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• We develop a quantitative spatial equilibrium model with emissions regulation. • Counterfactual analyses of regional structural changes due to emissions regulation. • Emissions regulations impact regional GDP via regional-sectoral linkages. • Cross-regional impacts of emissions regulations have typical geographical characteristics. • Sectoral linkages widen variation in emissions regulations' impact on regional GDP. We develop and quantitatively evaluate a spatial general equilibrium model that incorporates carbon emission regulations. We study the impact of emission regulation on the economies of regions within a country under climate change mitigation goals, and how the impact of emission regulation in one region influences other regions through regional‒sectoral linkages. The model is calibrated using Chinese regional and sectoral data, and several counterfactual exercises are performed. The results indicate that undifferentiated increases in emission regulation across regions have resulted in inter-regional differences in real GDP changes; however, "equity-oriented" regionally differentiated emissions regulations reduce this imbalance. Regarding interactions between regions, negative impacts on the economy are characterized by geographical proximity, whereas positive impacts are not geographically constrained. Sectoral linkages exacerbate the negative economic impacts of emission regulations and widen regional disparities. Additionally, we demonstrate the extended application of our model through two case studies. [ABSTRACT FROM AUTHOR]

China is facing challenges to tackle the threat of climate change while reducing social inequality. Poverty eradication requires improvement in the living conditions of low-income households, which leads in turn to higher carbon footprints and may undermine the efforts of climate change mitigation. Previous studies have assessed the climate impacts of poverty eradication, but few have quantified how the additional carbon emissions of poverty eradication are shared at the subnational level in China and the impact on China's climate targets. We investigated the recent trend of carbon footprint inequality in China's provinces and estimated the climate burden of different poverty reduction schemes, measured by increased carbon emissions. The results indicate that poverty eradication will not impede the achievement of national climate targets, with an average annual household carbon footprint increase of 0.1%–1.2%. However, the carbon emissions growth in less developed provinces can be 4.0%, five times that in wealthy regions. Less developed regions suffer a greater climate burden because of poverty eradication, which may offset carbon reduction efforts. Therefore, interregional collaboration is needed to coordinate inequality reduction with investments in low-carbon trajectories in all provinces. [ABSTRACT FROM AUTHOR]

• Proposal of a method to construct typical generic block models using local datasets. • Urban form influences strategy of solar technology in low-carbon scenario. • Solar cooling contributes to carbon reduction in subtropical areas. • Technology and morphology design can overcome the high-density constraints. The use of solar energy in an urban context is essential for low-carbon urban development and global climate change mitigation. In this paper, the application of multiple solar energy techniques, namely, photovoltaic (PV), photothermal (PT), and photothermal-driven cooling (PC) techniques, in tropical Macau was investigated. Based on the typological method, sixty generic block typologies were formulated. A parametric workflow was constructed to facilitate block modelling and simulate energy consumption and solar radiation. The optimal technique strategy for each typology was identified under a low-carbon scenario. The energy and environmental performance levels of the blocks were evaluated by calculating and comparing the solar potentials, load matching conditions, primary energy consumption levels, and carbon dioxide emissions. The results indicated that the PT technique should be preferred for blocks with high floor area ratio (FAR) values, while the PV technique should be prioritized for blocks with low FAR values under the low-carbon scenario. Moreover, the PC technique is necessary in subtropical areas to reduce carbon emissions. In addition, it is suggested that solar energy should be adopted in blocks with high site coverage ratio (SC) and low surface area-to-volume ratio (SAV) values, as well as blocks with low FAR values. Regarding blocks constrained by high-density urban development, appropriate decisions on technology and morphological design could help to overcome constraints and realize low-carbon community targets. This study could provide suggestions for urban planners and building designers in the application of the urban solar potential at the early stages of urban design or urban regeneration. [ABSTRACT FROM AUTHOR]

