Life Cycle Inventory Model Research Articles

Comprehensive evaluation of water utilisation during shale gas exploration and exploitation in China

This study comprehensively evaluates the impact of shale gas exploration and exploitation on water utilisation from the perspective of geological heterogeneity in China. Using a process-based life cycle inventory (LCI) model, we quantitatively analyse the water environment in three major shale gas regions in China (Changning-Weiyuan, Fuling and Yanchang areas). The results show that the water consumption amount during shale gas extraction in Changning-Weiyuan area is 21,594.26 m3, which is smaller than 28,105.94 m3 in Fuling area. And that in Yanchang area, approximately 25,000 m3, is estimated between the above two areas. The water shortage under the impact of shale gas extraction is then further measured by the water supply and demand index. Comparison reveals that Changning-Weiyuan region contains the most abundant water resources, and Yanchang is confronted with water scarcity during shale gas development. These conclusions provide a reference for the sustainable development of shale gas projects in China. [Received: March 28, 2020; Accepted: January 20, 2021]

A Systematic Framework for Quantifying Production System-Specific Challenges in Life Cycle Inventory Data Collection

Understanding the environmental impacts of production setups and process parameters is a necessity for process optimization and new process development within sustainable manufacturing. Previous research studies have focused on developing standard methodologies and frameworks for parametrically modelling the life cycle inventories of unit manufacturing processes. However, these approaches do not fully account for the challenges associated with implementing life cycle inventory models in real-world production setups. Therefore, the time- and cost-intensiveness associated with constructing such models limit their use for identifying sustainability-focused process improvements in complex, real-world production processes. To address the above challenges, this paper proposes a framework to identify process inventory data that have a significant influence on process resource consumption, taking into consideration the difficulties and variabilities in measuring these data. The overarching goal is to identify feasible process improvements from the perspective of process monitoring for sustainable manufacturing. The application of the proposed framework is presented using a case study on a real-world through-feed centerless grinding production process for rotor manufacturing. This study reveals grinding time is the most sensitive process parameter among the other time-related parameters. The manual nature of the process, lack of a data acquisition system, non-standardized sequence of operation, and inability to capture in-process measurements without disrupting real-time production significantly contributes to the difficulty and variability of measuring grinding time.

Life cycle assessment of global warming potential of feedstock recycling technologies: Case study of waste gasification and pyrolysis in an integrated inventory model for waste treatment and chemical production in Germany

Feedstock recycling in the form of gasification and pyrolysis are promising alternatives to thermal treatment for the utilization of non-recyclable waste fractions. To date, the systemic consequences of their application for waste treatment and chemical production as well as associated environmental effects remain insufficiently investigated. To address this gap, this study introduces an integrated life cycle inventory model based on Germany's production system which encompassed the treatment of major post-consumer waste fractions (municipal solid waste and source-separated packaging waste) and the production of major base chemicals (lower olefins, BTX aromatics, methanol, ammonia and hydrogen). The utilized approach facilitates a prospective comparative assessment of feedstock recycling, conventional and PTX-based production routes under uniform system frameworks, accounting for differences in production characteristics (e.g. product yields and utility demands) with minimized allocation assumptions. An evaluation of the global warming potential shows that under assumptions resembling the current production system (Framework Status Quo), feedstock recycling pathways lead to a reduction in greenhouse gas emissions, with gasification exhibiting higher emission reduction than pyrolysis. Under the assumption that limited renewable energy is available for system emission reduction (Framework Energy Integration), a higher greenhouse gas reduction is observed for feedstock recycling compared to PTX-based chemical production pathways.

Modeling the use and end-of-life phase of pharmaceuticals in support of a life cycle inventory analysis – Case study on different antibiotics in Germany

