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Processes
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Energy Conservation and Emission Reduction in Process Industry
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Energy Conservation and Emission Reduction in Process Industry

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (7 December 2021) | Viewed by 52489

Special Issue Editors

Prof. Dr. Zhiqiang Sun

E-Mail Website
Guest Editor
School of Energy Science and Engineering, Central South University, Changsha 410083, China
Interests: multiphase flow and heat and mass transfer; renewable energy and hydrogen energy; combustion pollution control and emission reduction
Dr. Yi Man

E-Mail Website
Guest Editor
School of Light Industry and Engineering, South China University of Technology, Guangzhou 510006, China
Interests: modeling and simulation of process industry; integration optimization; energy conservation and emission reduction; process systems engineering; process modeling, optimization and integration; life cycle analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Sheng Yang

E-Mail Website
Guest Editor
School of Energy Science and Engineering, Central South University, Changsha 410083, China
Interests: energy system engineering; sustainability assessment with life cycle perspective; process modeling and optimization for energy conservation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The process industry is one of the pillars of social development. At the same time, it is a high-energy intensive industry. Although around the world, the process industry has made considerable progress in recent decades, it is still severely restricted by resource, energy, and environmental problems. Energy conservation and emission reduction are the focus of the process industry, which are guiding the process industry toward sustainable development. For example, simulation models of the production process are being developed to evaluate the energy saving potential and provide guidance for the optimization of production operations to achieve the purposes of energy conservation and emission reduction. However, current research is insufficient for meeting these goals. There are various means of achieving energy conservation and emission reduction in process industry, such as through optimizing raw production materials, developing new production technologies, designing new types of equipment, analyzing the whole industrial chain, etc.

This Special Issue on “Energy Conservation and Emission Reduction in Process Industry” aims to summarize the latest progress in the theory and application of energy conservation and emission reduction in process industry to address the long-term challenge of high-energy consumption and high pollution and promote sustainable development of the process industry. Topics include, but are not limited to:

  • Innovations for sustainable process industry
  • Process modeling and optimization for energy conservation and emission reduction
  • Waste minimization and valorization
  • Sustainable supply chain management for process industry
  • Sustainability assessment with life cycle perspective

Prof. Dr. Zhiqiang Sun
Dr. Yi Man
Dr. Sheng Yang
Guest Editors

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. Processes is an international peer-reviewed open access monthly 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

  • energy conservation
  • energy transition
  • greenhouse gas emissions
  • emission reduction
  • carbon emission mitigation
  • sustainability assessment
  • waste recycling
  • supply chain management

Published Papers (21 papers)

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Editorial

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4 pages, 209 KiB  
Editorial
Special Issue on “Energy Conservation and Emission Reduction in Process Industry”
by Yi Man, Zhiqiang Sun and Sheng Yang
Processes 2022, 10(6), 1168; https://doi.org/10.3390/pr10061168 - 10 Jun 2022
Viewed by 947
Abstract
The process industry is an important pillar industry for national economic and social development and an important support force for sustained economic growth [...] Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)

