IPCC Methodology Research Articles

Analysis of Quantitative Estimates of the Greenhouse Gases Net Flow in the Russian Land Use Sector

A comparative analysis of the actual greenhouse gas net runoff by the Russian land use sector has been carried out, which showed that depending on the methodologies and approaches used, as well as the type of initial data, information on the absorptive capacity can be aggregated into three groups: 1) studies based on process (inverse) modeling and VNIILM methodology; 2) studies with statistical net runoff modeling and approaches regulated by the IPCC on the basis of the state forest registry; 3) studies based on dynamic global vegetation models (DGVM) and ROBUL methodology, verified by the IPCC, but using as input data information from the state forest registry. An assumption is made that the existing official Russian ROBUL methodology, which coincides with the IPCC methodology, currently reflects a conservative estimate of the absorption capacity of the Russian land use sector and can be adjusted with a potential increase to 35-45% of the current values due to additional accounting of reserve forests in the calculations, as well as the results of the state forest inventory and a new state forest registry with a high degree of spatial resolution.

Additionality in Blue Carbon Ecosystems: Recommendations for a Universally Applicable Accounting Methodology.

Blue carbon ecosystems (BCEs) remove carbon dioxide from the atmosphere and store significant amounts of organic carbon (OC) in their soils. Consequently, the protection and restoration of BCEs may contribute to net greenhouse gas emissions abatement and help address the global challenges of both mitigating and adapting to climate change. An ongoing debate is whether OC sequestered out with the blue carbon (BC) project and transported to its present location (allochthonous) should be counted as 'additional'. There are inconsistencies in the treatment of allochthonous carbon between BCE methodologies, potentially undermining the credibility of global BC accounting initiatives. To explore these inconsistences, we compare the methodologies which we were able to find online, with particular focus on the VERRA, IPCC and BlueCAM methodologies, and review the science underlying any approach to account for allochthonous OC. Our findings indicate that there are currently no robust scientific approaches to define an appropriate apportioning of allochthonous OC for discounting in the calculation of additionality. We therefore advocate for the inclusion of allochthonous OC in BC crediting projects when an observational and experimental approach does not support the calculation (and discounting) of the refractory allochthonous carbon contribution.

MSA-Net: A Precise and Robust Model for Predicting the Carbon Content on an As-Received Basis of Coal.

The carbon content as received (Car) of coal is essential for the emission factor method in IPCC methodology. The traditional carbon measurement mechanism relies on detection equipment, resulting in significant detection costs. To reduce detection costs and provide precise predictions of Cars even in the absence of measurements, this paper proposes a neural network combining MLP with an attention mechanism (MSA-Net). In this model, the Attention Module is proposed to extract important and potential features. The Skip-Connections are utilized for feature reuse. The Huber loss is used to reduce the error between predicted Car values and actual values. The experimental results show that when the input includes eight measured parameters, the MAPE of MSA-Net is only 0.83%, which is better than the state-of-the-art Gaussian Process Regression (GPR) method. MSA-Net exhibits better predictive performance compared to MLP, RNN, LSTM, and Transformer. Moreover, this article provides two measurement solutions for thermal power enterprises to reduce detection costs.

Actual problems of modeling greenhouse gas emissions from municipal solid waste landfills (Review)

Because Russia is one of the world’'s largest emitters of greenhouse gases. The tasks of mitigating the effects of climate change, which are based on ongoing measures to reduce greenhouse gas emissions, are becoming increasingly urgent. Waste, including municipal solid waste (MSW), has long become a problem that poses a threat to the environmental safety of the Russian Federation. Analysis of statistical data shows that the volume of MSW waste is growing from year to year and largely depends on the scale of cities and population. Cities account for more than 70 % of greenhouse gas emissions, and they are the main contributor to the climate crisis. MSW landfills are the third largest anthropogenic source of atmospheric methane. Therefore, it is important to study the formation of methane in the conditions of landfill and its dependence on various factors. This article is devoted to a review and comparative analysis of the functional capabilities of the most well-known calculation methods used to model greenhouse gas emissions from waste disposal facilities. A comparative analysis of such techniques made it possible to determine their advantages and disadvantages, as well as the possibility of mutual substitution of parameters. The parameters of the methods are interchangeable and can be specified for each specific MSW landfill. The accuracy of the calculated prediction depends on the completeness of accounting for all factors affecting the process (climatic conditions, morphological composition of waste, type of landfill, the presence of fires, etc.). As a result of the study, it was found that in order to develop a scientifically sound methodology for estimating greenhouse gas emissions from waste disposal facilities, additional comprehensive studies are necessary. In particular, supplementing the list of wastes considered in the IPCC methodology with other types of waste in accordance with the Federal Waste Classification Catalog, determining the required parameters for these types of waste, as well as clarifying the parameters of the model for the possibility of using it in calculating emissions from a specific waste disposal facility.