More focused measurements on antibiotics in the environment enable a more accurate assessment of potential risks to human health and ecosystems. Therefore, antibiotics are ranked as highly relevant with efforts to monitor and systematically map them (e.g., German Antibiotic Resistance Strategy, European Antimicrobial Resistance Surveillance Network, Global Antimicrobial Resistance Surveillance System). Due to limited life cycle analysis data, a recently developed life cycle inventory model to assess the use and end-of-life phase of pharmaceuticals in Germany is applied and reviewed for antibiotics, representatively for amoxicillin, ciprofloxacin and clarithromycin. Necessary data are collected from experimental research, publications by official agencies and data fact sheets by pharmaceutical companies, among others. To evaluate the model's accuracy and prediction potential, the results are compared to literature findings. The model predicts the emission pathway via the sewage treatment effluent to be the primary route ranging from 39.5% (clarithromycin) to 67% (amoxicillin). Accumulation in the sewage sludge is relevant for ciprofloxacin (24.3%) whereas clarithromycin shows the highest biodegradability (15.8%). Gaseous emissions are not predicted. Modeling of metabolites is not reliable because of major data gaps regarding the chemical structure and coherent physicochemical properties. The results highlight that currently neglected transformation processes (especially hydrolysis) need to be implemented prospectively to reclassify the gained results. Investigation of other software than SimpleTreat 4.0 should be done to display the fate of substances in sewage treatment plants more precisely. Also, more experimental, and scientifically assured data are needed to confirm the ratio of the antibiotics' pathways.

Embodied GHG Emissions of Wooden Buildings—Challenges of Biogenic Carbon Accounting in Current LCA Methods

Buildings play a vital role in reaching the targets stated by the Intergovernmental Panel on Climate Change to limit global warming to 1.5 degrees. Increasing the use of wood in construction is a proposed upcoming strategy to reduce the embodied greenhouse gas emissions of buildings. This study examines existing life cycle assessments of wooden buildings. The aim is to investigate embodied greenhouse gas emission results reported, as well as methodological approaches applied in existing literature. The study applies the protocol for Systematic Literature Reviews and finds 79 relevant papers. From the final sample, the study analyses 226 different scenarios in-depth in terms of embodied emissions, life cycle assessment method, life cycle inventory modelling and biogenic carbon approach. The analysis shows that the average reported values of embodied greenhouse gas emissions of wooden buildings are one-third to half of the embodied emissions reported from buildings in general. Additionally, from the analysis of the final sample we find that the majority of wooden building life cycle assessments apply similar methods and often leave out biogenic carbon from the assessment or simply do not declare it. This implies that the focus on variability in the different methods applied in wooden building life cycle assessments needs to be increased to establish the relationship between methodological choices and embodied emissions of wooden buildings. Further, transparency and conformity in biogenic carbon accounting in life cycle assessments is essential to enhance comparability between life cycle assessment studies and to avoid distortions in embodied GHG emission results.

Life Cycle Modelling of Extraction and Processing of Battery Minerals—A Parametric Approach

Sustainable battery production with low environmental footprints requires a systematic assessment of the entire value chain, from raw material extraction and processing to battery production and recycling. In order to explore and understand the variations observed in the reported footprints of raw battery materials, it is vital to re-assess the footprints of these material value chains. Identifying the causes of these variations by combining engineering and environmental system analysis expands our knowledge of the footprints of these battery materials. This article disaggregates the value chains of six raw battery materials (aluminum, copper, graphite, lithium carbonate, manganese, and nickel) and identifies the sources of variabilities (levers) for each process along each value chain. We developed a parametric attributional process-based life cycle model to explore the effect of these levers on the greenhouse gas (GHG) emissions of the value chains, expressed in kg of CO2e. The parametric life cycle inventory model is used to conduct distinct life cycle assessments (LCA) for each material value chain by varying the identified levers within defined engineering ranges. 570 distinct LCAs are conducted for the aluminum value chain, 450 for copper, 170 for graphite, 39 for lithium carbonate via spodumene, 20 for lithium carbonate via brine, 260 for manganese, and 440 for nickel. Three-dimensional representations of these results for each value chain in kg of CO2e are presented as contour plots with gradient lines illustrating the intensity of lever combinations on the GHG emissions. The results of this study convey multidimensional insights into how changes in the lever settings of value chains yield variations in the overall GHG emissions of the raw materials. Parameterization of these value chains forms a flexible and high-resolution backbone, leading towards a more reliable life cycle assessment of lithium-ion batteries (LIB).

