Effective climate policies for major emission reductions of ozone precursors: Global evidence from two decades
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| Format: | Preprint |
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2025
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| _version_ | 1866908372751613952 |
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| author | Yao, Ningning Xi, Huan Chen, Lang Song, Zhe Li, Jian Chen, Yulei Guo, Baocai Zhang, Yuanhang Zhu, Tong Li, Pengfei Rosenfeld, Daniel Seinfeld, John H. Yu, Shaocai |
| author_facet | Yao, Ningning Xi, Huan Chen, Lang Song, Zhe Li, Jian Chen, Yulei Guo, Baocai Zhang, Yuanhang Zhu, Tong Li, Pengfei Rosenfeld, Daniel Seinfeld, John H. Yu, Shaocai |
| contents | Despite policymakers deploying various tools to mitigate emissions of ozone (O\textsubscript{3}) precursors, such as nitrogen oxides (NO\textsubscript{x}), carbon monoxide (CO), and volatile organic compounds (VOCs), the effectiveness of policy combinations remains uncertain. We employ an integrated framework that couples structural break detection with machine learning to pinpoint effective interventions across the building, electricity, industrial, and transport sectors, identifying treatment effects as abrupt changes without prior assumptions about policy treatment assignment and timing. Applied to two decades of global O\textsubscript{3} precursor emissions data, we detect 78, 77, and 78 structural breaks for NO\textsubscript{x}, CO, and VOCs, corresponding to cumulative emission reductions of 0.96-0.97 Gt, 2.84-2.88 Gt, and 0.47-0.48 Gt, respectively. Sector-level analysis shows that electricity sector structural policies cut NO\textsubscript{x} by up to 32.4\%, while in buildings, developed countries combined adoption subsidies with carbon taxes to achieve 42.7\% CO reductions and developing countries used financing plus fuel taxes to secure 52.3\%. VOCs abatement peaked at 38.5\% when fossil-fuel subsidy reforms were paired with financial incentives. Finally, hybrid strategies merging non-price measures (subsidies, bans, mandates) with pricing instruments delivered up to an additional 10\% co-benefit. These findings guide the sequencing and complementarity of context-specific policy portfolios for O\textsubscript{3} precursor mitigation. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_14731 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Effective climate policies for major emission reductions of ozone precursors: Global evidence from two decades Yao, Ningning Xi, Huan Chen, Lang Song, Zhe Li, Jian Chen, Yulei Guo, Baocai Zhang, Yuanhang Zhu, Tong Li, Pengfei Rosenfeld, Daniel Seinfeld, John H. Yu, Shaocai Applications Machine Learning Despite policymakers deploying various tools to mitigate emissions of ozone (O\textsubscript{3}) precursors, such as nitrogen oxides (NO\textsubscript{x}), carbon monoxide (CO), and volatile organic compounds (VOCs), the effectiveness of policy combinations remains uncertain. We employ an integrated framework that couples structural break detection with machine learning to pinpoint effective interventions across the building, electricity, industrial, and transport sectors, identifying treatment effects as abrupt changes without prior assumptions about policy treatment assignment and timing. Applied to two decades of global O\textsubscript{3} precursor emissions data, we detect 78, 77, and 78 structural breaks for NO\textsubscript{x}, CO, and VOCs, corresponding to cumulative emission reductions of 0.96-0.97 Gt, 2.84-2.88 Gt, and 0.47-0.48 Gt, respectively. Sector-level analysis shows that electricity sector structural policies cut NO\textsubscript{x} by up to 32.4\%, while in buildings, developed countries combined adoption subsidies with carbon taxes to achieve 42.7\% CO reductions and developing countries used financing plus fuel taxes to secure 52.3\%. VOCs abatement peaked at 38.5\% when fossil-fuel subsidy reforms were paired with financial incentives. Finally, hybrid strategies merging non-price measures (subsidies, bans, mandates) with pricing instruments delivered up to an additional 10\% co-benefit. These findings guide the sequencing and complementarity of context-specific policy portfolios for O\textsubscript{3} precursor mitigation. |
| title | Effective climate policies for major emission reductions of ozone precursors: Global evidence from two decades |
| topic | Applications Machine Learning |
| url | https://arxiv.org/abs/2505.14731 |