SHAO Qinglong

Academic Background

• Associate Professor & PhD Supervisor, School of Ecology, Sun Yat-sen University(Shenzhen) (2025–present);
• Humboldt Fellow; Listed among Top 2% of Scientists Worldwide (2023 & 2024)by Stanford University, in Earth & Environmental Sciences;
• PhD (Joint Training Program), Universitat Autònoma de Barcelona, Institute of Social Ecology Vienna, and KTH Royal Institute of Technology;
• Engaged in interdisciplinary research at the interface of ecology/environment and economics; author of 50+ publications in Chinese and international journals; Principal Investigator/participant in over 10 research projects.

Research Interests

1. Ecological, Energy, and Environmental Economics

• Energy transition, energy justice, and energy poverty
• Green finance and sustainable investment
• Climate change and regional economic adaptation

2. Doughnut Model for Sustainable Development Assessment

• Planetary boundaries and sustainability assessment
• Linking socio-economic boundaries with biophysical limits
• Spatiotemporal analysis based on regional heterogeneity

3. Artificial Intelligence and Sustainability

• AI for optimizing resource allocation and ecosystem services
• AI-assisted multidimensional assessment and policy simulation of the Doughnut economy
• AI-driven green economic transition and practical applications of the Doughnut model

Academic Service

• Associate Editor, npj Climate Action
• Editorial Board Member of four leading international journals (Q1): Environmental Science and Ecotechnology, Environmental Technology & Innovation, Sustainable Development, and Humanities and Social Sciences Communications
• Author to The Fifth National Assessment Report on Climate Change (Lead author), World Energy Blue Book: Annual Report on World Energy Development (2024)(Chapter author), and the SAGE Handbook of Modern China: Transformations and Transitions(Chapter author).

Selected Grants and Projects (as Principal Investigator)

• Erasmus+ Jean Monnet Module (ERASMUS-JMO-2025-MODULE, 101234644 — DoughEU)

              Reimagining EU Sustainability: The Doughnut Economics Model as a Path to a Safe and Just Operating Space (2026–2028)

• Alexander von Humboldt Foundation Research Fellowship (1194898 HFST-P)

              Digital Governance for Sustainable Development in the COVID-19 Era in China: A Planetary Boundary Perspective (2022–2025)

• National Natural Science Foundation of China – Youth Project (71903131)

              Sustainability Assessment of the Guangdong–Hong Kong–Macao Greater Bay Area: A Spatial Econometric and Planetary Boundaries Perspective (2020–2023)

• China Postdoctoral Science Foundation (2019M653047)

              Empirical Analysis of Global Material Consumption and Economic Recession Based on Econometric Models (2019–2020)

• Major Research Project, Shenzhen Development Research Center

              High-Quality Land Use in Mega-Cities (2019–2020)

Selected publications

[1] Ying Jiang, Guikun Yin, Qinglong Shao*. Individualism and Support for COVID-19 Government Interventions: The Moderating Role of Perceived Economic Risk. Economics and Human Biology. DOI: 10.1016/j.ehb.2025.101513

[2] Qinglong Shao*. Did the pandemic undermine climate concern in Europe? a re-assessment of the Finite Pool of Worry. Climate Policy. DOI: 10.1080/14693062.2025.2510500

[3] Qinglong Shao*. Sustainability evaluation of the Doughnut Economics: A bibliometric analysis. Earth's Future. DOI: 10.1029/2024EF004638

[4] Qinglong Shao*. Systematic Review of Doughnut Economics from 2012 to 2024. Sustainability Science. DOI: 10.1007/s11625-025-01640-8.

[5] Qinglong Shao*. Assessing the sustainability of socio-economic boundaries in China: A downscaled “safe and just space” framework. npj Climate Action. 2023, 2(28). DOI: 10.1038/s44168-023-00062-5. 

[6] Songran Li, Qinglong Shao*. How do financial development and environmental policy affect renewable energy innovation? The Porter Hypothesis and beyond. Journal of Innovation & Knowledge. 2023, 8(3). DOI: 10.1016/j.jik.2023.100369.

[7] Qinglong Shao*. Pathway through which COVID-19 exacerbates energy poverty and proposed relief measures. Energy for Sustainable Development. 2023 (74). DOI: 10.1016/j.esd.2023.03.008. 

[8] Songran Li, Qinglong Shao*. Greening the finance for climate mitigation: An ARDL–ECM approach. Renewable Energy. Volume 199, 2022, 1469-1481. DOI: 10.1016/j.renene.2022.09.071.

[9] Qinglong Shao, Zhekai Zhang*. Carbon mitigation effect of emissions trading policy in China considering the regional disparity. Energy and Climate Change. Volume 3, Dec. 2022, 100079. DOI: 10.1016/j.egycc.2022.100079. 

[10] Xiaoling Wang, Tianyue Zhang, Jatin Nathwani, Fangming Yang, Qinglong Shao*. Environmental regulation, technology innovation, and low carbon development: Revisiting the EKC Hypothesis, Porter Hypothesis, and Jevons’ Paradox in China's iron & steel industry. Technological Forecasting and Social Change, Volume 176, March 2022, 121471. DOI: 10.1016/j.techfore.2022.121471. (Highly Cited + Hot Paper)

[11] Songran Li, Qinglong Shao*. Exploring the Determinants of Renewable Energy Innovation Considering the Institutional Factors: A Negative Binomial Analysis. Technology in Society, Volume 67, November 2021, 101680. DOI: 10.1016/j.techsoc.2021.101680. 

[12] Zhanglan Wu, Qinglong Shao*, Yantao Su, Dan Zhang. A socio-technical transition path for new energy vehicles in China: a multi-level perspective. Technological Forecasting and Social Change, Volume 172, November 2021, 121007. DOI: 10.1016/j.techfore.2021.121007. 