Research

Jump to: Editorial, Review

13 pages, 8766 KiB  
Article
Identifying Graphite Purity by Weighted Fusion Method
by Xiaoping Xu, Xiangjia Yu, Guangjun Liu and Feng Wang
Processes 2022, 10(2), 416; https://doi.org/10.3390/pr10020416 - 21 Feb 2022
Cited by 1 | Viewed by 1764
Abstract
The purity of graphite often affects its application in different fields. In view of the low efficiency of manual recognition and the omission of features extracted by single convolution neural network, this paper proposes a method for identifying graphite purity using a multi-model [...] Read more.
The purity of graphite often affects its application in different fields. In view of the low efficiency of manual recognition and the omission of features extracted by single convolution neural network, this paper proposes a method for identifying graphite purity using a multi-model weighted fusion mechanism. The ideas suggested in this paper are as follows. On the self-built small sample data set, offline expansion and online enhancement are carried out to improve the generalization ability of the model and reduce the overfitting problem of deep convolution neural networks. Combined with transfer learning, a dual-channel convolution neural network is constructed using the optimized Alex Krizhevsky Net (AlexNet) and Alex Krizhevsky Net 50 (AlexNet50) to extract the deep features of the graphite image. After the weighted fusion of the two features, the Softmax classifier is used for classification. Experimental results show that recognition accuracy after weighted fusion is better than that of single network, reaching 97.94%. At the same time, the stability of the model is enhanced, and convergence speed is accelerated, which proves the feasibility and effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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11 pages, 2023 KiB  
Article
Cognitive Behavioral Model of an Operation Crew in the Main Control Room of a Nuclear Power Plant Based on a State-Oriented Procedure
by Tao Qing, Zhaopeng Liu, Li Zhang, Yaqin Tang, Hong Hu and Shuai Chen
Processes 2022, 10(2), 182; https://doi.org/10.3390/pr10020182 - 18 Jan 2022
Cited by 2 | Viewed by 1458
Abstract
The team’s cognitive behavior plays a crucial role in dealing with accidents at nuclear power plants. Herein, the main behaviors of reactor operators and coordinators in performing accident management were analyzed in executing a state-oriented procedure. According to these cognitive behavioral characteristics, we [...] Read more.
The team’s cognitive behavior plays a crucial role in dealing with accidents at nuclear power plants. Herein, the main behaviors of reactor operators and coordinators in performing accident management were analyzed in executing a state-oriented procedure. According to these cognitive behavioral characteristics, we established cognitive behavioral models of accident management procedures. After that, a cognitive behavioral model was established for the team in the main control room of the nuclear power plant based on the two models, which is expected to provide support to the optimization of a corresponding Human Reliability Analysis model. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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15 pages, 938 KiB  
Article
How Environmental Knowledge and Green Values Affect the Relationship between Green Human Resource Management and Employees’ Green Behavior: From the Perspective of Emission Reduction
by Shaoying Zhu, Yuxin Wu and Qian Shen
Processes 2022, 10(1), 38; https://doi.org/10.3390/pr10010038 - 25 Dec 2021
Cited by 16 | Viewed by 4222
Abstract
Green human resource management (GHRM) determines the green behavior practice of employees and affects the social environment and the realization of “Beautiful China” and “Green Development”. In this study, to explore the impact mechanism of GHRM on employees’ green behavior, employees at all [...] Read more.
Green human resource management (GHRM) determines the green behavior practice of employees and affects the social environment and the realization of “Beautiful China” and “Green Development”. In this study, to explore the impact mechanism of GHRM on employees’ green behavior, employees at all levels in an enterprise were selected to be research subjects and a regulated intermediary model was established, based on social exchange theory and the individual-environment matching theory. This paper investigated the enterprise’s GHRM, personal green behavior, relational psychological contract, environmental knowledge and green values. The results show that GHRM has a significant positive predictive effect on employees’ green behavior, the relational psychological contract plays an intermediary role between GHRM and employees’ green behavior and the intermediary role of the relational psychological contract is regulated by environmental knowledge and green values. These research results explain the relationship between GHRM and employees’ green behavior and provide an important basis for enterprises to implement GHRM practice and promote employees’ green behavior. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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11 pages, 1050 KiB  
Article
Coordinated Development of Water Environment Protection and Water Ecological Carbon Sink in Baiyangdian Lake
by Yanli Li, Jinxu Lv and Lijun Li
Processes 2021, 9(11), 2066; https://doi.org/10.3390/pr9112066 - 18 Nov 2021
Cited by 4 | Viewed by 1797
Abstract
“The Hebei Xiongan New Area Planning Outline” states that the carbon sink of the water body should be improved and the quality of Baiyangdian water should be improved by cleaning the sludge, but the treatment of endogenous pollution in the water body will [...] Read more.
