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The greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs), consisting mainly of methane (CH 4 ) and nitrous oxide (N 2 O), have been constantly increasing and become a non-negligible contributor towards carbon neutrality. The precise evaluation of plant-specific GHG emissions, however, remains challenging. The current assessment approach is based on the product of influent load and emission factor (EF), of which the latter is quite often a single value with huge uncertainty. In particular, the latest default Tier 1 value of N 2 O EF, 0.016 ± 0.012 kg N2O - N kg TN , is estimated based on the measurement of 30 municipal WWTPs only, without involving any industrial wastewater. Therefore, to resolve the pattern of GHG emissions from industrial WWTPs, this work conducted a 14-month monitoring campaign covering all the process units at a full-scale industrial WWTP in Shanghai, China. The total CH -1 , is estimated based on the measurement of 30 municipal WWTPs only, without involving any industrial wastewater. Therefore, to resolve the pattern of GHG emissions from industrial WWTPs, this work conducted a 14-month monitoring campaign covering all the process units at a full-scale industrial WWTP in Shanghai, China. The total CH 4 and N 2 O emissions from the whole plant were, on average, 447.7 ± 224.5 kg CO2-eq d -1 and 1605.3 ± 2491.0 kg CO2-eq d -1 , respectively, exhibiting a 5.2- or 3.9-times more significant deviation than the influent loads of chemical oxygen demand (COD) or total nitrogen (TN). The resulting EFs, 0.00072 kg CH4 kg COD -1 and 0.00211 kg N2O - N kg TN -1 , were just 0.36% of the IPCC recommended value for CH 4 , and 13.2% for N 2 O. Besides, the parallel anoxic-oxic (A/O) lines of this industrial WWTP were covered in two configurations, allowing the comparison of GHG emissions from different odor control setup. Unit-specific analysis showed that the replacement of enclosed A/open O with enclosed A/O reduced the CH 4 EF by three times, from 0.00159 to 0.00051 kg CH4 kg COD -1 , and dramatically decreased the N 2 O EF by an order of magnitude, from 0.00376 to 0.00032 kg N2O - N kg TN -1 , which was among the lowest of all full-scale WWTPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Globally, forest soils are considered as important sources and sinks of greenhouse gases (GHGs). However, most studies on forest soil GHG fluxes are confined to the topsoils (above 20 cm soil depths), with only very limited information being available regarding these fluxes in the subsoils (below 20 cm soil depths), especially in managed forests. This limits deeper understanding of the relative contributions of different soil depths to GHG fluxes and global warming potential (GWP). Here, we used a concentration gradient-based method to comprehensively investigate the effects of thinning intensity (15% vs. 35%) and nutrient addition (no fertilizer vs. NPK fertilizers) on soil GHG fluxes from the 0-40 cm soil layers at 10 cm depth intervals in a Chinese fir (Cunninghamia lanceolata) plantation. Results showed that forest soils were the sources of CO 2 and N 2 O, but the sinks of CH 4 . Soil GHG fluxes decreased with increasing soil depth, with the 0-20 cm soil layers identified as the dominant producers of CO 2 and N 2 O and consumers of CH 4 . Thinning intensity did not significantly affect soil GHG fluxes. However, fertilization significantly increased CO 2 and N 2 O emissions and CH 4 uptake at 0-20 cm soil layers, but decreased them at 20-40 cm soil layers. This is because fertilization alleviated microbial N limitation and decreased water filled pore space (WFPS) in topsoils, while it increased WFPS in subsoils, ultimately suggesting that soil WFPS and N availability (especially NH 4 + -N) were the predominant regulators of GHG fluxes along soil profiles. Generally, there were positive interactive effects of thinning and fertilization on soil GHG fluxes. Moreover, the 35% thinning intensity without fertilization had the lowest GWP among all treatments. Overall, our results suggest that fertilization may not only cause depth-dependent effects on GHG fluxes within soil profiles, but also impede efforts to mitigate climate change by promoting GHG emissions in managed forest plantations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Quercus gilva, an evergreen tree species in Quercus section Cyclobalanopsis, is an ecologically and economically valuable species in subtropical regions of East Asia. Predicting the impact of climate change on potential distribution of Q. gilva can provide a scientific basis for the conservation and utilization of its genetic resources, as well as for afforestation. In this study, 74 distribution records of Q. gilva and nine climate variables were obtained after data collection and processing. Current climate data downloaded from WorldClim and future climate data predicted by four future climate scenarios (2040s SSP1-2.6, 2040s SSP5-8.5, 2060s SSP1-2.6, and 2060s SSP5-8.5) mainly based on greenhouse gases emissions of distribution sites were used in MaxEnt model with optimized parameters to predict distribution dynamics of Q. gilva and its response to climate change. The results showed that the predicted current distribution was consistent with natural distribution