Journal of Cleaner Production最新文献

{"title":"Techno-economic assessment of an industrial prosumer with biomass investment and time varying tariffs: An Australian case study","authors":"Ibrahim Anwar Ibrahim ,&nbsp;Tan Nhat Pham ,&nbsp;Rakibuzzaman Shah ,&nbsp;M.J. Hossain ,&nbsp;Syed Islam","doi":"10.1016/j.jclepro.2024.143957","DOIUrl":"10.1016/j.jclepro.2024.143957","url":null,"abstract":"<div><div>This paper investigates the potential for a value chain framework to deliver impact through innovation across the timber manufacturing process. A new and efficient combustion technology that converts timber waste to energy is considered for this study. The framework to estimate the new energy costs and savings derived from the new technology, compared with current supply and demand scenarios, as well as the value generated by waste streams. The opportunity of selling excess energy to the grid or local area has been investigated. Two alternatives of time-varying tariffs and time-varying tariffs with biomass, are used for assessing the costs. According to the numerical results, tariff 3, with 25,000 tonnes of biomass feedstock per year, is the best option for the mill. The price efficiency index is reduced by approximately 40% compared to this option’s usual business. In addition, the investor can save the whole energy bill compared to the current business as usual. The investor could make a profit of $460,401 per year by selling energy to the grid. The annual saving is around six times higher than the savings gained using a time-varying tariff alone. However, this option requires $1,811,635 as annual life cycle cost, with a payback period of ten years. The lowest levelised cost of energy of 0.14 c/kWh is also obtained for this option.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 143957"},"PeriodicalIF":9.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The benefits and burdens of wind power systems in reaching China's renewable energy goals: Implications from resource and environment assessment","authors":"Yilin Li ,&nbsp;Xu Tang ,&nbsp;Mingkai Liu ,&nbsp;Guoqian Chen","doi":"10.1016/j.jclepro.2024.144134","DOIUrl":"10.1016/j.jclepro.2024.144134","url":null,"abstract":"<div><div>Recognizing the economy's growing reliance on global energy landscape transformation on wind power deployment, as well as the general reality that renewable facilities require lower operational but higher up-front inputs than fossil-based power systems, this paper focuses on the life-cycle burdens of wind power systems and their substitution benefits compared with coal-fired power systems. The estimation considers the consumption of nonrenewable sources of energy, emissions of greenhouse gases, and other environmental resource factors that have received significantly less research attention, such as industrial land use, water use, PM2.5, SO₂, NO_X, and Hg emissions. The scope of this study differs from earlier ones in that it includes a comprehensive description of all the equipment, materials, and services used, as opposed to earlier studies that either omit crucial supporting infrastructure or just focus on the plant's physical structure as its primary materials. Results based on a typical plant in China show that the state-of-the-art onshore wind power systems can provide significant reductions in nonrenewable energy use (9.2 MJ/kWh) and GHG emissions (782.8 GtCO₂/kWh). To produce an equivalent amount of electricity, wind power systems require more than three times industrial land use and almost one-third of industrial water use of that for traditional coal-fired power systems. The avoided SO₂, Hg, PM2.5, and NO_X emissions per unit of electricity generation account for 60.6%–89.3% of the total air pollution emissions induced by supercritical coal-fired power systems. By integrating 3797 operating plant-specific data and fixed-point wind energy information, this study scales up results of the single plant to a country level. The macro picture implies different opportunities born by wind power systems in easing multiple resource and environmental pressures, highlighting the significance of designing hierarchical strategies to improve penetration levels of wind power. By 2050, cumulative climate benefits obtained from onshore wind power technology are predicted to reach 74.2 Gt CO₂, achieving around 17.2%–45.5% of the national carbon-neutral goal.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144134"},"PeriodicalIF":9.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the impact of regional coordinated development on a low-carbon future: Evidence from the Beijing-Tianjin-Hebei Coordinated Development Strategy","authors":"Yaqi Wang ,&nbsp;Wei Li ,&nbsp;Guomin Li ,&nbsp;Shizheng Tan","doi":"10.1016/j.jclepro.2024.144140","DOIUrl":"10.1016/j.jclepro.2024.144140","url":null,"abstract":"<div><div>The Beijing-Tianjin-Hebei Coordinated Development Strategy (BTHCDS) is an important way for China to explore the construction of an ecological civilization. Whether it can effectively reduce carbon emission (CE) not only affects the quality of the strategy's implementation but also has important implications for optimizing the low-carbon development model of the urban agglomeration and advancing the “dual carbon” process of China. Based on the panel data between of 30 provinces