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Ma JJ. Who shapes the embodied carbon dioxide emissions of interconnected power grids in China? A seasonal perspective. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 324:116422. [PMID: 36352720 DOI: 10.1016/j.jenvman.2022.116422] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 09/27/2022] [Accepted: 09/30/2022] [Indexed: 06/16/2023]
Abstract
With the rapid development of interregional power transmission, the redistribution of fossil and renewable energy resources has changed sharply, and its complexity poses a challenge to the evaluation of power carbon emission responsibility. This study constructs an interprovincial power transmission framework to measure the seasonal carbon emissions embodied in regional electricity consumption over the period of 2008-2015 based on quarterly data. Then, a structural decomposition approach was developed to identify the influential factors of carbon emissions embodied in provincial electricity consumption from a seasonal perspective. The results show that the assessment for embodied emissions of power consumption based on different levels of data may vary by as much as 20%, and the carbon emissions and carbon intensity of power consumption exhibit significant seasonal characteristics. Furthermore, it is revealed that the economic scale in the fourth quarter makes the most significant contribution to the emissions increment, especially in underdeveloped provinces, while the change in energy efficiency of power generation reduces more carbon emissions in the first and second quarters. In addition, the impact of the power transmission scale is more significant in the third and fourth quarters, and it has been close to or even more than the impact of traditional factors in some quarters. Finally, the impact of economic scale, power generation energy intensity, power generation mix and electricity utilization efficiency on the emissions of regional power grids shows a relatively stable increasing trend, but this trend of directional stability is not reflected in the effect of the power transmission structure and transmission scale. This study contributes to the identification of the impact of the power transmission structure and transmission scale. Moreover, this study highlights the importance of considering seasonal characteristics when estimating the carbon emissions of power consumption and formulating specific emission reduction policies. Additionally, it provides a more accurate evaluation of carbon emissions and proposes several prominent recommendations for policy makers.
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Affiliation(s)
- Jia-Jun Ma
- School of Economics, Zhejiang University of Technology, Hangzhou, 310023, China.
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2
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Interprovincial Metal and GHG Transfers Embodied in Electricity Transmission across China: Trends and Driving Factors. SUSTAINABILITY 2022. [DOI: 10.3390/su14148898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
With the increasing proportion of low-carbon power in electricity generation mix, power generation will be transformed from carbon-intensive to metal-intensive. In this context, metal and GHG transfers embodied in electricity transmission of China from 2015 to 2019 are quantified by the Quasi-Input-Output model. Combined with complex network theory, we have distinguished whether metal and GHG transfers show different trends as electricity trade changes. Driving factors contributing to forming the metal and GHG transfers are also explored based on the Quadratic Assignment Procedure. The results show that the electricity trade change has strengthened the metal transfer network significantly, while several key links in the GHG transfer network have weakened. Moreover, we find provincial differences in low-carbon electricity investment contributing to the metal transfer while affecting the GHG transfer little. The above facts imply an expanding embodied metal transfer in the future and shed light on policy making for power system decarbonization.
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3
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Von Wald G, Cullenward D, Mastrandrea MD, Weyant J. Accounting for the Greenhouse Gas Emission Intensity of Regional Electricity Transfers. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:6571-6579. [PMID: 33956448 DOI: 10.1021/acs.est.0c08096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Accurately quantifying greenhouse gas (GHG) emissions is essential for climate policy implementation but challenging in the case of electricity transfers across regulatory jurisdictions. Regulating emissions associated with delivered electricity is further complicated by contractual arrangements for dynamic electricity transfers that confound emission accounting approaches rooted in the physics of grid operations. Here, we propose a novel consumption-based accounting methodology to reconcile the nominal and the physical flows of electricity from generators to consumers. We also compare capacity factor-based and regression-based approaches for estimating default emission factors, in the absence of fully specified nominal electricity flows. As a case study, we apply this approach to assess the methods by which California regulators quantify specified and unspecified electricity imports and their associated GHG emissions. Collectively, these efforts illustrate principles for a comprehensive, empirical accounting framework that could inform efforts to improve the accuracy and consistency of policies regulating regional electricity transfers.
