 | 97.89 ± 62.14 | 58.68 ± 55.31 |
Urumqi | 93.08 ± 43.28 | 9.57 ± 3.81 | 41.12 ± 15.25 | 1.07 ± 0.62 | 79.12 ± 32.36 | 92.78 ± 44.12 | 51.55 ± 45.79 |
City | Air Mass Type | Frequency% | ρ */(μg m−3) | ρ */(μg m−3) | ||||
---|---|---|---|---|---|---|---|---|
PM2.5 | Stdev | Num | PM10 | Stdev | Num | |||
Changji | 1 | 60.07 | 170.32 | 64.41 | 499 | 226.06 | 94.38 | 554 |
2 | 20.06 | 155.67 | 66.86 | 144 | 193.83 | 9395 | 168 | |
3 | 18.75 | 161.53 | 66.05 | 158 | 201.83 | 90.61 | 175 | |
4 | 1.12 | 176.44 | 62.72 | 9 | 304.90 | 273.33 | 10 | |
Shihezi | 1 | 21.08 | 176.94 | 68.44 | 285 | 210.88 | 89.74 | 304 |
2 | 36.01 | 194.81 | 79.43 | 210 | 227.07 | 106.04 | 230 | |
3 | 10.73 | 180.11 | 78.65 | 98 | 212.57 | 109.79 | 106 | |
4 | 16.23 | 140.50 | 5564 | 8 | 319.90 | 334.52 | 10 | |
5 | 15.95 | 172.71 | 65.78 | 224 | 201.37 | 84.85 | 252 | |
Urumqi | 1 | 38.62 | 152.37 | 51.75 | 301 | 157.40 | 57.31 | 305 |
2 | 16.88 | 131.84 | 40.17 | 104 | 137.03 | 43.25 | 98 | |
3 | 33.40 | 136.04 | 42.42 | 247 | 156.33 | 59.53 | 260 | |
4 | 11.10 | 145.89 | 53.76 | 66 | 153.94 | 73.13 | 66 |
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Chen, Z.; Li, Z.; Xu, L.; Zhou, X.; Zhang, X.; Wang, F.; Luo, Y. Gaseous and Particulate Pollution in the Wu-Chang-Shi Urban Agglomeration on the Northern Slope of Tianshan Mountains from 2017 to 2021. Atmosphere 2023, 14, 91. https://doi.org/10.3390/atmos14010091
Chen Z, Li Z, Xu L, Zhou X, Zhang X, Wang F, Luo Y. Gaseous and Particulate Pollution in the Wu-Chang-Shi Urban Agglomeration on the Northern Slope of Tianshan Mountains from 2017 to 2021. Atmosphere. 2023; 14(1):91. https://doi.org/10.3390/atmos14010091
Chicago/Turabian StyleChen, Zhi, Zhongqin Li, Liping Xu, Xi Zhou, Xin Zhang, Fanglong Wang, and Yutian Luo. 2023. "Gaseous and Particulate Pollution in the Wu-Chang-Shi Urban Agglomeration on the Northern Slope of Tianshan Mountains from 2017 to 2021" Atmosphere 14, no. 1: 91. https://doi.org/10.3390/atmos14010091