Greenhouse Gas Emission Factors Research Articles

Abstract Climate change has emerged as a global issue, and the emission levels of greenhouse gases (GHGs) significantly influence global climate change. The patterns and controls of GHG emissions in urban rivers remain unclear. GHG fluxes in different types of urban rivers in Changzhou City, China, were calculated via the floating static chamber method and boundary layer equation method. Ultraviolet-visible (UV–vis) absorption spectroscopy and three-dimensional excitation–emission matrix fluorescence spectroscopy (3D-EEM) were employed to explore the sources and characteristics of the dissolved organic matter (DOM) in the rivers. The physical and chemical indicators of the rivers and sediment were monitored on-site and analyzed in the laboratory. Additionally, the species and quantity of bacteria in the sediment were determined. Spearman correlation analysis was used to identify the key factors influencing GHG emissions. The results showed (1) that the intensity of sunlight had an impact on the activity of pseudomonas, and thus affected N2O flux and that (2) the CO2 flux measured by the two above-mentioned methods significantly differed and were negatively correlated (p < 0.05), possibly because low wind speed influences the robustness of the boundary layer model. Therefore, using only the boundary layer equation method cannot accurately measure the GHG emissions of rivers in urban areas with low wind speeds. (3) The CO2 flux exhibited a strong positive correlation with both total phosphorus and ammonia nitrogen in the water, as indicated by a Spearman correlation coefficient with a significance level of p < 0.01. Thus, pollution control and input control play crucial roles in reducing GHG emissions. (4) DOM in the urban rivers was derived mainly from autochthonous sources, which are protein-like substances related to the metabolism of phytoplankton. Studies indicate that GHG emissions are negatively correlated with autochthonous parameters, suggesting that reduced human interference leads to lower GHG emissions.

IntroductionSoil pore-scale aeration is a crucial yet often overlooked factor influencing the effectiveness of nitrous oxide (N2O) emission mitigation strategies. Our previous work revealed a hundred-fold variation in N2O emissions among soils under apparently aerobic conditions and texture-dependent mitigation effects of biochar–manure co-compost (BM) compared to manure compost (M).MethodsWe analyzed soils of three textures—clay loam (CL), silt loam (SL), and sand (SA)—amended with BM or M. Metagenomic sequencing was used to profile microbial community composition and functional genes, with a focus on aeration-sensitive taxa and pathways.ResultsWe demonstrate that these changes of N2O emissions are aligned with variations in aeration-sensitive microbes and genes. SA, with the highest N2O emissions, was most abundant in obligate and facultative anaerobes and denitrification-related genes, while CL, with the lowest emissions, had more genes related to fermentation and dissimilatory nitrate reduction. Compared to M, BM in CL favored genes for microbial processes requiring a more reducing environment, likely because biochar-induced finer pores, exacerbating oxygen diffusion limitations. This severe oxygen restriction in CL after BM addition was substantiated by greater reductions in CO2 efflux and C-cycling genes than in the other soils.DiscussionOur findings suggest that hypoxic pore abundance and the severity of pore anaerobiosis imparted by degradation of organic amendments varied with soil texture and are the overriding factors of soil greenhouse gas (GHG) emissions. Metagenomic traits provide a sensitive tool for detecting pore-scale environmental shifts, improving our mechanistic understanding of soil-dependent GHG emissions following organic amendments.

The healthcare system accounts for 4 percent of United Kingdom (UK) greenhouse gas (GHG) emissions annually. In response to climate change, the National Health Service (NHS) is calling for less carbon-intensive care practices through prevention. Respiratory Syncytial Virus (RSV), a leading cause of infant hospitalization, currently has no widespread immunization program in the UK. This study estimates the impact on GHG emissions generated within the care pathway from an immunization against RSV in all infants in the UK with nirsevimab, a new monoclonal antibody used in prophylaxis. A novel approach was applied, mapping care pathway emissions from immunization and avoiding RSV-related primary and secondary care burden. Avoided healthcare resources were estimated using a published health economic model for nirsevimab versus standard of care (SoC), which is characterized as receiving palivizumab or having no immunization intervention, assuming different universal immunization scenarios. NHS England GHG emission factors were applied to each health outcome to measure the GHG emissions associated with a nirsevimab versus SoC strategy. Compared with SoC, a universal immunization program using nirsevimab leads to avoided GHG emissions, amounting to ~22 kilotons of CO2 equivalents per year, with immunizing all UK infants at birth leading to the greatest reduction. About 40 percent of avoided emissions were from reductions in inpatient hospitalizations. This study shows how prevention can deliver benefits to people, NHS system capacity, and the environment. However, avoided patient care pathway emissions must be considered alongside drug lifecycle emissions, which are not included here.

