Carbon pricing and system reliability impacts on pathways to universal electricity access in Africa

Off-grid photovoltaic systems have been proposed as a panacea for economies with poor electricity access, offering a lower-cost "leapfrog" over grid infrastructure used in higher-income economies. Previous research examining pathways to electricity access may understate the role of off-grid photovoltaics as it has not considered reliability and carbon pricing impacts. We perform high-resolution geospatial analysis on universal household electricity access in Sub-Saharan Africa that includes these aspects via least-cost pathways at different electricity demand levels. Under our "Tier 3" demand reference scenario, 24% of our study's 470 million people obtaining electricity access by 2030 do so via off-grid photovoltaics. Including a unit cost for unmet demand of 0.50 US dollars ($)/kWh, to penalise poor system reliability increases this share to 41%. Applying a carbon price (around $80/tonne CO2-eq) increases it to 38%. Our results indicate considerable diversity in the level of policy intervention needed between countries and suggest several regions where lower levels of policy intervention may be effective.

On the potential of vehicle-to-grid and second-life batteries to provide energy and material security

The global energy transition relies increasingly on lithium-ion batteries for electric transportation and renewable energy integration. Given the highly concentrated supply chain of battery materials, importing regions have a strategic imperative to reduce their reliance on battery material imports through, e.g., battery recycling or reuse. We investigate the potential of vehicle-to-grid and second-life batteries to reduce resource use by displacing new stationary batteries dedicated to grid storage. Based on dynamic material flow analysis, we show that equipping around 50% of electric vehicles with vehicle-to-grid or reusing 40% of electric vehicle batteries for second life each have the potential to fully cover the European Union's need for stationary storage by 2040. This could reduce total primary material demand from 2020-2050 by up to 7.5% and 1.5%, respectively, which could ease geopolitical risks and increase the European Union's energy and material security. Any surplus capacity could be used as a strategic reserve to increase resilience in the face of emergencies such as blackouts or adverse geo-political events.

Systematic review and meta-analysis of ex-post evaluations on the effectiveness of carbon pricing

Today, more than 70 carbon pricing schemes have been implemented around the globe, but their contributions to emissions reductions remains a subject of heated debate in science and policy. Here we assess the effectiveness of carbon pricing in reducing emissions using a rigorous, machine-learning assisted systematic review and meta-analysis. Based on 483 effect sizes extracted from 80 causal ex-post evaluations across 21 carbon pricing schemes, we find that introducing a carbon price has yielded immediate and substantial emission reductions for at least 17 of these policies, despite the low level of prices in most instances. Statistically significant emissions reductions range between -5% to -21% across the schemes (-4% to -15% after correcting for publication bias). Our study highlights critical evidence gaps with regard to dozens of unevaluated carbon pricing schemes and the price elasticity of emissions reductions. More rigorous synthesis of carbon pricing and other climate policies is required across a range of outcomes to advance our understanding of "what works" and accelerate learning on climate solutions in science and policy.

Public engagement for inclusive and sustainable governance of climate interventions

The need for public engagement is increasingly evident as discussions intensify around emerging methods for carbon dioxide removal and controversial proposals around solar geoengineering. Based on 44 focus groups in 22 countries across the Global North and Global South (N = 323 participants), this article traces public preferences for a variety of bottom-up and top-down engagement practices ranging from information recipient to broad decision authority. Here, we show that engagement practices need to be responsive to local political cultures and socio-technical environments, while attending to the global dimensions and interconnectedness of the issues at stake. Establishing public engagement as a cornerstone of inclusive and sustainable governance of climate-intervention technologies requires (i) recognizing the diversity of forms and intensities of engaging, (ii) considering national contexts and modes of engagement, (iii) tailoring to technological idiosyncrasies, (iv) adopting power-sensitive practices, (v) accounting for publics' prior experience, (vi) establishing trust and procedural legitimacy and (vii) engaging with tensions and value disagreements.

The differential impact of climate interventions along the political divide in 60 countries

A major barrier to climate change mitigation is the political polarization of climate change beliefs. In a global experiment conducted in 60 countries (N = 51,224), we assess the differential impact of eleven climate interventions across the ideological divide. At baseline, we find political polarization of climate change beliefs and policy support globally, with people who reported being liberal believing and supporting climate policy more than those who reported being conservative (Cohen's d = 0.35 and 0.27, respectively). However, we find no evidence for a statistically significant difference between these groups in their engagement in a behavioral tree planting task. This conceptual-behavioral polarization incongruence results from self-identified conservatives acting despite not believing, rather than self-identified liberals not acting on their beliefs. We also find three interventions (emphasizing effective collective actions, writing a letter to a future generation member, and writing a letter from the future self) boost climate beliefs and policy support across the ideological spectrum, and one intervention (emphasizing scientific consensus) stimulates the climate action of people identifying as liberal. None of the interventions tested show evidence for a statistically significant boost in climate action for self-identified conservatives. We discuss implications for practitioners deploying targeted climate interventions.

Compensating affected parties necessary for rapid coal phase-out but expensive if extended to major emitters

Coal power phase-out is critical for climate mitigation, yet it harms workers, companies, and coal-dependent regions. We find that more than half of countries that pledge coal phase-out have  "just transition" policies which compensate these actors. Compensation is larger in countries with more ambitious coal phase-out pledges and most commonly directed to national and regional governments or companies, with a small share going directly to workers. Globally, compensation amounts to over $200 billion (uncertainty 163-258), about half of which is funded through  international schemes, mostly through Just Energy Transition Partnerships and the European Union Just Transition Fund. If similar transfers are extended to China and India to phase out coal in line with the Paris temperature targets, compensation flows could become larger than current international climate financing. Our findings highlight that the socio-political acceptance of coal phase-out has a tangible economic component which should be factored into assessing the feasibility of achieving climate targets.

Public perceptions on carbon removal from focus groups in 22 countries

Carbon removal is emerging as a pillar of governmental and industry commitments toward achieving Net Zero targets. Drawing from 44 focus groups in 22 countries, we map technical and societal issues that a representative sample of publics raise on five major types of carbon removal (forests, soils, direct air capture, enhanced weathering, and bioenergy with carbon capture and storage), and how these translate to preferences for governance actors, mechanisms, and rationales. We assess gaps and overlaps between a global range of public perceptions and how carbon removal is currently emerging in assessment, innovation, and decision-making. In conclusion, we outline key societal expectations for informing assessment and policy: prioritize public engagement as more than acceptance research; scrutiny and regulation of industry beyond incentivizing innovation; systemic coordination across sectors, levels, and borders; and prioritize underlying causes of climate change and interrelated governance issues.

