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.

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.

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.

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.

An improved life cycle impact assessment principle for assessing the impact of land use on ecosystem services.

In order to consider the effects of land use, and the land cover changes it causes, on ecosystem services in life cycle assessment (LCA), a new methodology is proposed and applied to calculate midpoint and endpoint characterization factors. To do this, a cause-effect chain was established in line with conceptual models of ecosystem services to describe the impacts of land use and related land cover changes. A high-resolution, spatially explicit and temporally dynamic modeling framework that integrates land use and ecosystem services models was developed and used as an impact characterization model to simulate that cause-effect chain. Characterization factors (CFs) were calculated and regionalized at the scales of Luxembourg and its municipalities, taken as a case to show the advantages of the modeling approach. More specifically, the calculated CFs enable the impact assessment of six land cover types on six ecosystem functions and two final ecosystem services. A mapping and comparison exercise of these CFs allowed us to identify spatial trade-offs and synergies between ecosystem services due to possible land cover changes. Ultimately, the proposed methodology can offer a solution to overcome a number of methodological limitations that still exist in the characterization of impacts on ecosystem services in LCA, implying a rethinking of the modeling of land use in life cycle inventory.

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.

Morphological and Molecular Characterization of Orchid Fruit Development.

Efficient seed dispersal in flowering plants is enabled by the development of fruits, which can be either dehiscent or indehiscent. Dehiscent fruits open at maturity to shatter the seeds, while indehiscent fruits do not open and the seeds are dispersed in various ways. The diversity in fruit morphology and seed shattering mechanisms is enormous within the flowering plants. How these different fruit types develop and which molecular networks are driving fruit diversification is still largely unknown, despite progress in eudicot model species. The orchid family, known for its astonishing floral diversity, displays a huge variation in fruit dehiscence types, which have been poorly investigated. We undertook a combined approach to understand fruit morphology and dehiscence in different orchid species to get more insight into the molecular network that underlies orchid fruit development. We describe fruit development in detail for the epiphytic orchid species Erycina pusilla and compare it to two terrestrial orchid species: Cynorkis fastigiata and Epipactis helleborine. Our anatomical analysis provides further evidence for the split carpel model, which explains the presence of three fertile and three sterile valves in most orchid species. Interesting differences were observed in the lignification patterns of the dehiscence zones. While C. fastigiata and E. helleborine develop a lignified layer at the valve boundaries, E. pusilla fruits did not lignify at these boundaries, but formed a cuticle-like layer instead. We characterized orthologs of fruit-associated MADS-domain transcription factors and of the Arabidopsis dehiscence-related genes INDEHISCENT (IND)/HECATE 3 (HEC3), REPLUMLESS (RPL) and SPATULA (SPT)/ALCATRAZ (ALC) in E. pusilla, and found that the key players of the eudicot fruit regulatory network appear well-conserved in monocots. Protein-protein interaction studies revealed that MADS-domain complexes comprised of FRUITFULL (FUL), SEPALLATA (SEP) and AGAMOUS (AG) /SHATTERPROOF (SHP) orthologs can also be formed in E. pusilla, and that the expression of HEC3, RPL, and SPT can be associated with dehiscence zone development similar to Arabidopsis. Our expression analysis also indicates differences, however, which may underlie fruit divergence.

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.

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.

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.

Setting the stage for debating the roles of risk assessment and life-cycle assessment of engineered nanomaterials.

Although technological and environmental benefits are important stimuli for nanotechnology development, these technologies have been contested from an environmental point of view. The steady growth of applications of engineered nanomaterials has heated up the debate on quantifying the environmental repercussions. The two main scientific methods to address these environmental repercussions are risk assessment and life-cycle assessment. The strengths and weaknesses of each of these methods, and the relation between them, have been a topic of debate in the world of traditional chemistry for over two decades. Here we review recent developments in this debate in general and for the emerging field of nanomaterials specifically. We discuss the pros and cons of four schools of thought for combining and integrating risk assessment and life-cycle assessment and conclude with a plea for action.

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.

Product carbon footprints and their uncertainties in comparative decision contexts.

In response to growing awareness of climate change, requests to establish product carbon footprints have been increasing. Product carbon footprints are life cycle assessments restricted to just one impact category, global warming. Product carbon footprint studies generate life cycle inventory results, listing the environmental emissions of greenhouse gases from a product's lifecycle, and characterize these by their global warming potentials, producing product carbon footprints that are commonly communicated as point values. In the present research we show that the uncertainties surrounding these point values necessitate more sophisticated ways of communicating product carbon footprints, using different sizes of catfish (Pangasius spp.) farms in Vietnam as a case study. As most product carbon footprint studies only have a comparative meaning, we used dependent sampling to produce relative results in order to increase the power for identifying environmentally superior products. We therefore argue that product carbon footprints, supported by quantitative uncertainty estimates, should be used to test hypotheses, rather than to provide point value estimates or plain confidence intervals of products' environmental performance.