A dataset for climate, land, energy and water systems modelling in Lao PDR

We calculate the greenhouse gas (GHG) emissions and energy consumption of two French beekeeping systems, one amateur system (Amat) and one professional system (Pro) with 300 hives. The GHG emissions reach 2.7 kgCO2eq/kg of honey for Amat and 1.49 for Pro. Travel to visit the apiaries accounted for 59% of the total GHG emissions for Amat and 28% for Pro, and sugar accounted for 21% and 41%, respectively. The energy consumption reached 37.4 MJ/kg for Amat and 19.9 MJ/kg for Pro; travel represented 65% of energy consumption for Amat and 34% for Pro, and sugar accounted for 15% and 32%, respectively. The sensitivity analysis revealed that the most important factor influencing GHG emissions was the bee mortality rate, followed by the distances covered by vehicles and the level of sugar use. The average energy consumption per kg of dry matter produced between Amat and Pro is close to that observed for French dairy cattle production. The GHG emissions are well below those of dairy production, by factors of 3.7 and 6.6 for Amat and Pro, respectively. Finally, we make the following recommendations to improve the environmental performance of beekeeping farms, in terms of GHG emissions and energy consumption, in the French context but a priori also in other contexts i) maintain efforts to identify and reduce causes of bee mortality; ii) limiting distances traveled and using low-energy, low-carbon vehicles; and iii) using well-insulated hives. We also provide the GHG emission and energy consumption factors for the artificial swarms purchased.

The energy mix serves as the basis for calculating the greenhouse gas (GHG) emission factor of electricity, and therefore has a significant impact not only on the evaluation of GHG-related policies but also on the carbon footprint of industries that use electricity in life cycle assessments (LCA). As such, there is a need to annually publish GHG emission factors that reflect changes in the energy mix. The purpose of this study is to present IPCC- and LCA-based GHG emission factors and GHG emissions for the energy sector based on changes in the energy mix, and to assess whether the nationally determined contribution (NDC) can be achieved under these conditions. To achieve this, the study applies Intergovernmental Panel on Climate Change (IPCC) and LCA-based GHG emission factors for each power source to the energy mix outlined in the 10th Basic Plan for Electricity Supply and Demand, calculating annual (2018~2036) national electricity GHG emission factors and emissions, and analyzing the feasibility of meeting the NDC target. The analysis revealed that GHG emission factors fluctuate significantly with changes in the energy mix, underscoring the need for annual calculations. Under the planned energy mix, GHG emissions from the energy transition sector are projected to reach 159.9 million tons CO2eq, which exceeds the NDC target of 149.9 million tons CO2eq. However, reducing coal-fired power generation by 10% and replacing it with offshore wind and solar power could make achieving the target feasible. Additionally, the LCA-based GHG emission factors indicate that expanding offshore wind and solar power instead of relying on hydrogen and ammonia in the energy mix could achieve a 2.5% reduction. Therefore, adopting methodologies such as those used in this study to calculate annual GHG emission factors would allow efforts to transition the energy mix to be immediately reflected. Furthermore, when planning the energy mix, an LCA-based approach rather than an IPCC-based approach would provide a more effective means of responding to practical environmental regulations

This study aims to quantify the greenhouse gas (GHG) emission factors of by-product hydrogen generated from the Naphtha Cracking Center (NCC) process using Life Cycle Assessment (LCA), and to analyze the differences in emission results based on the selection of allocation criteria. The allocation methods were categorized by referring to international LCA guidelines such as ISO 14044, EU Product Environmental Footprint (PEF), ILCD Handbook, and Hy Guide. Four allocation criteria were applied: mass, lower heating value (LHV), economic value, and mole number. The study examines how the choice of allocation approach significantly influences LCA results and the calculated GHG emission factors. Mass-based allocation offers simplicity and general applicability, but lacks the ability to reflect product characteristics. LHV-based allocation is reasonable when all co-products are used as energy sources, but may not be appropriate when their end-uses vary. Economic allocation reflects market reality but is highly sensitive to price fluctuations. Mole-based allocation is theoretically sound as it reflects chemical stoichiometry, but its practical applicability is limited due to the lack of precedent in industrial or policy applications. The calculated GHG emission factors for each method were as follows 1.25 kgCO2eq./kgH2 for mass based allocation, 3.219 kgCO2eq./kgH2 for LHV based allocation, 13.24 kgCO2eq./ kgH2 for economic value based allocation, and 13.93 kgCO2eq./kgH2 for mole based allocation.

