Toward More Realistic Estimates of Product Displacement in Life Cycle Assessment.

Life-cycle assessment (LCA) is one of the most widely applied methods for sustainability assessment. A main application of LCA is to compare alternative products to identify and promote those that are more environmentally friendly. Such comparative LCA studies often rest on, explicitly or implicitly, an idealized assumption, namely, 1:1 displacement between functionally equivalent products. However, product displacement in the real world is much more complicated, affected by various factors such as the rebound effect and policy schemes. Here, we quantitatively review studies that have considered these aspects to evaluate the magnitude and distribution of realistic displacement estimates across several major product categories (biofuels, electricity, electric vehicles, and recycled products). Results show that displacement ratios concentrate around 40-60%, suggesting considerable overestimation of the benefits of alternative products if the 1:1 displacement assumption was used. Overall, there have been a small number of modeling studies on realistic product displacement and their scopes were limited. Additional research is needed to cover more product categories and geographies and improve the modeling of market and policy complexities. As such research accumulates, their displacement estimates can form a database that can be drawn upon by comparative LCA studies to more accurately determine the environmental impacts of alternative products.

Tackling Missing Heritability by Use of an Optimum Curve: A Systematic Review and Meta-Analysis.

Missing heritability is a common problem in psychiatry that impedes precision medicine approaches to autism and other heritable complex disorders. This proof-of-concept study uses a systematic review and meta-analysis of the association between variants of the serotonin transporter promoter (5-HTTLPR) and autism to explore the hypothesis that some missing heritability can be explained using an optimum curve. A systematic literature search was performed to identify transmission disequilibrium tests on the short/long (S/L) 5-HTTLPR polymorphism in relation to autism. We analysed five American, seven European, four Asian and two American/European samples. We found no transmission preference in the joint samples and in Europe, preferential transmission of S in America and preferential transmission of L in Asia. Heritability will be underestimated or missed in genetic association studies if two alternative genetic variants are associated with the same disorder in different subsets of a sample. An optimum curve, relating a multifactorial biological variable that incorporates genes and environment to a score for a human trait, such as social competence, can explain this. We suggest that variants of functionally related genes will sometimes appear in fixed combinations at both sides of an optimum curve and propose that future association studies should account for such combinations.

Quantified Uncertainties in Comparative Life Cycle Assessment: What Can Be Concluded?

Interpretation of comparative Life Cycle Assessment (LCA) results can be challenging in the presence of uncertainty. To aid in interpreting such results under the goal of any comparative LCA, we aim to provide guidance to practitioners by gaining insights into uncertainty-statistics methods (USMs). We review five USMs-discernibility analysis, impact category relevance, overlap area of probability distributions, null hypothesis significance testing (NHST), and modified NHST-and provide a common notation, terminology, and calculation platform. We further cross-compare all USMs by applying them to a case study on electric cars. USMs belong to a confirmatory or an exploratory statistics' branch, each serving different purposes to practitioners. Results highlight that common uncertainties and the magnitude of differences per impact are key in offering reliable insights. Common uncertainties are particularly important as disregarding them can lead to incorrect recommendations. On the basis of these considerations, we recommend the modified NHST as a confirmatory USM. We also recommend discernibility analysis as an exploratory USM along with recommendations for its improvement, as it disregards the magnitude of the differences. While further research is necessary to support our conclusions, the results and supporting material provided can help LCA practitioners in delivering a more robust basis for decision-making.

Assessment of Life Cycle Impacts on Ecosystem Services: Promise, Problems, and Prospects.

The analysis of ecosystem services (ES) is becoming a key-factor to implement policies on sustainable technologies. Accordingly, life cycle impact assessment (LCIA) methods are more and more oriented toward the development of harmonized characterization models to address impacts on ES. However, such efforts are relatively recent and have not reached full consensus yet. We investigate here on the transdisciplinary pillars related to the modeling of LCIA on ES by conducting a critical review and comparison of the state-of-the-art in both LCIA and ES domains. We observe that current LCIA practices to assess impacts on "ES provision" suffer from incompleteness in modeling the cause-effect chains; the multifunctionality of ecosystems is omitted; and the "flow" nature of ES is not considered. Furthermore, ES modeling in LCIA is limited by its static calculation framework, and the valuation of ES also experiences some limitations. The conceptualization of land use (changes) as the main impact driver on ES, and the corresponding approaches to retrieve characterization factors, eventually embody several methodological shortcomings, such as the lack of time-dependency and interrelationships between elements in the cause-effect chains. We conclude that future LCIA modeling of ES could benefit from the harmonization with existing integrated multiscale dynamic integrated approaches.

