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Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction
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Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 14066

Special Issue Editor

Dr. Chengkang Gao

E-Mail Website
Guest Editor
School of Metallurgy, Northeastern University, Shenyang 110819, China
Interests: environmental systems research in process industries; analysis of industrial and regional pollution sources

Special Issue Information

Dear Colleagues,

The process industry, an energy-intensive industry, has high levels of energy consumption and pollutant emissions, resulting in huge amounts of pollutant emissions. Coupled with the energy consumption in this area, this industry creates a large amount of CO2 emissions. Therefore, the environment and climate have become bottlenecks that restrict the sustainable development of the process industry. How to achieve the synergistic reduction of gaseous pollutants and CO2 has become an urgent issue for the process industry. The focus of this Special Issue is to obtain new technologies and ideas in the direction of saving energy and reducing emissions by presenting the most advanced research in order to alleviate the harm caused by the process industry to the environment and the climate.

The scope of this Special Issue will include the establishment of an accounting system and emission inventory of gaseous pollutants and CO2 emissions from process industries. It will also include research applications for energy conservation and emission reduction technologies, such as the adoption of new energy conservation technologies to improve thermal efficiency, the use of clean energy to reduce coal consumption, and the exploration of low-carbon technologies to achieve carbon emission reductions and integrated CO2 utilization.

This Special Issue will accept different types of articles, including research on existing literature, research conducted in the laboratory or in the field, etc. Submissions of interdisciplinary articles, including economic and policy analysis, are also encouraged. The expected impact of this issue is to promote further discussion and research on sustainability in the process industry in order to make a real difference to the environment and climate.

Dr. Chengkang Gao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable development
  • energy conservation and emission reduction
  • process industry
  • emission inventory
  • low carbon technologies
  • clean energy

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Published Papers (7 papers)