This study develops a multiperiod mixed-integer linear programming model for strategic planning of direct air capture (DAC) supply chains across Europe aiming at minimizing overall costs under uncertainty. DAC is pivotal for achieving net-zero targets and removing CO2 from the atmosphere to enable negative emissions. The optimization considers uncertainty in key parameters to ensure resilient decision-making. The model incorporates the influence of ambient air conditions on DAC performance, with temperature and humidity impacting productivity and energy consumption. Country-specific energy costs and greenhouse gas emission factors are accounted for, impacting the net cost of CO2 removal. Results indicate that with ambitious targets, technology learning curves, and renewable electricity transition, costs can fall to approximately 121 €/t CO2 by 2050, with 108 €/t attributed to capture costs. The findings highlight the importance of technological advancements and provide a systematic framework for policymakers to design resilient and cost-effective supply chains for large-scale deployment, positioning DAC as a potential decarbonization alternative for hard-to-abate emissions.

Electricity is often generated in one region and consumed in another. The regions consuming electricity should bear the responsibility for the greenhouse gas (GHG) emissions associated with their consumption. A consumption-based calculation helps address the imbalance between generation regions (typically where fossil fuel power plants such as coal and LNG are located) and consumption regions. This approach can reduce the issue of disproportionately concentrating GHG emission responsibility on specific regions. In this context, we propose a regionalized approach that allocates GHG emissions based on electricity consumption rather than production. Utilizing data from the Korea Electric Power Corporation, the study estimates GHG emissions by energy source and considers electricity transfers between regions. The study results revealed that the responsibility for emissions from consumption is concentrated in cities that rely on coal-fired power generation. For example, Seoul, which supplied electricity from Chungnam where coal-fired power is the main source, has an emission factor of 633 kgCO<sub>2</sub>eq/kWh. In contrast, Gyeongbuk, which primarily produces electricity through nuclear power, has an emission factor of only 12 kgCO<sub>2</sub>eq/kWh. The findings reveal significant disparities in GHG emission factors across each region, highlighting the limitations of the current system and the need for more accurate regional emission assessments.

Electricity is often generated in one region and consumed in another. The regions consuming electricity should bear the responsibility for the greenhouse gas (GHG) emissions associated with their consumption. A consumption-based calculation helps address the imbalance between generation regions (typically where fossil fuel power plants such as coal and LNG are located) and consumption regions. This approach can reduce the issue of disproportionately concentrating GHG emission responsibility on specific regions. In this context, we propose a regionalized approach that allocates GHG emissions based on electricity consumption rather than production. Utilizing data from the Korea Electric Power Corporation, the study estimates GHG emissions by energy source and considers electricity transfers between regions. The study results revealed that the responsibility for emissions from consumption is concentrated in cities that rely on coal-fired power generation. For example, Seoul, which supplied electricity from Chungnam where coal-fired power is the main source, has an emission factor of 633 kgCO2eq/kWh. In contrast, Gyeongbuk, which primarily produces electricity through nuclear power, has an emission factor of only 12 kgCO2eq/kWh. The findings reveal significant disparities in GHG emission factors across each region, highlighting the limitations of the current system and the need for more accurate regional emission assessments.

<p><strong>Background</strong>. Feeding cattle in small-scale silage-based dairy production systems can improve their production efficiency while reducing greenhouse gas emissions. <strong>Objective</strong>. To determine the effect of partial replacement of corn silage with sorghum silage on the concentration of secondary metabolites in terms of Total Phenols (TP), Total Tannins (TT), and Condensed Tannins (CT), as well as to estimate methane (CH4) and carbon dioxide (CO2) emissions. <strong>Methodology</strong>. The treatments were analyzed with a split-plot experimental design where the treatments (main plot) were; T1 = 50% sorghum silage cv Top Green + 50% corn silage, T2 = 50% sorghum silage cv Caña Dulce + 50% corn silage, T3 = 100% corn silage cv Cenzontle (control), and the measurement periods were the minor plots. <strong>Results</strong>. Inclusion of sorghum silage decreased enteric methane and carbon dioxide emissions (P<0.05), even though the concentration of phytochemical compounds among cultivars was not variable (P>0.05). <strong>Implications</strong>. Understanding the impact of changing forage chemical composition on reducing greenhouse gas (GHG) emissions in dairy systems is an important issue for mitigating climate change. <strong>Conclusions</strong>. The inclusion of sorghum silage in this study slightly reduced enteric methane and carbon dioxide emissions. Under these conditions, it is suggested that more information be provided on greenhouse gas emission factors and mitigation strategies in small-scale production systems.</p>