Achieving decarbonisation of the heating sector is a major challenge, especially in Ireland, which has the lowest proportion of renewable heat in Europe. In economically pursuing ambitious and equitable climate targets, Ireland's Climate Action Plan 2023 set a goal of reaching 2.5 TWh of district heating by 2030, starting from a limited existing capacity. This pioneering study explores supply sources and heat density demand cohorts to develop a model to understand district heating in a low-deployment region, using Ireland as a case study. We also conduct a sensitivity analysis considering different connection rates. Our research demonstrates that district heating is pivotal in achieving optimal decarbonisation pathways. Incorporating district heating reduces marginal CO 2 emission prices by 13%–25%. Additionally, with feasible growth limits applied, total savings for the energy system are anticipated to reach €17.2 billion by 2050. This reduction of emissions in the building sector, facilitated by district heating, allows for greater emissions allowances in other sectors and reduces reliance on electricity while meeting climate targets. These insights highlight the need for spatial energy policies and deepen our understanding of integrating district heating within an energy system optimisation model. • District heating in Ireland can reduce marginal CO 2 emission prices by 13%–25%. • District heating can cumulatively save €17.2 billion compared to no district heating. • Regional energy policy is needed to align with cost-optimal pathways. • Regional supply and demand quantified sensitivity analysis strengthens insights. [ABSTRACT FROM AUTHOR]

Efforts to enhance greenhouse gas (GHG) emission reduction in East Asia play a pivotal role on both global and regional scales in advancing climate mitigation strategies. This study aimed to better constrain anthropogenic CO 2 emission estimates by expanding the network of near-surface in-situ stations for CO 2 observations across South Korea. To achieve an optimal CO 2 network design, we conducted an Observing System Simulation Experiment (OSSE) coupled with the Stochastic Lagrangian Transport model (STILT), utilizing meteorological data from the Korean Integrated Model (KIM). Our inversion setup incorporated two CO 2 emission datasets with a 0.1o resolution: EDGAR v6 for prior emissions and GRACED for truth emissions. A uniform model-mismatch error of 3 ppm was introduced across sites. The effectiveness of the existing five in-situ stations, termed the base network, in South Korea was evaluated to gauge their ability to constrain CO 2 surface flux estimates. However, the findings revealed a reduction in flux uncertainty of only 29.2%, which fell short of the desired uncertainty reduction goal. In this base network, the Lotte World Tower (LWT: 37.5126°E, 127.1025°E) in Seoul and the Anmyeondo (AMY: 36.538576° N, 126.330071° E) site in Taean county stood as major contributors, with estimated reductions of 17.48% and 6.35%, respectively. Consequently, we proposed and developed an extended network, identifying seven candidate sites based on consideration of logistical factors, existing infrastructures, and proximity to the emission source regions. An incremental optimization scheme ranked their contributions, resulting in an additional 25% reduction, bringing the total to 54.13%. However, it is noteworthy that diminishing returns (ranging from 13% to less than 0.1%) were observed with an increase in station count mainly due to the possibility that adding a station earlier in the sequence might render subsequent stations redundant. Despite this, the proposed CO 2 network successfully reduced uncertainty in emissions, narrowing the gap with the objectives of the Global Greenhouse Gas Watch (G3W). • Designing CO 2 near-surface observation network over South Korea. • New stations selected considering logistic factors, existing infrastructures, and proximity to emission sources. • The base network was able to reduce 29.18% of the uncertainty in CO 2 emissions. • Extending network, by adding new seven candidate sites, led to a total uncertainty reduction of 54.13%. [ABSTRACT FROM AUTHOR]

