How does the capacity utilization of thermal power generation affect pollutant emissions? Evidence from the panel data of China's provinces

Thermal power plants are considered to be the culprit of various pollutants. In China, a country dominated by coal-fired power generation, the problem is more serious. Regulators must use capacity control of coal-fired power generation as a key policy tool for emission reduction. This paper was conc...

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Veröffentlicht in:Energy policy 2019-09, Vol.132, p.440-451
Hauptverfasser: Wang, Yongpei, Yan, Weilong, Komonpipat, Supak
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description Thermal power plants are considered to be the culprit of various pollutants. In China, a country dominated by coal-fired power generation, the problem is more serious. Regulators must use capacity control of coal-fired power generation as a key policy tool for emission reduction. This paper was concerned about the environmental effect of changes in thermal power capacity utilization on pollutants emissions in China. Under the econometric strategy of panel smoothing transformation regression (PSTR) model, the switching regimes and paths of seven pollutants emissions to thermal power capacity utilization were evaluated with the transition variables of power generation and electricity consumption, respectively. The three statistics, LM test, LMF and pseudo-LRT, unanimously verify the necessity of nonlinearity. In addition to CO2 emissions whose transition function presents U-shaped feature both in the models with power generation and electricity consumption as transition variable, the other pollutants such as SO2, NOX and so on generally exhibit quasi S-shaped change trend. The interaction term of installed capacity and average annual operating hours of thermal power plants introduced to reflect the interactive environmental effect of thermal power capacity utilization on pollutants emissions, appear similarity in most pollutants. However, the negative coefficients of the transition functions for interactive environmental effect imply that the policymakers reduce pollution by defusing capacity, which needs to be supplemented by setting reasonable warning line for operating hours of thermal power. •The PSTR model is employed to capture unobserved heterogeneity.•The relationship between capacity utilization and pollutant emissions is nonlinearity.•The transition functions of seven pollutants exhibit U-shaped and quasi S-shaped features.•The environmental disruption warning lines of operating hours of thermal power plants is instructive for policymakers.
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Evidence from the panel data of China's provinces</title><source>Elsevier ScienceDirect Journals Complete</source><source>PAIS Index</source><creator>Wang, Yongpei ; Yan, Weilong ; Komonpipat, Supak</creator><creatorcontrib>Wang, Yongpei ; Yan, Weilong ; Komonpipat, Supak</creatorcontrib><description>Thermal power plants are considered to be the culprit of various pollutants. In China, a country dominated by coal-fired power generation, the problem is more serious. Regulators must use capacity control of coal-fired power generation as a key policy tool for emission reduction. This paper was concerned about the environmental effect of changes in thermal power capacity utilization on pollutants emissions in China. Under the econometric strategy of panel smoothing transformation regression (PSTR) model, the switching regimes and paths of seven pollutants emissions to thermal power capacity utilization were evaluated with the transition variables of power generation and electricity consumption, respectively. The three statistics, LM test, LMF and pseudo-LRT, unanimously verify the necessity of nonlinearity. In addition to CO2 emissions whose transition function presents U-shaped feature both in the models with power generation and electricity consumption as transition variable, the other pollutants such as SO2, NOX and so on generally exhibit quasi S-shaped change trend. The interaction term of installed capacity and average annual operating hours of thermal power plants introduced to reflect the interactive environmental effect of thermal power capacity utilization on pollutants emissions, appear similarity in most pollutants. However, the negative coefficients of the transition functions for interactive environmental effect imply that the policymakers reduce pollution by defusing capacity, which needs to be supplemented by setting reasonable warning line for operating hours of thermal power. •The PSTR model is employed to capture unobserved heterogeneity.•The relationship between capacity utilization and pollutant emissions is nonlinearity.•The transition functions of seven pollutants exhibit U-shaped and quasi S-shaped features.•The environmental disruption warning lines of operating hours of thermal power plants is instructive for policymakers.