of Q. gilva, which was mainly located in Hunan, Jiangxi, Zhejiang, Fujian, Guizhou, and Taiwan provinces of China, as well as Japan and Jeju Island of South Korea. Under current climate conditions, precipitation factors played a more significant role than temperature factors on distribution of Q. gilva, and precipitation of driest quarter (BIO17) is the most important restriction factor for its current distribution (contribution rate of 57.35%). Under future climate conditions, mean temperature of driest quarter (BIO9) was the essential climate factor affecting future change in potential distribution of Q. gilva. As the degree of climatic anomaly increased in the future, the total area of predicted distribution of Q. gilva showed a shrinking trend (decreased by 12.24%-45.21%) and Q. gilva would migrate to high altitudes and latitudes. The research results illustrated potential distribution range and suitable climate conditions of Q. gilva, which can provide essential theoretical references for the conservation, development, and utilization of Q. gilva and other related species., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Inspection, standing for top-down environmental management practices, also known as campaign-style governance, is used by central governments to lessen local environmental pollution. However, there is no causal evidence for carbon abatement. Employing staggered difference-in-differences (DiD), I find that inspected cities mitigate carbon intensity and carbon emissions by 3.72% and 2.34%, respectively, with economic significance. Conducting a triple difference strategy, I suggest the channels are the local people's congresses and political consultative conferences' proposals, government attention, environmental regulation, industrial structure, and green innovation. Also, the heterogeneous effects suggest that municipal party secretaries assigned to their birthplace, the older the party standing and age, and those with natural sciences majors, are more conducive to the inspection achieving carbon mitigation. An alternative DiD specification shows that the "look-back" inspection achieves sustained carbon reduction. I support the argument that top-down inspection helps achieve resilience to climate change and reduce greenhouse gas emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Low-carbon cities (LCC) are conducive to low-carbon development and reshaping the urban economic growth model. However, it is still unknown whether it has a synergistic mitigation effect on other greenhouse gases (GHGs). In this study, a dataset comprising 283 Chinese cities spanning the period 2003 to 2019 is chosen. We employ spatial difference-in-difference (SDID) modeling to investigate both the impacts and mechanisms of LCC on GHG emissions performance. The results show that (1) LCC notably lowers local GHG emissions, enhances emission efficiency, and improves GHG emissions performance in neighboring cities within a 1000 km radius. (2) LCC indirectly enhances the GHG emissions performance of local and neighboring cities through energy intensity and green technology innovation. Notably, LCC boosts the local GHG emissions performance by industrial structure upgrading and resource allocation but harms the positive spillover effects on nearby cities due to the siphoning effect. (3) The effect and spatial impact of LCC on GHG emission performance is notably pronounced in eastern cities, non-resource cities, and key environmental protection areas. The results of the study will further promote the development of LCC and provide an important decision-making reference for urban low-carbon sustainability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

With global population growth and climate change, food security and global warming have emerged as two major challenges to agricultural development. Plastic film mulching (PM) has long been used to improve yields in rain-fed agricultural systems, but few studies have focused on soil gas emissions from mulched rainfed potatoes on a long-term and regional scale. This study integrated field data with the Denitrification-Decomposition (DNDC) model to evaluate the impacts of PM on potato yields, greenhouse gas (GHG) and ammonia (NH 3 ) emissions in rainfed agricultural systems in China. We found that PM increased potato yield by 39.7 % (1505 kg ha -1 ), carbon dioxide (CO 2 ) emissions by 15.4 % (123 kg CO 2 eq ha -1 ), nitrous oxide (N 2 O) emissions by 47.8 % (1016 kg CO 2 eq ha -1 ), and global warming potential (GWP) by 38.9 % (1030 kg CO 2 eq ha -1 ), while NH 3 volatilization decreased by 33.9 % (8.4 kg NH 3 ha -1 ), and methane (CH 4 ) emissions were little changed compared to CK. Specifically, the yield after PM significantly increased in South China (SC), North China (NC), and Northwest China (NWC), with increases of 66.1 % (2429 kg ha -1 ), 44.1 % (1173 kg ha -1 ), and 43.6 % (956 kg ha -1 ) compared to CK, respectively. The increase in GWP and greenhouse gas emission intensity (GHGI) under PM was more pronounced in the Northeast China (NEC) and NWC regions, with respective increases of 57.1 % and 60.2 % in GWP, 16.9 % and 10.3 % in GHGI. While in the Middle and Lower reaches of the Yangtze River (MLYR) and SC, PM decreased GHGI with 10.2 % and 31.1 %, respectively. PM significantly reduced NH 3 