Article
Environmental Sciences
Junqing Yu, Ting Yang, Tao Ding, Kaile Zhou
Summary: China's energy and carbon footprints have shown characteristics of slowing growth, consumption-driven increases, and the tertiary industry sector becoming critical nodes in the footprint networks during the new normal stage.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Green & Sustainable Science & Technology
Patrice Guillotreau, Sharif Antoine, Fatime Kante, Katrin Perchat
Summary: Small Island Developing States (SIDS) are highly vulnerable to marine litter and plastic waste pollution, but often lack the infrastructure for waste treatment. This research focuses on quantifying the plastic footprint of Seychelles using an Environmentally-Extended Input-Output Analysis (EEIOA) and multi-regional input-output (MRIO) approach. The study finds that SIDS may have the same level of plastic use and waste per capita as high-income countries, emphasizing the need for joint actions to reduce plastic pollution in these regions.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Environmental
Bu Zhao, Chenyang Shuai, Shen Qu, Ming Xu
Summary: This study proposes a machine learning-augmented method that combines the RAS method and deep neural network model to improve the accuracy of IO table prediction. The results show significant performance improvements in both short-term and long-term predictions, and the method is applicable to carbon footprint accounting.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2022)
Article
Environmental Sciences
Yawen Han, Hongmei Duan, Xin Du, Li Jiang
Summary: The study reveals that the environmental footprints of the wealthiest households are significantly larger than those of the poorest households; changes in consumption structure can help reduce environmental footprints; awareness of environmental issues can impact household footprints to some extent.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Engineering, Environmental
Meng Li, Bo Meng, Yuning Gao, Joaquim J. M. Guilhoto, Keying Wang, Yong Geng
Summary: The world has experienced an unprecedented growth in extraction of materials and natural resources in recent decades, which has been greatly impacted by the emergence of multinational enterprises. This study uses an environmental-extended multi-regional input-output approach and takes into account multinational enterprises to trace the material flows along Global Value Chains. The results show that both trade outsourcing and offshoring of production, as well as overseas investments by multinational enterprises, contribute to the increasing material extraction in developing countries. The role of fixed capital formation in driving the growth of material footprints is also highlighted. The sustainable development goals emphasize the collaboration of all nations, with a focus on the role of multinational enterprises.
RESOURCES CONSERVATION AND RECYCLING
(2023)
Article
Economics
Haruka Mitoma
Summary: This study estimates an input-output table for India, distinguishing between the formal and informal sectors in 25 manufacturing industries, to investigate the informal sector's contribution to the national carbon footprint. The results show that the informal sector in several industries significantly contributes to the carbon footprint of the top three supply chains with larger CO2 emissions in India. The study suggests that environmental policymakers target the informal sector and identify the actors involved in achieving CO2 emission reduction in the informal sector.
Article
Thermodynamics
Jijie Shen, Peng Yi, Xumin Zhang, Yuantao Yang, Jinzhu Fang, Yuanying Chi
Summary: Understanding the water-energy nexus is crucial for addressing water scarcity and high energy consumption issues in China. This study quantified the provincial energy, water-related energy, water, and energy-related water footprints to analyze the drivers of the spatiotemporal changes. Results showed that agriculture, manufacturing, and energy supply were dominant sectors in the water-energy nexus. Structural adjustment and key technological advances reduced water and energy footprints, but had mixed effects on energy-related water footprint.
Article
Biodiversity Conservation
Gino Sturla, Lorenzo Ciulla, Benedetto Rocchi
Summary: This study uses the MRIO approach and the latest database to estimate the pressure of Italian consumption on water resources. Disaggregated results show geographical and sectoral hotspots. The study compares different measures of water footprint and finds a significant asymmetry between domestic and external water exploitation.
