International trade sanctions imposed due to the Russia-Ukraine war may cause unequal distribution of environmental and health impacts

The study investigates how international trade sanctions on Russia’s energy-related products, enacted in response to the Russia-Ukraine conflict, propagate through global trade and supply chains to affect economies, the environment, and public health across regions. Given Russia’s central role as a fossil energy exporter and the multilateral sanctioning coalition (EU, UK, US, Canada, Australia, Japan, etc.), the sanctions are expected to disrupt energy markets, shift production structures, alter CO2 and air pollutant emissions, and redistribute health risks. The research aims to quantify these macroeconomic, environmental, and health implications under varying sanction intensities and scopes, and to assess potential inequalities in burden distribution and co-harm/co-benefit outcomes across regions.

Prior work assessed unilateral or regional sanctions’ impacts on Russian fossil energy, including estimates that suspending German energy imports could reduce German GDP by 0.5–3% and that high trade suffocation between Russia and the EU harms both economies. General equilibrium analyses suggested EU demand-side responses can curb economic losses and GHG emissions. Broader literature on trade-related policies (e.g., US–China trade war) documents spillovers on emissions and welfare and the relocation of pollution through trade. However, comprehensive assessments linking global equilibrium trade shifts to environmental and health outcomes under multilateral, energy-focused sanctions remained limited, motivating this integrated analysis.

An integrated framework couples: (1) a global computable general equilibrium model (GTAP) to simulate trade, production, and consumption shifts under sanction scenarios; (2) the TM5-FASST reduced-form atmospheric source–receptor model (TMS-FASST) to map changes in precursor emissions to ambient PM2.5 concentrations and premature mortality; (3) index decomposition analysis (LMDI) to separate activity, structural, and technical effects on changes in CO2 and air pollutants; and (4) Lorenz curves and Gini coefficients to evaluate inequality in environmental and public-health outcomes, supplemented by a regression-based inequality decomposition to attribute disparities to socio-economic factors (GDP per capita, energy-sector value-added share, trade openness, exports). GTAP implementation: Based on GTAP v10 (reference year 2014), covering 141 regions and 65 sectors, aggregated to 23 regions and 22 sectors for this study; primary factors aggregated to capital, land, and labor. Production follows nested CES and Leontief structures with Armington trade; consumption uses CDE (households) and Cobb–Douglas (government). Scenario design: A baseline TS0 reflects prevailing GTAP tariffs/trade settings. Sanction scenarios incrementally impose restrictions and tariffs on Russian energy-related products: TS1/TS2 represent initial sanctions by EU/UK/US (including 35% import tariffs on energy-intensive products in TS2); TS4 extends to major entities (Japan, Canada, Australia, EFTA) imposing 35% tariffs on both energy-related and energy-intensive products. Additional policy experiments include an EU emission-intensity reduction (EIR) scenario (accelerated clean energy deployment reducing sectoral emission intensities to global averages in the short run) and an import tariff reduction (ITR) scenario (EU reduces tariffs to shift supply chains toward alternative suppliers). Atmospheric modeling: TMS-FASST links country/region precursor emission changes (BC, CO, NH3, NOx, SOx, NMVOC) to receptor-region PM2.5 changes using source–receptor coefficients, with emissions based on EDGAR and GTAP outputs. Health impacts are quantified as changes in PM2.5 exposure and PM2.5-related premature mortality. Decomposition and inequality: LMDI separates activity (total output), structural (sectoral output shares), and technical (emission intensity) effects. Lorenz/Gini quantify distributional changes in CO2 and pollutant emissions across countries/regions; regression-based decomposition attributes inequality to socio-economic drivers. Mixed-level factorial analysis evaluates main and interaction effects among TS2, TS4, EIR, and ITR on global GDP and CO2 emissions.

