Greenhouse Gas Assessment Research Articles

Energy use and greenhouse gas emissions in selected tea factories in Kenya

Tea sector is a major contributor to Kenya’s economy through foreign exchange via export. However, extensive amount of energy is required to produce one kilogram of tea, making tea processing energy-intensive. Comparing greenhouse gas emissions from different types of energy consumed in tea factories is imperative to enable policymakers make informed intervention in emission reduction. Reducing greenhouse gas emissions in tea factories is one of the pathways to meeting Kenya’s nationally determined 32% reduction of carbon emissions by 2030 and commitment to the Paris Agreement. This paper assesses greenhouse gas emissions from different sources of energy used in four tea factories in Kenya. The Intergovernmental Panel on Climate Change emission factor is used to calculate the total emissions of each type of energy used for 5 years. Life cycle assessment using SimaPro 8 software, Eco-indicator 99 method and Eco invent database was used to assess the specific compound causing the emission. The findings reveal that the 5-year greenhouse gas emissions by biogas, solar, wood, briquettes, and electricity are 336.111, 7.108, 3057.729, and 1,338.28 kg CO2/MWh, respectively. Firewood has the highest concentration of carbon dioxide, while solar energy has the least. Analysis of variance confirms significant difference (0.05>p = 0.0272) in greenhouse gas emissions from the different energy sources. Post-hoc analyses shows a significant difference in emissions between solar and firewood (p<0.0125) and no significant difference between other sources of energy. The key environmental hotspot is the energy intensive processes such as drying involved in tea production and processing, which leads to consumption of fossil fuel in the factories. To reduce such key hotspot, switching to renewable energy sources is key. Sustainability in the tea sector can therefore be achieved through switching to macadamia briquettes as a source of thermal energy and a combination of electricity and solar for electrical energy.

Evaluation of greenhouse gas emission and reduction potential of high-food-waste-content municipal solid waste landfills: A case study of a landfill in the east of China

This study proposes a comprehensive evaluation method based on a two-stage model to assess greenhouse gas (GHG) emissions and reductions in high-food-waste-content (HFWC) municipal solid waste (MSW) landfills. The proposed method considers typical processes such as fugitive landfill gas (LFG), LFG collection, flaring, power generation, and leachate treatment. A case study of an HFWC MSW landfill in eastern China is considered to illustrate the evaluation. The findings revealed that the GHG emissions equivalent of the case landfill amounted to 21.23 million tons from 2007 to 2022, averaging 1.03 tons CO2-eq per ton of MSW. There was a potential underestimation of LFG generation at the landfill site during the initial stages, which led to delayed LFG collection and substantial fugitive LFG emissions. Additionally, the time distribution of GHG emissions from HFWC MSW was significantly different from that of low-food-waste-content (LFWC) MSW landfills, with peak emissions occurring much earlier. Owing to the rapid degradation characteristics of HFWC MSW, the cumulative LFG production of the landfill by 2022 (2 years after the final cover) was projected to reach 77 % of the total LFG potential. In contrast, it would take until 2030 for LFWC MSW landfills to reach this level. Furthermore, various scenarios were analyzed, in which if the rapid LFG generation characteristics of HFWC MSW are known in advance, and relevant facilities are constructed ahead of time, the collection efficiency can be improved from 31 % to over 78 %, resulting in less GHG emissions.

