Quantifying Greenhouse Gas Research Articles

Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning

Artificial Intelligence (AI) tools based on Machine learning (ML) have demonstrated their potential in modeling climate-related phenomena. However, their application to quantifying greenhouse gas emissions in cities remains under-researched. Here, we introduce a ML-based bottom-up framework to predict hourly CO2 emissions from vehicular traffic at fine spatial resolution (30 × 30 m). Using data-driven algorithms, traffic counts, spatio-temporal features, and meteorological data, our model predicted hourly traffic flow, average speed, and CO2 emissions for passenger cars (PC) and heavy-duty trucks (HDT) at the street scale in Berlin. Even with limited traffic information, the model effectively generalized to new road segments. For PC, the Relative Mean Difference (RMD) was +16% on average. For HDT, RMD was 19% for traffic flow and 2.6% for average speed. We modeled seven years of hourly CO2 emissions from 2015 to 2022 and identified major highways as hotspots for PC emissions, with peak values reaching 1.639 kgCO2 m−2 d−1. We also analyzed the impact of COVID-19 lockdown and individual policy stringency on traffic CO2 emissions. During the lockdown period (March 15 to 1 June 2020), weekend emissions dropped substantially by 25% (−18.3 tCO2 day−1), with stay-at-home requirements, workplace closures, and school closures contributing significantly to this reduction. The continuation of these measures resulted in sustained reductions in traffic flow and CO2 emissions throughout 2020 and 2022. These results highlight the effectiveness of ML models in quantifying vehicle traffic CO2 emissions at a high spatial resolution. Our ML-based bottom-up approach offers a useful tool for urban climate research, especially in areas lacking detailed CO2 emissions data.

Quantification Of Greenhouse Gas Emissions in a Cement Company and System Dynamics Modeling Toward Carbon Neutral

The cement industry is one of the sectors that produces carbon dioxide (CO2) emissions due to its raw material processing and energy requirements. CO2, as a greenhouse gas (GHG) emission, contributes to global warming, leading to environmental, health, and economic losses. To address these issues, Indonesia is committed to reducing GHG emissions in the industrial sector by 2050. To effectively plan for the reduction of GHG emissions generated by companies, this study aims to quantify emissions from a cement company, representing the cement industry in Indonesia, to understand the current state of the company's carbon footprint and identify feasible mitigation measures. The cement industry utilizes a GHG quantification system to calculate emissions from raw material processing, thermal energy consumption, and electricity purchases. The calculation results from a cement company are used for system dynamics modeling with Vensim PLE software for the period from 2021 to 2050, under business-as-usual (BAU) conditions with various emission reduction strategies. The results show that GHG emissions under BAU conditions with emission reduction strategies do not achieve carbon neutrality by 2050. More intensive adoption of decarbonization technologies, research on process optimization, and government policies such as carbon taxes and carbon trading are required to achieve carbon neutral goals.

Assessing the carbon footprint of marginal and smallholders farming systems: A typology driven approach

Agriculture is a significant contributor to greenhouse gas (GHG) emissions, with practices such as fertilizer application, soil tillage, and livestock management releasing carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4). To meet the demands of a growing population, it is essential to identify agricultural practices that boost food production while simultaneously reducing greenhouse gas emissions, contributing to climate change mitigation and adaptation. This study aimed to quantify GHG emissions from various farm typologies of marginal and smallholder households in the western regions of Tamil Nadu, India, using the Cool Farm Tool (CFT). Data was collected from 250 households in Coimbatore, Tiruppur, and Erode districts during 2022-2023 and farm typologies were identified through multivariate analysis, revealing four farm types: (i) cereal crop-dominated marginal farms, (ii) livestock-dominated marginal farms, (iii) cash crop-dominated marginal farms, and (iv) plantation crop-dominated small farms. The results show that cash crop and plantation crop dominated farms had the highest emissions, particularly from crop residue burning, fertilizer production and fertilizer application. In contrast, cereal crop-dominated farms recorded lower emissions. Livestock dominated farm type exhibited higher GHG emission from enteric fermentation and manure management due to higher number of livestock. The results of this study highlight the importance of developing farm-specific mitigation strategies to reduce emissions. The study also underscores the value of using tools such as CFT for comprehensive GHG quantification to ensure sustainable agricultural practices.

