Land | Special Issue : Urban Planning Pathways to Carbon Neutrality

Research

25 pages, 11963 KiB

Open AccessArticle

Spatio-Temporal Dynamics of Carbon Emissions and Their Influencing Factors at the County Scale: A Case Study of Zhejiang Province, China

by Xuanli Wang, Huifang Yu, Yiqun Wu, Congyue Zhou, Yonghua Li, Xingyu Lai and Jiahao He

Land 2024, 13(3), 381; https://doi.org/10.3390/land13030381 - 17 Mar 2024

Viewed by 831

Abstract

Significant carbon emissions, a key contributor to global climate warming, pose risks to ecosystems and human living conditions. It is crucial to monitor the spatial and temporal patterns of carbon emissions at the county level to reach the goals of carbon peak and [...] Read more.

Significant carbon emissions, a key contributor to global climate warming, pose risks to ecosystems and human living conditions. It is crucial to monitor the spatial and temporal patterns of carbon emissions at the county level to reach the goals of carbon peak and neutrality. This study examines carbon emissions and economic and social problems data from 89 counties in Zhejiang Province. It employs analytical techniques such as LISA time path, spatio-temporal transition, and standard deviational ellipse to investigate the trends of carbon emissions from 2002 to 2022. Furthermore, it utilizes the GTWR model to evaluate the factors that influence these emissions on a county scale. The findings reveal the following: (1) The LISA time path analysis indicates a pronounced local spatial structure in the distribution of carbon emissions in Zhejiang Province from 2002 to 2022, characterized by increasing stability, notable path dependency, and some degree of spatial integration, albeit with a diminishing trend in overall integration. (2) The LISA spatio-temporal transition analysis indicates significant path dependency or lock-in effects in the county-level spatial clustering of carbon emissions. (3) Over the period 2002–2022, the centroid of carbon emissions in Zhejiang’s counties mainly oscillated between 120°55′15″ E and 120°57′01″ E and between 29°55′52″ N and 29°59′11″ N, with a general northeastward shift forming a “V” pattern. This shift resulted in a stable “northeast–southwest” spatial distribution. (4) Factors such as population size, urbanization rate, and economic development level predominantly accelerate carbon emissions, whereas industrial structure tends to curb them. It is crucial to customize carbon mitigation plans to suit the circumstances of each county. This study provides insight into the spatial and temporal patterns of carbon emissions at the county level in Zhejiang Province. It offers crucial guidance for developing targeted and practical strategies to reduce carbon emissions. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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20 pages, 921 KiB

Open AccessArticle

The Effect of Public Traffic Accessibility on the Low-Carbon Awareness of Residents in Guangzhou: The Perspective of Travel Behavior

by Qingyin Li, Meilin Dai, Yongli Zhang and Rong Wu

Land 2023, 12(10), 1910; https://doi.org/10.3390/land12101910 - 11 Oct 2023

Viewed by 1004

Abstract

The demand for transportation among urban residents in China is increasing in tandem with the nation’s population growth, rising consumption levels, and increasing car ownership rates. Breaking the existing high-carbon travel practices and reshaping positive low-carbon awareness represents an inevitable way to change [...] Read more.

The demand for transportation among urban residents in China is increasing in tandem with the nation’s population growth, rising consumption levels, and increasing car ownership rates. Breaking the existing high-carbon travel practices and reshaping positive low-carbon awareness represents an inevitable way to change existing transportation structures and reduce urban traffic congestion and carbon emissions. A mediating effect model was employed and we found that community satisfaction is an essential variable in the effect of traffic accessibility and travel behavior on low-carbon awareness. First, the impact of residents’ zero and low-carbon actions on their low-carbon awareness is mediated by community satisfaction. Furthermore, compared to high-income groups, community satisfaction exerts a robust mediating influence on low-income groups. The mediating effect of community satisfaction on the relationship between residential proximity to commercial centers and low-carbon awareness among individuals with low incomes is evident. Based on these findings, this paper explores the heterogeneity and associated measures of low-carbon awareness among residents. The conclusion of this study provides suggestions to promote residents’ low-carbon awareness by improving their travel experience from the perspective of community construction, providing scientific reference and a basis for the formulation of transportation policies for low-carbon city construction. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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18 pages, 882 KiB

Open AccessArticle

Evaluating the Impact of Smart City Policy on Carbon Emission Efficiency

by Xingneng Xia, Ruoxi Yu and Sheng Zhang

Land 2023, 12(7), 1292; https://doi.org/10.3390/land12071292 - 26 Jun 2023

Cited by 3 | Viewed by 1127

Abstract

Smart city policy (SCP) is crucial to addressing climate change and achieving sustainable urban development with low carbon emissions. The purpose of this paper is to investigate the mechanisms through which smart city policies have an impact on carbon emission efficiency (CEE). In [...] Read more.