Evaluating the potential and eligibility of conservation agriculture practices for carbon credits

Carbon credits, a voluntary market mechanism to reduce greenhouse gas (GHG) emissions, can incentivize climate action. We evaluate the potential and eligibility of Conservation Agriculture (CA) practices for carbon credit generation in India under Verra's VM0042 methodology. Using farmer surveys and remote sensing data, we assess the eligibility based on the following conditions: Additionality Condition (GHG emission reductions to exceed legal requirements and the weighted mean adoption rate to be < 20% of area in the baseline), Yield Penalty Condition (no > 5% decrease in crop yields), and Quantitative Adjustment Condition (reduction in chemical fertilizer use by > 5%). Our analysis shows that CA has the potential to increase farmers' carbon credit earnings by USD 18/ha and USD 30/ha in Bihar and Punjab, respectively. Punjab's ban on crop residue burning and the fact that > 20% of the area unburned limits the full economic realization of CA through carbon markets, decreasing potential income to USD 16/ha. A 60% increase in carbon prices from the current norm (USD 25) is required to encourage wider adoption of CA. Zero tillage of wheat in both Punjab and Bihar and reduction of nitrogen fertilizer overuse in Punjab fulfil all the conditions and are eligible for carbon farming projects.

Increase in concerns about climate change following climate strikes and civil disobedience in Germany

Climate movements have gained momentum in recent years, aiming to create public awareness of the consequences of climate change through salient climate protests. This paper investigates whether concerns about climate change increase following demonstrative protests and confrontational acts of civil disobedience. Leveraging individual-level survey panel data from Germany, we exploit exogenous variations in the timing of climate protests relative to survey interview dates to compare climate change concerns in the days before and after a protest (N = 24,535). Following climate protests, we find increases in concerns about climate change by, on average, 1.2 percentage points. Further, we find no statistically significant evidence that concerns of any subpopulation decreased after climate protests. Lastly, the increase in concerns following protests is highest when concern levels before the protests are low.

Agri-environmental policies from 1960 to 2022

For both research and practice, it is paramount to understand what, where and when agri-environmental policies have been put in place. Here we present a database of 6,124 agri-environmental policies implemented between 1960 and 2022 in about 200 countries. The database comprises a wide range of policy types (including regulations and payment schemes) and goals (such as biodiversity conservation, safer pesticide use and reducing nutrient pollution). We illustrate the application of the database by exploring the association between economic development and agri-environmental policies and between the soil-related, agri-environmental policies of countries and their border discontinuities in cropland erosion. A strong, positive link between economic development and implemented agri-environmental policies is revealed, and it is found that 43% of all global border discontinuities in soil erosion between countries can be explained by differences in their policies.

Trade-offs in land-based carbon removal measures under 1.5 °C and 2 °C futures

Land-based carbon removals, specifically afforestation/reforestation and bioenergy with carbon capture and storage (BECCS), vary widely in 1.5 °C and 2 °C scenarios generated by integrated assessment models. Because underlying drivers are difficult to assess, we use a well-known integrated assessment model, GCAM, to demonstrate that land-based carbon removals are sensitive to the strength and scope of land-based mitigation policies. We find that while cumulative afforestation/reforestation and BECCS deployment are inversely related, they are both typically part of cost-effective mitigation pathways, with forestry options deployed earlier. While the CO2 removal intensity (removal per unit land) of BECCS is typically higher than afforestation/reforestation over long time horizons, the BECCS removal intensity is sensitive to feedstock and technology choices whereas the afforestation/reforestation removal intensity is sensitive to land policy choices. Finally, we find a generally positive relationship between agricultural prices and removal effectiveness of land-based mitigation, suggesting that some trade-offs may be difficult to avoid.

The atlas of unburnable oil for supply-side climate policies

To limit the increase in global mean temperature to 1.5 °C, CO2 emissions must be drastically reduced. Accordingly, approximately 97%, 81%, and 71% of existing coal and conventional gas and oil resources, respectively, need to remain unburned. This article develops an integrated spatial assessment model based on estimates and locations of conventional oil resources and socio-environmental criteria to construct a global atlas of unburnable oil. The results show that biodiversity hotspots, richness centres of endemic species, natural protected areas, urban areas, and the territories of Indigenous Peoples in voluntary isolation coincide with 609 gigabarrels (Gbbl) of conventional oil resources. Since 1524 Gbbl of conventional oil resources are required to be left untapped in order to keep global warming under 1.5 °C, all of the above-mentioned socio-environmentally sensitive areas can be kept entirely off-limits to oil extraction. The model provides spatial guidelines to select unburnable fossil fuels resources while enhancing collateral socio-environmental benefits.

Limited impact of hydrogen co-firing on prolonging fossil-based power generation under low emissions scenarios

Climate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators.

China's low-carbon policy intensity dataset from national- to prefecture-level over 2007-2022

Low-carbon policies are essential for facilitating manufacturing industries' low-carbon transformation and achieving carbon neutrality in China. However, recent studies usually apply proxy variables to quantify policies, while composite indices of policy intensity measured by objectives and instruments focus more on the national level. It is deficient in direct and comprehensive quantification for low-carbon policies. Hence, having extended the meaning of policy intensity, this paper constructs a low-carbon policy intensity index quantified by policy level, objective and instrument via phrase-oriented NLP algorithm and text-based prompt learning. This process is based on the low-carbon policy inventory we built for China's manufacturing industries containing 7282 national-, provincial- and prefecture-level policies over 2007-2022. Lastly, we organize the dataset in two formats (.dta and .xlsx) for multidiscipline researchers. Apart from the inventory and intensity for each policy, the policy intensity is also aggregated to national-, provincial- and prefecture-level with sub-intensity for four objectives and three instruments. This dataset has potential uses for future studies by merging with macro and micro data related to low-carbon performances.

