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Green Plan and Environmental Policy

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Earth Science and Medical Geology".

Deadline for manuscript submissions: closed (23 November 2023) | Viewed by 10817

Special Issue Editor

Dr. Weiwu Wang

E-Mail Website
Guest Editor
School of Architecture and Engineering, Zhejiang University, Hangzhou, China
Interests: regional and urban planning; urban GIS; remote sensing; urban ecology and landscape; urban environment; urban heat island; urban wind corridor
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Scientific and reasonable green planning and environmental policies play a key leading role in the sustainable development of a country and region. The problems of urban climate and urban environment caused by urbanization have had a significant impact on the development of Global social and economic development. While promoting high-quality socio-economic development, many countries around the world have formulated a series of environmental policies, especially carbon peak and carbon neutralization policies, which will have a far-reaching impact on the global society, economy and environment. This Special Issue is aimed to providing selected contributions on advances in green planning and environmental policy designation:

  • Large scale ecological and environmental protection planning and Strategies;
  • Territory space ecological collaborative planning;
  • Multi scale spatio-temporal prediction and public health planning response of urban heat island and urban wind and COVID-19;
  • Theories and methods of urban form optimization and urban green infrastructure;
  • Urban Ventilation and urban health;
  • Ecological space optimization of urban built environment;
  • Multi scale prediction and implementation effect evaluation under multi scenario of carbon peak and carbon neutralization;
  • Application of new technologies in urban environmental ecological planning and public health.

Dr. Weiwu Wang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • urban ventilation
  • carbon peak and carbon neutralization
  • urban form optimization
  • urban green infrastructure
  • environment justice
  • mental health
  • large-scale planning
  • public health
  • COVID-19 pandemic

Published Papers (5 papers)

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Research

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17 pages, 4617 KiB  
Article
Investigating the Association between Streetscapes and Mental Health in Zhanjiang, China: Using Baidu Street View Images and Deep Learning
by Anjing Zhang, Shiyan Zhai, Xiaoxiao Liu, Genxin Song and Yuke Feng
Int. J. Environ. Res. Public Health 2022, 19(24), 16634; https://doi.org/10.3390/ijerph192416634 - 11 Dec 2022
Cited by 4 | Viewed by 1848
Abstract
Mental health is one of the main factors that significantly affect one’s life. Previous studies suggest that streets are the main activity space for urban residents and have important impacts on human mental health. Existing studies, however, have not fully examined the relationships [...] Read more.
Mental health is one of the main factors that significantly affect one’s life. Previous studies suggest that streets are the main activity space for urban residents and have important impacts on human mental health. Existing studies, however, have not fully examined the relationships between streetscape characteristics and people’s mental health on a street level. This study thus aims to explore the spatial patterns of urban streetscape features and their associations with residents’ mental health by age and sex in Zhanjiang, China. Using Baidu Street View (BSV) images and deep learning, we extracted the Green View Index (GVI) and the street enclosure to represent two physical features of the streetscapes. Global Moran’s I and hotspot analysis methods were used to examine the spatial distributions of streetscape features. We find that both GVI and street enclosure tend to cluster, but show almost opposite spatial distributions. The Results of Pearson’s correlation analysis show that residents’ mental health does not correlate with GVI, but it has a significant positive correlation with the street enclosure, especially for men aged 31 to 70 and women over 70-year-old. These findings emphasize the important effects of streetscapes on human health and provide useful information for urban planning. Full article
(This article belongs to the Special Issue Green Plan and Environmental Policy)
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18 pages, 14360 KiB  
Article
Spatial-Temporal Pattern Evolution of Public Sentiment Responses to the COVID-19 Pandemic in Small Cities of China: A Case Study Based on Social Media Data Analysis
by Yuye Zhou, Jiangang Xu, Maosen Yin, Jun Zeng, Haolin Ming and Yiwen Wang
Int. J. Environ. Res. Public Health 2022, 19(18), 11306; https://doi.org/10.3390/ijerph191811306 - 8 Sep 2022
Cited by 3 | Viewed by 1997
Abstract
The impact of the COVID-19 pandemic on public mental health has become increasingly prominent. Therefore, it is of great value to study the spatial-temporal characteristics of public sentiment responses to COVID-19 exposure to improve urban anti-pandemic decision-making and public health resilience. However, the [...] Read more.
The impact of the COVID-19 pandemic on public mental health has become increasingly prominent. Therefore, it is of great value to study the spatial-temporal characteristics of public sentiment responses to COVID-19 exposure to improve urban anti-pandemic decision-making and public health resilience. However, the majority of recent studies have focused on the macro scale or large cities, and there is a relative lack of adequate research on the small-city scale in China. To address this lack of research, we conducted a case study of Shaoxing city, proposed a spatial-based pandemic-cognition-sentiment (PCS) conceptual model, and collected microblog check-in data and information on the spatial-temporal trajectory of cases before and after a wave of the COVID-19 pandemic. The natural language algorithm of dictionary-based sentiment analysis (DSA) was used to calculate public sentiment strength. Additionally, local Moran’s I, kernel-density analysis, Getis-Ord Gi* and standard deviation ellipse methods were applied to analyze the nonlinear evolution and clustering characteristics of public sentiment spatial-temporal patterns at the small-city scale concerning the pandemic. The results reveal that (1) the characteristics of pandemic spread show contagion diffusion at the micro level and hierarchical diffusion at the macro level, (2) the pandemic has a depressive effect on public sentiment in the center of the outbreak, and (3) the pandemic has a nonlinear gradient negative impact on mood in the surrounding areas. These findings could help propose targeted pandemic prevention policies applying spatial intervention to improve residents’ mental health resilience in response to future pandemics. Full article
(This article belongs to the Special Issue Green Plan and Environmental Policy)
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12 pages, 470 KiB  
Article
The Impact of the Gain-Loss Frame on College Students’ Willingness to Participate in the Individual Low-Carbon Behavior Rewarding System (ILBRS): The Mediating Role of Environmental Risk Perception
by Ani Qi, Zeyu Ji, Yuanchao Gong, Bo Yang and Yan Sun
Int. J. Environ. Res. Public Health 2022, 19(17), 11008; https://doi.org/10.3390/ijerph191711008 - 2 Sep 2022
Cited by 4 | Viewed by 2000
Abstract
Since Chinese households account for more than half of the country’s total carbon emissions, efforts focused on consumption will be key to reaching carbon reduction targets. The Individual Low-carbon Behavior Rewarding System (ILBRS) is an emerging mechanism in China that encourages the public [...] Read more.
Since Chinese households account for more than half of the country’s total carbon emissions, efforts focused on consumption will be key to reaching carbon reduction targets. The Individual Low-carbon Behavior Rewarding System (ILBRS) is an emerging mechanism in China that encourages the public to develop a low-carbon lifestyle and it is critical to look for various approaches to enhance the public’s willingness to participate in it. The framing effect has been widely used to study pro-environmental behavior as a low-cost nudge. We used an online questionnaire (N = 320) to investigate how framing information (loss and gain framing) influenced people’s willingness to participate in the ILBRS through the mediation of environmental risk perception. The results indicated that the public’s willingness to participate in the ILBRS under the loss frame was significantly higher than the gain frame. Furthermore, environmental risk perception played a mediating role in the proceedings. Based on our findings, the designers and promoters of ILBRS systems could employ loss-frame information to promote the public’s willingness to participate in the ILBRS and drive more people to live a low-carbon life in the process of mechanism construction, information communication, and operational promotion. Full article
(This article belongs to the Special Issue Green Plan and Environmental Policy)
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19 pages, 698 KiB  
Article
Spatial Convergence of Carbon Productivity: Theoretical Analysis and Chinese Experience
by Meng Sun, Yue Zhang, Yaqi Hu and Jiayi Zhang
Int. J. Environ. Res. Public Health 2022, 19(8), 4606; https://doi.org/10.3390/ijerph19084606 - 11 Apr 2022
Cited by 6 | Viewed by 1643
Abstract
Based on the neoclassical framework, we propose the convergence hypothesis of carbon productivity under sustainable growth and prove the different effects of knowledge spillover and technology diffusion on convergence. The convergence hypothesis is tested using China’s provincial spatial dynamic panel data from 1995 [...] Read more.
Based on the neoclassical framework, we propose the convergence hypothesis of carbon productivity under sustainable growth and prove the different effects of knowledge spillover and technology diffusion on convergence. The convergence hypothesis is tested using China’s provincial spatial dynamic panel data from 1995 to 2019. The results show that China’s provincial carbon productivity has conditional convergence and club convergence characteristics. The convergence speed of dynamic panel regression estimation is greater than that of cross-sectional regression. The convergence rate of dynamic spatial panel regression estimation is faster depending on the spatial spillover difference between the two technologies. In the early stage, the provincial spatial dependence of China’s carbon productivity is mainly knowledge spillover, and the convergence rate is lower than that of the closed economy. Over the past decade, the spatial spillover, dominated by low-carbon technology diffusion, has become the dominant force. The convergence rate is significantly faster than that of a non-spatial-dependent economy. In addition, the mechanism test found that the development of energy efficiency dominates the spatial transfer of technology, so the overall convergence of carbon productivity in China mainly comes from the apparent convergence of energy efficiency in provinces and cities. Our conclusion provides a new reference for the emission reduction actions of countries worldwide because the spatial knowledge spillover carried by capital flows is not conducive to the pursuit of carbon productivity in less developed regions. On the contrary, the dissemination and diffusion of low-carbon technologies can significantly reduce carbon equivalent input in the production process, accelerating the pursuit of developing countries or regions. Full article
(This article belongs to the Special Issue Green Plan and Environmental Policy)
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Review

