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Special Issue "Advances in Urban Spatial Planning and Carbon Emission"

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: 31 December 2022 | Viewed by 2245

Special Issue Editors

Prof. Dr. Qianxin Wang
E-Mail Website
Guest Editor
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Interests: remote sensing; geographic information science; urban spatial planning
Prof. Dr. Xiaoping Liu
E-Mail Website
Guest Editor
School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China
Interests: geographic information science; urban spatial planning; spatial modeling and analysis
Prof. Dr. Honghui Zhang
E-Mail Website
Guest Editor
The Key Laboratory of Carbon Neutrality and Territory Optimization, Ministry of Natural Resources, Beijing 100036, China
Interests: geographic information science; urban spatial planning; land use change and carbon
Dr. Guohua Hu
E-Mail Website1 Website2
Guest Editor
School of Geographic Sciences, East China Normal University, Shanghai 200062, China
Interests: geographic information science; urban sustainability; land use change modeling
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Special Issue Information

Dear Colleagues,

Global warming represents a significant and increasingly more serious challenge for humanity and the planet. The global average surface temperature increased by about 0.85 °C from 1880 to 2012, and the main factor was the emission of human-made greenhouse gases. Carbon dioxide represents the largest amount of greenhouse gases and has the greatest impact on the environment. Fundamentally, carbon dioxide is a byproduct of economic activity. Since the majority of economic activity happens in an urban setting, measures should be implemented to build a low-carbon city. Urban spatial planning is an efficient way to reduce urban carbon emissions and realize carbon neutrality. This Special Issue seeks to publish papers (original research and reviews) that report associations and findings on how the urban spatial pattern has influenced carbon emission and how to build a low-carbon city by urban spatial planning. In addition, papers on how to monitor and calculate urban carbon emissions by remote sensing, the Internet of Things, and simulation and analysis of urban carbon emission by Artificial Intelligence and Geographic Information System technology are welcomed. 

Potential topics include, but are not limited to: 

  • Urban planning for carbon neutrality;
  • Transportation and energy consumption;
  • Urban carbon emission monitoring and calculation;
  • Simulation and analysis of urban carbon dynamics;
  • Carbon sources and carbon sinks in urban and rural areas;
  • Policies and optimization path of carbon neutrality;
  • Green building and low-carbon city;
  • Land use/cover change and carbon emission.

Prof. Dr. Qianxin Wang
Prof. Dr. Xiaoping Liu
Prof. Dr. Honghui Zhang
Dr. Guohua Hu
Guest Editors

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 semimonthly 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 planning
  • low-carbon city
  • energy consumption
  • greenhouse gas
  • carbon emission
  • carbon neutrality
  • carbon footprint
  • carbon sources
  • carbon sinks

Published Papers (3 papers)

