publications.bib

@article{Li2019,
abstract = {{\textcopyright} 2019 by the authors. China's steel industry is an energy-intensive sector. Synergistic reduction of emissions of CO 2 and air pollutants (SO 2 , NOx, and PM2.5) in the steel industry has an important practical significance for climate change and air pollution control. According to the CO 2 emission reduction intensity targets (CERO) and air pollutant emission targets (PERO) for 2020 and 2030, 28 types of energy-saving and emission reduction technologies (20 types of carbon reduction technology and eight types of air pollution end-of-pipe technology) were selected for examination, and a two-stage dynamic optimization model with collaborative implementation of PERO and CERO was built to assess the near future (2015-2020) and long-term (2020-2030) implementation plans for synergistic emissions reduction of CO 2 and air pollutants. The results show that in the near future, the implementation of PERO will have a greater synergistic effect on CO 2 emission reduction. CO 2 emission reduction under PERO in 2020 will be 97 million tons (Mt) higher than that of CERO, an increase of nearly 26{\%}. However, the effects of implementing CERO are better in the long run. Under CERO, the emission reductions of SO 2 , NOx, and PM2.5 in 2030 are 2.44 Mt, 1.47 Mt, and 0.86 Mt, respectively, and 7{\%}, 4{\%}, and 5{\%} higher than the implementation of PERO. As far as marginal abatement cost is concerned, in the near future, the marginal abatement costs of CO 2 and air pollutant equivalents are 1.06 yuan/kgCO 2 and 133 yuan/kg pollution equivalent (pe) under PERO, which are 23{\%} and 11{\%} lower than that of CERO, while in the long run, the marginal abatement costs of CO 2 and pollutant equivalents under CERO are 0.025 yuan/kgCO 2 and 2.73 yuan/kgpe, about 96{\%} and 95{\%} lower than that of PERO.},
author = {Li, H. and Tan, X. and Guo, J. and Zhu, K. and Huang, C.},
doi = {10.3390/su11020352},
issn = {20711050},
journal = {Sustainability (Switzerland)},
keywords = {Air pollution treatment,CO   emission reduction  2,Steel industry,Synergistic emission reduction},
number = {2},
title = {{Study on an implementation scheme of synergistic emission reduction of CO2 and air pollutants in China's steel industry}},
volume = {11},
year = {2019}
}
@article{Huang2019,
abstract = {{\textcopyright} 2019 Elsevier Ltd Effective policy requires comprehensive analysis of many factors. But presently there does not exist a sufficiently comprehensive research on the interrelationship between energy input and output, carbon emissions, and water use in the oil and gas extraction process. To more comprehensively measure this phenomenon, this paper constructs an assessment model of energy return on energy, carbon, and water investment for the development of oil and gas resources using the Daqing and Shengli oilfields as practical examples. The results show that the method for evaluating energy input and output (energy return on energy invested) can be made more comprehensive for covering the resources required in the oilfield extraction process; this method ignores the environmental impacts of carbon emissions (energy return on carbon) and water use (energy return on water). However, the energy return evaluation method, which considers energy, carbon, and water inputs, is more comprehensive and practically used to evaluate the development status of oil and gas resources as well as other types of energy development processes. Policy implications for biophysical input accounting and the management of energy resource extraction are given accordingly.},
author = {Huang, C. and Gu, B. and Chen, Y. and Tan, X. and Feng, L.},
doi = {10.1016/j.enpol.2019.110979},
issn = {03014215},
journal = {Energy Policy},
keywords = {EROC,EROI,EROW,Oil and gas resources extraction},
title = {{Energy return on energy, carbon, and water investment in oil and gas resource extraction: Methods and applications to the Daqing and Shengli oilfields}},
volume = {134},
year = {2019}
}
@article{Guo2020,
abstract = {{\textcopyright} 2019 Elsevier B.V. Carbon utilization and storage (CCUS) project represented by enhanced oil recovery (EOR) technology provides a feasible way for the CCS dynamic cost to decline. With the development of CCS and the cost reduction of power plant capture, the possibility of oil companies receiving CO2 from power plants will increase, which makes CO2 and oil resources more fully utilized. Based on this fact, this work proposes a novel model regarding the CCS–EOR project to systematically evaluate the CCS development path and the EOR utilization process. By considering the CO2 source captured by CCS and the utilization process of EOR process, the cost-benefit model of integrated system is established, and the CO2 capture/injection path of CCS/EOR is optimized. This model helps to analyze CCS investment and carbon capture process from the perspective of the whole project process, and provides a feasible reference for practical large-scale engineering decision-making project.},
author = {Guo, J.-X. and Huang, C. and Wang, J.-L. and Meng, X.-Y.},
doi = {10.1016/j.petrol.2019.106720},
issn = {09204105},