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Research

29 pages, 16216 KiB  
Article
Study of Key Parameters and Uncertainties Based on Integrated Energy Systems Coupled with Renewable Energy Sources
by Xin Liu, Yuzhang Ji, Ziyang Guo, Shufu Yuan, Yongxu Chen and Weijun Zhang
Sustainability 2023, 15(23), 16266; https://doi.org/10.3390/su152316266 - 24 Nov 2023
Cited by 1 | Viewed by 833
Abstract
The extensive research and application of integrated energy systems (IES) coupled with renewable energy sources have played a pivotal role in alleviating the problems of fossil energy shortage and promoting sustainability to a certain extent. However, the uncertainty of photovoltaic (PV) and wind [...] Read more.
The extensive research and application of integrated energy systems (IES) coupled with renewable energy sources have played a pivotal role in alleviating the problems of fossil energy shortage and promoting sustainability to a certain extent. However, the uncertainty of photovoltaic (PV) and wind power in IES increases the difficulty of maintaining stable system operation, posing a challenge to long-term sustainability. In addition, the capacity configuration of each device in IES and the operation strategy under different conditions will also significantly impact the operation cost and expected results of the system, influencing its overall sustainability. To address the above problems, this paper establishes an optimization model based on linear programming to optimize the equipment capacity and operation strategy of IES coupled with PV and wind power with the minimum total annual cost as the objective function, thereby promoting economic sustainability. Moreover, an integrated assessment framework, including economic, energy efficiency, and environmental aspects, is constructed to provide a comprehensive assessment of the operation of IES, ensuring a holistic view of sustainability. Finally, taking the IES of an industrial park in Xi’an, China, as the specific case, sensitivity analysis is used to explore the impact of a variety of critical parameters on the equipment capacity and operating strategy. Additionally, the Monte Carlo method is used to explore the impact of source-load uncertainty on the performance of the IES. The results show that the facilitating or constraining relationship between renewable energy access and the cascading utilization of combined heat and power generation (CHP) energy depends on the relative magnitude of the user load thermoelectric ratio to the prime mover thermoelectric ratio. To cope with the negative impact of source-load uncertainty on the stable operation of the IES, the capacities of the electric chiller and absorption chiller should be increased by 4.0% and 5.8%, respectively. It is worth noting that the increase in the penetration rate of renewable energy has not changed the system’s dependence on the grid. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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21 pages, 1737 KiB  
Article
Green Supplier Assessment and Selection for Sea Cucumber (Apostichopus japonicus) Processing Enterprise: Case Study in China
by Anqi Ren, Xintao Zhao, Qi Liu, Lixingbo Yu, Fengfan Han, Fei Jia, Haochen Hou and Ying Liu
Sustainability 2023, 15(21), 15368; https://doi.org/10.3390/su152115368 - 27 Oct 2023
Cited by 3 | Viewed by 1584
Abstract
Green supply chain management is a crucial way to balance economic benefits and environmental impacts. As an important economic aquatic product in China, sea cucumber (Apostichopus japonicus) is facing the dual challenges of economic benefits (profit) and environmental sustainability (material input [...] Read more.
Green supply chain management is a crucial way to balance economic benefits and environmental impacts. As an important economic aquatic product in China, sea cucumber (Apostichopus japonicus) is facing the dual challenges of economic benefits (profit) and environmental sustainability (material input and emission output). Currently, the sea cucumber industry in China lacks a green supplier screening system, resulting in a fragmented pattern of cooperation among enterprises. Core enterprises in the supply chain cannot assume social responsibility to help and guide upstream and downstream enterprises to jointly improve environmental performance. This study focuses on the selection and evaluation of green suppliers for sea cucumber processing enterprises. Firstly, a green supplier assessment indicator system for sea cucumber processing enterprises was established, and the indicator weights were determined by the analytic hierarchy process (AHP) method. Next taking a large sea cucumber processing enterprise in Dalian, China, as an example, the importance level of each index was evaluated by fuzzy comprehensive evaluation (FCE), and the score and ranking of existing suppliers were determined. The validity and practicality of the method were verified. The results show that Supplier 1 (S1) has the highest score, and the price of sea cucumber farming, the cleaner production level of sea cucumber farming, environmental awareness, and long-term cooperation willingness were the most important factors in the selection of green suppliers for sea cucumber processing enterprises, which provides useful clues on the best practice of making sustainable development decisions. With an in-depth understanding of the key factors, suppliers can formulate different prices according to the differences in sales channels to improve the economic deficiencies. Environmental pollution can also be reduced by using clean energy, establishing a recirculating aquaculture system, and using micro-ecological preparations. The conclusions of this study can provide technical support and decision-making suggestions for the application of green supply chain management in China’s aquaculture industry. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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19 pages, 3108 KiB  
Article
Comprehensive Evaluation of Different Heating Modes in Northeast China
by Chengkang Gao, Huan You, Mingyan Tian and Yang Wu
Sustainability 2023, 15(18), 13494; https://doi.org/10.3390/su151813494 - 8 Sep 2023
Cited by 1 | Viewed by 1107
Abstract
Given the freezing temperatures and extended winters, heating is essential for residents living in Northeast China. When selecting the optimum heating mode for the region, various factors are taken into consideration, such as the impact on the environment, financial cost and energy consumption. [...] Read more.