Spatiotemporal variations and influencing factors of methane emissions from livestock in China: A spatial econometric analysis

In recent years, China has been implementing policies to improve the livestock industry in response to the global trend toward green and low-carbon development. These policies include the establishment of demonstration zones for high-standard agriculture, the relocation of farms to the north, etc. This study aims to investigate the impact of changes in the spatial structure of the livestock industry on methane emissions. It used panel data from 31 provinces in China from 2001 to 2021 and applied the IPCC methodology to quantify methane emissions at both the national and provincial levels. In addition, a spatial econometric model was used to analyze the impact of changes in the spatial structure of the livestock industry on methane emissions. The results show that methane from livestock in China decreased from 13.85 million tons in 2001 to 11.82 million tons in 2021. In addition, methane emissions from livestock in China show a significant spatial gradient and correlation. The Southwest has the highest methane emissions, accounting for 24 % of the total emissions. After controlling for spatial correlation and other factors in the model, it was found that the spatial structure of the livestock industry has a different influence on methane emissions both in the province and in neighboring provinces. To improve methane emission efficiency in the future, policies such as establishing functional zones for livestock farming, strengthening technological innovation and sharing for green development in agriculture, and promoting the optimization of agricultural and rural management structures should be implemented.

Analysis and prediction on carbon emissions from electrical and electronic equipment industry in China

This research employs the IPCC methodology to assess carbon emissions from China's Electrical and Electronic Equipment (EEE) industry for 2012–2020, utilizing the GM (1) model to predict emissions for the next decade. Six scenarios evaluate emissions, guiding strategies for reduction. Key findings reveal the usage phase as the highest emitter, while WEEE dismantling incurs the lowest. In 2020, emissions from production, sales, transportation, usage, recycling transportation, dismantling, and recycling were projected. Scrapping imported EEE from 2012 to 2020 results in 1.88 million tons of emissions. Projected 2030 emissions, under current policies or low-carbon measures, are 136 million tons and 72 million tons, respectively. Urgent actions, especially in Extended Producer Responsibility (EPR) and stakeholder roles, are essential. The study advocates for consumer awareness on energy conservation and reducing dependence on imported products. Manufacturing emissions highlight the need for eco-design, emphasizing sustainable practices. Recycling and dismantling phases also contribute emissions, necessitating optimized routes and advanced technologies. In addition, the study explores the potential for carbon reduction by incorporating the organic combination of carbon trading markets, evaluating the carbon emission reduction potential of recycling enterprises. The proposal suggests replacing government subsidies with the sale of carbon credits, not only to stimulate companies to actively promote green dismantling but also to address the current inadequacy of subsidies. Establishing a comprehensive life cycle management system is crucial to minimizing the EEE industry's carbon footprint and promoting a sustainable future.

Quantification and assessment of hazardous mercury emission from industrial process and other unattended sectors in India: A step towards mitigation

Hazardous pollutants like Mercury (Hg) have emerged as a pressing challenge in recent times where the expanding industrial sector is regarded as the major source in developing country India. In this study, we are trying to identify all possible industrial sectors at district level to quantify Hg emission load across India for the year 2019 using IPCC methodology where the country-specific technological emission factors are used. We have included 5 major sectors out of which emission from coal combustion in thermal power plants accounts for 186.5 t/yr of Hg emission followed by non-ferrous metal production (88.3 t/yr), captive power plants (65.5 t/yr) and fly ash generation from various manufacturing industries (45.9 t/yr). A total of 459.4 t/yr of Hg is released into the ecosystem in 2019 with an uncertainty of ± 48%. This study also estimated that about 233 million people living in and around 10 km periphery of major industrial zones with as many as 17 million people residing near the 10 major hotspots are susceptible to hazardous Hg emissions directly or indirectly. This information would be quite useful in formulating future Hg emission control strategies in India. Environmental ImplicationsPresent study is the first-of-its-kind quantification of Hg emission load from the Industrial process and many unattended sectors over India, which will not only give an insight into potential hotspots regions across the country but also assess the population exposed to it. It will provide aid in tracking the mercury burden to match the international conventions. The findings suggest that about 233 million people are likely to be exposed to hazardous Hg emissions. It will also enlighten the government, policymakers, stakeholders and people about their mercury footprint and envision protecting the biomes and formulating future control strategies in India.