journal = {Journal of Petroleum Science and Engineering},
keywords = {Carbon capture and storage,Carbon capture path,Enhanced oil recovery,Integrated operation},
title = {{Integrated operation for the planning of CO2 capture path in CCS–EOR project}},
volume = {186},
year = {2020}
}
@article{Guo2020a,
abstract = {{\textcopyright} 2019 Elsevier Ltd In the medium to long term, China must conduct deep emission reduction actions to transform the country's economy and meet the conditions of the Paris Agreement. As an advanced emission reduction technology, carbon capture and storage (CCS) is undoubtedly an important means of achieving this goal. China must consider how to retrofit existing thermal power plants to install CCS technology. Thus, the expected future roadmap for power plants with CO2 capture is of significant interest. To achieve this aim, we propose a new CCS project investment model, which helps design the CCS development roadmap for achieving the emission targets for 2050. Reductions in the cost of technologies as a result of learning-by-doing is considered to enrich the model to describe the reality more sensibly. Through some mathematical skills, we transform the original continuous problem into a nonlinear integer programming problem. By solving the model, we are trying to answer questions about when to adopt CCS technology and the cost. The results reveal that early large-scale CCS demonstrations are not necessary. The peak investment period of CCS is around 2035. Operating costs account for 80{\%} of the overall cost of CCS, and thus, policymakers must fully motivate the development and investment of operating technologies, especially capture technologies. The results also show that when the scale of CCS technology is promoted, flexible installation levels can be considered to improve efficiency and reduce costs.},
author = {Guo, J.-X. and Huang, C.},
doi = {10.1016/j.apenergy.2019.114112},
issn = {03062619},
journal = {Applied Energy},
keywords = {Abatement strategy,CCS development roadmap,Learning by doing,Nonlinear integer programming},
title = {{Feasible roadmap for CCS retrofit of coal-based power plants to reduce Chinese carbon emissions by 2050}},
volume = {259},
year = {2020}
}
@article{CHEN2020120933,
abstract = {Energy Return on Investment (EROI) has become a policy analysis tool related to sustainability. However, most EROI studies adopt the standard EROI method, which has two inherent defects. First, standard EROI leaves out energy quality. Second, input factors such as labor, auxiliary services and environmental factors are not considered. Therefore, this paper introduces exergy into the EROI calculation and establishes a new extended exergy-based EROI (ExEROI). ExEROI treats “available energy” as energy quality; with the idea of embodied flows, ExEROI quantifies all the five input factors of the EROI analysis framework. Shale gas exploitation in the Sichuan Basin is used as an example in the case study. The ExEROI result is 9.68, which is much lower than the standard EROI result of 82.95. This is due to the inclusion of more input factors and the fact that the input factors are measured by exergy. Specifically, the auxiliary service input factor accounts for 77.10{\%} of the total inputs, and such inputs are ignored by the standard EROI method. ExEROI makes up for the shortcomings of standard EROI and avoids the possible misinformation caused by standard EROI. ExEROI has the potential for use as an integral aspect of energy resource exploitation evaluations.},
author = {Chen, Yingchao and Feng, Lianyong and Tang, Songlin and Wang, Jianliang and Huang, Chen and H{\"{o}}{\"{o}}k, Mikael},
doi = {https://doi.org/10.1016/j.jclepro.2020.120933},
issn = {0959-6526},
journal = {Journal of Cleaner Production},
keywords = {Energy return on investment,Extended-exergy,Shale gas extraction},
pages = {120933},
title = {{Extended-exergy based energy return on investment method and its application to shale gas extraction in China}},
url = {http://www.sciencedirect.com/science/article/pii/S095965262030980X},
volume = {260},
year = {2020}
}
@article{Chen2018,
abstract = {By using Derwent Innovation Patent Database and an improved DWPI manual code classification,we applied the methods of patent distribution structure,patent application trends and future patent development forecast to analyze the oil gas industry's patents. In recent years,owing to the industry's main business income decline,the number of annual patent applications shows a downward trend in oil gas exploration and mining industry,as well as in oil gas refining industry. With the rapid development of domestic storage and transportation business,the development trend of oil gas storage and transportation industry patents is promising.},
author = {Chen, Huang and Yinghua, Xu and Lianyong, Feng and Yingchao, Chen and Ke, Wang},
doi = {10.3969 /j.issn.1000-7695.2018.20.023},
journal = {Science and technology management research},
number = {20},
pages = {164--169},
title = {{Analysis on Development Trend of Patents in China Oil {\&} Gas Industry (In Chinese)}},
volume = {38},
year = {2018}
}
@mastersthesis{Chen2018a,