An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping

Accurate spatio-temporal information on rice cropping patterns is vital for predicting grain production, managing water resource and assessing greenhouse gas emissions. However, current automated mapping of rice cropping patterns at regional scale is heavily constrained by insufficient training samples and frequent cloudy weathers in major rice-producing areas. To tackle this challenge, we proposed a Phenology domain Optical-SAR feature inTegration method to Automatically generate single (SC-Rice) and double cropping Rice (DC-Rice) sample (POSTAR) for efficient and refined rice mapping. POSTAR includes three major steps: (1) generating a potential rice map using a phenology- and object-based classification method with optical data (Sentinel-2 MSI) to select candidate rice samples; (2) employing K-means to identify SC- and DC-Rice candidate samples according to unique SAR-based (Sentinel-1 SAR) phenological features; (3) implementing a two-step refinement strategy to filter high-confidence SC- and DC-Rice samples, maintaining a balance between intraclass phenological variance and sample purity. Test areas selected for validation include the Dongting Lake plain and Poyang Lake plain in South China, as well as Fujin county located in the Sanjiang plain of North China. POSTAR proved effective in producing reliable SC- and DC-Rice samples, achieving a high spectral correlation similarity (>0.85) and low dynamic time wrapping distance (<8.5) with field samples. Applying POSTAR-derived samples to random forest classifier yielded an overall accuracy of 89.6%, with F1 score of 0.899 for SC-Rice and 0.938 for DC-Rice in the Dongting Lake plain. Owing to the incorporation of knowledge-based optical and SAR phenological features, POSTAR exhibited strong spatial transferability, achieving an overall accuracy of 96.0% in the Poyang Lake plain and 97.8% in the Fujin county. These results demonstrated the effectiveness of the POSTAR method in accurately mapping rice cropping patterns without extensive field visits, providing valuable insights for crop monitoring in large, diverse, and cloudy regions through the integration of optical and SAR data.

Assessing Greenhouse Gas Emissions and Methane Production During Post-Landfill Maintenance in Kish Island: A LandGEM Simulation Approach

Background: Municipal solid waste (MSW) landfills are significant contributors to the emission of greenhouse gases, particularly methane, during the breakdown of waste materials. Researchers have undertaken extensive investigations into quantifying methane emissions from landfills, utilizing various methodologies beyond reliance on the LandGEM model. Numerous studies have underscored the efficacy of this model in predicting methane generation and exploring its utility in activities such as energy generation and emission mitigation strategies. Objectives: Municipal solid waste landfills are vital contributors to greenhouse gas emissions, notably methane, during waste decomposition. Significant research has focused on estimating methane output from landfills, utilizing various approaches beyond the LandGEM model. Studies highlight the model's potential in assessing methane generation and its relevance to activities like energy generation and emission management. Methods: The LandGEM simulation model is employed to forecast future waste generation and provide valuable insights into the environmental consequences of landfill management on the island. By analyzing population data and waste generation statistics from 2023 to 2042, the study utilizes the LandGEM software to estimate methane emissions, incorporating site-specific data and waste composition analysis. Results: The findings reveal that 36% of the total waste on Kish Island consists of putrescible material, with food waste being a significant component. Over the study period, approximately 1,282,637 tons of waste are projected to be disposed of in the Kish landfill. The LandGEM model predicts the highest landfill gas emission in 2043, primarily methane, along with carbon dioxide and non-metallic organic compounds. The estimated quantities for these gases in 2043 are 5.415E+03, 1.486E+04, and 2.327E+02 metric tons, respectively. Conclusions: This research highlights the importance of tailored waste management strategies to mitigate environmental impacts and emphasizes the need for efficient gas collection systems. A proposed gas collection system combining vertical wells, horizontal trenches, and under-membrane pipes is discussed to enhance efficiency and reduce environmental risks. The study provides valuable insights into waste management and landfill gas emissions on Kish Island, underscoring the significance of accurate emission prediction and effective management to minimize environmental consequences and optimize the utilization of renewable energy resources.

