The International Journal of Life Cycle Assessment

This paper aims to compare the environmental impacts of LNG in different life cycle stages and for various usages by applying life cycle assessment (LCA). According to different usage processes, we set three scenarios including S1-hydrogen production, S2-electricity generation, and S3-vehicle fuel to evaluate their environmental impacts. Furthermore, in order to satisfy better city development, an optimization analysis was made to identify the optimal distribution structure of LNG. The environmental impact analysis of LNG was conducted using life cycle assessment and CML2001 method. LCA was performed based on the ISO 14040 standard using GaBi 5.0 software. Four impact categories (i.e., global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), and photochemical ozone creation potential (POCP)) were considered. Sensitivity analysis was also made by means of GaBi 5.0 software. Crystal Ball software was applied to make the optimization analysis for different LNG usage scenarios. The minimum environmental impact factor was taken as the objective function to confirm the optimal distribution structure of LNG. The LCA results indicate that the environmental impacts of the gasification and usage stages far outweigh that of the transportation stage, and the highest environmental impact category for each scenario is GWP. The largest contribution factor to GWP of S1 is the production supply of imported electricity, whereas the largest contribution factor to GWP of S2 and S3 is the emissions. The optimization analysis indicate that when imported LNG is allocated 25% for hydrogen production, 73% for electricity generation and 2% for vehicle fuel, the GWP and cost of the total LNG usage are both minimum. Environmental analysis on different LNG usage scenarios allows the identification and selection of comprehensive LNG usage plans with the minimum environment impacts and lowest cost. For different LNG usage scenarios, the GWP of LNG used for vehicle fuel is the highest and for hydrogen production is the lowest. The production supply of imported electricity and the emissions are the two largest contribution factors to LCA results as well as the sensitivity analysis results of the three scenarios. The optimization analysis method and results can provide technology reference for scientific urban planning of LNG application and allocation.

The main primary energy for electricity in Thailand is natural gas, accounting for 73% of the grid mix. Electricity generation from natural gas combustion is associated with substantial air emissions. The two technologies currently used in Thailand, thermal and combined cycle power plant, have been evaluated for the potential environmental impacts in a “cradle-to-grid” study according to the life cycle assessment (LCA) method. This study evaluates the environmental impacts of each process of the natural gas power production over the entire life cycle and compares two different power plant technologies currently used in Thailand, namely, combined cycle and thermal. LCA is used as a tool for the assessment of resource consumption and associated impacts generated from utilization of natural gas in power production. The details follow the methodology outlined in ISO 14040. The scope of this research includes natural gas extraction, natural gas separation, natural gas transmission, and natural gas power production. Most of the inventory data have been collected from Thailand, except for the upstream of fuel oil and fuel transmission, which have been computed from Greenhouse gases, Regulated Emissions, and Energy use in Transportation version 1.7 and Global Emission Model for Integrated Systems version 4.3. The impact categories considered are global warming, acidification, photochemical ozone formation, and nutrient enrichment potential (NEP). The comparison reveals that the combined cycle power plant, which has a higher efficiency, performs better than the thermal power plant for global warming potential (GWP), acidification potential (ACP), and photochemical ozone formation potential (POCP), but not for NEP where the thermal power plant is preferable. For the thermal power plant, the most significant environmental impacts are from power production followed by upstream of fuel oil, natural gas extraction, separation, and transportation. For the combined cycle power plant, the most significant environmental impacts are from power production followed by natural gas extraction, separation, and transportation. The significant difference between the two types of power production is mainly from the combustion process and feedstock in power plant. The thermal power plant uses a mix of natural gas (56% by energy content) and fuel oil (44% by energy content); whereas, the combined cycle power plant operates primarily on natural gas. The largest contribution to GWP, ACP, and NEP is from power production for both thermal as well as combined cycle power plants. The POCP for the thermal power plant is also from power production; whereas, for combined cycle power plant, it is mainly from transmission of natural gas. In this research, we have examined the environmental impact of electricity generation technology between thermal and combined cycle natural gas power plants. This is the overview of the whole life cycle of natural gas power plant, which will help in decision making. The results of this study will be useful for future power plants as natural gas is the major feedstock being promoted in Thailand for power production. Also, these results will be used in further research for comparison with other feedstocks and power production technologies.