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Affiliation(s)
- Gregory Von Wald
- Department of Energy Resources Engineering, Stanford University, Stanford, California 94305-6104, United States
| | - Danny Cullenward
- Stanford Law School, Stanford University, Stanford, California 94305, United States
| | - Michael D Mastrandrea
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California 94305, United States
| | - John Weyant
- Precourt Institute for Energy, Stanford University, Stanford, California 94305, United States
- Management Science and Engineering, Stanford University, Stanford, California 94305, United States
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Abstract
Water use within power supply chains has been frequently investigated. A unified framework to quantify the water use of power supply chains deserves more development. This article provides an overview of the water footprint and virtual water incorporated into power supply chains. A water-use mapping model of the power supply chain is proposed in order to map the analysed research works according to the considered aspects. The distribution of water footprint per power generation technology per region is illustrated, in which Asia is characterised by the largest variation of the water footprint in hydro-, solar, and wind power. A broader consensus on the system boundary for the water footprint evaluation is needed. The review also concludes that the water footprint of power estimated by a top-down approach is usually higher and more accurate. A consistent virtual water accounting framework for power supply chains is still lacking. Water scarcity risks could increase through domestic and global power trade. This review provides policymakers with insights on integrating water and energy resources in order to achieve sustainable development for power supply chains. For future work, it is essential to identify the responsibilities of both the supply and demand sides to alleviate the water stress.
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Siddik MAB, Chini CM, Marston L. Water and Carbon Footprints of Electricity Are Sensitive to Geographical Attribution Methods. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:7533-7541. [PMID: 32378885 DOI: 10.1021/acs.est.0c00176] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Environmental footprinting methods provide a means to relate the environmental externalities of electricity production to electricity consumers. Although several methods have been developed to connect the environmental footprint of electricity generation to end users, estimates produced by these methods are inherently uncertain due to the impossibility of actually tracing electricity from the point of generation to utilization. Previous studies rarely quantify this uncertainty, even though it may fundamentally alter their findings and recommendations. Here, we evaluate the sensitivity of water and carbon footprints estimates among seven commonly used methods to attribute electricity production to end users. We assess how sensitive water and carbon electricity footprint estimates are to attribution methods, how these estimates change over time, and the main factors contributing to the variability between methods. We evaluate and make available the water and carbon footprints of electricity consumption for every city across the contiguous United States for all assessed methods. We find significant but spatially heterogeneous variability in water and carbon footprint estimates across attribution methods. No method consistently overestimated or underestimated water and carbon footprints for every city. The variation between attribution methods suggests that future studies need to consider how the method selected to attribute environmental impacts through the electrical grid may affect their findings.
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Affiliation(s)
- Md Abu Bakar Siddik
- Department of Civil Engineering, Kansas State University, Manhattan, Kansas 66506, United States
| | - Christopher M Chini
- Department of Systems Engineering and Management, Air Force Institute of Technology, 2950 Hobson Way, Wright Patterson AFB, Dayton, Ohio 45433, United States
| | - Landon Marston
- Department of Civil Engineering, Kansas State University, Manhattan, Kansas 66506, United States
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Abstract
Understanding electricity consumption and production patterns is a necessary first step toward reducing the health and climate impacts of associated emissions. In this work, the economic input-output model is adapted to track emissions flows through electric grids and quantify the pollution embodied in electricity production, exchanges, and, ultimately, consumption for the 66 continental US Balancing Authorities (BAs). The hourly and BA-level dataset we generate and release leverages multiple publicly available datasets for the year 2016. Our analysis demonstrates the importance of considering location and temporal effects as well as electricity exchanges in estimating emissions footprints. While increasing electricity exchanges makes the integration of renewable electricity easier, importing electricity may also run counter to climate-change goals, and citizens in regions exporting electricity from high-emission-generating sources bear a disproportionate air-pollution burden. For example, 40% of the carbon emissions related to electricity consumption in California's main BA were produced in a different region. From 30 to 50% of the sulfur dioxide and nitrogen oxides released in some of the coal-heavy Rocky Mountain regions were related to electricity produced that was then exported. Whether for policymakers designing energy efficiency and renewable programs, regulators enforcing emissions standards, or large electricity consumers greening their supply, greater resolution is needed for electric-sector emissions indices to evaluate progress against current and future goals.