Revealing Greenhouse Gas Emission and Nitrogen Fertilizer Destination: A Case Study in Chengdu Plain Cultivation Industry

The cultivation industry occupies a large proportion of greenhouse gas emissions in agriculture. Assessing greenhouse gas emissions from the cultivation industry is pivotal for mitigating emissions and promoting sustainable cultivation. Utilizing greenhouse gas emission calculation methods recommended by the Intergovernmental Panel on Climate Change (IPCC) and other methods, this work evaluated annual emissions and the emission structure of major crops from 2005 to 2021 in the Chengdu Plain, a significant agricultural region in Southwest China. We identified nitrogen fertilizer as the primary contributing factor to high emissions from cultivation production. Subsequently, we analyzed the trend and utilization of nitrogen fertilizer, which proposes essential strategies for reducing greenhouse gas emissions. The results showed that greenhouse gas (GHG) emissions from the cultivation industry in the Chengdu Plain exhibited a growth, fluctuation, and eventual decline trend from 2005 to 2021. The emissions increased from 5,148,900 t in 2005 to 6,289,700 t in 2009, representing a 22.16% increase, and subsequently decreased to 5,109,900 t in 2021, marking a 23.31% decrease. Nitrogen fertilizer application emerges as the primary source of GHG emissions, constituting approximately half of the total, with nitrogen fertilizer manufacturing contributing significantly as well, collectively amounting to about 70%. We also found that the proportion of greenhouse gas emissions attributed to cash crop cultivation has gradually increased over the last decade. Among these crops, vegetables exhibit the highest emissions, comprising nearly half of the total emissions from 2019 onwards. However, the nitrogen fertilizer use efficiency of cash crops is less than 30%, with higher nitrogen surplus, ammonia volatilization, and nitrogen leaching per unit area, and the total amount is higher than that of grain crops. Among cash crops, vegetables exhibit the highest amount of nitrogen surplus, ammonia volatilization, and nitrogen leaching, constituting nearly half of the total amount in the study area since 2019. Our findings significantly affect sustainable and low-carbon cultivation industry development in the study area.

Reflections on the Consideration of Greenhouse Gas Emissions in Environmental Impact Assessment

Abstract Environmental impact assessment (EIA) involves assessing the implications of proposed activities on the environment to inform decisions about whether those actions should proceed and under what conditions. Efforts are being made to incorporate climate change considerations into EIA internationally, but the assessment of greenhouse gas (GHG) emissions poses particular challenges. This article compares the incorporation of GHG emissions into EIA in two jurisdictions: Canada (under the Impact Assessment Act 2019) and Western Australia (under the Environmental Protection Act 1986). Four questions are considered, relating to screening and scoping; information requirements; decision-making and condition setting; and post-approval activities. Key differences between the two jurisdictions were found in relation to screening and scoping (Western Australia applies an emissions threshold while Canada utilizes a project list coupled with tailored guidelines); decision-making (Western Australia generally considers a straight line trajectory to net zero by 2050 as acceptable whereas Canada considers emissions in the context of international commitments and against other sustainability considerations); and post-approval activities (a strength of the Western Australian system is mechanisms enabling review and tightening of GHG conditions over time). It will be important to continue to review the effectiveness of EIA as a tool for climate mitigation as practice evolves.

Three years of CO2, CH4 and N2O fluxes from different sheepfolds in a semiarid steppe region, China

