Changes In Greenhouse Gas Emissions Research Articles

An optimal global biochar application strategy based on matching biochar and soil properties to reduce global cropland greenhouse gas emissions: findings from a global meta-analysis and density functional theory calculation

Biochar has been extensively utilized to amend soil and mitigate greenhouse gas (GHG) emissions from croplands. However, the effectiveness of biochar application in reducing cropland GHG emissions remains uncertain due to variations in soil properties and environmental conditions across regions. In this study, the impact of biochar surface functional groups on soil GHG emissions was investigated using molecular model calculation. Machine learning (ML) technology was applied to predict the responses of soil GHG emissions and crop yields under different biochar feedstocks and application rates, aiming to determine the optimum biochar application strategies based on specific soil properties and environmental conditions on a global scale. The findings suggest that the functional groups play an essential role in determining biochar surface activity and the soil’s capacity for adsorbing GHGs. ML was an effective method in predicting the changes in soil GHG emissions and crop yield following biochar application. Moreover, poor-fertility soils exhibited greater changes in GHG emissions compared to fertile soil. Implementing an optimized global strategy for biochar application may result in a substantial reduction of 684.25 Tg year−1 CO2 equivalent (equivalent to 7.87% of global cropland GHG emissions) while simultaneously improving crop yields. This study improves our understanding of the interaction between biochar surface properties and soil GHG, confirming the potential of global biochar application strategies in mitigating cropland GHG emissions and addressing global climate degradation. Further research efforts are required to optimize such strategies.Graphical

454 Evaluating the effects of grazing native rangeland on enteric emissions

Abstract Understanding beef cattle enteric emissions on extensive western U.S. rangeland systems is critical for implementing sustainable grazing practices that reduce greenhouse gas (GHG) emissions. These practices must also improve livestock and plant productivity and climate resiliency while maintaining or reducing production costs. However, enteric emissions of grazing cattle under different stocking rates and grazing management strategies are largely unknown for western U.S. rangelands. Thus, our objective was to evaluate the differences in enteric emissions of stocker steers grazing native rangeland. Yearling Angus steers (n = 127) were stratified by initial body weight (BW) to six groups, then randomly assigned to one of six pastures grazed from June to September 2023 at the South Dakota State University Cottonwood Field Station (Cottonwood, SD) as part of a long-term stocking rate trial (80+ yr). Each pasture was equipped with a GreenFeed (C-Lock Inc, Rapid City, SD) pasture system to measure individual animal CH4 and CO2 emissions for continuous grazing (CG) and rotational grazing (RG) strategies in three stocking rates (Light, Moderate, and Heavy, 0.32, 0.40, and 0.72 animal unit months, respectively) in a 2 x 3 factorial design. Differences in enteric emissions among stocking rate and grazing strategy were analyzed using a linear mixed effects model in R, using the lme4 package, with animal as a random effect, and a post-hoc contrast among treatments was assessed using the lsmeans package. Steer initial and final BW were similar (P > 0.05) among treatments. For CH4 emissions, there was a significant interaction between stocking rate and grazing strategy (P < 0.05). Specifically, CH4 emissions for moderate-RG (195 ± 4.3 g/d) were less than those from heavy-CG (221 ± 4.5 g/d) and light-RG (221 ± 4.7 g/d) over the study period (P < 0.05). For CO2 emissions, light-CG steers respired greater CO2 emissions (6892 ± 101 g/d) than heavy-RG (6398 ± 107 g/d; P < 0.05). All other treatment lsmeans were similar (P > 0.05) and intermediate to these treatment effects. The assessment of GHG emission values for cattle grazing native rangeland is essential for informing climate mitigation strategies, improving animal efficiency, and understanding changes in GHG emissions over production phases and across animal classes.

Perspectives on healthcare decarbonization through plant-rich dietary shifts: cases from the US, Austria and Taiwan

The reduction of meat consumption in health systems is a high-impact pathway for healthcare decarbonization. Effects including changes in greenhouse gas emissions are rarely calculated following interventions, such as the implementation of plant-forward menus in hospitals, and the results of these changes are rarely published in peer-reviewed literature. In this perspective, we discuss the decarbonization outcomes of plant-rich dietary shifts across five health systems worldwide, gathered from peer-reviewed and gray literature. In each case, the implementation of a plant-rich approach reduced food-related greenhouse gas emissions. Health co-benefits are also commonly reported. The measurement of greenhouse gas emissions of plant-rich dietary shifts in future health system interventions is encouraged, with the results published in peer-reviewed journals.