Cities represent unique spaces for climate mitigation where wide-ranging action to reduce emissions meets ambition and collaboration. This research work distils climate neutrality narratives for 362 cities that expressed interest in the European Mission on 100 Climate-Neutral and Smart Cities and focuses on the 112 cities selected to spearhead the process of reaching climate neutrality by 2030 (representing a mitigation potential of 318.3 megatonnes of carbon dioxide equivalent emissions). The method involves steps that profile the characteristics of these cities, enunciate cross-cutting patterns in cities' visions by thematic groupings, and compare 14 contextual factors with 77 possible main barriers. There are both similarities and differences among the results as a basis for learning together and certain barriers can be relatively more dominant in some thematic groupings, such as fragmentation of responsibilities. As a synthesis of the main findings, the original analyses are used to derive and prioritise nine high-level recommendations based on the cities' visions, contextual factors, and expected main barriers. Opportunities for mobilising transformative change relate to transforming siloed into integrated approaches, inclusive climate governance and collaborations, innovative financing, welfare and just transition as well as planning, implementation, and policy coherence. The advances provide pioneering steps for stimulating co-learning processes among Mission Cities and beyond to support the transition to climate neutrality and open up opportunities to progress together in climate action while producing impact with global reach. [Display omitted] • Visions and narratives for achieving climate neutrality by 2030 are enunciated across cities. • The 112 Mission Cities represent an emissions reduction potential of 318.3 MtCO 2 eq. • Thematic groupings are formed by cross-comparing degree of ambition and collaboration. • Recommendations are prioritised based on enablers and barriers in the thematic groupings. • Cross-cutting patterns in cities' visions provide opportunities to stimulate co-learning. [ABSTRACT FROM AUTHOR]

• Implementation costs are a more relevant constraint to afforestation than opportunity costs. • Financial incentives for afforestation are constrained by market access and market prices. • Carbon-neutral and food multi-oriented land policies need further exploration. • Collaboration among global carbon markets can enhance CO 2 removal efficiency. Afforestation is a promising nature-based climate solution for mitigating climate change, but it is subject to a complex web of biophysical, cost-benefit, market, and policy processes. Although its biophysical feasibility has been established, the cost, market, and policy constraints that affect climate change mitigation through afforestation are still unclear. Here, we estimate such cost, market, and policy constraints on the basis of biophysical feasibility. Our findings reveal that implementation costs are a more relevant constraint than opportunity costs on mitigating climate change through afforestation. The China Certified Emission Reduction market currently provides only a 0.308 % incentive for climate change mitigation through afforestation, due to market access constraints. The current market prices of China Certified Emission Reduction, China Carbon Emissions Trading Exchange, and Nature Based Carbon Offset in Voluntary Carbon Market constrain 88.15 %, 87.95 %, and 85.75 % of CO 2 removal actions through afforestation, compared to the carbon price scenario (US$62.97 tCO 2 -1) of the EU Emissions Trading System. Moreover, land policy under the scenarios of prohibiting conversion of cultivated land to forest and forest restoration in degraded areas exhibit 8.87–29.59 % and 65.16–74.10 % constraints, respectively, on mitigating climate change through afforestation compared to land-use freedom conversion scenarios from 2020 to 2060. Thus, enhancing the incentive price of CO 2 removal, addressing the market access barrier, strengthening cooperation between global carbon markets, and exploring carbon–neutral and food multi-oriented land policies can be valuable sources of mitigation efforts over the next 40 years. [ABSTRACT FROM AUTHOR]

Planning power system (PS) towards renewable energy is crucial for reducing carbon dioxide (CO 2) emission as well as mitigating climate change. However, the inherent uncertainty and hierarchical structure of PS pose intractable challenges to the planning process. This study develops a multi-GCM-based interval bi-level programming (MIBP) method that can balance two-level decision-making conflict between CO 2 -emisison reduction and system cost minimization. MIBP can also deal with uncertainties expressed as interval values in objective functions and constraints. Then, a MIBP-PS model is formulated to plan PS for China (2021–2050), where the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. The major findings are: (i) the CO 2 emission for PS would reach peak value before 2030 and then reduce by [10.2, 20.4]% in 2050, which is mainly owing to the curtailment of fossil fuel; (ii) compared with the conventional model, CO 2 emission from MIBP-PS model could decrease by [3.1, 4.8]%, which shows the superiority of the developed model; (iii) the fossil-fuel power would be gradually replaced by renewable energy, and the proportion of coal-fired power would decrease by 38.8% by 2050, especially small coal-fired facilities (i.e., below 0.3 GW) should be gradually phased down. [Display omitted] [ABSTRACT FROM AUTHOR]