To better assess greenhouse gas (GHG) emissions from livestock folds in semi-arid steppe zones and reduce uncertainties in regional and national GHG emission inventories, we measured the fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) from sheepfolds under contrasting management regimes (i.e., summer sheepfolds under continuous and rotational grazing strategies and the winter sheepfold) for 3 consecutive years. Our results showed that these GHG fluxes had high intra-annual and interannual variations, emphasizing the importance of multi-year measurement for achieving temporally representative annual budgets. Sheep presence and temperature appeared to be the key factors driving CH4, CO2 and N2O fluxes from sheepfolds, e.g., higher GHG emissions usually occurred in seasons with sheep presence. However, the sheepfold type exerted a distinct influence on the temperature sensitivity of GHG fluxes, i.e., the Q10 values for GHG fluxes were generally higher in summer sheepfolds than in winter sheepfold. The annual CH4, CO2 and N2O emissions for the 3 sheepfolds were estimated to be 1.5–16.5 kg C ha−1 yr−1 (or 1.9–2.6 g C yr−1sheep−1), 8.6–16.0 t C ha−1 yr−1 (or 5.1–6.6 kg C yr−1sheep−1) and 28.3–41.9 kg N ha−1 yr−1 (or 19.0–26.8 g N yr−1sheep−1), respectively. Averaging across the 3 years, the annual net GHG emissions (CH4 + CO2 + N2O) for all sheepfolds ranged from 47 to 71 t CO2-eq ha−1 yr−1 (or 27–36 kg CO2-eq yr−1 sheep−1), of which CO2 and N2O emissions contributed the most; moreover, the annual net GHG emissions had no significant differences between sheepfold types or grazing strategies. Given that local steppe soils have a lower magnitude of soil respiration (CO2) and N2O emissions and are also net sink for atmospheric CH4, the sheepfold sites in this region are undoubtedly one of the significant hotspots for GHG emissions and could be key areas to focus mitigation action.

Assessment of Ammonia Emissions and Greenhouse Gases in Dairy Cattle Facilities: A Bibliometric Analysis.

A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April 2024) were reviewed. Publications notably increased from 1997, with the highest number of papers published in 2022. Research mainly focuses on ammonia and methane emissions, including quantification, volatilization, and mitigation strategies. Other gases like carbon dioxide, nitrous oxide, and hydrogen sulfide were also studied. Key institutions include the University of California-Davis and Aarhus University. Bibliometric analysis revealed research evolution, identifying trends, gaps, and future research opportunities. This bibliometric analysis offers insights into emissions, air quality, sustainability, and animal welfare in dairy farming, highlighting areas for innovative mitigation strategies to enhance production sustainability. This research contributes to academia, enhancing agricultural practices, and informing environmental policies. It is possible to conclude that this research is a valuable tool for understanding the evolution of research on gas emissions in dairy cattle facilities, providing guidance for future studies and interventions to promote more sustainable production.

2023 Exploration and appraisal year in review

Petroleum exploration expenditure in 2023 increased modestly over that of 2022, but remains well below expenditure highs of a decade ago which were dominated by offshore activity. Exploration is dominant in onshore state jurisdictions and has been since 2019, and will continue to be with no Federal offshore petroleum exploration acreage release rounds or exploration permit awards in 2023. Despite the modest increase in exploration expenditure there were 38 exploration wells drilled in 2023, an increase from the 26 wells drilled in 2022. Three of these 2023 wells were located offshore, targeting prospective resources in the vicinity of liquefied natural gas (LNG) project upstream gas fields. Thirty-four conventional onshore exploration wells were drilled in 2023 compared to 18 in 2022, a significant increase. The Cooper–Eromanga Basin was the focus of onshore exploration drilling with 21 exploration wells, compared to 13 in 2022, which yielded six discoveries. The onshore Northern Perth Basin continues to be an exploration hot spot with five wells drilled in 2023, compared to four in 2022. The Permian Kingia Sandstone exploration play continues to deliver exploration success, with discoveries at North Erregulla Deep-1, Trigg Northwest-1, South Erregulla-3 and Tarantula Deep-1. Five exploration permits were awarded in onshore Western Australia and two in Queensland. These permits were awarded with modest exploration work programs. The interest in carbon capture and storage projects and assessment acreage continues with a Federal offshore greenhouse gas (GHG) release round in 2023 and 26 onshore state jurisdiction GHG assessment permits awarded or nominated preferred tender status.

