Carbon Footprint Estimation and Sensitive Analysis for Onsite Construction with Quota-Based Carbon Tracing Model

Posted: 28 Jun 2019 Last revised: 16 Oct 2019

See all articles by Yuan Fang

Yuan Fang

Guangdong University of Technology

Date Written: June 27, 2019

Abstract

As the global temperature is on a rise due to global warming, the issue of climate change is indeed a ‘hot’ topic among the climate scientists and policy-makers worldwide. The GHG (Green House Gas) emissions resulting from human activities have been claimed to be the major cause of this development. As a most important part of human’s life, the construction and using of buildings generate a considerable amount of GHG. Many researchers believe that the construction industry contributes significantly to carbon dioxide reduction through cleaner and more sustainable building construction method. This study aims to estimate and analysis the carbon emissions data during buildings’ construction process using quota-based carbon tracing method. Detail study and comparing are carried out on the environmental impact of every unit construction process and construction machines of 12 commercial buildings. The findings show that the relationship of carbon emissions with the construction activities, machines and construction unit process with trend curve based on a large scale of data fitting. Correlation, standard deviation and sensitive analysis are also listed to verify the analysis result and find the most sensitive factor to the carbon emissions. These findings help the project manager to better understand the carbon footprint from on site construction process, and provide useful inputs for policy making in terms of setting up carbon quota during construction bidding stage.

Suggested Citation

Fang, Yuan, Carbon Footprint Estimation and Sensitive Analysis for Onsite Construction with Quota-Based Carbon Tracing Model (June 27, 2019). Abstract Proceedings of 2019 International Conference on Resource Sustainability - Cities (icRS Cities), Available at SSRN: https://ssrn.com/abstract=3410918

Yuan Fang (Contact Author)

Guangdong University of Technology ( email )

No. 100 Waihuan Xi Road
Guangzhou Higher Education Mega Center
Guangzhou, Panyu 510006
China

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