A Systems Engineering Approach to Decarbonizing Mining: Analyzing Electrification and CO2 Emission Reduction Scenarios for Copper Mining Haulage Systems

Due to climate change risks, the public, regulators, and investors require solid actions to minimize the greenhouse gas (GHG) emissions of mineral extraction and metals production. The mining sector considers alternatives to reduce its carbon footprint by transforming the business and adopting new technologies into operations. Given the capital intensity, technical characteristics, and business structure involved, a shift in the mining industry necessitates impartial insights into the trade-offs and risks. Considering the low-carbon transition trade-offs and risks in mining, this study presents the application of system dynamics modeling (SDM) in mining projects to analyze the impact of decarbonization alternatives with respect to carbon footprint and costs. A system dynamics model of an open-pit copper mine is developed to quantify greenhouse gas (GHG) emissions, as well as capital and operational costs, during the project life cycle. The change in GHG emissions in the business-as-usual scenario with diesel equipment haulage versus the alternative scenario with electric overland conveyor haulage is compared concerning GHG emissions and associated costs. The results unequivocally demonstrated that electrifying material mobility offers significant decarbonization in open-pit mining if the on-site electricity has a low emission factor. The findings also indicate that the substantial cost difference between electrification and diesel alternatives is another major obstacle to implementing electrification in an open-pit copper mine. This research proves that implementing SDM in the mining industry can offer impartial insights into decision-making and enable a thorough evaluation of options using quantitative criteria. It effectively assesses and communicates the trade-offs and risks of transitioning to low-carbon alternatives because it analyzes project variables quantitatively and holistically and is easy to run.

Effects of a cafeteria-based sustainable diet intervention on the adherence to the EAT-Lancet planetary health diet and greenhouse gas emissions of consumers: a quasi-experimental study at a large German hospital

SummaryBackgroundSustainable diets contribute to improving human health and reducing food-related greenhouse gas emissions (GHGE). Here, we established the effects of a facility-based sustainable diet intervention on the adherence to the EAT-Lancet Planetary Health Diet and GHGE of consumers.MethodsIn this quasi-experiment, vegan menus and educational material on sustainable diets were provided in the largest cafeteria of a German hospital for 3 months. Regular customers (> 1/week) in this cafeteria (intervention group) and in all other hospital cafeterias (control group) completed a questionnaire about their sociodemographic and dietary characteristics before and after the intervention period. We calculated difference-in-differences (DID), their 95% confidence intervals (CIs), and p-values for the adherence to the EAT-Lancet Planetary Health Diet Index (PHDI; 0–42 score points) and food-related GHGE. The protocol was registered at the German Clinical Trial Register (reference: DRKS00032620).FindingsIn this study population (N = 190; age range: 18–79 years; women: 67%; highest level of formal education: 63%), the mean baseline PHDI (25·1 ± 4·8 vs. 24·7 ± 5·8 points) and the mean baseline GHGE (3·3 ± 0·8 vs. 3·3 ± 0·7 kg CO2-eq./d) were similar between the intervention (n = 92) and the control group (n = 98). The PHDI increase was 0·6 points (95% CI: -0·4, + 1·6) higher in the intervention group than in the control group. This trend was stronger among frequent consumers of the vegan menu than among rare and never consumers. No between-group difference was seen for GHGE changes (DID: 0·0; 95% CI: -0·2, + 0·1 kg CO2-eq./d).InterpretationPending verification in a longer-term project and a larger sample, this quasi-experiment in a big hospital in Germany suggests that offering vegan menus and information material in the cafeteria enhances the adherence to healthy and environmentally friendly diets among regular customers. These findings argue for making sustainable food choices the default option and for improving nutrition literacy.FundingFederal Ministry of Economic Affairs and Climate Action (BMWK), Else-Kröner-Fresenius Foundation (EKFS), Robert-Bosch Foundation (RBS).