between 2004 and 2019, this study employed the synthetic control method (SCM) to construct a counterfactual path and assess the impact of BTHCDS on CE reduction at both the whole regional and provincial levels. The results show that the BTHCDS has a positive leading role in shaping the region's low-carbon future and can drive the overall CE reduction in the Beijing-Tianjin-Hebei region at an annual rate of 10.43%. Despite short-term fluctuations in implementation, the CE reduction effect of BTHCDS has shown a steady trend of expanding overall. The CE reduction effects of BTHCDS exhibit heterogeneity across individual provinces, but there is no “pollution haven.” This study enriches research on the effect of regional coordinated integration development on CE reduction and provides an important policy reference for low-carbon development in other urban agglomerations.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144140"},"PeriodicalIF":9.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142563103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coupling and coordination association between night light intensity and women safety – A comparative assessment of Indian metropolitan cities","authors":"Priya Gupta,&nbsp;Neha Pranav Kolhe,&nbsp;Supriya Vyas","doi":"10.1016/j.jclepro.2024.144135","DOIUrl":"10.1016/j.jclepro.2024.144135","url":null,"abstract":"<div><div>Street lighting is an important aspect influencing women safety (WS) at night. Increased crime rate against women (CRAW) in Indian metropolitan areas (IMC) have a negative impact on the establishment of a safe environment for women (SEW). Women feel insecure when traveling alone because visibility is poor at night on urban streets. In order to create a safe environment and promote social justice, the study aims to analyze the impact of night light intensity (LI) on WS. The research uses remote sensing nighttime light (NTL) data to assess the temporal transition of LI and uses the coupling and coordination degree (CCD) technique to analyze the interaction between LI and WS in 53 IMC from 2012 to 2021. The following conclusions are drawn - first, LI has a higher temporal transition than CRAW in capital cities than non-capital cities due to better streetlight infrastructure. Second, CRAW shows a significant negative but three times higher impact while LI shows a significant positive impact on women safety. Third, Capital cities have 6.58% higher increases in coupling and 5.45% better levels of coordination compared to non-capital cities. Cities with high LI and high WS have a good level of coupling and coordination. Lastly, it is estimated that 96% of cities lack efficient light energy for SEW development. This study also makes policy recommendations to assist decision-makers in developing ways to improve the SEW by prioritizing cities. To move further, future studies should combine different time zones, such as daytime LI and crime rate, with other demographic groupings. This study can help to better understand the present situation of WS at night and serve as a reference for future studies on the subject.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144135"},"PeriodicalIF":9.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142562268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporal neural networks for monitoring and prediction of CO2 plume migration from measurable field data","authors":"Yingxiang Liu ,&nbsp;Zhen Qin ,&nbsp;Fangning Zheng ,&nbsp;Behnam Jafarpour","doi":"10.1016/j.jclepro.2024.144080","DOIUrl":"10.1016/j.jclepro.2024.144080","url":null,"abstract":"<div><div>Carbon capture and storage (CCS) technologies are crucial for mitigating greenhouse gas emissions. The success of CCS projects hinges on accurately predicting and monitoring the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> plume migration during and after injection. To address the computational burden of traditional numerical simulation methods, previous studies have used neural networks as proxy models to expedite the prediction of the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> plume migration. However, these models rely on uncertain inputs, such as the distribution of heterogeneous rock permeability and porosity maps, which can lead to erroneous predictions and limit their adoption in real-world applications. To address this issue, this study introduces a framework for reconstruction and short-term prediction of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> plume migration based solely on field measurements that directly provide information on the migration of the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> plumes, thus eliminating the dependency on uncertain geological information as model input. The framework trains a spatio-temporal neural network model using simulated data under various geologic settings to capture the plume evolution dynamics without constraining it to a specific geological scenario. Once trained, the model integrates global and local field measurements from multiple sources to reconstruct the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> plume and predict its spatio-temporal evolution. The effectiveness of the proposed framework is tested using two case studies: one using a synthetic dataset and another with data generated from a model of a real field in the Southern San Joaquin Basin. The results show that the proposed framework can accurately reconstruct and perform short-term predictions of the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> plume migration by integrating various forms of field measurements.