The clean energy development path and sustainable development of the ecological environment driven by big data for mining projects

被引:27
作者
Li, Dandan [1 ,2 ]
Guan, Xin [3 ]
Tang, Tingting [4 ]
Zhao, Luyang [5 ]
Tong, Wenrui [6 ]
Wang, Zeyu [7 ]
机构
[1] Hubei Univ Econ, Collaborat Innovat Ctr Emiss Trading Syst Coconstr, Wuhan 430072, Peoples R China
[2] Hubei Univ Econ, Sch Low Carbon Econ, Wuhan 430205, Peoples R China
[3] Guangzhou Xinhua Univ, Dongguan 523133, Peoples R China
[4] Univ Liverpool, Management Sch, Liverpool L69 7ZX, England
[5] Wuhan Univ, Sch Power & Mech Engn, Wuhan 430072, Peoples R China
[6] Hankou Univ, Mus Sch, Wuhan 430212, Peoples R China
[7] Guangzhou Univ, Sch Publ Adm, Guangzhou 510006, Peoples R China
关键词
Mining projects; Big data; Clean energy development path; Wind energy optimization model; Sensitivity analysis;
D O I
10.1016/j.jenvman.2023.119426
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Clean energy is urgently needed to realize mining projects' sustainable development (SD). This study aims to discuss the clean energy development path and the related issues of SD in the ecological environment driven by big data for mining projects. This study adopts a comprehensive research approach, including a literature review, case analysis, and model construction. Firstly, an in-depth literature review of the development status of clean energy is carried out, and the existing research results and technology applications are explored. Secondly, some typical mining projects are selected as cases to discuss the practice and effect of their clean energy application. Finally, the corresponding clean energy development path and the SD analysis model of the ecological environment are constructed based on big data technology to evaluate the feasibility and potential benefits of promoting and applying clean energy in mining projects. (1) It is observed that under different Gross Domestic Product (GDP) growth rates, the new and cumulative installed capacities of wind energy show an increasing trend. In 2022, under the low GDP growth rate, the cumulative installed capacity of global wind energy was 370.60 Gigawatt (GW), and the new installed capacity was 45 GW. With the high GDP growth rate, the cumulative and new installed capacities were 367.83 GW and 46 GW. As the economy grows, new wind energy capacity is expected to increase significantly by 2030. In 2046, 2047, and 2050, carbon dioxide (CO2) emissions reductions are projected to be 8183.35, 8539.22, and 9842.73 Million tons (Mt) (low scenario), 8750.68, 9087.16, and 10,468.75 Mt (medium scenario), and 9083.03, 9458.86, and 10,879.58 Mt (high scenario). By 2060, it is expected that CO2 emissions reduction will continue to increase. (2) The proposed clean energy development path model has achieved a good effect. Through this study, it is hoped to provide empirical support and decision-making reference for the development of mining projects in clean energy, and promote the SD of the mining industry, thus achieving a win-win situation of economic and ecological benefits. This is of great significance for protecting the ecological environment and realizing the sustainable utilization of resources.
引用
收藏
页数:8
相关论文
共 36 条
  • [1] Powering Mobile Networks with Optimal Green Energy for Sustainable Development
    Alsharif, Mohammed H.
    Albreem, Mahmoud A.
    Jahid, Abu
    Raju, Kannadasan
    Uthansakul, Peerapong
    Nebhen, Jamel
    Chandrasekaran, Venkatesan
    Aly, Ayman A.
    [J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 69 (01): : 661 - 677
  • [2] Production Modeling in the Oil and Natural Gas Industry: An Application of Trend Analysis
    Aydin, G.
    [J]. PETROLEUM SCIENCE AND TECHNOLOGY, 2014, 32 (05) : 555 - 564
  • [3] Are clean energy and carbon emission allowances caused by bitcoin? A novel time-varying method
    Dogan, Eyup
    Majeed, Muhammad Tariq
    Luni, Tania
    [J]. JOURNAL OF CLEANER PRODUCTION, 2022, 347
  • [4] STUDY ON GOVERNMENT SUBSIDY IN A TWO-LEVEL SUPPLY CHAIN OF DIRECT-FIRED BIOMASS POWER GENERATION BASED ON CONTRACT COORDINATION
    Fan, Kun
    Mao, Wenjin
    Qu, Hua
    Li, Xinning
    Wang, Meng
    [J]. JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION, 2023, 19 (04) : 2436 - 2451
  • [5] Measurement and Enhancement of Environmental Responsibility Level of an Energy Enterprise in the Context of Energy Transformation
    Hou, Shanshan
    Tang, Liang
    Xue, Jiuyang
    Lu, Jingnan
    [J]. DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2021, 2021
  • [6] Green financial regulation and shale gas resources management
    Hu, Hui
    Xiong, Shuaizhou
    Wang, Zeyu
    Wang, Zishuo
    Zhou, Xiang
    [J]. RESOURCES POLICY, 2023, 85
  • [7] A Novel Hybrid Fuel Consumption Prediction Model for Ocean-Going Container Ships Based on Sensor Data
    Hu, Zhihui
    Zhou, Tianrui
    Osman, Mohd Tarmizi
    Li, Xiaohe
    Jin, Yongxin
    Zhen, Rong
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (04)
  • [8] Forecasting GHG emissions for environmental protection with energy consumption reduction from renewable sources: A sustainable environmental system
    Huang, Jiaqing
    Wang, Linlin
    Siddik, Abu Bakkar
    Abdul-Samad, Zulkiflee
    Bhardwaj, Arpit
    Singh, Bharat
    [J]. ECOLOGICAL MODELLING, 2023, 475
  • [9] A two-stage planning and optimization model for water-hydrogen integrated energy system with isolated grid
    Huang, Yuansheng
    Shi, Mengshu
    Wang, Weiye
    Lin, Hongyu
    [J]. JOURNAL OF CLEANER PRODUCTION, 2021, 313
  • [10] Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies
    Li, Chengming
    Xu, Yang
    Zheng, Hao
    Wang, Zeyu
    Han, Haiting
    Zeng, Liangen
    [J]. RESOURCES POLICY, 2023, 81