Global outcomes: • Under sanction scenarios, global GDP decreases by 0.15–0.26% while global CO2 emissions decline by 0.03–0.07% relative to no sanctions. • Sectoral CO2 changes (global): large reductions in Electricity (12,221–26,485 kt) and Petroleum (13,495–19,036 kt); Transport declines by 925–12,933 kt. Increases occur in Natural Gas (2,258–4,264 kt) and Chemicals (2,537–6,617 kt), largely offset by reductions elsewhere. • Global air pollutant emissions fall by 0.03–0.05%: CO (−141 to −197 kt), SO2 (−35 to −81 kt), NOx (−21 to −66 kt), PM2.5 (−29 to −31 kt), NMVOCs (−10.3 to −13 kt), OC (−8 to −22 kt), PM2.5–5 (−8 kt), BC (−11 to −18 kt), NH3 (−10 to −12 kt). Regional outcomes and trade shifts: • Russia: GDP falls by roughly 6.9–10.8% across scenarios; exports shift toward MENA, China, Rest of Europe and Central Asia (ECA), and East Asia. Domestic price effects increase diesel consumption; Russia’s CO2 emissions rise by 1.3–1.79% (22,520–30,384 kt), driven mainly by structural (sectoral output) changes. Sectorally, CO2 increases in Chemicals (+6,674–12,390 kt), Electricity (+8,202–19,906 kt), Transport (+5,161–7,290 kt), and Natural Gas (+499–991 kt); decreases in Petroleum (−2,509–−4,270 kt), Coal (−517–−819 kt), and Oil (−157–−281 kt). • European Union: Imports reorient toward MENA, SSA, Rest of ECA, and the US. Household consumption falls for fossil energy (−7.8% to −9.5%) and energy-intensive goods (−0.6% to −0.9%). EU GDP declines by 0.69–0.90%; EU CO2 emissions decline by 1.1–1.3%, with structural reductions of 36,797–42,947 kt and activity reductions of 2,884–3,206 kt. Sectorally, EU CO2 increases in Natural Gas (+1,215–1,664 kt) and Coal (+165–994 kt) due to boosted domestic production; declines in Petroleum (−12,962–−13,981 kt), Electricity (−6,135–−8,231 kt), Chemicals (−1,293–−1,856 kt), and Transport (−2,016–−2,492 kt). • Spillovers: Regions such as Rest of ECA and Central America/Caribbean (CAC) generally see increased exports (+0.03% to +2.36%) and CO2 (+0.09% to +0.91%), driven by structural effects. Several regions (Canada, Rest of South America, Oceania, MENA, Mexico/Rest of North America) show decreased exports (−0.04% to −0.74%) and CO2 (−0.01% to −0.61%). • Country/sector highlights: Canada’s Transport sector dominates reductions (−209 to −391 kt), while Petroleum and Natural Gas increase; in the UK and US, CO2 changes concentrate in manufacturing, with declines in Electricity and Transport; Japan’s sectoral impacts vary by scenario, with TS4 reducing Electricity (−501 kt) and Petroleum (−2,219 kt) but increasing Natural Gas (+426 kt) and Transport (+29 kt). Air pollution and health: • EU air pollutant emissions decline by roughly 545–503 kt under sanctions; Russia’s air pollutant emissions increase by ~232–431 kt under TS1–TS3 but decrease by ~25 kt under TS4, generally mirroring CO2 trends. Developed regions (US, UK, Canada, Oceania) see small declines. • Sanctioning regions show improvements in public-health indicators: indices for PM2.5 exposure and PM2.5-related premature mortality are positive (≈0.17–0.20 and 0.52–0.62, respectively), indicating net public-health benefits. Regions adjacent to or trading with Russia (Central Asia, East Asia, Southeast Asia) bear increased risks or smaller benefits relative to sanctioning regions. Inequality: • Gini coefficients under TS4 indicate unequal distributions: CO2 emissions Gini ≈ 0.3238; air pollutant emissions Gini ≈ 0.5062, highlighting more unequal distribution of air-pollution-related burdens than carbon across regions. • One-fifth of regions (e.g., Russia, China, CAC, UK) face co-harm (GDP declines alongside emissions increases), while about half experience co-benefits (economic and environmental improvements).

Findings show that multilateral sanctions on Russia’s energy-related products propagate through global supply chains, yielding heterogeneous macroeconomic, environmental, and health effects. Restrictions reduce global economic welfare slightly but also lead to modest global CO2 and pollutant declines, with strong sectoral reallocation. Sanctioning regions such as the EU tend to secure environmental co-benefits (notably via structural output shifts), whereas Russia experiences economic losses and higher emissions due to domestic substitution and rerouted exports. Trade reorientation reallocates energy production toward alternative suppliers, many in developing regions with higher emission intensities and looser environmental regulations, exacerbating the inequality of air-pollution burdens and related health risks (higher Gini for pollutants than for CO2). The analysis highlights policy-relevant trade-offs: while sanctions may improve air quality and health in sanctioning regions, they can worsen burdens in exporter regions like Rest of ECA and in parts of Asia. Addressing these transboundary consequences requires coordinated post-sanction adaptation, technology transfer to lower emission intensities in affected supplier regions, and sector-specific cooperation to mitigate unintended distributional harms.

This study integrates a global equilibrium trade model with an atmospheric source–receptor and decomposition/inequality analyses to quantify how Russia-related energy sanctions reshape trade, production, emissions, and health outcomes worldwide. Sanctions induce modest global CO2 and pollutant reductions but cause uneven burden shifting: sanctioning regions generally gain environmental benefits while some exporting or neighboring regions incur higher emissions and health risks, and certain regions (e.g., Russia, China, CAC, UK) face co-harm (GDP losses with emission increases). Policy implications include embedding post-sanction adaptation measures in multilateral agreements, facilitating low-carbon technology transfer and eco-innovation partnerships with impacted supplier regions, and coordinating sector-specific actions to reduce emission intensities in reoriented supply chains. Future research could refine dynamic sanction scenarios amid evolving geopolitics, incorporate more granular sectoral technologies and realistic technical change, update databases beyond 2014 with recent trade/energy shifts, and enhance health impact assessments with localized exposure–response heterogeneity.

Key limitations include scenario and policy uncertainty due to evolving geopolitics; reliance on GTAP v10 with a 2014 base year and aggregated sectors/regions; the assumption that, absent specific management interventions, technical effects are zero (placing emphasis on activity and structural changes); and the reduced-form, linear source–receptor relationships in TMS-FASST. These constraints may affect precision and generalizability of regional outcomes and health-impact estimates, especially where emission intensities or regulations differ rapidly over time.