Angel CCS project – decarbonising the hard-to-abate industries of WA

The Angel CCS Project is a proposed large-scale multi-user carbon capture and storage (CCS) hub located near Karratha, WA. It is being progressed by the Angel CCS Joint Venture (JV). Angel CCS is ideally located to aggregate emissions from existing sources in the Pilbara region and has the potential to facilitate the development of new lower-carbon industries, such as the production of hydrogen and ammonia, by providing a local solution for emissions. The JV has been awarded greenhouse gas assessment permit G-10-AP, located in the Northern Carnarvon Basin off the north-western coast of Western Australia and is now assessing the technical, regulatory and commercial feasibility of aggregating emissions from existing and potential future facilities and the geological storage of carbon dioxide in the permit area. Notionally, the Angel CCS project is expected to be able to handle up to 5 Mtpa. The proposed project could be the first large scale CCS hub with offshore storage in Australia and potentially one of the largest CCS hubs in the Asia Pacific. The paper provides an overview of the Angel CCS Project, outlines key enabling factors for CCS Hub developments, and explains the key considerations that informed the development concept.

Impacts of Behavioral, Organizational, and Spatial Factors on the Carbon Footprint of Traditional Retail and E-commerce in the Paris Region.

Carbon footprint assessment of retail is necessary to optimize procurement strategies and adopt sustainable shopping habits. However, estimating carbon footprints is a complex task, given the diversity of existing distribution channels. Average values for carbon emissions of "conventional" retail (i.e., purchasing and receiving the product directly at the physical point of sale) found in most studies mask a heterogeneous reality: different retail strategies entail diverse shopping behavior for consumers, as well as varied procurement processes for outlets. In this paper, we propose a methodology to assess greenhouse gas (GHG) impacts of different distribution systems related to the consumption of goods in the Paris Region by coupling traditional transport modeling with a life-cycle assessment (LCA) approach. We model and compare six distribution systems, including five traditional retail formats (hypermarkets, supermarkets, small generalist retail, small food retail, and small nonfood retail) and E-commerce home deliveries. Our model includes warehouse activity, shop and home delivery, shop energy consumption, consumer mobility, and goods packaging. Overall, we conclude that E-commerce emits fewer GHG emissions than retail outlets per kilogram of product purchased. This result is in line with the existing literature on the topic. However, the carbon footprint varies greatly within the case study depending on the characteristics of the logistics procurement processes of outlets, the behavior of shoppers, and spatial characteristics.

Is cell-based meat a climate solution for Canada?

Interest and technological know-how in cell-based meat production has grown tremendously in recent years. The appeal is wide ranging, but two main drivers include: i) the possibility of producing edible meat without requiring the slaughter of sentient animals; and ii) the potential to significantly reduce the environmental impact of animal agriculture. Owing to these potential benefits, proponents have called for major government investments in cell-based meat to further develop the technology and help launch the industry. This article critically examines the environmental promise of cell-based meat, focussing specifically on its potential role in climate change mitigation, and specifically within the context of Canada’s agri-food sector. The analysis is founded upon a comparison of available life cycle greenhouse gas assessments of cell-based and conventional meat, supplemented with contextual data about the Canadian agri-food sector. Cell-based meat in Canada is found to have a likely carbon footprint similar in scale to poultry meat, pork, and beef from dairy cattle, though considerably lower than meat from beef cattle. Alongside these findings and additional contextual factors pertaining to Canada’s agri-food sector, the paper argues that cell-based meat is best understood as one tool among many which could potentially support greenhouse gas emissions reductions in domestic food production if supporting conditions are met, not a silver bullet climate solution obtained by fully replacing conventional meat.

An Assessment on the Carbon Footprint of a Football Club—an Action Research from Theory to Practice