SPATIAL DIFFERENTIATION OF THE EMISSIVITY OF AGRICULTURE IN EUROPE

This paper presents the results of a study aimed at determining the spatial variation in the carbon intensity of the agricultural sector in Europe. The analyses used the volume of greenhouse gas emissions from the agricultural sector (in 2020), expressed in carbon dioxide equivalent, calculated according to the IPCC methodology for 31 European countries. To reduce variance and the impact of country size on emissions, three emissivity factors were calculated, depending on: agricultural area, value of goods produced by agriculture and population. To verify the relationship between emissivity and location, the Moran autocorrelation coefficient was used, calculated on a modified weighting matrix that, in addition to the criterion of a common border, takes into account the similarity of objects in terms of the values of diagnostic variables (similarity determined using cluster analysis) – in this case indicators describing the emissivity of the agricultural sector. The study showed that there was no reason to reject the hypothesis of a random distribution of objects in space with respect to the values of the indicators included in the study. It can therefore be concluded that there are some similarities in the emissivity from the different European economies, as evidenced by the cluster analysis results, while there is no spatial correlation.

Application of the IPCC Methodology to Assess the Spatial Distribution of CO2 Emissions in Russian Ferrous Metallurgy

Application of the IPCC Methodology to Assess the Spatial Distribution of CO2 Emissions in Russian Ferrous Metallurgy

Calculation of Muğla Sıtkı Koçman University's Carbon Footprint with IPCC Tier 1 Approach and DEFRA Method

As a result of the increase and diversification of human needs from past to present, greenhouse gas accumulation occurs in the atmosphere. The natural disasters and climate change problems experienced today are especially caused by air pollution. The continuous increase in human needs brought about by the production age, which started with the industrial revolution and was supported by rapid population growth and urbanization, has caused intense greenhouse gas emissions and air pollution. The air pollution has increased due to the growing demand for energy met by fossil fuels. In order to combat air pollution, which is clearly felt, many conferences and meetings have been held in the past and declarations and agreements have begun to be made. The fight against air pollution has not only been carried out internationally, but has also been supported by individual countries creating rules such as regulations, laws and statutes. Especially with the Kyoto Protocol, attention was drawn to greenhouse gases, and it was emphasized that greenhouse gas emissions should be reduced. For this purpose, it has become important to calculate the greenhouse gas emissions, that is, the carbon footprint of countries, institutions, and areas of activity. In this study, the carbon footprint of Muğla Sıtkı Koçman University was calculated using IPCC Tier 1 methodology and DEFRA conversion factors. Carbon dioxide emission values resulting from the university's fuel and electricity consumption were subsequently compared. The results of carbon dioxide emissions resulting from electricity consumption in IPCC and DEFRA methods were confronted with the results obtained with Turkey data. Fuel and electricity consumption data received from the university were used in the calculations. It was found that the emission amount was 4,759,087.57 kg CO2e in 2020 when calculated with the IPCC Tier 1 approach, and 3,419,082.09 kg CO2e in 2020 when calculated using DEFRA conversion factors. In 2021, when calculated with the IPCC Tier 1 approach, this value increased by 88% to 8,955,635.86 kg CO2e, and when calculated using DEFRA conversion factors, the same value increased by 119.69% to 7,511,422.31 kg CO2e in 2021. In 2022, when calculated with the IPCC Tier 1 approach, it was seen to be 10,093,960.88 kg CO2e, increasing by 13% with the same method, and when calculated using DEFRA conversion factors, it was found to be 7,625,269.61 kg CO2e, increasing by 1.88% in 2022 using the same method. According to the calculations, while the number of trees required to be on campus to zero the campus carbon footprint is 211,515 for the IPCC methodology for 2020, this number is 151,959 according to the DEFRA method. For 2021, while it was 398,028 for the IPCC methodology, this number was 333,841 according to the DEFRA method. The required number of trees was calculated as 448,620 and 340,101 for 2022 according to IPCC and DEFRA methods, respectively.