Idiosyncratic phenology of greenhouse gas emissions in a Mediterranean reservoir

AbstractExtreme hydrological and thermal regimes characterize the Mediterranean zone and can influence the phenology of greenhouse gas (GHG) emissions in reservoirs. Our study examined the seasonal changes in GHG emissions of a shallow, eutrophic, hardwater reservoir in Spain. We observed distinctive seasonal patterns for each gas. CH4 emissions substantially increased during stratification, influenced predominantly by the increase in water temperature, net ecosystem production, and the decline in reservoir mean depth. N2O emissions mirrored CH4's seasonal trend, significantly correlating to water temperature, wind speed, and gross primary production. Conversely, CO2 emissions decreased during stratification and displayed a quadratic, rather than a linear relationship with water temperature—an unexpected deviation from CH4 and N2O emission patterns—likely associated with photosynthetic uptake of bicarbonate and formation of intracellular calcite that might be exported to sediments. This investigation highlights the imperative of integrating these idiosyncratic patterns into GHG emissions models, enhancing their predictive power.

Econometric Analysis of the Influence of Factors on the Share of Energy From Renewable Sources in the EU

The use of renewable energy is at the core of EU energy policy, reducing dependence on fossil fuels imported from non-EU countries, reducing greenhouse gas emissions and decoupling energy costs from oil prices. Currently, 22.5% of energy consumed in the EU comes from renewable sources. This increase over 2021 is due to strong growth in solar energy. This share is also increasing due to the consumption of non-renewable energy sources in 2022. According to expert forecasts, the share of renewable energy sources in Europe will continue to grow. Achieving the 42.5% target by 2030 will require a deep transformation of the European energy system. The very strong climate and energy policies pursued in the EU for about a dozen years and aimed at limiting emissions of harmful substances into the environment have led to a gradual abandonment of traditional energy sources. Increasing demand for energy while reducing its supply from traditional sources means that in order not to make the economy too dependent on energy imports, the dynamic development of renewable energy is necessary. The EU is therefore taking very extensive operational and strategic actions to use other sources for production, such as wind, solar energy, mechanical water energy, biomass and geothermal energy, as well as tidal waves, ocean heat, wave energy and sea currents. In this study, we assess the impact of energy, economic and environmental factors on the share of renewable energy in the EU. The aim of these studies was to identify the energy, economic and environmental indicators that have the greatest impact on the share of energy from renewable sources in the European Union. The study was conducted using the Statgraphics Centurion software package. The source data for the study was data from the official Eurostat website for the period from 2012 to 2022. The results of this study show that changes in gross domestic product in market prices per capita have a positive impact, as do changes in greenhouse gas emissions per capita negatively affect the share of energy from renewable sources in the EU in the period 2012-2022. This may most likely be due to the fact that EU countries are more likely to invest in renewable energy as they can afford to invest in the development of expensive renewable energy technologies and support subsidies for the promotion and regulation of renewable energy. The negative impact of per capita greenhouse gas emissions on renewable energy development is due to the high share of coal in the EU energy mix, meaning that coal not only has negative environmental impacts, but also negative environmental impacts. development of renewable energy.

Analysis of Interactions among Greenhouse Gas Emissions, Carbon Sinks, and Food Security in China’s Agricultural Systems

Reducing greenhouse gas (GHG) emissions and increasing the size of carbon sinks are closely related to food security in agricultural systems. This study conducted an in-depth data analysis of previous studies to explore the dynamic causal relationships among the reduction of emissions, carbon sink increases, and food security in agricultural systems. The fixed-effect regression model, causality tests, PVAR model, impulse response functions, and variance decomposition were used to explore correlations among the three variables. The results show that the national average carbon sinks surged from 2662.194 Mg in 2000 to 4010.613 Mg in 2020, with the food security index concurrently climbing from 0.198 to 0.308. Moreover, GHG emissions exhibited a negative growth rate from 2016 onwards, yet the 2020 mean remained 142.625 Mg above the 2000 baseline. The agricultural “three subsidies” reform has not directly promoted food security, but significantly inhibited GHG emissions. However, conflicts exist between emissions reduction and carbon sinks increase in agricultural systems and food security. At the whole level, changes in carbon sinks only have a positive effect on the increase in GHG emissions, whereas changes in GHG emissions have a positive effect on both carbon sinks and food security. Changes in food security strongly inhibit the increase in carbon sinks. This relationship varies among distinct grain functional zones. Policy objectives should be coordinated, target thresholds set, and policies classified according to different functional orientations, to achieve a win–win situation for food supply and low-carbon development.