There is a lack of academic literature that explores the evaluation of football club’s carbon footprints. To the best of the author’s knowledge, this study is the first study where the football’s club’s overall carbon footprints were assessed. This study’s main objectives were to measure the football club environmental impact and promote the reduction of greenhouse gases (GHGs) emissions for famous significant sports events such as the Federation Internationale de Football Association (FIFA) and The Union of European Football Associations (UEFA) matches. The football club is a part of one of the biggest football clubs in Europe, which operates, manages, and maintains various facilities by assisting the football club in decision-making processes to identify the most relevant business engagement areas. The following research questions were considered: (a) What are the hotspots and the most significant contributors to GHG emissions of a football club? (b) How to improve emissions management within the stadium organization? (c) How to establish a carbon reduction and management plan? The researchers visited this stadium to collect data and interview managers of the football club. The GHG assessment results provide some relevant confirmation of the guidelines that emerged during the onsite visit. This study found that indirect emissions produced by a supporter’s transportation mode are equivalent to 38%, followed by energy consumption, accounting for 25% of the total GHG emissions. Specific future recommendations for sports organizations, such as (i) intermediate goal is to cut GHG emissions by at least 50% by 2030 and (ii) model scope 3 emissions and set scope 3 targets if scope 3 emissions account for 40% or more of their overall emissions, have emerged after this study.

Resource Efficiency and Environmental Impact Assessment Method for Small-Scale Producers: A Case Study of Pond and In-Pond Raceway System Production for Growing Nile Tilapia

The purpose of this study was to employ Resource Value Mapping (REVAM) and carbon footprint assessments to evaluate the resource efficiency and environmental impact of the aquaculture sector in Thailand. Focusing on tilapia production, a case study that compares the innovative In-Pond Raceway System (IPRS) with the traditional pond system was conducted to serve as a guideline for small-scale producers toward achieving the Sustainable Development Goals (SDGs). The assessment applied lean classification to the agriculture context and used both machine and non-machine resources. Moreover, the Muda Index (MI) and the concurrent assessment of greenhouse gas (GHG) emissions through the proposed map were introduced to identify resource efficiencies and environmental impacts across activities, respectively. The analysis highlighted resources with the highest MI values, waste proportions, and emissions requiring improvement. This study shows that addressing specific resources in REVAM can enhance resource management, facilitate control over variable costs, and ensure sustainability in both of these dimensions. Finally, a feasibility analysis was incorporated to weigh investment between in-pond and IPRS systems, in addition to resource use efficiency and environmental impact dimensions, creating an opportunity to meet the increasing demands in the international market.

Carbon footprint of hospital laundry: a life-cycle assessment

ObjectivesTo assess greenhouse gas (GHG) emissions from a regional hospital laundry unit, and model ways in which these can be reduced.DesignA cradle to grave process-based attributional life-cycle assessment.SettingA large hospital...

Low-carbon efficiency assessment for Hong Kong's oceanic artificial cities applying the novel prefabricated diaphragm wall technology

Oceanic artificial cities built by reclamation are vital for addressing the future sustainable development of land in Hong Kong. However, traditional cast-in-situ (CIS) construction methods face issues such as significant environmental impacts and low durability, making it challenging to meet the requirements of low-carbon and resilient development. To address these challenges, a novel low-carbon construction technology for oceanic artificial cities is proposed: prefabricated two-wall-in-one diaphragm wall (PTDW). This study aims to address the comprehensive assessment and decision-making issues of greenhouse gas (GHG) emissions and load-bearing performance. First, the adaptability of PTDW technology to oceanic artificial cities is introduced. Second, the Carbon-mechanics Dual-control Assessment Model-Section level (CDAM-SL) is established. Finally, CDAM-SL is used to assess the GHG reduction efficiency of construction technologies for oceanic artificial cities. The results reveal the following key findings: (1) The Bearing Property Indicators (BPI) of the PTDW-Cavity scheme surpass the CIS scheme across the construction and operation phases. (2) Comparing to the traditional CIS scheme, the GHG emissions of the PTDW-Cavity scheme are reduced by 33.31% (8.65 t CO2e). This reduction is primarily attributed to PTDW technology, which eliminates the temporary enclosure structure construction. Furthermore, the refined PTDW technology significantly decreases the GHG emissions of precast components and enhances drainage performance. (3) The GHG reduction efficiency of the PTDW-Cavity scheme consistently outperforms the CIS scheme across both phases. Consequently, PTDW technology demonstrates significant advantages in load-bearing performance and GHG emissions reduction. The research findings provide a theoretical foundation and applicable tool for the comprehensive assessment and decision-making of low-carbon construction technology for oceanic artificial cities.

