Investing in mini-livestock production for food security and carbon neutrality in China.

Future food farming technology faces challenges that must integrate the core goal of keeping the global temperature increase within 1.5 °C without reducing food security and nutrition. Here, we show that boosting the production of insects and earthworms based on food waste and livestock manure to provide food and feed in China will greatly contribute to meeting the country's food security and carbon neutrality pledges. By substituting domestic products with mini-livestock (defined as earthworms and insects produced for food or feed) protein and utilizing the recovered land for bioenergy production plus carbon capture and storage, China's agricultural sector could become carbon-neutral and reduce feed protein imports to near zero. This structural change may lead to reducing greenhouse gas emissions by 2,350 Tg CO2eq per year globally when both domestic and imported products are substituted. Overall, the success of mini-livestock protein production in achieving carbon neutrality and food security for China and its major trading partners depends on how the substitution strategies will be implemented and how the recovered agricultural land will be managed, e.g., free use for afforestation and bioenergy or by restricting this land to food crop use. Using China as an example, this study also demonstrates the potential of mini-livestock for decreasing the environmental burden of food production in general.

Multiple spatial scales of bacterial and fungal structural and functional traits affect carbon mineralization.

Studying the functional heterogeneity of soil microorganisms at different spatial scales and linking it to soil carbon mineralization is crucial for predicting the response of soil carbon stability to environmental changes and human disturbance. Here, a total of 429 soil samples were collected from typical paddy fields in China, and the bacterial and fungal communities as well as functional genes related to carbon mineralization in the soil were analysed using MiSeq sequencing and GeoChip gene microarray technology. We postulate that CO2 emissions resulting from bacterial and fungal carbon mineralization are contingent upon their respective carbon consumption strategies, which rely on the regulation of interactions between biodiversity and functional genes. Our results showed that the spatial turnover of the fungal community was 2-4 times that of the bacterial community from hundreds of meters to thousands of kilometres. The effect of spatial scale exerted a greater impact on the composition rather than the functional characteristics of the microbial community. Furthermore, based on the establishment of functional networks at different spatial scales, we observed that both bacteria and fungi within the top 10 taxa associated with carbon mineralization exhibited a prevalence of generalist species at the regional scale. This study emphasizes the significance of spatial scaling patterns in soil bacterial and fungal carbon degradation functions, deepening our understanding of how the relationship between microbial decomposers and soil heterogeneity impacts carbon mineralization and subsequent greenhouse gas emissions.

Methanogenic Potential of Sewer Microbiomes and Its Implications for Methane Emission.

The sewer system, despite being a significant source of methane emissions, has often been overlooked in current greenhouse gas inventories due to the limited availability of quantitative data. Direct monitoring in sewers can be expensive or biased due to access limitations and internal heterogeneity of sewer networks. Fortunately, since methane is almost exclusively biogenic in sewers, we demonstrate in this study that the methanogenic potential can be estimated using known sewer microbiome data. By combining data mining techniques and bioinformatics databases, we developed the first data-driven method to analyze methanogenic potentials using a data set containing 633 observations of 53 variables obtained from literature mining. The methanogenic potential in the sewer sediment was around 250-870% higher than that in the wet biofilm on the pipe and sewage water. Additionally, k-means clustering and principal component analysis linked higher methane emission rates (9.72 ± 51.3 kgCO2 eq m-3 d-1) with smaller pipe size, higher water level, and higher potentials of sulfate reduction in the wetted pipe biofilm. These findings exhibit the possibility of connecting microbiome data with biogenic greenhouse gases, further offering insights into new approaches for understanding greenhouse gas emissions from understudied sources.

Aging Increases Global Annual Food Greenhouse Gas Emissions up to 300 Million Tonnes by 2100.

The dietary preferences of the elderly population exhibit distinct variations from the overall averages in most countries, gaining increasing significance due to aging demographics worldwide. These dietary preferences play a crucial role in shaping global food systems, which will result in changed environmental impacts in the future such as greenhouse gas (GHG) emissions. We present a quantitative evaluation of the influence of population aging on the changes in GHG emissions from global food systems. To achieve this, we developed regional dietary coefficients (DCs) of the elderly based on the Global Dietary Database (GDD). We then reconciled the GDD with the dataset from the Food and Agriculture Organization of the United Nations (FAO) to calculate the food GHG emissions of the average population in each of the countries. By applying the DCs, we estimated the national food GHG emissions and obtained the variations between the emissions from aged and average populations. We employed a modified version of the regional integrated model of climate and the economy model (RICE) to forecast the emission trends in different countries based on FAO and GDD data. This integrated approach allowed us to evaluate the dynamic relationships among aging demographics, food consumption patterns, and economic developments within regions. Our results indicate that the annual aging-embodied global food GHG emissions will reach 288 million tonnes of CO2 equivalent (Mt CO2e) by 2100. This estimation is crucial for policymakers, entrepreneurs, and researchers as it provides insights into a potential future environmental challenge and emphasizes the importance of sustainable food production and consumption strategies to GHG emission mitigations associated with aging dietary patterns.