Machine-Specific Estimation of Milling Energy Consumption in Detailed Design

AbstractManufacturing is a significant contributor to global greenhouse gas emissions and there is an urgent need to reduce the energy consumption of production processes. An important step towards this goal is proactively estimating process energy consumption at the detailed design stage. This is a challenging task as variabilities in factors such as process specifications, machine tool architecture, and workpiece geometry can significantly reduce the accuracy of the estimated energy consumption. This paper discusses a methodology for machine-specific energy estimation in milling processes at the detailed design stage based on the unit process life cycle inventory (UPLCI) model. We develop an adjusted UPLCI model that includes adjustment factors for uncertainties in machine tool specifications and the specific cutting energy of a workpiece material. These adjustment factors are calculated through experimental measurement of energy consumption for a reference test part on a specific machine tool. To validate the adjusted UPLCI model, we conducted a case study that measured the energy consumption for machining three parts made of Aluminum 6082 on two separate three-axis vertical milling machines, a Chevalier QP2040-L and a Leadwell MCV-OP. Results show that the UPLCI model consistently overestimated the total energy consumption for machining the three validation parts across both machine tools. We also found that the adjusted UPLCI model significantly reduced the estimation errors for the same tests for both machine tools.

Scale-Up of Pilot Line Battery Cell Manufacturing Life Cycle Inventory Models for Life Cycle Assessment

Even though the gate-to-gate production of lithium based battery cells is one of the main contributors to the environmental impacts of electric vehicles, primary data required for the estimation of environmental impacts of large-scale production of battery cells remains scarce. While Life Cycle Assessment for battery cells produced in research pilot lines can increase the understanding of related environmental impacts, the data is difficult to scale up to large-scale production systems. This paper presents a scale up methodology along with a Life Cycle Inventory and Life Cycle Assessment for battery cells manufactured in the Battery LabFactory Braunschweig (BLB). CO2-eq emissions of a single battery cell produced in a pilot line can be tenfold of comparable industrial cells. Material and energy efficiency, dry room sizing, lacking systemic efficiencies and unoptimized product design are the main reasons for this difference in the foreground system. Based on two scenarios, the paper elaborates how Life Cycle Inventories can be up-scaled from a pilot scale so that they can be used to estimate large-scale production environmental impacts.

Improving robustness of LCA results through stakeholder engagement: A case study of emerging oil sands technologies

Life cycle assessments can help inform decision-making about greenhouse gas (GHG) emission reduction opportunities but are often not embraced by stakeholders associated with industries where study results are highly scrutinized and often contentious. This project was motivated by stakeholder interest in understanding open source life cycle models (the Oil Production Greenhouse Gas Emissions Estimator, OPGEE, and the Petroleum Refinery Life Cycle Inventory Model, PRELIM) and how accurately they can estimate emissions for existing oil sands projects and emerging technologies. We evaluate the robustness of these models and improve them using data from three existing oil sands projects (mining + upgrading, mining + dilution, and steam assisted gravity drainage, SAGD, + dilution). The models are then applied to estimate the GHG emissions reduction potential for two emerging in situ oil sands technologies. We find that, when boundaries are aligned, OPGEE can generate upstream GHG emissions estimates for the projects modeled within 1-4% of company reported GHG emissions data. Extending the boundary to include indirect (life cycle) emissions can lead to a doubling in upstream GHG emissions intensity. The two emerging technologies evaluated in the study can reduce upstream emissions by 14-19% compared to a SAGD project operating at the same reservoir, or 1.4-1.9% on a well-to-wheel basis. This work contributes a revised process of conducting LCAs that includes stakeholder input throughout and results in more robust and transparent estimates of emissions from deploying existing and emerging technologies.

Environmental Sustainability of Mixed Cation Perovskite Materials in Photovoltaics Manufacturing

Efficiencies of lead halide perovskite photovoltaics have increased to 25%, putting them on track for commercialization within the next 1–3 years. Devices exhibiting the best combination of high efficiency and long operational lifetimes have used mixed cation perovskite absorber layers such as cesium/methylammonium/formamidinium lead iodide (CsxMAyFA1-x-yPbI3). However, the associated environmental burdens of the supply chains of perovskite precursors should also be considered when selecting compositions for commercialization. Prior literature based on laboratory-scale data reported a particularly high environmental burden for FA and warned against using these highest-performing film compositions. Here, we report a comprehensive study of the environmental impacts of common precursor salts used to form mixed cation perovskite films, using a life cycle assessment approach. We have used updated data sources, process scale-up concepts, and sensitivity analysis to build commercial-scale life cycle inventory models for perovskite precursors that can inform industrial manufacturing choices with more transparent and robust environmental analysis. Our results indicate that the process-based climate change, cumulative energy demand, and human toxicity impacts of CsI, MAI, and FAI are similar to each other and lead to iodide (PbI2) salts on a molar basis. The current cesium supply appears sufficient for near-future perovskite deployment. Additionally, the impacts of the perovskite precursors are ∼1000-fold smaller than those of glass when considering amounts needed per module area. Therefore, selection of perovskite composition can be based on PV efficiency and operational stability, without additional constraints of environmental impact.