“The Hebei Xiongan New Area Planning Outline” states that the carbon sink of the water body should be improved and the quality of Baiyangdian water should be improved by cleaning the sludge, but the treatment of endogenous pollution in the water body will release a large amount of carbon dioxide, which will reduce the carbon sink of Baiyangdian, which makes the improvement of water body quality and increasing carbon sink conflicting. In order to realize the coordinated development of Baiyangdian water quality improvement and carbon sink increase, this paper establishes the calculation model of the amount of sludge to be cleared to improve the unit water quality and the amount of carbon dioxide released by clearing the silt using the release flux and diffusion flux of nitrogen and phosphorus elements in the water body, and the relationship between the content of nitrogen and phosphorus elements, the depth of Baiyangdian sludge excavation and the amount of carbon dioxide released: as the content of nitrogen and phosphorus elements in the water decreases, the depth of sludge excavated to improve the unit water body increases, and the amount of carbon dioxide released gradually increases. As the nitrogen and phosphorus content in the water decreases, the depth of dredged sludge to improve the quality of the water body increases, the carbon dioxide released gradually increases, and when the nitrogen and phosphorus concentration reaches 0.18 g/m3 and 0.6 g/m3 respectively, the carbon dioxide released will increase exponentially. Thus, we propose countermeasures to improve the water quality of Baiyangdian and increase the carbon sink capacity: we can improve the water quality by reasonable dredging before the water quality reaches poor category 3; we can achieve the dual goals of improving the water quality and increasing the carbon sink by increasing the reed planting area. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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12 pages, 3169 KiB  
Article
Influencing Factors on the Accuracy of Soil Calibration Models by EDG
by Haoming Yang, Xiaoping Yang, Min Zhang and Jiaojian Hou
Processes 2021, 9(11), 1892; https://doi.org/10.3390/pr9111892 - 22 Oct 2021
Cited by 2 | Viewed by 1330
Abstract
Compaction is an important standard in evaluating the quality of earth filling work. The EDG, an electrical density gauge, is a new type of fast and nondestructive compaction detection equipment. It is used to test the dry density and water content of the [...] Read more.
Compaction is an important standard in evaluating the quality of earth filling work. The EDG, an electrical density gauge, is a new type of fast and nondestructive compaction detection equipment. It is used to test the dry density and water content of the soil by establishing a soil calibration model while the accuracy of measurement is mainly based on the precision of equation of calibration model. In this paper, the factors affecting the accuracy of the soil calibration model were studied by an indoor calibration test, and soil samples were prepared to verify the accuracy of the soil calibration model. The test results showed that the dry density range, water content range, and sample quantity 13 samples of soil had a significant influence on the correlation coefficient (R2) of the equation of the soil calibration model. In addition, when using the calibration model with different sample numbers and sample combinations but similar correlation coefficients to test multiple groups of density and moisture content, there are also differences in the expected value and standard deviation of the error probability curve of the test results. In the engineering practice, the reasonable sample quantity was determined by the applicable range of dry density and water content obtained from the measurement error analysis of the soil calibration model. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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15 pages, 8743 KiB  
Article
Ecological Restoration of Wetland Polluted by Heavy Metals in Xiangtan Manganese Mine Area
by Yang Lin, Yunan Jiao, Meifang Zhao, Guangjun Wang, Deming Wang, Wei Xiao, Huajun Li, Zhuo Xu and Yuqi Jiang
Processes 2021, 9(10), 1702; https://doi.org/10.3390/pr9101702 - 23 Sep 2021
Cited by 6 | Viewed by 2584
Abstract
Due to manganese mining and slag accumulation, the geological structure of the wetland polluted by heavy metals in Xiangtan Manganese Mine area was seriously damaged, hence biodiversity loss, severe soil, and water pollution, as well as serious heavy metal pollution to food, vegetables, [...] Read more.
Due to manganese mining and slag accumulation, the geological structure of the wetland polluted by heavy metals in Xiangtan Manganese Mine area was seriously damaged, hence biodiversity loss, severe soil, and water pollution, as well as serious heavy metal pollution to food, vegetables, and other natural sources. In order to restore the ecological environment of the mining area, in 2015, the ecological restoration test of heavy metal polluted wetlands in the mining area was carried out. The results showed that the Mn content of different parts of Koelreuteria paniculata root from high to low order: fine root > small root > medium root > large root. The Mn content of different parts of Elaeocarpus decipiens root from high to low order: large root > medium root > small root > fine root. The order of Mn content in plants of the wetland restoration from high to low is as follows: Canna warscewiezii > Thalia dealbata > Boehmeria > Pontederia cordata > Typha orientalis > Nerium oleander > Softstem bulrush > Iris germanica > Acorus calamus > Arundo donax > Phragmites australis; The order of Internal Cu content from high to low is as follows: Acorus calamus > Thalia dealbata > Softstem bulrush > Canna warscewiezii > Typha orientalis > Arundo donax > Boehmeria > Iris germanica > Pontederia cordata > Nerium oleander > Phragmites australis; Zn content from high to low order is as follows: Canna warscewiezii > Acorus calamus > Thalia dealbata > Typha orientalis > Pontederia cordata > Arundo donax > Softstem bulrush > Iris germanica > Boehmeria > Phragmites australis > Nerium oleander; Cd content from high to low order is as follows: Phragmites australis > Softstem bulrush > Thalia dealbata > Nerium oleander > Boehmeria > Canna warscewiezii > Acorus calamus > Iris germanica > Typha orientalis > Pontederia cordata > Arundo donax. The results of this study have provided a theoretical basis and decision-making reference for the evaluation of heavy metals polluted wetland restoration, protection, and reconstruction effects and the selection of ecological restoration modes. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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14 pages, 380 KiB  
Article
How Does Environmental Regulation Affect the Relationship between FDI and Technological Innovation: From the Perspective of Technology Transactions
by Meng Zeng, Lihang Liu, Fangyi Zhou and Yigui Xiao
Processes 2021, 9(8), 1264; https://doi.org/10.3390/pr9081264 - 22 Jul 2021
Cited by 6 | Viewed by 1750
Abstract