The renewal of old bridges is sometimes restricted to avoid the high carbon emissions caused by materials and construction, which however might not be conductive to climate change mitigation due to their insufficient functions. In order to facilitate the optimization of renewal timing and strategy from the perspective of reducing the comprehensive global warming impacts, we put forward the low-carbon bridge renewal decision method referring to the ideas of consequential life cycle assessment (LCA) and dynamic LCA. In the proposed method, a comparative system boundary matching the bridge renewal characteristics is constructed, where the carbon emission reduction owing to the traffic efficiency improvement by functional updating is incorporated as the low-carbon benefits of renewal, and three types of time-dependent factors, i.e., time-dependent characterization factor, trend factors and changes of traffic demands, are introduced to characterize the influence of renewal timing. The proposed method provided guidance for the renewal of Maogang Bridge, the first long-span cable-stayed bridge in Shanghai. Results illustrate that the global warming impacts of renewal construction activities and the low-carbon benefits from functional updating decrease with the renewal timing. For Maogang Bridge, the rapidly increasing traffic demands inevitably advocated renewal in advance, and the reduction of global warming impacts from emission reduction or carbon uptake could be manifested for renewal in advance. Adopting material recycling in the disposal of old bridge helped reconstructing a new bridge while deconstructing the old one in 2019 becoming the finally selected low-carbon renewal strategy, which is expected to reduce 15.04 kt CO 2 e-2019 compared to the essential renewal in 2050 with the landfill disposal method. The robustness of the strategy choice has been justified, given the variations of analytical time horizon, expected emission trends and repair emissions. In this way, the low-carbon renewal decision method could build a quantitative basis for judging the urgency of functional updating and verifying the low-carbon benefits of immediate concrete recycling in up-coming urban renewals. • Low-carbon bridge renewal decision optimizes renewal timing and strategy. • System boundary is expanded for quantifying benefits from functional updating. • Emission trends and time-dependent characterization factors are explored. [ABSTRACT FROM AUTHOR]

The environmental impact of battery electric vehicles (BEVs), which are an integral part of climate change mitigation measures, depends on charging strategies, such as uncontrolled charging, controlled charging (V1G), and discharging (V2G). However, the impact is unclear because power system operation involves the cost of carbon dioxide (CO 2) emissions and flexibility requirements for imbalances caused by renewable energies. To clarify the robustness of the environmental impact of BEVs, we assessed the interactions between CO 2 prices and flexibility requirements in Japan in 2030 using a production cost model. The results showed that uncontrolled charging increases CO 2 emissions, whereas V1G or V2G reduces them. Further, the impact of BEVs was non-monotonic with respect to CO 2 prices, implying that policymakers should carefully evaluate CO 2 prices to achieve decarbonization as BEVs do not always reduce CO 2 emissions. This study provides useful insights for policymakers in countries with low-cost, inflexible, and high-emission power plants. [ABSTRACT FROM AUTHOR]

The ever-increasing challenges related to water security and climate mitigation underscore the pressing need for forward-thinking systems planning tools to drive urban sustainability transitions. In this study, we propose a novel city-level multi-objective planning framework that explores the nexus between carbon trading and water management, with the aim of facilitating water-efficient urban industrial restructuring. The framework integrates cap-and-trade mechanisms into a two-layered optimization model, creating an integrated approach to optimizing carbon emissions and generating economic opportunities for improving water efficiency. To illustrate the potential application of this framework, we conducted a case study focusing on Dongguan City, a water-stressed industrial metropolis in southern China. The results illustrate potential synergies between water planning strategies and carbon trading schemes, which could be harnessed to enable targeted reductions in water usage and carbon emissions. Furthermore, our findings identify the textile, apparel, and paper products manufacturing industries as primary candidates for strategic production scale reduction, emphasizing the importance of sustained support for the development of the computer and electronic manufacturing sector as a catalyst for urban sustainability transitions. By pioneering this new nexus-based perspective, our study offers valuable insights into long-term strategic planning for a low-carbon and resource-efficient urban economy. • Synergizing carbon trading and water management within a novel integrated planning framework. • Implementing resource-efficiency-driven optimization for water- and carbon-intensive manufacturing sectors. • Gaining insights into the specific roles of key manufacturing sectors in water management and carbon trading. • Introducing carbon trading systems may help in promoting water-efficient industrial restructuring. [Display omitted] [ABSTRACT FROM AUTHOR]

