The Effect of Vegetation Enhancement on Particulate Pollution Reduction: CFD Simulations in an Urban Park

Qin, Hongqiao; Hong, Bo; Jiang, Runsheng; Yan, Shanshan; Zhou, Yunhan

doi:10.3390/f10050373

Cited by 23 publications

(14 citation statements)

References 87 publications

(126 reference statements)

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“…In the case of the control site (H1-1) and the experimental site after the experiment (H1-3), the concentration of fine dust outside the planting zone was higher than that inside. Consistent with the results of this study, several previous studies have demonstrated that the concentration of fine dust inside is lower than that outside of the planting zone [42,43]. However, in the case of the experimental site before the experiment (H1-2), the concentration of fine dust inside the planting zone was higher than that outside.…”

Section: Verification Of Differences In Fine Dust Concentrations Outs...supporting

confidence: 91%

Development and Verification of the Effectiveness of a Fine Dust Reduction Planting Model for Socially Vulnerable Area

Choi

Chon

2021

Sustainability

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Creating a green infrastructure that is effective for reducing fine dust is a significant challenge for urban landscape planners. In this study, a fine dust reduction planting model that can be applied to socially vulnerable area was developed, and its effects were verified. Using PM10, PM2.5, temperature, relative humidity, wind direction, and wind speed measured for approximately one year, the changes in the concentration of fine dust according to the weather conditions were investigated. As a result of the analysis, there was a significant difference in the concentration of fine dust inside and outside the planting zone (p < 0.05). In addition, there is a significant difference between the fine dust reduction effect of the multilayered planting model and the single planting model (p < 0.05). The paper’s main findings are as follows: (1) When the green cover rate is over 50%, the concentration of fine dust is lower than that outside the planting zones. (2) Multilayered planting zones are more effective in reducing the concentration of fine dust than single-structured planting zones. (3) Multilayered planting zones reduce the concentration of fine dust by changing the microclimate. The results of this study can be used as basic data for small urban planting design to reduce fine dust for children’s health in socially vulnerable areas.

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Section: Verification Of Differences In Fine Dust Concentrations Outs...supporting

confidence: 91%

Development and Verification of the Effectiveness of a Fine Dust Reduction Planting Model for Socially Vulnerable Area

Choi

Chon

2021

Sustainability

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“…Table 7 repeats our core analysis separately by city. 18 Since calls are randomly routed to each location, we should not expect to see significant differences by 18 Including worker fixed effects does not meaningfully change the results (Appendix Table A2). Notes: Column 1 presents linear probability models; in columns 2 through 4, the logarithm of the indicated dependent variable is the outcome of interest.…”

Section: Robustness Checksmentioning

confidence: 97%

The Effect of Pollution on Worker Productivity: Evidence from Call Center Workers in China

Chang¹,

Zivin²,

Gross

et al. 2019

American Economic Journal: Applied Economics

287

162

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“…For example, Wang, Yao, Xu, Sun, and Li [25] found an inverted U-shaped relationship between built-up area and PM2.5 levels but lacked in-depth discussions. Qin et al [33] simulated the impact of urban greening on atmospheric particulate matter, and the results showed that reasonable tree cover could reduce PM by 30%. In addition, there are still many deficiencies in this study.…”

Section: Analysis Of Socioeconomic Influence Factorsmentioning

confidence: 99%

Analysis of Spatio-Temporal Heterogeneity and Socioeconomic driving Factors of PM2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

Xue

et al. 2021

Atmosphere

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Due to rapid urbanization and socio-economic development, fine particulate matter (PM2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of “high–high” and “low–low”. The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM2.5 pollutions from a socio-economic perspective.

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The Effect of Vegetation Enhancement on Particulate Pollution Reduction: CFD Simulations in an Urban Park

Cited by 23 publications

References 87 publications

Development and Verification of the Effectiveness of a Fine Dust Reduction Planting Model for Socially Vulnerable Area

Development and Verification of the Effectiveness of a Fine Dust Reduction Planting Model for Socially Vulnerable Area

The Effect of Pollution on Worker Productivity: Evidence from Call Center Workers in China

Analysis of Spatio-Temporal Heterogeneity and Socioeconomic driving Factors of PM2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

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