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Research

Article
Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England
Int. J. Environ. Res. Public Health 2022, 19(10), 5986; https://doi.org/10.3390/ijerph19105986 - 14 May 2022
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Abstract
The spatiotemporal inventory of carbon dioxide (CO2) emissions from the building sector is significant for formulating regional and global warming mitigation policies. Previous studies have attempted to use energy consumption models associated with field investigations to estimate CO2 emissions from [...] Read more.
The spatiotemporal inventory of carbon dioxide (CO2) emissions from the building sector is significant for formulating regional and global warming mitigation policies. Previous studies have attempted to use energy consumption models associated with field investigations to estimate CO2 emissions from buildings at local scales, or they used spatial proxies to downscale emission sources from large geographic units to grid cells for larger scales. However, mapping the spatiotemporal distributions of CO2 emissions on a large scale based on buildings remains challenging. Hence, we conducted a case study in England in 2015, wherein we developed linear regression models to analyze monthly CO2 emissions at the building scale by integrating the Emissions Database for Global Atmospheric Research, building data, and Visible Infrared Imaging Radiometer Suite night-time lights images. The results showed that the proposed model that considered building data and night-time light imagery achieved the best fit. Fine-scale spatial heterogeneity was observed in the distributions of building-based CO2 emissions compared to grid-based emission maps. In addition, we observed seasonal differences in CO2 emissions. Specifically, buildings emitted significantly more CO2 in winter than in summer in England. We believe our results have great potential for use in carbon neutrality policy making and climate monitoring. Full article
(This article belongs to the Special Issue Advances in Urban Spatial Planning and Carbon Emission)
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Article
The Effect of Urban Shrinkage on Carbon Dioxide Emissions Efficiency in Northeast China
Int. J. Environ. Res. Public Health 2022, 19(9), 5772; https://doi.org/10.3390/ijerph19095772 - 09 May 2022
Viewed by 472
Abstract
Climate change caused by CO2 emissions is a controversial topic in today’s society; improving CO2 emission efficiency (CEE) is an important way to reduce carbon emissions. While studies have often focused on areas with high carbon and large economies, the areas [...] Read more.
Climate change caused by CO2 emissions is a controversial topic in today’s society; improving CO2 emission efficiency (CEE) is an important way to reduce carbon emissions. While studies have often focused on areas with high carbon and large economies, the areas with persistent contraction have been neglected. These regions do not have high carbon emissions, but are facing a continuous decline in energy efficiency; therefore, it is of great relevance to explore the impact and mechanisms of CO2 emission efficiency in shrinking areas or shrinking cities. This paper uses a super-efficiency slacks-based measure (SBM) model to measure the CO2 emission efficiency and potential CO2 emission reduction (PCR) of 33 prefecture-level cities in northeast China from 2006 to 2019. For the first time, a Tobit model is used to analyze the factors influencing CEE, using the level of urban shrinkage as the core variable, with socio-economic indicators and urban construction indicators as control variables, while the mediating effect model is applied to identify the transmission mechanism of urban shrinkage. The results show that the CEE index of cities in northeast China is decreasing by 1.75% per annum. For every 1% increase in urban shrinkage, CEE decreased by approximately 2.1458%, with urban shrinkage, industrial structure, and expansion intensity index (EII) being the main factors influencing CEE. At the same time, urban shrinkage has a further dampening effect on CEE by reducing research and development expenditure (R&D) and urban compactness (COMP), with each 1% increase in urban shrinkage reducing R&D and COMP by approximately 0.534% and 1.233%, respectively. This can be improved by making full use of the available built-up space, increasing urban density, and promoting investment in research. Full article
(This article belongs to the Special Issue Advances in Urban Spatial Planning and Carbon Emission)
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Article
Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
Int. J. Environ. Res. Public Health 2022, 19(3), 1272; https://doi.org/10.3390/ijerph19031272 - 24 Jan 2022
Viewed by 878
Abstract
Roadsides are important urban public spaces where residents are in direct contact with the thermal environment. Understanding the effects of different vegetation types on the roadside thermal environment has been an important aspect of recent urban research. Although previous studies have shown that [...] Read more.
Roadsides are important urban public spaces where residents are in direct contact with the thermal environment. Understanding the effects of different vegetation types on the roadside thermal environment has been an important aspect of recent urban research. Although previous studies have shown that the thermal environment is related to the type and configuration of vegetation, remote sensing-based technology is not applicable for extracting different vegetation types at the roadside scale. The rapid development and usage of street view data provide a way to solve this problem, as street view data have a unique pedestrian perspective. In this study, we explored the effects of different roadside vegetation types on land surface temperatures (LSTs) using street view images. First, the grasses–shrubs–trees (GST) ratios were extracted from 19,596 street view images using semantic segmentation technology, while LST and normalized difference vegetation index (NDVI) values were extracted from Landsat-8 images using the radiation transfer equation algorithm. Second, the effects of different vegetation types on roadside LSTs were explored based on geographically weighted regression (GWR), and the different performances of the analyses using remotely sensed images and street view images were discussed. The results indicate that GST vegetation has different cooling effects in different spaces, with a fitting value of 0.835 determined using GWR. Among these spaces, the areas with a significant cooling effect provided by grass are mainly located in the core commercial area of Futian District, which is densely populated by people and vehicles; the areas with a significant cooling effect provided by shrubs are mainly located in the industrial park in the south, which has the highest industrial heat emissions; the areas with a significant cooling effect provided by trees are mainly located in the core area of Futian, which is densely populated by roads and buildings. These are also the areas with the most severe heat island effect in Futian. This study expands our understanding of the relationship between roadside vegetation and the urban thermal environment, and has scientific significance for the planning and guiding of urban thermal environment regulation. Full article
(This article belongs to the Special Issue Advances in Urban Spatial Planning and Carbon Emission)
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