Article
Green & Sustainable Science & Technology
Lu-Xuan Sun, Yin-Shuang Xia, Chao Feng
Summary: The study revealed that global carbon productivity (CP) has been gradually increasing, primarily driven by technological progress. However, there is inequality in carbon productivity between countries with different income levels, with higher-income countries experiencing faster growth. The global potential for reducing CO2 emissions is mainly expected to come from improving management efficiency, followed by technological progress and scale efficiency.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2021)
Article
Environmental Studies
Min Cheng, Yujie Lu, Hang Zhu, Jianzhuang Xiao
Summary: Rapid urbanization in China has turned the construction sector into a major industry for CO2 emissions. A global Malmquist CO2 emissions performance index (GMCPI) has been proposed to evaluate CO2 emission performance of multi-input and multi-output production processes. The study found an overall improvement of 13.6% in CO2 emissions performance in China's construction industry from 2004 to 2016, with technological progress playing a key role. Regional differences in CO2 emissions performance were observed, with the eastern region showing the best performance. Reasons contributing to different levels of CO2 emissions performance in different provinces were explained based on the decomposition of GMCPI.
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
(2022)
Article
Biodiversity Conservation
Yufeng Chen, Rui Zhang, Jiafeng Miao
Summary: By using the meta-frontier super SBM model and the global Malmquist-Luenberger index, this paper explores the marine ecological efficiency and technology gaps among coastal regions in China. The findings reveal that China's coastal regions still have ineffective marine ecological efficiency, significant regional technological heterogeneity, and technological progress as the primary factor affecting marine ecological efficiency.
ECOLOGICAL INDICATORS
(2023)
Article
Development Studies
Jiawei Li, Fangqing Wei, Junfei Chu
Summary: This study combines two methods, general equilibrium efficient frontier data envelopment analysis (GEEFDEA) and meta-frontier Malmquist-Luenberger productivity index (MMLPI), to measure the CO2 emission performance (CEP) of China's provincial-level thermal power industries. The results show that the CEP of China's thermal power industry was good during the sample period, mainly due to technical efficiency gains and technological progress. The study also reveals that the drivers of CEP changes differ between provinces, suggesting the need for tailored policies to improve CEP.
JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT
(2023)
Article
Public, Environmental & Occupational Health
Shen Zhong, Shuqi Liang, Yuxin Zhong, Yunying Zheng, Fengjun Wang
Summary: This paper estimates the innovation efficiency of China's pharmaceutical manufacturing industry in 23 provinces from 2010 to 2020, based on the super-network SBM model and Global-Malmquist index. The results show that there is an increasing trend in the efficiency of both the research and development stage and the economic transformation stage, with the western region showing the most prominent growth.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Computer Science, Artificial Intelligence
Xin Liu, Jingkai Huang
Summary: This paper introduces a new method called virtual frontier DEA model to measure the efficiency of the high-tech industry. The model can decompose the driving force of efficiency change when analyzing the Malmquist productivity index.
Article
Energy & Fuels
Yufeng Chen, Mingxin Chen, Tao Li
Summary: This study establishes a new measurement method using Inverse Data Envelopment Analysis and frontier changes to evaluate China's CO2 emissions reduction. The results show that China's CO2 emissions reduction generally meets expectations, with different regions exhibiting distinct characteristics in emissions reduction. Specific management strategies are recommended for different regions to help them achieve emission reduction goals.
ENERGY STRATEGY REVIEWS
(2021)
Article
Green & Sustainable Science & Technology
Jincheng Lu, Meijuan Li, Zijie Shen
Summary: This study uses an inverse data envelopment analysis method to analyze the realization path of CO2 emission reduction and economic growth targets in China from 2020 to 2030. Results show that the eastern region faces the highest pressure for CO2 emissions reduction, and provincial-level reduction shows a polarized distribution. Increased human and energy resources input in the future is key to achieving the goals of emission reduction and economic development.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Economics
Arnaud Abad, Michell Arias, Paola Ravelojaona
Summary: This paper examines the performance of 20 Ecuadorian petroleum companies from 2014 to 2018 by using pollution-adjusted Malmquist (PM) and Hicks-Moorsteen (PHM) productivity indices within a convex neutral analytical framework. It is the first study to investigate the environmental performance variation of the Ecuadorian oil industry. Unlike previous research, which assumed convexity in the production process, this paper considers possible non-linearities. The PM and PHM indices used in this paper are decomposed to identify the key drivers of economic and pollution-related productivity changes. The assessment of performance change is conducted through a nonparametric enumerative method.