GREENHOUSE GAS EMISSIONS FROM MUNICIPAL WASTE DISPOSAL SITES AND MEASURES FOR ITS REDUCTION

Disposal of household waste at landfills and dumps leads to greenhouse gas emissions. Usually emissions are estimated based on the IPCC methodology, which takes into account the amount and composition of household waste as well as the climate conditions of the region. However, greenhouse gas emissions are significantly influenced by the technical and operational parameters of landfills and dumps. The Ukrainian landfill gas model, which is adapted to local conditions, allows these parameters to be taken into account. The objective of this study was the estimation of greenhouse gas emissions from certain classes of landfills and dumps, taking into account their specific parameters based on the Ukrainian landfill gas model, as well as the development of measures for its reduction. For this, landfills and dumps were classified by area, which indirectly characterizes their capacity and place of location. Based on the results of the classification, it was determined that out of more than 7,000 landfills and dumps in Ukraine, about 320 are classified as large sites. These sites occupy more than a third of the total area of landfills and dumps in Ukraine and contain up to 84% of disposed household waste. Large landfills and dumps are a priority for greenhouse gas emissions study. According to the results of greenhouse gas emissions study, their total amount is estimated to be 5,833.5 thousand tСО2. These amount 32.9% less than similar estimates according to the IPCC methodology, which is explained by the higher accuracy of the Ukrainian landfill gas model and its parameters. Of the total amount of greenhouse emissions, up to 40% can potentially be reduced by the continued development of landfill gas collection systems, which actually reduced about 10% greenhouse gas emission in 2021. This potential can be increased by half and the reduction of greenhouse gas emissions can potentially reach up to 60% of their total emissions from landfills and dumps. For this purpose, the rehabilitation of the landfills and dumps should be conducted along with the development of landfill gas collection systems. However, rehabilitation is a complex and expensive measure, and the rationale for its application may be the subject of further research.

Strategies to Mitigate Greenhouse Gas (GHG) Emissions from the Solid Waste Management Sector: A Case Study of Vavuniya, Sri Lanka.

The waste sector is a substantial source of GHG emissions worldwide. Open dumping and internal combustion (IC) waste collection vehicles are significant sources of GHG emissions in Vavuniya. This research aims to estimate GHG emissions and recommend strategies to reduce emissions from the solid waste management sector. The IPCC methodology, considering Tier 1 estimation values based on default activity data, was used to estimate CH4 emissions from solid waste disposal sites. GHG emissions from collection vehicles were calculated based on IPCC mobile combustion recommendations. Three recommended strategies were considered based on demand, economic, and environmental feasibility and are expected to commence in 2025. According to current practices, open dumping generated 29.217 Gg of CO2 equivalent up to 2023, projected to rise by 37.8% by 2040. There will be a 57% decrease in open dumping-related GHG emissions by 2040 if composting is made mandatory for biodegradable waste, even though it produces emissions. Solar panels will be used to charge electric vehicles that will replace IC ones to cut emissions and fuel expenditures by 2025. The carbon sink reforestation program at the district level would need to begin in 2025 with an area of 161 hectares to sequester cumulative GHG emissions from composting dumpsites and fuel vehicles to achieve carbon neutrality by 2040. Investments from Vavuniya Carbon Sink Bonds (VCSB) on additional solar panels will ensure financial feasibility, having an internal rate of return of 23.18%. It paves the path to reducing GHG emissions, which is highly emphasized in the Nationally Determined Contributions, National Climate Change Policy, and waste management policy of Sri Lanka.

Environmental impact assessment of green ammonia-powered very large tanker ship for decarbonized future shipping operations

