Effects of Green space landscape patterns on particulate matter in Zhejiang Province, China

Wu, Haitian; Yang, Chi; Chen, Jian; Yang, Shan; Lü, Ting; Lin, Xintao

doi:10.1016/j.apr.2018.03.004

Cited by 67 publications

(20 citation statements)

References 39 publications

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“…The average concentration was found to decline exponentially with increasing CVC. This is consistent with the findings of Wu et al (2018) [90]. The difference in concentration between PM2.5 and PM10 was initially small at CVC = 0.2 m 3 /m 2 and gradually increased towards CVC = 3.5 m 3 /m 2 .…”

Section: Crown Volume Coverage (Cvc)supporting

confidence: 93%

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

Qin

Hong

Jiang

et al. 2019

Forests

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Vegetation in parks is regarded as a valuable way to reduce particulate pollution in urban environments but there is little quantitative information on its effectiveness. The aim of this study was to conduct on-site measurements and computational fluid dynamic (CFD) simulations to determine the aerodynamic and deposition effects of vegetation enhancement on particulate matter (PM) dispersions in an urban park in Xi’an, China. Initially, the airflow characteristics and deposition effects of vegetation were predicted and compared with measured air velocities and particulate pollution data to validate the numerical modeling. Then, associated coverage ratios and supplementary green areas (tree coverage ratio, crown volume coverage (CVC), and roof greening) were added to numerical simulations. After a series of numerical simulations and comparisons, results indicated that: (1) Numerical models with simplified vegetation method could reproduce the distribution of particulate matter concentrations in the real park environment; (2) with a tree coverage ratio >37.8% (or CVC > 1.8 m3/m2), the pedestrian-level PM2.5 could meet the World Health Organization’s air quality guidelines (IT-1) standards in the park; (3) roof greening on leeward buildings produced greater PM removal effects compared with windward buildings; and (4) the most economical and reasonable tree coverage ratio and CVC to reduce atmospheric PM in urban parks should be 30% and 1.8 m3/m2, respectively. These results are useful guidelines for urban planners towards a sustainable design of vegetation in urban parks.

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Section: Crown Volume Coverage (Cvc)supporting

confidence: 93%

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

Qin

Hong

Jiang

et al. 2019

Forests

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“…In South Korea, PM is divided into PM10 (smaller than 10 µm) and PM2.5 (smaller than 2.5 µm), based on aerodynamic diameter [10,16]. A smaller aerodynamic diameter of PM has a more direct impact on health and the environment [3,34] and is related to many health risks such as respiratory and lung diseases, thus starting to form the public's risk perception in South Korea [12,13]. The PMRP can be redefined as a negative perception that is formed by the direct risks caused by PM or the indirect influences of the public, such as public opinion or policies (POP) related to PM.…”

Section: Risk Perception Variables Related To Particulate Mattermentioning

confidence: 99%

“…The situation regarding particulate matter (PM), a common indicator of the severity of air pollution, has become a serious problem for several developing countries [1][2][3]. South Korea is likewise in a critical situation.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Risk Perceptions Related to Particulate Matter on Outdoor Activity Satisfaction in South Korea

Kim

Yoon

Kim

et al. 2020

IJERPH

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In recent years, the Korean public has become aware of the form of air pollution known as particulate matter, with a consequent growth of public anxiety causing a negative risk perception about outdoor activity. This study aims at determining the causal relationship between risk perceptions about particulate matter and outdoor activity satisfaction in South Korea. An Internet survey was conducted with 412 people, and a structural equation model was used to perform confirmatory factor analysis. The statistically significant results show that the perceived risk of particulate matter is higher when people do not show interest in or trust public opinion or policy on the subject. This increases people’s perceptions of health risks, which in turn lowers their satisfaction with outdoor activity. Although trust levels in public opinion or policy had a positive impact on outdoor activity satisfaction, this was not statistically significant. These results are expected to contribute to risk communication guidelines in public opinion reporting and to the direction of environmental health policies in developing countries with high levels of air pollution, such as particulate matter.

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“…Based on the daily PM 10 and PM 2.5 concentration data from 50 monitoring stations in Zhejiang Province from 1 February 2015 to 28 February 2017, Wu et al conducted a quantitative study on the relationship between PM 10 and PM 2.5 concentration and green spaces and landscape structure through Principal Composition Cluster Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Their results showed that the increase of urban green space can reduce PM pollution, and the correlation between green space and PM 2.5 concentration is stronger than that between green space and PM 10 on the scale of 5 km or less [27]. Xu et al selected four representative locations (two cities, one suburb site and one rural site) in Hangzhou and Ningbo from December 2014 to November 2015 in order to study the seasonal and spatial variation in terms of fine particle pollution in Zhejiang Province.…”

Section: Introductionmentioning

confidence: 99%

“…(1) By constructing the six major pollutants defined by China's air quality standards, we have evaluated the air quality of Zhejiang Province more comprehensively than the existing research. In similar studies of air quality in Zhejiang Province, scholars often use particulate pollutants as research objects [27,28,78]. Then, few research works contain the six major pollutants.…”

mentioning

confidence: 99%

Application of Fuzzy Optimization Model Based on Entropy Weight Method in Atmospheric Quality Evaluation: A Case Study of Zhejiang Province, China

Wang

Yang

2019

Sustainability

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A fuzzy optimization model based on the entropy weight method for investigating air pollution problems in various cities of Zhejiang Province, China has been proposed in this paper. Meanwhile, the air quality comprehensive evaluation system has been constructed based on the six major pollutants (SO2, NO2, CO, PM10, PM2.5 and O3) involved in China’s current air quality national standards. After analyzing the monthly data of six pollutants in 11 cities of Zhejiang Province from January 2015 to April 2018 by the above method, the authors found that, although the air quality of cities in Zhejiang Province did not reach the long-term serious pollution of Beijing, Tianjin, and Hebei, the air quality changes in the northern cities of Zhejiang were worse than those in southern Zhejiang. For example, the air quality of Shaoxing in northern Zhejiang has dropped by 14.85% in the last study period when compared with that of the beginning period, and Hangzhou, the provincial capital of Zhejiang, has also seen a decrease of 6.69% in air quality. The air quality of Lishui, Zhoushan and Wenzhou in southern Zhejiang has improved by 8.04%, 4.67% and 4.22% respectively. Apart from the geographical influence, the industrial structure of these cities is also an important cause for worse air quality. From the local areas in southern Zhejiang, cities have developed targeted air pollution control measures according to their own characteristics, including adjusting the industrial structure, changing the current energy consumption structure that heavily relies on coal, and improving laws and regulations on air pollution control, etc. In the four cities in central Zhejiang, the air quality at the end of the period (April 2018) has decreased from the beginning of the period (January 2015), given that there were no fundamental changes in their industrial structure and energy pattern.

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Effects of Green space landscape patterns on particulate matter in Zhejiang Province, China

Cited by 67 publications

References 39 publications

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

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

The Effects of Risk Perceptions Related to Particulate Matter on Outdoor Activity Satisfaction in South Korea

Application of Fuzzy Optimization Model Based on Entropy Weight Method in Atmospheric Quality Evaluation: A Case Study of Zhejiang Province, China

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