Literature review: How to solve/limit Global Warming, By Thomas Yiu with Einsteinian AI

Literature Review

Key Findings on How to Solve or Limit Global Warming

Rapid and deep CO₂ reductions during this decade are decisive for limiting warming to 1.5–2 °C. The IPCC AR6 and related syntheses show that staying “well below 2 °C” and keeping 1.5 °C within reach requires global CO₂ emissions to decline by approximately 45% from 2010 levels by 2030 and reach net zero around mid-century, alongside substantial reductions in non-CO₂ greenhouse gases such as CH₄, N₂O, and F-gases. Liu et al. (2024) also show that wetlands are significant natural greenhouse gas sources, including CO₂, CH₄, and N₂O, while also functioning as major carbon sinks. This means climate mitigation must balance wetland protection for carbon storage with careful management of methane emissions from marshes and riverine systems [1].

Decarbonizing energy systems remains the central pillar of climate mitigation. Pachauri et al. (2024) emphasize that transitioning to clean electricity sources such as solar, wind, hydro, and nuclear power, electrifying end uses such as vehicles and heating, and improving efficiency across all sectors are among the most critical climate solutions. These measures are strengthened by demand-side changes, including reduced energy and material use, dietary shifts, and changes in transport behavior [12]. Watts et al. (2024) argue that achieving carbon neutrality before mid-century is feasible with existing technologies if governments prioritize rapid coal phase-out, massive renewable deployment, grid modernization, building and industry efficiency, transport electrification, methane abatement, and nature-based solutions. They also stress that these actions produce major co-benefits for health and equity [13].

Carbon dioxide removal is likely needed, but it cannot substitute for rapid emissions cuts. Scenario analyses in IPCC AR6 indicate that limiting warming to 1.5 °C with no or limited overshoot requires some level of CDR, estimated at approximately 0.1–1.3 GtCO₂ per year by 2030 and higher levels later in the century. This removal would come primarily from afforestation, reforestation, soil carbon enhancement, and, to a lesser extent, BECCS and DACCS. Eisenman et al. (2024) introduce the concept of “net-zero carbon debt,” which captures how much a country overshoots the remaining carbon budget even after reaching net zero. This metric clarifies that heavy emitters may bear future obligations to deploy carbon dioxide removal or achieve net-negative emissions to restore temperatures below threshold levels [11].

Nature-based solutions and land-use change are powerful but double-edged climate strategies. Protecting and restoring forests, wetlands, and peatlands can provide large and relatively low-cost mitigation potential while improving biodiversity and adaptation benefits. However, draining wetlands or converting forests for agriculture can release significant greenhouse gases. Liu et al. (2024) show that research on wetland greenhouse gas dynamics is rapidly growing, with reported average CO₂ fluxes of approximately 60 mg m⁻² h⁻¹ and higher global warming potential from marsh systems. This highlights the need for careful management to avoid unintended climate consequences [1].

Mitigation and adaptation must be pursued together. Recent studies, including Rahman et al. (2023) and Watts et al. (2024), treat mitigation and adaptation as co-dependent because failure to mitigate leads to rapidly escalating adaptation costs and residual damages, including heat-related health impacts, crop failures, and extreme weather losses [13]. Impact studies based on global warming levels rather than calendar years, such as Lange et al. (2024), show that hazard exposure increases nonlinearly between 2 °C and 3 °C. For example, compound drought-heatwave events in Northern Australia may double at 3 °C [4]. Higher global warming levels also drastically increase population exposure to heatwaves, floods, and droughts, emphasizing the importance of staying as close to 1.5 °C as possible [7].

Governance gaps and policy design are central to solving global warming. Hak et al. (2010) explain that the Copenhagen Accord failed to deliver a binding and fair international framework, pointing to institutional fragmentation, weak compliance mechanisms, and insufficient climate finance as major obstacles [14]. Eisenman et al. (2024) further show that weak cooperation and delayed mitigation create substantial intergenerational carbon debt, increasing the burden on future generations to deploy large-scale carbon dioxide removal and cope with overshoot impacts [11]. Related literature also shows that current nationally determined contributions remain incompatible with a 1.5 °C pathway, meaning implementation gaps are now as important as ambition gaps.

Hyperlocal data and polycentric governance can accelerate climate mitigation. Lauvaux et al. (2022) argue that hyperlocal greenhouse gas monitoring, including urban-scale sensor networks, satellites, and ground-based measurements, can support targeted mitigation by identifying major point sources, verifying emissions inventories, and enabling cities and non-state actors to act even when national policy is slow [15]. This aligns with evidence that sub-national actors, including cities, firms, and regions, can contribute meaningfully to closing the gap to Paris Agreement goals when supported by transparent monitoring and accountability systems.

