The decoupling effect and driving factors of carbon footprint in megacities: The case study of Xi’an in western China

Yang, Yi; Meng, Guanfei

doi:10.1016/j.scs.2018.11.012

Cited by 43 publications

(12 citation statements)

References 21 publications

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“…This has a double target. On the one hand, the main CF driving factors for a certain industrial activity [39] are clearly illustrated; and on the other hand, the research explains the structure and data size that every LCI requires [40].…”

Section: Lci Input Applied To the Scenarios Considered In The Papermentioning

confidence: 99%

Quantifying the Impact of Production Globalization through Application of the Life Cycle Inventory Methodology and Its Influence on Decision Making in Industry

Prado-Galiñanes

Domingo

2021

Processes

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Industries are nowadays not only expected to produce goods and provide services, but also to do this sustainably. What qualifies a company as sustainable implies that its activities must be defined according to the social and ecological responsibilities that are meant to protect the society and the environment in which they operate. From now on, it will be necessary to consider and measure the impact of industrial activities on the environment, and to do so, one key parameter is the carbon footprint. This paper demonstrates the utility of the LCI as a tool for immediate application in industries. Its application shall facilitate decision making in industries while choosing amongst different scenarios to industrialize a certain product with the lowest environmental impact possible. To achieve this, the carbon footprint of a given product was calculated by applying the LCI method to several scenarios that differed from each other only in the supply-chain model. As a result of this LCI calculation, the impact of the globalization of a good’s production was quantified not only financially, but also environmentally. Finally, it was concluded that the LCI/LCA methodology can be considered as a fundamental factor in the new decision-making strategy that sustainable companies must implement while deciding on the business and industrial plan for their new products and services.

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Section: Lci Input Applied To the Scenarios Considered In The Papermentioning

confidence: 99%

Quantifying the Impact of Production Globalization through Application of the Life Cycle Inventory Methodology and Its Influence on Decision Making in Industry

Prado-Galiñanes

Domingo

2021

Processes

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“…To ensure that each selected indicator did affect carbon emissions, the carbon effect analysis of the indicators was conducted for screening the initial indicators. The methods of the logarithmic mean weight division Index (LDMI) model [51], stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, decoupled model [70,71], regression analysis, and correlation analysis [51,64,72] were usually used in previous research to analyze the carbon effects of multi-indicators. Correlation analysis is a more suitable method for judging the correlation between a comprehensive multi-indicator and carbon emissions.…”

Section: Carbon Emission Governance Indicator System For Countiesmentioning

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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“…Xianyang, Baoji, and Wuwei) experienced an emission peak in 2013 or 2014 based on the up-to-date results of this study. These, studying the historical trajectory of CO 2 emissions in these typical cities could be crucial because this process could help cities struggling with tackling climate change to reduce emissions (Dhakal, 2009;Hoornweg et al, 2011;Wang et al, 2008;Yang and Meng, 2019).…”

Section: Total Emissionsmentioning

confidence: 99%

“…Also, coal tends to be more carbon intensive than other fossil fuels like natural gas (Pan et al, 2013). Therefore, energy transition could be another feasible approach to alleviating emissions (Yang and Meng, 2019;Zhuang et al, 2010). However, during the energy transition process, some barriers could occur (Geng et al, 2016;Ren et al, 2015).…”

Section: Emissions By Sectors and Energy Typesmentioning

confidence: 99%

“…When it comes to absolute CO 2 emissions and associated structural patterns in northwestern Chinese cities over time, research gaps are as follows: (1) absolute emissions have not been paid more attention to in CO 2 alleviation than CO 2 intensity (Guan et al, 2017;Li et al, 2016). Further, northwestern Chinese cities have encountered constraints in data availability (Guan et al, 2017;Xie and Fan, 2014) and quality (Xie et al, 2007); (2) spatiotemporal measurements of emissions have not been enough although current researches for other areas have emphasized spatial, temporal or spatiotemporal changes of emissions (Shan et al, 2018;Tong et al, 2018;Xu et al, 2018); (3) detailed comparative analyses across cities have not been sufficient; (4) regarding structural patterns of absolute emissions in light of industrial structure and energy mix, studies have mainly focused on decomposition techniques (Guan et al, 2017), and econometric methods (Yang and Meng, 2019) to gain the relative importance of influential factors, rather than the absolute shares of these factors, in absolute emissions; and (5) although some studies have explored HCE and HCE per capita (Li et al, 2016), and HCE from peasants and herdsmen (Qu et al, 2013), urban-rural disparities in HCE by energy type and HCE per capita by energy type have not been explored.…”

Section: Introductionmentioning

confidence: 99%

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Structural patterns of city-level CO2 emissions in Northwest China

Tian

Shan

Zheng

et al. 2019

Journal of Cleaner Production

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In Northwest China, quantifying city-level CO 2 emissions is fundamental to CO 2 alleviation but encounters difficulties in data availability and quality. Further, structuring citylevel emissions could be conductive to CO 2 reduction. This study applies a practical methodology to 16 northwestern Chinese cities to grasp their historical trajectories of CO 2 emissions. Then, structuring CO 2 emissions is explored in terms of industrial structure, energy mix and urban-rural disparities for 8 northwestern Chinese cities. Results show that: (1) for 16 cities (2010-2015), capital and industrial cities generated most emissions. Meanwhile, CO 2 emissions were mostly incompatible with CO 2 intensity, but consistent with CO 2 per capita; (2) for 8 cities (2006~2015), energy producing sectors, heavy manufacturing sectors, and coal remained major drivers of emissions. Then, the interconnection between industrial structure and energy mix exerted temporally varying impacts on emissions from energy producing sectors and heavy manufacturing sectors. Besides, urban gas consumption and rural coal use continued affecting most of household consumption emissions and household consumption emissions per capita. Moreover, the interplay between emissions and population was changed when emissions by energy type were decomposed among urban and rural households; and (3) uncertainty results averagely fall in the range of-39% to 6%. Finally, implications for CO 2 reduction and future work are proposed. Highlights • CO 2 intensity differs from CO 2 emissions and CO 2 per capita across most cities • Structural changes in CO 2 emissions are city-specific in Northwest China (2006~2015) • Energy producing sectors and coal are still main drivers of emissions • Rural coal use remains a vital concern to curb rural household consumption emissions • The interplay between emissions and household population changes with energy types

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The decoupling effect and driving factors of carbon footprint in megacities: The case study of Xi’an in western China

Cited by 43 publications

References 21 publications

Quantifying the Impact of Production Globalization through Application of the Life Cycle Inventory Methodology and Its Influence on Decision Making in Industry

Quantifying the Impact of Production Globalization through Application of the Life Cycle Inventory Methodology and Its Influence on Decision Making in Industry

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

Structural patterns of city-level CO2 emissions in Northwest China

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