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144080"},"PeriodicalIF":9.7,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of ion imprinted diethylenetriamine pentaacetic acid-polyethylenimine modified magnetic graphene oxide for selective adsorption of Ce(III)","authors":"Ting Guo ,&nbsp;Chaoke Bulin ,&nbsp;Rongxiang Zheng","doi":"10.1016/j.jclepro.2024.144104","DOIUrl":"10.1016/j.jclepro.2024.144104","url":null,"abstract":"<div><div>Selective recovery of rare earth elements is essential for both sustainable exploitation of rare earth resources and environmental remediation. Herein, Ce(Ⅲ) imprinted diethylenetriamine pentaacetic acid-polyethylenimine modified magnetic graphene oxide (IIP-DTPA-PEI-MGO) was fabricated for selective adsorption of Ce(Ⅲ). Adsorption efficiency and selectivity performance of IIP-DTPA-PEI-MGO towards Ce(Ⅲ) were evaluated via batch adsorption targeted at single and mixed solution, respectively. Adsorption mechanism was elucidated based on versatile adsorption fittings (isotherms, kinetics, thermodynamics) and spectroscopic tests (XPS, FTIR). Result presents, maximum adsorption efficiency of IIP-DTPA-PEI-MGO for Ce(III) is reached at pH = 5 in 30 min, demonstrating superior efficiency. The maximum mono layer adsorption capacity determined by the Langmuir model is 281.69 mg g⁻¹. After adsorption, 75.65 % of original Ce(Ⅲ) is transferred into Ce(Ⅳ), while 24.35 % remain as Ce(Ⅲ). Furthermore, by virtue of its paramagnetic property, IIP-DTPA-PEI-MGO can be easily recovered for cyclic adsorption, thereby keeping adsorption quantity 90.44 mg g⁻¹ on Ce(Ⅲ) in five consecutive cycles. Owing to ion imprinting sites, IIP-DTPA-PEI-MGO exhibits selectivity coefficient 1.34, 1.69, 2.32, 2.96, 15.24, 10.51 towards Ce(III) for binary solution Ce/La, Ce/Nd, Ce/Eu, Ce/Dy, Ce/Cu, Ce/Cr, respectively. In terms of adsorption mechanism, versatile functional groups O-H, C-N, C-O in IIP-DTPA-PEI-MGO provide heterogeneous affinity for Ce(Ⅲ), inducing chemical adsorption. This work provides a novel approach towards fabricating magnetic bio adsorbent for selective recovery of Ce(Ⅲ).</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144104"},"PeriodicalIF":9.7,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of green supply chain management on corporate performance under the full process model: A MASEM analysis based on heterogeneous moderation","authors":"Fanbo Li ,&nbsp;Hongfeng Zhang","doi":"10.1016/j.jclepro.2024.144099","DOIUrl":"10.1016/j.jclepro.2024.144099","url":null,"abstract":"<div><div>This study explores the impact of green supply chain management on corporate performance, focusing on environmental, economic, operational, and social outcomes. Using Meta-Analytic Structural Equation Modeling, we analyzed data from 98 quantitative studies conducted since 2001. Our findings demonstrate that green supply chain management practices significantly enhance corporate performance. We also identify key moderating factors, such as industry diversity, company size, geographical location, economic development, cultural level, and logistics performance, that influence the effectiveness of green supply chain management. The study highlights the importance of tailoring green supply chain management initiatives to specific industry and regional contexts, providing actionable insights and policy recommendations for promoting sustainable development in the Carbon Trading Era.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144099"},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing aquifer vulnerability mapping through integrated deep learning approaches","authors":"Fatemeh Faal ,&nbsp;Mohammad Reza Nikoo ,&nbsp;Seyed Mohammad Ashrafi ,&nbsp;Jiří Šimůnek","doi":"10.1016/j.jclepro.2024.144112","DOIUrl":"10.1016/j.jclepro.2024.144112","url":null,"abstract":"<div><div>Groundwater vulnerability maps are crucial for safeguarding groundwater quality. A research gap exists in using advanced data fusion techniques to identify areas subject to seawater intrusion. To address this gap, this research enhances the GALDIT method and applies diverse deep learning models, combined with machine learning techniques, to improve the precision of aquifer vulnerability mapping. The new GALDITMW model incorporates the seawater mixing index and the parameters related to the production well density and aquifer porous medium. For the first time, supervised and unsupervised deep learning models, such as deep neural networks, deep belief networks, deep stacked autoencoders, and convolutional neural networks, are used for vulnerability mapping. In the second stage, the results of various machine learning models are fused to improve performance. The models' effectiveness is evaluated using a vulnerability index based on total dissolved solids (TDS) in an aquifer hydraulically connected with Salt Lake in central Iran, which faces groundwater depletion and salinization. The evaluation of the models based on performance metrics and the confusion matrix demonstrates that initial deep-learning models perform well. Significant improvements were observed in the second stage involving machine learning models, confirming their strong correlation (R² &gt; 0.985) with observed chloride values. The GPR model achieved an F1 score of 86.92%, an NSE of 0.911, and an RMSE reduction of 0.026 mg/L compared to the first-stage models. The proposed method offers a novel and accurate method for identifying vulnerable areas and provides helpful information for groundwater resource management.