Quantitative analysis of carbon emissions for new town planning based on the system dynamics approach

Liu, Luyun; Zheng, Bohong; Bedra, Komi Bernard

doi:10.1016/j.scs.2018.08.006

Cited by 32 publications

(7 citation statements)

References 18 publications

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“…Chen, based on the case analysis of Changzhou municipal-level new town, believes that real estate investment has produced significant negative effects. This paper finds that real estate has a positive, but small in intensity, effect on both the city and province scales, quite different from Chen's conclusion [31].…”

Section: City Scalecontrasting

confidence: 99%

“…Important papers are as follows: Review and prospects of the development and planning of new towns in China's Shanghai and Taiwan [19,20], the logic of green development mechanism and space production in China's new towns [21][22][23], China's national new district identification standards [24], and comparative study of South Korea and China, India, and China on the development and planning modes of new towns [25,26]. The second category is about the research on the sustainable development indicators and paths of the new town, including prediction of the potential impacts and risks of the development of new towns by SEA (Environmental Strategic Assessment) and ESIA (Environmental and Social Impact Assessment) [27], scenario prediction for the future development of new towns in Kuwait [28], new town planning methods for sustainable development of public space [29], role of participatory landscape in the sustainable development of new towns [30], forecast of carbon emissions for new town planning by system dynamics [31], measurement of diversity of new towns [32], evaluation of new town development sustainability [33], and new town development and sustainable transition under urban entrepreneurialism in China [34].…”

Section: Literature Reviewmentioning

confidence: 99%

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The Key Factors Driving the Development of New Towns by Mother Cities and Regions: Evidence from China

Zhao

Zhang

2021

IJGI

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As an important carrier of expanded urban spatial growth, new towns have been a “policy tool” for spatial production in the new era and have received long-term and constant attention from circles such as geography, planning, and economics. National new districts constitute a new regional space for China to implement the national strategy and promote the transformation of urban development mode. They are mutually reinforcing with their mother cities and hinterland provinces. Based on the geodetector method, this paper reveals the key factors driving the development of national new districts by mother cities and hinterland provinces and their interaction effects, which provides a basis for municipal and provincial governments to accurately formulate policies to promote the development of new towns by classification. The study shows that, firstly, there are five types of driving factors, that is, all-round driving factors, scale-increasing factors, expansion and quality-improving factors, expertise driving factors, and non-driving factors. The strength and dimension of the driving factors are characterized by prominent heterogeneity; R&D personnel, export and import trade are the key factors to expand the increment, optimize the inventory, and improve the quality; the overall development driving forces are in the order of innovation > opening > industry > investment > population. Secondly, the pairwise interaction between different factors exhibits two-factor enhancement, and the population shows a nonlinear increase in the driving force of investment, openness, and innovation on a provincial scale. Thirdly, according to the driving force of the factors and the interaction between them, suggestions are put forward based on the development stage and key demands for city and provincial governments to make policies for the development of national new districts, to support the establishment of scientific competition and cooperation between new towns and mother cities or regions, and to build a long-term collaborative development mechanism.

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Section: City Scalecontrasting

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

The Key Factors Driving the Development of New Towns by Mother Cities and Regions: Evidence from China

Zhao

Zhang

2021

IJGI

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“…Predicting carbon emissions can also help us better test whether the results of implementing carbon emission reduction policies are ideal and analyze which circumstances the carbon emission reduction effect is better. In recent years, system dynamics models have frequently been used in urban carbon emissions prediction research [25,26] to dynamically simulate the carbon emission trends of various provinces and cities in China under different conditions. It found the most favorable situation for emission reduction and provided new ideas for emission reduction for planning decision-making departments.…”

Section: Prediction Of Carbon Emissions Trendsmentioning

confidence: 99%

Carbon Emissions in the Yellow River Basin: Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors Based on a Logarithmic Mean Divisia Index (LMDI) Decomposition Method

et al. 2022

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The “14th Five-Year Plan” period is a critical period and a window to obtain emission peak and carbon neutrality in China. The Yellow River Basin, a vital location for population activities and economic growth, is significant to China’s emission peak by 2030. Analyzing carbon emissions patterns and decomposing the influencing factors can provide theoretical support for reducing carbon emissions. Based on the energy consumption data from 2000–2019, the method recommended by Intergovernmental Panel on Climate Change (IPCC) is used to calculate the carbon emissions in the Yellow River Basin. The Logarithmic Mean Divisia Index (LMDI) decomposition method decomposes the influence degree of each influencing factor. The conclusions are as follows: First, The Yellow River Basin has not yet reached the peak of carbon emissions. Regional carbon emissions trends are different. Second, Shandong, Shanxi, Henan and Inner Mongolia consistently ranked in the top four in total carbon emissions, with low carbon emission efficiency. Third, Economic development has the most significant contribution to carbon emissions; other factors have various effects on nine provinces.

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“…In the past decades, scholars from different disciplines have conducted a large number of carbon emission governance studies in different regions and on different spatial scales, and the studies mainly focus on the following three categories: low-carbon city indicators, governance methods, and case studies. First, a large number of studies on lowcarbon indicators have been conducted on urban clusters [1][2][3], large cities [4,5], and other large-scale objects, such as research on low-carbon urban assessment [6,7] and carbon emission estimation methods [8,9]. Second, studies on governance methods have proposed some carbon emission governance tools [10,11] or models [12][13][14][15], targeting one aspect, such as production or building, of governance, at the city level [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Carbon Emission Governance Zones at the County Level to Promote Sustainable Development

Peng

et al. 2021

Land

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Low-carbon governance at the county level has been an important issue for sustainable development due to the large contributions to carbon emission. However, the experiences of carbon emission governance at the county level are lacking. This paper discusses 5 carbon emission governance zones for 1753 counties. The zoning is formed according to a differentiated zoning method based on a multi-indicator evaluation to judge if the governance had better focus and had formulated a differentiated carbon emission governance system. According to zoning results, there is 1 high-carbon governance zone, 2 medium-carbon governance zones, and 2 low-carbon zones. The extensive high-carbon governance zone and medium-carbon zones are key governance areas, in which the counties are mainly located in the northern plain areas and southeast coastal areas and have contributed 51.88% of total carbon emissions. This paper proposes differentiated governance standards for each indicator of the 5 zones. The differentiated zoning method mentioned in this paper can be applied to other governance issues of small-scale regions.

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Quantitative analysis of carbon emissions for new town planning based on the system dynamics approach

Cited by 32 publications

References 18 publications

The Key Factors Driving the Development of New Towns by Mother Cities and Regions: Evidence from China

The Key Factors Driving the Development of New Towns by Mother Cities and Regions: Evidence from China

Carbon Emissions in the Yellow River Basin: Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors Based on a Logarithmic Mean Divisia Index (LMDI) Decomposition Method

Carbon Emission Governance Zones at the County Level to Promote Sustainable Development

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