Growing concern over climate change mitigation has heightened the search for low-carbon, affordable, and non-intermittent energy alternatives. In this perspective, hydropower, thermal, solar, photovoltaic, and nuclear energy sources fit all these qualities as they are well-known as cleaner and ecosystem-friendly energy sources. However, despite the attractiveness of the clean energy transition, the extant literature has less documentation on the pertinent role of nuclear energy in the "climate change mitigation (SDG-13)" agenda, hence making it difficult to predict nuclear energy-CO 2 emissions (CO 2 e) nexus. Hence, the present study, using IPAT and the "environmental Kuznets curve (EKC)" framework, explores the consequences of nuclear energy generation, population dynamics, and economic progress on CO 2 e in the "United States of America (USA)" by applying a "dynamic autoregressive distributed lag (DARDL)" model from 1973 to 2021. The study provides evidence the existence of the EKC phenomena, suggesting that economic expansion hurts the environment up to a specific threshold level of per capita income, which is identified as US$ 29,581.16. Further empirical findings also show the detrimental effect of population-induced-emission. Remarkably, a 1% rise in nuclear energy generation dwindles CO 2 e by around 0.819%. The outcomes of this research demonstrate that economic growth level, population, and CO 2 emission are entangled. However, there is a need for a collective role from both stakeholders and policymakers in achieving "SDG-13" as well as "clean and affordable energy (SDG-7)" with a paradigm shift of the USA energy portfolio away from fossil fuels to renewables. • The nexus between nuclear energy-population-CO 2 emissions is investigated for USA. • We applied dynamic ARDL simulations model. • Environmental Kuznets Curve (EKC) hypothesis prevails in USA. • Nuclear energy generation dampens the effect of CO 2 emission. • The population induced-emission in both the short- and long-run is observed. [ABSTRACT FROM AUTHOR]

The Chinese government has announced ambitious carbon reduction goals to address climate change, however, there has been limited scientific attention to the achievement of deep decarbonization in regions with insufficient economic development. Moreover, the complex impacts of climate change mitigation on energy system, environment and economic development remain unclear in Northwest China. Here we construct a comprehensive evaluation model system to evaluate the effects of different climate mitigation pathways in Qinghai, Ningxia, Gansu and Xinjiang provinces. Results show that the four provinces need to vigorously increase the share of electricity that consumed in final energy to 53.1–60.0% and 52.9–62.0% for 2 °C and 1.5 °C target, respectively, and reduce total energy demand to 11.6–44.4 Mtoe and 8.2–34.1 Mtoe in 2050. Meanwhile, the CO 2 emissions for their energy systems will reach peak by 2025 at lower values. Moreover, the synergies of CO 2 reduction are most conducive to abating SO 2 pollution and also contributing to decreasing PM 2.5 concentrations. Additionally, the GDP losses in 2050 fluctuate from 5.0 to 21.7 billion USD in the 2 °C scenario to 11.5–52.7 billion USD in the 1.5 °C scenario. Our study provides practical guidance on achieving carbon reductions in less developed regions of China and lays foundations to promote decarbonization of energy systems in other provinces. • Realizing climate goals requires low-carbon energy systems led by electricity. • Energy-related carbon emissions in Northwest China will peak by 2025. • More ambitious climate and clean air policies are needed for air quality improvement. • Economic loss shows an upward trend in the future under climate targets. [ABSTRACT FROM AUTHOR]