MANAGERIAL AND DECISION ECONOMICS
(2023)
Article
Environmental Sciences
Jun Zheng, Yicheng Ren, Jinkang Yao, Feng Lin, Junjie Shi, Wei Ling, Bangwen Zhu, Weigang Tang, Ling Hu
Summary: Unconventional machining of WEDM plays a significant role in the manufacturing industry. Predictive modeling of energy consumption and CO2 emissions in this method is crucial for achieving energy-saving and emission-reducing goals. This study proposes a predictive model considering process characteristics and validates its accuracy in an example. The findings suggest the influence of cutting fluid substitution, geometric structure angles, thickness, and machine tool auxiliary materials quality on energy consumption.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Mathematics
Chia-Nan Wang, Phi-Hung Nguyen, Thi-Ly Nguyen, Thi-Giang Nguyen, Duc-Thinh Nguyen, Thi-Hoai Tran, Hong-Cham Le, Huong-Thuy Phung
Summary: This research develops a two-stage DEA model to measure the performance efficiency of Vietnam's top 18 seaports. The DEA resampling technique is used to forecast future performance, and the DEA Malmquist model analyzes efficiency improvement. The results indicate that most ports have slightly advanced in technological efficiency.
Article
Environmental Sciences
Ruochong Xu, Dan Tong, Steven J. Davis, Xinying Qin, Jing Cheng, Qinren Shi, Yang Liu, Cuihong Chen, Liu Yan, Xizhe Yan, Huaxuan Wang, Dongsheng Zheng, Kebin He, Qiang Zhang
Summary: The critical role of the iron and steel industry in decarbonizing global energy systems requires refined strategies for climate mitigation. Using a newly developed database, this study explores the differences in age-to-capacity ratio and emissions intensity of individual steelmaking plants worldwide. By targeting specific proportions of plants, regional cost-effective decarbonization strategies are customized. The findings indicate that emissions intensity is a more effective indicator for targeted decarbonization in developing regions, while age-to-capacity ratio is more relevant in developed countries. Transformation towards secondary steelmaking is generally more cost-effective than efficiency improvement, with some regional priorities. This study emphasizes the importance of region-specific indicators and strategies in mitigating steel-related CO2 emissions.
NATURE CLIMATE CHANGE
(2023)
Article
Engineering, Industrial
Tsung-Xian Lin, Zhong-Huan Wu, Jia-Jia Yang
Summary: The paper applies the three-stage network DEA and DEA-Malmquist method to measure the innovation efficiency of the high-tech Manufacturing industry in China from 2009 to 2017. The analysis is divided into two parts, analyzing the innovation efficiency using a three-stage network DEA and evaluating the efficiency of technological innovation dynamically using the DEA-Malmquist index method. The findings show that there is room for improvement in the average innovation efficiency, especially in the basic and applied innovation stages. The development of high technology is unbalanced and insufficient, with innovation mainly driven by the east.
PRODUCTION PLANNING & CONTROL
(2023)
Article
Environmental Sciences
Jiao Li, Tao Ding, Weijun He
Summary: Based on the consideration of space technology differences and time technology progress, this study constructs a decomposition model to analyze the driving factors of PM2.5 emissions in China. The results show that economic activity is the main factor promoting the increase of PM2.5 emissions, but its effect is decreasing, while the inhibitory effect of catch-up effect is increasing. Additionally, different factors have varying impacts at national, regional, and provincial levels, and energy intensity effect, space technology catch-up effect, and time technology catch-up effect are increasingly important in inhibiting PM2.5 emissions.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Haochang Yang, Xuan Zhu
Summary: Green innovation, combining innovation-driven and green development, is a powerful way to overcome resource and environmental constraints in manufacturing industry. The green innovation efficiency in China is relatively low with regional heterogeneity, while the green innovation productivity shows a dynamic evolution with regional differences. The eastern region has high efficiency but low productivity, the central region has low efficiency and productivity, and the western region has high productivity but low efficiency.