Maritime transport has been critical for the world economy and trade for centuries. Greenhouse gases and their environmental impacts are significant contributors to global warming and climate change and have compelled authorities to take substantial steps toward decarbonizing the energy system. Since then, the International Maritime Organization, policymakers, classification societies, shipping companies, and related stakeholders have been increasingly concerned about the environmental impacts of carbon-based fuels. Green ammonia as an energy vector is considered one of the top contenders for future energy systems. However, gaps remain in the literature regarding environmental impact assessment and usage. This study assessed the environmental impacts and performance of a newly built green ammonia-powered, very large oil and chemical tanker designed for the Atlantic Ocean route from Rotterdam to New York Port. This life cycle assessment study considers a tanker's entire transport life cycle from its manufacturing process to the production, material transportation, energy required for manufacturing, operation, maintenance, disassembly, scrap processing, and using green ammonia as a marine fuel. Performed an environmental impact assessment using IPCC, Environmental footprint, and ReCiPe midpoint Hierarchist (H) methodologies for five broad impact groups: Eutrophication, ozone, Climate change, Human and Ecotoxicity, and analyzed green ammonia process impacts. This study performed a comparative environmental performance assessment of HFO, LNG, blue ammonia, and green ammonia using impact categories such as GWP 100 and GTP 100. Green ammonia exhibited the most substantial negative percentage difference values (higher than −90%) per tonne-kilometer, indicating a lower environmental impact than all fuels in both categories. Adequately managing the ammonia-powered marine energy system would be indispensable for reducing environmental footprints and successfully lowering carbon, nitrogen oxide, and ammonia-based emissions.

Comparative life cycle impact assessment of offshore support vessels powered by alternative fuels for sustainable offshore wind operations using machine learning

Offshore Anchor handling tug supply (AHTS) vessels, a type of offshore support vessel, are critical for the operations related to handling anchors of offshore structures, oil rigs, and wind turbines, towing them to remote deep-sea locations, and securing them in place. Amidst growing concerns regarding the environmental footprints of carbon-based fuels and impending carbon taxation, the International Maritime Organization, policymakers, classification societies, shipping firms, and stakeholders are seeking cleaner alternatives. LNG (Liquefied natural gas) and Green ammonia as energy vectors are considered among the top contenders for future clean alternatives for offshore vessels. This study evaluated the environmental performance of newly built AHTS vessels powered by LNG and Green ammonia as marine fuels designed for offshore operations. This environmental impact assessment study uses IPCC and Environmental footprint methodologies. Considered broad impact groups: Global warming, human toxicity, eutrophication, ecotoxicity, and atmosphere-related impacts, and analyzed the process impacts. This study uses Supervised machine learning algorithms such as the Random forest, Decision tree, and XGBOOST models for environmental performance evaluation and prediction. The study reveals that the recently manufactured AHTS vessel, utilizing conventional fuels like Heavy fuel oil, Marine diesel oil, and LNG, exhibits significantly increased GTP 100 and GWP 100 emission levels per tonne-kilometer when compared to green ammonia, with a 44 % and 10.6 % rise compared to Heavy fuel oil, respectively. Furthermore, the XGBOOST regression model outperformed the Random forest and Decision tree models in predictive accuracy for GWP 100. It is analyzed and proposed that effectively managing unsustainable processes would minimize environmental footprints and reduce carbon, nitrogen oxide, LNG, and ammonia-based emissions.

Higher N2O emissions from organic compared to synthetic N fertilisers on sandy soils in a cool temperate climate

The atmospheric increase in N2O is mainly derived from N fertilisation in agriculture, and improved emission estimates are needed for effective mitigation. This study presents first estimates of country-specific N2O emissions from synthetic and liquid organic fertilisers in Denmark. Representative crop rotations were established in four locations across Denmark to provide a realistic context for the estimation of N2O emissions, i.e., a dairy farm rotation in Western Denmark, dairy and pig farm rotations in Southwestern Denmark, and an arable rotation in Eastern Denmark. The four sites were light-textured and typical for Northern Europe, whereas rainfall varied considerably among sites and years. A randomised block design was used, and all crops were represented in triplicate each year with monitoring of N2O emissions between April 2020 and March 2022. Spring barley was part of all rotations, and here three synthetic fertilisers (NS, NPK and urea ammonium nitrate) and eight organic fertilisers (three cattle slurries, three pig slurries and two digestates) were applied in 1 m2 plots at either two or four sites in order to compare N2O emissions from the same N fertiliser materials under contrasting site conditions. Identical methodologies for management, fertiliser application, and N2O measurement and flux calculation, were used at all sites to ensure comparability. Manually operated chambers were used for N2O flux measurements. The continuous monitoring indicated a strong seasonal pattern across all four sites with the main part of N2O emissions during spring. The side-by-side comparison of several N sources at four sites in two years showed for synthetic fertilisers an average N2O emission factor for the spring period of 0.15% (95% C.I. −0.17 to 0.37%, n = 16), and for liquid organic fertilisers (pig and cattly slurries, and digestates) an average of 1.02% (95% C.I. 0.75 – 1.30%, n = 44). The higher N2O emissions from organic fertilisers, which was significant at each of the four sites, is in opposition to new N2O emission factors recently proposed in a refinement of the IPCC methodology for national inventories. The conflicting results are discussed with reference to region-specific site conditions and fertiliser types, and in particular the predominance of soils with a low clay content, and of liquid manure management, may explain the deviations from global estimates. A comparison of annual and spring N2O emissions indicated a difference in the order of 0.1 – 0.2% of the N input (n = 8), and the feasibility of estimating N2O emission factors based on emissions during the growing season only is discussed.