Many studies have found that FDI can reduce the pollutant emissions of host countries. At the same time, the intensity of environmental regulation would affect the emission reduction effect of FDI in the host country. This study aims to reveal the internal mechanisms [...] Read more.
Many studies have found that FDI can reduce the pollutant emissions of host countries. At the same time, the intensity of environmental regulation would affect the emission reduction effect of FDI in the host country. This study aims to reveal the internal mechanisms of this effect. Specifically, this paper studies the impact of FDI on technological innovation in China’s industrial sectors from the perspective of technology transactions from 2001 to 2019, and then analyzes whether the intensity of environmental regulation can promote the relationship. Results indicate that FDI promotes technological innovation through technology transactions. In addition, it finds that the intensity of environmental regulation significantly positively moderates the relationship between FDI and technological innovation, which is achieved by positively moderating the FDI–technology transaction relationship. Regional heterogeneity analysis is further conducted, and results show that in the eastern and western regions of China, FDI can stimulate technological innovation within regional industrial sectors through technology trading. Moreover, environmental regulation has a significant positive regulatory effect on the above relationship, but these effects are not supported by evidence in the central region of China. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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11 pages, 1634 KiB  
Article
Synergic Effect of Adsorption and Biodegradation by Microsphere Immobilizing Bacillus velezensis for Enhanced Removal Organics in Slaughter Wastewater
by Jing Deng, Qijue Chen, Boyong Hu, Wen Li, Mingxi Jia, Yi Shi, Shouyao Xiong, Jie Bai and Huaqun Yin
Processes 2021, 9(7), 1145; https://doi.org/10.3390/pr9071145 - 30 Jun 2021
Cited by 6 | Viewed by 1602
Abstract
Bacterial cell immobilization offers considerable advantages over traditional biotreatment methods using free bacteria. Bacillus velezensis was underwented isolation and genetic identification as COD-degrading bacteria in slaughter wastewaterand immobilized on the surface of polyvinyl alcohol (PVA) microsphere with the adhesion to bio-carrier through direct [...] Read more.
Bacterial cell immobilization offers considerable advantages over traditional biotreatment methods using free bacteria. Bacillus velezensis was underwented isolation and genetic identification as COD-degrading bacteria in slaughter wastewaterand immobilized on the surface of polyvinyl alcohol (PVA) microsphere with the adhesion to bio-carrier through direct physical adsorption. The removal CODMn rates of microsphere (PVA) immobilized cells were 16.99%, increased 9.38% from a 50% concentration of slaughter wastewater within 24 h at 37 °C, pH 7.0, and 120 rpm, which was about 2.2 times that of the free bacteria. A significant difference was found in two groups (p < 0.01 p value less than 0.01 means statistical significance), and the COD degradation rate of the microsphere immobilized Bacillus velezensis strain was higher than the control group (PVA: control vs 20.08: 10.81), with the processing time reaching 36 h (p < 0.05). Additionally, similar results were obtained from a 20% concentration of slaughter wastewater within 24 h and 36 h. Moreover, the starch and protein digestibility of the immobilized Bacillus velezensis strain was higher than that of the free bacteria (20.1%: 42.2% vs. 17.5%: 37.2%). These findings revealed that the PVA-bacteria system was a simple, green, and inexpensive process, as well as a promising method. The research goal is aimed to synergize the effects of adsorption and biodegradation, as it can enhance organic removal by immobilized Bacillus velezensis in slaughter wastewater. Moreover, it may be possible that more potential materials can be used as biological carriers for the immobilization of bacterial cells later, which is beneficial for the recycling of resources. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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11 pages, 3287 KiB  
Article
Theoretical Estimation of Evaporation Heat in Paper Drying Process Based on Drying Curve
by Xiaobin Chen, Qifu Zheng and Yunyuan Dong
Processes 2021, 9(7), 1117; https://doi.org/10.3390/pr9071117 - 28 Jun 2021
Cited by 5 | Viewed by 3017
Abstract
At present, the theoretical estimation of paper web’s evaporation heat is based on sorption isothermals. The measuring conditions are harsh, and the test speed is slow. This paper attempts to explore a theoretical method which can quickly determine the evaporation heat of paper [...] Read more.
At present, the theoretical estimation of paper web’s evaporation heat is based on sorption isothermals. The measuring conditions are harsh, and the test speed is slow. This paper attempts to explore a theoretical method which can quickly determine the evaporation heat of paper web. During the new method, based on the measurement of the paper drying curve, the theoretical estimation model of paper evaporation heat was obtained by deducing the mechanism of heat and mass transfer. Compared with the traditional method based on sorption isothermals, the new model based on the drying curve has some advantages in measurement speed and easy access to basic data. Finally, the paper verifies the reliability of the model from two application scenarios of the laboratory and production line. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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19 pages, 2303 KiB  
Article
Analysis of Cadmium-Stress-Induced microRNAs and Their Targets Reveals bra-miR172b-3p as a Potential Cd2+-Specific Resistance Factor in Brassica juncea
by Lili Liu, Hanqi Yin, Yanhui Liu, Lunhao Shen, Xiaojun Yang, Dawei Zhang, Mei Li and Mingli Yan
Processes 2021, 9(7), 1099; https://doi.org/10.3390/pr9071099 - 24 Jun 2021
Cited by 10 | Viewed by 1758
Abstract
The contamination of soil with high levels of cadmium (Cd) is of increasing concern, as Cd is a heavy metal element that seriously limits crop productivity and quality, thus affecting human health. (1) Background: Some miRNAs play key regulatory roles in response to [...] Read more.