In the context of combating climate change, accurately evaluating the environmental impact of wastewater treatment is of great significance for sustainable development. This study centers on two methods for determining greenhouse gas emission factors in wastewater treatment. One approach calculates per-unit-volume emission factors by utilizing measured greenhouse gas data and the volume of treated water. When measured data are unavailable, an alternative method is adopted to obtain empirical values. Wastewater treatment plant A, with its relatively large scale and certain monitoring capabilities, can acquire partially measured data on greenhouse gas emissions from its treatment units. Thus, both the emission factor measurement method and the empirical value calculation method were utilized to analyze the greenhouse gas emission characteristics and compare the differences in accounting results. For this plant, the average measured values of CH₄ and N₂O emissions were 0.0304 kg CO₂-eq/m3 and 0.0343 kg CO₂-eq/m3, respectively. In contrast, the empirical values were 0.0505 kg CO₂-eq/m3 for CH₄ and 0.0711 kg CO₂-eq/m3 for N₂O. Wastewater treatment plant B, due to its smaller scale, currently lacks the conditions for on-site greenhouse gas measurement. Consequently, only the empirical value calculation method could be used to analyze its greenhouse gas emission characteristics. Its empirical CH₄ and N₂O values were 0.0645 kg CO₂-eq/m3 and 0.1135 kg CO₂-eq/m3, respectively.

The current research is focused on the introduction of a heat pump (HP)-assisted organic Rankine cycle (ORC), which runs on the heat extracted from a high-temperature borehole thermal energy storage (BTES). By varying different source temperatures from 40 °C to 60 °C, the HP cycle works to upgrade the heat to run the ORC. Different combinations of environmentally friendly fluids are studied in comparison to match the top and bottom cycles and to make the overall system a combined heat and power (CHP) system. A power sufficiency condition is defined to compare and identify the best working fluid combination for the HP cycle and ORC. Based on the analysis, ammonia for the HP and R1234zee for the ORC emerged to be a suitable combination among all the studied combinations. As an example, for a BTES heat source of 237 kW at the source temperature of 60 °C, the BTES–HP–ORC–district heating system with the ammonia–R1234zee pair has resulted in the HP compressor work input of 21.9 kW with the coefficient of performance (COP) of 10.9 for the HP cycle and the ORC net work output and district heating supply of 10.4 kW and 209 kW, respectively, with the thermal efficiency (η) of 4.3% for the ORC at the evaporation temperature of 65 °C. A study in terms of the greenhouse gas (GHG) emissions reveals the feasibility of the system depending on the regional GHG intensity and emission factor of electricity and natural gas.

Greenhouse gas emissions and mitigation strategies in China's municipal solid waste sector under the impact of the COVID-19 pandemic

An integral assessment of carbon and nitrogen emissions in dairy cattle production systems: Comparing dynamic process-based greenhouse gas emissions factors with IPCC Tier 1 and Tier 2 approaches in confinement and pasture-based systems

With the proposal of carbon neutrality goals, the high energy consumption and significant greenhouse gas emissions caused by traditional wastewater treatment processes have attracted widespread attention. Research on carbon emissions during wastewater treatment has become a hot topic. In this context, wastewater treatment plants need to achieve not only water resource sustainability but also carbon reduction. Precisely monitoring and evaluating the carbon emission levels of urban drainage systems and wastewater treatment plants, and scientifically proposing wastewater treatment carbon reduction paths and carbon neutrality models, are key breakthrough points for urban water pollution control to achieve the “carbon peak, carbon neutrality” goals, and are also the cutting-edge and focus of current environmental science and technology. This paper takes urban drainage systems and wastewater treatment plants as the main objects, summarizes the current research status of greenhouse gas emission monitoring and quantitative assessment, discusses and analyzes the main sources, emission status, and influencing factors of greenhouse gases in wastewater treatment plants.

The paper assesses fugitive emissions of greenhouse gases from the petroleum and coal industries of the Novosibirsk region. The authors compiled a database for calculations and justified the choice of conversion factors for greenhouse gas emissions in accordance with recommendations of the Intergovernmental Panel on Climate Change and the Russian Ministry of Natural Resources. The dynamics analysis of production, primary processing and transportation of raw materials in oil and gas and coal industries of the Novosibirsk region was carried out, location map of the main industrial facilities and pipelines was compiled, the main sources of greenhouse gas emissions were identified, and the uncertainty ranges of calculations were presented. It is shown that the main source of fugitive emissions in the region is an open-pit coal mining and its subsequent transportation. Moreover, a significant amount of emissions is created during gas transportation via main pipelines and gas distribution.