abstract = {As one of the essential sub-industry of the energy industry, the oil{\&} gas extraction industry contributes oil{\&} gas resources for our social-economic system. Meanwhile, it consumes energy inputs as the investment in energy resources exploitation, emits greenhouse gases(GHG), and consumes water resources. There is still a lack of systematic research on energy input, carbon emissions and water consumption of oil and gas extraction industry. To accurately measure the exploitation status and concomitant environmental impacts of the oil{\&} gas extraction industry, the present study, from a perspective of huge oilfields, applies the theory of industrial metabolism from industrial ecology research field to investigate the energy, carbon and water metabolism of oil{\&} gas extraction industry. This paper builds a comprehensive assessment model for energy, carbon, and water metabolism in oil{\&} gas industry and applies it to research objects such as Daqing and Shengli oilfields. The results show that from the perspective of energy metabolism, for Daqing, Shengli, Liaohe oilfields, their EROIs are all declining and the future net energy outputs of them will significantly drop; the EROIs of Xinjiang and Shaanxi provinces'oil{\&} gas extraction display rising trends. The EROIs of the imported oil{\&} gas are generally higher than domestic oilfields. The accounting results of carbon metabolism show that the carbon emissions of Daqing and Shengli oilfields are declining. The EROC of Daqing is basically higher than Shengli. The water metabolism results show that, for Daqing's industrial water use and freshwater use, both rise originally and then decline; The industrial and freshwater consumptions of Shengli oilfield are both falling. The direct water consumptions of Shengli and Daqing are rising. The EROWFresh of Shengli is generally higher than Daqing. However, the EROWTotal of Shengli almost equals to Daqing. Within the research field, for Shengli and Daqing oilfields, the EROIs is generally backsliding. However, the EROC and EROWFresh are rising; both of them needs more energy inputs, fewer carbon emissions, and fewer freshwater consumptions to produce one unit energy outputs. To slow down the downward trend of net energy output of Shengli and Daqing, and simultaneously, to continually alleviate the environmental impacts of oil{\&} gas production process, we need the oil{\&} gas industry to reduce energy, carbon, and water uses intensities unceasingly by using multiple methods. The oilfields ought to mitigate direct energy inputs, carbon emissions, and water consumptions.},
author = {Chen, Huang},
school = {China University of Petroleum (Beijing)},
title = {{Research on the metabolism of oil{\&} gas extraction industry: from the perspective of huge oilfields (In Chinese)}},
year = {2018}
}
@Article{niu2021,
AUTHOR = {Niu, Miaomiao and Tan, Xianchun and Guo, Jianxin and Li, Guohao and Huang, Chen},
TITLE = {Driving Factors and Growth Potential of Provincial Carbon Productivity in China},
JOURNAL = {Sustainability},
VOLUME = {13},
YEAR = {2021},
NUMBER = {17},
ARTICLE-NUMBER = {9759},
URL = {https://www.mdpi.com/2071-1050/13/17/9759},
ISSN = {2071-1050},
ABSTRACT = {Climate change has become a global concern, and the development of a green economy has attracted wide attention. Understanding the driving factors and growth potential of provincial-level carbon productivity is crucial for China’s green economic development in the new normal phase. In this study, the logarithmic mean Divisia index (LMDI) is adopted to systematically investigate the driving factors of provincial carbon productivity and explore the growth potential of provinces’ carbon productivity based on the clustering analysis. The results show that: (1) China’s provincial carbon productivity presents an increasing trend in 2001–2017, but the differences in carbon productivity among provinces are widening. (2) Economic activity and industrial structure are key to push up regional carbon productivity in China, while energy intensity is the main factor pulling it down. (3) The potential for carbon productivity improvement varies greatly among provinces in the four groups. Specifically, in groups 1 and 2, the developed provinces have little potential for improving carbon productivity, while the developing provinces in group 4 are just the opposite. These findings can enlighten policymakers that the development of a green economy should focus on optimizing and upgrading industrial structure and reducing energy intensity, and provincial heterogeneity must be considered when formulating green economic development policies.},
DOI = {10.3390/su13179759}
}
@article{liu2022evaluating,
  title={Evaluating cost and benefit of air pollution control policies in China: a systematic review},
  author={Liu, Xinyuan and Guo, Chaoyi and Wu, Yazhen and Huang, Chen and Lu, Keding and Zhang, Yuanhang and Duan, Lei and Cheng, Miaomiao and Chai, Fahe and Mei, Fengqiao and others},
  journal={Journal of Environmental Sciences},
  year={2022},
  publisher={Elsevier}
}
@article{xian2022analysis,
  title={Analysis on the key findings related to emission trends and drivers from the IPCC AR6 report},
