4.7 Article

Sectoral changing patterns of China's green GDP considering climate change: An investigation based on the economic input-output life cycle assessment model

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 251, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.119764

Keywords

Green GDP; Green accounting; Greenhouse gas emissions; Environmental cost; EIO-LCA model

Funding

  1. Major Program of the National Social Science Foundation of China [14 ZDA070]
  2. Fundamental Research Funds for the Central Universities
  3. 2018 Zhejiang University Academic Award for Outstanding Doctoral Candidates
  4. Zhejiang University's Fund for Doctoral Students to Carry Out International Cooperation Research and Exchange Activity
  5. School of Management's (Zhejiang University) Fund for Doctoral Students to Carry Out International Cooperation Research and Exchange Activity

Ask authors/readers for more resources

The rapid growth of energy-intensive and high-emission industries has underpinned China's economic boom over the past few decades. Since her economic development entered the new normal phase in 2013, China has faced the challenge of mitigating greenhouse gas (GHG) emissions while achieving medium-high economic growth. Transforming the economic development pattern and restructuring the economy is a principal solution, and one important prerequisite is discerning great sectoral disparities of GHG emissions and corresponding environmental costs because the diversity of characteristics among different sectors causes the pollutants that are discharged to vary. Hence, this paper aims to assess the environmental costs of China's total and sectoral GHG emissions. Based on the System of Environmental and Economic Accounts and using the economic input-output life cycle assessment model, this study calculates the green GDP and green output value of 27 sectors to reflect the environmental costs of GHG emissions in China during 1991-2016. The findings are as follows: (1) while China's direct GHG emissions increased from 3,040.60 million tons of carbon dioxide equivalent (MtCO(2)eq) to 10,641.10 MtCO(2)eq during 1991-2014, declining trends were observed in the total and 16 sectors' direct GHG emissions in the subsequent two years; (2) although the ratios of direct GHG emissions to total GHG emissions in most sectors decreased, total GHG emissions in eight sectors rose first and then fell, and in 15 sectors continued to rise; (3) China's green GDP grew from 2,003.88 billion Chinese Yuan to 26,245.25 billion Chinese Yuan during 1991-2016, and the difference between China's GDP and green GDP decreased from 2.73% to 1.02%; and (4) differences between the output value and green output value decreased in over 20 sectors. Finally, some policy implications are given from the perspective of some key sectors of the Manufacturing industry, Agricultural sector, and Transport, storage, and post sector. (C) 2019 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
Article Green & Sustainable Science & Technology

Relative evaluation of probabilistic methods for spatio-temporal wind forecasting

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

Comparison of ethane recovery processes for lean gas based on a coupled model

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

A novel deep-learning framework for short-term prediction of cooling load in public buildings

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

The impact of social interaction and information acquisition on the adoption of soil and water conservation technology by farmers: Evidence from the Loess Plateau, China

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

Study on synergistic heat transfer enhancement and adaptive control behavior of baffle under sudden change of inlet velocity in a micro combustor

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)