Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing–Tianjin–Hebei Region
Abstract
:1. Introduction
2. Methodology
2.1. Study Area and Modeling Domains
2.2. Model Configuration and Input Data
2.3. Model Evaluation
3. Results and Discussion
3.1. Impact of Inter-Annual Meteorological Variation on PM2.5 Concentration in Beijing–Tianjin–Hebei Region
3.2. Average Transport of PM2.5 among Cities in the BTH Region from 2010 to 2019
3.3. Impact of Inter-Annual Meteorological Variation on the Contribution of Regional Transport in the BTH Region
4. Conclusions
- (1)
- Inter-annual variation in meteorological conditions has an impact on both PM2.5 concentration and inter-city transport in the Beijing–Tianjin–Hebei (BTH) region.
- (2)
- The results show that the 10-year average PM2.5 concentration in 13 cities ranged from 30.1 μg/m3 to 134.4 μg/m3, showing a strong spatial inhomogeneity distribution. The highest PM2.5 concentration was found in Baoding (134.4 μg/m3), and the cities located in the southern part of the study area.
- (3)
- The simulated annual average concentrations in 13 cities in BTH are highly variable, with fluctuations ranging from 30.8% to 54.1%, and more evident variations were found in seasonal results, with winter having the most significant inter-annual variation.
- (4)
- Seven out of thirteen cities have a contribution from regional transport exceeding 50%, which are located in the eastern half of the Beijing–Tianjin–Hebei region, while the western half is dominated by local contributions.
- (5)
- The magnitude of the regional transport contribution varies significantly among the cities of BTH, on an annual basis, from a minimum inter-annual fluctuation of 8.9% to a maximum of 37.2%, and seasonal fluctuation is even more strongly evident.
- (6)
- Both in terms of concentration and regional contribution, values above and below the historical average in different seasons often cancel each other out, causing the annual average to be close to the historical average.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameters | Month | MB 1 | MAE 2 | NMB 3 (%) | NME 4 (%) | R 5 |
---|---|---|---|---|---|---|
T2 (Temperature at 2 m) unit: °C | January | 0.93 | 1.63 | 6.23 | 3.37 | 0.87 |
April | 1.67 | 2.83 | 10.70 | 17.93 | 0.83 | |
July | 4.37 | 4.67 | 16.50 | 17.43 | 0.83 | |
October | 2.33 | 3.03 | 17.53 | 22.10 | 0.90 | |
RH2 (Relative humidity at 2 m) unit: % | January | −6.67 | 13.60 | −12.73 | 24.60 | 0.80 |
April | −6.83 | 11.13 | −13.60 | 24.33 | 0.73 | |
July | −13.73 | 15.83 | −13.93 | 18.87 | 0.80 | |
October | −12.67 | 17.13 | −18.13 | 24.73 | 0.77 | |
WS10 (Wind speed at 10 m) unit: m/s | January | 0.07 | 0.70 | −3.20 | 30.43 | 0.70 |
April | 0.23 | 0.50 | 15.50 | 32.53 | 0.70 | |
July | 0.47 | 0.63 | 15.57 | 29.90 | 0.70 | |
October | 0.27 | 0.50 | 17.40 | 32.97 | 0.70 |
Species | Month | NMB (%) | NME (%) | MFB 6 (%) | MFE 7 (%) | R |
---|---|---|---|---|---|---|
January | −9.41 | 19.54 | −6.59 | 10.25 | 0.79 | |
PM2.5 | April | −7.99 | 16.01 | −5.61 | 10.49 | 0.83 |
(μg/m3) | July | 1.10 | 21.07 | −5.30 | 11.97 | 0.83 |
October | −9.58 | 18.12 | −5.57 | 8.31 | 0.89 |
Year | BJ | TJ | HD | XT | HS | SJZ | CZ | LF | BD | TS | QHD | CD | ZJK |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2010 | 87.1 | 91.1 | 135.7 | 115.0 | 109.4 | 141.0 | 110.6 | 103.4 | 138.6 | 98.0 | 61.5 | 57.5 | 29.8 |
2011 | 75.4 | 83.8 | 120.5 | 106.5 | 98.0 | 125.5 | 90.3 | 92.1 | 121.2 | 79.2 | 56.1 | 47.5 | 27.7 |
2012 | 75.5 | 76.4 | 120.8 | 100.0 | 89.5 | 126.2 | 84.9 | 82.8 | 131.8 | 81.3 | 54.4 | 47.9 | 26.9 |
2013 | 103.4 | 99.1 | 149.3 | 127.0 | 119.5 | 161.1 | 121.8 | 118.0 | 169.1 | 102.0 | 67.2 | 53.0 | 33.6 |
2014 | 92.4 | 95.5 | 125.6 | 111.7 | 98.8 | 133.5 | 104.4 | 107.5 | 149.5 | 104.3 | 72.5 | 62.8 | 35.3 |
2015 | 78.1 | 86.9 | 115.1 | 96.7 | 91.5 | 122.3 | 91.8 | 93.1 | 128.9 | 95.6 | 65.1 | 50.5 | 33.3 |
2016 | 71.1 | 73.8 | 116.3 | 100.9 | 87.4 | 121.2 | 76.0 | 79.1 | 128.8 | 78.1 | 52.6 | 47.7 | 28.6 |
2017 | 99.1 | 97.9 | 121.8 | 101.3 | 98.4 | 122.8 | 97.8 | 105.5 | 137.4 | 108.8 | 72.3 | 64.0 | 34.6 |
2018 | 94.8 | 111.3 | 104.8 | 88.7 | 83.7 | 113.5 | 92.0 | 101.2 | 112.0 | 116.5 | 87.8 | 53.0 | 23.4 |
2019 | 80.4 | 84.6 | 110.0 | 94.1 | 87.0 | 114.7 | 87.5 | 91.6 | 126.7 | 96.6 | 63.7 | 52.6 | 27.7 |
Average | 85.7 | 90.0 | 122.0 | 104.2 | 96.3 | 128.2 | 95.7 | 97.4 | 134.4 | 96.0 | 65.3 | 53.6 | 30.1 |
Fluctuation (%) | 37.7 | 41.6 | 49.5 | 36.8 | 37.2 | 54.1 | 47.9 | 39.9 | 52.8 | 40.0 | 53.9 | 30.8 | 39.6 |
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Chen, D.; Jin, X.; Fu, X.; Xia, L.; Guo, X.; Lang, J.; Zhou, Y.; Wei, W. Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing–Tianjin–Hebei Region. Sustainability 2022, 14, 6210. https://doi.org/10.3390/su14106210
Chen D, Jin X, Fu X, Xia L, Guo X, Lang J, Zhou Y, Wei W. Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing–Tianjin–Hebei Region. Sustainability. 2022; 14(10):6210. https://doi.org/10.3390/su14106210
Chicago/Turabian StyleChen, Dongsheng, Xin Jin, Xinyi Fu, Lin Xia, Xiurui Guo, Jianlei Lang, Ying Zhou, and Wei Wei. 2022. "Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing–Tianjin–Hebei Region" Sustainability 14, no. 10: 6210. https://doi.org/10.3390/su14106210