Sector-specific research provides concrete mitigation pathways. In agriculture and livestock, studies show that dietary shifts, improved manure management, feed additives, and food-waste reduction can significantly reduce CH₄ and N₂O while protecting nutritional security. In transport, electric vehicle adoption, public transit, cycling, and low-carbon fuels are central strategies, with lifecycle analyses showing large net emission reductions when electricity decarbonizes rapidly. In industry and buildings, high efficiency, electrification, process innovation, green hydrogen, low-carbon cement, and carbon capture for high-heat industrial processes are critical. Policy tools such as standards, carbon pricing, and innovation support are also important for accelerating these transitions.

Methods Used in Research on Global Warming Solutions

Research on global warming solutions commonly uses systematic literature reviews and bibliometric analyses to synthesize knowledge, identify solution categories, and track research trends. Pachauri et al. (2024) perform a systematic review of proposed solutions to anthropogenic climate change using multiple databases, predefined inclusion criteria, and PRISMA-style screening to categorize technological, behavioral, and governance solutions while evaluating their evidence base [12]. Liu et al. (2024) apply CiteSpace and VOSviewer to 1,865 papers on wetland greenhouse gases, mapping authorship networks, keyword co-occurrence, and temporal research stages before combining this with meta-analysis of greenhouse gas flux observations [1]. Li et al. (2017) conduct a bibliometric analysis of global warming research using 1,672 articles from 2005 to 2014 in Web of Science and social network analysis to identify productive journals, collaboration networks, and keyword clusters [10].

Integrated assessment models and scenario analysis are also widely used. IAMs such as IMAGE, REMIND, MESSAGE, and GCAM link energy, land, economy, and climate systems to evaluate mitigation pathways consistent with temperature goals. IPCC AR6 and related papers use these models to derive Representative Concentration Pathways and Shared Socioeconomic Pathways, quantify required emissions trajectories for 1.5–2 °C, evaluate technology mixes such as renewables, nuclear, carbon capture, and carbon dioxide removal, and assess economic costs and distributional implications. Eisenman et al. (2024) add the net-zero carbon debt metric to such pathways in order to quantify overshoot responsibilities under different cooperation assumptions [11].

Global climate and hydrological model ensembles are frequently analyzed through global warming levels. Lange et al. (2024) build a database of 12 climate change indicators and 42 variants using CMIP6 and ISIMIP3b simulations at 0.5° resolution, expressed by global warming levels from 1.2 °C to 3.5 °C rather than by calendar time [7]. These indicators cover temperature and precipitation extremes, heatwaves, and hydrological variability. Their bivariate hazard score combines absolute hazard magnitude with relative change under warming, allowing researchers to estimate exposed land area and population under different SSP population scenarios.

High-resolution regional climate modeling and pseudo-global warming methods are also important for studying regional risks. The pseudo-global warming method runs a regional model, such as WRF, using historical boundary conditions plus a climate-change delta derived from global climate models. Wang et al. (2024) apply this method to Typhoon Mangkhut using sea surface temperature perturbations from 28 CMIP6 models across SSP1-2.6, SSP2-4.5, and SSP5-8.5, simulating changes in maximum wind speed and urban wind fields at high spatial resolution [6]. Krieger et al. (2024) examine hurricane intensity in the southeastern United States under different pseudo-global warming configurations, including thermodynamic, dynamic, and comprehensive perturbations, revealing important sensitivities and uncertainties for adaptation planning [8]. Gürbüz et al. (2023) use 4 km WRF simulations with pseudo-global warming over the Eastern Mediterranean–Black Sea region to study regional warming, drying, and precipitation changes relevant to water and flood management [9].

Impact modeling and hazard-exposure frameworks are used to quantify climate risks across populations, infrastructure, water resources, agriculture, and ecosystems. High-resolution impact models are forced with climate projections to estimate changes in water availability, crop production, coastal hazards, and infrastructure vulnerability. Lange et al. (2024) combine hazard scores with gridded population scenarios to compute population exposure to hazards by country and region, allowing prioritization of adaptation and mitigation [7]. Xing et al. (2024) analyze compound drought-heatwave events in Australia using downscaled CMIP6 simulations and indices such as the Standardized Precipitation Index, Standardized Precipitation-Evapotranspiration Index, and Excess Heat Factor. Their work helps identify the additional risks avoided through stronger mitigation [4].

