Emission Trajectories Research Articles

Balancing Economic Growth and Emission Reductions: Policy Trade-offs in India’s Power Sector Towards Achieving the 2070 Net-Zero Goal

India faces significant policy trade-offs between raising living standards for 1.4 billion people and reducing global GHG emissions. While the government has introduced policies to promote renewable energy and reduce coal dependency, numerous efforts are required to meet the 2070 net-zero target. Cutting emissions will likely slow short-term growth and affect coal-dependent communities. However, the right policies can minimize these costs. This paper reviews India’s current climate policies and models emission trajectories under various policy scenarios to explore ways to reduce GHG emissions effectively.

Mapping Climatic Regions of the Cerrado: General Patterns and Future Change

ABSTRACTThe Cerrado biome, renowned for its biodiversity and threatened by rapid land transformation, encompasses a vast savanna ecosystem in Brazil. The region is characterised by a seasonal climate, influenced by a myriad of meteorological systems creating diverse and non‐homogeneous rainfall regimes across the region. To account for this heterogeneity, we propose a novel classification of the Cerrado using rainfall data to delineate three distinct climatic regions: Eastern, Southern and Central‐West Cerrado. The Eastern region exhibited the driest and most seasonal climate, marked by high vapour pressure deficit (VPD) and predominantly open‐canopy vegetation. Conversely, the Southern region, characterised by lower seasonality, boasts a higher proportion of forest cover and lower mean VPD. The Central‐West region, encompassing diverse landscapes, featured areas with higher precipitation levels, particularly along the Amazônia border. Furthermore, we conducted trend analyses on observed station data and used CMIP6 models to evaluate future scenarios under differing emissions trajectories. While observed trends in mean rainfall were marginal, VPD demonstrated a notable upward trend of approximately 1% annually throughout the biome. Climate models indicated a substantial drying close to the Amazônia border, and wetter conditions in the southeast. All Cerrado regions are anticipated to experience amplified seasonality and VPD, with VPD projected to surge by approximately 30% (60%) under low (high) emissions scenarios by the end of the century. Notably, the transition from the dry to wet season was the most affected. Our study provides critical insights on how the climatic heterogeneity of the Cerrado shapes vegetation structure distribution and how future changes will exacerbate water stress throughout the biome. These findings underscore the importance of understanding climate variability for effective conservation and management strategies in the region.

Liquid solvent direct air capture’s cost and carbon dioxide removal vary with ambient environmental conditions

Emission trajectories produced by integrated assessment models increasingly suggest that gigatonnes of carbon removal will be required to stabilize atmospheric greenhouse gas concentrations at safe levels. This can be accomplished using the direct air capture of carbon dioxide, among other technologies. Process models of these systems assume that they would operate at standard ambient temperature and pressure, when capture rates vary with ambient conditions, including temperature, relative humidity, and other factors. Here, we build an open-source model of a liquid solvent direct air capture technology and analyze its capture performance as a function of hourly varying ambient environmental conditions across Canada. We find that, in the cool climate considered, capture performance is degraded due to both varying environmental conditions and the intermittent operation that could result. Our findings can be used to calibrate policy and investment decisions, and to support engineers in making operational design choices.

Scenario analysis of supply‐ and demand‐side solutions for circular economy and climate change mitigation in the global building sector

AbstractResidential and non‐residential buildings are a major contributor to human well‐being. At the same time, buildings cause 30% of final energy use, 18% of greenhouse gas emissions (GHGE), and about 65% of material accumulation globally. With electrification and higher energy efficiency of buildings, material‐related emissions gain relevance. The circular economy (CE) strategies, narrow, slow, and close, together with wooden buildings, can reduce material‐related emissions. We provide a comprehensive set of building stock transformation scenarios for 10 world regions until 2060, using the resource efficiency climate change model of the stock–flow–service nexus and including the full CE spectrum plus wood‐intensive buildings. The 2020–2050 global cumulative new construction ranges from 150 to 280 billion m2 for residential and 70‐120 billion m2 for non‐residential buildings. Ambitious CE reduces cumulative 2020–2050 primary material demand from 80 to 30 gigatons (Gt) for cement and from 35 to 15 Gt for steel. Lowering floor space demand by 1 m2 per capita leads to global savings of 800‐2500 megatons (Mt) of cement, 300‐1000 Mt of steel, and 3‐10 Gt CO2‐eq, depending on industry decarbonization and CE roll‐out. Each additional Mt of structural timber leads to savings of 0.4‐0.55 Mt of cement, 0.6‐0.85 Mt of steel, and 0.8‐1.8 Mt CO2‐eq of system‐wide GHGE. CE reduces 2020–2050 cumulative GHGE by up to 44%, where the highest contribution comes from the narrow CE strategies, that is, lower floorspace and lightweight buildings. Very low carbon emission trajectories are possible only when combining supply‐ and demand‐side strategies. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.