emissions in all regions and these reductions were most significant in Southwest China (SWC), SCand MLYR, which were 41 %, 38.0 %, and 38.0 % lower than CK, respectively. In addition, climatic and edaphic variables were the main contributors to GHG and NH 3 emissions. In conclusion, it is appropriate to promote the use of PM in the MLYR and SC regions, because of the ability to increase yields while reducing environmental impacts (lower GHGI and NH 3 emissions). The findings provide a theoretical basis for sustainable agricultural production of PM potatoes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Monoculture is widely practiced to increase crop productivity, but long-term adaptation has drawbacks as it increases the depletion of soil nutrients and reduces soil quality, especially in dryland areas. Conversion from traditional maize monoculture to intercropping improves sustainable production. However, maize/peanut intercropping, especially rotation of planting strips impacts of maize/peanut intercropping in dryland on carbon (C) budgets and economic benefits remain unclear. In this study, a 5-year field experiment was conducted to evaluate the influence of maize/peanut intercropping with rotation of planting strips on soil health, indirect CO 2 -eq greenhouse gas emissions, and ecosystem C inputs. Four intercropping treatments viz. maize monoculture, peanut monoculture, maize/peanut intercropping, and maize/peanut rotation-intercropping were tested from 2018 to 2022. Maize/peanut rotation intercropping significantly improved the land equivalent ratio followed by intercropping and monoculture. Rotation-intercropping also improved economic benefits over intercropping and monoculture which were mainly associated with increased peanut yield where the border rows contributed the maximum, followed by the middle rows. Moreover, rotation-intercropping significantly increased the soil organic C and nitrogen (N) content. Rotation-intercropping decreased indirect CO 2 -eq greenhouse gas emissions and ecosystem C inputs by 3.11% and 18.04%, whereas increased ecosystem C outputs and net ecosystem C budget by 10.38% and 29.14%, respectively, over the average of monoculture. On average for intercropping and monoculture, rotation-intercropping increased ecosystem C emission efficiency for economic benefits by 51.94% and 227.27% in 2021 and 2022, respectively, showing the highest C utilization efficiency than other treatments. In the long run, maize/peanut rotation-intercropping can be practiced in dryland agriculture to achieve sustainable agriculture goals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Excessive irrigation and nitrogen application have long seriously undermined agricultural sustainability in the North China Plain (NCP), leading to declining groundwater tables and intensified greenhouse gas (GHG) emissions. Developing low-input management practices that meet the growing food demand while reducing environmental costs is urgently needed. Here, we developed a novel nitrogen management strategy for a typical winter wheat-summer maize rotation system in the NCP under limited irrigation (wheat sowing irrigation only (W0) or sowing and jointing irrigation (W1)) and low nitrogen input (360 kg N ha -1 , about 70 % of traditional annual nitrogen input). Novel nitrogen management strategy promoted efficient nitrogen fertilizer uptake and utilization by both crops via optimization of nitrogen fertilizer allocation between the two crops, i.e., increasing nitrogen inputs to wheat (from 180 to 240 kg N ha -1 ) while reducing nitrogen inputs to maize (from 180 to 120 kg N ha -1 ). Three-year field study demonstrated that integrated management practices combining novel nitrogen management strategy with limited irrigation increased annual yields and PFPN by 1.9-5.7 %, and reduced TGE by 55-68 kg CO 2 -eq ha -1 and GHGI by 2.2-10.3 %, without any additional cost. Our results provide agricultural operators and policymakers with practical and easy-to-scalable integrated management strategy, and offer key initiative to promote grain production in the NCP towards agriculture sustainable intensification with high productivity and efficiency, water conservation and emission reduction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Certain nations have opted for stimulus-based regulations to curtail emissions, build a liveable, environmentally friendly setting, and work towards aspirational mitigation targets. New Zealand (NZ) prefers an Emission Trading Scheme (ETS) to taxation, mitigating emissions on one hand while retaining incentives for economic growth on the other. As a result, NZ has initiated a legal framework since 2008 to allow its economic sectors to engage in ETS and minimize emissions. Yet, selecting the appropriate sectors and effectively adjusting sector-specific regulations remain critical and complex challenges in the global design of ETS since both excessive and insufficient intervention can lead to inefficiencies in the system's functioning. Therefore, this study begins validating the NZ ETS's abatement potential regarding sectoral carbon intensity by executing the double machine learning techniques, consolidating the ETS efficacy that has robustly mitigated sectoral carbon intensity in NZ during 2006-2020. However, this conclusion seems