Health-focused climate-energy assessments combine emissions scenarios with air pollution, epidemiology, health, and economic models to quantify the co-benefits of mitigation. Watts et al. (2024) integrate evidence from epidemiology, air quality modeling, and energy scenarios to show how rapid clean energy transitions reduce premature deaths from air pollution and heat exposure. This frames climate mitigation not only as an environmental necessity but also as a public health imperative [13].

Governance and policy analysis uses qualitative case studies and comparative policy analysis to examine why some policy mixes succeed while others fail. Hak et al. (2010) review the Copenhagen Accord and subsequent negotiations, analyzing actor coalitions, institutional barriers, and equity debates [14]. More recent literature uses polycentric governance and multi-level climate policy frameworks to assess the role of cities, regions, firms, and private actors in closing emissions gaps when international progress is slow.

Monitoring, reporting, and verification systems are increasingly important in climate research and policy. Lauvaux et al. (2022) describe emerging hyperlocal greenhouse gas monitoring systems that combine urban sensor networks, continuous atmospheric measurements, high-resolution inversion models, and satellite observations such as OCO-2 and TROPOMI [15]. These systems support verification of mitigation measures, identify high-impact local interventions, and improve transparency for public policy and corporate climate claims.

Contradictions, Gaps, and Open Questions

A major unresolved question is whether 1.5 °C remains achievable in practice. Watts et al. (2024) argue that 1.5 °C remains technically achievable with very rapid emissions reductions and clean energy scale-up [13]. However, IPCC and independent analyses indicate that current policies and nationally determined contributions place the world closer to approximately 2.4–2.7 °C by 2100. Near-term cumulative emissions may soon exhaust the remaining 1.5 °C carbon budget, shifting attention toward limiting overshoot and reducing associated risks. Eisenman et al. (2024) explicitly show how overshoot and net-zero carbon debt become increasingly likely under weak cooperation [11]. There remains disagreement over how much short-term overshoot is acceptable, especially because risks such as tipping points remain poorly understood.

The scale, timing, and equity of carbon dioxide removal deployment remain deeply contested. Integrated assessment models often rely on large-scale BECCS and afforestation in later decades to offset residual emissions, but this raises concerns about land competition, biodiversity loss, and food security. The net-zero carbon debt framework proposed by Eisenman et al. (2024) raises unresolved questions about which countries should finance and host carbon dioxide removal projects and how the world can avoid over-reliance on future carbon removal that may not materialize at the required scale [11]. Governance of emerging CDR approaches, including direct air capture and ocean alkalinization, remains underdeveloped, and their lifecycle climate impacts, costs, and social acceptability are still uncertain.

The role of natural systems remains complex because ecosystems can serve as both carbon sinks and future greenhouse gas sources. Wetlands and forests can store large amounts of carbon, but they may become net emitters if mismanaged or if climate impacts such as drought, fire, or hydrological change intensify. Liu et al. (2024) show that marsh wetlands can have particularly high global warming potential due to methane fluxes [1]. This creates open questions about how strongly wetland restoration should be prioritized given methane emissions and how warming, nutrient loading, and changing hydrology may alter the net greenhouse gas balance of wetlands. Similar debates apply to boreal forests and permafrost, which store massive amounts of carbon but may become net sources under warming and increased fire risk.

There is also ongoing debate about the optimal balance between technological solutions and demand-side or socio-behavioral change. IPCC AR6 WGIII highlights significant mitigation potential from demand-side measures such as dietary shifts and energy sufficiency, yet policy and investment continue to emphasize supply-side technology. Pachauri et al. (2024) note that behavioral and systemic demand-side changes have high technical potential but that empirical evidence remains limited on how to induce these changes at scale, especially in high-income societies [12]. Open questions include which policies, such as pricing, regulation, norms, and infrastructure changes, can drive durable lifestyle shifts and how such measures can be made equitable and politically acceptable.

Another major tension concerns governance architecture. On one hand, Hak et al. (2010) emphasize the need for a strong, coordinated international framework with enforceable targets [14]. On the other hand, evidence from polycentric and bottom-up climate action suggests that cities, firms, civil society, and regional governments can drive rapid innovation even when UNFCCC negotiations progress slowly. Lauvaux et al. (2022) show that hyperlocal greenhouse gas data can support this kind of decentralized action by improving accountability and targeting [15]. However, open questions remain about how to integrate hyperlocal actions and emissions data into national and international accountability systems and how to ensure non-state actions are additional rather than substitutes for national commitments.