An umbrella review of health co-benefits from actions to reduce greenhouse gas emissions

BackgroundThere have been many modelled studies of potential health co-benefits from actions to reduce greenhouse gas emissions, but so far there have been no large-scale attempts to compare the magnitude of health and climate effects across sectors, countries, and study designs. MethodsAs part of the Pathfinder Initiative project an umbrella review of studies was done, and 26 previous reviews were identified with 57 primary studies included. Studies included in the review were required to have quantified changes in greenhouse gas emissions and health effects (or risk factors) from defined actions to reduce climate effects. Study data were extracted and harmonised by standardising impact measures per 100 000 of the national population (or urban population for city-level actions), averaging effects over a 1-year period and aggregating actions into their respective sectors by use of a predefined framework. FindingsFrom 200 mitigation actions, the majority were in the agriculture, forestry, and land use sector (103 actions [52%]), followed by the transport sector (43 actions [22%]). The largest effects on greenhouse gas emissions were seen from actions in the energy sector, and these actions also had substantial health co-benefits in lower middle-income countries, although benefits were smaller in high-income settings. The greatest health benefits were seen from actions to change diets and introduce clean cookstoves. The major pathways to health were through reduced air pollution, healthier diets, and increased physical activity from switching to active travel modes. Effect sizes tended to be larger from national modelling studies and smaller from localised or implemented actions. InterpretationThe potential co-benefits to health from actions to reduce climate change are large, but most evidence still comes from modelling studies and from high-income and middle-income countries. There are also major context-dependent differences in the magnitude of effects found, so actions need to be tailored to the local context and careful attention needs to be paid to potential trade-offs and spillover effects. FundingThe Wellcome Trust and the Oak Foundation.

Flood Impacts on Agriculture under Climate Change: The case of the Awanui Catchment, New Zealand

We assess the economic and environmental impacts on agriculture of flooding under projected climate change, including land-use change as an adaption response to floods. Our case study area is the Awanui catchment located in the far north of New Zealand, where flooding is a significant hazard. The study uses an integrated approach and combines spatial information on agricultural exposure and damage from flooding, economic land-use modelling, and valuation approaches. We analyse direct tangible and direct intangible flood impacts under various extents, frequencies, and water depth levels. Our results show areas with flood exposure and damage costs increase with projected climate change. As an adaptation measure to reduce flood damage costs, pastoral farms convert to other land uses, mainly to unfarmed land. Flooding reduces the net revenue for the catchment, while it can result in some reduction of environmental pollution. When the probability of all possible flood events are considered, the value of the changes in greenhouse gas emissions are equivalent to approximately 18% of the change in total net revenue, while the value of changes in other environmental outputs is equivalent to less than 1% of the change in total net revenue. Based on this study, the assessment of various flood impacts and adaptation responses to them can help to develop resilience strategies for the agricultural sector to future climate-induced flooding.

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.

Spatial and temporal evolution and drivers of GHG emissions from urban domestic wastewater treatment in China: a review at the provincial level.

To mitigate greenhouse gas (GHG) emissions from the wastewater treatment industry, it is crucial to explore GHG emission patterns and propose useful measures. In this study, we use the Kaya model and LMDI decomposition method to analyze the changes in GHG emissions from urban domestic wastewater treatment at the provincial level and further explore the distribution characteristics and driving factors of urban domestic wastewater treatment GHG emissions across various years and regions. The results indicate the following: (1) In the temporal dimension, urban domestic wastewater treatment GHG emissions are increasing, from 21.0 MtCO2 in 2011 to 27.1 MtCO2 in 2020, with an average annual growth rate of 2.88%. The spatial distribution is high in the southeast and low in the northwest. There is variability in the spatial evolution trend of GHG emissions by province, with the growth rate becoming slower or even negative in Jiangsu, Zhejiang, and North China, while the average annual growth rate exceeds 25% in Inner Mongolia and Xinjiang. (2) According to the decomposition results of driving factors, economic scale is the dominant positive driver, and the positive contributions of TI and the population effect are limited. The sludge disposal structure is the main negative driver, and the EEI and technology have restricted negative contributions. (3) Based on the decomposition results, for major coastal GHG emitters, such as Guangdong and Shandong, it is necessary to invest capital and technology to continuously upgrade the wastewater treatment process and reduce non-CO2 emissions. Along with adopting circular economy schemes, local governments in the northwestern region should transform the traditional sludge disposal structure and optimize the power supply structure to increase carbon offset and reduce CO2 emissions. The findings suggest a low-carbon transformation path to support the industry's dual carbon goals.