invalid at the disaggregated level when focusing on forward-backward linkages, where NZ's input-output tables furnish a compelling scenario of sectoral dependencies and the products (residuals) they provide. Altogether, the regulatory requirements are either too strict or too lax, leaving out five of the 24 (as a whole) key sectors. Rather, the ETS could be powerful, providing these five key sectors are well tackled, necessitating a reformulation of the ongoing ETS regulatory regime., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Saline water has proven to be one of the alternative sources of freshwater for agricultural irrigation in water-scarce areas. However, the changes in farmland ecology caused by saline water irrigation remain unclear. In this study, six irrigation water salinities (CK: 1.3 dS m -1 , S1: 3.4 dS m -1 , S2: 7.1 dS m -1 , S3: 10.6 dS m -1 , S4: 14.1 dS m -1 , S5: 17.7 dS m -1 ) were set in a three-year (2019, 2021-2022) experiment to investigate their effects on soil environment and greenhouse gas emissions in cotton fields under long-term saline water irrigation. Results show that soil salinity in the same layer increased as increasing water salinity. Soil moisture of S3-S5 increased significantly by 4.99-12.94%. There was no significant difference in soil organic matter content between CK and S1. Saline water irrigation increased soil ammonium nitrogen content by 0.57-49.26%, while decreasing nitrate nitrogen content by 1.43-32.03%. Soil CO 2 and N 2 O emissions and CH 4 uptake were lower in S1-S5 than in CK at different cotton growth stages. In addition, saline water irrigation reduced the global warming potential by 6.93-53.86%. A structural equation model was developed to show that soil salinity, moisture, and ammonium nitrogen content were negatively correlated with global warming potential, while organic matter and nitrate nitrogen had positive effects on global warming potential. Considering the comprehensive perspectives of gas emissions and cotton yield, irrigation water with salinity less than 10.6 dS m -1 could effectively reduce greenhouse gas emissions from cotton fields while maintaining stable cotton yields in the experimental area and similar region., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

While research on carbon productivity is growing rapidly, the role of structural change in green transition remains unexplored due to the scarcity of firm-level emission data. This study addresses this gap by utilizing unique register-based greenhouse gas emission data from Finland's energy-intensive manufacturing firms for 2000-2019. Applying a structural change productivity decomposition, we break down the sector's carbon productivity and green total factor productivity into four components: contributions from non-switching continuing firms, industry-switching continuing firms, the effects of entry and exit, and resource allocation. The findings highlight the important role of structural change in the sector's productivity. Non-switching continuing firms emerged as the key drivers of both carbon and green total factor productivity growth. The contribution of entry and exit was negative during the financial crisis, while inefficient resource allocation significantly hindered productivity growth throughout the study period. These findings emphasize the importance of public subsidies targeted at environmentally efficient firms to enhance their competitiveness under challenging market conditions. Furthermore, the establishment of a stable yet positive carbon price would incentivize less-productive firms to adopt environmentally friendly technologies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Cities occupy a central position in addressing climate change and promoting sustainable regional development. Synergistic control of urban gas emissions at the city level is one of the main issues typically explored. The confounding effect and the interactions between the urban indicators of population and area have been ignored in previous studies. In this study, we examined the spatial distribution characteristics and synergy between greenhouse gases (CO 2 ) and air pollutants (SO 2 and NO X ) using spatial population and gas emission data. By upgrading the city clustering algorithm (CCA), we established a method for defining active areas of gas emissions (spatial element-coupled clustering, SECC) and identified active areas of gas emissions in China. In this study, we created a research framework that can simultaneously consider the effects of population and area, as well as the possible interactions between these indicators in active areas. The superlinear scaling relationship between the above three gases was revealed at the active zone level, and the existence of synergy between the emission patterns of the three gases was confirmed. Via further model application, we measured the synergistic efficiency of the three gases. It was found that for every 1% increase in SO 2 and NO X in an active zone, CO 2 increases by 0.86%. In this study, we explored a new perspective and approach to explain the synergy between greenhouse gases and air pollutants. This is essential to promote national competition among cities to achieve synergistic control of CO 2 and local air pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Controlled-release