Time Series Forecasting of Emission Trends Using Recurrent Neural Networks

This paper explores the application of Recurrent Neural Networks (RNNs) for forecasting emission trends, a critical aspect of addressing climate change and formulating effective environmental policies. Traditional forecasting methods, such as Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing, often fail to capture the complex nonlinear relationships and temporal dependencies inherent in emission data. In contrast, RNNs, particularly Long Short-Term Memory (LSTM) networks, are designed to recognize patterns in sequential data, making them well-suited for time series forecasting tasks. This study employs a comprehensive methodology that includes data collection from reputable sources, feature selection, RNN model design, and rigorous evaluation using various performance metrics. The results indicate that RNNs significantly outperform traditional forecasting techniques in terms of accuracy, providing valuable insights into future emission trajectories. The findings underscore the potential of RNNs as powerful tools for policymakers and researchers, facilitating more informed decision-making in the fight against climate change.

Carbon emission measurement and regional decomposition analysis of China’s beef cattle farming industry

IntroductionWarming caused by greenhouse gas (GHG) emissions has become a global environmental issue of widespread concern, and China, as a responsible power, has the pressing task of reducing carbon emissions. China is one of the world’s major beef producers and consumers, and at the same time, beef cattle, as a large livestock, is the largest source of GHG emissions in the livestock industry.MethodsThis study considered the panel data of 31 provinces in China from 2008 to 2022. The kernel density estimation and Dagum Gini coefficient were used to analyze the spatiotemporal dynamic evolution patterns and influencing factors of carbon emissions from China’s beef cattle farming industry.Results(1) The carbon emission trajectory of beef cattle production follows a distinctive “ascend-descend-ascend” three-phase pattern. By 2022, the sector’s cumulative carbon emissions had burgeoned by 37.62% relative to 2008, reflecting an average annual escalation of 2.31%. Despite the overall upward trend in carbon emissions, significant regional differences were observed. The Central Plains region has witnessed a consistent decline, in stark contrast to the Southwest and Northeast regions, which have emerged as hotspots for heightened carbon emissions and intensified emission densities within China’s beef cattle production landscape, underscoring the intensifying significance of carbon mitigation measures. (2) The kernel density curve shows an overall rightward shift with a specific gradient effect on carbon emissions. In addition, the range of the right drag of the curve in 2022 was significantly reduced, which laterally reflects the narrowing of the difference between the provinces with the highest and lowest carbon emissions from beef cattle farming. The principal source of variance in the overall carbon emissions from beef cattle production is the disparities between regions, which accounts for an average annual contribution rate of 52.52%. Conversely, the within-region contribution rates have remained relatively stable, while those for the intensity of transvariation have witnessed a substantial rise, with annual averages of 18.31 and 28.96%, respectively. (3) Regarding the factors influencing carbon emissions reduction, environmental regulations and production efficiency significantly drive carbon emissions reduction in beef cattle farming.DiscussionRelevant government departments should actively guide farmers toward green production, establish perfect policies and regulations for low-carbon beef cattle farming, and promote low-carbon beef cattle farming models based on local conditions.

Climate strategies for oil and gas production under the lens of an Integrated Assessment Model: The case of Brazil

Future projections of oil and gas demand suggest that some production will remain necessary. Although attention often focuses on CO2 emissions from the combustion of their products, oil and gas production is also a relevant global emission source of both CO2 and CH4. Hence, understanding the carbon performance of upstream activities in producing nations is vital for distinguishing producers in a climate-pressured global market. This work explores climate strategies for the oil and gas upstream sector, using Brazil as a case study. The sector´s emissions profile is evaluated under distinct national climate scenarios. The analysis employs BLUES, a national Integrated Assessment Model (IAM), to access production volumes, mitigation measures applicable to the sector, and carbon dioxide removal potentials within the country to eventually offset the sector's remaining emissions. Results indicate sustained oil and gas production over the evaluated horizon (2020–2050) without compromising national climate goals, yet the sector's future emissions trajectory does not align with decarbonization targets pursued by more ambitious oil-producing nations and industry players. Despite sectoral mitigation measures indicated by the model, considerable emissions remain until 2050. Conversely, the country offers ample offsetting opportunities with potential synergies for the sector, especially through BECCS. Furthermore, the acceptability of offsets is discussed.