Greenhouse gas contribution and emission reduction potential prediction of China's aluminum industry

The aluminum industry, with its traditionally high energy consumption, high emissions and high pollution, is facing increasing pressure to reduce greenhouse gas (GHG) emissions in China. This study analyzes the trajectory and characteristics of GHG emissions during the lifecycle of China's aluminum industry (CAI) from 2011 to 2020, and identifies key driving factors affecting the changes in GHG emissions from CAI. The results indicate that the GHG emissions of CAI mainly come from indirect emissions generated by electricity production (over 69 %). Electrolytic aluminum is the largest sub process of GHG emissions in CAI. In addition, the total energy consumption effect is the main driving factor for the increase in GHG emissions from CAI. On this basis, emission reduction measures are proposed, the economic benefits and applicability of various emission reduction measures are analyzed, and the grey prediction model GM (1,1) is used to predict the GHG emission reduction potential of CAI in 2030. According to analysis, the GHG emission reduction efficiency of CAI is expected to reach 86 % by 2030, and can produce an annual economic benefit of 2.93 × 109RMB. This study will provide a theoretical basis for GHG emission reduction in CAI and even the global aluminum industry (GAI).

Is demand-side management environmentally beneficial? Analyzing the greenhouse gas emissions due to load shifting in electric power systems

Demand-side management via load shifting allows synchronizing electricity demand with supply from fluctuating renewable energies. Synchronizing seems desirable so that electricity from renewables will not be curtailed and overall greenhouse gas (GHG) emissions can be reduced. However, the change in GHG emissions by utilizing load shifting in electric power systems depends on the prevailing electricity generation mix. Although some publications discuss the impact of load shifting on the GHG emissions of specific electric power systems, a systematic analysis on the GHG emissions due to load shifting in general is still missing. We fill this gap by determining the changes in GHG emissions that result from cost-optimal load shifting in electric power systems. For our analysis, we consider the impact of load shifting in electric power systems with different shares of low-, medium-, and high-emission technologies. The results show that GHG emissions can both increase and decrease by utilizing load shifting, depending on the electricity generation mix in electric power systems. Hence, we emphasize that load shifting is not per se environmentally beneficial. Furthermore, we analyze the electric power systems of three regions of the world and conclude that utilizing load shifting is not reducing GHG emissions in every region today. However, the targeted electricity generation mix for the regions in 2050 suggests that the utilization of load shifting will reduce GHG emissions in the future. Furthermore, we show that under a sufficiently high CO2-price, load shifting is always environmentally beneficial in today's electric power systems.

Analyzing long-term dynamics of agricultural greenhouse gas emissions in Austria, 1830–2018

Agriculture is an important contributor to greenhouse gas (GHG) emissions. While the development of agricultural GHG emissions on national and global scales is well studied for the last three to six decades, little is known about their trajectory and drivers over longer periods. In this article, we address this research gap by calculating and analyzing GHG emissions related to agriculture in Austria from 1830 to 2018. We calculate territorial emissions on an annual basis and include all GHG emissions from the processes directly involved in agricultural production. Based on this time series, we quantify the relative importance of major drivers of changes in GHG emissions across time and agricultural product categories, applying a structural decomposition analysis. We find that agricultural GHG emissions in Austria increased by 69 % over the total study period, from 4.6 Mt. CO2e/yr in 1830 to 7.7 Mt. CO2e/yr in 2018. While emissions increased only moderately from 1830 to 1945 (+22 % overall), with strong fluctuations between 1914 and 1945, they doubled from 1945 to 1985. In the most recent period from 1985 to 2018, emissions fell by one third, with decreases leveling off over time. Our decomposition analysis reveals that increases in agricultural production per capita most importantly contributed to the high growth in GHG emissions from 1945 to 1985. Conversely, decreasing emission intensities of products and a more climate friendly product mix were key drivers in the emissions reduction observed after 1985. We also contribute to the discussion around the global warming potential star (GWP*), by calculating GHG emissions based on this alternative metric, and contextualize our data within total socio-economic GHG emission trends. By providing insights into the historical trends and drivers of agricultural GHG emissions, our findings enhance the understanding of their long-term historical dynamics and adds to the knowledge base for future mitigation efforts.