Exploring negative emission potential of biochar to achieve carbon neutrality goal in China

Limiting global warming to within 1.5 °C might require large-scale deployment of premature negative emission technologies with potentially adverse effects on the key sustainable development goals. Biochar has been proposed as an established technology for carbon sequestration with co-benefits in terms of soil quality and crop yield. However, the considerable uncertainties that exist in the potential, cost, and deployment strategies of biochar systems at national level prevent its deployment in China. Here, we conduct a spatially explicit analysis to investigate the negative emission potential, economics, and priority deployment sites of biochar derived from multiple feedstocks in China. Results show that biochar has negative emission potential of up to 0.92 billion tons of CO2 per year with an average net cost of US$90 per ton of CO2 in a sustainable manner, which could satisfy the negative emission demands in most mitigation scenarios compatible with China's target of carbon neutrality by 2060.

Greenhouse gas emissions from US irrigation pumping and implications for climate-smart irrigation policy

Irrigation reduces crop vulnerability to drought and heat stress and thus is a promising climate change adaptation strategy. However, irrigation also produces greenhouse gas emissions through pump energy use. To assess potential conflicts between adaptive irrigation expansion and agricultural emissions mitigation efforts, we calculated county-level emissions from irrigation energy use in the US using fuel expenditures, prices, and emissions factors. Irrigation pump energy use produced 12.6 million metric tonnes CO2e in the US in 2018 (90% CI: 10.4, 15.0), predominantly attributable to groundwater pumping. Groundwater reliance, irrigated area extent, water demand, fuel choice, and electrical grid emissions intensity drove spatial heterogeneity in emissions. Due to heavy reliance on electrical pumps, projected reductions in electrical grid emissions intensity are estimated to reduce pumping emissions by 46% by 2050, with further reductions possible through pump electrification. Quantification of irrigation-related emissions will enable targeted emissions reduction efforts and climate-smart irrigation expansion.

Modelling six sustainable development transformations in Australia and their accelerators, impediments, enablers, and interlinkages

There is an urgent need to accelerate progress on the Sustainable Development Goals (SDGs) and recent research has identified six critical transformations. It is important to demonstrate how these transformations could be practically accelerated in a national context and what their combined effects would be. Here we bridge national systems modelling with transformation storylines to provide an analysis of a Six Transformations Pathway for Australia. We explore important policies to accelerate progress, synergies and trade-offs, and conditions that determine policy success. We find that implementing policy packages to accelerate each transformation would boost performance on the SDGs by 2030 (+23% above the baseline). Policymakers can maximize transformation synergies through investments in energy decarbonization, resilience, social protection, and sustainable food systems, while managing trade-offs for income and employment. To overcome resistance to transformations, ambitious policy action will need to be underpinned by technological, social, and political enabling conditions.

Stakeholder-driven transformative adaptation is needed for climate-smart nutrition security in sub-Saharan Africa

Improving nutrition security in sub-Saharan Africa under increasing climate risks and population growth requires a strong and contextualized evidence base. Yet, to date, few studies have assessed climate-smart agriculture and nutrition security simultaneously. Here we use an integrated assessment framework (iFEED) to explore stakeholder-driven scenarios of food system transformation towards climate-smart nutrition security in Malawi, South Africa, Tanzania and Zambia. iFEED translates climate-food-emissions modelling into policy-relevant information using model output implication statements. Results show that diversifying agricultural production towards more micronutrient-rich foods is necessary to achieve an adequate population-level nutrient supply by mid-century. Agricultural areas must expand unless unprecedented rapid yield improvements are achieved. While these transformations are challenging to accomplish and often associated with increased greenhouse gas emissions, the alternative for a nutrition-secure future is to rely increasingly on imports, which would outsource emissions and be economically and politically challenging given the large import increases required.

Approaching national climate targets in China considering the challenge of regional inequality

Achievement of national climate targets and the corresponding costs would entirely depend on regional actions within the country. However, because of substantial inequalities and heterogeneities among regions, especially in developing economies, aggressive or uniform actions may exacerbate inequity and induce huge economic losses, which in turn challenges the national climate pledges. Hence, this study extends prior research by proposing economically optimal strategies that can achieve national climate targets and ensure the greatest local and national benefits as well as regional equality. Focusing on the biggest developing country China, we find this strategy can avoid up to 1.54% of cumulative GDP losses for approaching carbon neutrality, and more than 90% of regions would obtain economic gains compared either with existing independently launched targets or with the uniform strategy that all regions achieve peak carbon emissions before 2030. We also provide optimal carbon mitigation pathways to regional peak carbon, carbon intensity and energy consumption.

Towards understanding policy design through text-as-data approaches: The policy design annotations (POLIANNA) dataset

Despite the importance of ambitious policy action for addressing climate change, large and systematic assessments of public policies and their design are lacking as analysing text manually is labour-intensive and costly. POLIANNA is a dataset of policy texts from the European Union (EU) that are annotated based on theoretical concepts of policy design, which can be used to develop supervised machine learning approaches for scaling policy analysis. The dataset consists of 20,577 annotated spans, drawn from 18 EU climate change mitigation and renewable energy policies. We developed a novel coding scheme translating existing taxonomies of policy design elements to a method for annotating text spans that consist of one or several words. Here, we provide the coding scheme, a description of the annotated corpus, and an analysis of inter-annotator agreement, and discuss potential applications. As understanding policy texts is still difficult for current text-processing algorithms, we envision this database to be used for building tools that help with manual coding of policy texts by automatically proposing paragraphs containing relevant information.

Spread in climate policy scenarios unravelled

Analysis of climate policy scenarios has become an important tool for identifying mitigation strategies, as shown in the latest Intergovernmental Panel on Climate Change Working Group III report1. The key outcomes of these scenarios differ substantially not only because of model and climate target differences but also because of different assumptions on behavioural, technological and socio-economic developments2-4. A comprehensive attribution of the spread in climate policy scenarios helps policymakers, stakeholders and scientists to cope with large uncertainties in this field. Here we attribute this spread to the underlying drivers using Sobol decomposition5, yielding the importance of each driver for scenario outcomes. As expected, the climate target explains most of the spread in greenhouse gas emissions, total and sectoral fossil fuel use, total renewable energy and total carbon capture and storage in electricity generation. Unexpectedly, model differences drive variation of most other scenario outcomes, for example, in individual renewable and carbon capture and storage technologies, and energy in demand sectors, reflecting intrinsic uncertainties about long-term developments and the range of possible mitigation strategies. Only a few scenario outcomes, such as hydrogen use, are driven by other scenario assumptions, reflecting the need for more scenario differentiation. This attribution analysis distinguishes areas of consensus as well as strong model dependency, providing a crucial step in correctly interpreting scenario results for robust decision-making.

