Effective climate policies for major emission reductions of ozone precursors: Global evidence from two decades

• URL: http://arxiv.org/abs/2505.14731v1
• Date: Tue, 20 May 2025 02:20:36 GMT
• Title: Effective climate policies for major emission reductions of ozone precursors: Global evidence from two decades
• Authors: Ningning Yao, Huan Xi, Lang Chen, Zhe Song, Jian Li, Yulei Chen, Baocai Guo, Yuanhang Zhang, Tong Zhu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, Shaocai Yu,
• Abstract summary: We use structural break detection and machine learning to pinpoint effective interventions across the building, electricity, industrial, and transport sectors.<n>We detect 78, 77, and 78 structural breaks for NOtextsubscriptx, 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.
• Score: 13.609484778909335
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

Related papers

• CarboNeXT and CarboFormer: Dual Semantic Segmentation Architectures for Detecting and Quantifying Carbon Dioxide Emissions Using Optical Gas Imaging [0.0]
  Carbon dioxide (CO$$) emissions are critical indicators of both environmental impact and various industrial processes, including livestock management.<n>We introduce CarboNeXT, a semantic segmentation framework for Optical Gas Imaging (OGI), designed to detect and quantify CO$$ emissions across diverse applications.
  arXiv  Detail & Related papers  (2025-05-23T18:01:42Z)
• Machine Learning Techniques for Multifactor Analysis of National Carbon Dioxide Emissions [0.46873264197900916]
  The study aims to understand the factors contributing to carbon dioxide emissions and identify the most predictive elements.<n>The analysis provides country-specific emission estimates, highlighting diverse national trajectories.<n>The study aims to support policymaking with accurate representations of carbon dioxide emissions.
  arXiv  Detail & Related papers  (2025-03-19T11:36:08Z)
• Dynamic Incentive Allocation for City-scale Deep Decarbonization [4.146808838321321]
  Governments and utilities have designed incentives to stimulate the adoption of decarbonization technologies such as rooftop PV and heat pumps.<n>We present a novel data-driven approach that adopts a holistic, emissions-based and city-scale perspective on decarbonization.<n>We show that our framework can accommodate equity-aware constraints to equitably allocate incentives across socioeconomic groups, achieving 78.84% of the carbon reductions of the optimal solution.
  arXiv  Detail & Related papers  (2025-02-13T01:25:49Z)
• Carbon Market Simulation with Adaptive Mechanism Design [55.25103894620696]
  A carbon market is a market-based tool that incentivizes economic agents to align individual profits with the global utility. We propose an adaptive mechanism design framework, simulating the market using hierarchical, model-free multi-agent reinforcement learning (MARL) Numerical results show MARL enables government agents to balance productivity, equality, and carbon emissions.
  arXiv  Detail & Related papers  (2024-06-12T05:08:51Z)
• Generative AI for Low-Carbon Artificial Intelligence of Things with Large Language Models [67.0243099823109]
  Generative AI (GAI) holds immense potential to reduce carbon emissions of Artificial Intelligence of Things (AIoT) In this article, we explore the potential of GAI for carbon emissions reduction and propose a novel GAI-enabled solution for low-carbon AIoT. We propose a Large Language Model (LLM)-enabled carbon emission optimization framework, in which we design pluggable LLM and Retrieval Augmented Generation (RAG) modules.
  arXiv  Detail & Related papers  (2024-04-28T05:46:28Z)
• Global, robust and comparable digital carbon assets [0.28106259549258145]
  We propose a new digital carbon asset (the PACT stablecoin) against which carbon offsetting claims can be transparently verified. We implement and evaluate the PACT carbon stablecoin on the Tezos blockchain, which is designed to facilitate low-cost transactions. Our work brings scale and trust to the voluntary carbon market by providing a transparent, scalable, and efficient framework for high integrity carbon credit transactions.
  arXiv  Detail & Related papers  (2024-03-21T17:35:07Z)
• Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system [4.721325160754968]
  The adoption of CDRT is not economically viable at the current carbon price. The proposed DRL agent can meet the prosumers' multi-energy demand and schedule the CDRT energy demand economically. The configuration with PCCS and solid-sorbent DACS is considered the most suitable.
  arXiv  Detail & Related papers  (2023-01-18T20:22:44Z)
• (Private)-Retroactive Carbon Pricing [(P)ReCaP]: A Market-based Approach for Climate Finance and Risk Assessment [64.83786252406105]
  Retrospective Social Cost of Carbon Updating (ReSCCU) is a novel mechanism that corrects for limitations as empirically measured evidence is collected. To implement ReSCCU in the context of carbon taxation, we propose Retroactive Carbon Pricing (ReCaP) To alleviate systematic risks and minimize government involvement, we introduce the Private ReCaP (PReCaP) prediction market.
  arXiv  Detail & Related papers  (2022-05-02T06:02:13Z)
• Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation [122.83280749890078]
  We propose an improved certified defense against general poisoning attacks, namely Finite Aggregation. In contrast to DPA, which directly splits the training set into disjoint subsets, our method first splits the training set into smaller disjoint subsets. We offer an alternative view of our method, bridging the designs of deterministic and aggregation-based certified defenses.
  arXiv  Detail & Related papers  (2022-02-05T20:08:58Z)
• Modelling the transition to a low-carbon energy supply [91.3755431537592]
  A transition to a low-carbon electricity supply is crucial to limit the impacts of climate change. Reducing carbon emissions could help prevent the world from reaching a tipping point, where runaway emissions are likely. Runaway emissions could lead to extremes in weather conditions around the world.
  arXiv  Detail & Related papers  (2021-09-25T12:37:05Z)
• Optimizing carbon tax for decentralized electricity markets using an agent-based model [69.3939291118954]
  Averting the effects of anthropogenic climate change requires a transition from fossil fuels to low-carbon technology. Carbon taxes have been shown to be an efficient way to aid in this transition. We use the NSGA-II genetic algorithm to minimize average electricity price and relative carbon intensity of the electricity mix.
  arXiv  Detail & Related papers  (2020-05-28T06:54:43Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.