Smart city policy (SCP) is crucial to addressing climate change and achieving sustainable urban development with low carbon emissions. The purpose of this paper is to investigate the mechanisms through which smart city policies have an impact on carbon emission efficiency (CEE). In terms of research methodology, we construct a quasi-natural experiment on smart city policies in China and use the time-varying DID approach to study this issue. The DEA method was used to measure the CEE. For the data sample, panel data from 281 cities in China between 2007 and 2020 was used in this study. The findings are as follows: ① SCP has a significant impact on CEE. This conclusion remains valid after introducing parallel trend tests, placebo tests, and other robustness tests. ② The mechanism test result reveals that SCP has a positive impact on urban CEE through three main channels: promoting industrial upgrading, increasing public environmental attention, and enhancing marketization. ③ The analysis of heterogeneity reveals that the impact of SCP on CEE is noticeable in cities that belong to well-developed economic regions with a lower intensity of environmental regulations, higher levels of green finance, and fewer official changes. This research contributes to the existing literature on the environmental assessment of SCP and offers valuable policy insights for cities to tackle climate change and sustainable urban planning. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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18 pages, 1048 KiB

Open AccessArticle

Towards Carbon-Neutral Cities: Urban Classification Based on Physical Environment and Carbon Emission Characteristics

by Jiah Lee and Seunghyun Jung

Land 2023, 12(5), 968; https://doi.org/10.3390/land12050968 - 26 Apr 2023

Cited by 2 | Viewed by 1565

Abstract

Cities are highly industrialized and populated areas and major sources of greenhouse gas emissions. For carbon neutrality, examining the correlation between urban characteristics and greenhouse gas emissions is necessary. This study aimed to analyze the characteristics of each city from a carbon neutrality [...] Read more.

Cities are highly industrialized and populated areas and major sources of greenhouse gas emissions. For carbon neutrality, examining the correlation between urban characteristics and greenhouse gas emissions is necessary. This study aimed to analyze the characteristics of each city from a carbon neutrality perspective. As such, we conducted a carbon-neutral city analysis. First, the physical environmental variables of 250 municipal, county, and district local governments were collected and constructed and then reduced and purified through factor analysis. Second, the type was derived by performing cluster analysis on the reduced factor variables and carbon emissions by analysis unit. Finally, the characteristics of each type were analyzed, and the carbon-neutral city planning and applicable carbon-neutral technology fields were proposed according to the characteristics. After the categorization of carbon-neutral cities throughout Korea, six cluster types were derived; cities in each cluster had similar characteristics. This study suggests that solutions for carbon reduction should be applied by comprehensively considering the social, economic, and environmental characteristics of each city. It concludes that regional physical environmental indicators and energy consumption statistics can be used comprehensively to establish effective policies and apply technologies and techniques at the local government level. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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19 pages, 8378 KiB

Open AccessArticle

Spatiotemporal Evolution Trends of Urban Total Factor Carbon Efficiency under the Dual-Carbon Background

by Haiyan Luo and Xiaoe Qu

Land 2023, 12(1), 69; https://doi.org/10.3390/land12010069 - 26 Dec 2022

Cited by 4 | Viewed by 1393

Abstract

In order to grasp the development laws of carbon efficiency and help China to achieve the dual-carbon goal as soon as possible, we used the super-efficiency EBM model to calculate the total factor carbon efficiency of cities, based on panel data for 283 [...] Read more.