  author={Xian-Chun, TAN and Han-Cheng, DAI and Bai-He, GU and Chen, HUANG and Kai-Wei, ZHU and Xiao-Tian, MA and Hong-Shuo, YAN and Xin-Yuan, LIU and Yan-Lei, ZHU},
  journal={Advances in Climate Change Research},
  pages={0},
  year={2022}
}
@article{liu2022uncovering,
  title={Uncovering the key mechanisms of how deep decarbonization benefits air pollution alleviation in China},
  author={Liu, Xiaorui and Guo, Chaoyi and Ma, Xiaotian and Wu, Kai and Wang, Peng and Huang, Zhijiong and Zhou, Ziqiao and Huang, Chen and Zhang, Silu and Wang, Minghao and others},
  journal={Environmental Research Letters},
  year={2022},
  publisher={IOP Publishing}
}
@article{HUANG2023106704,
title = {Prospective climate change impacts on China's fossil and renewable power-generation infrastructure: Regional and plant-level analyses},
journal = {Resources, Conservation and Recycling},
volume = {188},
pages = {106704},
year = {2023},
issn = {0921-3449},
doi = {https://doi.org/10.1016/j.resconrec.2022.106704},
url = {https://www.sciencedirect.com/science/article/pii/S0921344922005377},
author = {Chen Huang and Yuyao Zhu and Ming Ren and Pei Zhang and Yingchao Chen and Hancheng Dai and Xianchun Tan},
keywords = {Climate risk, Power infrastructure, Climate resilience, Climate adaptation},
abstract = {The energy infrastructure has emitted massive GHGs and will suffer greatly from climate risks. Given China's largest installed capacity globally, assessing climate impacts on diverse power infrastructures will yield critical risk information and support climate-resilient policymaking. However, lacking detailed plant-level data and ignoring the integrated infrastructural management of adaptation and mitigation priorly impede an in-depth evaluation. By employing high-coverage and -resolution plant-level data and the outputs of six CMIP6 models, we evaluate the pending climate impacts on five power-production sources at the interprovincial and plant levels in China. We find a pervasive negative impact on China's power sector, and the adverse effects expand over time (short-term: 214–342 TWh, long-term: 268–397 TWh, 25–75% quantile). For different future scenarios, the greater the radiative forcing, the greater the loss of power generation. Fossil-related production loss will completely offset the gain in most provinces from renewable power, with an overall negative impact in these regions. Besides, two evident phenomena occur: First, spatial heterogeneity appears across diverse provinces; second, a critical minority of China's plants with a low capacity share contribute to the main body of climate impacts. We consider the need for a targeted coal decommissioning strategy for climate adaptation.}
}
@article{zhai2023feasibility,
  title={Feasibility analysis of achieving net-zero emissions in China's power sector before 2050 based on ideal available pathways},
  author={Zhai, Hanbing and Gu, Baihe and Zhu, Kaiwei and Huang, Chen},
  journal={Environmental Impact Assessment Review},
  volume={98},
  pages={106948},
  year={2023},
  publisher={Elsevier}
}
@article{REN2023120254,
title = {Negative emission technology is key to decarbonizing China's cement industry},
journal = {Applied Energy},
volume = {329},
pages = {120254},
year = {2023},
issn = {0306-2619},
doi = {https://doi.org/10.1016/j.apenergy.2022.120254},
url = {https://www.sciencedirect.com/science/article/pii/S0306261922015112},
author = {Ming Ren and Teng Ma and Chen Fang and Xiaorui Liu and Chaoyi Guo and Silu Zhang and Ziqiao Zhou and Yanlei Zhu and Hancheng Dai and Chen Huang},
keywords = {Cement industry, Integrated assessment model, Carbon neutrality, Bioenergy with carbon capture and storage, Environmental impact},
abstract = {The cement industry, which contributes to 8 % of global CO2 emissions and a large quantity of air pollutants, plays a pivotal role in achieving the carbon neutrality target. However, the question of how to decarbonize the cement industry toward net-zero emissions and the corresponding environmental impact remains unclear. An integrated assessment framework combining a top-down computable general equilibrium model, a bottom-up technology selection model, and a life-cycle assessment was developed to explore the cement industry’s carbon–neutral pathways and associated environmental impact. Results show that promoting energy-efficient technologies is crucial for reducing CO2 emissions in the short term, which can also significantly reduce air pollutant emissions. Improving energy efficiency contributes to reducing the emissions of SO2, NOx, and PM2.5, by 33 %, 35 %, and 8 %, respectively, by 2030. In the long run, achieving net-zero carbon emissions requires implementation of bioenergy with carbon capture and storage (BECCS) and demand-side mitigation measures. The share of kilns equipped with BECCS would increase to 68–75 % by 2060. Corresponding unit abatement costs of CO2 are 484–676 CNY/tonne CO2. However, BECCS triggers adverse side effects by increasing water consumption and land cover by 7–11 km3 and 3–4 Mha, respectively, in 2060. Thus, China should take full advantage of energy-efficient technologies to co-control CO2 and air pollutant emissions while avoiding negative effects of BECCS.}
}