Carbon peaking trajectory links to development of a coupled urbanization-industrialization-energy system

On the way towards carbon emission peaking, the influence of the interactions within urbanization, industrialization and energy consumption on the peaking process from the perspective of system evolution remains exclusive. Herein, targeting 30 Chinese provincial regions, we design an integrated framework consisting of 21 indices to represent a coupled urbanization-industrialization-energy (UIE) system. The coupling and coordination within the UIE system are measured and linked to regional carbon emission trajectory during 2000–2021 to explore the influence mechanism on its peaking process. The findings reveal levels of the coupling and coordination ranging from 0.30 to 0.99, with an inverted U-shaped pattern for the coupling and a progression from rapid to gradual growth for the coordination. The comprehensive coupling-coordination degree for regions has not yet reached the state beneficial for achieving the emission peak. The development quality of urbanization subsystem and industrialization subsystem is progressively relieving reliance on the energy subsystem, while a complete decoupling from carbon emissions has not been achieved. The influences of driving forces of the coordination exhibit spatiotemporal variations. The region-specific insights into steering the UIE system towards peaking carbon emissions with emphasis on the key driving forces are of practical significance.

A greater negative impact of future climate change on vegetation in Central Asia: Evidence from trajectory/pattern analysis

In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies.

Transitioning Toward a Zero-Emission Electricity Sector in a Net-Zero Pathway for Africa Delivers Contrasting Energy, Economic and Sustainability Synergies Across the Region.

Although Africa contributes less than 5% to global greenhouse gas (GHG) emissions, its role in global climate action is pivotal. To date, 53 African countries have submitted their Nationally Determined Contributions (NDCs), and four have committed to a net-zero target. However, many of Africa's NDCs are vaguely expressed and without specific focus on explicit sectoral decarbonization targets. Furthermore, Africa's huge land-based carbon dioxide removal (CDR) potential remains unclear in the context of enabling net-zero (NZ) emissions within the continent. This study achieves two objectives: Under a NZ GHG emission trajectory in Africa, we uncover the implications of a targeted zero-emission electricity sector by 2030, on the energy landscape and other sustainability factors. This study also features the role of land-based biological removal methods─bioenergy carbon capture and storage (BECCS) and afforestation/reforestation (A/R)─in net zero actualization in Africa. Our results reveal a unified but disparate actualisation of the mid-century net zero emission goal across the continent, as all regions except North Africa achieve carbon neutrality. The industrial sector faces significant difficulties in transitioning and contributes substantially to positive emissions on the continent, with its share of total residual emissions reaching 49-64% by 2050. This difficulty persists even with targeted sectoral decarbonization of the electricity sector, although it is significantly reduced by the availability of BECCS as a CDR option. Under the zero-emission electricity pathway, emissions in buildings and transport sectors are reduced due to rapid electrification. A trade-off emerges in the net zero pathway concerning land allocation for negative emissions versus other land use activities. A key result shows that achieving a net zero target in Africa leads to a cumulative loss of $102 billion in fossil fuel infrastructure within the electricity sector by mid-century, which doubles when the zero-emission electricity goal is achieved.

The effect of different climate and air quality policies in China on in situ ozone production in Beijing

Abstract. In recent years, clean air policies have led to reductions in air pollution across China. Alongside this, emerging carbon neutrality (CN) policies that aim to address the impacts of climate change may also deliver air quality (AQ) co-benefits or climate penalties. Different CN policies will lead to different changes in volatile organic compound (VOC), NOx and particulate matter (PM) emissions, which will in turn impact the photochemical production of secondary pollutants such as ozone (O3). It is currently unclear how different combinations of AQ and CN policies may impact in situ O3 production across China in the future. A detailed chemical box model incorporating the Master Chemical Mechanism was developed to investigate the impact of combined AQ and CN policies on O3 formation in Beijing. The Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) and the Dynamic Projection model for Emissions in China (DPEC) were used to estimate future pollutant mixing ratios, relative to ambient observations of 35 VOCs, NOx, CO and aerosol surface area (ASA) during the APHH-Beijing 2017 summer campaign. The most ambitious policy scenario, “Ambitious Pollution 1.5D Goals”, led to the largest reduction in O3 production by 2060 but was not the most impactful scenario for reducing O3 production between 2030–2045. Larger reductions were observed under the “Ambitious Pollution Neutral Goals” policy, which focuses on achieving net zero by 2060. O3 production was found to be most sensitive to changes in the OLE2 group of VOCs (alkenes where kOH>7×104 ppm−1 min−1; a 5 % increase in OLE2 increased simulated O3 production by 1.12 %). However, reducing less reactive but higher concentration species in Beijing (such as short-chain alkanes) led to larger reductions in O3 production under all scenarios. O3 production was not sensitive to changes in ASA, with a 69 % decrease in ASA leading to a change of <1 % in O3. However, doubling biogenic VOCs in the model further increased O3 production in 2060 under all future scenarios by up to 18 %, indicating that the influence of future climate-induced changes in biogenic emissions may have a significant impact on in situ O3 formation in Beijing. This study highlights that the emission trajectories of certain specific VOCs are highly influential in determining possible future O3 air quality effects that may arise from increasing ambient temperatures and decarbonisation in Beijing.