The social costs of tropical cyclones

Tropical cyclones (TCs) can adversely affect economic development for more than a decade. Yet, these long-term effects are not accounted for in current estimates of the social cost of carbon (SCC), a key metric informing climate policy on the societal costs of greenhouse gas emissions. We here derive temperature-dependent damage functions for 41 TC-affected countries to quantify the country-level SCC induced by the persistent growth effects of damaging TCs. We find that accounting for TC impacts substantially increases the global SCC by more than 20%; median global SCC increases from US$ 173 to US$ 212 per tonne of CO2 under a middle-of-the-road future emission and socioeconomic development scenario. This increase is mainly driven by the strongly TC-affected major greenhouse gas emitting countries India, USA, China, Taiwan, and Japan. This suggests that the benefits of climate policies could currently be substantially underestimated. Adequately accounting for the damages of extreme weather events in policy evaluation may therefore help to prevent a critical lack of climate action.

Spatiotemporal differences in and influencing effects of per-capita carbon emissions in China based on population-related factors

Intensive human activities and resource consumption in China have led to increasing carbon emissions, placing enormous pressure on achieving sustainable development goals. Nonetheless, the effects of population-related factors and carbon emissions remain controversial. This study focuses on the spatiotemporal differences in and influencing effects of per-capita carbon emissions using 2010-2019 panel data covering 30 regions in China. Differing from previous studies, population-related factors are employed to classify the 30 regions into 4 classes, and kernel density estimation, σ convergence and spatial econometric models are used to analyse the spatiotemporal differences in and influencing effects of per-capita carbon emissions. The results demonstrate that overall per-capita carbon emissions rose, but there was heterogeneity in the change in per-capita carbon emissions in the 4 classes of regions. The difference in regional per-capita carbon emissions has been widening, but the change rate of the difference stabilized. Overall, per-capita carbon emissions are heavily affected by household size; however, the driving forces behind per-capita carbon emissions in the 4 classes of regions vary. These results suggest that precise and coordinated governance of carbon emissions and reverting to the traditional household structure should be considered to meet the dual carbon goal.

Exposure to climate change information predicts public support for solar geoengineering in Singapore and the United States

Solar geoengineering is a controversial climate policy measure that could lower global temperature by increasing the amount of light reflected by the Earth. As scientists and policymakers increasingly consider this idea, an understanding of the level and drivers of public support for its research and potential deployment will be key. This study focuses on the role of climate change information in public support for research and deployment of stratospheric aerosol injection (SAI) in Singapore (n = 503) and the United States (n = 505). Findings were consistent with the idea that exposure to information underlies support for research and deployment. That finding was stronger in the United States, where climate change is a more contentious issue, than in Singapore. Cost concern was negatively related to support for funding and perceived risk was negatively related to support for deployment. Perceived government efficacy was a more positive predictor of support for funding in Singapore than in the United States. Additionally, relatively low support for local deployment was consistent with a NIMBY mindset. This was the first study to quantify the role of climate change information in SAI policy support, which has practical implications for using the media and interpersonal channels to communicate about SAI policy measures.

Decarbonization potential of electrifying 50% of U.S. light-duty vehicle sales by 2030

The U.S. federal government has established goals of electrifying 50% of new light-duty vehicle sales by 2030 and reducing economy-wide greenhouse gas emissions 50-52% by 2030, from 2005 levels. Here we evaluate the vehicle electrification goal in the context of the economy-wide emissions goal. We use a vehicle fleet model and a life cycle emissions model to project vehicle sales, stock, and emissions. To account for state-level variability in electric vehicle adoption and electric grid emissions factors, we apply the models to each state. By 2030, greenhouse gas emissions are reduced by approximately 25% (from 2005) for the light-duty vehicle fleet, primarily due to fleet turnover of conventional vehicles. By 2035, emissions reductions approach 45% if both vehicle electrification and grid decarbonization goals (100% by 2035) are met. To meet climate goals, the transition to electric vehicles must be accompanied by an accelerated decarbonization of the electric grid and other actions.

Aiding food security and sustainability efforts through graph neural network-based consumer food ingredient detection and substitution

Understanding precisely what is in food products is not always straightforward due to food fraud, differing labelling regulations, naming inconsistencies and the hierarchical nature of ingredients. Despite this, the need to detect and substitute ingredients in consumer food products is far-reaching. The cultivation and production of many ingredients is unsustainable, and can lead to widespread deforestation and biodiversity loss. Understanding the presence and replaceability of these ingredients is an important step in reducing their use. Furthermore, certain ingredients are critical to consumer food products, and identifying these ingredients and evaluating supply-chain resilience in the event of losing access to them is vital for food security analysis. To address these issues, we first present a novel machine learning approach for detecting the presence of unlabelled ingredients. We then characterise the unsolved problem of proposing viable food substitutions as a directed link prediction task and solve it with a graph neural network (GNN).

Equivalent impacts of logging and beaver activities on aboveground carbon stock loss in the southernmost forest on Earth

The conservation of forest landscapes is crucial for global climate strategies, and the forest in Tierra del Fuego, located in Patagonia, represents the southernmost example on Earth. These ecosystems are critical for Chile's roadmap toward carbon neutrality. Unfortunately, these ecosystems have been impacted by logging and beaver activities. Currently, the precise contribution of each driver to forest cover and carbon stock loss remains insufficiently quantified, impeding effective policymaking and the implementation of strategies to safeguard and enhance carbon stocks in these ecosystems. In this study, we conducted an assessment of forest carbon stock loss resulting from both logging and beaver activities in Chilean Tierra del Fuego from 1986 to 2019. While beavers have received significant attention for their substantial contribution to forest cover loss (56.1% forest cover, ≈ 1.4 MtC), our findings suggest that logging has nearly equally contributed to carbon stock depletion (43.8% forest cover, ≈ 1.2 MtC). Consequently, the prevailing focus on beavers has obscured the ongoing logging-induced carbon stock loss. The implications of our study highlight the urgency for comprehensive consideration of both drivers in Chile's climate strategy to fulfill the country's mitigation commitments.