Abstract To promote the sustainable development of urban rail transit (URT) in China, it is necessary to quantitatively analyze the greenhouse gas (GHG) emissions and its internal driving factors. Based on the LMDI algorithm, this research constructs an assessment model and makes a quantitative analysis of internal driving factors for GHG emissions in the operational phase of the URT system in China. According to the official investigated data, the GHG emission of URT in the operational phase is between 600 × 104 and 2000 × 104 tons of carbon dioxide equivalent (CO2e) per year from 2012 to 2023. The results of the driving factors decomposition showed that the passenger demand intensity was the key and positive factor affecting carbon emissions in the operational phase and the contribution rate was 12.93%–60.81% from 2013 to 2023. Therefore, it is necessary to formulate targeted policies in terms of management and technical means to reduce the average traveling distance demanded by passengers and reasonably control the scale of the line network for GHG reduction in the Chinese URT system.

Agricultural greenhouse gas emission reduction plays an important role in addressing global climate warming. Researching and revealing the spatial and temporal characteristics, as well as the influencing mechanisms of agricultural greenhouse gas emissions, is of great significance for achieving the goals of green and low-carbon development in agriculture. This study examines the agricultural greenhouse gas emissions from 31 provinces （municipalities, autonomous regions） in China from 2000 to 2020. Through the use of geographic detectors, spatial econometric analysis, and other methods, it explores the spatiotemporal evolution characteristics and driving factors of agricultural greenhouse gas emissions. The results indicated the following： ① From 2000 to 2020, agricultural greenhouse gas emissions in China showed a development process of "slow increase - sharp increase - sharp decrease." ② The spatial heterogeneity of agricultural greenhouse gas emissions was significant, forming three high emission areas in space： the central high emission area centered on Henan, the southern high emission area centered on Guangdong, and the southwestern high emission area centered on Sichuan. The center of gravity showed a trend of shifting northward and westward. ③ Rural population, regional gross domestic product, and agricultural output value were the dominant driving factors causing spatial heterogeneity of agricultural greenhouse gas emissions. ④ Agricultural greenhouse gas emissions had spatial spillover effects. When formulating agricultural greenhouse gas reduction targets, it is necessary to adopt a coordinated control strategy among different regions.

Objective: Currently, methane (CH4) emissions from rice cultivation in Malaysia are calculated using the regional’s methane emission factor (EF) of 1.60 kg CH₄ ha⁻¹ day⁻¹, as Malaysia has not yet developed a national emission factor. The objective of this study is to generate a country-specific EF of CH4 emission from rice cultivation in Malaysian rice fields. The EF generated would then be used in future emission estimates and the country’s greenhouse gas (GHG) inventory reports to the United Nations Framework Convention on Climate Change (UNFCCC). Theoretical Framework: The establishment of a national GHG emission factor for rice cultivation in Malaysia is critical for accurate GHG inventory reporting and effective climate change mitigation. This study utilizes the Intergovernmental Panel on Climate Change (IPCC) guidelines to derive a country-specific emission factor, enhancing Malaysia’s compliance with international climate obligations and promoting sustainable agricultural practices. Method: A new national EF was developed from eleven rice planting seasons in rice granary areas (IADA Pulau Pinang, IADA Barat Laut Selangor, MADA and KADA) and non-granary area (Sik, Kedah). The EF was calculated from methane emissions from the new data sets, published journals and unpublished data from MARDI. For the new data set, methane gas (CH4) was measured using a static chamber method (Minamikawa et al., 2015). Sampling of GHG from the gas chamber is carried out in the field every 2 weeks and gas was analysed by a GC System Agilent 7890A gas chromatography. The daily methane flux and methane emission follow the methods by Habib et al. (2007), Fauzi et al. (2023) and the Guidelines for National Greenhouse Gas Inventories for Cropland (IPCC, 2006a). Results and Discussion: The national EF calculated from CH4 gas emissions over eleven rice planting seasons in Malaysia between 2012-2024 was 1.80 kg CH4 ha-1 day-1, which is higher than the current regional EF used (1.60 kg CH4 ha-1 day-1). However, the value is within the range of the default value of 1.30 kg CH4 ha-1 day-1 by the Intergovernmental Panel on Climate Change (IPCC) 2006 and 2.00 kg CH4 ha-1 day-1 (IPCC, 1996). Research Implications: The use of this new EF resulted in 12.49% increase in the national GHG inventory from the rice cultivation sub-sector as compared to using the current regional EF. This initiative is part of a comprehensive plan to enhance and strengthen GHG inventory reporting for Malaysia's agriculture sector, aiming to meet IPCC requirements and progress to Tier 2 status.