Predicting and assessing greenhouse gas emissions during the construction of monorail systems using artificial intelligence.

Based on partial data, this paper uses BP neural network optimised by particle swarm optimisation algorithm to predict the total greenhouse gas (GHG) emissions of the line in the construction phase. The GHG emission efficiency is analysed by SBM (Slacks-Based Measure) super efficiency method. Finally, the grey relational analysis (GRA) is applied to sort the GHG emission correlation factors. Based on the existing design and quota document data of 16 stations and 16 sections of the Wuhu Monorail Line 1, we have employed a neural network optimized by particle swarm optimization algorithm to predict the total emissions of greenhouse gases during the construction phase of the entire line consisting of 25 stations and 24 sections. The GHG emissions of all stations and sections are 29,300 tons and 21,000 tons. The technical efficiency, pure technical efficiency, and scale efficiency of the stations and sections were high. As for stations, the order of influence degree is metal material consumption (0.9731) > cost (0.9486) > electric energy consumption (0.9481) > station area (0.9109) > concrete and cement consumption (0.9032) > other material consumption (0.8831) > gasoline and diesel consumption (0.7258). For the section, the order of influence degree is cost (0.9766) > concrete (0.9581) > steel reinforcement (0.9483) > other steels (0.874) > section length (0.8337) > power energy consumption (0.7169) > wood consumption (0.6684).

A new set of Lean indicators to assess Greenhouse Gas emissions related to industrial losses

PurposeThis paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.Design/methodology/approachThe new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.FindingsThe proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.Originality/valueThis paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

Life Cycle Assessment of a Gas Turbine Installation

Gas turbine installations (GTIs) are widely used to generate electrical and thermal energy, mainly by burning gaseous fuels. With the development of hydrogen energy technology, a current area of particular interest is the use of GTIs to burn hydrogen. In order to assess the prospects of using GTIs in this way, it is necessary to understand the carbon emissions of gas turbines within the larger context of the entire hydrogen life cycle and its carbon footprint. The article provides an overview of results from previously published studies on life cycle assessment (LCA) of complex technical devices associated with the production and consumption of fuel and energy, which are most similar to GTIs when it comes to the complexity of LCA. The subject of analysis was a set of GTIs located in Russia with a capacity of 16 MW. An assessment of greenhouse gas (GHG) emissions per MWh of electricity produced showed that at different stages of the GTI life cycle, the total carbon footprint was 198.1–604.3 kg CO2-eq., of which more than 99% came from GTI operation. Greenhouse gas emissions from the production and end-of-life management stages are significantly lower for GTIs compared to those for other complex technical devices used to generate electricity. This is an indicator of the strong prospects for the future use of GTIs.

Greenhouse gas emissions in Danish environmental assessments: a critical review

ABSTRACT Climate change is a key focus in society, and environmental assessments (EAs) are seen as key instruments to inform decision-makers about climate consequences of plans and projects. Previous research has, however, identified shortcomings of practice of assessing greenhouse gas (GHG) emissions and their significance, and this paper aims to unfold current practices with a focus on Denmark. From an initial set of 762 Danish EA reports published between 2017 and 2021, researchers scrutinized 102 of them to assess their handling of GHG emissions. The findings show that climate change mitigation receives continuous sparse attention and is only to a limited extent included in the scope of the EA. Moreover, analysis of GHG emissions only involves few phases in a life-cycle perspective, GHG emissions are seldomly deemed significant, and justifications provided are varied and frequently inadequate. The results contrast with the increasing focus in society on climate change as a pivotal concern across numerous societal activities. The repercussions of this current practice are discussed. Finally, a research agenda to support better practice is outlined.