CCUS in China’s mitigation strategy: insights from integrated assessment modeling

Yu, Sha; Horing, Jill; Liu, Qiang; Dahowski, Robert T.; Davidson, Casie L.; Edmonds, James A.; Liu, Bo; McJeon, Haewon; McLeod, Jeff; Patel, Pralit; Clarke, Leon

doi:10.1016/j.ijggc.2019.03.004

Cited by 90 publications

(42 citation statements)

References 15 publications

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“…Total energy consumed by fuel type in rural and urban areas in the residential sector is separately provided by the GCAM-China building sector (Table S1). The residential sector includes two distinct types of coal combustion equipment for different uses (boilers for heating and stoves for cooking and heating), and their emission factors are quite different (Zhang et al, 2007;Peng et al, 2019). The final residential energyuse split for each usage (i.e.…”

Section: Residential Sectormentioning

confidence: 99%

“…S3). We projected the year-to-year dynamics of coal combustion technologies (boiler or stove) by assuming that coal stoves are used in individual houses for decentralized heating, cooking, and hot water supply, while coal-fired boilers are used for heating in large buildings in urban areas (Zhang et al, 2007). Finally, we projected the effects of clean coal use, advanced coal stoves and boilers, and end-of-pipe control technologies for coal-fired boilers in the target years (i.e.…”

Section: Residential Sectormentioning

confidence: 99%

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Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

et al. 2020

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Abstract. Future trends in air pollution and greenhouse gas (GHG) emissions for China are of great concern to the community. A set of global scenarios regarding future socio-economic and climate developments, combining shared socio-economic pathways (SSPs) with climate forcing outcomes as described by the Representative Concentration Pathways (RCPs), was created by the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China's future anthropogenic emission pathways. The DPEC is designed to integrate the energy system model, emission inventory model, dynamic projection model, and parameterized scheme of Chinese policies. The model contains two main modules, an energy-model-driven activity rate projection module and a sector-based emission projection module. The activity rate projection module provides the standardized and unified future energy scenarios after reorganizing and refining the outputs from the energy system model. Here we use a new China-focused version of the Global Change Assessment Model (GCAM-China) to project future energy demand and supply in China under different SSP–RCP scenarios at the provincial level. The emission projection module links a bottom-up emission inventory model, the Multi-resolution Emission Inventory for China (MEIC), to GCAM-China and accurately tracks the evolution of future combustion and production technologies and control measures under different environmental policies. We developed technology-based turnover models for several key emitting sectors (e.g. coal-fired power plants, key industries, and on-road transportation sectors), which can simulate the dynamic changes in the unit/vehicle fleet turnover process by tracking the lifespan of each unit/vehicle on an annual basis. With the integrated modelling framework, we connected five SSP scenarios (SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and three pollution control scenarios (business as usual, BAU; enhanced control policy, ECP; and best health effect, BHE) to produce six combined emission scenarios. With those scenarios, we presented a wide range of China's future emissions to 2050 under different development and policy pathways. We found that, with a combination of strong low-carbon policy and air pollution control policy (i.e. SSP1-26-BHE scenario), emissions of major air pollutants (i.e. SO2, NOx, PM2.5, and non-methane volatile organic compounds – NMVOCs) in China will be reduced by 34 %–66 % in 2030 and 58 %–87 % in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important role in continuous emission reduction until 2050. In contrast, China's emissions will remain at a high level until 2050 under a reference scenario without active actions (i.e. SSP3-70-BAU). Compared to similar scenarios set from the CMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates of emission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in 2020–2030, but their emission ranges become similar in the year 2050.

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Section: Residential Sectormentioning

confidence: 99%

Section: Residential Sectormentioning

confidence: 99%

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

et al. 2020

Self Cite

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“…Most energy system models, including GCAM, take China as a whole section in simulations and fail to reflect the differences in regional or provincial energy and socioeconomic developments. To better explore the provincial evolution and development in China, JGCRI developed and expanded GCAM to include greater spatial detail in China's provinces, and this model is referred to as GCAM-China (Yu et al, 2019). In GCAM-China, the 31 provinces are operated as explicit regions within the global GCAM model.…”

Section: The Gcam-china Modelmentioning

confidence: 99%

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socioeconomic, climate policy, and pollution control scenarios