Circular wood use can accelerate global decarbonisation but requires cross-sectoral coordination

Predominantly linear use of wood curtails the potential climate-change mitigation contribution of forestry value-chains. Using lifecycle assessment, we show that more cascading and especially circular uses of wood can provide immediate and sustained mitigation by reducing demand for virgin wood, which increases forest carbon sequestration and storage, and benefits from substitution for fossil-fuel derived products, reducing net greenhouse gas emissions. By United Kingdom example, the circular approach of recycling medium-density fibreboard delivers 75% more cumulative climate-change mitigation by 2050, compared with business-as-usual. Early mitigation achieved by circular and cascading wood use complements lagged mitigation achieved by afforestation; and in combination these measures could cumulatively mitigate 258.8 million tonnes CO2e by 2050. Despite the clear benefits of implementing circular economy principles, we identify many functional barriers impeding the structural reorganisation needed for such complex system change, and propose enablers to transform the forestry value-chain into an effective societal change system and lead to coherent action.

Life cycle assessment of a direct air capture and storage plant in Ireland

Despite the efforts to transition to a low carbon economy, greenhouse gas emissions are surging to critical levels. Carbon dioxide removals (CDR) methods, such as direct air capture (DAC), have been gaining substantial public attention in the last few years. DAC is essential in curbing CO2 concentrations and achieving climate targets. It is said that DAC can be deployed at anywhere, but a throughout life cycle assessment (LCA) is imperative to prove its viability. Therefore, this paper aims to explore the feasibility of constructing a 1 [Formula: see text] plant in Ireland, using Kinsale and Corrib gas fields as storage points. The results showed that the country is an ideal candidate for scaling up this emerging industry. The efficiency is primarily influenced by the construction of the pipeline section, given a reliable sources of heat and electricity. The study highlights the significant impact of distances to the storage points on feasibility, favouring counties near of the gas fields. In conclusion, Ireland has the potential to establish its own DAC industry.

Concentration of asset owners exposed to power sector stranded assets may trigger climate policy resistance

Thoroughly assessing the owners and distribution of stranded assets in a 2 °C scenario is essential to anticipate climate policy resistance. We employ novel data to analyze owners and incidence of asset stranding in the power sector globally. We show that Asia-Pacific, Europe, and the US are highly exposed to stranded assets, especially coal plants. Stranded assets are highly concentrated in a few asset owners in some countries (e.g., India). Even if owners are more equally exposed (e.g., in the US) they can vary considerably in the asset stranding timing due to differences in plant fleets' age profile. European, US, and Chinese asset owners own large shares of stranded coal plants abroad. Listed owners may face stranded assets of up to 78% of their share price or more than 80% of their equity. Asset stranding exposure positively correlates with ownership of alternative energy assets. India stands out owning many stranded assets but little alternative energy.

Achieving decent living standards in emerging economies challenges national mitigation goals for CO2 emissions

Emerging economies, low- and middle-income countries experiencing rapid population and GDP growth, face the challenge of improving their living standards while stabilizing CO2 emissions to meet net-zero goals. In this study, we quantify the CO2 emissions required for achieving decent living standards (DLS) in emerging economies. The results show that, compared to other regions, achieving DLS in emerging Asian and African economies will result in more additional CO2 emissions, particularly in the DLS indicators of Mobility and Electricity. Achievement of DLS in emerging economies will result in 8.6 Gt of additional CO2 emissions, which should not jeopardize global climate targets. However, a concerning trend arises as more than half of the emerging economies (62 out of 121) will face substantial challenges in aligning their expected emission growth for achieving DLS with their national emission mitigation targets.

Costs and health benefits of the rural energy transition to carbon neutrality in China

The rural energy transition is critical in China's efforts to achieve carbon neutrality and improve air quality. However, the costs and health benefits associated with the transition to carbon neutrality remain unclear. Here we explore the cost-effective transition pathways and air quality-related health impacts using an integrated energy-air quality-health modeling framework. We find that decarbonizing rural cooking and heating would triple contemporary energy consumption from 2014 to 2060, considerably reducing energy poverty nationwide. By 2060, electric cooking ranges and air-to-air heat pumps should be widely integrated, costing an additional 13 billion USD nationally in transformation costs, with ~40% concentrated in Shandong, Heilongjiang, Shanxi and Hebei provinces. Rural residential decarbonization would remarkably improve air quality in northern China, yielding substantial health co-benefits. Notably, monetized health benefits in most provinces are projected to offset transformation costs, except for certain relatively lower-development southwestern provinces, implying more financial support for rural residents in these areas will be needed.

A comprehensive walkability evaluation system for promoting environmental benefits

Pedestrian-oriented urban strategies such as the Paris 15-minute City are needed to respond to the global boiling. Quantitative evaluation of pedestrian-oriented urban objectives is important for various cities, and in this paper, a walkability evaluation system for the advanced model is developed considering the characteristics of a large city. The system calculates the walkability of Seoul. The evaluation system uses the Betweenness index as a weight in the urban network analysis. Considering stations with a high betweenness in urban traffic is essential for evaluating a pedestrian-oriented metropolis. Our findings in this study are that the UNA index in WES is critical for transit-oriented, walkable cities. The large city needs to find the location for mobility hubs or stations to observe the last mile. Installing a mobility hub or station at a high-value location in the city center is functionally important. In a pedestrian-oriented city, citizens can walk and bike the last mile in a busy city center. Walkable cities can encourage active transport and ultimately create more sustainable and environmentally friendly transportation systems. This study offers valuable insights into pedestrian infrastructure, urban systems, and policies that promote green transportation.