An Initial Approximation to the Simulation of Soil CO2 Emissions Using the IPCC Methodology in Agricultural Systems of Villavicencio

At a global level, the agricultural sector has represented the largest source of greenhouse gas (GHG) emissions. Our research hypothesizes whether it is possible to faithfully define the effect of soil management factors on modeling soil carbon organic (SOC) sequestration and reducing soil CO2 emissions in different agricultural systems across three zones of Villavicencio (Colombia) by applying the Tier-1 IPCC process‐based model. Agroforestry systems (AFS) are typically found in zone 1, and intensive croplands (CL) in zones 3 and 4. Soil CO2 emissions rates are calculated according to the current IPCC guidelines for national GHG inventories. Root-mean square error (RMSE, RMSE/n), R2, and Nash‐Sutcliffe efficiency (NSE) are measured to assess model performance. In zone 1, 7-year coffee-based agroforestry stored higher SOC, neutralizing -10,83t CO2 eq ha-1 year−1 than 25-year soybean/corn crop rotation in zone 3, with emissions of 2,56t CO2eq ha-1 year-1. The agricultural systems of zones 3 and 4 turned out to be greater emitters, with 7 223 and 3 889t CO2 eq year-1, respectively, which could increase if CL continues to adopt agricultural practices that encourage full tillage. The beneficial effects of AFS on stored SOC are identified via field observations and correctly reproduced by RMSE evaluation.

Greenhouse gas emissions and carbon footprint of collard greens, spinach and chicory production systems in Southeast of Brazil.

Food production in sustainable agricultural systems is one of the main challenges of modern agriculture. Vegetable intercropping may be a strategy to mitigate greenhouse gas (GHG) emissions, replacing monoculture systems. The objective is to identify the main emissions sources and to estimate GHG emissions of intercropping and monoculture production of collard greens, New Zealand spinach and chicory. Four scenarios were evaluated: ICS - intercropping collard greens and spinach; MCS - monoculture collard greens and spinach; ICC - intercropping collard greens and chicory; MCC - monoculture collard greens and chicory. The boundaries' reach from "cradle-to-gate" and the calculation of GHG emissions were performed using IPCC methodology and specific factors (Tier 2). The total GHG emitted was standardized as CO2 equivalent (CO2eq). The GHG emissions in ICS and ICC scenarios were approximately 31% lower than in MCS and MCC scenarios. Carbon footprint in ICS (0.030 kg CO2eq kg-1 vegetables year-1) and ICC (0.033 kg CO2eq kg-1 vegetables year-1) scenarios were also lower than in MCS (0.082 kg CO2eq kg-1 vegetables year-1) and MCC (0.071 kg CO2eq kg-1 vegetables year-1) scenarios. Fertilizers, fuel (diesel) and irrigation were the main contributing sources for total GHG emitted and carbon footprint in all evaluated scenarios. The results suggest that intercropping systems may reduce GHG emissions associated with the production of vegetables evaluated as compared with monoculture.

Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales.