Underestimating demographic uncertainties in the synthesis process of the IPCC

In this work, we systematically analyse the population projections used in the emissions scenario ensembles reviewed by the Working Group III in the latest three reports of the Intergovernmental Panel on Climate Change (IPCC). We show that emissions scenarios span smaller demographic uncertainties than alternative estimates both for the world and for critical regions, such as South-East Asia, Sub-Saharan Africa, and China. Furthermore, the range of demographic projections has consistently shrunk over subsequent reports, exposing a problematic convergence towards a single socio-economic pathway: the “middle path” or SSP2. We argue that the undersampling of population uncertainties limits the range of future emission trajectories and has implications for climate transition scenarios. Emissions scenarios with a wider set of assumptions about future population should be submitted to the IPCC. The methods utilised in this study inform the development of independent audit methods for the assessment of relevant uncertainty sources in IPCC databases.

Achieving net zero greenhouse gas emissions critical to limit climate tipping risks

Under current emission trajectories, temporarily overshooting the Paris global warming limit of 1.5 °C is a distinct possibility. Permanently exceeding this limit would substantially increase the probability of triggering climate tipping elements. Here, we investigate the tipping risks associated with several policy-relevant future emission scenarios, using a stylised Earth system model of four interconnected climate tipping elements. We show that following current policies this century would commit to a 45% tipping risk by 2300 (median, 10–90% range: 23–71%), even if temperatures are brought back to below 1.5 °C. We find that tipping risk by 2300 increases with every additional 0.1 °C of overshoot above 1.5 °C and strongly accelerates for peak warming above 2.0 °C. Achieving and maintaining at least net zero greenhouse gas emissions by 2100 is paramount to minimise tipping risk in the long term. Our results underscore that stringent emission reductions in the current decade are critical for planetary stability.

The degree of population aging and carbon emissions: Analysis of mediation effect and multi-scenario simulation

The continuous deepening of aging has posed new challenges for global sustainable development. Measuring the impact of population aging on carbon emissions is crucial for the next stage of climate governance. However, the structural changes in social production and consumption make it difficult to evaluate the impact effects. Therefore, this study constructed a bidirectional fixed Space Durbin Model to explore the mediating pathway of aging's impact on carbon emissions. Furthermore, we have established high-precision prediction models to simulate the evolution trajectory of carbon emissions under multi-factor driving scenarios. The main findings are as follows: (1) The process of carbon emission reduction due to population aging has significant energy hindrance effect and industrial structure effect, while the process of carbon growth is constrained by the consumption enhancement effect, technology progress effect and labor participation effect. (2) The moderating effects of energy consumption and technological innovation on carbon emissions under the aging process are 10.74% and 10.24%, respectively, while the moderating effects of industrial structure and labor force participation are relatively weak. (3) The goodness of fit of the MNGM-ARIMA and MNGM-BPNN models is over 97%. Carbon emissions in the high aging regions show a decreasing trend in all scenarios except the energy consumption-driven scenario, while in the medium and low aging regions decrease slowly only in the R&D- and labor supply-driven scenarios. This study advocates developing heterogeneous emission reduction measures based on the degree of aging, accelerating supply side upgrading, and increasing the proportion of green consumption.