Efforts to avoid the acceleration of global warming have tended to focus on countries with high CO 2 emissions levels and large populations, with a high level of economic development or industrialization. African countries, which often do not conform to such criteria, are more vulnerable to climate change due to their dependence on climate-sensitive industries and their limited infrastructure and technological capacity to cope with its impacts. The long-term economic growth rates projected for Africa's rapid development period will, further, make Africa a potential emission hotspot in the near future. Here, for the first time, we built an energy-related emissions inventory for 19 African countries for 2010–2019, which addresses emissions from 47 economic sectors and 5 energy types, making it the most comprehensive of its kind. The degree of decoupling of economy and emissions, and drivers of CO 2 emission changes are also examined. Most African countries experienced rapid growth in CO 2 emissions, with an average annual growth rate of 5.5% for fossil fuel-related CO 2 emissions and 6.0% for unsustainable biomass-related CO 2 emissions. Only two countries, South Africa and Tanzania, have achieved a strong decoupling of economic growth from CO 2 emissions. Economic and population are the most important drivers of emissions, while energy intensity has been identified as a key factor in mitigating CO 2 emissions, especially for those countries that have reached strong or weak decoupling. The findings from this study provide essential insights that could guide the development of low-carbon policies and strategies in Africa. • We provide energy-related emission inventories for 19 African countries from 2010 to 2019. • African countries experienced rapid growth in CO2 emissions. • Two countries achieved strong decoupling of GDP from CO2 emissions. • Economic and population growth are the most important drivers of emissions. [ABSTRACT FROM AUTHOR]

Decarbonizing the passenger transportation sector is critical for climate change mitigation. Existing studies on net-zero scenarios using Energy System Optimization Models (ESOM) often overlook non-monetary aspects of consumers' mobility choices but primarily focus on cost aspects. This study incorporates consumers' travel time duration and valuation, and an endogenous modal shift option into the Swiss TIMES Energy system Model (STEM). STEM is applied in a multi-objective optimization framework to quantify the impacts of faster Public Transport (PT) and slower car speeds on modal shifts in the transport sector's transformation. Similarly, we assess scenarios where consumers weigh travel time less, reflecting improved travel productivity. The results show that speed variations on medium- and long-distance trips, which can be interpreted as policies for highway speed limits and more efficient PT, can induce modal shifts towards 5–10% higher PT demand. Its implied secondary effects across the energy system include a reduced need for electrification of heavy-duty trucks by 11% and a decrease in hydrogen demand in road transportation by 34% by 2050. If travelers weigh costs over travel time, PT becomes less competitive against cars. Thus, electric vehicles (EVs) need to play a more dominant role in decarbonization, with a demand increase of 13% in 2040 (+9.2 billion passenger kilometer (bpkm)) and 6% in 2050 (+5.0 bpkm), along with the need for additional 45,000 public chargers of 22 kW size. Policy implications include the emphasis on improved PT speeds, speed limits on highways, needs to achieve more widespread EV adoption, and the need for balancing travelers' decision factors when aiming for reduced transport CO 2 emissions. • Non-monetary aspects relevant for modal shift incorporated in the Swiss TIMES model. • Multi-objective optimization to quantify net-zero impacts of non-monetary aspects. • Travel speed measures induce a 5–10% demand uptake of public transport. • Weighing travel time less makes electric cars more critical for decarbonization. • Secondary energy system effects are quantified & policy implications are drawn. [ABSTRACT FROM AUTHOR]