urea application and straw incorporation have been conducted in recent years as environmental-friendly and sustainable farming strategies, but the long-term effects of controlled-release urea application and combination with straw on the dryland maize yield, soil fertility and the environment under future climate scenarios remain unclear. Hence, based on a six-year field experiment, four treatments were used to calibrate and validate the DeNitrification-DeComposition (DNDC) model, including non-nitrogen (CK), split applications of conventional urea (UR), single basal application of conventional urea and controlled-release urea at a ratio of 2:1 (CU), and CU combined with straw (CUS). Subsequently, coupled the well-validated model with future climate to evaluate suitable agricultural production practices under two shared socioeconomic pathways (SSP)-SSP245 and SSP585. The validation results indicated a good fit between the simulated and observed data of greenhouse gas emissions, soil organic carbon (SOC) contents and maize yields. With the anticipation of warmer temperatures and increased precipitation in the future, the yields of UR, CU, and CUS treatment significantly rose. Under SSP585 scenario, the positive impacts of CU treatment on maize yields reduced after the 2050s, exhibiting an average decline of 12.03%. Compared with the UR treatment, the CU treatment markedly reduced cumulative N 2 O emissions, and both treatments maintained the original state of SOC storages in the 2030s, furthermore, the CUS treatment reduced N 2 O emissions by 47.10%, 35.07%, 23.80% and 10.04% in the 2030s, 2050s, 2070s and 2090s, respectively. SOC storages for the CUS treatment gradually increased with an average of 464.58, 350.22, 250.87 and 177.75 kg C ha -1 y -1 for two SSP scenarios in the 2030s, 2050s, 2070s and 2090s, which excellently offset the CO 2 equivalent of emissions caused by N 2 O emissions. Therefore, in dryland maize production, combined controlled-release urea with straw incorporation could achieve the best comprehensive effect among increase of yield, improvement of SOC storages and alleviation of greenhouse gas emissions under future climate scenario., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Inland shallow lakes are recognized as an important source of greenhouse gases (GHGs), and their contribution is expected to increase due to global eutrophication. The generation and release of GHGs involved multiple variables, leading to many uncertain potential factors. This study examined the emission characteristics of GHGs at the water-air interface in 12 shallow lakes categorized into four eutrophic levels in the Yangtze River basin. The average emission rates of CH 4 , CO 2 and N 2 O were 1.55, 3.43, 18.13 and 30.47 mg m -2 h -1 , 4.12, 14.64, 25.11 and 69.84 mg m -2 h -1 , and 0.2, 0.25, 0.43 and 0.79 mg m -2 day -1 in the oligotrophic, mesotrophic, eutrophic and hypereutrophic lakes, respectively. There were significant correlations between eutrophic levels and the emission rates of CH 4 and CO 2 (p < 0.05). Redundancy analysis and Mantel test were conducted to further examine the key factors influencing carbon emissions from eutrophic water. It was found that the presence of algae and nutrients in the overlying water played a crucial role in the release of GHGs, indicating the importance of ecosystem productivity in the carbon budget of the lake. In order to assess the bioavailability of organic matter, a new indicator called R (P/H) was proposed. This indicator represents the ratio of protein and humus-like components, which were obtained through EEMs-PARAFAC modeling. The relationship between R (P/H) and CH 4 was found to be exponential (R 2  = 0.90). Additionally, R (P/H) showed a linear relationship with CO 2 and N 2 O (R 2  = 0.68, R 2  = 0.75). Therefore, it is crucial to consider R (P/H) as an important factor in accurately estimating global GHG emission fluxes in the future, especially with advancements in the database., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

China plays a crucial role in responding to global climate change. Provinces are the main sources of energy consumption and greenhouse gas emissions in China's economic and social development. However, it is still unclear how to achieve dual-carbon goals by formulating and implementing local policies to adapt to climate change. In this study, we take Zhejiang Province in China as the research object, based on the LEAP (Low Emissions Analysis Platform) model to construct four social scenarios under different policies, comprehensively considering regional economic characteristics, population, and energy consumption patterns. The results show that to achieve Zhejiang Province's goal of carbon peaking by 2030 while maintaining steady economic growth, additional measures are required to reduce energy consumption intensity or improve the power generation structure. Otherwise, energy demand will increase to 228.06 million tonnes of coal equivalent and carbon emissions will be 487.76 million tonnes in 2050. Moreover, developing clean energy and promoting CCUS technology can continuously reduce carbon emissions to 293.59 and 210.76 million tonnes respectively. The economic viability of CCUS power generation is contingent upon the development of carbon