Replacing Plastics with Alternatives Is Worse for Greenhouse Gas Emissions in Most Cases.

Plastics are controversial due to their production from fossil fuels, emissions during production and disposal, potential toxicity, and leakage to the environment. In light of these concerns, calls to use less plastic products and move toward nonplastic alternatives are common. However, these calls often overlook the environmental impacts of alternative materials. This article examines the greenhouse gas (GHG) emission impact of plastic products versus their alternatives. We assess 16 applications where plastics are used across five key sectors: packaging, building and construction, automotive, textiles, and consumer durables. These sectors account for about 90% of the global plastic volume. Our results show that in 15 of the 16 applications a plastic product incurs fewer GHG emissions than their alternatives. In these applications, plastic products release 10% to 90% fewer emissions across the product life cycle. Furthermore, in some applications, such as food packaging, no suitable alternatives to plastics exist. These results demonstrate that care must be taken when formulating policies or interventions to reduce plastic use so that we do not inadvertently drive a shift to nonplastic alternatives with higher GHG emissions. For most plastic products, increasing the efficiency of plastic use, extending the lifetime, boosting recycling rates, and improving waste collection would be more effective for reducing emissions.

Microbial Sources and Sinks of Nitrous Oxide during Organic Waste Composting.

Composting is widely used for organic waste management and is also a major source of nitrous oxide (N2O) emission. New insight into microbial sources and sinks is essential for process regulation to reduce N2O emission from composting. This study used genome-resolved metagenomics to decipher the genomic structures and physiological behaviors of individual bacteria for N2O sources and sinks during composting. Results showed that several nosZ-lacking denitrifiers in feedstocks drove N2O emission at the beginning of the composting. Such emission became negligible at the thermophilic stage, as high temperatures inhibited all denitrifiers for N2O production except for those containing nirK. The nosZ-lacking denitrifiers were notably enriched to increase N2O production at the cooling stage. Nevertheless, organic biodegradation limited energy availability for chemotaxis and flagellar assembly to restrain nirKS-containing denitrifiers for nitrate reduction toward N2O sources but insignificantly interrupt norBC- and nosZ-containing bacteria (particularly nosZ-containing nondenitrifiers) for N2O sinks by capturing N2O and nitric oxide (NO) for energy production, thereby reducing N2O emission at the mature stage. Furthermore, nosZII-type bacteria included all nosZ-containing nondenitrifiers and dominated N2O sinks. Thus, targeted strategies can be developed to restrict the physiological behaviors of nirKS-containing denitrifiers and expand the taxonomic distribution of nosZ for effective N2O mitigation in composting.

Consequences of intense drought on CO2 and CH4 fluxes of the reed ecosystem at Lake Neusiedl.

Reed (Phragmites australis) dominated wetlands are commonly known as strong carbon (C) sinks due to the high productivity of the reed plant and C fixation in the wetland soil. However, little is known about the effects of drought on reed-dominated wetlands and the possibility of Pannonian reed ecosystems being a source of greenhouse gases (GHG). The drought at Lake Neusiedl had a particular impact on the water level, but also had consequences for the reed belt. Therefore, we investigated the drought-influenced C fluxes and their drivers in the reed ecosystem of this subsaline lake over a period of 4.5 years (mid-2018 to 2022). We applied eddy covariance technique to continuously quantify the vertical turbulent GHG exchange between reed belt & atmosphere and used vegetation indices to account for reed growth. Methane emissions decreased by 76% from 9.2 g CH4-C m-2a-1 (2019) to 2.2 g CH4-C m-2 a-1 (2022), which can be explained by the falling water level, the associated drying out of the reed belt and its consequences. Carbon dioxide emissions initially decreased by 85% from 181 g CO2-C m-2 a-1 (2019) to 27 g CO2-C m-2 a-1 (2021), but then increased to twice the 2019 level in 2022 (391 g CO2-C m-2 a-1). Due to the drying reed belt, the reed initially grew into formerly water-covered areas within the reed belt, especially in 2021, leading to higher photosynthesis through 2021. This development stopped and even reversed in 2022 as a consequence of the sharp decrease in sediment water content from about 65 to 32 Vol-% in mid-2022. Overall, drought led to a decoupling of the reed ecosystem from the open lake area and developed the wetland into a strong C source.