Climate Change Impacts on Legume Physiology and Ecosystem Dynamics: A Multifaceted Perspective

As valuable sources of plant-based protein, leguminous vegetables (grain legumes) are essential for global food security and contribute to body growth and development in humans as well as animals. Climate change is a major challenge for agriculture development that creates major problems for the growth and development of plants. However, legume productivity is threatened by climate change factors, including rising temperatures, shifting precipitation patterns, increased atmospheric carbon dioxide levels, intensified extreme events, and altered pest/pathogen activity. This review synthesizes approximately 136 studies to assess the climate effects on major legume crops. Under all the global emissions trajectories, the mean temperatures are projected to rise beyond the optimal legume growing thresholds by 2050, carrying yield reductions between 10 and 49% for beans, soybeans, cowpeas, and lentils without adaptation measures. The elevated carbon dioxide may transiently enhance the yields up to 18%, but the benefits dramatically decline above 550 ppm and cannot offset the other climate impacts. Altered rainfall along with recurrent drought and heat waves are also expected to decrease the legume crop yields, seed quality, and soil nitrogen levels worldwide. Furthermore, the proliferation of legume pests and fungal diseases poses significant risks, amplified by climate shifts in 84% of the reviewed studies. These multifaceted impacts threaten the productivity gains in leguminous vegetables essential to sustainably meeting the global protein demand. Realizing resilience will require the accelerated development of heat/drought-tolerant legume varieties, enhanced climate-informed agronomic practices, strong policy interventions, and social safety nets explicitly supporting legume producers, in addition to the policies/steps that governments are taking to address the challenges of the climate crisis. This review highlights the essential adaptations and mechanisms required for legume crops to thrive and fulfill their significant roles in global nutrition. It explores how these crops can be improved to better withstand the environmental stresses, enhance their nutritional profiles, and increase their yields. Additionally, the review discusses the importance of legumes in sustainable agriculture and food security, emphasizing their potential to address the future challenges in feeding the growing global population. By focusing on these critical aspects, the review aims to underscore the importance of legumes in ensuring a healthy and sustainable food supply.

A sustainable blue economy may not be possible in Tanzania without cutting emissions

Balancing blue growth with the conservation of wild species and habitats is a key challenge for global ocean management. This is exacerbated in Global South nations, such as Tanzania, where climate-driven ocean change requires delicate marine spatial planning (MSP) trade-offs to ensure climate resilience of marine resources relied upon by coastal communities. Here, we identified challenges and opportunities that climate change presents to the near-term spatial management of Tanzania's artisanal fishing sector, marine protected areas and seaweed farming. Specifically, spatial meta-analysis of climate modelling for the region was carried out to estimate the natural distribution of climate resilience in the marine resources that support these socially important sectors. We estimated changes within the next 20 and 40 years, using modelling projections forced under global emissions trajectories, as well as a wealth of GIS and habitat suitability data derived from globally distributed programmes. Multi-decadal analyses indicated that long-term climate change trends and extreme weather present important challenges to the activity of these sectors, locally and regionally. Only in few instances did we identify areas exhibiting climate resilience and opportunities for sectoral expansion. Including these climate change refugia and bright spots in effective ocean management strategies may serve as nature-based solutions: promoting adaptive capacity in some of Tanzania's most vulnerable economic sectors; creating wage-gaining opportunities that promote gender parity; and delivering some economic benefits of a thriving ocean where possible. Without curbs in global emissions, however, a bleak future may emerge for globally valuable biodiversity hosted in Tanzania, and for its coastal communities, despite the expansion of protected areas or curbs in other pressures. Growing a sustainable ocean economy in this part of the Global South remains a substantial challenge without global decarbonization.

Options to enhance China’s national emission trading system design for carbon neutrality

ABSTRACT To better align the emissions trajectory of China’s power sector with the country’s neutrality target for 2060, China’s national Emission Trading System (ETS) needs to be enhanced. This study uses a power system planning model that incorporates an output-based ETS module to explore the effects of three enhanced ETS options: 1) tightening the benchmark faster, 2) introducing auctions, and 3) transitioning to a cap-and-trade ETS. A cap-and-trade ETS can achieve deep decarbonization at the lowest cost by encouraging cheap renewables. With an increased benchmark stringency under free allocation and output-based ETS, the power sector can achieve the same level of emission reduction at a 5.2% higher cost compared to a cap-and-trade ETS. This is due to the extensive development of carbon capture, utilization, and storage (CCUS) technology, facilitated by the free allowance allocation of the output-based ETS. Introducing auctions into an output-based ETS would encourage both renewables and CCUS and increase the cost by 1.4% compared to the cap-and-trade ETS. First, we suggest that auctioning be introduced into an output-based ETS to cost-effectively encourage a diversified power supply. Subsequently, we recommend turning to a cap-and-trade ETS after 2030 to reduce the cost of decarbonization.

