Peer Review #1 of "Impact of COVID-19 lockdown on air quality analyzed through machine learning techniques (v0.1)" DOI Creative Commons

P Mukherji

Published: March 31, 2023

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

Language: Английский

Characterization and source apportionment for light absorption amplification of black carbon at an urban site in eastern China DOI
Dong Chen, Wenxin Zhao, Lei Zhang

et al.

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 865, P. 161180 - 161180

Published: Dec. 27, 2022

Language: Английский

Citations

3
Characteristics of air pollution variation and potential source contributions of typical megacities in the Sichuan Basin, Southwest China DOI

Xiaoju Li,

Luqman Chuah Abdullah, Shafreeza Sobri

et al.

Air Quality Atmosphere & Health, Journal Year: 2023, Volume and Issue: 17(3), P. 641 - 660

Published: Nov. 30, 2023

Language: Английский

Citations

1
Characterization of carbonaceous particles by single particle aerosol mass spectrometer in the urban area of Chengdu, China DOI
Junke Zhang, Rui Wang, Chunying Chen

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(5), P. 7934 - 7947

Published: Jan. 3, 2024

Language: Английский

Citations

0
Reply on RC2 DOI Creative Commons

Xinlei Ge

Published: March 18, 2024

Abstract. Black carbon-containing (BCc) particles are pervasive in ambient atmosphere. The unexpected outbreak of the COVID-19 pandemic 2021 summer prompted a localized and prolonged lockdown Yangzhou City, situated YRD, China, which provides unique opportunity to gain insights into relationship between emission sources BCc. Satellite ground-level measurements both demonstrated that strict controls effectively reduced local gaseous pollutants. Meanwhile, single particle aerosol mass spectrometer (SPA-MS) analysis showed number fraction freshly emitted BCc decreased 28 % during (LD), with from vehicle emissions experiencing most substantial reduction. However, uncontrolled reductions nitrogen oxides (NOx) volatile organic compounds (VOCs) likely contributed increased ozone (O3) concentrations, oxidizing capacity, may turn enhanced secondary PM2.5 formation compensated primary As result, we did observe slight increase concentration (21.2 μg m-3) LD period compared before (BLD), more aged particles. Reactive trace gases (e.g., NOx, SO2, VOCs) could form thick coatings on pre-existing via heterogeneous hydrolysis under high RH as well, resulting significant growth (~600 nm) period. Furthermore, source apportionment reveals were primarily origin (78 %) normal summertime. coal combustion (23 (21 prominent non-local pollution sources, air originating southeast, along biomass burning (19 northeast, contributing significantly. Our research highlights short-term, not reduce PM pollution, due non-linear responses PM2.5 to its precursors , further effective reduction requires comprehensive extensive approach regionally coordinated balanced control strategy through joint regulation.

Language: Английский

Citations

0
Reply on RC1 DOI Creative Commons
Xinlei Ge

Published: March 18, 2024

Abstract. Black carbon-containing (BCc) particles are pervasive in ambient atmosphere. The unexpected outbreak of the COVID-19 pandemic 2021 summer prompted a localized and prolonged lockdown Yangzhou City, situated YRD, China, which provides unique opportunity to gain insights into relationship between emission sources BCc. Satellite ground-level measurements both demonstrated that strict controls effectively reduced local gaseous pollutants. Meanwhile, single particle aerosol mass spectrometer (SPA-MS) analysis showed number fraction freshly emitted BCc decreased 28 % during (LD), with from vehicle emissions experiencing most substantial reduction. However, uncontrolled reductions nitrogen oxides (NOx) volatile organic compounds (VOCs) likely contributed increased ozone (O3) concentrations, oxidizing capacity, may turn enhanced secondary PM2.5 formation compensated primary As result, we did observe slight increase concentration (21.2 μg m-3) LD period compared before (BLD), more aged particles. Reactive trace gases (e.g., NOx, SO2, VOCs) could form thick coatings on pre-existing via heterogeneous hydrolysis under high RH as well, resulting significant growth (~600 nm) period. Furthermore, source apportionment reveals were primarily origin (78 %) normal summertime. coal combustion (23 (21 prominent non-local pollution sources, air originating southeast, along biomass burning (19 northeast, contributing significantly. Our research highlights short-term, not reduce PM pollution, due non-linear responses PM2.5 to its precursors , further effective reduction requires comprehensive extensive approach regionally coordinated balanced control strategy through joint regulation.

Language: Английский

Citations

0
Reply on RC3 DOI Creative Commons
Xinlei Ge

Published: March 18, 2024

Abstract. Black carbon-containing (BCc) particles are pervasive in ambient atmosphere. The unexpected outbreak of the COVID-19 pandemic 2021 summer prompted a localized and prolonged lockdown Yangzhou City, situated YRD, China, which provides unique opportunity to gain insights into relationship between emission sources BCc. Satellite ground-level measurements both demonstrated that strict controls effectively reduced local gaseous pollutants. Meanwhile, single particle aerosol mass spectrometer (SPA-MS) analysis showed number fraction freshly emitted BCc decreased 28 % during (LD), with from vehicle emissions experiencing most substantial reduction. However, uncontrolled reductions nitrogen oxides (NOx) volatile organic compounds (VOCs) likely contributed increased ozone (O3) concentrations, oxidizing capacity, may turn enhanced secondary PM2.5 formation compensated primary As result, we did observe slight increase concentration (21.2 μg m-3) LD period compared before (BLD), more aged particles. Reactive trace gases (e.g., NOx, SO2, VOCs) could form thick coatings on pre-existing via heterogeneous hydrolysis under high RH as well, resulting significant growth (~600 nm) period. Furthermore, source apportionment reveals were primarily origin (78 %) normal summertime. coal combustion (23 (21 prominent non-local pollution sources, air originating southeast, along biomass burning (19 northeast, contributing significantly. Our research highlights short-term, not reduce PM pollution, due non-linear responses PM2.5 to its precursors , further effective reduction requires comprehensive extensive approach regionally coordinated balanced control strategy through joint regulation.

Language: Английский

Citations

0
Microscopic Characterization of Individual Aerosol Particles in a Typical Industrial City and Its Surrounding Rural Areas in China DOI Creative Commons

Yunfei Su,

Yuhan Long,

Xunzhe Yao

et al.

Toxics, Journal Year: 2024, Volume and Issue: 12(7), P. 525 - 525

Published: July 22, 2024

Transmission electron microscopy was used to analyze individual aerosol particles collected in Lanzhou (urban site) and its surrounding areas (rural early 2023. The results revealed that from the pre-Spring Festival period Spring period, main pollutants at urban site decreased significantly, while PM

Language: Английский

Citations

0
Spatial variation, multi-meteorological factors and potential source analysis of air pollutants in Chengdu megacity of Chengdu-Chongqing economic circle DOI

Xiaoju Li,

Luqman Chuah Abdullah,

Jinzhao Hu

et al.

Air Quality Atmosphere & Health, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 24, 2024

Language: Английский

Citations

0
Algorithm for improving the sizing accuracy in real-time bioaerosol single particle mass spectrometer DOI
Shaoyong Li, Lei-lei Tang, Jingzhen Li

et al.

Journal of Aerosol Science, Journal Year: 2024, Volume and Issue: unknown, P. 106501 - 106501

Published: Dec. 1, 2024

Language: Английский

Citations

0
Peer Review #1 of "Impact of COVID-19 lockdown on air quality analyzed through machine learning techniques (v0.3)" DOI Creative Commons

P Mukherji

Published: March 31, 2023

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

Language: Английский

Citations

0