Towards Supporting Satellite Design Through the Top-Down Approach: A General Model for Assessing the Ability of Future Satellite Missions to Quantify Point Source Emissions

Monitoring and accurately quantifying greenhouse gas (GHG) emissions from point sources via satellite measurements is crucial for validating emission inventories. Numerous studies have applied varied methods to estimate emission intensities from both natural and anthropogenic point sources, highlighting the potential of satellites for point source quantification. To promote the development of the space-based GHG monitoring system, it is pivotal to assess the satellite’s capacity to quantify emissions from distinct sources before its design and launch. However, no universal method currently exists for quantitatively assessing the ability of satellites to quantify point source emissions. This paper presents a parametric conceptual model and database for efficiently evaluating the quantification capabilities of satellites and optimizing their technical characteristics for particular detection missions. Using the model and database, we evaluated how well various satellites can detect and quantify GHG emissions. Our findings indicate that accurate estimation of point source emissions requires both high spatial resolution and measurement precision. The requirement for satellite spatial resolution and measurement precision to achieve unbiased emission estimation gradually decreases with increasing emission intensity. The model and database developed in this study can serve as a reference for harmonious satellite configuration that balances measurement precision and spatial resolution. Furthermore, to progress the evaluation model of satellites for low-intensity emission point sources, it is imperative to implement a more precise simulation model and estimate method with a refined mask-building approach.

Tidal influence on carbon dioxide and methane fluxes from tree stems and soils in mangrove forests

Abstract. Mangroves are critical blue carbon ecosystems. Measurements of methane (CH4) emissions from mangrove tree stems have the potential to reduce uncertainty in the capacity of carbon sequestration. This study is the first to simultaneously measure CH4 fluxes from both stems and soils throughout tidal cycles. We quantified carbon dioxide (CO2) and CH4 fluxes from mangrove tree stems of Avicennia marina and Kandelia obovata, which have distinct root structures, during tidal cycles. Tree stems of both species served as net CO2 and CH4 sources. Compared to fluxes in the soils, the mangrove tree stems exhibited remarkably lower CH4 fluxes but no difference in CO2 fluxes. The stems of A. marina exhibited an increasing trend in CO2 flux from low to high tides. However, CH4 fluxes showed high temporal variability, with the stems of A. marina functioning as a CH4 sink before tidal inundation and becoming a source after ebbing. In contrast, the stems of K. obovata showed no consistent pattern in the CO2 or CH4 fluxes. Based on our findings, the stem CH4 fluxes in A. marina may vary by up to 1200 % when considering tidal influence, compared to when tidal influence is ignored. Therefore, sampling only during low tides might underestimate stem CO2 and CH4 fluxes on a diurnal scale. This study highlights the necessity of considering tidal influence and species when quantifying greenhouse gas (GHG) fluxes from mangrove tree stems. Further study is needed to explore the underlying mechanisms driving the observed flux variations and improve the understanding of GHG dynamics in mangrove ecosystems.

Preparing for net zero greenhouse gas emissions in 2050: lifecycle emissions of dairy products in Brazil

Dairy products play an important role in human nutrition and the world economy. Livestock farming, including cows rearing to produce milk and dairy products, is one of the world's major sources of greenhouse gas emissions. Progress towards net zero goals requires monitoring emissions from companies and products, and greenhouse gas inventories are essential. This work quantifies greenhouse gas emissions from milk production, considering the milk delivered at the farm gate and the milk delivered at the cooperative gate. Emissions accounting was based on greenhouse gas inventories for two units and lifecycle emissions for major farm inputs. Results have shown that milk production on the farm emits 0.57 kg CO2e / liter, with enteric fermentation accounting for more than 90% of emissions at the farm gate, and more than 50% at the milk processing unit gate. Dairy production adds 0.533 kg CO2e / liter to the emissions coming from raw milk, most of which comes from wastewater treatment. Thus, the footprint of dairy products is 1.103 kg CO2e / liter of processed milk. The producers' cooperative's greenhouse gas emissions are essentially indirect and amount to 0.626 kg CO2e/liter of milk delivered to customers, in which emissions from purchased milk account for more than 85% and emissions from transportation account for around 15%.

