Benefit evaluation of energy-saving and emission reduction in construction industry based on rough set theory

• Autorzy: Zhong Zhengjun , Zhang Xin , Yang Xudong

Identyfikatory

DOI

10.2478/eces-2021-0006

• Języki publikacji: EN

Abstrakty

EN

Achieving energy conservation and emission reduction in the industry is an inevitable way to promote harmony between society and nature and achieve sustainable human development. China’s infrastructure construction industry is developing rapidly. Still, there is a lack of a well-established industry standard for evaluating the potential and level of energy reduction in infrastructure construction. A severe lack of quantitative research on energy-saving and CO₂ outflow decreases the benefits of green development advances. This study takes the energy conservation and outflow decrease of construction waste slurry treatment in Guangdong Province, China, as the background, establishes an evaluation system with three rule levels: social, economic, and environmental, and adopts rough set theory to determine the weights of each index to ensure the objectivity of each index. According to the recommendations of the carbon emission calculation guidelines, select the relevant data to evaluate the energy-saving and emission reduction benefits of the new green construction technology of grouted piles in a road project in Guangdong Province. The results show that the development level and potential of energy saving and emission reduction technology in the construction sector in Guangdong Province are increasing year by year. It’s potential changes with the increase or decrease of highway mileage, and it is an urgent need to increase investment in pollution control. The research results can evaluate the benefits of energy-saving and carbon dioxide emission reduction in the construction industry，also be used as a reference to assess energy-saving and emission reduction in the construction industry in other countries.

Słowa kluczowe

EN

rough set theory; slurry; construction industry; energy-saving; emission reduction; benefit analysis

PL

teoria zbiorów przybliżonych; zawiesina; przemysł budowlany; oszczędzanie energii; redukcja emisji; analiza korzyści

• Wydawca: Towarzystwo Chemii i Inżynierii Ekologicznej
• Czasopismo: Ecological Chemistry and Engineering. S
• Rocznik: 2021
• Tom: Vol. 28, nr 1
• Strony: 61--73
• Opis fizyczny: Bibliogr. 29 poz., tab., wykr., rys.

Twórcy

autor

Zhong Zhengjun

• Shenzhen Engineering Company of CREGC, Shenzhen 518000 China

autor

Zhang Xin

• School of Civil Engineering, Architecture and Environment, Xihua University, Chengdu 610039 China

autor

Yang Xudong

• School of Civil Engineering, Architecture and Environment, Xihua University, Chengdu 610039 China