Analysis of changes in greenhouse gas emissions and technological approaches for achieving carbon neutrality by 2050 in Taiwan.

Over the past two decades, the Taiwan government promulgated some regulatory measures and promotional actions on energy efficiency promotion and renewable energy development. In March 2022, the "Taiwan's Pathway to Net-Zero Emissions in 2050" was announced to respond to the Paris Agreement. In order to achieve the goal, the Climate Change Response Act (CCRA) was passed on February 15, 2023, requiring the de-carbonization measures and adaptation strategies. The main aim of this paper was to analyze the changes in GHG emissions and renewable energy supply by using the updated data from the official statistics in connection with the trends of environmental and energy sustainability since 2000. The findings showed that total installed capacity of renewable power (especially in solar power and wind power) showed an amazing increase over the past decade, leading to the inclined GHG emissions and thus supporting the environmental and energy sustainability toward a low-carbon society. Furthermore, this paper summarized the development history and main differences concerning the carbon neutrality policy and legislation in Japan and South Korea. For achieving the staged targets of GHG emissions by 2030 and 2050, this paper finally addressed the technological approaches for achieving carbon neutrality by 2050 in Taiwan, focusing on the transformation of energy and industry, and the policy implications by all levels of government.

Livestock greenhouse gas emission and mitigation potential in China

Livestock is an important source of greenhouse gas emissions (GHGE) in China. Understanding the greenhouse gas (GHG) emission trends and reduction strategies in livestock is crucial for promoting low-carbon transformation of the livestock sector (LS) and achieving the goal of “carbon peak and carbon neutralization”. First, based on the life cycle assessment and IPCC coefficient methods, we calculated the GHGE of the LS in 31 provinces of China from 2000 to 2020 and identified the temporal and spatial evolution of GHG emission intensity. The LMDI method was then used to analyze the influence of efficiency, structure, economy, and population size on GHGE. Finally, the STIRPAT model was used to simulate the future evolution trend of the LS emissions under the SSPs scenario. The results revealed that the GHGE in the life cycle of livestock production decreased from 535.47 Mt carbon dioxide equivalent (CO2e) in 2000 to 532.18 Mt CO2e in 2020, and the main source was CH4 emissions from enteric fermentation of livestock. Economic and efficiency factors markedly influenced the changes in GHGE from the LS in China. Further, economic factors contributed >40% to the increase in GHGE in most provinces. Under the SSP1, SSP2, and SSP4 scenarios, livestock production can achieve the carbon peak target in 2030. Under the baseline scenario (SSP2), the GHGE of China's LS in 2030 and 2060 are expected to be 491.48 Mt CO2e and 352.11 Mt CO2e, respectively. The focus of mitigation measures for livestock production in the future is to optimize the production structure of the LS, promote the low-carbon transformation of the energy structure of livestock feeding, and establish an efficient and intensive management model. In addition, we focus on emission reduction in key areas, such as Northeast and Northwest China, while optimizing diet and reducing food waste from the consumer side.

Greenhouse gas emissions under work from home vs. office: An activity-based individual-level accounting model

Changes in residential, work, and commuting activities caused by work from home (WFH) have great impacts on greenhouse gas (GHG) emissions, but high-resolution quantifications of the changes in GHG emissions are still lacking. In this study, an activity-based bottom-up modeling approach and U.S. nation-scale datasets were employed to investigate the impact of different work arrangements on GHG emissions. The GHG footprint of a typical day (24 h) under WFH and work in office (WIO) was estimated and compared. The results revealed that WFH could mitigate GHG emissions by 29.11% (4.06 kg CO2e/person/day) compared with WIO. This was mainly due to the decrease in commuting and workplace emissions (reduced by 4.23 and 1.34 kg CO2e/day/person, respectively), but residential GHG emissions increased by 1.51 kg CO2e/day/person under WFH due to work, cooking, laundry, and watching TV and movies. Moreover, the demographic groups that reduced their work hours more after a shift from WIO to WFH achieved fewer reductions in GHG emissions, emphasizing the importance of group-specific considerations when proposing decarbonization strategies. Finally, several recommendations were provided to decarbonize WFH and WIO from an activity-based perspective. The results of this study provide insights into the environmental benefits of WFH and contribute to promoting low-carbon living to achieve climate goals.

