The Russia-Ukraine conflict led to widespread international trade sanctions targeting Russia's energy-related products. These sanctions, imposed by a coalition of countries including the EU, UK, US, Canada, Australia, and Japan, aimed to hinder Russia's economic development and leverage its significant role as a global energy exporter. Given the interconnected nature of global energy markets and the embodiment of socio-economic and environmental impacts within trade flows, the imposition of these sanctions presents significant risks to the global energy system, environment, and human health, potentially hindering global sustainable development. The research question addresses how these sanctions affect various regions economically and environmentally. The study aims to provide a comprehensive analysis of the resulting environmental, economic, and public health implications, going beyond previous research that largely focused on unilateral sanctions and their effects on specific regions or sectors.

Existing studies on the Russia-Ukraine conflict's economic and environmental effects have primarily examined unilateral sanctions on Russia's fossil energy. These studies used various models, including multi-sector-open economy models and general equilibrium approaches, to investigate the macroeconomic effects of reduced energy imports from Russia and the impact of trade disruptions between Russia and the EU. The findings from these studies indicated negative economic effects on both Russia and sanction-imposing countries, with varying degrees of GDP decline depending on the intensity of the sanctions. However, there's been a gap in understanding the broader, global ramifications of multilateral sanctions on environmental and public health outcomes.

This study employs an integrated modeling framework combining the Global Trade Analysis Project (GTAP) model and the Transport Model 5-Fast Atmospheric Source-Receptor model (TMS-FASST). The GTAP model is a multi-sector, multi-region, global general equilibrium model used to analyze the macroeconomic and sectoral impacts of the trade sanctions, incorporating production, consumption, and international trade modules. The model accounts for different factors of production and uses constant elasticity of substitution (CES) functions to represent production and consumption behaviors. The TMS-FASST model is a reduced-form atmospheric source-receptor model used to assess the impacts of air pollutant emissions from source regions on receptor regions, particularly focusing on PM2.5 concentrations and associated premature mortality. This model tracks country and regional emissions, considering the decay of pollutants, and estimates ambient PM2.5 concentrations for different trade sanction scenarios. The study used GTAP version 10 data, aggregating it to cover 23 regions and 22 economic sectors. Four trade sanction scenarios (TS0-TS4) were developed, ranging from a baseline (TS0) to increasingly stringent measures. These scenarios incorporated different levels of import tariffs on energy-related products from Russia imposed by various countries and the increased imports from alternative suppliers. Furthermore, the study considered two additional scenarios: the emission intensity reduction scenario (EIRS) and the import tariff reduction (ITR). The EIRS considers technological and financial support for the EU to reduce its reliance on fossil fuel imports, while the ITR simulates the EU's increased imports from alternative suppliers by reducing trade barriers. A mixed-level factorial analysis examined the interactive effects of these factors on global GDP and CO2 emissions. Index decomposition analysis (IDA) was used to quantify the contribution of different factors (activity, structural, and technical effects) to changes in CO2 and air pollutant emissions. Finally, Lorenz curves and Gini coefficients were employed to measure the distribution of environmental and public health outcomes across regions under different scenarios.

The study's key findings reveal a complex interplay between economic and environmental consequences of the sanctions. Globally, GDP loss was projected between 0.15-0.26%, while CO2 emissions declined by 0.03-0.07% under different sanction scenarios. However, the distribution of these impacts was highly uneven. Approximately one-fifth of global regions (including Russia, China, and Central America) experienced a ‘co-harm’ situation, characterized by decreased GDP and increased emissions and health risks. Intensifying sanctions reallocated energy production and export to less-developed regions, exacerbating inequalities. Specific regional impacts were analyzed: Russia experienced a significant GDP loss (6.9-10.8%) and increased CO2 emissions (due to increased domestic production). The EU experienced a GDP fall (0.69-0.90%) and CO2 emission reductions (1.1-1.3%). Other regions showed varied impacts, with some experiencing increased exports and CO2 emissions (e.g., Rest of ECA, CAC) and others experiencing decreased exports and CO2 emissions (e.g., MENA, Mexico). Sectoral analysis showed that while some sectors (e.g., Transport, Petroleum, Electricity) experienced significant CO2 emission reductions due to trade restrictions, others (e.g., Natural Gas, Chemical) experienced increases. Air pollutant emissions followed similar patterns of uneven distribution. The EU saw reductions, while Russia experienced increases. The study calculated health risks, mainly related to PM2.5 exposure, showing significant impacts in Russia and its neighboring regions. The analysis used Lorenz curves and Gini coefficients to demonstrate the unequal distribution of environmental and health outcomes, highlighting the significant increase in inequality under the sanctions. A mixed-level factorial analysis further showed that the interactions between various trade sanction measures and mitigation strategies significantly impacted the overall outcomes.

The findings demonstrate that the international trade sanctions, while aiming to curb Russia's economy, have created complex and unevenly distributed environmental and public health consequences. The observed ‘co-harm’ situations in several regions highlight the limitations of solely focusing on the direct impact on the targeted country. The significant increase in inequality in the distribution of environmental and health burdens underscores the need for more targeted policies and international collaborations. The study's results support the need for post-sanction adaptation strategies, including targeted support for vulnerable regions, promotion of clean energy technologies, and adjustment of environmental tariffs to mitigate the unintended negative consequences. The abrupt shift in comparative advantage induced by sanctions necessitates multilateral cooperation to address transboundary environmental and health impacts.

This study provides a comprehensive analysis of the cascading environmental, economic, and public health implications of the international trade sanctions imposed on Russia. The uneven distribution of impacts and the ‘co-harm’ scenarios identified call for a more nuanced approach to sanctioning that accounts for the potential unintended consequences. Future research should explore more sophisticated models to capture the long-term dynamics and regional specificities of this multifaceted problem, further refining mitigation strategies and providing more targeted support to vulnerable regions. Emphasis should be placed on international cooperation to address the global inequalities exacerbated by the sanctions.

While the study uses sophisticated modeling techniques, certain limitations exist. The model relies on assumptions about economic behavior and technological changes, which may not perfectly reflect real-world complexities. Data availability and accuracy could also impact the precision of the results. The study focuses primarily on the short- to medium-term effects of the sanctions and may not fully capture long-term impacts. Furthermore, the model may not fully capture the complex geopolitical and social factors influencing the sanctions' effects.