The influence of green areas on city-dwellers' perceptions of air pollution: The case of Nigde city center

Çetin, Ç.; Karafaki, Filiz Çetinkaya

doi:10.22438/jeb/41/2(si)/jeb-26

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…The physical environment created by green area can reduce the exposure to air pollution, noise, and heat, which closely affects the quality of life of the inhabitants [80,81] Additionally, many studies provide evidence for the importance of living in urban green areas for reducing mental stress and increasing well-being [20,82]. As urbanites confront heightened pressure from work and family or other domains, a need for recovery is mandated [25,81].…”

Section: Hypotheses Development 21 the Relationship Between Community Engagement Flow Experience Green Area And Life Satisfactionmentioning

confidence: 99%

Expanding Social, Psychological, and Physical Indicators of Urbanites’ Life Satisfaction toward Residential Community: A Structural Equation Modeling Analysis

Peng

Yuan

Mao

et al. 2020

IJERPH

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Attention on, and interest in, life satisfaction has increased worldwide. However, research on life satisfaction focused toward the urban dwellers’ residential community is mainly from western countries, and the limited research from China is solely focused on the geriatric population via a narrowly constrained research perspective. This study, therefore, aimed to investigate urbanites’ life satisfaction toward their community, combining the psychological (behavioral community engagement, mental state of flow, and cognitive community identity), physical (PREQIs-perceived residential environment quality indicators: e.g., green area), and social perspectives (social capital). The proposed conceptual model was tested on a regionally representative sample of 508 urban community residents in the city of Chengdu, Sichuan province, China. Data were analyzed via a structure equation modelling approach in AMOS software. Findings suggested that all of the psychological, physical and social factors contributed to a prediction of life satisfaction. Specifically, social capital mediated the path from community engagement and flow to life satisfaction, and community identity mediated the path from flow experience and green area to life satisfaction. Additionally, social capital contributed to predict life satisfaction through its influence on community identity. Findings provide suggestions for urban designers and policymakers to focus on creating an urban community equipped with green area, which helps to promote physical activities that are flow-productive, to enhance residents’ identification to their residential community and, therefore, increase life satisfaction.

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Section: Hypotheses Development 21 the Relationship Between Community Engagement Flow Experience Green Area And Life Satisfactionmentioning

confidence: 99%

Expanding Social, Psychological, and Physical Indicators of Urbanites’ Life Satisfaction toward Residential Community: A Structural Equation Modeling Analysis

Peng

Yuan

Mao

et al. 2020

IJERPH

View full text Add to dashboard Cite

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“…Theories from environmental epidemiology and air quality provide possible mechanisms by which urban green spaces can indirectly affect the health of residents by improving air quality ( 14 ). Urban green spaces effectively improve air quality by absorbing pollutants from the atmosphere, increasing the negative oxygen ion content of the air, and maintaining soil ecology ( 15 ).…”

Section: Theoretical Analysis and Research Hypothesismentioning

confidence: 99%

Urban green spaces and resident health: an empirical analysis from data across 30 provinces in China

Bi,

Wang,

Yang

et al. 2024

Front. Public Health

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BackgroundThis study aims to explore the correlation between urban green space coverage and resident health, and to analyze its underlying mechanisms.MethodsUsing panel data from 30 provinces in China from 2006 to 2022, which mainly includes urban green space coverage, general health of the population, air quality, and social connectivity. This research constructed a fixed effects model to perform baseline regression analysis. A series of robustness tests, including variable substitution, controlling for geographical differences, regional robustness tests, and shortening the time span of the study, further verified the robustness of the results. Additionally, mechanism tests were conducted to examine the positive impacts of urban green spaces on resident health by improving air quality and enhancing social connectivity.ResultsThe findings indicate a significant positive correlation between urban green space coverage and resident health levels. That is, the greater the area covered with urban green space, the healthier the residents of the area will be. Robustness tests support the reliability of this finding, while mechanism analysis reveals that urban green spaces have a positive impact on the health of the population by improving air quality and increasing social connectivity.DiscussionThis study underscores the importance of urban green space planning in improving resident health and quality of life, providing urban planners with scientific evidence to optimize urban green systems for broader health objectives.

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“…People perceived air as very clean when the weather is cool and dry, while people perceived warm and highly humid air as stuffy even if the air is clean [ 20 ]. Green space is found to mitigate people’s negative perceptions of air quality [ 21 ]. People are also aware that poor air quality had negative health consequences in commuting [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Assessment of air pollution and air quality perception mismatch using mobility-based real-time exposure

Song,

Kwan,

Huang

2024

PLoS ONE

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Air pollution poses a threat to human health. Public perceptions of air pollution are important for individual self-protection and policy-making. Given the uncertainty faced by residence-based exposure (RB) measurements, this study measures individuals’ real-time mobility-based (MB) exposures and perceptions of air pollution by considering people’s daily movement. It explores how contextual uncertainties may influence the disparities in perceived air quality by taking into account RB and MB environmental factors. In addition, we explore factors that are related to the mismatch between people’s perceived air quality and actual air pollution exposure. Using K-means clustering to divide the PM2.5 values into two groups, a mismatch happens when the perceived air quality is poor but the air pollution level is lower than 15.536μg/m3 and when the perceived air quality is good but the air pollution level is higher than 15.608μg/m3. The results show that there is a mismatch between air pollution exposure and perception of air pollution. People with low income are exposed to higher air pollution. Unemployed people and people with more serious mental health symptoms (e.g., depression) have a higher chance of accurately assessing air pollution (e.g., perceiving air quality as poor when air pollution levels are high). Older people and those with a higher MB open space density tend to underestimate air pollution. Students tend to perceive air quality as good. People who are surrounded by higher MB transportation land-use density and green space density tend to perceive air quality as poor. The results can help policymakers to increase public awareness of high air pollution areas, and consider the health effects of landscapes during planning.

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The influence of green areas on city-dwellers' perceptions of air pollution: The case of Nigde city center

Cited by 8 publications

References 7 publications

Expanding Social, Psychological, and Physical Indicators of Urbanites’ Life Satisfaction toward Residential Community: A Structural Equation Modeling Analysis

Expanding Social, Psychological, and Physical Indicators of Urbanites’ Life Satisfaction toward Residential Community: A Structural Equation Modeling Analysis

Urban green spaces and resident health: an empirical analysis from data across 30 provinces in China

Assessment of air pollution and air quality perception mismatch using mobility-based real-time exposure

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