The contamination of soil with high levels of cadmium (Cd) is of increasing concern, as Cd is a heavy metal element that seriously limits crop productivity and quality, thus affecting human health. (1) Background: Some miRNAs play key regulatory roles in response to Cd stress, but few have been explored in the highly Cd-enriched coefficient oilseed crop, Brassica juncea. (2) Methods: The genome-wide identification and characterization of miRNAs and their targets in leaves and roots of Brassica juncea exposed to Cd stress was undertaken using strand specific transcript sequencing and miRNA sequencing. (3) Results: In total, 11 known and novel miRNAs, as well as 56 target transcripts, were identified as Cd-responsive miRNAs and transcripts. Additionally, four corresponding target transcripts of six miRNAs, including FLA9 (Fasciclin-Like Arabinogalactan-protein 9), ATCAT3 (catalase 3), DOX1 (dioxygenases) and ATCCS (copper chaperone for superoxide dismutase), were found to be involved in the plant’s biotic stress pathway. We further validated the expression of three miRNA and six target genes in response to Cd, hydrargyrum (Hg), manganese (Mn), plumbum (Pb) or natrium (Na) stress and Mucor infection by qRT-PCR, and show that ATCCS and FLA9 were significantly and differentially regulated in the Cd-treated leaves. In addition, our results showed that DOX1 was obviously induced by Pb stress. Among the respective target miRNAs, bra-miR172b-3p (target for ATCCS) and ra-miR398-3p (target for FLA9) were down-regulated in Cd-treated leaves. (4) Conclusions: We identified bra-miR172b-3p as a potential Cd-specific resistant inhibitor, which may be negatively regulated in ATCCS in response to Cd stress. These findings could provide further insight into the regulatory networks of Cd-responsive miRNA in Brassica juncea. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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13 pages, 1194 KiB  
Article
A Method to Reduce Steam Consumption of ECF Bleaching Based on Operation Optimizing
by Shaoxu Chen, Zhichao Ma, Jiang Liu, Jingjing Yang, Yongjun Yin and Lei Zhan
Processes 2021, 9(6), 928; https://doi.org/10.3390/pr9060928 - 25 May 2021
Cited by 2 | Viewed by 2260
Abstract
Development of paper industry has been restricted by resources, energy and environment deeply; further reducing energy consumption becomes an urgent problem to be solved. In this paper, the calculating model of steam consumption in bleaching process is established under the premise of ensuring [...] Read more.
Development of paper industry has been restricted by resources, energy and environment deeply; further reducing energy consumption becomes an urgent problem to be solved. In this paper, the calculating model of steam consumption in bleaching process is established under the premise of ensuring product quality and controlling bleaching cost. Then, an optimization model for minimizing steam consumption is constructed. Compared with before optimization, the steam consumption of the optimized bleaching system reduced by 19.48% (0.5014 t/adt) at a loss of 0.11% brightness (0.1 ISO%) and 5.17% viscosity (33 mL/g). The amount of chemicals should be increased to ensure the quality of the pulp while decreasing the bleaching temperature to reduce steam consumption, the cost of bleaching pulp has decreased by 1.62% (3.19 USD/adt) after optimization. The verification experiments showed all the pulp quality indices can meet the requirements of bleached pulp. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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18 pages, 24371 KiB  
Article
Intergenerational Externalities Influence for Exploitation Process of Rare Metal Minerals
by Shijie Ding, Mengxian Wang and Hongwei Zhang
Processes 2021, 9(5), 883; https://doi.org/10.3390/pr9050883 - 18 May 2021
Cited by 2 | Viewed by 1823
Abstract
Rare metal minerals are important strategic resources. Promoting the sustainable development of their mining process is not only related to energy and environmental issues, but also directly affects the sustainable development of the entire supply chain. Considering the influence of intergenerational externalities on [...] Read more.
Rare metal minerals are important strategic resources. Promoting the sustainable development of their mining process is not only related to energy and environmental issues, but also directly affects the sustainable development of the entire supply chain. Considering the influence of intergenerational externalities on the equilibrium in the rare metal mineral exploitation process is of critical significance to maintaining the sustainable development of rare metal minerals and securing a sustainable resource exploitation process. This paper develops a sustainability analysis model based on an intergenerational externalities influence and examines the influence of the shift in comprehensive production cost burden through the whole supply chain, which aims at the sustainable development of the exploitation process of rare metal minerals. The results indicate that in a vertically linked industrial chain, the upstream and downstream structure of the supply chain and the type of production cost are the factors that determine sustainable development. Upstream suppliers or countries should design their production systems based on their own circumstances. Specifically, when an upstream country has a low technological level for mineral exploitation processes and high development costs, a resource tax would be more effective in mediating sustainable development. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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23 pages, 8223 KiB  
Article
Machine Learning Based Optimization Model for Energy Management of Energy Storage System for Large Industrial Park
by Ying Gao, Jigeng Li and Mengna Hong
Processes 2021, 9(5), 825; https://doi.org/10.3390/pr9050825 - 09 May 2021
Cited by 18 | Viewed by 3146
Abstract
Renewable energy represented by wind energy and photovoltaic energy is used for energy structure adjustment to solve the energy and environmental problems. However, wind or photovoltaic power generation is unstable which caused by environmental impact. Energy storage is an important method to eliminate [...] Read more.