Comparative Eco-Profiles of Polyethylene Terephthalate (PET) and Polymethyl Methacrylate (PMMA) Using Life Cycle Assessment

Polyethylene terephthalate (PET) and polymethyl methacrylate (PMMA) are extensively applied to produce nano-energy by harvesting ambient mechanical energy for energizing wearable electronics. Nowadays importance has been given to study on both PET and PMMA due to their growing demand in building Triboelectric Nanogenerators (TENG) to replace small batteries. The manufacturing of both triboelectric polymers from raw materials is hazardous to the environment. However, there has been no comparative evaluation of the probable effects of PET and PMMA production plants yet. This study highlights their comparative eco-profiles. An inclusive Life Cycle Inventory (LCI) model is built for methodical assessment of their impacts. Life Cycle Assessment (LCA) has been done by the ILCD midpoint method, Eco-indicator 99 endpoint method, Raw Material Flow (RMF) method, Greenhouse gas protocol method, and Ecopoints 97 method utilizing the Ecoinvent database and SimaPro software. The effects are assessed and compared for 21 impact categories such as global warming, acidification, eutrophication, terrestrial ecotoxicity, human toxicity, human carcinogenic toxicity, and fine particulate matter formation, marine ecotoxicity etc. The results indicate an estimated 3.01 kg CO2 eq./kg and 8.43 kg CO2 eq./kg of greenhouse gas (GHG) emission to the environment by a PET plant and a PMMA plant, respectively. Moreover, PET plants have the highest effect on land use, ionizing radiation and ozone depletion; whereas PMMA plants have the greatest impact on climate change, acidification, eutrophication and resources. Overall, PMMA polymer production plants are found to be more hazardous to the environment than PET polymer production plants. It is recommended that a better environmental profile from both types of production plants can be achieved through optimization, via abating the effects by replacing the problematic materials, designs, methods and devices with their equivalent environment-friendly options without compromising the quality and production rates.

Assessing life cycle impacts from changes in agricultural practices of crop production

PurposeThis paper presents an improved methodological approach for studying life cycle impacts (especially global warming) from changes in crop production practices. The paper seeks to improve the quantitative assessment via better tools and it seeks to break down results in categories that are logically separate and thereby easy to explain to farmers and other relevant stakeholder groups. The methodological framework is illustrated by a concrete study of a phosphate inoculant introduced in US corn production.MethodsThe framework considers a shift from an initial agricultural practice (reference system) to an alternative practice (alternative system) on an area of cropland A. To ensure system equivalence (same functional output), the alternative system is expanded with displaced or induced crop production elsewhere to level out potential changes in crop output from the area A. Upstream effects are analyzed in terms of changes in agricultural inputs to the area A. The yield effect is quantified by assessing the impacts from changes in crop production elsewhere. The field effect from potential changes in direct emissions from the field is quantified via biogeochemical modeling. Downstream effects are assessed as impacts from potential changes in post-harvest treatment, e.g., changes in drying requirements (if crop moisture changes).Results and discussionAn inoculant with the soil fungus Penicillium bilaiae has been shown to increase corn yields in Minnesota by 0.44 Mg ha−1 (~ 4%). For global warming, the upstream effect (inoculant production) was 0.4 kg CO2e per hectare treated. The field effect (estimated via the biogeochemical model DayCent) was − 250 kg CO2e ha−1 (increased soil carbon and reduced N2O emissions) and the yield effect (estimated by simple system expansion) was − 140 kg CO2e ha−1 (corn production displaced elsewhere). There were no downstream effects. The total change per Mg dried corn produced was − 36 kg CO2e corresponding to a 14% decrease in global warming impacts. Combining more advanced methods indicates that results may vary from − 27 to − 40 kg CO2e per Mg corn.Conclusion and recommendationsThe present paper illustrates how environmental impacts from changes in agricultural practices can be logically categorized according to where in the life cycle they occur. The paper also illustrates how changes in emissions directly from the field (the field effect) can be assessed by biogeochemical modeling, thereby improving life cycle inventory modeling and addressing concerns in the literature. It is recommended to use the presented approach in any LCA of changes in agricultural practices.

