Subnational governments (cities, states, provinces) play a crucial role in global climate change mitigation. The IPCC acknowledges their potential contributions, recognizing their jurisdiction over key emissions sources like energy, waste management, and land use. Many subnational actors have pledged to address climate change, aiming to bridge the gap between national policies and global 1.5°C warming goals. However, few studies have systematically evaluated the impact of these subnational mitigation actions. Aggregating analyses across diverse spatial levels, circumstances, and capacities is challenging. Previous research often focuses on the quantity and ambition of targets rather than implementation and impacts. While numerous case studies exist, a systematic review and analysis of these studies are needed to understand the relative effectiveness of various approaches. This study uses meta-analysis to combine and analyze data from multiple quantitative subnational mitigation case studies to estimate expected emissions reductions from a range of mitigation strategies and evaluate the actions taken by cities and regions. This is the first study, to the authors' knowledge, to focus on subnational mitigation strategies across multiple jurisdictional scales, providing critical information for decision-makers to develop and evaluate effective mitigation plans and improve coordination between governmental levels.

Existing literature on subnational climate action often relies on climate action plans or voluntary reporting platforms, primarily assessing the ambition of targets rather than the actual impact of implemented strategies. While numerous case studies evaluate mitigation strategies in specific contexts, a systematic synthesis of their quantitative findings has been lacking. A few studies have employed meta-analytical methods to assess mitigation strategies, but these either focus on specific sectors or contexts, or examine qualitative characteristics of policies rather than quantitative emission reductions. Only one previous study compared quantitative emission reductions across various sectors and strategies within urban contexts. This study addresses this gap by systematically reviewing and synthesizing findings from quantitative case studies to provide a comprehensive assessment of subnational mitigation effectiveness.

The study began with a comprehensive literature search in Scopus and Web of Science, yielding nearly 300,000 initial results. After removing duplicates and applying rules-based and manual screening based on pre-defined eligibility criteria (quantitative GHG emission impact, mitigation strategy focus, subnational government context, and original research), 234 subnational climate change mitigation case studies were selected. From these studies, 1413 emissions reduction impacts and various metadata were extracted. A "synthesis dataset" (137 comparable studies, 779 impacts) was created by standardizing the reported impacts to annualized, per-capita metric tons of CO2 equivalent (tCO2e capita⁻¹ year⁻¹). A separate "actions dataset" (49 studies, 134 actions) was created to analyze subnational government actions and policies. Clustered, non-parametric bootstrapping was used to estimate the average emissions reduction impact and confidence intervals for 12 categories of mitigation strategies, accounting for dependence at the study level. The study also analyzed the types of policy instruments used by subnational governments and their geographic distribution. Additional analyses investigated the alignment between the prevalence of strategies in the literature and their effectiveness and uncertainty in achieving emissions reductions.

The study found that strategies related to land use and development, circular economy, and waste management were the most effective and reliable for reducing greenhouse gas emissions. The analysis revealed significant variation in the effectiveness and certainty of emissions reductions across different mitigation strategy categories. * **Land use and development:** This cross-sectoral category showed the highest expected emissions reductions (0.80 ± 0.30 tCO2e capita⁻¹ year⁻¹), primarily driven by afforestation and greening. * **Circular economy:** This cross-sectoral category, encompassing industrial symbiosis and recycled materials, also ranked highly (0.30 ± 0.10 tCO2e capita⁻¹ year⁻¹). * **Waste and water treatment practices:** This sector-specific category ranked third, characterized by low uncertainty. * **Electricity and heat:** Among sector-specific categories, this showed high mitigation potential (0.44 ± 0.18 tCO2e capita⁻¹ year⁻¹ for clean energy generation and 0.37 ± 0.14 tCO2e capita⁻¹ year⁻¹ for energy system operations), but also high uncertainty. * **Transportation and building sector strategies:** These generally showed smaller expected emission reductions, with exceptions like transportation system management (0.17 ± 0.06 tCO2e capita⁻¹ year⁻¹), but with limited studies. * **Market-based mechanisms:** While showing high expected reductions (0.71 ± 0.37 tCO2e capita⁻¹ year⁻¹), this category also exhibited high uncertainty, and was only evaluated in four countries. The study also found a misalignment between the strategies frequently implemented by subnational governments (as observed in the case study literature) and the strategies with the greatest mitigation potential. Cities and regions are taking action to reduce emissions but are not prioritizing strategies with the largest expected impacts or lowest uncertainty. Transportation strategies were most frequently used by governments, particularly in Europe and North America, while cross-sectoral strategies were more common in Asia. Cities predominantly used direct investment and policy support, whereas regions utilized more economic and regulatory instruments.

The study's findings highlight the crucial need for a more evidence-based approach to subnational climate mitigation strategies. The ranking of mitigation strategies based on absolute emissions reductions and uncertainty differs from previous studies, potentially due to the inclusion of multiple jurisdictional scales (cities and regions), focusing on subnational-wide strategies, and using absolute rather than relative emissions reductions. The misalignment between the most frequently studied and implemented strategies and those with the highest impact suggests that other factors, such as co-benefits, political viability, resource constraints, or implementation complexity, influence policy choices. Subnational governments may prioritize strategies that achieve co-benefits with other policy goals (e.g., public health, sanitation), even if they have lower emissions reduction potential. The study also reveals differences in the sectoral distribution of strategies between cities and regions, reflecting variations in jurisdictional responsibilities.

This study provides a comparative assessment of subnational climate mitigation strategies, emphasizing the need for evidence-based decision-making. Land use and development, circular economy, and waste management strategies emerge as the most effective. Policymakers should prioritize strategies based not only on their potential for emissions reductions but also on their certainty and potential co-benefits. Future research should investigate the influence of factors beyond emissions reductions on strategy selection, including costs, strategy interactions, and political and institutional contexts. Further ex-post evaluations of climate mitigation policies are also essential.

The study acknowledges several limitations. Many included studies did not report error metrics, and variations in methodologies and baseline scenarios introduce uncertainty. The analysis focused on subnational-wide strategies and standardized impacts by population; however, both cities and regions are heterogeneous. The study did not consider the costs of implementation or interactions between strategies. Sample size limitations prevented further breakdown of analysis by actor type or geographic region. The analysis treats mitigation strategies autonomously, without fully accounting for potential synergies or trade-offs between them.