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19 pages, 1838 KiB  
Review
Research Progress and Hotspot Analysis of Residential Carbon Emissions Based on CiteSpace Software
by Yi Chen, Yinrong Chen, Kun Chen and Min Liu
Int. J. Environ. Res. Public Health 2023, 20(3), 1706; https://doi.org/10.3390/ijerph20031706 - 17 Jan 2023
Cited by 2 | Viewed by 2043
Abstract
Residential carbon emissions are one of the critical causes of climate problems such as global warming. It is significant to explore the development and evolution trend of residential carbon emissions research for mitigating global climate change. However, there have been no studies that [...] Read more.
Residential carbon emissions are one of the critical causes of climate problems such as global warming. It is significant to explore the development and evolution trend of residential carbon emissions research for mitigating global climate change. However, there have been no studies that comprehensively review this research field. Based on the research papers on residential carbon emissions included in the Web of Science core database and China National Knowledge Infrastructure database, the CiteSpace bibliometric analysis software was used in this paper to draw the visual knowledge map of residential carbon emissions research and reveal its research status, research hotspots, and development trend. We found that residential carbon emissions research has gone through the stage of “emergence–initiation–rapid development”, and the research in the United States and the United Kingdom has played a fundamental role in developing this research field. Research hotspots mainly focus on analyzing energy demand, quantitative measurement, and impact mechanisms of residents’ direct and indirect carbon emissions and low-carbon consumption willingness. The focus of research has gradually shifted from qualitative analysis based on relevant policies to the analysis of quantitative spatiotemporal measurements and drive mechanisms of direct and indirect carbon emissions from residential buildings, transportation, and tourism based on mathematical models and geographic information system technologies. Modern intelligent means such as remote sensing technology and artificial intelligence technology can improve the dynamics and accuracy of this research, but there are few related types of research at present. Based on these research status and trends, we proposed that the future research direction of residential carbon emissions should focus more on spatial analysis and trend prediction based on intelligent methods under a low-carbon background. Full article
(This article belongs to the Special Issue Green Plan and Environmental Policy)
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