Comparison of Asian Aquaculture Products by Use of Statistically Supported Life Cycle Assessment.

We investigated aquaculture production of Asian tiger shrimp, whiteleg shrimp, giant river prawn, tilapia, and pangasius catfish in Bangladesh, China, Thailand, and Vietnam by using life cycle assessments (LCAs), with the purpose of evaluating the comparative eco-efficiency of producing different aquatic food products. Our starting hypothesis was that different production systems are associated with significantly different environmental impacts, as the production of these aquatic species differs in intensity and management practices. In order to test this hypothesis, we estimated each system's global warming, eutrophication, and freshwater ecotoxicity impacts. The contribution to these impacts and the overall dispersions relative to results were propagated by Monte Carlo simulations and dependent sampling. Paired testing showed significant (p < 0.05) differences between the median impacts of most production systems in the intraspecies comparisons, even after a Bonferroni correction. For the full distributions instead of only the median, only for Asian tiger shrimp did more than 95% of the propagated Monte Carlo results favor certain farming systems. The major environmental hot-spots driving the differences in environmental performance among systems were fishmeal from mixed fisheries for global warming, pond runoff and sediment discards for eutrophication, and agricultural pesticides, metals, benzalkonium chloride, and other chlorine-releasing compounds for freshwater ecotoxicity. The Asian aquaculture industry should therefore strive toward farming systems relying upon pelleted species-specific feeds, where the fishmeal inclusion is limited and sourced sustainably. Also, excessive nutrients should be recycled in integrated organic agriculture together with efficient aeration solutions powered by renewable energy sources.

Building and characterizing regional and global emission inventories of toxic pollutants.

To define consistent strategies for managing the environmental sustainability of chemicals, it is important to quantify the magnitude of their emissions and their associated impacts. Not all countries monitor and report emissions related to their activities. This is particularly the case for chemical emissions, whose toxic impacts on human health and ecosystems cannot be readily determined because of gaps in the available data. Emission data that can be retrieved from publicly available databases are typically restricted to a limited number of toxic substances, for a few countries, or for aggregated regions. Extrapolation strategies are thus needed to fill in those data gaps and to move from the consideration of single countries or regions to the world scale. Little is known about how effective these strategies are in extrapolating emissions. With the use of emission data available in public databases in the world, the current work explores different opportunities to compile representative inventories of toxic emissions. In this study, we build global and European emission inventories using three extrapolation proxies, namely the gross domestic product, the emissions of carbon dioxide, and the emissions of mercury. The three proxies are compared and their efficacies are tested statistically to identify the best performer for specific classes of substances. The potential impacts associated with the emissions in the European and global inventory are further tested by using an impact system adopted for the comparative assessment of chemicals in the field of life cycle assessment.

Development and application of dynamic hybrid multi-region inventory analysis for macro-level environmental policy analysis: a case study on climate policy in Taiwan.

We develop a novel inventory method called Dynamic Hybrid Multi-Region Inventory analysis (DHMRI), which integrates the EEMRIOA and Integrated Hybrid LCA and applies time-dependent environmental intervention information for inventory analysis. Consequently, DHMRI is able to quantify the change in the environmental footprint caused by a specific policy while taking structural changes and technological dynamics into consideration. DHMRI is applied to assess the change in the total CO2 emissions associated with the total final demand caused by the climate policy in Taiwan to demonstrate the practicality of this novel method. The evaluation reveals that the implementation of mitigation measures included in the existing climate policy, such as an enhancement in energy efficiency, promotion of renewable energy, and limitation of the growth of energy-intensive industries, will lead to a 28% increase in the total CO2 emissions and that the main driver is the export-oriented electronics industry. Moreover, a major increase in the total emissions is predicted to occur in Southeast Asia and China. The observations from the case study reveal that DHMRI is capable of overcoming the limitations of existing assessment tools at macro-level evaluation of environmental policies.

