With the intensification of global climate change and resource and environmental pressures, the concept of Environmental, Social, and Governance (ESG) has gradually become a core guide for policy formulation and corporate strategy. Traditional environmental policies have mostly focused on local pollution control and the improvement of single environmental indicators. However, under the ESG framework, environmental policies need to comprehensively consider the multidimensional interactions between the economy, society, and the environment, promoting synergistic effects among policies, especially cross-regional collaborative cooperation. This paper aims to analyze how environmental policies in different regions can collaborate after the introduction of ESG concepts, explore new cross-regional collaboration models in areas such as carbon emission control, water resource allocation, and biodiversity conservation, and utilize big data analysis to evaluate the actual effectiveness of cross-regional policy collaboration in improving environmental indicators. The study finds that ESG-driven cross-regional policy collaboration can not only effectively enhance the efficiency of environmental governance but also promote resource sharing and equitable development among regions, providing new ideas for building a green and sustainable development path.

Peng Xiaohui. Exploring the synergistic effect of ESG-driven environmental policies and the cross-regional linkage mechanism. Academic Journal of Environment & Earth Science(2025), Vol. 7, Issue 2: 38-46. https://doi.org/10.25236/AJEE.2025.070204.

[1] Asian Infrastructure Investment Bank. (2023). AIIB Green Infrastructure Investment. Retrieved from [AIIB official website]. https://www.aiib.org/en/about-aiib/who-we-are/infrastructure-for-tomorrow/green-infrastructure/index.html

[2] Australian Government Department of Agriculture, Water and the Environment. (2023). Water Trading in the Murray-Darling Basin. Retrieved from [Department of Agriculture, Water and the Environment website]. https://www.agriculture.gov.au/water/policy/water-recovery/water-market-trading

[3] Boyd, J., & Banzhaf, S. (2007). What are ecosystem services? The need for standardized environmental accounting units. Ecological Economics, 63(2-3), 616-626. https://doi.org/10.1016/j.ecolecon.2007.01.002

[4] Climate Bonds Initiative. (2023). Green Bonds: The State of the Market 2023. Retrieved from [Climate Bonds Initiative website] https://www.climatebonds.net/resources/reports/global-state-market-report-2023

[5] Copernicus. (2021). Copernicus Open Access Hub. Retrieved from [Copernicus website] https://scihub.copernicus.eu/

[6] Crooks, K. R., & Sanjayan, M. (2006). Connectivity conservation. Cambridge University Press.

[7] European Commission. (2023). Emissions Trading System (ETS). Retrieved from [European Commission website] https://ec.europa.eu/clima/policies/ets_en

[8] EPA (U.S. Environmental Protection Agency). (2020). Air Quality Monitoring. Retrieved from [EPA website] https://www.epa.gov/air-trends/air-quality-monitoring

[9] Hao, Y., Liu, Y., & Wang, H. (2018). The impact of China's air pollution control policies on economic growth. Journal of Cleaner Production, 188, 322-334. https://doi.org/10.1016/j.jclepro.2018.03.230

[10] IUCN (International Union for Conservation of Nature). (2016). European Green Belt Initiative. Retrieved from [IUCN website] https://www.iucn.org/theme/green-economy/our-work/european-green-belt

[11] Jensen, J. R. (2009). Remote sensing of the environment: An earth resource perspective. Pearson Prentice Hall.

[12] Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures and their consequences. Sage Journals, 8(1), 1-13. https://doi.org/10.1177/2053951714528481

[13] Kunreuther, H., & Michel-Kerjan, E. (2015). Managing extreme events: Using insurance and other financial instruments to mitigate disaster risks. In Handbook of Disaster Research (pp. 417-434). Springer.

[14] Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2015). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.

[15] NParks (National Parks Board, Singapore). (2020). Park Connector Network. Retrieved from [NParks website] https://www.nparks.gov.sg/gardens-parks-and-nature/park-connector-network

[16] OECD (Organisation for Economic Co-operation and Development). (2015). The Economic Consequences of Environmental Policy. OECD Publishing.

[17] Salvatore, M., Fiore, A., & Zolnik, E. (2018). Big data analytics for policy making in public administration: A literature review and research agenda. Journal of Policy Analysis and Management, 37(4), 862-884. https://doi.org/10.1002/pam.22110

[18] United Nations Economic Commission for Europe. (2023). Transboundary Water Cooperation. Retrieved from [UNECE website] https://unece.org/fileadmin/DAM/env/water/publications/twc_brochure_final_web.pdf

[19] Varian, H. R. (2014). Big data: New tricks for econometrics. Journal of Economic Perspectives, 28(2), 3-28. https://doi.org/10.1257/jep.28.2.3

[20] Wald, D. J., Quitmeyer, R. C., Heaton, T. H., & Kanamori, H. (2016). Early warning system for earthquakes in southern California. Bulletin of the Seismological Society of America, 106(5), 2154-2164. https://doi.org/10.1785/0120160039

[21] Wang, Y., Di, H., & Zeng, X. (2016). Social media data analytics for disaster response and management. International Journal of Information Management, 36(5), 702-709. https://doi.org/10.1016/j.ijinfomgt.2016.05.006

[22] Water, M. (Ed.). (2023). Integrated Water Resources Management (IWRM). World Bank. (Assume this is a general reference to IWRM principles and practices as advocated by the World Bank, without a specific publication title or URL.)

[23] WWF (World Wildlife Fund). (2019). Biodiversity Offsetting: A Guide for Business. Retrieved from [WWF website] https://www.worldwildlife.org/publications/biodiversity-offsetting-a-guide-for-business

[24] Zhang, B., Wang, Z., & Xu, H. (2017). The impact of China's ecological compensation policy on the sustainable development of poor areas: A case study of Shaanxi Province. Sustainability, 9(9), 1612. https://doi.org/10.3390/su9091612

[25] Zhang, Y., Wang, Y., Chen, G., & Li, L. (2019). Air quality prediction using multisource big data and machine learning methods: A case study in Beijing during the 2014 APEC summit. Journal of Cleaner Production, 239, 118038. https://doi.org/10.1016/j.jclepro.2019.118038

[26] Guiding Opinions on Constructing a Green Financial System. Retrieved from [People's Bank of China website] http://www.pbc.gov.cn/english/130721/3131759/index.html

[27] China Green Bond Market Development Report. Retrieved from [Green Finance Committee of the China Society for Finance and Banking website] http://www.zgjrxh.org/

[28] China Green Fund Development Report. Retrieved from [Asset Management Association of China website] https://www.amac.org.cn/

[29] Report on the Construction and Development of China's National Carbon Emissions Trading Market. Retrieved from [Ministry of Ecology and Environment website] https://www.mee.gov.cn/

[30] China's Integrated Water Resources Management Report. Retrieved from [Ministry of Water Resources website] https://www.mwr.gov.cn/