Animal production faces challenges related to thermal comfort, air quality, and carbon dioxide (CO 2) emissions, thereby the need for more efficient and sustainable systems due to climate change. This study examines green roofs and their potential to absorb atmospheric CO 2 and reduce heat load through photosynthesis and evapotranspiration, resulting in decreased energy consumption and increased CO 2 emissions. The maximum CO 2 concentration limit in animal production facilities is 3000 ppm. Depending on the ventilation system used in broiler production facilities, the CO 2 concentration can exceed 2000 ppm. Dark House poultry facilities tend to have higher concentrations reaching up to 777 ppm. In pig farming, the nursery sector has higher concentrations of CO 2 , exceeding 1200 ppm. In dairy farming, the number of milkings, the type of ventilation system and local climatic conditions can affect the CO 2 concentration, reaching values of up to 1401 ppm. C3 plants have a CO 2 saturation point at 800 ppm and C4 plants at 200 ppm. The CO 2 balance in animal production facilities that use a green roof can be done considering the CO 2 produced and the CO 2 absorbed. Green roofs are therefore considered a sustainable solution for animal production. Its implementation enhances air quality in the facilities, supporting the reduction of environmental impacts and mitigation of climate change effects caused by the agroindustry. This investigation underscores the significance of green roofs, emphasizing their environmental, social, and economic benefits, as well as their applicability in animal production. • It is possible to estimate the CO 2 balance in animal production facilities with a green roof. • Green roof can improve air quality in animal production. • Green roof can reduce the thermal stress of the animals in the premises. • Green roof can contribute to the sustainability of animal production. [ABSTRACT FROM AUTHOR]

Green manure is a widely applied to increase grain yield, while it also attributes to greenhouse gas (GHG) emissions in agriculture ecosystems. Combining green manure with inorganic fertilizer inputs is a common practice that can influence soil GHG emissions and grain yield, however, its impacts on grain yield and global warming potential (GWP) under different initial soil conditions before rotating experiments and agronomic management in paddy fields remain unclear. We synthesized 508 data pairs to evaluate the responses of CO 2 emissions, CH 4 emissions, N 2 O emissions, and grain yield to combined inputs of green manure plus inorganic fertilizer compared with only inorganic fertilizer application. Our findings indicate that both inorganic fertilizer plus extra green manure (GM-E) and green manure substitutes for inorganic fertilizer (GM-S) could increase CO 2 emissions (22.5 %−76.8 %), CH 4 emissions (100 %−103 %), N 2 O emissions (29.8 %−50.9 %), and yield (2.21 %−19.6 %). Except for GM-E, which showed a non-significant increase in grain yield. The initial soil properties before rotating experiments, the types and timing of green manure application were key drivers of GHG emissions and yield, and extra green manure applied in areas with low initial soil pH and high C:N can increase GWP and yield. Overall, the mixed green manure application had greater impact than leguminous or non-leguminous green manure applied alone. The responses of GHG emissions and yield to GM-S were modulated by mean annual precipitation and initial soil properties before rotating experiments, and green manure substitutes for inorganic fertilizer in areas with high initial soil pH and low C:N can increase GWP and yield. Meanwhile, excessive precipitation caused a reduction in yield and a significant increase in GWP intensity. Our results showed that extra green manure applications of less than 68.1 kg N ha−1 would not significantly increase GWP. Therefore, an effective green manure strategy can achieve a win-win situation for the dual challenge of agricultural production and climate change mitigation. • Green manure inputs significantly increased GHG emissions from paddy fields. • Green manure combined inorganic fertilizer may not increase the yield significantly. • Mixed green manure had greater impact than single-type green manure application. • Green manure substitutes for inorganic fertilizer may not increase the GWPI. • Extra green manure (<68.1 kg N ha-1) is recommended to achieve a win-win situation. [ABSTRACT FROM AUTHOR]