[13] Qinglong Shao, Junjie Guo*, Peng Kang. Environmental response to growth in the marine economy and urbanization: A heterogeneity analysis of 11 Chinese coastal regions using a panel vector autoregressive model. Marine Policy, Volume 124, 2021, 104350. DOI: 10.1016/j.marpol.2020.104350. 

[14] Renqu Tian†, Qinglong Shao†, Fenglan Wu*. Four-dimensional evaluation and forecasting of marine carrying capacity in China: empirical analysis based on the entropy method and grey Verhulst model. Marine Pollution Bulletin, Volume 160, 2020, 111675. DOI: 10.1016/j.marpolbul.2020.111675. 

[15] Qinglong Shao*. Nonlinear effects of marine economic growth and technological innovation on marine pollution: Panel threshold analysis for China’s 11 coastal regions. Marine Policy, 15 August 2020, 104110. DOI: 10.1016/j.marpol.2020.104110. 

[16] Qinglong Shao, Xuechen Liu*, Weijun Zhao. An alternative method for analyzing dimensional interactions of urban carrying capacity: Case study of Guangdong-Hong Kong-Macao Greater Bay Area. Journal of Environmental Management, Volume 273, 1 November 2020, 111064. DOI: 10.1016/j.jenvman.2020.111064.

[17] Xuedi Ren, Qinglong Shao*, Ruoyu Zhong. Nexus between green finance, non-fossil energy use, and carbon intensity: Empirical evidence from China based on a vector error correction model. Journal of Cleaner Production, Volume 277, 20 December 2020, 122844. DOI: 10.1016/j.jclepro.2020.122844. (Highly Cited Paper)

[18] Qian Zhou, Qinglong Shao, Xiaoling Zhang*, Jie Chen. Do housing prices promote total factor productivity? Evidence from spatial panel data models in explaining the mediating role of population density. Land Use Policy. Volume 91, Feb 2020. DOI: 10.1016/j.landusepol.2019.104410.

[19] Xiaoling Wang, Yawen Wei, Qinglong Shao*. Decomposing the decoupling of CO2 emissions and economic growth in China’s iron and steel industry. Resources, Conservation and Recycling, Volume 152, January 2020. DOI: 10.1016/j.resconrec.2019.104509. 

[20] Xiaoling Wang, Qinglong Shao*, Jatin Nathwani, Qian Zhou. Measuring wellbeing performance of carbon emissions using hybrid measure and meta-frontier techniques: Empirical tests for G20 countries and implications for China. Journal of Cleaner Production, Volume 237, 10 November 2019. DOI: 10.1016/j.jclepro.2019.117758. 

[21] Qian Zhou, Xiaoling Zhang*, Qinglong Shao*, Xiaoling Wang. The non-linear effect of environmental regulation on haze pollution: Empirical evidence for 277 Chinese cities during 2002-2010. Journal of Environmental Management, Volume 248, 15 October 2019. DOI: 10.1016/j.jenvman.2019.109274. 

[22] Qinglong Shao, Xiaoling Wang*, Qian Zhou, László Balogh. Pollution haven hypothesis revisited: A comparison of the BRICS and MINT countries based on VECM approach. Journal of Cleaner Production, Volume 227, 1 August 2019, p.724-738. DOI: 10.1016/j.jclepro.2019.04.206. 

[23] Zhanglan Wu, Anke Schaffartzik, Qinglong Shao*, Dong Wang, Guicai Li, Yantao Su. Does Economic Recession Reduce Material Use? Empirical Evidence based on 157 Economies Worldwide. Journal of Cleaner Production, Volume 214, 20 March 2019, p. 823-836. DOI: 10.1016/j.jclepro.2019.01.015.

[24] Xiaoling Wang, Qinglong Shao*. Non-linear effects of heterogeneous environmental regulations on green growth in G20 countries: Evidence from panel threshold regression. Science of the Total Environment. Volume 660, 10 April 2019, p.1346-1354. DOI: 10.1016/j.scitotenv.2019.01.094. (Highly Cited Paper)

[25] Xiao Ouyang, Qinglong Shao*, Xiang Zhu*, Qingyun He, Chao Xiang, Guoen Wei. Environmental regulation, economic growth and air pollution: Panel threshold analysis for OECD countries. Science of the Total Environment, Volume 657, 20 March 2019, p. 234–241. DOI: 10.1016/j.scitotenv.2018.12.056. (Highly Cited Paper)

[26] Qinglong Shao*, Anke Schaffartzik, Andreas Mayer, Fridolin Krausmann. The high 'price' of dematerialization: A dynamic panel data analysis of material use and economic recession. Journal of Cleaner Production, Volume 167, 1 November 2017, p. 120-132. DOI: 10.1016/j.jclepro.2017.08.158.

Join Our Research Group!

We are looking for motivated researchers to join our team at the intersection of ecological economics, sustainability assessment, and artificial intelligence for green transitions. Our projects focus on topics such as energy transition and justice, the Doughnut model for sustainable cities, planetary boundaries, and AI applications in sustainability science.

• Requirements:

              Academic Background: Ecology/Environmental Science, Economics, Artificial Intelligence, or related disciplines

Technical Skills: Strong programming skills (Python, R, or related software); experience in survey design and data analysis is highly desirable

• Opportunities:

              We welcome applications for positions at multiple levels, including Research Assistants, Master’s students, PhD students, and Postdoctoral researchers. We offer an interdisciplinary environment, international collaboration opportunities, and engagement with real-world sustainability policy and practice.

              If you are passionate about contributing to solutions for a more just and sustainable future, we encourage you to get in touch.