Estimation of carbon dioxide emission in highway construction: a case study in southwest region of China

Wang, Xianwei; Duan, Zhengyu; Wu, Lingsheng; Yang, Dongyuan

doi:10.1016/j.jclepro.2014.10.030

Cited by 117 publications

(37 citation statements)

References 18 publications

(23 reference statements)

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“…In addition, Wang et al (2015) estimated carbon emissions for three types of projects, namely subgrade, pavement, and bridges and tunnels [6]. The boundary comprises raw material production, material transportation, and onsite construction.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Carbon emission at the material transportation stage could be estimated by using Equation (6). The emission factors are calculated by using Equation (7).…”

Section: Materials Transportationmentioning

confidence: 99%

“…Another hindrance to carbon emission estimation for pavement construction is the scarcity of reliable data [5]. It is worth noting that, recently, Wang et al 's (2015) and Ma et al's (2016) studies presented a list of carbon emission factors for pavement construction in China [6,7]. However, uptake of these factors would face challenges as practitioners have to collect a separate panel of data for the calculation methodology.…”

Section: Introductionmentioning

confidence: 99%

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Measuring Carbon Emissions of Pavement Construction in China

et al. 2016

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While various methodologies for quantifying carbon emissions of pavement construction are developed worldwide, adopting and promoting the existing tools to China's market is found fairly challenging due to institutional constraints. Therefore, the objectives of this study are to propose a methodology for measuring carbon emissions of pavement construction compatible with the fixed pricing systems prevalent in China; and develop an automatic tool for carbon estimations. The total carbon emissions are measured by aggregating emissions of energy consumption and materials used along with four stages, namely material manufacture, transportation, construction, and disposal. A set of composite carbon emission factors for energy and materials was calculated based on existing emission factors with the consideration of the boundaries concerned. The quantity of energy and materials used in pavement construction are obtained through bills of quantity and the fixed price system. The database of the emission factors for energy and materials was embedded into a C# based tool, and validated in a real case.Keywords: carbon emission calculation; pavement construction; China BackgroundIt is predicted that, by 2020, carbon emission of infrastructure projects in China will reach 0.197 billion tons [1]. Pavement construction is one of the significant contributors. According to the China Statistical Yearbook (2012), the numbers of municipal projects including pavement projects under construction and planned were 47097 and 30079, respectively in 2011 [2]; and these numbers are still increasing along with the rapid urbanization. To reduce carbon emissions, quantifying them is of significant importance. While various methodologies are available for quantifying carbon emission of pavement construction worldwide, adopting and promoting the existing tools to China's market is found to be fairly challenging due to the institutional constraints. Research widely recognized that carbon emission calculation varies across different countries due to difference associated with parameters, data source, construction methods and regional conditions [3,4]. This renders the comparison between different countries complex and difficult [4]. Another hindrance to carbon emission estimation for pavement construction is the scarcity of reliable data [5]. It is worth noting that, recently, Wang et al.'s (2015) and Ma et al.'s (2016) studies presented a list of carbon emission factors for pavement construction in China [6,7]. However, uptake of these factors would face challenges as practitioners have to collect a separate panel of data for the calculation methodology.The objectives of this study are to develop a carbon emission calculation methodology with a customized database; and develop an automatic tool for carbon emission estimation. The customized database is compatible with the fixed pricing systems (Dinge) prevalent in China. Therefore, practitioners

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Section: Literature Reviewmentioning

confidence: 99%

“…Carbon emission at the material transportation stage could be estimated by using Equation (6). The emission factors are calculated by using Equation (7).…”

Section: Materials Transportationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring Carbon Emissions of Pavement Construction in China

et al. 2016

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“…Mi et al (2015) assessed the effect of Beijing industry structure on its energy consumption and carbon emissions by optimized input-output model. Wang et al (2015b) estimated the carbon emissions of three construction phases in four highway construction projects of southwest China. However, few studies employed intra-provincial data to make regional comparison (Liu et al 2010;Zhang et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Contrastive analyses of the influence factors of interprovincial carbon emission induced by industry energy in China

Zhou

Zhang

2016

Nat Hazards

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As a major contributor of carbon emission in the world, China should focus on the balance between the universality of development and regional heterogeneity of carbon discharge during the transformation toward low-carbon economy. To reveal the differences among interprovincial industry energy's carbon emissions, some relevant data of carbon emissions in 29 provinces and municipalities during the period of 1996-2012 are selected in this study. Based on the Logarithmic Mean Divisia index decomposition model and hierarchical clustering method, the 29 provinces were clustered in turn by four time intervals according to some indicators, including economic intensity, energy intensity, industry structure, energy structure, demographic effect, and carbon density influence. Research results show that during 1996-2000, economic intensity has a strong positive driving effect on carbon emissions in such eastern provinces as Shanghai, Zhejiang, and Jiangsu, and other seven inland provinces, such as Hunan and Hubei. Demographic effects have strong pulling effects on carbon emissions in municipalities and eastern coastal provinces, and they also exert strong negative effects on carbon emissions in Anhui, Guangxi, Guizhou, and Sichuan in the first three time intervals. During the four periods, highly energy-efficient provinces are Jiangsu, Guangdong, Sichuan, Shandong, Hubei, etc., whose carbon emissions are significantly inhibited by their energy intensity, whereas inefficient provinces are concentrated in western regions, like Guangxi, Hainan, Gansu, Qinghai, Ningxia, Xinjiang, etc.

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“…This reflects the increased attention of using LCA in assessing the environmental burdens of pavements. Most of these papers focused on the implementation of new technologies on pavements construction, the use of recycled materials, and the investigation of various phases of the pavement life cycle rather than improving the applicability and the adequacy of LCA methodology to the pavement problems (Blankendaal et al 2014, Wang et al 2014, Anthonissen et al 2015, Noland and Hanson 2015. The emphasis will be given to recent papers published since the latest literature review conducted by Santero et al in 2011.…”

mentioning

confidence: 99%