Water footprint of nations amplified by scarcity in the Belt and Road Initiative.

The growing water scarcity due to international trade poses a serious threat to global sustainability. Given the intensified international trade throughout the Belt and Road Initiative (BRI), this paper tracks the virtual water trade and water footprint of BRI countries in 2005-2015. By conducting a multi-model assessment, we observe a substantial increase in BRI's water footprint after taking water scarcity into account. Globally the BRI acts as a net exporter of virtual water, while the export volume experiences a decreasing trend. Noticeable transitions in nations' role (net exporters vs. net importers) are found between the BRI and global scales, but also between with and without considering water scarcity. Overall economic and population growth is major drivers of scarcity-weighted water footprint for BRI nations, as opposed to the promotion of water-use efficiency and production structure that can reduce water scarcity. Improving international trade and strengthening cooperation on water resources management deserve priority in alleviating the water scarcity of BRI.

Towards a general framework for including noise impacts in LCA.

PURPOSE: Several damages have been associated with the exposure of human beings to noise. These include auditory effects, i.e., hearing impairment, but also non-auditory physiological ones such as hypertension and ischemic heart disease, or psychological ones such as annoyance, depression, sleep disturbance, limited performance of cognitive tasks or inadequate cognitive development. Noise can also interfere with intended activities, both in daytime and nighttime. ISO 14'040 also indicated the necessity of introducing noise, together with other less developed impact categories, in a complete LCA study, possibly changing the results of many LCA studies already available. The attempts available in the literature focused on the integration of transportation noise in LCA. Although being considered the most frequent source of intrusive impact, transportation noise is not the only type of noise that can have a malign impact on public health. Several other sources of noise such as industrial or occupational need to be taken into account to have a complete consideration of noise into LCA. Major life cycle inventories (LCI) typically do not contain data on noise emissions yet and characterisation factors are not yet clearly defined. The aim of the present paper is to briefly review what is already available in the field and propose a new framework for the consideration of human health impacts of any type of noise that could be of interest in the LCA practice, providing indications for the introduction of noise in LCI and analysing what data is already available and, in the form of a research agenda, what other resources would be needed to reach a complete coverage of the problem. MAIN FEATURES: The literature production related to the impacts of noise on human health has been analysed, with considerations of impacts caused by transportation noise as well as occupational and industrial noise. The analysis of the specialist medical literature allowed for a better understanding of how to deal with the epidemiological findings from an LCA perspective and identify areas still missing dose-response relations. A short review of the state-of-science in the field of noise and LCA is presented with an expansion to other contributions in the field subsequent to the comprehensive work by Althaus et al. (2009a; 2009b). Focusing on the analogy between toxicological analysis of pollutants and noise impact evaluation, an alternative approach is suggested, which is oriented to the consideration of any type of noise in LCA and not solely of transportation noise. A multi-step framework is presented as a method for the inclusion of noise impacts on human health in LCA. RESULTS AND DISCUSSION: A theoretical structural framework for the inclusion of noise impacts in LCA is provided as a basis for future modelling expansions in the field. Rather than evaluating traffic/transportation noise, the method focuses on the consideration of the noise level and its impact on human health, regardless of the source producing the noise in an analogous manner as considered in the fields of toxicology and common noise evaluation practices combined. The resulting framework will constitute the basis for the development of a more detailed mathematical model for the inclusion of noise in LCA. The toxicological background and the experience of the analysis of the release of chemicals in LCA seem to provide sufficient ground for the inclusion of noise in LCA: taken into account the physical differences and the uniqueness of noise as an impact, the procedure applied to the release of chemicals during a product life cycle is key for a valuable inclusion of noise in the LCA logic. CONCLUSIONS: It is fundamental for the development of research in the field of LCA and noise to consider any type of noise. Further studies are needed to contribute to the inclusion of noise sources and noise impacts in LCA. In this paper, a structure is proposed that will be expanded and adapted in the future and which forms the basic framework for the successive modelling phase.

Patterns of carbon footprints of main grains production in China: a comparison between main and non-main producing areas.