Investigating the characteristics of combustible fraction of legacy waste: A study on energy recovery potential and GHG emission quantification.

In India, majority of the generated municipal solid waste (MSW) was dumped in poorly managed landfills and dumpsites over the past decades and is an environmental and health hazard. Landfill mining is a promising solution to reclaim these sites along with the recovery of resources (materials and energy). During landfill mining operations, the combustible fraction is one of the major components recovered and needs proper management for maximizing resource recovery. For the identification of appropriate resource recovery options, knowledge of the physicochemical characteristics is required. The present study aims to assess the depth-wise change in the composition of legacy waste and the physicochemical characteristics of the combustible fraction. Furthermore, a material flow analysis considering the incineration of combustible fraction was performed to estimate the energy generation potential and the associated greenhouse gas (GHG) emissions. The results of the compositional analysis of dry legacy waste revealed that the fine fraction (<4 mm soil-like material) was dominating with a share of 36%. The depth-wise analysis showed a decrease in the calorific value with increasing landfill depth, while no specific trend was observed for the other parameters analyzed, including proximate and ultimate analysis, and chlorine content. The material flow analysis performed for 100 tonnes of wet legacy waste indicated that 52 tonnes of waste is combustible fraction. The GHG emissions through incineration of one tonne of dry combustible fraction would be 1389 kg CO2-eq, with 1125 kWh of electrical energy generation potential.

Effects of cashew nut shell extract and monensin on in vitro ruminal fermentation, methane production, and ruminal bacterial community.

The objective of this study was to evaluate the effects of cashew nut shell extract (CNSE) and monensin on ruminal in vitro fermentation, CH4 production, and ruminal bacterial community structure. Treatments were as follows: control (CON, basal diet without additives); 2.5 µM monensin (MON); 0.1 mg CNSE granule/g DM (CNSE100); and 0.2 mg CNSE granule/g DM (CNSE200). Each treatment was incubated with 52 mL of buffered ruminal content and 500 mg of total mixed ration for 24 h using serum vials. The experiment was performed as a complete randomized block design with 3 runs. Run was used as a blocking factor. Each treatment had 5 replicates, in which 2 were used to determine nutrient degradability, and 3 were used to determine pH, NH3-N, volatile fatty acids, lactate, total gas, CH4 production, and bacterial community composition. Treatment responses for all data, excluding bacterial abundance, were analyzed with the GLIMMIX procedure of SAS v9.4. Treatment responses for bacterial community structure were analyzed with a PERMANOVA test run with the R package vegan. Orthogonal contrasts were used to test the effects of (1) additive inclusion (ADD: CON vs. MON, CNSE100, and CNSE200); (2) additive type (MCN: MON vs. CNSE100 and CNSE200); and (3) CNSE dose (DOS: CNSE100 vs. CNSE200). We observed that pH, acetate, and acetate:propionate ratio in the CNSE100 treatment were lower compared with CNSE200, and propionate in the CNSE100 treatment was greater compared with CNSE200. Compared with MON, CNSE treatments tended to decrease total lactate concentration. Total gas production of CON was greater by 2.63% compared with all treatments, and total CH4 production was reduced by 10.64% in both CNSE treatments compared with MON. Also, compared with MON, in vitro dry matter degradabilities in CNSE treatments were lower. No effects were observed for NH3-N or in vitro neutral detergent fiber degradability. Finally, the relative abundances of Prevotella, Treponema, and Schwartzia were lower, whereas the relative abundances of Butyrivibrio and Succinivibrio were greater in all treatments compared with CON. Overall, the inclusion of CNSE decreased CH4 production compared with MON, making CNSE a possible CH4 mitigation additive in dairy cattle diets.

Ecological effect of microplastics on soil microbe-driven carbon circulation and greenhouse gas emission: A review.