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Wang H, Wang W, Liang S, Zhang C, Qu S, Liang Y, Li Y, Xu M, Yang Z. Determinants of Greenhouse Gas Emissions from Interconnected Grids in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:1432-1440. [PMID: 30602110 DOI: 10.1021/acs.est.8b06516] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
While direct greenhouse gas (GHG) emissions by China's power sector from the generation side have been widely investigated, driving forces from the electricity consumption perspective and inter-regional electricity transmission have been overlooked to a large extent. This study quantified relative contributions of six factors to changes in GHG emissions from interconnected grids in China during 2008-2015. These six factors include three generation-side factors (i.e., fuel mix of thermal power generation, energy efficiency of thermal power generation, and electricity structure), two consumption-side factors (i.e., electricity efficiency of GDP and GDP), and electricity transmission structure. GDP growth and changes in fuel mix of thermal power generation are two major drivers of increased GHG emission during 2008-2015, especially for the North China Grid. In contrast, changes in electricity transmission structure (especially in East China Grid and Southern China Grid), the increase in electricity efficiency of GDP (except for Northwest China Grid), improvements in energy efficiency of thermal power generation (especially in North China Grid and Central China Grid), and changes in electricity structure (especially in Southern Power Grid) are major factors offsetting GHG emission increments. Findings of this study can provide multiple-perspective policy implications for GHG mitigation in China's power sector.
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Affiliation(s)
- Hongxia Wang
- Donlinks School of Economics and Management , University of Science and Technology Beijing , Beijing , 100083 , China
| | - Weicai Wang
- Donlinks School of Economics and Management , University of Science and Technology Beijing , Beijing , 100083 , China
| | - Sai Liang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment , Beijing Normal University , Beijing , 100875 , China
| | - Chao Zhang
- School of Economics and Management , Tongji University , Shanghai , 200092 , China
- United Nation Environment-Tongji Institute of Environment for Sustainable Development , Tongji University , Shanghai , 200092 , China
| | - Shen Qu
- School for Environment and Sustainability , University of Michigan , Ann Arbor , Michigan 48109-1041 , United States
| | - Yuhan Liang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment , Beijing Normal University , Beijing , 100875 , China
| | - Yumeng Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment , Beijing Normal University , Beijing , 100875 , China
| | - Ming Xu
- School for Environment and Sustainability , University of Michigan , Ann Arbor , Michigan 48109-1041 , United States
- Department of Civil and Environmental Engineering , University of Michigan , Ann Arbor , Michigan 48109-2125 , United States
| | - Zhifeng Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment , Beijing Normal University , Beijing , 100875 , China
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8
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Optimal Surface Aeration Control in Full-Scale Oxidation Ditches through Energy Consumption Analysis. WATER 2018. [DOI: 10.3390/w10070945] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Oxidation ditches are popularly used in rural areas and decentralized treatment facilities where energy deficiency is of concern. Aeration control technologies are well established for diffusion systems in order to improve energy efficiency, but there are still challenges in their application in oxidation ditches because surface aerators have unique characteristics with respect to oxygen transfer and energy consumption. In this paper, an integral energy model was proposed to include the energy, aeration, and fluidic effects of surface aerators, by which the energy for aeration of each aerator can be estimated using online data. Two types of rotating disks with different diameters (1800 mm and 1400 mm) were monitored in situ to estimate the model parameters. Furthermore, a feedforward–feedback loop control strategy was proposed using the concept of energy analysis and optimization. The simplified control system was implemented in a full-scale Orbal oxidation ditch, achieving an approximately 10% saving in full-process energy consumption. The cost–benefit analysis and carbon emission assessment confirmed the economic feasibility and environmental contribution of the control system. The energy model can help process designers and operators to better understand and optimally control the aeration process in oxidation ditches.
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Qu S, Li Y, Liang S, Yuan J, Xu M. Virtual CO 2 Emission Flows in the Global Electricity Trade Network. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2018; 52:6666-6675. [PMID: 29738231 DOI: 10.1021/acs.est.7b05191] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Quantifying greenhouse gas emissions due to electricity consumption is crucial for climate mitigation in the electric power sector. Current practices primarily use production-based emission factors to quantify emissions for electricity consumption, assuming production and consumption of electricity take place within the same region. The increasingly intensified cross-border electricity trade complicates the accounting for emissions of electricity consumption. This study employs a network approach to account for the flows in the whole electricity trade network to estimate CO2 emissions of electricity consumption for 137 major countries/regions in 2014. Results show that in some countries, especially those in Europe and Southern Africa, the impacts of electricity trade on the estimation of emission factors and embodied emissions are significant. The changes made to emission factors by considering intergrid electricity trade can have significant implications for emission accounting and climate mitigation when multiplied by total electricity consumption of the corresponding countries/regions.
