Pollution Remediation by Urban Forests: PM2.5 Reduction in Beijing, China

Chen, Bin; Lu, Shengyong; Zhao, Yao; Li, Shaoning; Yang, Xiu‐Qun; Wang, Bing; Zhang, Hong-Jiang

doi:10.15244/pjoes/63208

Cited by 13 publications

(6 citation statements)

References 24 publications

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“…However, PM2.5 and PM10 have increased partially compared to 2018, which is consistent with the results in Section 3.1.1. Overall, all pollutants' daily trends during the lockdown period were "double-peaked and double-valleyed" type during the lockdown period of 2017-2020, except for ozone, which was "single-peaked", and similar results were obtained in other studies (Chen et al, 2016). From Fig.…”

Section: Comparison Of Hourly Mean Pollutant Concentrationssupporting

confidence: 86%

Analysis of Air Quality Changes and Influencing Factors in Changchun during the COVID-19 Pandemic in 2020

Gao

et al. 2021

Aerosol Air Qual. Res.

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To study the air quality changes during the Corona Virus Disease 2019 (COVID-19) lockdown in Changchun, we analyzed the changes in pollution of six major pollutants (PM2.5, PM10, SO2, NO2, O3, CO) and correlated them with meteorological parameters, using meteorological data and pollutants concentration data. Regional transport pathways and potential source areas of pollutants were analyzed using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). The results showed that the concentrations of PM2.5, PM10, SO2, NO2, CO were 30.5%-53.8% lower in the Level I period and 49.4%-65.0% lower in the Level II period than in the Pre-lockdown period, respectively.Conversely, O3 increased 59.6% and 58.1% during Level I and Level II, respectively, compared to the Pre-lockdown period. During the 55-day lockdown, daily average concentrations of each pollutant were lower than in previous years on 36-55 days, while O3 was higher on 35 days. The pollutants that decreased in concentration during the lockdown also showed an increase during the Level III period (up to 188.5%). The maximum daily growth rate of PM2.5 during the lockdown period in 2020 was 16.0%, which was higher than this value in the same period of previous years (21.8%, 21.4%, 17.4%). This shows that the change trend of pollutants during the lockdown period is smoother than in previous years. Temperature and O3 were positively correlated before the lockdown and during Level Ⅰ and weakly negatively correlated during Level Ⅱ and Level Ⅲ.Despite the prevalence of northwest winds in winter, a high percentage of trajectories from other directions (up to 36.8%) was observed during the lockdown. Simultaneously, the lockdown reduced the potential source area for PM2.5 (WPSCF≥0.000007), but rebounded after the lockdown was lifted. In conclusion, the lockdown only temporarily reduced the air pollution in Changchun.

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Section: Comparison Of Hourly Mean Pollutant Concentrationssupporting

confidence: 86%

Analysis of Air Quality Changes and Influencing Factors in Changchun during the COVID-19 Pandemic in 2020

Gao

et al. 2021

Aerosol Air Qual. Res.

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“…Plant level study [10][11][12][13][31][32][33][35][36][37][38][39][40][41][42][43][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59]65,69,73] Local scale [14][15][16][17]19,[21][22][23][24][26][27][28][29]34,44,63,75,76] Neighbourhood scale [18,…”

Section: Scale Referencementioning

confidence: 99%

Urban Vegetation in Air Quality Management: A Review and Policy Framework

2020

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Recent episodes of high air pollution concentration levels in many Polish cities indicate the urgent need for policy change and for the integration of various aspects of urban development into a common platform for local air quality management. In this article, the focus was placed on the prospects of improving urban air quality through proper design and protection of vegetation systems within local spatial planning strategies. Recent studies regarding the mitigation of air pollution by urban greenery due to deposition and aerodynamic effects were reviewed, with special attention given to the design guidelines resulting from these studies and their applicability in the process of urban planning. The conclusions drawn from the review were used to conduct three case studies: in Gdańsk, Warsaw, and Poznań, Poland. The existing local urban planning regulations for the management of urban greenery were critically evaluated in relation to the findings of the review. The results indicate that the current knowledge regarding the improvement of urban air quality by vegetation is not applied in the process of urban planning to a sufficient degree. Some recommendations for alternative provisions were discussed.

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“…However, studies examining the degree to which urban forests trap particulates, combined with data from forest management planning inventories (FMPI), remote sensing imagery, population density, and impervious surface percentages, are rare. These types of environmental data could be extremely helpful for managing urban forests and improving air quality [6]. Focusing on urban forests is important because urban forests help protect human health and improve environmental quality by improving air quality (e.g., forests absorb pollutants and reduce chemical reaction rates [7,8]).…”

Section: Introductionmentioning

confidence: 99%

Individual and Interactive Influences of Anthropogenic and Ecological Factors on Forest PM2.5 Concentrations at an Urban Scale

et al. 2018

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Abstract:Integration of Landsat images and multisource data using spatial statistical analysis and geographical detector models can reveal the individual and interactive influences of anthropogenic activities and ecological factors on concentrations of atmospheric particulate matter less than 2.5 microns in diameter (PM 2.5 ). This approach has been used in many studies to estimate biomass and forest disturbance patterns and to monitor carbon sinks. However, the approach has rarely been used to comprehensively analyze the individual and interactive influences of anthropogenic factors (e.g., population density, impervious surface percentage) and ecological factors (e.g., canopy density, stand age, and elevation) on PM 2.5 concentrations. To do this, we used Landsat-8 images and meteorological data to retrieve quantitative data on the concentrations of particulates (PM 2.5 ), then integrated a forest management planning inventory (FMPI), population density distribution data, meteorological data, and topographic data in a Geographic Information System database, and applied a spatial statistical analysis model to identify aggregated areas (hot spots and cold spots) of particulates in the urban area of Jinjiang city, China. A geographical detector model was used to analyze the individual and interactive influences of anthropogenic and ecological factors on PM 2.5 concentrations. We found that particulate concentration hot spots are mainly distributed in urban centers and suburbs, while cold spots are mainly distributed in the suburbs and exurban region. Elevation was the dominant individual factor affecting PM 2.5 concentrations, followed by dominant tree species and meteorological factors. A combination of human activities (e.g., population density, impervious surface percentage) and multiple ecological factors caused the dominant interactive effects, resulting in increased PM 2.5 concentrations. Our study suggests that human activities and multiple ecological factors effect PM 2.5 concentrations both individually and interactively. We conclude that in order to reveal the direct and indirect effects of human activities and multiple factors on PM 2.5 concentrations in urban forests, quantification of fusion satellite data and spatial statistical methods should be conducted in urban areas.

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Pollution Remediation by Urban Forests: PM2.5 Reduction in Beijing, China

Abstract: We based our research on real-time monitoring data for PM 2

Cited by 13 publications

References 24 publications

Analysis of Air Quality Changes and Influencing Factors in Changchun during the COVID-19 Pandemic in 2020

Analysis of Air Quality Changes and Influencing Factors in Changchun during the COVID-19 Pandemic in 2020

Urban Vegetation in Air Quality Management: A Review and Policy Framework

Individual and Interactive Influences of Anthropogenic and Ecological Factors on Forest PM2.5 Concentrations at an Urban Scale

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