Soil organic carbon (SOC) pool, the largest part of terrestrial ecosystem, controls global terrestrial carbon balance and consequently presented carbon cycle-climate feedback in climate projections. Microplastics, (MPs, <5 mm) as common pollutants in soil ecosystems, have an obvious impact on soil-borne carbon circulation by affecting soil microbial processes, which play a central role in regulating SOC conversion. In this review, we initially presented the sources, properties and ecological risks of MPs in soil ecosystem, and then the differentiated effects of MPs on the component of SOC, including dissolved organic carbon, soil microbial biomass carbon and easily oxidized organic carbon varying with the types and concentrations of MPs, the soil types, etc. As research turns into a broader perspective, greenhouse gas emissions dominated by the mineralization of SOC coming into view since it can be significantly affected by MPs and is closely associated with soil microbial respiration. The pathways of MPs impacting soil microbes-driven carbon conversion include changing microbial community structure and composition, the functional enzyme's activity and the abundance and expression of functional genes. However, numerous uncertainties still exist regarding the microbial mechanisms in the deeper biochemical process. More comprehensive studies are necessary to explore the affected footprint and provide guidance for finding the evaluation criterion of MPs affecting climate change.

Half substitution of mineral N with fish protein hydrolysate enhancing microbial residue C and N storage and climate benefits under high straw residue return.

The widespread utilization of straw return was a popular practice straw disposal for highly intensive agriculture in China, which has brought about some negative impacts such as less time for straw complete biodegradation, aggravation of greenhouse gas evolution, and lower efficient of carbon accumulation. It was urgent to find an eco-friendly N-rich organic fertilizer instead of mineral N as activator to solve the above problems and lead a carbon accumulation in long tern management. Besides, microbial necromass was considered as a crucial contributor to persistent soil carbon (C) and nitrogen (N) pool. How organic fertilizer activators influence microbial residue under different amount of crop residues input remained unclear. Thus, soils incorporating moderate and high rate of rice straw residue with additions of half and full of organic activators (fish protein hydrolysates vs. manure) were incubated for measuring carbon dioxide (CO2) and nitrous oxide (N2O) emission, microbial community and necromass. It was found that soil CO2 emission was rapidest during the first 13 days of straw decomposition but remained lowest in the treatments of 50% mineral N substituted by fish protein hydrolysate. There were that 81%-89% of total CO2 release and 59%-65% of total N2O emission occurred within 60 days of incubation period, and bacterial community and nitrate positively affected soil CO2 and N2O release respectively. Straw incorporation amount and organic activator application interactively influenced soil CO2 emission but not affected soil N2O emission. After 360 days of incubation, the difference of bacterial necromass was noticeable but fungal necromass remained almost unaltered across all treatments. All treatments showed generally comparable contribution of microbial necromass N to the total N pool. The treatment of 50% mineral N substituted by fish protein hydrolysate under high rate of straw input (HSF50) promoted the highest proportion of microbial necromass C in soil organic C because of alleviating N limitation for microorganisms. Finally, HSF50 was recommended as an eco-friendly strategy for enhancing microbial necromass C and N storage and climate benefits in agroecosystems.

Decision tree-based approach to extrapolate life cycle inventory data of manufacturing processes.

Life cycle assessment (LCA) plays a crucial role in green manufacturing to uncover the critical aspects for alleviating the environmental burdens due to manufacturing processes. However, the scarcity of life cycle inventory (LCI) data for the manufacturing processes is a considerable challenge. This paper proposes a novel approach to extrapolate LCI data of manufacturing processes. Taking advantage of LCI data in the Ecoinvent datasets, decision tree-based supervised machine learning models, namely decision tree, random forest, gradient boosting, and adaptive boosting, have been developed to extrapolate the data of GHG emissions, i.e., carbon dioxide, nitrous oxide, methane, and water vapor. Initially, a correlation analysis was conducted to derive the most influential factors on GHG quantities resulting from manufacturing activities. First, the collected data have been preprocessed and split into train and test sets (70% and 30%, respectively). Second, a five-fold cross-validation method was applied to tune the hyperparameters of the models. Then, the models were re-trained using the best hyperparameters and evaluated using the test set. The results reveal that the Gradient Boosting model has a superior predictive performance for extrapolating the GHG emission data, with average coefficients of determination (R2) on the test set <0.95. Moreover, the model predictions involve relatively low values of the average root mean squared error and an average mean percentage of error on the test set. The correlation and feature importance analyses emphasized that the workpiece material and manufacturing technology have a considerable effect on natural resource consumption, i.e., energy, material, and water inflows into the process. Meanwhile, energy consumption, water usage, and raw aluminum depletion were the most influential factors in GHG emissions. Eventually, a case study to extrapolate the inflows and the outflows for new manufacturing activities has been conducted using the validated models. The proposed GraBoost model provides a computational supplementary approach to estimate and extrapolate the GHG emissions for different manufacturing processes when LCI data are incomplete or don't exist within LCI databases.