Article
Environmental Sciences
Youliang Yan, Jixin Cheng, Yunmin Wang, Yating Li
Summary: The study found that all provinces in China are actively improving their ecological efficiency, and social trust plays a significantly positive role in enhancing regional eco-efficiency, especially in regions with poor legal development.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2021)
Article
Environmental Sciences
Jixin Cheng, Ran Zou, Hongxuan Wang, Zhifei Geng
Summary: This study estimates the shadow price of China's urban industrial wastewater (IWSP) using the non-parametric dual evaluation linear analysis framework, and analyzes its spatiotemporal characteristics and sources of differences. The results show an increasing trend of China's urban IWSP, indicating the significant results and increasing difficulty of emission reduction policies. There are differences among regions and variations in green production processes. IWSP gradually diverges, with regions with lower average shadow prices converging faster. The overall difference of IWSP and intra/inter-regional differences decrease, with the contribution rate of intensity of transvariation becoming the main reason for the imbalanced distribution of IWSP.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Economics
Jun Yang, Jixin Cheng, Ran Zou, Zhifei Geng
Summary: This paper proposes a multi-hierarchy meta-frontier parametric approach to evaluate the industrial SO2 technical efficiency of China's cities. The study finds that most cities have significantly improved their STE values, especially those in central and western China. By optimizing industrial structure and promoting market-oriented reforms, China's industrial SO2 emissions could be reduced.
Article
Green & Sustainable Science & Technology
Jixin Cheng, Lan Xu, Hongxuan Wang, Zhifei Geng, Yunming Wang
Summary: Reducing the cost of carbon emissions reduction is crucial for the low-carbon development of urban agglomerations. This study investigates the dynamic characteristics of the marginal abatement cost (MAC) of CO2 emissions in China's major urban agglomerations. The results show a U-shaped relationship between carbon emission intensity and MAC, with narrowing differences in MAC within most urban agglomerations. The study suggests exploring technology spillover and scale effect to lower the costs of emissions reduction and promote low-carbon development.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2022)
Article
Environmental Sciences
Hanhua Shao, Jixin Cheng, Yuansheng Wang, Xiaoming Li
Summary: This paper examines the impact of urban digital finance on urban low-carbon development in China using data from 281 cities from 2011 to 2019. The empirical results show that digital finance significantly improves urban comprehensive carbon emission performance (CCEP) and has a positive effect on the breadth of coverage, usage depth, and digital support services. Digital finance mainly improves CCEP by promoting green technology innovation and the development of urban tertiary industry.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Economics
Lan Xu, Jun Yang, Jixin Cheng, Hanghang Dong
Summary: This study focuses on the impact of the low-carbon city pilot project in China on the marginal abatement cost of CO2 emissions. The results show that the project has increased the cost of reducing CO2 emissions in pilot cities due to the effects of green technology progress and emissions intensity. In addition, the study finds that the project has a greater impact on small and medium-sized cities and non-resource-based cities.
Article
Environmental Studies
Jun Yang, Ran Zou, Jixin Cheng, Zhifei Geng, Qi Li
Summary: This study constructs a meta-frontier parametric framework combined with the bootstrap method to estimate the industrial environmental technical efficiency (ETE) and pollutants emissions reduction potential of different types of cities in China. The findings show that China's industrial ETE has been continuously improving, with non-resource-based cities having higher ETE than resource-based cities. Industrial ETE also conforms to sigma and beta convergence, indicating a decrease in inequality across the country. Different types of cities should formulate targeted policies according to their resource endowment characteristics.
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)