Applying trade mechanisms to quantify dynamic GHG emissions of electricity consumption in an open economy - The case of Switzerland

Applying trade mechanisms to quantify dynamic GHG emissions of electricity consumption in an open economy - The case of Switzerland

Preliminary Results on the Use of Straw Cover and Effective Microorganisms for Mitigating GHG and Ammonia Emissions in Pig Slurry Storage Systems

Spain has been the largest pork producer in the EU in recent years, leading to significant pig slurry (PS) production that requires proper management to prevent environmental impacts. The objectives of this study were to quantify greenhouse gas (GHG) and ammonia emissions and to characterize the PS in storage pond systems. A straw cover pond (SP) and addition of effective microorganisms (EMs) in a biological pond (BP) were used to treat the slurries. During two periods (autumn and spring), PS was characterized and GHG (CO2, CH4, N2O) and NH3 emissions were measured with a dynamic chamber. After 5 weeks of storage, BP achieved a reduction of 96% for CO2, 98% for CH4 and 59% for NH3 compared to the control pond (CP) in spring, while SP presented a 74% reduction for CO2 in autumn, and 60% and 97% reductions for CH4 and NH3, respectively, in spring. Additionally, the PS samples showed a decreasing trend for EC, dry matter, COD, BOD5, total N, NH4+-N, Org.-N, NO3−-N, and PO43− during both seasons. This preliminary study shows promise in reducing GHG/NH3 emissions and improving PS properties, but further replication is recommended. Varying straw cover thickness, optimizing EM dose, and a pH reduction may enhance outcomes.

Bio-organic substitution in tobacco (Nicotiana tabacum L) cultivation: Optimum strategy to lower carbon footprint and boost net ecosystem economic benefit

The partial substitution of organic manure for chemical nitrogen fertilizers, known as organic substitution, is widely regarded as a cleaner and more sustainable production strategy. However, few studies have quantified greenhouse gas emissions, product income and net ecosystem economic benefit (NEEB) using a life cycle assessment (LCA) approach, particularly for typical tobacco (Nicotiana tabacum L.) production. Here, we quantified the yield and quality of a typical tobacco production in Qujing, Yunnan, China, through field experiments and calculated its carbon footprint and NEEB using the LCA approach. Four organic substitution strategies were established with equal nitrogen inputs, including synthesized chemical fertilizer (SN), farmyard organic manure (NF), commercial organic manure (NC), and bio-organic (Trichoderma viride Pers.) manure (NT), each substituting 15% of synthesized nitrogen fertilizer. Compared to the SN strategy, the NT strategy significantly increased yield and income by 10.3% and 9.6%, respectively. In contrast, the NF strategy significantly reduced income, while the NC strategy showed no significant difference. Both the NC and NT strategies significantly reduced N2O cumulative emissions (by 15.9% and 8.0%, respectively), increased δSOC (by 38.4% and 15.0%, respectively), and decreased carbon footprint compared to the SN strategy. However, the NF strategy significantly increased the income-scaled carbon footprint, even though it also notably reduced N2O cumulative emissions (by 22.6%) and increased δSOC (by 7.9%). The NT strategy achieved a win-win scenario of low environmental risk and high economic returns of tobacco production with significantly increased NEEB (by 10.6%) compared to the SN strategy (37.60×103 CNY yr-1). This suggests that the bio-organic Trichoderma manure substituting 15% synthesized nitrogen fertilizer is the best organic substitution strategy for sustainable tobacco production.

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.

Ancillary Benefit of Microbiology Culture Diagnostic Stewardship: Decreasing Healthcare’s Climate Impact

Abstract We calculated weights of blood, urine, and endotracheal tube culture supplies and quantified greenhouse gas emissions emitted for disposal of these supplies. Of note, disposal related emissions for a positive blood and endotracheal tube culture are each equivalent to driving 0.6 and 0.4 miles, respectively, in a gasoline-powered vehicle.

Accounting for Carbon Emissions Among Large U.S. Companies: Does Materiality Matter

This paper investigates carbon emissions materiality with regards to financial statements and investigates potential methods of accounting for carbon emission rights. We investigate whether some of the largest U.S. companies should be required to discuss and quantify greenhouse gas emissions, as defined by the GHG Protocol, in the required 10-K annual report. Our analysis uses a new metric, based on social carbon cost, that suggests social cost of carbon emissions could be material, and supports the need for transparent accounting of the financial impact of carbon emissions in the required 10-K annual report. We searched each company’s 10-K for information on climate change and emissions-related disclosures. We found that while most companies acknowledge climate change as a risk factor, their 10-K narratives do not discuss or explain the impact of emissions on financial performance. Our findings suggest that climate-related factors are not being appropriately captured in current 10-Ks despite increasing calls for greater transparency on climate-related exposure, raising concerns that investors are not receiving the appropriate information necessary to evaluate investments. Providing such information would allow investors to gain a better understanding of company risks, and enhance their ability to make better investment choices.