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Affiliation(s)
- Shen Qu
- School for Environment and Sustainability , University of Michigan , Ann Arbor , Michigan 48109-1041 , United States
| | - Yun Li
- School for Environment and Sustainability , University of Michigan , Ann Arbor , Michigan 48109-1041 , United States
- School of Economics and Management , North China Electric Power University , Beijing 102206 , People's Republic of China
| | - Sai Liang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment , Beijing Normal University , Beijing , 100875 , People's Republic of China
| | - Jiahai Yuan
- School of Economics and Management , North China Electric Power University , Beijing 102206 , People's Republic of China
| | - Ming Xu
- School for Environment and Sustainability , University of Michigan , Ann Arbor , Michigan 48109-1041 , United States
- Department of Civil and Environmental Engineering , University of Michigan , Ann Arbor , Michigan 48109-2125 , United States
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10
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Grinstein A, Kodra E, Chen S, Sheldon S, Zik O. Carbon innumeracy. PLoS One 2018; 13:e0196282. [PMID: 29723206 PMCID: PMC5933710 DOI: 10.1371/journal.pone.0196282] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Accepted: 04/10/2018] [Indexed: 11/25/2022] Open
Abstract
Individuals must have a quantitative understanding of the carbon footprint tied to their everyday decisions to make efficient sustainable decisions. We report research of the innumeracy of individuals as it relates to their carbon footprint. In three studies that varied in terms of scale and sample, respondents estimate the quantity of CO2 released when combusting a gallon of gasoline in comparison to several well-known metrics including food calories and travel distance. Consistently, respondents estimated the quantity of CO2 from gasoline compared to other metrics with significantly less accuracy while exhibiting a tendency to underestimate CO2. Such relative absence of carbon numeracy of even a basic consumption habit may limit the effectiveness of environmental policies and campaigns aimed at changing individual behavior. We discuss several caveats as well as opportunities for policy design that could aid the improvement of people’s quantitative understanding of their carbon footprint.
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Affiliation(s)
- Amir Grinstein
- Associate Professor of Marketing, D'Amore-McKim School of Business, Northeastern University, Boston, MA, United States of America.,Associate Professor of Marketing, School of Economics and Business Administration, VU Amsterdam, The Netherlands
| | - Evan Kodra
- risQ Inc., Cambridge, MA, United States of America
| | - Stone Chen
- risQ Inc., Cambridge, MA, United States of America
| | - Seth Sheldon
- Sheldon Data, Athens, OH, United States of America
| | - Ory Zik
- Oryzik.com, Brookline, MA, United States of America
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Qu S, Liang S, Xu M. CO 2 Emissions Embodied in Interprovincial Electricity Transmissions in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2017; 51:10893-10902. [PMID: 28792748 DOI: 10.1021/acs.est.7b01814] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Existing studies on the evaluation of CO2 emissions due to electricity consumption in China are inaccurate and incomplete. This study uses a network approach to calculate CO2 emissions of purchased electricity in Chinese provinces. The CO2 emission factors of purchased electricity range from 265 g/kWh in Sichuan to 947 g/kWh in Inner Mongolia. We find that emission factors of purchased electricity in many provinces are quite different from the emission factors of electricity generation. This indicates the importance of the network approach in accurately reflecting embodied emissions. We also observe substantial variations of emissions factors of purchased electricity within subnational grids: the provincial emission factors deviate from the corresponding subnational-grid averages from -58% to 44%. This implies that using subnational-grid averages as required by Chinese government agencies can be quite inaccurate for reporting indirect CO2 emissions of enterprises' purchased electricity. The network approach can improve the accuracy of the quantification of embodied emissions in purchased electricity and emission flows embodied in electricity transmission.
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Affiliation(s)
- Shen Qu
- School for Environment and Sustainability, University of Michigan , Ann Arbor, Michigan 48109-1041, United States
| | - Sai Liang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University , Beijing, 100875, People's Republic of China
| | - Ming Xu
- School for Environment and Sustainability, University of Michigan , Ann Arbor, Michigan 48109-1041, United States
- Department of Civil and Environmental Engineering, University of Michigan , Ann Arbor, Michigan 48109-2125, United States
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