Global fossil fuel reduction pathways under different climate mitigation strategies and ambitions

The mitigation scenarios database of the Intergovernmental Panel on Climate Change's Sixth Assessment Report is an important resource for informing policymaking on energy transitions. However, there is a large variety of models, scenario designs, and resulting outputs. Here we analyse the scenarios consistent with limiting warming to 2 °C or below regarding the speed, trajectory, and feasibility of different fossil fuel reduction pathways. In scenarios limiting warming to 1.5 °C with no or limited overshoot, global coal, oil, and natural gas supply (intended for all uses) decline on average by 95%, 62%, and 42%, respectively, from 2020 to 2050, but the long-term role of gas is highly variable. Higher-gas pathways are enabled by higher carbon capture and storage (CCS) and carbon dioxide removal (CDR), but are likely associated with inadequate model representation of regional CO2 storage capacity and technology adoption, diffusion, and path-dependencies. If CDR is constrained by limits derived from expert consensus, the respective modelled coal, oil, and gas reductions become 99%, 70%, and 84%. Our findings suggest the need to adopt unambiguous near- and long-term reduction benchmarks in coal, oil, and gas production and use alongside other climate mitigation targets.

Carbon balance of plywood from a social reforestation program in Indonesia

Social reforestation programs plant trees on degraded, uncultivated land in low-income regions to allow the local population to generate income from selling wood products and-in case of agroforestry systems-to grow food. For fundraising it is of interest to demonstrate not only positive social impacts but also environmental ones. Proving negative greenhouse gas (GHG) emissions would allow the programs to enter the market for carbon offsetting projects and liberate further funding. In a case study, a social reforestation program in Kalimantan, Indonesia, is analyzed. GHG emissions (according to ISO 14067, PAS 2050 and EU ILCD Handbook for LCA) of the main product, laminated veneer lumber plywood, are determined as 622 and 21 kg CO2-e/m3 for short-term and long-term (above 100 years) plywood use, respectively. Switching to lignin-based resins and renewable electricity could reduce emissions down to - 363 kg CO2-e/m3 for long-term use. The analyzed agroforestry system produces almost carbon-neutral plywood today and could be climate positive in the mid-term.

Machine learning-enabled regional multi-hazards risk assessment considering social vulnerability

The regional multi-hazards risk assessment poses difficulties due to data access challenges, and the potential interactions between multi-hazards and social vulnerability. For better natural hazards risk perception and preparedness, it is important to study the nature-hazards risk distribution in different areas, specifically a major priority in the areas of high hazards level and social vulnerability. We propose a multi-hazards risk assessment method which considers social vulnerability into the analyzing and utilize machine learning-enabled models to solve this issue. The proposed methodology integrates three aspects as follows: (1) characterization and mapping of multi-hazards (Flooding, Wildfires, and Seismic) using five machine learning methods including Naïve Bayes (NB), K-Nearest Neighbors (KNN), Logistic Regression (LR), Random Forest (RF), and K-Means (KM); (2) evaluation of social vulnerability with a composite index tailored for the case-study area and using machine learning models for classification; (3) risk-based quantification of spatial interaction mechanisms between multi-hazards and social vulnerability. The results indicate that RF model performs best in both hazard-related and social vulnerability datasets. The most cities at multi-hazards risk account for 34.12% of total studied cities (covering 20.80% land). Additionally, high multi-hazards level and socially vulnerable cities account for 15.88% (covering 4.92% land). This study generates a multi-hazards risk map which show a wide variety of spatial patterns and a corresponding understanding of where regional high hazards potential and vulnerable areas are. It emphasizes an urgent need to implement information-based prioritization when natural hazards coming, and effective policy measures for reducing natural-hazards risks in future.

A study of management decisions to adopt emission reduction measures in heavy industry in an emerging economy

Heavy industry can face challenges in choosing applicable climate change mitigation measures due to a lack of technical background and practical guidance. A better understanding of these determinants is needed to design region-specific climate policies that most effectively enable more 'successful' low carbon transitions. Set in an emerging economy, this study aims to understand the determinants which underlie investment decision-making in greenhouse gas reduction. It relies on empirical research using an exploratory case study method in the leading cement company in Indonesia. The results show four key determinants influencing (constraining) adoption were (1) the primacy of profit-seeking objectives in operational planning and development; (2) the availability of sources (clinker substitutes and alternative energy fuels); (3) the limited access to cash capital; and (4) the complexity in implementing emissions reduction projects. The inquiry also compares determinants in an emerging and developed country to provide a comparative perspective on emissions management in manufacturing. It appears that firms from the industrial sector in emerging economies have investment strategies that are largely characterised by activities that accentuate achieving financial benefits or best value for money or cost savings in a short time frame, or 'short-termism'. Currently, greenhouse gas emissions management activities tend to be second-preference strategies for firms in emerging economies, at least in the industrial manufacturing sector.

Analysis of time-dependent effects of ambient temperatures on health by vulnerable groups in Korea in 1999-2018

This study compared the relative risks of heat days on mortalities by vulnerable groups (elderly, single-person households, less-educated) in the past decade (1999-2008) and the recent decade (2009-2018) in four cities, Seoul, Incheon, Daegu, and Gwangju, in Korea. It has been known that the health impacts of heatwaves have gradually decreased over time due to socio-economic development, climate adaptation, and acclimatization. Contrary to general perception, we found that the recent relative risk of mortality caused by heat days has increased among vulnerable groups. It may associate with recent increasing trends of severe heat days due to climate change. The increasing relative risk was more significant in single-person households and less-educated groups than in the elderly. It implies that the impacts of climate change-induced severe heat days have been and will be concentrated on vulnerable groups. It suggests that social polarization and social isolation should be addressed to reduce heatwave impacts. Furthermore, this study shows the necessity of customized heatwave policies, which consider the characteristics of vulnerable groups.

Effects of emission trading scheme (ETS) on change rate of carbon emission

This paper investigates the effects of Emission Trading Scheme (ETS) adoption on the country-level reduction rate of carbon emission. We first used Environmental Kuznets Curve (EKC) tests to group countries into three categories: inverse U-shaped and gamma-shaped EKC for decoupled countries, and a positive linear EKC for non-decoupled countries. We then examined the effectiveness of ETS adoption. We found ETS was effective for both post-industrial and pre-industrial economies. Compared to countries that have not adopted ETS, the carbon emission reduction (increment) rate of decoupled (non-decoupled) countries that have adopted ETS is faster (slower). Furthermore, ETS adoption significantly reduces overall carbon emissions per capita compared to other global events, such as oil crises. The results imply that a market-based mechanism is an effective strategy for achieving sustainable development, thus, providing insights for policymakers and governments to design effective carbon neutrality policies to achieve sustainable development.

Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement

Transformation pathways for the land sector in line with the Paris Agreement depend on the assumption of globally implemented greenhouse gas (GHG) emission pricing, and in some cases also on inclusive socio-economic development and sustainable land-use practices. In such pathways, the majority of GHG emission reductions in the land system is expected to come from low- and middle-income countries, which currently account for a large share of emissions from agriculture, forestry and other land use (AFOLU). However, in low- and middle-income countries the economic, financial and institutional barriers for such transformative changes are high. Here, we show that if sustainable development in the land sector remained highly unequal and limited to high-income countries only, global AFOLU emissions would remain substantial throughout the 21st century. Our model-based projections highlight that overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. While also a scenario purely based on either global GHG emission pricing or on inclusive socio-economic development would achieve the stringent emissions reductions required, only the latter ensures major co-benefits for other Sustainable Development Goals, especially in low- and middle-income regions.

Social media enables people-centric climate action in the hard-to-decarbonise building sector

The building and construction sector accounts for around 39% of global carbon dioxide emissions and remains a hard-to-abate sector. We use a data-driven analysis of global high-level climate action on emissions reduction in the building sector using 256,717 English-language tweets across a 13-year time frame (2009-2021). Using natural language processing and network analysis, we show that public sentiments and emotions on social media are reactive to these climate policy actions. Between 2009-2012, discussions around green building-led emission reduction efforts were highly influential in shaping the online public perceptions of climate action. From 2013 to 2016, communication around low-carbon construction and energy efficiency significantly influenced the online narrative. More significant interactions on net-zero transition, climate tech, circular economy, mass timber housing and climate justice in 2017-2021 shaped the online climate action discourse. We find positive sentiments are more prominent and recurrent and comprise a larger share of the social media conversation. However, we also see a rise in negative sentiment by 30-40% following popular policy events like the IPCC report launches, the Paris Agreement and the EU Green Deal. With greater online engagement and information diffusion, social and environmental justice topics emerge in the online discourse. Continuing such shifts in online climate discourse is pivotal to a more just and people-centric transition in such hard-to-decarbonise sectors.

Improving public support for climate action through multilateralism

For decades, policymakers have been attempting to negotiate multilateral climate agreements. One of the motivations for securing cooperation among multiple states is the belief that the public will be more supportive of adopting costly climate policies if other countries do so, both because this makes it more likely that important sustainability goals will be reached and because those efforts resonate with widely held fairness norms. However, some recent research suggests that public approval of climate action is independent of the policy choices made by other countries. Here, we present two different experimental studies fielded in multiple countries showing that multilateralism significantly increases public approval of costly climate action. Multilateralism makes climate policy more appealing by improving effectiveness beliefs and the policy's perceived fairness. Pursuing climate action within a multilateral setting does not only promise improved policy impacts, but may also generate higher levels of public support. Preregistration: This study has been pre-registered at AEA RCT Registry under #AEARCTR-0004090.

Low-cost adaptation options to support green growth in agriculture, water resources, and coastal zones

The regional climate as it is now and in the future will put pressure on investments in sub-Saharan Africa in water resource management, fisheries, and other crop and livestock production systems. Changes in oceanic characteristics across the Atlantic Ocean will result in remarkable vulnerability of coastal ecology, littorals, and mangroves in the middle of the twenty-first century and beyond. In line with the countries' objectives of creating a green economy that allows reduced greenhouse gas emissions, improved resource efficiency, and prevention of biodiversity loss, we identify the most pressing needs for adaptation and the best adaptation choices that are also clean and affordable. According to empirical data from the field and customized model simulation designs, the cost of these adaptation measures will likely decrease and benefit sustainable green growth in agriculture, water resource management, and coastal ecosystems, as hydroclimatic hazards such as pluviometric and thermal extremes become more common in West Africa. Most of these adaptation options are local and need to be scaled up and operationalized for sustainable development. Governmental sovereign wealth funds, investments from the private sector, and funding from global climate funds can be used to operationalize these adaptation measures. Effective legislation, knowledge transfer, and pertinent collaborations are necessary for their success.

High deforestation trajectories in Cambodia slowly transformed through economic land concession restrictions and strategic execution of REDD+ protected areas

Protected Areas (PAs) are continuously being established in tropical forests in an effort to preserve biodiversity and reduce deforestation. It was recently demonstrated that PAs are more effective at reducing forest loss than unprotected control sites across southeast Asia. The voluntary REDD+ scheme offers a new framework for the protection of high deforestation landscapes, jurisdictions, and countries backed by international carbon finance. Here we analyzed the economic drivers of deforestation in Cambodia and the effectiveness of 3 REDD+ projects vs. adjacent protected areas. We find that Economic Land Concessions were a predominant driver of deforestation in Cambodia and influenced the trajectory of illegal forest conversion in PAs. Furthermore, REDD+ projects offer significantly more protection against deforestation than adjacent PAs in two of the three analyzed cases, likely due to enhanced funding enabling implementation of targeted community activities and rigorous monitoring and enforcement.

Multiple climate change-driven tipping points for coastal systems

As the climate evolves over the next century, the interaction of accelerating sea level rise (SLR) and storms, combined with confining development and infrastructure, will place greater stresses on physical, ecological, and human systems along the ocean-land margin. Many of these valued coastal systems could reach "tipping points," at which hazard exposure substantially increases and threatens the present-day form, function, and viability of communities, infrastructure, and ecosystems. Determining the timing and nature of these tipping points is essential for effective climate adaptation planning. Here we present a multidisciplinary case study from Santa Barbara, California (USA), to identify potential climate change-related tipping points for various coastal systems. This study integrates numerical and statistical models of the climate, ocean water levels, beach and cliff evolution, and two soft sediment ecosystems, sandy beaches and tidal wetlands. We find that tipping points for beaches and wetlands could be reached with just 0.25 m or less of SLR (~ 2050), with > 50% subsequent habitat loss that would degrade overall biodiversity and ecosystem function. In contrast, the largest projected changes in socioeconomic exposure to flooding for five communities in this region are not anticipated until SLR exceeds 0.75 m for daily flooding and 1.5 m for storm-driven flooding (~ 2100 or later). These changes are less acute relative to community totals and do not qualify as tipping points given the adaptive capacity of communities. Nonetheless, the natural and human built systems are interconnected such that the loss of natural system function could negatively impact the quality of life of residents and disrupt the local economy, resulting in indirect socioeconomic impacts long before built infrastructure is directly impacted by flooding.