In order to grasp the development laws of carbon efficiency and help China to achieve the dual-carbon goal as soon as possible, we used the super-efficiency EBM model to calculate the total factor carbon efficiency of cities, based on panel data for 283 prefecture-level cities in China from 2004 to 2019. The spatiotemporal variations in carbon efficiency were analyzed using the Dagum Gini coefficient, LISA aggregation and standard deviational ellipse. The dynamic evolution trends were analyzed using kernel density estimation and the spatial Markov chain. The results showed that the overall difference in total factor carbon efficiency between the 283 cities decreased, and the difference within the three regions was greater than that between regions. The total factor carbon efficiency of the cities had a significant spatial correlation, and the spatial distribution patterns showed a centripetal aggregation from northeast to southwest. The dynamic evolution characteristics of the carbon emission intensity in different regions were quite different and the polarization of eastern and central cities was more obvious. There was a significant path dependence effect on the transition probability of total factor carbon efficiency between cities, and the carbon efficiency level of neighboring cities could affect the transition probability of the carbon efficiency of the cities. Based on the above conclusions, we also put forward relevant policy recommendations for technological changes on the energy supply side, innovative development patterns and the governance of regional policies. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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17 pages, 2180 KiB

Open AccessArticle

Analysis of Spatial Carbon Metabolism by ENA: A Case Study of Tongzhou District, Beijing

by Yongchao Qu, Jian Zhang, Chongyuan Xu, Yichao Gao, Shanwen Zheng and Meiling Xia

Land 2022, 11(9), 1573; https://doi.org/10.3390/land11091573 - 15 Sep 2022

Cited by 2 | Viewed by 1354

Abstract

Carbon metabolism research has attracted worldwide attention as an important way to cope with climate change, promote carbon emission reduction, increase carbon sequestration, and support low-carbon city construction. Ecological network analysis (ENA) plays an important role in network analysis and simulation of carbon [...] Read more.

Carbon metabolism research has attracted worldwide attention as an important way to cope with climate change, promote carbon emission reduction, increase carbon sequestration, and support low-carbon city construction. Ecological network analysis (ENA) plays an important role in network analysis and simulation of carbon metabolism. However, current studies largely focus on single elements or local processes while rarely analyzing the spatial coupling between land use and carbon metabolism. Therefore, taking Tongzhou District as an example, based on the data of land use change and energy consumption, this study constructed an analysis framework based on ENA to explore the comprehensive impact of land use changes on carbon metabolism. The results show the following: (1) From 2014 to 2020, the total carbon emissions increased year by year. Carbon emissions of other construction land (OCL) were dominant, while the carbon sequestration capacity of forest land (FL) increased by 236%. The positive carbon metabolic density remained relatively stable, while the negative carbon metabolic density decreased year by year. (2) The negative carbon flow was concentrated in the transfer of other land to OCL, accounting for 40.2% of the total negative “carbon flow.” The positive carbon flow was primarily from the transfer of other land to FL. (3) From 2014 to 2016, the spatial ecological relationships of carbon flow were dominated by exploitation and control. From 2016 to 2018, competition relationships intensified due to the expansion of the field; from 2016 to 2018, exploitation and control relationships, competition relationships, and mutualism relationships increased significantly and were evenly distributed. This study provides decision-making guidance for the subsequent formulation of government carbon emission reduction policies. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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22 pages, 29221 KiB

Open AccessArticle

Carbon Metabolism in Urban “Production–Living–Ecological” Space Based on Ecological Network Analysis

by Xinhui Feng, Yan Li, Lu Zhang, Chuyu Xia, Er Yu and Jiayu Yang

Land 2022, 11(9), 1445; https://doi.org/10.3390/land11091445 - 31 Aug 2022

Cited by 8 | Viewed by 1749

Abstract

To understand the changing pattern of urban carbon metabolism from the perspective of urban “production–living–ecological” (PLE) space, taking Suzhou City as an example, this study constructed a carbon metabolic network model in urban PLE space, analyzed the changes of horizontal carbon flow, and [...] Read more.