Renewable energy represented by wind energy and photovoltaic energy is used for energy structure adjustment to solve the energy and environmental problems. However, wind or photovoltaic power generation is unstable which caused by environmental impact. Energy storage is an important method to eliminate the instability, and lithium batteries are an increasingly mature technique. If the capacity is too large, it would cause waste and cost would increase, but too small capacity cannot schedule well. At the same time, the size of energy storage capacity is also constrained by power consumption, whereas large-scale industrial power consumption is random and non-periodic. This is a complex problem which needs a model that can not only dispatch but also give a reasonable storage capacity. This paper proposes a model considering the cycle life of a lithium battery and the installation parameters of the battery, and the electricity consumption data and photovoltaic power generation data of an industrial park was used to establish an energy management model. The energy management system aimed to reduce operating costs and obtain optimal energy storage capacity, which is constrained by lithium battery performance and grid demand. With the operational cost and reasonable battery capacity as the optimization objectives, the Deep Deterministic Policy Gradient (DDPG) method, the greedy dynamic programming algorithm, and the genetic algorithm (GA) were adopted, where the performance of lithium battery and the requirement of power grid were the constraints. The simulation results show that compared with the current forms of energy, the three energy management methods reduced the cost of capacity and operating of the energy storage system by 18.9%, 36.1%, and 35.9%, respectively. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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18 pages, 4490 KiB  
Article
Machine Learning-Based Energy System Model for Tissue Paper Machines
by Huanhuan Zhang, Jigeng Li and Mengna Hong
Processes 2021, 9(4), 655; https://doi.org/10.3390/pr9040655 - 09 Apr 2021
Cited by 5 | Viewed by 2037
Abstract
With the global energy crisis and environmental pollution intensifying, tissue papermaking enterprises urgently need to save energy. The energy consumption model is essential for the energy saving of tissue paper machines. The energy consumption of tissue paper machine is very complicated, and the [...] Read more.
With the global energy crisis and environmental pollution intensifying, tissue papermaking enterprises urgently need to save energy. The energy consumption model is essential for the energy saving of tissue paper machines. The energy consumption of tissue paper machine is very complicated, and the workload and difficulty of using the mechanism model to establish the energy consumption model of tissue paper machine are very large. Therefore, this article aims to build an empirical energy consumption model for tissue paper machines. The energy consumption of this model includes electricity consumption and steam consumption. Since the process parameters have a great influence on the energy consumption of the tissue paper machines, this study uses three methods: linear regression, artificial neural network and extreme gradient boosting tree to establish the relationship between process parameters and power consumption, and process parameters and steam consumption. Then, the best power consumption model and the best steam consumption model are selected from the models established by linear regression, artificial neural network and the extreme gradient boosting tree. Further, they are combined into the energy consumption model of the tissue paper machine. Finally, the models established by the three methods are evaluated. The experimental results show that using the empirical model for tissue paper machine energy consumption modeling is feasible. The result also indicates that the power consumption model and steam consumption model established by the extreme gradient boosting tree are better than the models established by linear regression and artificial neural network. The experimental results show that the power consumption model and steam consumption model established by the extreme gradient boosting tree are better than the models established by linear regression and artificial neural network. The mean absolute percentage error of the electricity consumption model and the steam consumption model built by the extreme gradient boosting tree is approximately 2.72 and 1.87, respectively. The root mean square errors of these two models are about 4.74 and 0.03, respectively. The result also indicates that using the empirical model for tissue paper machine energy consumption modeling is feasible, and the extreme gradient boosting tree is an efficient method for modeling energy consumption of tissue paper machines. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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11 pages, 1999 KiB  
Article
Permeability Evolution of Naturally Fractured Coal Injected with High-Temperature Nitrogen: Experimental Observations
by Shengcheng Wang, Haijian Li and Lanying Huang
Processes 2021, 9(2), 296; https://doi.org/10.3390/pr9020296 - 03 Feb 2021
Cited by 3 | Viewed by 1455
Abstract
The permeability of more than 70% of coal seams in China is less than 1 mD, creating difficulties in recovering underground coal methane. Therefore, a new technology of high-temperature nitrogen (HTN2) injection into the coal seam was proposed to improve the [...] Read more.
The permeability of more than 70% of coal seams in China is less than 1 mD, creating difficulties in recovering underground coal methane. Therefore, a new technology of high-temperature nitrogen (HTN2) injection into the coal seam was proposed to improve the coal permeability and gas extraction rate. In this paper, the effects of the N2 temperature, injection pressure and cycle number on the permeability of naturally fractured coking coal has been investigated. When HTN2 was injected into coal samples, the results indicated that the permeability decreased over time in the beginning, suddenly increased to a large value, and was subsequently maintained in a relatively stable range. The maximum permeability ratio increased with the rise of the N2 temperature and injection pressure. An analysis indicated that the increase of coal permeability was the result of the increase of the global coal strain caused by thermal expansion and the adsorption-induced expansion. The maximum permeability ratios in various cycles of multicycle N2 injection into the coal sample were all greater than 1.0 while progressively declining. Obviously, the alternating stress was conducive to the further expansion of the coal fractures to increase the coal permeability. However, on the basis of the first period of expansion, re-expansion was difficult and required more energy. The effects of multicycle N2 injection on coal permeability have been considerably improved when compared with N2 injection with only one cycle. The research results are helpful for rapidly extracting methane and guaranteeing mine safety. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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24 pages, 17366 KiB  