• The network structure characteristics of land-use carbon emissions (LUCE) are explored. • The problems of synergistic CO 2 reduction in Jiangxi province were identified. • The LUCE network structure in study areas becomes increasingly intricate and stable. • The LUCE spatial correlation network exhibited pronounced spatial spillover effects. • The study combines new relevant indicators to conduct carbon balance zoning. Exploring the spatial network structure of land-use carbon emissions (LUCE) and the carbon balance in developing regions is pivotal for climate change mitigation in these areas. Using socio-economic and land-use data from 2000 to 2020, this study focused on Jiangxi Province as a representative case to elucidate the spatial network structure of LUCE and conduct carbon balance zoning. The primary findings were as follows: (1) The LUCE distribution in Jiangxi Province demonstrated a spatial pattern with high values in the northwest and low values in the southeast. An increasing trend was observed in the total amount of LUCE. Furthermore, there were evident regional differences in the Ecological Support Coefficient (ESC), indicating a weakening regional carbon sink capacity. (2) The spatial network structure of LUCE was intricate but stable. Although the gravitational interactions of LUCE between cities have intensified, overall network connectivity remained moderately correlated, indicating a prominent regional development imbalance. (3) There was a pronounced "core-periphery" structure in the LUCE spatial correlation network. Northern Jiangxi was the "core" of the network, taking an "initiator" role, whereas most cities in southern Jiangxi played a "passive" role, and resided at the "periphery" of the network. The inter-regional LUCE network exhibited pronounced spatial spillover, with inter-block correlations surpassing those within blocks. (4) By leveraging empirical data and spatial metrics, we categorized Jiangxi Province into five distinct carbon balance zoning types and subsequently proposed land-use optimization strategies. From the perspective of social network analysis (SNA), this study offers methodological insights into low-carbon development and synergistic emission reduction in developing regions. [ABSTRACT FROM AUTHOR]

Carbon emission reduction in China matters to global climate change mitigation. China has been experiencing extensive land changes, which profoundly influence terrestrial ecosystem carbon storage (TECS) and carbon emissions. Scholars have predicted influences of land changes on TECS in China with scenarios obtained from global integrated assessment models (IAMs), which lack national details. Moreover, universally existing variations in land-use intensity have not been considered when estimating influences on TECS. This study simulated changes of land-use intensity of China from 2000 to 2050 using CLUMondo under China-specified policies for sustainable development modeled by a national IAM named Threshold21-China. We proposed a more precise TECS estimation method by distinguishing land-vegetation and land-soil types. Results demonstrated that under scenario with preceding policies, the total TECS can increase by 865.5 Tg C from 2000 to 2050. Through implementing preceding policies, TECS loss by conversions from cultivated land to artificial surfaces can decline by 82 Tg C, and new TECS accumulated by increased and densified forests can increase by 73 Tg C. Mountainous and rapidly urbanizing regions are sensitively influenced and need more restrict land change management policies. This study demonstrates the significance of sustainable development policies for TECS conservation and indicates specific critical regions. • Introducing national IAM into land change simulation. • Considering land-use intensities in land change simulation. • Proposing an improved TECS estimation method. • Estimating influences of land changes on China's TECS. • TECS accumulation could be improved under sustainable policies. [ABSTRACT FROM AUTHOR]

Mangrove ecosystems can absorb significant amounts of carbon and help mitigate climate change. However, their existence continues to be endangered by natural and human forces. Therefore, mangrove restoration is regarded as a crucial component of the global climate change agenda. This study aims to estimate the potential total carbon stock of restored mangrove ecosystems in Pasarbanggi, Rembang, Central Java. The above-below-ground (root) carbon stock was calculated using several published allometric equations. The loss-on-ignition method analyzed leaf litter and sediment carbon stocks. This study estimates the Pasarbanggi mangrove ecosystem's total carbon stock potential at 0.02 × 106 MgC, which is equivalent to the potential CO 2 emission of 0.08 × 106 MgCO 2 e, with up to 65% stored in sediments. This study highlights the critical role of restored mangrove ecosystems on the climate change mitigation agenda by reducing the concentration of atmospheric CO 2. • Mangroves are essential coastal ecosystems that offer ecosystem and environmental services. • Carbon stock sediment in mangrove ecosystems contributed up to 65 % of this total carbon stock. • Role of mangrove ecosystems on climate change mitigation by reducing the concentration of atmospheric CO 2. • Conservation is better initiative for the mangrove management approach, restoration is effective strategy in increasing carbon stocks and tree diversity. • The active role of local communities, supported by the government, is required in restoring mangrove ecosystems. [ABSTRACT FROM AUTHOR]