To understand the changing pattern of urban carbon metabolism from the perspective of urban “production–living–ecological” (PLE) space, taking Suzhou City as an example, this study constructed a carbon metabolic network model in urban PLE space, analyzed the changes of horizontal carbon flow, and evaluated the comprehensive effect of the PLE space changes using the ecological network analysis method. The results showed that the total carbon sequestration showed a fluctuating change of increasing and then decreasing, while the total carbon emissions grew dramatically. Production spaces were the key nodes for the generation of horizontal carbon flow. The exploitation relationship was the dominant ecological relationship in the network, the mutualism relationship was abundant from 2005 to 2010 and gradually decreased from 2010 to 2018, and the frequency of competition relationship appeared gradually increased. The ecological network hierarchy evolved from an irregular shape dominated by primary consumers in 2000–2005 to a pyramidal shape dominated by producers in 2010–2018 at the driving weight end, and the pull weight showed a declining trend, with pull weight of producers increasing from 1.72% to 24.33%. The results can provide a theoretical basis for planning adjustments to the city’s PLE space structure to achieve low-carbon goals. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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21 pages, 1464 KiB

Open AccessArticle

Urbanization Influences CO₂ Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

by Yabo Zhao, Ruiyang Chen, Tong Sun, Ying Yang, Shifa Ma, Dixiang Xie, Xiwen Zhang and Yunnan Cai

Land 2022, 11(8), 1373; https://doi.org/10.3390/land11081373 - 22 Aug 2022

Cited by 3 | Viewed by 1709

Abstract

As the largest carbon emitter in the world, China is facing increasing challenge to reduce CO₂ emissions. Given this issue, exploring the influencing factors is of great significance for scientific low-carbon emission policymaking. Although previous literature has explored the effects of urbanization [...] Read more.

As the largest carbon emitter in the world, China is facing increasing challenge to reduce CO₂ emissions. Given this issue, exploring the influencing factors is of great significance for scientific low-carbon emission policymaking. Although previous literature has explored the effects of urbanization on CO₂ emissions, the impact of the space of flow on urban carbon emissions have been less explored. Due to the increasing connection between cities, its impact on urban carbon emissions cannot be ignored. Thus, this paper takes the space of flows into account as an aspect of urbanization to supplement the existing literature and empirically examines the multiple effects of urbanization on CO₂ emissions in the Pearl River Delta (PRD) urban agglomeration. By using a STIRPAT model, statistical data, and web crawler data, we examined impacts of different types of urbanization on CO₂ emissions. Our empirical results show that: (1) Within the PRD urban agglomeration, urban linkage intensity is strongly connected to urban socioeconomic growth, establishing a geographical structure with Guangzhou and Shenzhen as the double core. (2) Our results show that urbanization exerts two opposite effects on CO₂ emissions: positively connects carbon emissions with population urbanization, integrated urban linkage flow, and energy intensity, whereas economic urbanization and social urbanization are shown to be negatively correlated. However, spatial urbanization has no significant positive effect on urban CO₂ emissions. (3) It is worth noting that urban linkage flows are the second most important factor affecting urban carbon emissions after economic urbanization. Our study could formulate effective planning suggestions for future CO₂ emission reduction paths and development modes in the PRD. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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17 pages, 1993 KiB

Open AccessArticle

Evaluating the Effects of Renewable Energy Consumption on Carbon Emissions of China’s Provinces: Based on Spatial Durbin Model

by Yang Sun, Mengna Du, Leying Wu, Changzhe Li and Yulong Chen

Land 2022, 11(8), 1316; https://doi.org/10.3390/land11081316 - 15 Aug 2022

Cited by 2 | Viewed by 1344

Abstract

Renewable energy consumption is considered as the main form of energy consumption in the future. The carbon emissions produced by renewable energy can be approximately ignored, and renewable energy is essential for regional sustainable development. In this study, we used the Durbin model [...] Read more.

Renewable energy consumption is considered as the main form of energy consumption in the future. The carbon emissions produced by renewable energy can be approximately ignored, and renewable energy is essential for regional sustainable development. In this study, we used the Durbin model with panel data to explore the spatial dependence between renewable energy consumption the and carbon emissions of China’s 30 provinces from 1997 to 2017. The results show that: (1) there is a negative spatial correlation between renewable energy consumption and carbon emissions, and “High-Low” areas are mainly concentrated in southern provinces in 1997–2011; (2) the center of gravity of renewable energy consumption moves southwest, which is consistent with the center of gravity of carbon emissions; (3) renewable energy consumption has a significant inhibitory effect on carbon emissions of a local region, but the spatial spillover effect is not significant. Specifically, a 1% increase in renewable energy consumption in a region will reduce carbon emissions by 0.05%. Finally, on the basis of this study, it was proposed to give full play to the advantages of renewable energy in the western region, and further accelerate the development of the renewable energy industry. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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18 pages, 3051 KiB

