Dataset Information

Optimal deployment for carbon capture enables more than half of China's coal-fired power plant to achieve low-carbon transformation.

ABSTRACT: Carbon capture, utilization and storage (CCUS) technology is critical to global net-zero emission goal, whereas actual deployment is well below expectations. This study constructs a comprehensive framework, integrating nonlinear dynamic optimization, real option and technology learning curve, to explore optimal CCUS deployment for China's coal-fired power plant toward carbon neutrality. The commercialization application will occur in 2030-2035, with the optimal potential ranging between 248.54 GW and 564.90 GW. East China has the greatest potential, reaching 196.85 GW, followed by North China with the potential of 116.29 GW. The cost of second-generation capture technology will decrease from 219 CNY/ton CO₂ to 165 CNY/ton CO₂ during 2030-2031.The annual corporate expenditure (R&D investment and capture cost) and government expenditure (subsidy) will peak at 23.92 billion CNY in 2035 and 63.71 billion CNY in 2044, respectively. The financial burden can be lessened by carbon trading market and third-party intervention in the later period.

SUBMITTER: Yang L

PROVIDER: S-EPMC9730147 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimal deployment for carbon capture enables more than half of China's coal-fired power plant to achieve low-carbon transformation.

Yang Lin L Wei Ning N Lv Haodong H Zhang Xian X

iScience 20221123 12

Carbon capture, utilization and storage (CCUS) technology is critical to global net-zero emission goal, whereas actual deployment is well below expectations. This study constructs a comprehensive framework, integrating nonlinear dynamic optimization, real option and technology learning curve, to explore optimal CCUS deployment for China's coal-fired power plant toward carbon neutrality. The commercialization application will occur in 2030-2035, with the optimal potential ranging between 248.54 G ...[more]

PMID: 36505929

Similar Datasets

Project description:BackgroundCoal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants contributes to children's neurobehavioral disorders.ObjectiveThis community-based study collected primary data to investigate the relationships of residential proximity to power plants and neurobehavioral problems in children.Methods235 participants aged 6-14 years who lived within 10 miles of two power plants were recruited. Exposure to particulate matter ≤10 μm (PM10) was measured in children's homes using personal modular impactors. Neurobehavioral symptoms were assessed using the Child Behavior Checklist (CBCL). Multiple regression models were performed to test the hypothesized associations between proximity/exposure and neurobehavioral symptoms. Geospatial statistical methods were used to map the spatial patterns of exposure and neurobehavioral symptoms.ResultsA small proportion of the variations of neurobehavioral problems (social problems, affective problems, and anxiety problems) were explained by the regression models in which distance to power plants, traffic proximity, and neighborhood poverty was statistically associated with the neurobehavioral health outcomes. Statistically significant hot spots of participants who had elevated levels of attention deficit hyperactivity disorder, anxiety, and social problems were observed in the vicinity of the two power plants.SignificanceResults of this study suggest an adverse impact of proximity to power plants on children's neurobehavioral health. Although coal-fired power plants are being phased out in the US, health concern about exposure from coal ash storage facilities remains. Furthermore, other countries in the world are increasing coal use and generating millions of tons of pollutants and coal ash. Findings from this study can inform public health policies to reduce children's risk of neurobehavioral symptoms in relation to proximity to power plants.

Dataset Information

Optimal deployment for carbon capture enables more than half of China's coal-fired power plant to achieve low-carbon transformation.

Publications

Optimal deployment for carbon capture enables more than half of China's coal-fired power plant to achieve low-carbon transformation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets