Ofori, Elvis KwameLi, JinkaiGyamfi, Bright AkwasiOpoku-Mensah, EvansZhang, Jin2024-09-112024-09-1120230301-47971095-8630https://doi.org/10.1016/j.jenvman.2023.118121https://hdl.handle.net/11363/7734Anthropogenic global warming strategies on carbon mitigation are driven by encouraging green innovation and using carbon taxes, yet an empirical model to validate this is non-existing. Moreover, the existing stochastic effects by regression on population, wealth, and technology (STIRPAT) model has been found to lack policy tools on taxes and institutions that cut carbon emissions. This study amends the STIRPAT model with environmental technology, environmental taxes, and strong institutional frameworks to create a new model STIRPART(sto-chastic impacts by regression on population, affluence, regulation, and technology) to understand the factors impacting carbon pollution using the emerging 7 economies. Using data from 2000 to 2020, the Driscoll-Kraay fixed effects are employed in this analysis to conduct evidential tests of the impacts of environmental policies, eco-friendly innovations, and strong institutions. The outcomes indicate that environmental technology, envi-ronmental taxation, and institution quality decrease E7's carbon emissions by 0.170%, 0.080%, and 0.016%, respectively. It is recommended that E7 policymakers should adopt the STIRPART postulate as the theoretical basis for policies favoring environmental sustainability. The key contribution is the amendment of the STIRPAT model and the enhancement of the market-based mechanisms, such as patents, strong institutions, and carbon taxes, to enable environmental policy to be carried out sustainably and cost-effectively.eninfo:eu-repo/semantics/closedAccessTransition towards renewablesEnvironmental technologiesEnvironmental taxEnvironmental regulationsSTIRPATGreen industrial transition: Leveraging environmental innovation and environmental tax to achieve carbon neutrality. Expanding on STRIPAT modelArticle34310.1016/j.jenvman.2023.118121372246842-s2.0-85160209324WOS:001007288000001Q1