Open AccessArticle

The Impact of Urbanization Growth Patterns on Carbon Dioxide Emissions: Evidence from Guizhou, West of China

by Canying Zeng, Shaohua Wu, Hua Zhou and Min Cheng

Land 2022, 11(8), 1211; https://doi.org/10.3390/land11081211 - 01 Aug 2022

Cited by 3 | Viewed by 1560

Abstract

Little attention has been paid to the impact of future urban expansion patterns on carbon emissions based on the existing urban pattern of a region. This study used the Central Guizhou Urban Agglomeration as the study area, and the relationships between regional urbanization [...] Read more.

Little attention has been paid to the impact of future urban expansion patterns on carbon emissions based on the existing urban pattern of a region. This study used the Central Guizhou Urban Agglomeration as the study area, and the relationships between regional urbanization and CO₂ emissions in the study area were analyzed based on historical data. Urban growth patterns were then simulated in four scenarios that focused on the next 15 years, and they were based on the cellular automaton model. In each different scenario, the CO₂ emissions were predicted, and some implications regarding the impact of those emissions were provided. The results showed that as urban land-use intensity increases, CO₂ emissions first increase then decrease; however, the rate of decline for CO₂ emissions is much slower than the rate at which it rises. Moreover, in the next 15 years, urban expansion will lead to a significant increase in CO₂ emissions. The CO₂ emissions were found to be lowest in the spatial agglomeration scenario and highest in the spatial dispersion scenario. The spatial agglomeration scenario was conducive to understanding how CO₂ emissions eventually peak; however, different cities in the study area should adopt different urban expansion patterns. These research results can provide a reference guide for the government with regard to urban planning. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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18 pages, 2609 KiB

Open AccessArticle

A Big Data-Based Commuting Carbon Emissions Accounting Method—A Case of Hangzhou

by Song Li, Fei Xue, Chuyu Xia, Jian Zhang, Ao Bian, Yuexi Lang and Jun Zhou

Land 2022, 11(6), 900; https://doi.org/10.3390/land11060900 - 13 Jun 2022

Cited by 8 | Viewed by 2157

Abstract

Commuting carbon emissions are an essential component of urban carbon emissions, and determining how to reduce them is an area of great debate among researchers. The current research lacks a tool and instrument that can extensively account for residents’ commuting. Traditional methods are [...] Read more.

Commuting carbon emissions are an essential component of urban carbon emissions, and determining how to reduce them is an area of great debate among researchers. The current research lacks a tool and instrument that can extensively account for residents’ commuting. Traditional methods are mainly based on questionnaire surveys, which have low accuracy at spatial and temporal aspects. High accuracy carbon emission accounting methods can effectively assist urban planning and achieve precise urban emissions reductions. This study applies a taxi commuting carbon emissions accounting method divided into two main steps. Firstly, the carbon emissions of taxi trajectories are calculated using taxi trajectory data and a carbon emission calculation method developed based on VSP. Secondly, the taxi trajectory and POI data are used to filter the commuter trajectory with the help of a two-step moving search method. In this way, the taxi commuting carbon emissions were obtained. Then, the spatial distribution characteristics of residential taxi commuting carbon emissions are analysed by spatial autocorrelation tools, which could facilitate low carbon zoning management. A typical working day in Hangzhou was selected as the research object of this study. The results show that (1) morning peak commuting carbon emissions in the main urban area of Hangzhou reached 2065.14 kg per hour, accounting for 13.73% of all taxi travel carbon emissions; and evening peak commuting carbon emissions reached 732.2 kg per hour, accounting for 4% of all taxi travel carbon emissions; (2) At the grid level, the spatial distribution of commuting carbon emissions in Hangzhou shows a single central peak that decays in all directions; and (3) The results at the resident community scale show that urban public transport facilities influence resident community commuting carbon emissions. In areas such as at the urban-rural border, resident community commuting carbon emissions show high levels of aggregation, and in the main urban area, resident community commuting carbon emissions show low levels of aggregation. This study not only provides a new method of commuting investigation but also offers constructive suggestions for future carbon emission reduction under Hangzhou’s urban planning. Full article

(This article belongs to the Special Issue Urban Planning Pathways to Carbon Neutrality)

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