Managing transition risks and climate justice is another major gap. Clean energy transitions create winners and losers across regions, sectors, and social groups. Health-focused literature emphasizes broad co-benefits from clean energy transitions, but coal-dependent regions may face job losses and stranded assets, while developing countries remain concerned about energy access and development constraints [13]. Research is still needed on concrete models of just-transition financing and governance that combine mitigation, poverty reduction, and economic development. These questions are closely linked to carbon debt, adaptation finance, and the equitable distribution of future CDR responsibilities [11].

Finally, global warming research still underrepresents intersecting crises and non-CO₂ impacts. Some sectors reveal complex climate-health-nutrition interactions. For example, global warming appears to reduce the nutritional quality of livestock milk, including protein and fat content, in many studies, with possible consequences for vulnerable populations. However, a systematic review found no studies on climate impacts on human breastmilk composition [2]. This illustrates how climate mitigation and adaptation research often underrepresents low-income populations, women, and children. Non-CO₂ gases such as CH₄, N₂O, and F-gases also have strong near-term warming effects. Although technical solutions exist, including methane leak reduction and improved fertilizer use, deployment remains slow, and their role in staying below 1.5–2 °C remains an active debate.

Key References Cited

[1] Liu et al. 2024. “Recent advances on greenhouse gas emissions from wetlands: mechanism, global warming potential, and environmental drivers.” Environ. Pollut.

[2] (2025). “Global warming impacts on lactating mammalian milk: A systematic review.” Sci. Total Environ.

[4] Xing et al. 2024. “Impacts on compound drought heatwave events in Australia per global warming level.” Environ. Res. Lett.

[6] Wang et al. 2024. “A novel framework to assess climate change impacts on typhoon-induced urban wind fields using pseudo-global warming simulations: A case study of Typhoon Mangkhut.” Phys. Fluids.

[7] Lange et al. 2024. “Global warming level indicators of climate change and hotspots of exposure.” Environ. Res. Clim.

[8] Krieger et al. 2024. “Future projections of hurricane intensity in the southeastern U.S.: sensitivity to different Pseudo-Global Warming methods.” Front. Clim.

[9] Gürbüz et al. 2023. “High-Resolution Climate Simulations Over the Eastern Mediterranean Black Sea Region Using the Pseudo-Global Warming Method With a CMIP6 Ensemble.” J. Geophys. Res.: Atmos.

[10] Li et al. 2017. “Current trends in scientific research on global warming: a bibliometric analysis.” Int. J. Global Warming.

[11] Eisenman et al. 2024. “Using net-zero carbon debt to track climate overshoot responsibility.” Nat. Commun.

[12] Pachauri et al. 2023/24. “Proposed solutions to anthropogenic climate change: A systematic literature review and a new way forward.” Lancet Planet. Health or similar high-impact journal.

[13] Watts et al. 2024. “Accelerating Clean Energy Transitions to Safeguard Human Health and Survival.” Proc. Natl. Acad. Sci. USA or equivalent.

[14] Hak et al. 2010. “Regaining momentum for international climate policy beyond Copenhagen.” Proc. Natl. Acad. Sci. USA.

[15] Lauvaux et al. 2022. “Zooming-in for climate action—hyperlocal greenhouse gas data for mitigation action?” Environ. Res. Lett.

Citations

[1] https://linkinghub.elsevier.com/retrieve/pii/S0269749124009187[2] https://linkinghub.elsevier.com/retrieve/pii/S0048969725023976[3] http://biorxiv.org/lookup/doi/10.1101/2024.11.22.624945[4] https://iopscience.iop.org/article/10.1088/1748-9326/adc8bd[5] https://link.springer.com/10.1007/s41748-025-00710-2[6] https://pubs.aip.org/pof/article/37/7/077172/3355962/A-novel-framework-to-assess-climate-change-impacts[7] https://iopscience.iop.org/article/10.1088/2752-5295/ad8300[8] https://www.frontiersin.org/articles/10.3389/fclim.2024.1353396/full[9] https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD040145[10] http://www.inderscience.com/link.php?id=97858[11] https://pmc.ncbi.nlm.nih.gov/articles/PMC12002226/[12] https://pmc.ncbi.nlm.nih.gov/articles/PMC10585315/[13] https://pmc.ncbi.nlm.nih.gov/articles/PMC11851206/[14] https://pmc.ncbi.nlm.nih.gov/articles/PMC2894817/[15] https://pmc.ncbi.nlm.nih.gov/articles/PMC8991672/