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<p>Industrialized countries such as Germany continue to struggle to meet their greenhouse gas (GHG) reduction targets, underscoring the need for a clear understanding of the structural forces shaping emission trends. This study applies Structural Decomposition Analysis (SDA) to examine the drivers and inhibitors of Germany’s GHG emissions from 1996 to 2022, using the newly developed Python tool TOAD (Trade-Oriented Analysis through Decomposition). TOAD applies the Dietzenbacher and Los (Economic Systems Research, 10:307–324, 1998) method across four accounting schemes: territorial-based, consumption-based, production-based, and a trade-balance-adjusted perspective. Across perspectives, improvements in production efficiency and cleaner technologies emerge as the dominant source of emission reductions (−&#xa0;617 Mt CO<sub>2</sub>-eq), while growth in the scale of final demand remains the main driver of increases (+ 309 Mt CO<sub>2</sub>-eq). Under a trade-balance-adjusted perspective, however, net reductions amount to only—38 Mt CO<sub>2</sub> -eq, as rising emissions embodied in imports substantially offset domestic efficiency gains. These findings demonstrate that Germany’s apparent mitigation progress critically depends on accounting for trade-related outsourcing. A sectoral breakdown further reveals pronounced heterogeneity in the underlying emission drivers: energy-intensive industries are shaped by structural and activity-related rebound effects, whereas electricity and service sectors benefit most from intensity-driven improvements. These sector-specific dynamics remain hidden in aggregate SDA results. Overall, the study shows that Germany’s mitigation performance can only be fully understood when decomposed across multiple allocation principles and sectoral contexts. By enabling transparent and reproducible multi-perspective decomposition analyses, TOAD highlights the growing influence of consumption-driven demand, trade integration, and sector-specific rebound risks - insights that can inform more targeted climate and industrial policy.</p>

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Structural drivers and outsourcing effects in Germany’s greenhouse gas emissions: a multi-perspective, sectoral decomposition (1996−2022)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月18日

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  • Philipp Daun,
  • Jonathan Kummer,
  • Aaron Praktiknjo

摘要

Industrialized countries such as Germany continue to struggle to meet their greenhouse gas (GHG) reduction targets, underscoring the need for a clear understanding of the structural forces shaping emission trends. This study applies Structural Decomposition Analysis (SDA) to examine the drivers and inhibitors of Germany’s GHG emissions from 1996 to 2022, using the newly developed Python tool TOAD (Trade-Oriented Analysis through Decomposition). TOAD applies the Dietzenbacher and Los (Economic Systems Research, 10:307–324, 1998) method across four accounting schemes: territorial-based, consumption-based, production-based, and a trade-balance-adjusted perspective. Across perspectives, improvements in production efficiency and cleaner technologies emerge as the dominant source of emission reductions (− 617 Mt CO2-eq), while growth in the scale of final demand remains the main driver of increases (+ 309 Mt CO2-eq). Under a trade-balance-adjusted perspective, however, net reductions amount to only—38 Mt CO2 -eq, as rising emissions embodied in imports substantially offset domestic efficiency gains. These findings demonstrate that Germany’s apparent mitigation progress critically depends on accounting for trade-related outsourcing. A sectoral breakdown further reveals pronounced heterogeneity in the underlying emission drivers: energy-intensive industries are shaped by structural and activity-related rebound effects, whereas electricity and service sectors benefit most from intensity-driven improvements. These sector-specific dynamics remain hidden in aggregate SDA results. Overall, the study shows that Germany’s mitigation performance can only be fully understood when decomposed across multiple allocation principles and sectoral contexts. By enabling transparent and reproducible multi-perspective decomposition analyses, TOAD highlights the growing influence of consumption-driven demand, trade integration, and sector-specific rebound risks - insights that can inform more targeted climate and industrial policy.