The mortality cost of carbon

Many studies project that climate change can cause a significant number of excess deaths. Yet, in integrated assessment models (IAMs) that determine the social cost of carbon (SCC) and prescribe optimal climate policy, human mortality impacts are limited and not updated to the latest scientific understanding. This study extends the DICE-2016 IAM to explicitly include temperature-related mortality impacts by estimating a climate-mortality damage function. We introduce a metric, the mortality cost of carbon (MCC), that estimates the number of deaths caused by the emissions of one additional metric ton of CO2. In the baseline emissions scenario, the 2020 MCC is 2.26 × 10‒4 [low to high estimate -1.71× 10‒4 to 6.78 × 10‒4] excess deaths per metric ton of 2020 emissions. This implies that adding 4,434 metric tons of carbon dioxide in 2020-equivalent to the lifetime emissions of 3.5 average Americans-causes one excess death globally in expectation between 2020-2100. Incorporating mortality costs increases the 2020 SCC from $37 to $258 [-$69 to $545] per metric ton in the baseline emissions scenario. Optimal climate policy changes from gradual emissions reductions starting in 2050 to full decarbonization by 2050 when mortality is considered.

Commercial afforestation can deliver effective climate change mitigation under multiple decarbonisation pathways

Afforestation is an important greenhouse gas (GHG) mitigation strategy but the efficacy of commercial forestry is disputed. Here, we calculate the potential GHG mitigation of a UK national planting strategy of 30,000 ha yr-1 from 2020 to 2050, using dynamic life cycle assessment. What-if scenarios vary: conifer-broadleaf composition, harvesting, product breakouts, and decarbonisation of substituted energy and materials, to estimate 100-year GHG mitigation. Here we find forest growth rate is the most important determinant of cumulative mitigation by 2120, irrespective of whether trees are harvested. A national planting strategy of commercial forest could mitigate 1.64 Pg CO2e by 2120 (cumulative), compared with 0.54-1.72 Pg CO2e for planting only conservation forests, depending on species composition. Even after heavy discounting of future product substitution credits based on industrial decarbonisation projections, GHG mitigation from harvested stands typically surpasses unharvested stands. Commercial afforestation can deliver effective GHG mitigation that is robust to future decarbonisation pathways and wood uses.

Spatial-temporal characterization of rainfall in Pakistan during the past half-century (1961-2020)

Spatial-temporal rainfall assessments are integral to climate/hydrological modeling, agricultural studies, and water resource planning and management. Herein, we evaluate spatial-temporal rainfall trends and patterns in Pakistan for 1961-2020 using nationwide data from 82 rainfall stations. To assess optimal spatial distribution and rainfall characterization, twenty-seven interpolation techniques from geo-statistical and deterministic categories were systematically compared, revealing that the empirical Bayesian kriging regression prediction (EBKRP) technique was best. Hence, EBKRP was used to produce and utilize the first normal annual rainfall map of Pakistan for evaluating spatial rainfall patterns. While the largest under-prediction was estimated for Hunza (- 51%), the highest and lowest rainfalls were estimated for Malam Jaba in Khyber Pakhtunkhwa province (~  1700 mm), and Nok-kundi in Balochistan province (~  50 mm), respectively. A gradual south-to-north increase in rainfall was spatially evident with an areal average of 455 mm, while long-term temporal rainfall evaluation showed a statistically significant (p = 0.05) downward trend for Sindh province. Additionally, downward inter-decadal regime shifts were detected for the Punjab and Sindh provinces (90% confidence). These results are expected to help inform environmental planning in Pakistan; moreover, the rainfall data produced using the optimal method has further implications in several aforementioned fields.

An integrated life cycle and water footprint assessment of nonfood crops based bioenergy production

Biomass gasification, especially distribution to power generation, is considered as a promising way to tackle global energy and environmental challenges. However, previous researches on integrated analysis of the greenhouse gases (GHG) abatement potentials associated with biomass electrification are sparse and few have taken the freshwater utilization into account within a coherent framework, though both energy and water scarcity are lying in the central concerns in China's environmental policy. This study employs a Life cycle assessment (LCA) model to analyse the actual performance combined with water footprint (WF) assessment methods. The inextricable trade-offs between three representative energy-producing technologies are explored based on three categories of non-food crops (maize, sorghum and hybrid pennisetum) cultivated in marginal arable land. WF results demonstrate that the Hybrid pennisetum system has the largest impact on the water resources whereas the other two technology options exhibit the characteristics of environmental sustainability. The large variances in contribution ratio between the four sub-processes in terms of total impacts are reflected by the LCA results. The Anaerobic Digestion process is found to be the main contributor whereas the Digestate management process is shown to be able to effectively mitigate the negative environmental impacts with an absolute share. Sensitivity analysis is implemented to detect the impacts of loss ratios variation, as silage mass and methane, on final results. The methane loss has the largest influence on the Hybrid pennisetum system, followed by the Maize system. Above all, the Sorghum system demonstrates the best performance amongst the considered assessment categories. Our study builds a pilot reference for further driving large-scale project of bioenergy production and conversion. The synergy of combined WF-LCA method allows us to conduct a comprehensive assessment and to provide insights into environmental and resource management.

The potential land requirements and related land use change emissions of solar energy

Although the transition to renewable energies will intensify the global competition for land, the potential impacts driven by solar energy remain unexplored. In this work, the potential solar land requirements and related land use change emissions are computed for the EU, India, Japan and South Korea. A novel method is developed within an integrated assessment model which links socioeconomic, energy, land and climate systems. At 25-80% penetration in the electricity mix of those regions by 2050, we find that solar energy may occupy 0.5-5% of total land. The resulting land cover changes, including indirect effects, will likely cause a net release of carbon ranging from 0 to 50 gCO₂/kWh, depending on the region, scale of expansion, solar technology efficiency and land management practices in solar parks. Hence, a coordinated planning and regulation of new solar energy infrastructures should be enforced to avoid a significant increase in their life cycle emissions through terrestrial carbon losses.