</description><identifier>ISSN: 0301-4215</identifier><identifier>EISSN: 1873-6777</identifier><identifier>DOI: 10.1016/j.enpol.2019.06.010</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Averages ; Carbon dioxide ; Carbon dioxide emissions ; Coal ; Coal-fired power plants ; Consumption ; Econometrics ; Electric power generation ; Electricity ; Electricity consumption ; Electricity generation ; Emissions ; Emissions control ; Energy policy ; Environmental effects ; Genetic transformation ; Industrial plant emissions ; Longitudinal studies ; Nonlinear systems ; Panel data ; Policy making ; Pollutant emissions ; Pollutants ; Pollution ; Pollution control ; Power consumption ; Power generating capacity ; Power plants ; Provinces ; PSTR model ; Regression models ; Regulators ; Statistical tests ; Statistics ; Sulfur dioxide ; Thermal power ; Thermal power plants ; Thermal utilization ; Thermoelectricity ; Transformation ; Utilization</subject><ispartof>Energy policy, 2019-09, Vol.132, p.440-451</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. 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In addition to CO2 emissions whose transition function presents U-shaped feature both in the models with power generation and electricity consumption as transition variable, the other pollutants such as SO2, NOX and so on generally exhibit quasi S-shaped change trend. The interaction term of installed capacity and average annual operating hours of thermal power plants introduced to reflect the interactive environmental effect of thermal power capacity utilization on pollutants emissions, appear similarity in most pollutants. However, the negative coefficients of the transition functions for interactive environmental effect imply that the policymakers reduce pollution by defusing capacity, which needs to be supplemented by setting reasonable warning line for operating hours of thermal power. •The PSTR model is employed to capture unobserved heterogeneity.•The relationship between capacity utilization and pollutant emissions is nonlinearity.•The transition functions of seven pollutants exhibit U-shaped and quasi S-shaped features.•The environmental disruption warning lines of operating hours of thermal power plants is instructive for policymakers.</description><subject>Averages</subject><subject>Carbon dioxide</subject><subject>Carbon dioxide emissions</subject><subject>Coal</subject><subject>Coal-fired power plants</subject><subject>Consumption</subject><subject>Econometrics</subject><subject>Electric power generation</subject><subject>Electricity</subject><subject>Electricity consumption</subject><subject>Electricity generation</subject><subject>Emissions</subject><subject>Emissions control</subject><subject>Energy policy</subject><subject>Environmental effects</subject><subject>Genetic transformation</subject><subject>Industrial plant emissions</subject><subject>Longitudinal studies</subject><subject>Nonlinear systems</subject><subject>Panel data</subject><subject>Policy making</subject><subject>Pollutant emissions</subject><subject>Pollutants</subject><subject>Pollution</subject><subject>Pollution control</subject><subject>Power consumption</subject><subject>Power generating capacity</subject><subject>Power plants</subject><subject>Provinces</subject><subject>PSTR model</subject><subject>Regression models</subject><subject>Regulators</subject><subject>Statistical tests</subject><subject>Statistics</subject><subject>Sulfur dioxide</subject><subject>Thermal power</subject><subject>Thermal power plants</subject><subject>Thermal utilization</subject><subject>Thermoelectricity</subject><subject>Transformation</subject><subject>Utilization</subject><issn>0301-4215</issn><issn>1873-6777</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNp9kMtO3DAUhi1UJKYDT8DGEouukh5fcltUVTWCDhJSN2VtGecYHGXi1PYMglfgpXGYrlkd6_yXI3-EXDIoGbD6-1DiNPux5MC6EuoSGJyQFWsbUdRN03whKxDACslZdUa-xjgAgGw7uSJvW_9Me4-RpiekRs_auPRC98mN7lUn5yfq7aKFnR7p7J8x0EecMBw1bS2alPfjuE96ShR3LsasxJ_0-uB6nAxSG_zuo37WE46010kvpZsnN-lvkc7BH1z2xXNyavUY8eL_XJP7m-u_m21x9-f37ebXXWFELVPRC-iEEVz2rXwAphtRgTQcOWOc9ZKLrpJW6K6yRle1ldDWrWEcm_zSD4BiTa6Ovfnyvz3GpAa_D1M-qTjveCehqZrsEkeXCT7GgFbNwe10eFEM1EJdDeqDulqoK6hVpp5TP44pzB84OAwqGrdQ6F3IpFTv3af5dwz2jaw</recordid><startdate>201909</startdate><enddate>201909</enddate><creator>Wang, Yongpei</creator><creator>Yan, Weilong</creator><creator>Komonpipat, Supak</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TA</scope><scope>7TB</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>DHY</scope><scope>DON</scope><scope>F28</scope><scope>FQK</scope><scope>FR3</scope><scope>H8D</scope><scope>JBE</scope><scope>JG9</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>201909</creationdate><title>How does the capacity utilization of thermal power generation affect pollutant emissions? 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source Elsevier ScienceDirect Journals Complete; PAIS Index
subjects Averages
Carbon dioxide
Carbon dioxide emissions
Coal
Coal-fired power plants
Consumption
Econometrics
Electric power generation
Electricity
Electricity consumption
Electricity generation
Emissions
Emissions control
Energy policy
Environmental effects
Genetic transformation
Industrial plant emissions
Longitudinal studies
Nonlinear systems
Panel data
Policy making
Pollutant emissions
Pollutants
Pollution
Pollution control
Power consumption
Power generating capacity
Power plants
Provinces
PSTR model
Regression models
Regulators
Statistical tests
Statistics
Sulfur dioxide
Thermal power
Thermal power plants
Thermal utilization
Thermoelectricity
Transformation
Utilization
title How does the capacity utilization of thermal power generation affect pollutant emissions? Evidence from the panel data of China's provinces
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