Assessing evidence on the impacts of nature-based interventions for climate change mitigation: a systematic map of primary and secondary research from subtropical and tropical terrestrial regions

BackgroundNature-based interventions (NbIs) for climate change mitigation include a diverse set of interventions aimed at conserving, restoring, and/or managing natural and modified ecosystems to improve their ability to store and sequester carbon and avoid greenhouse gas (GHG) emissions. Recent projections estimate that terrestrial NbIs can lead to more than one-third of the climate change mitigation necessary to meet the Paris Climate Agreement by 2030. Further, these interventions can provide co-benefits in the form of social and ecological outcomes. Despite growing recognition of the potential benefits, a clear characterization of the distribution and occurrence of evidence which supports linkages between different types of NbIs and outcomes for climate change mitigation, ecosystems, and people remains poorly understood.MethodsThis systematic map assesses the evidence base on the links between NbIs and climate change mitigation, social, and ecological outcomes in tropical and subtropical terrestrial regions. We searched three bibliographic databases, 65 organization websites, and conducted backward citation chasing within 39 existing evidence syntheses to identify relevant articles. Additionally, we reached out to key informants for additional sources of evidence. We then used machine learning to rank returned results by relevance at the title and abstract stage and manually screened for inclusion using predefined criteria at the title, abstract, and full text stages. We extracted relevant meta-data from included articles using an a priori coding scheme. Lastly, we conducted a targeted, complementary search to identify relevant review and synthesis articles to provide broader context for the findings of the systematic map.Review findingsWe included 948 articles in this systematic map. Most of the evidence base (56%) examined links between protection, natural resource management, and restoration interventions with changes to ‘proxy’ outcomes for climate change mitigation (changes to land condition, land cover, and/or land use). Other areas with high occurrence of articles included linkages between interventions within natural resource management and trees in croplands categories and changes to aboveground carbon storage and/or sequestration (17% of articles). A key knowledge gap was on measured changes in GHG emissions across all intervention types (6% of articles). Overall, articles in the evidence base did not often assess changes in co-benefits alongside direct or indirect changes for climate change mitigation (32%). In most cases, the evidence base contained studies which did not explicitly test for causal linkages using appropriate experimental or quasi-experimental designs.ConclusionsThe evidence base for NbIs is significant and growing; however, key gaps in knowledge hamper the ability to inform ongoing and future investment and implementation at scale. More comprehensive evidence is needed to support causal inference between NbIs and direct outcomes for climate change mitigation to better determine additionality, permanence, leakage, and other unintended consequences. Similarly, priorities emerging from this map include the need for coordinated and harmonized efforts to collect diverse data types to better understand whether and how other outcomes (e.g. social, ecological) of NbIs can be achieved synergistically with mitigation objectives. Understanding potential benefits and trade-offs of NbIs is particularly urgent to inform rapidly expanding carbon markets for nature.

НАЛИЗ ДИНАМИКИ НАЦИОНАЛЬНЫХ ВЫБРОСОВ И ПОГЛОЩЕНИЙ ПАРНИКОВЫХ ГАЗОВ В КАЗАХСТАНЕ ЗА 2012...2021 ГГ

An overview of national greenhouse gas emissions from Kazakhstan for 2012-2021 (the last 10 years according to the UNFCCC reporting schedule) by sector and IPCC categories is presented. The data sources and the general methodology of emissions estimation are shown. The main trends and causes of changes in greenhouse gas emissions and removals are described. The key sectors and categories responsible for the main emissions are shown. Recommendations on the implementation of Kazakhstan’s obligations under the Paris Agreement are given. It is shown that there is a certain result of the country’s efforts to reduce the total greenhouse gas emissions in the framework of achieving the NDC.