Given the freezing temperatures and extended winters, heating is essential for residents living in Northeast China. When selecting the optimum heating mode for the region, various factors are taken into consideration, such as the impact on the environment, financial cost and energy consumption. However, it is uncertain which heating mode can fulfill all conditions and requirements. In this study, seven heating modes were selected from the national and northeastern heating strategies. A comprehensive index system based on the life cycle theory was developed from the perspectives of energy, the environment, the economy, technology and society. Additionally, a comprehensive evaluation of the seven heating modes was performed using the analytical hierarchy process (AHP) and gray relation analysis. The results of this research showed that, from a complete standpoint, the ground-source heat pump heating mode (HMg) had the best comprehensive benefit, with a correlation of 0.8173, followed by the coal-fired cogeneration heating mode (HMcc), which had the highest correlation degree among the centralized heating modes at 0.6111. Based on the findings of our thorough examination, a recommended scheme made up of HMg, HMcc, the electro-thermal membrane heating mode (HMef), the natural gas boiler room regional central heating mode (HMgrc) and the natural gas boiler room decentralized heating mode (HMgrd) was established. The recommended scheme can provide a theoretical basis for the implementation of clean heating policies in Northeast China. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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17 pages, 8898 KiB  
Article
Analysis of Machine Learning Models for Wastewater Treatment Plant Sludge Output Prediction
by Shuai Shao, Dianzheng Fu, Tianji Yang, Hailin Mu, Qiufeng Gao and Yun Zhang
Sustainability 2023, 15(18), 13380; https://doi.org/10.3390/su151813380 - 6 Sep 2023
Cited by 8 | Viewed by 2840
Abstract
With China’s significant investment in wastewater treatment plants, urban sewage is effectively collected and treated, resulting in a substantial byproduct—sludge. As of 2021, a total of 2827 wastewater treatment plants have been constructed across 31 provinces, municipalities, and autonomous regions in China, with [...] Read more.
With China’s significant investment in wastewater treatment plants, urban sewage is effectively collected and treated, resulting in a substantial byproduct—sludge. As of 2021, a total of 2827 wastewater treatment plants have been constructed across 31 provinces, municipalities, and autonomous regions in China, with a processing capacity of 60.16 billion cubic meters. The production of dry sludge amounts to 14.229 million tons. The treatment and utilization of sludge pose significant challenges. The scientific calculation of sludge production is the basis for the reduction at the source and the design of sludge treatment and energy utilization. It is directly related to the construction scale, structure size, and equipment selection of the sludge treatment and utilization system and affects the operation and environmental management of the sludge treatment system. The wastewater treatment process using microbial metabolism is influenced by various known and unknown parameters, exhibiting highly nonlinear characteristics. These complex characteristics require the use of mathematical modeling for simulations and control. In this study, nine types of machine learning algorithms were used to establish sludge production prediction models. The extreme gradient boosting tree (XGBoost) and random forest models had the best prediction accuracies, with the former having RMSE, MAE, MAPE, and R2 values of 4.4815, 2.1169, 1.7032, 0.0415, and 0.8218, respectively. These results suggested a superiority of ensemble learning models in fitting highly nonlinear data. In addition, the contribution and influence of various input features affecting sludge output were also studied for the XGBoost model, and the daily wastewater inflow volume and surrounding temperature features had the greatest impact on sludge production. The innovation of this study lies in the application of machine learning algorithms to achieve the prediction of sludge production in wastewater treatment plants. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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13 pages, 1170 KiB  
Article
An Environmental Impact Assessment of Largemouth Bass (Micropterus salmoides) Aquaculture in Hangzhou, China
by Haochen Hou, Anqi Ren, Lixingbo Yu, Zhen Ma, Yun Zhang and Ying Liu
Sustainability 2023, 15(16), 12368; https://doi.org/10.3390/su151612368 - 14 Aug 2023
Cited by 13 | Viewed by 2406
Abstract
With the rapid increase in aquaculture production, its role in food safety and nutritional security has become increasingly important, but this has also given rise to environmental problems that cannot be ignored. The largemouth bass (Micropterus salmoides) has become a widely [...] Read more.
With the rapid increase in aquaculture production, its role in food safety and nutritional security has become increasingly important, but this has also given rise to environmental problems that cannot be ignored. The largemouth bass (Micropterus salmoides) has become a widely cultivated and highly economic freshwater farmed species since it was introduced to China in 1983; however, the environmental impacts of its freshwater pond aquaculture process have not yet been elucidated. Here, life cycle assessment (LCA), a decision-making tool that can evaluate and identify environmental issues during production processes, was used to evaluate the environmental performance of the largemouth bass freshwater pond aquaculture process, and a large-scale, commercial company was selected as an example in Hangzhou, China. The results showed that the pond-farming stage and marine aquatic ecotoxicity potential (MAETP) had the largest environmental impacts on the entire aquaculture process. An environmental contribution analysis indicated that electricity (48%) and emissions (23%) were two key factors in the seed-rearing stage, and electricity (60%) and feeds (26%) were two main impact contributors in the pond-farming stage. Improvement measures based on emerging technologies in aquaculture were discussed, namely, clean energies, industrial pond farming, and intelligent feeding strategies, to help with decision making for continuous improvement in the environmental performance of largemouth bass pond farming. Moreover, suggestions for further aquaculture LCA studies in China were summarized, as they will provide a useful reference for promoting the development of China’s aquaculture LCA research and the enrichment of the world’s aquaculture life cycle inventory databases. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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Graphical abstract