Data representativeness in LCA: A framework for the systematic assessment of data quality relative to technology characteristics

AbstractA shortcoming in current data quality assessment schemes is that the data quality information is not used systematically to identify the critical data in a life cycle inventory (LCI) model. In addition, existing criteria employed to evaluate representativeness lack relevance to the specific context of a study. A novel framework is proposed herein for the evaluation of the representativeness of LCI data, including an analysis of the importance of the data and a modification of quality criteria based on unit process characteristics. Temporal characteristics are analyzed by identifying the technology shift, because data generated before this time are considered outdated. Geographical and technological characteristics are analyzed by defining a “related area” and a “related technology,” which is done by identifying a number of relevant geographical and technical factors, and then comparing the collected data with these factors. The framework was illustrated in a case study on household waste incineration in Denmark. The results demonstrated the applicability of the method in practice, and they provided data quality criteria unique to waste incineration unit processes, for example, different time intervals to evaluate temporal representativeness. However, the proposed method is time demanding, and thus sector‐level characteristic analyses are feasible instead of the user having to do the analyses.

Life cycle environmental and cost evaluation of renewable diesel production

Computer simulations are used to study the production of renewable diesel through the biochemical transformation of biomass sorghum [Sorghum bicolor (L.) Moench] to free fatty acids using a genetically modified strain of Escherichia Coli. We evaluate select environmental and economic metrics using life cycle assessment (LCA) and techno-economic analysis (TEA). The biofuel supply chain includes feedstock production, handling, pretreatment and hydrolysis, fermentation to free fatty acids, saponification of the free fatty acids, wax production on an electrochemical synthesis reactor, and hydrocracking to convert the wax to renewable diesel. The TEA model developed uses experimental data from pretreatment to wax synthesis steps and literature for the conversion of wax to diesel. The TEA model is integrated into a life cycle inventory model to estimate life cycle greenhouse gas and non-renewable energy consumption. Considering both environmental and economic factors we find that the performance of this pathway to produce renewable diesel returns lower product yield, higher cost, and higher GHG and energy impacts compared to biomass-to-ethanol pathways, primarily due to poor process yields (mainly fermentation). This limitation in the metabolic pathway constrains the maximum yield potential of FFA and therefore renewable diesel and other potential co-products from biomass derived sugars.

Renewable diesel from oils and animal fat waste: implications of feedstock, technology, co-products and ILUC on life cycle GWP

We investigate the use of rendered poultry fat, beef tallow, and soybean oil as ready sources of free fatty acids (FFAs) and triglycerides (TG) for conversion to renewable diesel. Laboratory scale saponification and decarboxylation experiments using trilaurin, lauric acid, protein, and water as a model compound representing rendered animal fat are reported and combined with chemical process simulations, and thermodynamic and kinematics equations to build energy and material balances where Ab Initio methods are used for estimating missing data to build a life cycle inventory model. Life cycle greenhouse gas (GHG) emissions for producing renewable diesel from soybean oil, poultry fat, and beef tallow fall between −8.7 and 47.2 g CO2 equivalent/MJ even considering induced land use change when soybean oil is used as feedstock. Emissions vary depending on co-products and allocation rules used, which can affect compliance with energy policies.

Life cycle inventory modelling framework for symbiotic and distributed agricultural food production systems

Abstract Agricultural food production systems are essential to face current and future climate, food security and nutrition challenges. Several novel urban agriculture production concepts are utilizing symbiotic production and distributed/urban production principles to address these challenges. Life cycle engineering can support the planning and design of production systems and help to identify hotspots and avoid problem shifting. In this work the authors identify the factors resulting from symbiotic, distributed and enclosed food production, influencing life cycle inventory modelling for life cycle assessment. Based on the influencing factors a life cycle inventory modelling framework is proposed and the application pathway is illustrated by an in-development production system called CUBES Circle.