Aquatic macrophytes mitigate the conflict between nitrogen removal and nitrous oxide emissions during tailwater treatments.

Tailwater from wastewater treatment plants (WWTP) usually reduces the nitrogen (N) removal efficiency while simultaneously elevates nitrous oxide (N2O) emissions due to the low carbon-nitrogen (C/N) ratio. Conflicts between N removal and N2O emissions require mitigation by selecting appropriate aquatic plants for tailwater treatment. In this study, a simulated tailwater mesocosm was established using three aquatic plants including Eichhornia crassipes, Myriophyllum aquaticum and Pistia stratiotes. Results of the 15N isotope mass balance analysis revealed the considerable contributions from plant uptake and benthic retention to overall N removal. It was demonstrated that the N assimilation efficiency of aquatic plants depended more on the root-shoot ratio rather than on growth rate. Furthermore, aquatic plants indirectly influence microbial N removal and N2O emissions by altering the water quality parameters. Additionally, aquatic plants could regulate the N transformation through affecting the structure of bacterial community, including microbial abundance, diversity and association networks. Overall, the study underlined the enormous capacities of E. crassipes and P. stratiotes for N uptake and N2O mitigation in tailwater treatment. Utilizing these two aquatic plants for phytoremediation may help mitigate the conflict between tailwater purification and N2O production.

Strip clear-cutting transformations increase soil N2O emissions in abandoned Moso bamboo forests.

Forest transformation can markedly impact soil greenhouse gas emissions and soil environmental factors. Due to increasing labor costs and declining bamboo prices, the abandonment of Moso bamboo forests is sharply escalating in recent years, which weakens the carbon sequestration capacity and decreases the ecological function of forests. To improve the ecological quality of abandoned Moso bamboo forests, transformations of abandoned bamboo forests have occurred. However, the impact of such transformations on N2O emissions remains elusive. To bridge the knowledge gap, we conducted a 23-month field experiment to compare the effects of various forest management practices on soil N2O emissions and soil environmental factors in abandoned Moso bamboo forests in subtropical China. These practices included uncut abandonment as a control, intensive management, three intensities (light, moderate, and heavy) of strip clear-cutting with replanting local tree species, and clear-cutting with replanting transformation. During the experimental period, the mean soil N2O flux in abandoned Moso bamboo forests was 13.2 ± 0.1 µg m-2 h-1, representing a 44% reduction compared to intensive management forests. In comparison to the uncut control, light, moderate, and heavy strip clear-cutting and clear-cutting transformations increased soil N2O emission rates by 20%, 43%, 64%, and 94%, respectively. Soil temperature (69-71%), labile C (2-6%) and N (3-8%) were the main factors that explain N2O emissions following the transformation of abandoned Moso bamboo forests. Additionally, replanting could decrease soil N2O emissions by increasing the contribution of soil moisture. Overall, the light strip clear-cutting transformation is suggested to convert abandoned Moso bamboo forests to mitigate N2O emissions.

Low-carbon city construction, spatial spillovers and greenhouse gas emission performance: Evidence from Chinese cities.

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.

The recovery potential and utilization pathway of chemical energy from wastewater pollutants during wastewater treatment in China.

Research on the potential for chemical energy recovery and the optimization of recovery pathways in different regions of China is still lacking. This study aimed to address this gap by evaluating the potential and optimize the utilization pathways for chemical energy recovery in various regions of China for achieving sustainable wastewater treatment. The results showed that the eastern and northeastern regions of China exhibited higher chemical energy levels under the existing operating conditions. Key factors affecting chemical energy recovery included chemical oxygen demand removal (ΔCOD), treatment scale, and specific energy consumption (µ) of wastewater treatment plants (WWTPs). Furthermore, the average improvement in the chemical energy recovery rate with an optimized utilization pathway was approximately 40% in the WWTPs. The use of the net-zero energy consumption (NZE) model proved effective in improving the chemical energy recovery potential, with an average reduction of greenhouse gas (GHG) emissions reaching next to 95% in the investigated WWTPs.

Enhancing supply chain relationships in the circular economy: Strategies for a green centralized supply chain with deteriorating products.

