Sustainable urbanisation is key to building resilient cities and communities that balance development with environmental conservation. As populations rise and cities expand, the need for sustainability becomes even more pressing. This study evaluates two prominent modelling approaches, i.e., STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) and Environmental Modelling (EM), to understand their respective contributions to urban sustainability research. Using a bibliometric and meta-analysis approach, the study analyses 331 EM and 184 STIRPAT publications from 2000 to 2024. The findings reveal distinct yet complementary emphases: STIRPAT highlights the linkages among population growth, affluence, and technology, while EM offers a more comprehensive perspective on ecosystems, resource use, and environmental dynamics. Although STIRPAT is valued for its empirical precision, it often omits broader ecological interactions. Conversely, EM captures macro-level environmental processes but overlooks finer socio-economic details. Additionally, this review also examines 20 studies that attempt to integrate both approaches, identifying only seven that explicitly discuss their potential convergence. These findings indicate that full methodological integration remains limited but conceptually promising. Overall, this study provides a two-decade assessment of STIRPAT and EM research trends, highlighting opportunities for interdisciplinary advancement and improved urban sustainability modelling. It concludes by proposing a conceptual pathway for integrating the empirical strengths of STIRPAT with the ecological inclusivity of EM to inform future policy development and research aligned with Sustainable Development Goal 11 (Sustainable Cities and Communities).
Dixit et al. (Fri,) studied this question.