Carbon reduction in cement industry - An indigenized questionnaire on environmental impacts and key parameters of life cycle assessment (LCA) in China.

Life cycle assessment (LCA) is an effective tool to quantitatively assess the environmental impacts of cement products in the whole life cycle. The establishment of the indigenized and recognized weight coefficients of LCA plays an important role in promoting the application and development of LCA in China's cement industry. An online questionnaire survey was carried out across the cement academia and industry of China, and a total of more than 200 valid samples were collected. Descriptive analysis, Chi-square test, multiple response analysis and Pareto chart were then conducted to analyze the real application situation of carbon footprint accounting, LCA and carbon reduction measures in the cement industry. Based on the scoring by senior experts and feedback from cement academic and industry, the analytic hierarchy process was used to determine the weight coefficients of LCA. The findings suggested that the most effective measures to reduce carbon emissions in the cement industry included development of low-carbon cementitious materials, fuel substitution, utilization of alternative raw materials for clinker production, application of carbon capture-utilization-storage (CCUS) and so on. For the cement production stage, the clinker calcination was considered to have the largest potential contribution to reducing the overall environmental impacts of cement, accounting for 39.04%. Further calculation indicated the weight coefficients of abiotic depletion potential (ADP), global warming potential (GWP) and human toxicity potential (HTP) were relatively large, which were 0.3005, 0.2663 and 0.2502, respectively. [Display omitted] • A questionnaire survey was conducted across cement academia and industry of China. • The most effective carbon reduction measures were identified based on Pareto chart. • Relevant experts were participated for determining weight coefficients of LCA by AHP. • The study can help to understand the application of LCA in a statistical way. [ABSTRACT FROM AUTHOR]