Particle composition, sources and evolution during the COVID-19 lockdown period in Chengdu, southwest China: Insights from single particle aerosol mass spectrometer data

Zhang, Junke; Li, Huan; Chen, Luyao; Huang, Xiaojuan; Zhang, Wei; Zhao, Rui

doi:10.1016/j.atmosenv.2021.118844

Cited by 12 publications

(6 citation statements)

References 63 publications

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“…Combined with previous studies, the year-on-year declines in PM 2.5 and PM 10 observed in this study are mainly due to strict air quality control policies and other measures [82,108,130]. However, the mean value of the PM 2.5 /PM 10 ratio in Chengdu ranged from 0.6 to 0.65 (Fig.…”

Section: Pm 25 /Pm 10 Ratiosupporting

confidence: 77%

“…Chengdu is located in southwest China (30.08 • ~31.43 • N, 102.9 • ~104.88 • E), in the hinterland of the Chengdu Plain, with a total area of 14,335 km 2 and an average altitude of 500 meters [80][81][82]. It is the capital city of Sichuan province as well as one of the largest cities in Western China and is encircled by the Longquan Mountains to the east and the Qionglai Mountains to the west [53,[80][81][82][83][84]. The city has a total of 20 county-level administrative districts, including the central urban area and the main urban area [80][81][82].…”

Section: Study Areamentioning

confidence: 99%

“…It is the capital city of Sichuan province as well as one of the largest cities in Western China and is encircled by the Longquan Mountains to the east and the Qionglai Mountains to the west [53,[80][81][82][83][84]. The city has a total of 20 county-level administrative districts, including the central urban area and the main urban area [80][81][82]. In addition, the terrain of this area is high in the west and low in the east, with a height difference of 4,966 meters, and the terrain is relatively closed [41,56,58,75].…”

Section: Study Areamentioning

confidence: 99%

“…The main reason is that due to the impact of the COVID-19 epidemic in 2020, most cities in China adopted lockdown measures, resulting in a reduction in NO x emissions from industry and transportation [141,[148][149][150]. Zhang et al [82] found that NO 2 concentrations Overall, the gradual increase in the NO 2 /SO 2 ratio also indicates that mobile sources of pollution such as vehicle exhaust emissions have a higher contribution than stationary sources such as coal combustion, power generation, and industrial production [18]. In addition, the NO 2 /SO 2 ratio showed an increasing trend in each season (Fig.…”

Section: No 2 /So 2 Ratiomentioning

confidence: 99%

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Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Li,

Abdullah,

Sobri

et al. 2023

Environmental Engineering Research

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The air pollution process and impact mechanism of megacities located in complex terrain are particularly complex. As a typical megacity in China, Chengdu has unique topographical and meteorological conditions, and its pollution control is difficult. This study systematically elucidated the variation characteristics of six criteria air pollutants in Chengdu between 2014 and 2020. Besides, the PM2.5/PM10 and NO2/SO2 ratios were discussed. Furthermore, a detailed analysis of the correlation between air pollutants was carried out. Finally, the collaborative path of carbon reduction and air pollution control is discussed. The results indicated that SO2, PM2.5, PM10 and CO were significantly decreased by 62.9%, 50.8%, 45.5%, and 36.7%, respectively. PM2.5 and O3 compliance rates are very low, and O3 increases with fluctuations. SO2, NO2, CO, PM showed a “U-shaped” seasonal variation, and there was a “seesaw” phenomenon between O3 and PM2.5. The continuous changing trends also found in the ratios of PM2.5/PM10 and NO2/SO2. The results highlight the importance of coordinated reduction of carbon emissions and pollutants in Chengdu. This research can improve the prediction accuracy of air pollution in complex terrain areas under global warming, and improve the understanding of the formation mechanism of air pollution in special terrains around the world.

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Section: Pm 25 /Pm 10 Ratiosupporting

confidence: 77%

Section: Study Areamentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

Section: No 2 /So 2 Ratiomentioning

confidence: 99%

See 2 more Smart Citations

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Li,

Abdullah,

Sobri

et al. 2023

Environmental Engineering Research

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show abstract

“…Lockdown, on the other hand, dramatically improves air quality ( Bhatti et al, 2022 ). According to a Chinese study ( Zhang et al, 2022 ), the concentration of air pollutants reduced by 5 to 24 percent during the lockdown, with the decline reaching 40 percent in megacities. Another study of megacities found that lockout reduces PM2.5 concentrations by 20 to 60 percent ( Rodríguez-Urrego & Rodríguez-Urrego, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 lockdown on air quality analyzed through machine learning techniques

Zukaib

Maray

Mustafa

et al. 2023

PeerJ Computer Science

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After February 2020, the majority of the world’s governments decided to implement a lockdown in order to limit the spread of the deadly COVID-19 virus. This restriction improved air quality by reducing emissions of particular atmospheric pollutants from industrial and vehicular traffic. In this study, we look at how the COVID-19 shutdown influenced the air quality in Lahore, Pakistan. HAC Agri Limited, Dawn Food Head Office, Phase 8-DHA, and Zeenat Block in Lahore were chosen to give historical data on the concentrations of many pollutants, including PM2.5, PM10 (particulate matter), NO2 (nitrogen dioxide), and O3 (ozone). We use a variety of models, including decision tree, SVR, random forest, ARIMA, CNN, N-BEATS, and LSTM, to compare and forecast air quality. Using machine learning methods, we looked at how each pollutant’s levels changed during the lockdown. It has been shown that LSTM estimates the amounts of each pollutant during the lockout more precisely than other models. The results show that during the lockdown, the concentration of atmospheric pollutants decreased, and the air quality index improved by around 20%. The results also show a 42% drop in PM2.5 concentration, a 72% drop in PM10 concentration, a 29% drop in NO2 concentration, and an increase of 20% in O3 concentration. The machine learning models are assessed using the RMSE, MAE, and R-SQUARE values. The LSTM measures NO2 at 4.35%, O3 at 8.2%, PM2.5 at 4.46%, and PM10 at 8.58% in terms of MAE. It is observed that the LSTM model outperformed with the fewest errors when the projected values are compared with the actual values.

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Characterization of carbonaceous particles by single particle aerosol mass spectrometer in the urban area of Chengdu, China

Zhang,

Wang,

Chen

et al. 2024

Environ Sci Pollut Res

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Particle composition, sources and evolution during the COVID-19 lockdown period in Chengdu, southwest China: Insights from single particle aerosol mass spectrometer data

Cited by 12 publications

References 63 publications

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

Impact of COVID-19 lockdown on air quality analyzed through machine learning techniques

Characterization of carbonaceous particles by single particle aerosol mass spectrometer in the urban area of Chengdu, China

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