ECOLOGICAL INDICATORS
(2023)
Review
Engineering, Environmental
Yutong Jin, Heming Wang, Yafei Wang, Jacob Fry, Manfred Lenzen
Summary: The study reveals an imbalance in material footprint between affluent coastal cities and less-developed inland cities in China. Chongqing is the only city that relies more on materials extracted from its own environment.
RESOURCES CONSERVATION AND RECYCLING
(2021)
Article
Green & Sustainable Science & Technology
Feng Wang, Baoling Xu, Yumei Si, Yuzhu Shang, Wei Zhang, Beiming Cai, Minxing Jiang, Siqi Xu, Siqi Lu
Summary: This study investigated the components and internal drivers of household water footprint inequality in China from 2002 to 2012 and found that household grey water footprint is unevenly distributed, with food, clothing, and residence being the main sources of inequality. The study also revealed that although the household water Gini coefficient increased slightly, the structural changes in household water footprint contributed to a reduction in inequality.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2023)
Article
Engineering, Environmental
Zhan-Ming Chen, Peilin Chen, Manfred Lenzen, Baigao Xiao, Arunima Malik
Summary: This study constructs a dynamic energy input-output model to analyze the embodied energy flows and stocks from 2000 to 2014. The results show that the global fixed capital stock stored a significant amount of embodied energy, which was three times the world's direct energy use. The gaps between the dynamic energy footprints and the traditional ones were larger in fast-developing countries. Net embodied energy usually flowed from high-intensity economies to lower-intensity economies.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2022)
Article
Engineering, Environmental
Hui Li, Sai Liang, Yuhan Liang, Ke Li, Jianchuan Qi, Xuechun Yang, Cuiyang Feng, Yanpeng Cai, Zhifeng Yang
Summary: The grey water footprint (GWF) in China is significantly influenced by interregional trade, with traditional GWF quantification methods often overlooking the impacts of coexisting compounds. An improved GWF quantification method reveals that GWF in Chinese regions decreases by 19-35%, with up to 35% of the improved GWF related to commodities produced outside of the regions they are consumed. Sectors such as corn, cattle, swine, poultry, and other animal husbandry contribute the most to GWF outsourcing. This study provides region-specific and sector-specific results for more accurate policy decisions on water resource conservation in China.
RESOURCES CONSERVATION AND RECYCLING
(2021)
Article
Green & Sustainable Science & Technology
Ipsita Kumar, Kuishuang Feng, Laixiang Sun, Varaprasad Bandaru
Summary: This study uses an extended input-output model in Thailand and the Northeast to examine the impacts of renewable energy policies and a no burn policy. The findings suggest that these policies have positive effects on output, employment, and income, contributing to the achievement of sustainable development goals.
Article
Environmental Studies
Decun Wu, Guangzhu Wu, He Yang
Summary: Studying the production intensity of ecological footprint is crucial in the ecological compensation strategy for designated industries, especially in identifying high-polluting industries. Environment-extended input-output (EE-IO) tables are useful for analyzing pollution and land occupation within economic sectors. By using ecological footprint (EF) and input-output tables (IOTs), this study analyzed China's EFPI and its flow among sectors in 2005, 2010, and 2015. The results showed a downward trend in the average total pollution coefficient (TPC) component and net embodied EFPI transfers from 2005 to 2015. The electricity, heat, gas, and water sector (S11) and the agriculture sector (S1) had significant contributions to TPC and net embodied EFPI transfers. Recommendations were made to impose an ecological tax and control high-EFPI industries for optimization.