Integration of anaerobic co-digestion of grass silage and cattle slurry within a livestock farming system in Ireland: Quantification of greenhouse gas emission reduction and nutrient flow

Integration of anaerobic co-digestion of grass silage and cattle slurry within a livestock farming system in Ireland: Quantification of greenhouse gas emission reduction and nutrient flow

Rapidly increased greenhouse gas emissions by Pacific white shrimp aquacultural intensification and potential solutions for mitigation in China

Rapidly increased greenhouse gas emissions by Pacific white shrimp aquacultural intensification and potential solutions for mitigation in China

Quantifying greenhouse gas emissions mitigation potential in China's agricultural plastic greenhouses

To promote sustainable intensification and provide guidance for decisionmakers, we must understand the potential for mitigating greenhouse gas emissions in greenhouse cultivation. Therefore, this study aimed to evaluate the greenhouse gas emission mitigation potential of agricultural plastic greenhouses in China using a combination of life cycle assessment, data envelopment analysis, and scenario analysis. We found that: (1) In China, the mean mitigation potential for greenhouse gas emission intensity related to the crop production inputs of agricultural plastic greenhouses is 1.67 kt CO2-eq/km2, demonstrating a remarkable mitigation rate of 47%. This mitigation potential, driven mostly by fertilizer use, exhibited a spatial pattern characterized by high mitigation rates in the southern regions compared to those in the northern regions; (2) in scenarios S1 and S2, the greenhouse gas emission intensity mitigation potential of greenhouse construction materials was 0.645 kt CO2-eq/km2 and 0.968 kt CO2-eq/km2, respectively, with steel being the primary contributor to mitigation; (3) under scenarios S1 and S2, the greenhouse gas emission mitigation rates for China's agricultural plastic greenhouses were 42% and 48%, respectively. This study highlights the greenhouse gas emission mitigation potential of China's agricultural plastic greenhouses. To ensure sustainability in plastic greenhouses, emphasis should be placed on optimizing fertilizers and extending the lifespan of construction materials.

A Methodology to Evaluate GHG Emissions for Large Sports Events

Determining whether a large sports event is sustainable or not is one of the main objectives of the sports industry in the coming years. Indeed, there are several sources of greenhouse gas (GHG) emissions within a sports event that are not directly controlled by the sports companies but are linked to the event itself. The literature does not offer a standardized methodology for calculating the CO2 emissions of sports events, and consequently, there are different approaches. The objective of this article is to provide an updated state-of-the-art on the topic and to propose an innovative methodology for the calculation of Greenhouse Gas emission of a large sport event. The methodology entails the analysis of purchased goods and services, fuel and energy consumption, waste generation, business travel, and the impact of accommodations. Within the analysis, tools are provided to calculate carbon emissions for each category based on easily understandable data and utilizing reference conversion factors. The research presented in this paper may be useful for professionals in the sector in identifying a comprehensive methodology to quantify greenhouse gas (GHG) emissions for a large sports event.

Synergies from off-gas analysis and mass balances for wastewater treatment — Some personal reflections on our experiences

Looking back at over a decade of research by herself and her group, the author advocates the added value of gas phase measurements and the application of mass balances, as well as the synergetic benefits obtained when combining both. The increased application of off-gas measurements for greenhouse gas emission monitoring offers a great opportunity to look at other components in the gas phase, particularly oxygen. Mass balances should not be strictly reserved for modellers but also prove useful while conducting lab experiments and studying full-scale measurement data. Combining off-gas measurements with mass balances may serve not only to quantify greenhouse gas emission factors and aeration efficiency but also to follow dynamic concentration profiles of dissolved components without dedicated sensors and/or to calculate other unmeasured variables. Mass-balance-based data reconciliation allows for obtaining reliable and accurate data, and even more when combined with off-gas analysis.