This article introduces a green centralized supply chain in a two-stage stochastic programming model using deteriorating products. The model reduces the cost of purchasing, transporting, storing, product recovery and shortages. This cuts down on greenhouse emission related to transportation, product recovery, and recycling programs. On the basis of this, we explore the utilization of the circular economy to the damages that could occur from used products. Furthermore, revenue sharing and quantity discount contracts are examined in the business models between the members of the supply chain and the external manufacturer. Demand is assumed to be uncertain, and scenarios are created to account this. The model specifies the optimal order quantities, transportation modes and contract terms that minimize costs and environmental impacts. Numerical examples analyze the trade-offs between economic and environmental objectives under different supply chain parameters. The results provide insights for circular supply chains that reconcile economic incentives with environmental responsibility for deteriorating product.

Modelling future climate effects on N2O emission and soil carbon storage in maize fields under controlled-release urea and straw incorporation.

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 N2O emissions, and both treatments maintained the original state of SOC storages in the 2030s, furthermore, the CUS treatment reduced N2O 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 CO2 equivalent of emissions caused by N2O 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.

The impact of fuel cell vehicles deployment on road transport greenhouse gas emissions through 2050: Evidence from 15 G20 countries.

As global concern over the negative impacts of global warming, primarily caused by using passenger vehicles (PVs), the transition to hydrogen fuel cell vehicles (HFCVs) is an essential alternative for reducing greenhouse (GHG) emissions. This research employs a bottom-up approach to analyze road vehicle fleet's GHG emissions. We calculated GHG emissions from PVs in 15 Group of Twenty (G20) countries based on four scenarios adopting the global HFCVs from 2024 to 2050. This paper introduces business-as-usual (BaU), moderate, aggressive, and non-HFCVs scenario. The results show that the aggressive scenario has the highest sales, estimated between 62,000 and 29.48 million vehicles by 2050, with global hydrogen market penetration rates 48.48%. Building on countries' respective national strategies, the findings highlight China and India as the leading markets for hydrogen demand, with Germany and Japan also showing significant interest. The aggressive scenario further demonstrates that transitioning from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), and HFCVs can significantly reduce annual GHG emissions. Ultimately, this study finds that the transition to HFCVs could reduce emissions by up to 67.09% by 2050.

Effects of coordinated regulation of water, nitrogen, and biochar on the yield and soil greenhouse gas emission intensity of greenhouse tomatoes.

Regulating the coupled relationship among water, nitrogen, and biochar is an effective strategy for increasing production and reducing emissions in greenhouse agriculture. However, a comprehensive evaluation model remains lacking. Toward this end, we aimed to evaluate the emission patterns of greenhouse gases and greenhouse tomato yield during the spring and autumn cultivation seasons as influenced by irrigation water use efficiency, nitrogen fertilizer partial productivity, and soil organic carbon (SOC). We applied three irrigation levels: 100% (W1), 80% (W2), and 60% (W3) of the reference crop evapotranspiration; three nitrogen application levels: 240, 192, and 144 kg ha-1, representing 100% (N1), 80% (N2), and 60% (N3) of the actual local application amount; and four biochar application gradients: B0, B1, B2, and B3 corresponding to 0, 30, 50, and 70 t ha-1, respectively. Interaction experiments were conducted based on the implementation the incomplete multifactorial design, using W1N1B0 as the control. The entropy weight method was used to calculate the main and sub-weights of the evaluation indicators. During the growing season, greenhouse gas emissions have a significant impact. The cumulative emissions of CO2, N2O, and CH4 from soil in spring are 24.4%, 42.18%, and 13.9% higher than those in autumn, respectively. Soil temperature was a key environmental factor influencing soil CO2 emissions, while soil moisture content and nitrogen fertilizer input efficiency were the main factors affecting soil N2O emissions, and the correlation between soil CH4 emissions and soil organic carbon content was most significant. Water-nitrogen-biochar interaction significantly affected yield and GHGI: adding biochar under the same water-nitrogen- and moderately deficient irrigation(W1) under the same nitrogen-biochar application modes increased yield and reduced GHGI. However, moderately reduced nitrogen application decreased(N2) both measures under the same water-biochar application mode. The VIKOR comprehensive evaluation method determined W2N2B2 as the most suitable water-nitrogen-biochar application mode for optimizing yield and GHGI. This study provides a theoretical basis for stable, low-carbon development in green-intensive agriculture.