Article
Environmental Sciences
Xiawei Liao, Li Chai, Yi Liang
Summary: Urbanization in China has led to significant changes in household consumption patterns, resulting in a notable increase in greywater footprint for urban households while a slight decrease for rural households. The study also highlights the significant impact of total Nitrogen on GWF and how food consumption dominates GWF for household consumption. Meanwhile, the study shows that urban households on average require higher GWF for consumption compared to rural households, with variations depending on income levels.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Engineering, Multidisciplinary
Jason Maximino C. Ongpeng, John Barra, Kristin Carampatana, Christian Sebastian, Julienne James Yu, Kathleen B. Aviso, Raymond R. Tan
Summary: The study focuses on using Recycled PET bottles as reinforcement for rectangular concrete columns, resulting in a significant increase in compressive strength and practicality for construction in rural areas with low skilled workers. Further research is recommended to test long-term durability and scalability of this waste management solution.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2021)
Article
Chemistry, Physical
Jian Xiang Tan, Hong Sheng Tan, Amelie Peter Affery, Ian Yan Beng Ong, Dominic C. Y. Foo, Kathleen B. Aviso, Raymond R. Tan, ChangKyoo Yoo
Summary: A P-graph model is developed in this paper for the synthesis of hydrogen networks, capable of generating optimal solutions for pressure and impurity constraints, and applicable to hydrogen header.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Green & Sustainable Science & Technology
Kathleen B. Aviso, Jui-Yuan Lee, Aristotle T. Ubando, Raymond R. Tan
Summary: Enhanced weathering is a negative emissions technology that accelerates weathering of alkaline minerals to capture and permanently store CO2 in the ocean. Planning enhanced weathering networks like industrial supply chains, considering supply constraints of alkaline minerals and availability of land sinks, is crucial. This study developed a fuzzy mixed-integer linear programming model for optimal planning of enhanced weathering networks.
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2022)
Letter
Green & Sustainable Science & Technology
Raymond R. Tan, Kathleen B. Aviso
Summary: Enhanced weathering is a scalable negative emissions technology with significant carbon dioxide removal potential. Life-cycle assessment provides reliable estimates of climate change mitigation potential, and a comprehensive life-cycle optimization approach can maximize environmental performance, extending to sustainability optimization by including economic and social dimensions.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Hoa Thi Nguyen, Kathleen B. Aviso, Masayuki Fujioka, Lisa Ito, Akihiro Tokai
Summary: This study explores the impact of environmental management and sustainable growth strategies on human and ecosystem health by analyzing the drivers of chemical pollution in Japan between 2001 and 2015. A hybrid approach combining input-output analysis and structural decomposition analysis is used to identify socio-economic determinants of changes in ToxF. The results show a significant decrease in the overall ToxF from the Japanese industrial sectors during the analyzed period, with contributions from consumption structure and emission intensity.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Thermodynamics
Jason Maximino C. Ongpeng, Brian Immanuel B. Rabe, Luis F. Razon, Kathleen B. Aviso, Raymond R. Tan
Summary: Old buildings often have poor energy performance but new buildings are focusing on sustainable design and energy improvement. A systematic decision framework is developed to evaluate energy retrofit strategies and identify a compromise solution, which considers all stakeholders involved. Stakeholders preferred retrofit scenarios with on-site generation, mechanical/electrical improvements, and building envelope improvements.
Review
Green & Sustainable Science & Technology
Kathleen B. Aviso, Alexsa Laddaran, Janne S. Ngo
Summary: Industrial symbiosis is a mechanism to achieve a more sustainable industrial ecosystem by promoting waste and by-product exchange. Modelling stakeholder objectives is critical in identifying feasible and sustainable networks, and game theoretic principles can provide conditions for drafting agreements and contracts between network participants.
PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY
(2022)
Article
Energy & Fuels
Jia Wen Chong, Suchithra Thangalazhy-Gopakumar, Raymond R. Tan, Kathleen B. Aviso, Nishanth G. Chemmangattuvalappil
Summary: A data-driven rough-set-based machine learning model is proposed in this work to predict the properties of pyrolysis bio-oil. The model is trained based on a database consisting of feedstock proximate and ultimate analyses, pyrolysis temperature, bio-oil's pH value, and bio-oil's higher heating value. The results demonstrate that the model has good predictive capability and can be used for feedstock composition and pyrolysis temperature selection in pyrolysis bio-oil production.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Angelyn R. Lao, Kathleen B. Aviso, Heriberto Cabezas, Raymond R. Tan
Summary: This study demonstrates how co-culture systems can optimize food production by maximizing the involvement of species, thus addressing food security without requiring additional land area.