Carbon reserves on the soils of the Dmitrievsky village council of the Ufa district of the Republic of Bashkortostan

The research was carried out within the framework of the state task of the Ministry of Education and Science of the Russian Federation “Program for the creation and operation of a carbon landfill in the Republic of Bashkortostan “Eurasian carbon landfill” for 2022-2023 (Publication number: FEUR-2022-0001). Carbon deposition in the soil is an essential function arising from the interaction of ecological processes. Human activity influencing these processes leads to dehumidification or, conversely, deposition of soil carbon. The article presents the materials of the analysis of literary sources on the subject of carbon farming, as well as the content of organic matter in the soils of agricultural lands of the southern forest-steppe of the Republic of Bashkortostan in the conditions of a carbon landfill in the Ufa district (Russian Federation). This study aims to analyse carbon reserves in the humus-accumulative soil horizon of a carbon landfill on agricultural lands in the Dmitrievsky Village Council of the Ufa district of the Republic of Bashkortostan. An agrochemical analysis of the accumulation of soil organic matter was carried out, and the capacity of the humus horizon of the soils of this site was determined. Carbon reserves in the studied soils were determined according to the methodology for quantifying greenhouse gas emissions and uptake [Order of the Ministry of Natural Resources of Russia No. 371 dated 05/27/2022, Guidelines for Quantifying the volume of greenhouse gas uptake]. The carbon content in the organic matter of soils is assumed to equal 58%. The conversion to the stock of soil carbon was carried out, considering the density of the soil composition. The degree of saturation of the soils of the studied sites, including the carbon landfill, is calculated. The reserves of organic carbon under individual varieties of soils in the humus-accumulative horizon - 4616360 tons were estimated.

An assessment of the environmental sustainability of beef production in Canada

This study assessed the environmental impacts of beef cattle production and their effects on the overall sustainability of Canadian beef production. Cradle to farm gate, cradle to processor’s gate, and cradle to consumer plate life cycle assessments were carried out to quantify greenhouse gases (GHG), resource use (i.e., water, land, and fuel), and potential water and air pollution (i.e., freshwater eutrophication, terrestrial acidification, and photochemical oxidants formation). Across the production chain, feed production had the greatest impact on most environmental indicators. The GHG intensity without dairy meat was estimated as 10.4 kg CO2-eq per kg of live weight (LW), corresponding to 32.8 kg CO2-eq per kg of consumed boneless beef. Including dairy meat reduced GHG intensity by 5.8% (0.6 kg CO2-eq kg LW–1) compared to when it was excluded. Other environmental metrics per kg of LW were 657 L, 38.7 m2 annual crop-eq, 0.4 kg oil-eq, 2.6 kg P-eq, 115.9 kg SO2-eq, and 8.7 kg NOx-eq for water use, land use, fossil fuel use, freshwater eutrophication, terrestrial acidification, and photochemical oxidants, respectively. Data provide benchmarks for use in future regional and national assessments that are designed to encourage the adoption of sustainable management practices that can lower the environmental footprint of Canadian beef production.

A Greenhouse Gas Budget for Mexico During 2000–2019

AbstractApplication of the best available science to improve quantification of greenhouse gas (GHG) emissions at regional and national scales is key to climate action. Here, we present a two‐decade (2000–2019) GHG (CO2, CH4, and N2O) budget for Mexico derived from multiple products. Data from the National GHG Inventory, global observations, and the scientific literature were compared to identify knowledge gaps on GHG flux dynamics and discrepancies among estimates. Total mean annual GHG emissions were estimated at 695–910 TgCO2‐eq year−1 over these two decades, with 70% of the emissions attributable to CO2, 23% to CH4, and 5% to N2O (2% to other gases). When divided by sectors, we found agreement across emission estimates from various sources for fossil fuels, cattle, agriculture, and waste for all GHGs. However, considerable discrepancies were identified in the fluxes from terrestrial ecosystems. The disagreement was particularly large for the land CO2 sink, where net biome production estimations from the national inventory were double those from any other observational product. Extensive knowledge gaps exist, mainly related to aquatic systems (e.g., outgassing in rivers) and the lateral fluxes (e.g., wood trade). In addition, limited information is available on CH4 emissions from wetlands and soil CH4 consumption. We expect these results to guide future research to reduce estimation uncertainties and fill the information gaps across Mexico.