Bibliografia

• [1] Zhang H, Chen J, Li Y, Seiler MJ. Does the Development of China’s Building Industry Influence the Global Energy Consumption and Carbon Emissions? an Analysis Based on the GVAR Model. Singapore: Springer; 2018. DOI: 10.1007/978-981-10-6190-5_58.
• [2] Governments, USaC. U.S.-China Joint Announcement on Climate Change. 2014. Available from: https://obamawhitehouse.archives.gov/the-press-office/2014/11/11/us-china-joint-announcement-climatechange.
• [3] Jiang J, Ye B, Liu J. Peak of CO2 emissions in various sectors and provinces of China: Recent progress and avenues for further research. Renew Sust Energy Rev. 2019;112:813-33. DOI: 10.1016/j.rser.2019.06.024.
• [4] IPCC (2008). 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Available from: https://www.ipcc.ch/report/2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/.
• [5] IPCC (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Available from: https://www.ipcc.ch/report/2019-refinement-to-the-2006-ipcc-guidelines-for-nationalgreenhouse-gas-inventories/.
• [6] Lin BQ, Xu B. Growth of industrial CO2 emissions in Shanghai city: Evidence from a dynamic vector autoregression analysis. Energy Oxford. 2018;151:167-77. DOI: 10.1016/j.energy.2018.03.052.
• [7] Wen L, Zhang X. CO2 emissions in China’s Yangtze River Economic Zone: A dynamic vector autoregression approach. Pol J Environ Stud. 2019;28:923-33. DOI: 10.15244/pjoes/83668.
• [8] Xu B, Lin BQ. What cause a surge in China’s CO2 emissions? A dynamic vector autoregression analysis. J Clean Prod. 2016;143:17-26. DOI: 10.1016/j.jclepro.2016.12.159.
• [9] Xu B, Lin BQ. Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model. Appl Energy. 2016;161:357-86. DOI: 10.1016/j.apenergy.2015.10.039.
• [10] Hao H, Geng Y, Li W, Guo B. Energy consumption and GHG emissions from China’s freight transport sector: Scenarios through 2050. Energy Policy. 2015;85:94-101. DOI: 10.1016/j.enpol.2015.05.016.
• [11] Shao S, Liu J, Geng Y, Miao Z, Yang Y. Uncovering driving factors of carbon emissions from China’s mining sector. Appl Energy. 2016;166:220-38. DOI: 10.1016/j.apenergy.2016.01.047.
• [12] Huang WL, Yin X, Chen WY. Prospective scenarios of CCS implementation in China’s power sector: An analysis with China TIMES. Energy Procedia. 2014;61:937-40. DOI: 10.1016/j.egypro.2014.11.999.
• [13] Lin B, Moubarak M, Ouyang XL. Carbon dioxide emissions and growth of the manufacturing sector: Evidence for China. Energy. 2014;76:830-7. DOI: 10.1016/j.energy.2014.08.082.
• [14] Shi Q, Chen J, Shen L. Driving factors of the changes in the carbon emissions in the Chinese construction industry. J Clean Prod. 2017;(166):615-27. DOI: 10.1016/j.jclepro.2017.08.056.
• [15] Yang T, Pan Y, Yang Y, Lin M, Qin B, Xu P, et al. CO2 emissions in China’s building sector through 2050: A scenario analysis based on a bottom-up model. Energy. 2017;128:208-23. DOI: 10.1016/j.energy.2017.03.098.
• [16] Ai F, Yin X, Hu R, Ma H, Liu W. Research into the super-absorbent polymers on agricultural water. Agr Water Manage. 2021:106513. DOI: 10.1016/j.agwat.2020.106513.
• [17] Zhang X, Zang C, Ma H, Wang Z. Study on removing calcium carbonate plug from near wellbore by high-power ultrasonic treatment. Ultrason Sonochem. 2020:104515. DOI: 10.1016/j.ultsonch.2019.03.006.
• [18] Mo L, Sun W, Jiang S, Zhao X, Ma H, Liu B, et al. Removal of colloidal precipitation plugging with high-power ultrasound. Ultrason Sonochem. 2020;69:105259. DOI: 10.1016/j.ultsonch.2020.105259.
• [19] Liu W, Ma H, Walsh A. Advance in photonic crystal solar cells. Renew Sust Energy Rev. 2019;116:109436. DOI: 10.1016/j.rser.2019.109436.
• [20] Ma H, Zhang X, Ju F, Tsai SB. A study on curing kinetics of nano-phase modified epoxy resin. Sci Rep. 2018;8. DOI: 10.1038/s41598-018-21208-0.
• [21] Ma H, Tsai SB. Design of research on performance of a new iridium coordination compound for the detection of Hg2+. Int J Env Res Pub HE. 2017;14. DOI: 10.3390/ijerph14101232.
• [22] Yang G, He XL, Li JF, Jia XJ. The research of water resource sustainable utilization in Manas River. Acta Ecologica Sinica. Available from: https://www.oalib.com/paper/1402574.
• [23] Gendron C. Beyond environmental and ecological economics: Proposal for an economic sociology of the environment. Ecol Econ. 2014;105:240-53. DOI: 10.1016/j.ecolecon.2014.06.012.
• [24] Men B, Liu H, Tian W, Liu H. Evaluation of sustainable use of water resources in Beijing based on rough set and fuzzy theory. Water. 2017;9:852. DOI: 10.3390/w10070925.
• [25] Wu X, Wen QB, Hu LM, Liu MY. Evaluation of unconventional water resources based on knowledge granularity. E3S Web Conf. 2020;144(1-3):01004. DOI: 10.1051/e3sconf/202014401004.
• [26] Pawlak Z. Rough sets. Int J Comput Inform Sci. 1982;11:341-56. DOI: 10.1007/BF01001956.
• [27] Pawlak Z. Rough classification. Int J Man Mach Stud. 1984;20:469-83. DOI: 10.1016/S0020-7373(84)80022-X.
• [28] Pawlak Z. Rough sets and intelligent data analysis. Inform Sci. 2002;147:1-12. DOI: 10.1016/S0020-0255(02)00197-4.
• [29] Pawlak Z, Skowron A. Rough sets: Some extensions. Inform Sci. 2007;177:28-40. DOI: 10.1016/j.ins.2006.06.006.

Uwagi

1. This work was supported by the Key Project of Xihua University (Z201036).

2. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).