Understanding the spatiotemporal patterns of carbon footprints (CFs) of grains production is important to formulate regional heterogeneous greenhouse gas (GHG) mitigation strategies. This study evaluates the CFs, farm CFs (FCFs: CFs of per unit area), and production CFs (PCFs: CFs of per unit yield) of main grains production in China based on a new scale data set: agricultural statistics data of over 300 prefecture-level regions. A comparison of CFs of main grains production between main producing area (MPA) and non-main producing area (NMPA) are firstly discussed on a totally new scale. Results show that the CFs of main grains production of MPA accounts for 54-57% of country's total although the area of farmland of MPA only accounts for 42%. The PCF and FCF of rice production are higher in MPA, while those of wheat and maize production are lower in MPA. It implies that there are less GHG emission of rice (main paddy grain) productions in NMPA and less GHG emission of wheat and maize (main dryland grains) production in MPA. In additional, the PCF of rice shows growth, while that of wheat and maize shows decline from 2008 to 2017. The growth of PCF of rice is mainly driven by the rise of PCF in MPA. Findings are expected to improve the understanding patterns of China's CF of main grains production and subsequently contribute to GHG mitigation.

Life cycle assessment: past, present, and future.

Environmental life cycle assessment (LCA) has developed fast over the last three decades. Whereas LCA developed from merely energy analysis to a comprehensive environmental burden analysis in the 1970s, full-fledged life cycle impact assessment and life cycle costing models were introduced in the 1980s and 1990 s, and social-LCA and particularly consequential LCA gained ground in the first decade of the 21st century. Many of the more recent developments were initiated to broaden traditional environmental LCA to a more comprehensive Life Cycle Sustainability Analysis (LCSA). Recently, a framework for LCSA was suggested linking life cycle sustainability questions to knowledge needed for addressing them, identifying available knowledge and related models, knowledge gaps, and defining research programs to fill these gaps. LCA is evolving into LCSA, which is a transdisciplinary integration framework of models rather than a model in itself. LCSA works with a plethora of disciplinary models and guides selecting the proper ones, given a specific sustainability question. Structuring, selecting, and making the plethora of disciplinary models practically available in relation to different types of life cycle sustainability questions is the main challenge.

Antimicrobial Activity of Necklace Orchids is Phylogenetically Clustered and can be Predicted With a Biological Response Method.

Necklace orchids (Coelogyninae, Epidendroideae) have been used in traditional medicine practices for centuries. Previous studies on a subset of unrelated orchid species utilized in these traditional practices revealed they possessed antimicrobial, anti-inflammatory, and anti-oxidant activity, providing experimental proof for their medicinal properties. To date however none of these species have been investigated ethno-botanically in a phylogenetic context. This study carried out comparative bioprospecting for a group of wild orchids using EBDCS (the Economic Botany Data Collection Standards) organ targeted and biological response methods. The traditional medicinal use of necklace orchids was recorded from books and journals published between 1984 and 2016. Two orchids, Coelogyne cristata and Coelogyne fimbriata, were selected, cultivated both indoors and outdoors, and the antimicrobial properties on extracts from their leaves and pseudobulbs tested against a selection of human pathogens. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS and plastid matK DNA sequences obtained from 148 species was reconstructed with Maximum Likelihood (ML) using RAxML, Maximum Parsimony (MP) using PAUP and Bayesian Inference using MrBayes. Bioprospecting comparison of EBDCS and biological response was carried out using customized R scripts. Ethanolic extracts obtained from leaves of C. fimbriata inhibited growth of Bacillus cereus, Staphylococcus aureus, and Yersinia enterocolitica, confirming the antimicrobial properties of these extracts. Leaf extracts were found to have slightly stronger antimicrobial properties for plants cultivated outdoors than indoors. These differences were not found to be statistically significant though. Three hot nodes with high potency for antimicrobial activities were detected with the EBDCS organ targeted classification method, and eight hot nodes were detected with the biological response classification method. The biological response classification method is thus a more effective tool in finding hot nodes amongst clades of species with high medicinal potential.

Recent developments in Life Cycle Assessment.