NATURE SUSTAINABILITY
(2022)
Article
Environmental Sciences
Jia Yong Tang, Boaz Yi Heng Chung, Jia Chun Ang, Jia Wen Chong, Raymond R. R. Tan, Kathleen B. B. Aviso, Nishanth G. G. Chemmangattuvalappil, Suchithra Thangalazhy-Gopakumar
Summary: Biochar is a high-carbon-content organic compound with potential applications in energy storage and conversion. The relationship between biomass type, operating conditions, and biochar properties is crucial for large-scale biochar production. Machine learning-based data analysis is necessary to establish this relationship. In this study, a rough set-based machine learning approach was used to generate decision rules and classify biochar properties.
ENVIRONMENTAL TECHNOLOGY
(2023)
Article
Green & Sustainable Science & Technology
Raymond R. Tan, Ivan Henderson V. Gue, John Frederick D. Tapia, Kathleen B. Aviso
Summary: Interactions between government and industry in environmental protection involve leader-follower games, where the government sets policies and the industry reacts accordingly. This paper develops a leader-follower model for selecting carbon emissions mitigation measures, assuming the government determines emissions reduction target, subsidy percentage, and economic penalty. A case study on maritime shipping emissions demonstrates the model's effectiveness, achieving an 11.5% reduction through the implementation of six measures, with only one subsidized. The implications for decarbonization policy are also discussed.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Fang Wang, Jinkang Cao, Yanmei Zhang, Kathleen B. Aviso, Raymond R. Tan, Zhiwei Li, Xiaoping Jia
Summary: This study develops a systematic framework that combines process modeling and accident risk assessment for a regional CCUS supply chain. A process simulation using Aspen Plus is proposed, along with a comprehensive inherent safety index system to evaluate CCUS risk performance. The study investigates the quantitative risk characteristics and severity of accidents in different components of the CCUS supply chain, with highest risk severity in winter. Additionally, the study simulates the impact range of regional CCUS accidents. It provides a method to assess CCUS systems on a system perspective and explores the safety risks on spatial and temporal scales.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Kathleen B. Aviso, Krista Danielle Yu, Jui-Yuan Lee, Raymond R. Tan
Summary: Input-output analysis is a method used to model economic networks and assess the interdependencies between sectors. This paper introduces an improved approach that incorporates partial substitution to optimize input-output systems, and demonstrates its effectiveness through two case studies.
CLEANER ENGINEERING AND TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Maria Victoria Migo-Sumagang, Raymond R. Tan, John Frederick D. Tapia, Kathleen B. Aviso
Summary: Following the COP26 agreement to reduce coal usage and eliminate fossil fuel subsidies, fossil fuels will continue to be used in the coming decades. Negative Emissions Technologies (NETs) can help offset the emissions caused by residual fossil fuel use by removing CO2 from the atmosphere and storing it. However, the large-scale implementation of NETs requires careful consideration of resource footprints and their operation within planetary boundaries. No single NET can sustainably achieve the necessary CO2 removal, emphasizing the importance of optimized regional portfolios of NETs that can reduce both physical and social impacts.
CLEANER ENGINEERING AND TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Raymond R. Tan, Joseph R. Ortenero, Kathleen B. Aviso
Summary: The selection of the best green technology for a given application is a subjective process that requires tradeoffs among conflicting attributes of alternatives. In this work, a machine-learning based methodology using logical analysis of data (LAD) is developed to rank green technologies based on multiple criteria, with patterns approximating expert rules for comparing and ranking alternatives. This novel technique provides a rapid means to elicit expert knowledge for ranking alternatives based on multiple criteria.
CLEANER ENGINEERING AND TECHNOLOGY
(2021)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