Electricity flows are frequently used life cycle assessment modeling and are often a significant source of emissions so creating inventories based on detailed inventories, representative of regional differences in grid supplied power, is important. We sought to understand the influence electricity trades have on consumption mixes and developed a method for creating regionalized US electricity inventories based on publicly available data for electricity generation and trades. With generation inventories for the eGRID subregions and trading within NERC regions, the trading operates within boundaries representative of distinct production regions while enabling trading. We created two approaches for allocating electricity trades within NERC regions, gross, and net trading. Trading is modeled using FERC data. Gross trading assumes that all trades within a NERC region contribute to each eGRID subregion receiving trades in to satisfy their demand while the net trading approach assumes that only eGRID subregions producing surplus electricity contribute to the mix in regions with deficits. We introduce the concept of trade pools for modeling electricity flows between individual eGRID subregions and the corresponding NERC regions. Challenges for modeling electricity trade flows are described in the Methodology section. We compare the results of the two trading approaches demonstrating the influence of prioritizing eGRID subregion generation mixes or trading within NERC regions. While trades represent a relatively small portion of total consumed electricity, some eGRID regions, like CAMX and those in New York state, rely heavily on trade to in order to meet their consumptive demand. The method presented here establishes the basis for eGRID-level consumption mixes which account for energy trades and provide regionalized life cycle inventories for electricity in the USA. We provide recommendations for their use including in attributional LCA as well as approaches requiring marginal electricity demands. The trading approaches have been implemented in a US EPA repository to provide these inventories and can be found at https://github.com/USEPA/ElectricityLCI .

A basic principle for Type I ecolabels is to consider the whole product life cycle in order to avoid transferring impacts from one life cycle phase or environmental medium to another. By using the example of the Blue Angel, this paper provides an overview of the typical criteria over the product life cycle established in ecolabels for different product categories. Further, the paper provides details about two selected issues that are of particular concern in the current debate within product policy: the longevity of products and the coverage of social aspects. The presented results are based on desk research, which included the creation of product and criteria categories and a complete analysis of all existing Blue Angel criteria sets for products. The coverage of different life cycle phases with criteria is very diverse, as expected, and varies across product categories. A focus of the Blue Angel is on the use phase. While longevity criteria are present in half of the Blue Angel criteria sets, they are in most cases not too comprehensive. The current discussion on adequate methodologies with regard to reparability and longevity, in general, is however speeding up at EU level, and this will also influence ecolabels. Social criteria are still rare in the Blue Angel, especially when it comes to social aspects during raw material extraction. There is, however, the intention to elaborate a more systematic basis for social criteria within the Blue Angel. While the ongoing debates on longevity and social criteria will most likely result in such criteria being applied to more product groups in Type I ecolabels, ecolabels always have to find a compromise between coverage of ideally all relevant life cycle impacts for which an improvement potential exists on the one hand, and feasibility for licensees to comply with the criteria and provide the according verification on the other.