Tong¹,

Cheng²,

Yang³

et al. 2020

Preprint

Self Cite

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Abstract. Future trends in air pollution and greenhouse gas (GHG) emissions for China are of great concern to the community. A set of global scenarios regarding future socioeconomic and climate developments, combining shared socioeconomic pathways (SSPs) with climate forcing outcomes as described by the representative concentration pathways (RCPs), were created by the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP-RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China&#8217;s future anthropogenic emission pathways. The DPEC model is designed to integrate the energy system model, emission inventory model, dynamic projection model, and parameterized scheme of Chinese policies. The model contains two main modules, an energy-model-driven activity rate projection module and a sector-based emission projection module. The activity rate projection module provides the standardized and unified future energy scenarios after reorganizing and refining the outputs from the energy system model. Here we use a new China-focused version of the Global Change Assessment Model (GCAM-China) to project future energy demand and supply in China under different SSP-RCP scenarios at the provincial level. The emission projection module links a bottom-up emission inventory model, the Multi-resolution Emission Inventory for China (MEIC), to GCAM-China, and accurately tracks the evolution of future combustion/production technologies and control measures under different environmental policies. We developed technology-based turnover models for several key emitting sectors (e.g., coal-fired power plants, key industries, and on-road transportation sectors), which can simulate the dynamic changes in the unit/vehicle fleet turnover process by tracking the lifespan of each unit/vehicle on an annual basis. With the integrated modelling framework, we connected five SSP scenarios (SSP1-5), five RCP scenarios (RCP 8.5, 7.0, 6.0, 4.5, and 2.6), and three pollution control scenarios (business as usual (BAU), enhanced control policy (ECP), and best health effect (BHE)) to produce six combined emission scenarios. With those scenarios, we presented a wide range of China's future emissions to 2050 under different development and policy pathways. We found that, with a combination of strong low-carbon policy and air pollution control policy (i.e., SSP1-26-BHE scenario), emissions of major air pollutants (i.e., SO2, NOx, PM2.5, and NMVOCs) in China will be reduced by 34&#8211;66&#8201;% in 2030 and 58&#8211;87&#8201;% in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play more important role for continuous emission reduction until 2050. On contrast, China's emissions will remain high level until 2050 under a reference scenario without active action (i.e., SSP3-70-BAU). Compared to similar scenarios set in the CMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates of emission ranges are much lower than the estimates from the CMIP6 in 2020/2030, but their emission ranges become similar in the year 2050.

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“…The dynamic material flow analysis method is used to analyze the energy demand of cooling, heating, hot water, and cooking in different regions of the construction department [41], taking factors such as economic and social development, per capita construction area, and possible climate change into account. The econometric method and industrial life cycle curve method are adopted in the industrial department [42], while the Global Change Assessment Model-China (GCAM-China) method is mainly used to predict passenger and freight turnover in transportation department uses [43]. In addition, driven by the results of the energy service demand prediction module, by applying linear programming using the General Algebraic Modelling System (GAMS), the energy system module analyzes the impact of different policies or measures on the energy system by setting different resources, technologies, and environmental constraints [44].…”

Section: Assumptionsmentioning

confidence: 99%

An Air Pollutant Emission Reduction Path of China’s Power Industry

Jin

et al. 2020

Atmosphere

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In China, as the major source of energy consumption and air pollutant emissions, the power industry is not only the principal force that bears the responsibility of national emission reduction targets but also a breakthrough that reflects the effectiveness of emission reduction. In this study, based on the integrated MARKAL-EFOM system (TIMES) model and scenario analysis method, a bottom-up energy system optimization model for the power industry was established, and four scenarios with different constraints were set up to predict and analyze the power demand and the energy consumption structure. Emission characteristics, emission reduction characteristics, and emission reduction cost of sulfur dioxide (SO2), nitrogen oxide (NOX), particulate matter 2.5 (PM2.5), and mercury (Hg) were quantitatively studied. Finally, for the environmentally friendly development and optimal adjustment of power production systems in China, the control path in the power industry that is conducive to the emission reduction of air pollutants was obtained, which is of great significance for the ultimate realization of climate friendliness. The results demonstrate that from 2020 to 2050, the power demand of the terminal departments will increase, with the composition significantly changed. The focus of power demand will change from industry to the service industry gradually. If no additional targeted emission reduction or adjustment policies are added in the power industry, the primary energy and air pollutant emissions will increase significantly, putting great pressure on resources and the environment. For the emission reduction of air pollutants, the promotion effect of emission reduction measures, such as the implementation and promotion of non-fossil fuels, is restricted. The power industry can introduce and maximize the best available technologies while optimizing the structure of energy consumption to realize efficient emission reduction of air pollutants and energy conservation. In 2030, emissions will reach peak values with reasonable emission reduction cost. This has the additional effect of abating energy consumption and preventing deterioration of the ecological environment, which is of profound significance for the ultimate realization of climate friendliness.

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CCUS in China’s mitigation strategy: insights from integrated assessment modeling

Cited by 90 publications

References 15 publications

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socioeconomic, climate policy, and pollution control scenarios

An Air Pollutant Emission Reduction Path of China’s Power Industry

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