Quantitative estimation of meteorological impacts and the COVID-19 lockdown reductions on NO2 and PM2.5 over the Beijing area using Generalized Additive Models (GAM)

Hua, Jian; Zhang, Yuanxun; Foy, B. de; Shang, Jing; Schauer, James J.; Mei, Xiaodong; Sulaymon, Ishaq Dimeji; Han, Tingting

doi:10.1016/j.jenvman.2021.112676

Cited by 59 publications

(29 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Higher scores indicate places with higher concentrations of NO 2 , lower precipitations and relative humidity. These results also reaffirm the seasonal factor of NO 2 concentrations, which are mainly related to humid climatic conditions (Hua et al 2021 ). The scores are higher from July through August, the driest months of the year.…”

Section: Resultssupporting

confidence: 81%

Spatio-temporal variations of tropospheric nitrogen dioxide in South Mato Grosso based on remote sensing by satellite

Souza

Aristone

Abreu

et al. 2022

Meteorol Atmos Phys

View full text Add to dashboard Cite

The study evaluates the characteristics of tropospheric nitrogen dioxide (NO 2 ) concentrations from 2005 to 2020 in eight cities in the State of Mato Grosso do Sul (MS), Midwestern Brazil, using data available from the Ozone Monitoring Instrument (OMI). The average concentration varies from 2981 × 10 15 molecules/cm 2 in Campo Grande, where commercial, industrial and vehicular activities take place, to 2906 × 10 15 molecules/cm 2 in Corumbá and 3035 × 10 15 molecules/cm 2 in Porto Murtinho, regions of livestock and biomass burning. The results, based on the Mann–Kendall (MK) test, show a significant increase ( p < 0.05) in the NO 2 column levels in the region. For each of the eight cities studied, a significant seasonal cycle of NO 2 columns was determined. The maximum value of NO 2 concentration was observed in the dry period, from July to September, while the minimum value was registered in the rainy period, from October to March. Supplementary Information The online version contains supplementary material available at 10.1007/s00703-021-00855-5.

show abstract

Section: Resultssupporting

confidence: 81%

Spatio-temporal variations of tropospheric nitrogen dioxide in South Mato Grosso based on remote sensing by satellite

Souza

Aristone

Abreu

et al. 2022

Meteorol Atmos Phys

View full text Add to dashboard Cite

show abstract

“…In fact, it was due to the fact that the sources of NO 2 output behavior is closely related to human activities, especially traffic activities. NO 2 is one of the most concerned pollutants that are dominantly emitted by transportation ( Hua et al, 2021 ). Beijing Municipal Ecology and Environment Bureau announced that motor vehicles were responsible for up to 86% of all nitrogen oxides emissions in 2019.…”

Section: Resultsmentioning

confidence: 99%

“…At the start of pandemic, poor diffusion conditions were dominated by extreme meteorological variation comprising low boundary layer height, stagnant airflow and high relative humidity in February 2020 ( Le et al, 2020 ; Sun et al, 2020 ). After April, favorable diffusion conditions came and frequent southern winds facilitated NO 2 output from the south ( Hua et al, 2021 ), which could explain the few increase of output performance in some areas. But relatively poor diffusion conditions in May were received by Beijing again ( Hua et al, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

“…After April, favorable diffusion conditions came and frequent southern winds facilitated NO 2 output from the south ( Hua et al, 2021 ), which could explain the few increase of output performance in some areas. But relatively poor diffusion conditions in May were received by Beijing again ( Hua et al, 2021 ). In terms of the overall period from February 1 to May 31 in 2020, the complex meteorological variation promoted output performance in some areas compared to that in normal year.…”

Section: Resultsmentioning

confidence: 99%

“…Meteorology plays an important role in the formation, transportation, and diffusion processes of air pollutants ( Hua et al, 2021 ). To understand following results potentially explained by meteorology conditions in this study, we calculated the T-test for corresponding meteorological parameters by two hourly samples before exploring the impact of COVID-19 on diffusion.…”

Section: Study Area and Data Descriptionmentioning

confidence: 99%

See 2 more Smart Citations

Spatiotemporal evolution of NO2 diffusion in Beijing in response to COVID-19 lockdown using complex network

Zhang

Yang

et al. 2022

Chemosphere

View full text Add to dashboard Cite

The COVID-19 pandemic and the corresponding lockdown measures have been confirmed to reduce the air pollution in major megacities worldwide. Especially at some monitoring hotspots, NO 2 has been verified to show a significant decrease. However, the diffusion pattern of these hotspots in responding to COVID-19 is not clearly understood at present stage. Hence, we selected Beijing, a typical megacity with the strictest lockdown measures during COVID-19 period, as the studied city and attempted to discover the NO 2 diffusion process through complex network method. The improved metrics derived from the topological structure of the network were adopted to describe the performance of diffusion. Primarily, we found evidences that COVID-19 had significant effects on the spatial diffusion distribution due to combined effect of changed human activities and meteorological conditions. Besides, to further quantify the impacts of disturbance caused by different lockdown measures, we discussed the evolutionary diffusion patterns from lockdown period to recovery period. The results displayed that the difference between normal operation and pandemic operation firstly increased at the cutoff of lockdown measures but then declined after the implement of recovery measures. The source areas had greater vulnerability and lower resilience than receptors areas. Furthermore, based on the conclusion that the diffusion pattern changed during different periods, we explored the key stations on the path of diffusion process to further gain information. These findings could provide references for comprehending spatiotemporal pattern on city scale, which might be help for high-resolution air pollution mapping and prediction.

show abstract

Probabilistic Transport-Induced Emissions and Health Risks for Adelaide, South Australia

Iqbal,

Rahman

2024

Environ Model Assess

View full text Add to dashboard Cite

The research aims to assess the risks associated with the transport-induced emissions (major criteria pollutants) in Adelaide, South Australia. A stochastic emission modelling strategy was implemented for a probabilistic risk assessment of the transport system for current and future scenarios, by analysing the road specific transport system data. The simulated result suggests that NOx and PM2.5 risks are significant at about 35% of city areas, especially along the roads with heavy vehicle concentration and higher traffic. The risk will significantly increase in 10 years if the current practice persists, demonstrating a high probability (more than 60%) of emissions above 150% of the air quality standard. The research suggests that appropriate planning is necessary to cope with the development needs for the system’s future sustainability.

show abstract

Quantitative estimation of meteorological impacts and the COVID-19 lockdown reductions on NO2 and PM2.5 over the Beijing area using Generalized Additive Models (GAM)

Cited by 59 publications

References 56 publications

Spatio-temporal variations of tropospheric nitrogen dioxide in South Mato Grosso based on remote sensing by satellite

Spatio-temporal variations of tropospheric nitrogen dioxide in South Mato Grosso based on remote sensing by satellite

Spatiotemporal evolution of NO2 diffusion in Beijing in response to COVID-19 lockdown using complex network

Probabilistic Transport-Induced Emissions and Health Risks for Adelaide, South Australia

Contact Info

Product

Resources

About