The main purpose of this article is to assess the environmental impacts associated with the fishing operations related to European anchovy fishing in Cantabria (northern Spain) under a life cycle approach. The life cycle assessment (LCA) methodology was applied for this case study including construction, maintenance, use, and end of life of the vessels. The functional unit used was 1 kg of landed round anchovy at port. Inventory data were collected for the main inputs and outputs of 32 vessels, representing a majority of vessels in the fleet. Results indicated, in a similar line to what is reported in the literature, that the production, transportation, and use of diesel were the main environmental hot spots in conventional impact categories. Moreover, in this case, the production and transportation of seine nets was also relevant. Impacts linked to greenhouse gas (GHG) emissions suggest that emissions were in the upper range for fishing species captured with seine nets and the value of global warming potential (GWP) was 1.44 kg CO2 eq per functional unit. The ecotoxicity impacts were mainly due to the emissions of antifouling substances to the ocean. Regarding fishery-specific categories, many were discarded given the lack of detailed stock assessments for this fishery. Hence, only the biotic resource use category was computed, demonstrating that the ecosystems’ effort to sustain the fishery is relatively low. The use of the LCA methodology allowed identifying the main environmental hot spots of the purse seining fleet targeting European anchovy in Cantabria. Individualized results per port or per vessel suggested that there are significant differences in GHG emissions between groups. In addition, fuel use is high when compared to similar fisheries. Therefore, research needs to be undertaken to identify why fuel use is so high, particularly if it is related to biomass and fisheries management or if skipper decisions could play a role.

The development and use of, as well as scientific discussions on, eco-balances and in particular life cycle assessment has largely occurred without involving experts on environmental law. However, in the light of recent proposals to ‘legalize’ eco-balances, i.e. formally introducing them into environmental law, the legal implications of eco-balancing must be addressed in the future. The formal introduction, especially of LCA, cannot be decided independent of the general economic and environmental policy implications of material flow management, and it raises major questions of policy and constitutional law. An important question of principle is whether eco-balances should be prescribed or only a legal framework set forth for voluntary use. In view of the unfinished methodological development of LCA, any formal introduction raises the constitutional problem of conformity with the requirements of legal certainty. References to the ‘principles of good eco-balancing’ are problematic, and an introduction on an experimental basis would have to be confined to cases where the legal consequences of grossly divergent interpretations of this term are tolerable to affected firms. Where eco-balances are prescribed as a method of preparing governmental or administrative decisions, one must determine whether and to what extent they are binding on the decision-maker, and develop proper mechanisms of participation, transparency and critical review.

The use of life cycle assessment (LCA) as a decision support tool can be hampered by the numerous uncertainties embedded in the calculation. The treatment of uncertainty is necessary to increase the reliability and credibility of LCA results. The objective is to provide an overview of the methods to identify, characterize, propagate (uncertainty analysis), understand the effects (sensitivity analysis), and communicate uncertainty in order to propose recommendations to a broad public of LCA practitioners. This work was carried out via a literature review and an analysis of LCA tool functionalities. In order to facilitate the identification of uncertainty, its location within an LCA model was distinguished between quantity (any numerical data), model structure (relationships structure), and context (criteria chosen within the goal and scope of the study). The methods for uncertainty characterization, uncertainty analysis, and sensitivity analysis were classified according to the information provided, their implementation in LCA software, the time and effort required to apply them, and their reliability and validity. This review led to the definition of recommendations on three levels: basic (low efforts with LCA software), intermediate (significant efforts with LCA software), and advanced (significant efforts with non-LCA software). For the basic recommendations, minimum and maximum values (quantity uncertainty) and alternative scenarios (model structure/context uncertainty) are defined for critical elements in order to estimate the range of results. Result sensitivity is analyzed via one-at-a-time variations (with realistic ranges of quantities) and scenario analyses. Uncertainty should be discussed at least qualitatively in a dedicated paragraph. For the intermediate level, the characterization can be refined with probability distributions and an expert review for scenario definition. Uncertainty analysis can then be performed with the Monte Carlo method for the different scenarios. Quantitative information should appear in inventory tables and result figures. Finally, advanced practitioners can screen uncertainty sources more exhaustively, include correlations, estimate model error with validation data, and perform Latin hypercube sampling and global sensitivity analysis. Through this pedagogic review of the methods and practical recommendations, the authors aim to increase the knowledge of LCA practitioners related to uncertainty and facilitate the application of treatment techniques. To continue in this direction, further research questions should be investigated (e.g., on the implementation of fuzzy logic and model uncertainty characterization) and the developers of databases, LCIA methods, and software tools should invest efforts in better implementing and treating uncertainty in LCA.