taxes in the future. Once the growth rate reaches 7.2%, power cost will be 167.77 billion RMB and CCUS will become economically advantageous in 2050., Competing Interests: Declaration of competing interest The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Lakes serve as vital reservoirs of dissolved organic matter (DOM) and play pivotal roles in biogeochemical carbon cycles. However, the sources and compositions of DOM in freshwater lakes and their potential effects on lake sediment carbon pools remain unclear. In this study, seven inflowing rivers in the Lake Taihu basin were selected to explore the potential effects of multi-source DOM inputs on the stability of the lake sediment carbon pool. The results showed the high concentrations of dissolved organic carbon in the Lake Taihu basin, accompanied by a high complexity level. Lignins constituted the majority of DOM compounds, surpassing 40% of the total, while the organic carbon content was predominantly composed of humic acids (1.02-3.01 g kg -1 ). The high amounts of lignin oxidative cleavage led to CHO being the main molecular structure in the DOM of the seven rivers. The carbon constituents within the sediment carbon reservoir exhibited a positive correlation with dissolved CH 4 and CO 2 , with a notable emphasis on humic acid and dissolved CH 4 (R 2  = 0.86). The elevated concentration of DOM, coupled with its intricate composition, contributed to the increases in dissolved greenhouse gases (GHGs). Experiments showed that the mixing of multi-source DOM can accelerate the organic carbon mineralization processes. The unit carbon emission efficiency was highest in the mixed group, reaching reached 160.9 μmol∙C g -1 , which also exhibited a significantly different carbon pool. The mixed decomposition of DOM from different sources influenced the roles of the lake carbon pool as source and sink, indicating that the multi-source DOM of this lake basin was a potential driving factor for increased carbon emissions. These findings have improved our understanding of the sources and compositions of DOM in lake basins and revealed their impacts on carbon emissions, thereby providing a theoretical basis for improving assessments of lake carbon emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Optimization of crop structure is an efficient way to reduce greenhouse gas (GHGs) from agriculture production. However, carbon footprint have rarely been incorporated into previous planting structure optimization models due to the challenges of assessing the spatial and temporal distribution of agricultural carbon footprint for multiple crops in irrigated districts. In addition, previous planting structure models suffered from strong subjectivity in objective function determination, and the obtained non-dominated solution set offered difficulties to decision-makers in selecting specific implementation options. To fill such gaps, an integrated accounting-assessment-optimization-decision making (AAODM) approach was proposed, which remedies the shortcomings of previous crop planting structure optimization models in carbon footprint mitigation, and overcomes the subjectivity of objective function determination and the difficulty in selecting specific implementation options. Firstly, life cycle assessment (LCA) method was used to account for the multi-year agricultural carbon footprints of multiple crops in the irrigation district. The optimization objective functions of planting structure optimization models can then be determined based on the assessment method of carbon footprint influencing factors. Next, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was used to generate a non-dominated solution set of the optimization model. The optimal planting structure can be finally obtained based on decision making methods by determining the maximum harmonic mean (HM) and knee points (KPs) of the non-dominated solution set. The developed AAODM approach was then applied to a case study of agricultural crop management in Bayan Nur City, China. The results showed that the level of economic development was a key factor influencing the increase in carbon footprint in Bayan Nur City over the past 20 years. The regulation of the level of economic development would significantly influence the agricultural carbon footprint in Bayan Nur City. Moreover, two optimal crop cultivation patterns were provided for decision-makers by selecting solutions from the Pareto front with decision making methods. The comparison results with other methods showed that the solutions obtained by NSGA-II were superior to MOPSO in terms of carbon reduction. The developed AAODM approach for agricultural GHG mitigation could help agricultural production systems in achieving low carbon emissions and high efficiency., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO 2 e) in 2000 to 77.568 Mt CO 2 e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively. • GHG emissions from livestock in cities of the YRB continued to rise from 2000 to 2021. • GHG emissions per unit of GDP of livestock shown a downward trend. • Analyzing parameter of factors from spatiotemporal aspect by using GTWR model. • Probability of GHG emission transfer in urban livestock was spatially dependent. [ABSTRACT FROM AUTHOR]

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]