17 pages, 950 KiB  
Article
Environmental Performance of China’s Industrial System Considering Technological Heterogeneity and Interaction
by Lei Li, Ruizeng Zhao and Feihua Huang
Sustainability 2023, 15(4), 3425; https://doi.org/10.3390/su15043425 - 13 Feb 2023
Cited by 2 | Viewed by 1515
Abstract
The industrial sector, the backbone of China’s economic development, is a key field that requires environmental management. The purpose of this study is to propose an improved data envelopment analysis (DEA) model to analyze the performance of provincial industrial systems (ISs) from 2011 [...] Read more.
The industrial sector, the backbone of China’s economic development, is a key field that requires environmental management. The purpose of this study is to propose an improved data envelopment analysis (DEA) model to analyze the performance of provincial industrial systems (ISs) from 2011 to 2020 in China. To comprehensively characterize the operational framework of ISs, this study proposes an improved meta-frontier network DEA model. Unlike the existing models, the one proposed in this study not only considers the technical heterogeneity of ISs, but also reflects the interaction between IS subsystems. The empirical analysis yields valuable research findings. First, the overall environmental performance of Chinese ISs is generally low, with an average performance of 0.50, showing a U-shaped trend during the study period. Furthermore, significant regional differences are observed in the environmental performance of Chinese ISs. Second, the average performance of the production subsystem is 0.75, while the average performance of the pollution control subsystem (PTS) is 0.44. The low performance of the PTS pulls down the overall performance of Chinese ISs. Third, the technological level of Chinese ISs is low, with about 50% improvement potential. Finally, targeted suggestions to promote the green development of ISs are proposed on the basis of the empirical results. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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11 pages, 850 KiB  
Article
Comparative Life Cycle Assessment of the Manufacturing of Conventional and Innovative Aerators: A Case Study in China
by Haochen Hou, Haiheng Wang, Anqi Ren, Yun Zhang and Ying Liu
Sustainability 2022, 14(22), 15115; https://doi.org/10.3390/su142215115 - 15 Nov 2022
Cited by 2 | Viewed by 2444
Abstract
China aims to achieve a 50% rate of mechanization for aquaculture by 2025. Aerators are crucial mechanical equipment in aquaculture for increasing yield, but their manufacturing has an environmental impact. Improving the yield and controlling the environmental impacts of aerators in China is [...] Read more.
China aims to achieve a 50% rate of mechanization for aquaculture by 2025. Aerators are crucial mechanical equipment in aquaculture for increasing yield, but their manufacturing has an environmental impact. Improving the yield and controlling the environmental impacts of aerators in China is an important issue have to be considered, as is comparing the environmental impact of manufacturing innovative and conventional aerators. Herein, life cycle assessment (LCA) as a quantitative analysis method was used, and six models of three widely used aerators (impeller, paddle wheel, and wave) were selected as an example to compare the environmental impacts of conventional and innovative aerators from large-scale aerator manufacturing enterprises in Taizhou, China. The results showed that the conventional paddle wheel aerator (SC-1.5) had the largest environmental impact, while the innovative paddle wheel aerator (GSC-1.5) had the lowest environmental impact, reduced by 30%. In addition, the environmental impact of the innovative impeller aerator (SYL-1.5) and wave aerator (GYL-1.5) was less than that of the conventional impeller aerator (YL-1.5) wave aerator (SW-1.5), but only by 0.21% and 0.02%, respectively. Human toxic potential (HTP) made the largest contribution, and the manufacturing of copper wire was critical; the environmental impact was from 96.50% to 98.21% for all material inputs. The contributions of iron and stainless steel were 1.05–1.28% and 0.74–1.04%, respectively. Therefore, conductive materials with excellent environmental performance, such as carbon nanomaterials and nano copper wire, should replace copper wire in aerator manufacturing. The results expand aquaculture life cycle knowledge and could reduce the environmental impacts of aerator manufacturing in China. Full article
(This article belongs to the Special Issue Sustainable Study of Industrial Ecology, Energy Conservation and Emission Reduction)
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