Streams and rivers are important sources of nitrous oxide (N2 O), a powerful greenhouse gas. Estimating global riverine N2 O emissions is critical for the assessment of anthropogenic N2 O emission inventories. The indirect N2 O emission factor (EF5r ) model, one of the bottom-up approaches, adopts a fixed EF5r value to estimate riverine N2 O emissions based on IPCC methodology. However, the estimates have considerable uncertainty due to the large spatiotemporal variations in EF5r values. Factors regulating EF5r are poorly understood at the global scale. Here, we combine 4-year in situ observations across rivers of different land use types in China, with a global meta-analysis over six continents, to explore the spatiotemporal variations and controls on EF5r values. Our results show that the EF5r values in China and other regions with high N loads are lower than those for regions with lower N loads. Although the global mean EF5r value is comparable to the IPCC default value, the global EF5r values are highly skewed with large variations, indicating that adopting region-specific EF5r values rather than revising the fixed default value is more appropriate for the estimation of regional and global riverine N2 O emissions. The ratio of dissolved organic carbon to nitrate (DOC/NO3 - ) and NO3 - concentration are identified as the dominant predictors of region-specific EF5r values at both regional and global scales because stoichiometry and nutrients strictly regulate denitrification and N2 O production efficiency in rivers. A multiple linear regression model using DOC/NO3 - and NO3 - is proposed to predict region-specific EF5r values. The good fit of the model associated with easily obtained water quality variables allows its widespread application. This study fills a key knowledge gap in predicting region-specific EF5r values at the global scale and provides a pathway to estimate global riverine N2 O emissions more accurately based on IPCC methodology.

Exploring the mitigation of greenhouse gas emissions from the current municipal solid waste system of Kazakhstan: case study of Nur-Sultan city

As we move forward, municipal solid waste (MSW) landfills, particularly in developing countries, contribute notably to global greenhouse gas (GHG) emissions. Therefore, the MSW sector plays a key role in planning strategies for developing countries such as Kazakhstan to decrease GHG emissions. With respect to the Paris Agreement, Kazakhstan has set the target of reducing GHG emissions to 15-25% by 2030 compared to the level of 1991, which will undoubtedly require certain measures in the field of MSW management. Several recent articles have been published on the waste management sector of Kazakhstan; however, none have explicitly focused on the impact of greenhouse gas emissions and possible pathways towards sustainable management. Thus, this paper describes the existing MSW system in Nur Sultan city as representative for the rest of the country. The quantitative evaluation of GHG emissions from the existing MSW system in the capital is carried out based on the IPCC methodology using the SWM-GHG calculator developed by the Institute for Energy and Environmental Research (IFEU). An assessment and cost analysis of a set of several suitable MSW management scenarios, such as scenario 1: existing case (15% recycling rate and 85% disposal), scenario 2: 30% recyclable materials, and 70% sanitary landfill with gas collection; scenario 3: 30% recyclable materials and 70% biological stabilization and landfill without gas collection; scenario 4: 30% recyclable materials, 20% composting and 50% waste to be sent to the WtE plant (incineration). The level of GHG emissions decreases with the introduction of more integrated waste management methods, but requires more financial investments. Therefore, Scenario 3 is the most efficient to implement in terms of the combination of cost of €19.4 million/year and magnitude of GHG emissions of 48 kt of CO2 eq/year. The outcomes of this work will help to extrapolate the model to other large cities in Kazakhstan

Nitrogen fertilisation impacts greenhouse gas emissions, carbon footprint, and agronomic responses of beet intercropped with arugula

Although the response of plants to nitrogen (N) in conventional systems has been extensively described in the literature, there is a lack of information available to refine the strategic N fertilisation program required in intercropping systems to match the nutrient supply with crop demands and reduce environmental impacts on greenhouse gas emissions. Therefore, this study aims to investigate the effect of N management on the growth, production, quality, greenhouse gas emissions (GHG) and carbon footprint of a beet-arugula intercropping system during two growing seasons (winter and summer). The efficiency of N fertilisation in each season was assessed by the supply of 20 N doses, varying the amounts applied at planting and as a side dressing (0–80, 0–120, 0–160, 0–200, 0–240, 20–80, 20–120, 20–160, 20–200, 20–240, 40–80, 40–120, 40–160, 40–200, 40–240, 60–80, 60–120,60–160, 60–200 and 60–240 kg N ha−1). GHG emissions and carbon footprint were calculated and converted to CO2 equivalent (CO2 eq) utilising IPCC methodology. The height, total and marketable productivities of beet plants were 33, 31 and 34% higher in winter than in summer, respectively. Arugula plants achieved the highest performance (height, fresh mass and yield) in summer. Considering the environmental impact on global warming/climate change caused by the use of N fertilisers, total GHG emissions may range from 1723.9 to 3369.8 kg CO2eq ha−1 cycle−1 according to the N dose applied. However, based on the carbon footprint, the application of 60–120 kg N ha−1 at planting and as side dressing was the best N dose, since it reduced the carbon footprint (equivalent to 0.134 g CO2eq kcal−1 vegetables) without compromising crop yield.