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144112"},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing operational efficiency and regulation performance, for guiding pumped-storage day-ahead scheduling","authors":"Yu Xiao ,&nbsp;Meng Zhang ,&nbsp;Liuwei Lei ,&nbsp;Cheng Ma ,&nbsp;Ziwen Zhao ,&nbsp;Hongyu Chen ,&nbsp;Apel Mahmude ,&nbsp;Diyi Chen","doi":"10.1016/j.jclepro.2024.144097","DOIUrl":"10.1016/j.jclepro.2024.144097","url":null,"abstract":"<div><div>Pumped-storage plants (PSPs) have significant potential to regulate intermittent energy sources. However, achieving coordinated optimization of regulation stability and operational efficiency has been a long-standing challenge. This study proposes a new soft linking model to address the limitation that current scheduling methods fail to account for both efficiency and second-level stability simultaneously, aiming to improve the day-ahead scheduling strategies for PSP. Firstly, a Pumped-Storage Hydroelectric System (PSHS) model is developed to reflect the regulation stability of PSP, considering the transient characteristics of hydraulic, mechanical, and electrical subsystems. Then, by analyzing transient responses under various operating working conditions, the study integrates the transient variation laws of the power plant into a regulation stability dataset (RSD). Finally, using RSD as the coupling interface, with regulation stability and operational efficiency as the objective functions, a Pumped-Storage Power Day-ahead Scheduling (PSPDS) model is established. An actual PSP is used as a case study to evaluate the effects of four operational scenes with varying optimization objectives on operational efficiency and subsystem performance. The results indicate that controlling load change magnitude and increasing the load decrease working conditions effectively enhance the stability of PSP subsystems. In addition, although the proposed scheduling scheme increases water consumption by 0.0213% compared to traditional scheduling method, it improves regulation stability by at least 15.14%. The findings suggest that a minor compromise in operational efficiency can lead to a significant improvement in regulation stability. This study provides new perspectives and methods for the management and optimization of PSPs.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144097"},"PeriodicalIF":9.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable environmental performance: A cross-country fuzzy set qualitative comparative analysis empirical study of big data analytics and contextual factors","authors":"Adilson Carlos Yoshikuni ,&nbsp;Rajeev Dwivedi ,&nbsp;Marcio Quadros Lopes dos Santos ,&nbsp;Feng Liu ,&nbsp;Miguel Mitio Yoshikuni","doi":"10.1016/j.jclepro.2024.144040","DOIUrl":"10.1016/j.jclepro.2024.144040","url":null,"abstract":"<div><div>The rise of big data analytics has become crucial in aiding firms facing sustainability challenges, prompting researchers and practitioners to explore how this technology can contribute to environmental sustainability performance under specific circumstances. Based on the resource-based and dynamic capabilities view theory lens, it uses partial least square structural equation modeling and qualitative comparative analysis to explore the contribution of big data analytics-driven dynamic capabilities in innovation on environmental performance under enterprise factors and combinations of conditions. The empirical study gathered data from 319 Indian and American enterprises. The results demonstrate seven solutions with very high environmental performance, depicting core presence for big data analytics-driven dynamic capabilities in sensing, seizing, and transforming in an uncertain environment of dynamism and hostility in India and American firms. The synergy of big data analytics-enabled dynamic capabilities in sensing, seizing, and transforming shows an essential role in enhancing sustainable environmental performance for enterprises in the USA compared to those in India. Based on the configuration analyses, big data analytics significantly mitigates environmental dynamism and hostility challenges enterprises encounter. It consequently exerts a more pronounced influence on green performance, particularly within the service sector and small enterprises in the USA, through radical process innovation. Conversely, this impact is observed primarily among large product firms in India by incremental innovation strategies. This indicates that this emerging technology is essential to attend to the necessary aspects of the circular economy in developing and developed economies through specific configuration conditions.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"481 ","pages":"Article 144040"},"PeriodicalIF":9.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}