Life Cycle Assessment is a tool to assess the environmental impacts and resources used throughout a product's life cycle, i.e., from raw material acquisition, via production and use phases, to waste management. The methodological development in LCA has been strong, and LCA is broadly applied in practice. The aim of this paper is to provide a review of recent developments of LCA methods. The focus is on some areas where there has been an intense methodological development during the last years. We also highlight some of the emerging issues. In relation to the Goal and Scope definition we especially discuss the distinction between attributional and consequential LCA. For the Inventory Analysis, this distinction is relevant when discussing system boundaries, data collection, and allocation. Also highlighted are developments concerning databases and Input-Output and hybrid LCA. In the sections on Life Cycle Impact Assessment we discuss the characteristics of the modelling as well as some recent developments for specific impact categories and weighting. In relation to the Interpretation the focus is on uncertainty analysis. Finally, we discuss recent developments in relation to some of the strengths and weaknesses of LCA.

Resource depletion potentials from bottom-up models: Population dynamics and the Hubbert peak theory.

Life cycle impact assessment uses so-called characterization factors to address different types of environmental impact (e.g. climate change, particulate matter, land use…). For the topic of resource depletion, a series of proposals was based on heuristic and formal arguments, but without the use of expert-based models from relevant research areas. A recent study in using fish population models has confirmed the original proposal for characterization factors for biotic resources of the nineties. Here we trace the milestones of the arguments and the designs of resource depletion, delivering an ecological-based foundation for the biotic case, and extend it by a novel analysis of the Hubbert peak theory for the abiotic case. We show that the original abiotic depletion potential, used for two decades in life cycle assessment, estimates accurately a marginal depletion characterization factor obtained from a dynamic model of the available reserve. This is illustrated for 29 metal resources using published data.

Towards optimal trade-offs between material and energy recovery for green waste.

Green waste is a type of biomass consisting mainly of grass, leaves and fresh prunings originating from gardens and parks. It can be used as feedstock for composting, or for energy recovery. The EU Waste Directive 2008/98/EC advocates composting to prevent waste. This directive allows green waste to be used for (renewable) energy valorization only if a better overall environmental outcome can be demonstrated. In this paper, we propose an assessment procedure based on examining the Pareto front of optimal trade-off combinations for maximizing composting and energy recovery of green waste while minimizing environmental impact and minimizing particulate matter emission. The Pareto optimal front is determined by solving a multi-objective optimization problem using the ε-constraint method. Previous research on green waste valorization using Life Cycle Analysis (LCA) shows that either energy recovery or composting is the preferred option depending on how environmental impact is assessed. In contrast to the full assignment to one of these recovery methods produced by LCA, we demonstrate, using the case of green waste valorization in the Netherlands and Belgium, that the proposed assessment procedure provides optimal solutions in a range between full allocation to compost or energy recovery. The proposed methodology supports the selection of optimal solutions taking the decision makers' preference into account that allows complying with Directives that have opposite goals on green waste valorization. Finally, computational results show that the assessment of the "better environmental outcome" requested by the EU waste Directive 2008/98/EC is influenced by the life cycle impact categories and the policy makers preferences with respect to the valorization options taken into account. Since the EU waste Directive 2008/98/EC does not specify how to execute the outcome assessment of valorization alternatives, this can lead to ambiguity.

A tool to guide the selection of impact categories for LCA studies by using the representativeness index.

Understanding the environmental profile of a product computed from the Life Cycle Assessment (LCA) framework is sometimes challenging due to the high number of environmental indicators involved. The objective here, in guiding interpretation of LCA results, is to highlight the importance of each impact category for each product alternative studied. For a given product, the proposed methodology identifies the impact categories that are worth focusing on, relatively to a whole set of products from the same cumulated database. The approach extends the analysis of Representativeness Indices (RI) developed by Esnouf et al. (2018). It proposes a new operational tool for calculating RIs at the level of impact categories for a Life Cycle Inventory (LCI) result. Impact categories and LCI results are defined as vectors within a standardized vector space and a procedure is proposed to treat issues coming from the correlation of impact category vectors belonging to the same Life Cycle Impact Assessment (LCIA) method. From the cumulated ecoinvent database, LCI results of the Chinese and the German electricity mixes illustrate the method. Relevant impact categories of the EU-standardized ILCD method are then identified. RI results from all products of a cumulated LCI database were therefore analysed to assess the main tendencies of the impact categories of the ILCD method. This operational approach can then significantly contribute to the interpretation of the LCA results by pointing to the specificities of the inventories analysed and for identifying the main representative impact categories.