Enhancing life cycle chemical exposure assessment through ontology modeling

In its 2014 report, A Framework Guide for the Selection of Chemical Alternatives, the National Academy of Sciences placed increased emphasis on comparative exposure assessment throughout the life cycle (i.e., from manufacturing to end-of-life) of a chemical. The inclusion of the full life cycle greatly increases the data demands for exposure assessments, including both the quantity and type of data. High throughput tools for exposure estimation add to this challenge by requiring rapid accessibility to data. In this work, ontology modeling was used to bridge the domains of exposure modeling and life cycle inventory modeling to facilitate data sharing and integration. The exposure ontology, ExO, is extended to describe human exposure to consumer products, while an inventory modeling ontology, LciO, is formulated to support automated data mining. The core ontology pieces are connected using a bridging ontology and discussed through a theoretical example to demonstrate how data from LCA can be leveraged to support rapid exposure modeling within a life cycle context.

Handling uncertainties inherited in life cycle inventory and life cycle impact assessment method for improved life cycle assessment of wastewater sludge treatment

Life cycle assessment (LCA) has been used to evaluate environmental impacts of products or processes including wastewater treatment. Uncertainty has not received adequate attention in LCA studies. Uncertainty inherited in LCA steps such as the life cycle inventory (LCI) or the life cycle impact assessment (LCIA) method use is unavoidable, but it affects LCA outcomes and associated decision-making. The objective of this paper was to show the impact of uncertainty from LCI and LCIA method on LCA outcomes by using a case study base approach on wastewater sludge treatment processes. A qualitative analysis included setting criteria about what data to be included in LCI, characterization of data, differentiating between major and minor contributors in LCI modeling, evaluation of data quality indicators, setting achievable alternative scenarios, and selecting proper LCIA method were used, in addition to quantitative analysis included assigning most appropriate values for data gaps and proper distribution, and conducting probabilistic analysis to evaluate overall uncertainty. This research used a full-scale wastewater treatment plant in Missouri, USA for case study in which multiple hearth incineration (MHI) is the existing process, while fluid bed incineration (FBI) and anaerobic digestion (AD) were proposed as the alternatives. Using ReCipe method, the study revealed that variation in LCA results of MHI is 63.4% for a single end-point score of 57.9 mPt. On the two alternative processes, it is 54.6% probable that FBI would have more environmental impact than AD. The case study showed that the proposed steps were able to address issues of data uncertainty. Due to differences in characterization, normalization, and weighting factors, different LCIA methods may point out different conclusions and need to be addressed in evaluation.

Economic, Exergy, Environmental (3E) Analysis of Methanol Production from Shale Gas

Compared with direct utilisation as fuel, the downstream processing of shale gas shows great potential in economic competitiveness, in which methanol is a particularly important product. This study simulates a technical route for producing methanol from shale gas, which is evaluated from the points of economic, exergy and environment. The economic target is estimated by purchased cost curves, while exergy analysis demonstrates the distribution of exergy destruction. A hybrid LCI (Life cycle inventory) model is established to assess pollutant emissions by sources. The results show that methane reforming features the highest capital cost, while methanol synthesis requires the highest operating cost. The reaction systems account for 73.3 % of total exergy destruction. Electricity consumption dominates the environmental impacts of the whole process.

Life cycle environmental impact assessment of coupled underground coal gasification and CO2 capture and storage: Alternative end uses for the UCG product gases

Underground coal gasification (UCG) has the potential to provide a source of energy or chemical feedstock derived from coal seams, where traditional mining methods are not suitable or are uneconomical. This paper presents the life cycle inventory models developed for the UCG processes and three alternative syngas utilisation options with and without CO2 capture and storage. The paper compares the life cycle carbon footprint of two different conventional above ground coal fired power generation options with UCG Integrated Gasification Combined Cycle power generation with/without CCS for two different lignites and one bituminous coal. One of the lignites is then used to compare the life cycle performance of different syngas utilisation options: power generation, ammonia production with power generation, and methanol production with power generation. It was found that the life cycle carbon footprint of conventional above ground coal fired power generation is very much dependent on the in-situ methane content of the coal used, and methane emissions experienced during mining and accompanying upstream processes, whereas the same for UCG-IGCC power depends more on the process dependent syngas composition. UCG methanol production with associated power and CCS is shown to release more life cycle CO2-eq emissions per tonne of lignite consumed than that of UCG ammonia production with associated power and CCS and UCG CCGT power generation with CCS. Furthermore, when chemicals production from UCG is considered as the main objective, the most substantial improvements in comparison to conventional methods are associated with UCG ammonia process per tonne of chemical produced.