Article
Energy Saving for Tissue Paper Mills by Energy-Efficiency Scheduling under Time-of-Use Electricity Tariffs
by Zhiqiang Zeng, Xiaobin Chen and Kaiyao Wang
Processes 2021, 9(2), 274; https://doi.org/10.3390/pr9020274 - 31 Jan 2021
Cited by 7 | Viewed by 2747
Abstract
Environmental concerns and soaring energy prices have brought huge pressure of energy saving and emission reduction to tissue paper mills. Electricity is one of the main energy sources of tissue paper mills. The production characteristics of tissue paper mills make it easy to [...] Read more.
Environmental concerns and soaring energy prices have brought huge pressure of energy saving and emission reduction to tissue paper mills. Electricity is one of the main energy sources of tissue paper mills. The production characteristics of tissue paper mills make it easy to decrease energy cost by using time-of-use (TOU) electricity tariffs. This study investigates the bi-objective energy-efficiency scheduling of tissue paper mills under time-of-use electricity tariffs, the objectives of which are makespan and energy cost. First, considering the processing energy cost, setup energy cost, and transportation energy cost, an energy cost model of a tissue paper mill under TOU electricity tariffs is established. Second, the energy-efficiency scheduling model under TOU electricity tariffs is built based on the energy cost model. Finally, on the basis of decomposition and teaching–learning optimization, this study proposes a novel multi-objective evolutionary algorithm and further combined with the variable neighborhood search to solve the problem. The case study results demonstrate that our study of tissue paper mill energy saving is feasible, and the proposed method has better performance than the existing methods. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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14 pages, 37471 KiB  
Article
Effects of Flow Velocity on Transient Behaviour of Liquid CO2 Decompression during Pipeline Transportation
by Chenghuan Xiao, Zhaijun Lu, Liguo Yan, Jiaqiang Wang and Shujian Yao
Processes 2021, 9(2), 192; https://doi.org/10.3390/pr9020192 - 20 Jan 2021
Cited by 6 | Viewed by 1984
Abstract
Investigating the transient behaviour of liquid CO2 decompression is of great importance to ensure the safety of pipeline transportation in carbon capture and storage (CCS) technology. A computational fluid dynamics (CFD) decompression model based on the non-equilibrium phase transition and Span–Wagner equation [...] Read more.
Investigating the transient behaviour of liquid CO2 decompression is of great importance to ensure the safety of pipeline transportation in carbon capture and storage (CCS) technology. A computational fluid dynamics (CFD) decompression model based on the non-equilibrium phase transition and Span–Wagner equation of state (EoS) was developed to study the effects of actual flowing state within the pipeline on the transient behaviour of liquid CO2 decompression. Then, the CFD model was verified by comparing the simulated results to test data of a large-scale “shock tube” with an inner diameter of 146.36 mm. The results showed that the evaporation coefficient had a significant impact on the transition behaviour of CO2 decompression, while the condensation coefficient made no difference. When the evaporation coefficient was 15 s−1, the CFD-predicted results were in good agreement with the test results. Moreover, the effects of flow velocity on transient behaviour of liquid CO2 decompression were further investigated. It was found that the flow velocity affected the temperature drop of liquid CO2 during decompression, thereby affecting the phase transition of liquid CO2. In addition, the initial flow velocity also showed a significant influence on the transient behaviour of CO2 outside the pipe. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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18 pages, 2853 KiB  
Article
Investigation on the Performance Enhancement and Emission Reduction of a Biodiesel Fueled Diesel Engine Based on an Improved Entire Diesel Engine Simulation Model
by Weigang Yu, Zhiqing Zhang and Bo Liu
Processes 2021, 9(1), 104; https://doi.org/10.3390/pr9010104 - 06 Jan 2021
Cited by 10 | Viewed by 2430
Abstract
In order to improve the efficiency of the diesel engine and reduce emissions, an improved heat transfer model was developed in an AVL-BOOST environment which is a powerful and user-friendly software for engine steady-state and transient performance analysis. The improved heat transfer model [...] Read more.
In order to improve the efficiency of the diesel engine and reduce emissions, an improved heat transfer model was developed in an AVL-BOOST environment which is a powerful and user-friendly software for engine steady-state and transient performance analysis. The improved heat transfer model considers the advantages of the Woschni1978 heat transfer model and Honhenberg heat transfer model. In addition, a five-component biodiesel skeletal mechanism containing 475 reactions and 134 species was developed to simulate the fuel spray process and combustion process since it contained methyl linolenate, methyl linoleate, methyl oleate, methyl stearate, and methyl palmitate, which are a majority component in most biodiesel. Finally, the propulsion and load characteristics of a diesel engine fueled with biodiesel fuel were investigated by the improved heat transfer model in term of power, brake specific fuel consumption (BSFC), soot and NOx emissions. Similarly, the effects of the fuel injection rate on the diesel engine’s characteristic fueled with biodiesel was studied. The result showed that the errors between experiment and simulation were less than 2%. Thus, the simulation model could predict the propulsion and load characteristics of the diesel engine. The nozzle diameter, injection pressure, and injection advance angle are significant to the injection system. Thus, it is very important to choose the injection rate reasonably. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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Review