An Investigation of the Carbon Emissions and Climate Change Awareness from the Artisanal and Small-scale Gold Mining (ASGM) sector in Guyana: The Case of Mahdia

Mineral extractive industries are becoming increasingly relevant in climate change science and policy. Guyana’s economic policy, the Low Carbon Development Strategy, seeks to align sectors of the economy along a low carbon emission trajectory. Although the artisanal and small-scale gold mining (ASGM) sector is economically important, it is a known emissions-intensive sector that contributes to deforestation and direct operational emissions. This study sought to increase understanding of direct operational emissions by investigating carbon emissions associated with fuel combustion in ASGM. Further, the study investigated miners’ awareness of carbon emissions and willingness to reduce emissions; thus providing context for policymakers to advance measures aimed at reducing carbon emissions in the ASGM sector. The research methods used were qualitative document analysis, questionnaire-survey, and interviews. It was found that the average carbon dioxide emission per volume of earth moved from a sample of ASGM operations in Mahdia per quarter was 4.69 x 10-6 MtCO2e/m3. Miners were generally unaware of their carbon footprint and its link to mining, climate change, and the Low Carbon Development Strategy. This knowledge gap was accompanied by negative attitudes. 79% of miners indicated there was no need to reduce their carbon footprint, and 85% of miners were unwilling to change their usual practices. Recommendations to advance and integrate the sector within the Low Carbon Development Strategy framework were explored within the themes of: regulation and management; fiscal measures; technology; and education and awareness.

Double Counting of Emission Reductions Undermines the Credibility of Corporate Mitigation Claims.

Companies are increasingly relying on emission reductions attributable to their adoption of renewable electricity to achieve net-zero emission targets. However, there is a risk of double counting of emission reductions threatening the credibility of corporate climate actions due to defective accounting rules of GHG emissions related to electricity consumption and the overlap between different market-based instruments, including carbon credit markets, renewable power purchase agreements, and renewable energy certificates. Using data of 63 major Chinese companies in seven sectors, we quantitatively assess the risks of double counting related to corporate sourcing of renewables and their consequent influences on the alignment of corporate emission trajectories with the 1.5 °C goal of the Paris Agreement. Results show that 7.1% of the electricity consumed by sample companies in 2021 was from renewable energy procurement and deployment, with which they reported 8.27 Mt of CO2e emission reductions compared to the scenario with no renewable electricity consumption. However, emission reductions that could be double counted are predicted to be 0.9-1.3 times as many as emission reductions that companies will report during 2021-2030. After adjustment of the reported emissions that might be underestimated due to double counting, the overall emission trajectories of sample companies are no longer aligned with the 1.5 °C goal. Our findings suggest that it is urgently needed to improve the corporate carbon accounting rules and increase the transparency of corporate carbon disclosures.

Decoupling state of urban development and carbon emissions and its driving factors and predictions: A case study of Chengdu metropolitan area

Prioritizing the reduction of carbon emissions in key developing urban centers is a significant step toward achieving China's carbon peaking and neutrality goals. We examined the Chengdu metropolitan area as a case study. We proposed a coupled method for inversely estimating nighttime light and carbon emissions from energy consumption, enhancing the accuracy of fitting at the county scale and addressing the issue of missing energy consumption data. We integrated the Tapio decoupling model and the Logarithmic Mean Divisia Index (LMDI) model for comprehensive analysis, mitigating the limitations arising from the use of a singular model. Furthermore, we employed a multi-scenario analysis with an extended STIRPAT model to forecast the carbon emission trajectory of the Chengdu urban agglomeration and elucidate potential pathways for achieving carbon peaking and carbon neutrality goals. The findings indicated the following:(1)carbon emissions are predominantly concentrated in regions characterized by high levels of urban development. Forested land serves as the primary carbon sink; however, its capacity in the Chengdu metropolitan area fails to offset carbon emissions from energy consumption;(2)factor decomposition analysis revealed that economic development was the principal driver of carbon emissions, leading to an increase of 23.7964 million tons. Conversely, energy intensity emerged as the primary mitigation factor, reducing carbon emissions by 11.0677 million tons;(3)The Chengdu metropolitan area is projected to reach a carbon peak by 2030, with the multi-factor coordinated optimization (MFO) model representing the most favorable trajectory, with a projected peak of approximately 15.6998 million tons. However, to achieve carbon neutrality by 2060, there is still a surplus of approximately 10.4808 million tons.