Sources of PM2.5 and its responses to emission reduction strategies in the Central Plains Economic Region in China: Implications for the impacts of COVID-19

Environmental Pollution, Год журнала: 2021, Номер 288, С. 117783 - 117783

Опубликована: Июль 16, 2021

The Central Plains Economic Region (CPER) located along the transport path to Beijing-Tianjin-Hebei area has experienced severe PM2.5 pollution in recent years. However, few modeling studies have been performed on sources of PM2.5, especially impacts emission reduction strategies. In this study, Nested Air Quality Prediction Model System (NAQPMS) with an online tracer-tagging module was adopted investigate source sectors and a series sensitivity tests were conducted different sector-based mitigation strategies pollution. response surfaces pollutants changes built. results showed that resident-related sector (resident agriculture), fugitive dust, traffic industry emissions main Zhengzhou, contributing 49%, 19%, 15% 13%, respectively. Response Henan revealed combined efficiently decreased Zhengzhou. reduced only region barely satisfied national air quality standard 75 μg/m3, whereas 50%–60% over whole could reach goal. On severely polluted days, even 60% these two insufficient satisfy μg/m3. Moreover, resulted increase O3 concentration. surface method Zhengzhou by 19% COVID-19 lockdown, which approached observed 21%, indicating be employed study lockdown This provides scientific reference for formulation CPER.

Язык: Английский

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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

Atmospheric Environment, Год журнала: 2021, Номер 268, С. 118844 - 118844

Опубликована: Ноя. 9, 2021

Язык: Английский

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Airflow deflectors of external windowsto induce ventilation: Towards COVID-19 prevention and control

Sustainable Cities and Society, Год журнала: 2021, Номер 77, С. 103548 - 103548

Опубликована: Ноя. 18, 2021

Язык: Английский

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Meteorology-normalized variations of air quality during the COVID-19 lockdown in three Chinese megacities

Atmospheric Pollution Research, Год журнала: 2022, Номер 13(6), С. 101452 - 101452

Опубликована: Май 14, 2022

Язык: Английский

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Air Quality Index (AQI) Did Not Improve during the COVID-19 Lockdown in Shanghai, China, in 2022, Based on Ground and TROPOMI Observations

Remote Sensing, Год журнала: 2023, Номер 15(5), С. 1295 - 1295

Опубликована: Фев. 26, 2023

The lockdowns from the coronavirus disease of 2019 (COVID-19) have led to a reduction in anthropogenic activities and hence reduced primary air pollutant emissions, which were reported helped quality improvements. However, expressed by index (AQI) did not improve Shanghai, China, during COVID-19 outbreak spring 2022. To better understand reason, we investigated variations nitrogen dioxide (NO2), ozone (O3), PM2.5 (particular matter with an aerodynamic diameter less than 2.5 μm), PM10 10 μm) using situ satellite measurements 1 March 31 June 2022 (pre-, full-, partial-, post-lockdown periods). results show that benefit significantly decreased ground-level PM2.5, PM10, NO2 was offset amplified O3 pollution, therefore leading increased AQI. According backward trajectory analyses multiple linear regression (MLR) model, emissions dominated observed changes pollutants full-lockdown period relative previous years (2019–2021), whereas long-range transport local meteorological parameters (temperature, pressure, wind speed, humidity, precipitation) influenced little. We further identified chemical mechanism caused increase concentration. pollution oxides (NOx) under VOC-limited regime high background concentrations owing seasonal variations. In addition, found downtown area, more sensitively responded lockdown measures they suburbs. These findings provide new insights into impact emission control restrictions on implications for future.

Язык: Английский

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Characterizing vertical distribution patterns of PM2.5 in low troposphere of Shanghai city, China: Implications from the perspective of unmanned aerial vehicle observations

Atmospheric Environment, Год журнала: 2021, Номер 265, С. 118724 - 118724

Опубликована: Сен. 14, 2021

Язык: Английский

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Assessing the effects of short-term traffic restriction policies on traffic-related air pollutants

The Science of The Total Environment, Год журнала: 2023, Номер 867, С. 161451 - 161451

Опубликована: Янв. 5, 2023

Язык: Английский

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Spatio-temporal analysis of air pollution dynamics over Bangalore city during second wave of COVID-19

Natural Hazards Research, Год журнала: 2024, Номер 4(3), С. 401 - 412

Опубликована: Сен. 1, 2024

The country wide lockdown implemented during 27th April to 14th June 2021 in order prevent the spread of COVID-19 second wave India. Effect restricted resulted improved air quality. This study focuses on analyzing spatio-temporal distribution analysis major pollutant concentration over Bangalore city inverse distance weighting (IDW) method is for spatial quantify concentrations at each location Urban Bangalore. research considers distinct periods pre-lockdown and pandemic investigate impact reduced human activities quality city. mainly utilizes pollution data collected from Central Pollution Control Board (CPCB) monitoring stations across Bangalore, including measurements pollutants such as PM2.5, PM10, O3, NO2, SO2, CO. IDW create high-resolution maps both periods. provides valuable insights into variations levels though out comparative reveals significant changes between two periods; similarly, temporal weekly average also witnessed negative anomalies weeks. results indicate substantial reductions lockdown, attributed decreased vehicular emissions, industrial activities, construction operations. period serves a baseline assessing improvements lockdown. modeling approach enhances our understanding patterns metropolitan findings underscore potential benefits implementing sustainable strategies maintain even after subsides.

Язык: Английский

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Impact of COVID-19 lockdown on NO2 and PM2.5 exposure inequalities in London, UK

Environmental Research, Год журнала: 2021, Номер 198, С. 111236 - 111236

Опубликована: Май 4, 2021

Язык: Английский

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Changes in air pollutants during the COVID-19 lockdown in Beijing: Insights from a machine-learning technique and implications for future control policy

Atmospheric and Oceanic Science Letters, Год журнала: 2021, Номер 14(4), С. 100060 - 100060

Опубликована: Апрель 30, 2021

The COVID-19 lockdowns led to abrupt reductions in human-related emissions worldwide and had an unintended impact on air quality improvement. However, quantifying this is difficult as meteorological conditions may mask the real effect of changes observed concentrations pollutants. Based data at 35 sites Beijing from 2015 2020, a machine learning technique was applied decouple impacts meteorology results showed that ("deweathered") pollutants (expect for O3) dropped significantly due lockdown measures. Compared with scenario without (predicted concentrations), values PM2.5, PM10, SO2, NO2, CO during decreased by 39.4%, 50.1%, 51.8%, 43.1%, 35.1%, respectively. In addition, significant decline NO2 found background (51% 37.8%) rather than traffic (37.1% 35.5%), which different common belief. While primary reduced period, episodic haze events still occurred unfavorable conditions. Thus, developing optimized strategy tackle pollution essential future. 摘要 基于2015–2020年北京35个环境空气站和20个气象站观测资料, 应用机器学习方法 (随机森林算法) 分离了气象条件和源排放对大气污染物浓度的影响. 结果发现, 为应对疫情采取的隔离措施使北京2020年春节期间大气污染物浓度降低了35.1%–51.8%; 其中, 背景站氮氧化物和一氧化碳浓度的降幅最大, 超过了以往报道较多的交通站点. 同时, 2020年春节期间的气象条件不利于污染物扩散, 导致多次霾污染事件发生.为进一步改善北京空气质量, 未来需要优化减排策略.

Язык: Английский

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