Jump to: Editorial, Research

15 pages, 2865 KiB  
Review
Research and Application of Double-Reheat Boiler in China
by Hu Liu, Pengfei Yu, Jingwen Xue, Lei Deng and Defu Che
Processes 2021, 9(12), 2197; https://doi.org/10.3390/pr9122197 - 06 Dec 2021
Cited by 7 | Viewed by 4557
Abstract
The ultra-supercritical (USC) double-reheat technology is an immediate area of research focus in China, since the thermal efficiency of USC double-reheat unit is higher than the USC single-reheat unit. The parameters and capacity of USC double-reheat unit in China have made major breakthroughs, [...] Read more.
The ultra-supercritical (USC) double-reheat technology is an immediate area of research focus in China, since the thermal efficiency of USC double-reheat unit is higher than the USC single-reheat unit. The parameters and capacity of USC double-reheat unit in China have made major breakthroughs, and the thermal efficiency of the units are as high as 47–48%, which is the highest in the world. USC double-reheat boiler is one of the most important devices for USC double-reheat unit, and the design concept and precision have a vital effect on the operation of boiler and power station. The most difficult and important factors in the design of double-reheat boiler are the layout of heating surface and the steam temperature regulation method. Therefore, this work summarizes the arrangement of heating surface and temperature regulation method of existing double-reheat boiler in China. It is hoped that the work will set a benchmark for the development of double-reheat boiler and the future 700 °C power generation unit in the world. Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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21 pages, 1809 KiB  
Review
A Review on Temperature Control of Proton Exchange Membrane Fuel Cells
by Qinghe Li, Zhiqiang Liu, Yi Sun, Sheng Yang and Chengwei Deng
Processes 2021, 9(2), 235; https://doi.org/10.3390/pr9020235 - 27 Jan 2021
Cited by 53 | Viewed by 5835
Abstract
This paper provides a comprehensive review of the temperature control in proton exchange membrane fuel cells. Proton exchange membrane (PEM) fuel cells inevitably emit a certain amount of heat while generating electricity, and the fuel cell can only exert its best performance in [...] Read more.
This paper provides a comprehensive review of the temperature control in proton exchange membrane fuel cells. Proton exchange membrane (PEM) fuel cells inevitably emit a certain amount of heat while generating electricity, and the fuel cell can only exert its best performance in the appropriate temperature range. At the same time, the heat generated cannot spontaneously keep its temperature uniform and stable, and temperature control is required. This part of thermal energy can be classified into two groups. On the one hand, the reaction heat is affected by the reaction process; on the other hand, due to the impedance of the battery itself to the current, the ohmic polarization loss is caused to the battery. The thermal effect of current generates Joule heat, which is manifested by an increase in temperature and a decrease in battery performance. Therefore, it is necessary to design and optimize the battery material structure to improve battery performance and adopt a suitable cooling system for heat dissipation. To make the PEM fuel cell (PEMFC) universal, some extreme situations need to be considered, and a cold start of the battery is included in the analysis. In this paper, the previous studies related to three important aspects of temperature control in proton exchange membrane fuel cells have been reviewed and analyzed to better guide thermal management of the proton exchange membrane fuel cell (PEMFC). Full article
(This article belongs to the Special Issue Energy Conservation and Emission Reduction in Process Industry)
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