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Defining freshwater as a natural resource: A framework linking water use to the area of protection natural resources.

ABSTRACT: Purpose:While many examples have shown unsustainable use of freshwater resources, existing LCIA methods for water use do not comprehensively address impacts to natural resources for future generations. This framework aims to (1) define freshwater resource as an item to protect within the Area of Protection (AoP) natural resources, (2) identify relevant impact pathways affecting freshwater resources, and (3) outline methodological choices for impact characterization model development. Method:Considering the current scope of the AoP natural resources, the complex nature of freshwater resources and its important dimensions to safeguard safe future supply, a definition of freshwater resource is proposed, including water quality aspects. In order to clearly define what is to be protected, the freshwater resource is put in perspective through the lens of the three main safeguard subjects defined by Dewulf et al. (2015). In addition, an extensive literature review identifies a wide range of possible impact pathways to freshwater resources, establishing the link between different inventory elementary flows (water consumption, emissions and land use) and their potential to cause long-term freshwater depletion or degradation. Results and discussion:Freshwater as a resource has a particular status in LCA resource assessment. First, it exists in the form of three types of resources: flow, fund, or stock. Then, in addition to being a resource for human economic activities (e.g. hydropower), it is above all a non-substitutable support for life that can be affected by both consumption (source function) and pollution (sink function). Therefore, both types of elementary flows (water consumption and emissions) should be linked to a damage indicator for freshwater as a resource. Land use is also identified as a potential stressor to freshwater resources by altering runoff, infiltration and erosion processes as well as evapotranspiration. It is suggested to use the concept of recovery period to operationalize this framework: when the recovery period lasts longer than a given period of time, impacts are considered to be irreversible and fall into the concern of freshwater resources protection (i.e. affecting future generations), while short-term impacts effect the AoP ecosystem quality and human health directly. It is shown that it is relevant to include this concept in the impact assessment stage in order to discriminate the long-term from the short-term impacts, as some dynamic fate models already do. Conclusion:This framework provides a solid basis for the consistent development of future LCIA methods for freshwater resources, thereby capturing the potential long-term impacts that could warn decision makers about potential safe water supply issues in the future.

SUBMITTER: Pradinaud C

PROVIDER: S-EPMC6733276 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Defining freshwater as a natural resource: A framework linking water use to the area of protection natural resources.

Pradinaud Charlotte C Northey Stephen S Amor Ben B Bare Jane J Benini Lorenzo L Berger Markus M Boulay Anne-Marie AM Junqua Guillaume G Lathuillière Michael J MJ Margni Manuele M Motoshita Masaharu M Niblick Briana B Payen Sandra S Pfister Stephan S Quinteiro Paula P Sonderegger Thomas T Rosenbaum Ralph K RK

The international journal of life cycle assessment 20190101 5

<h4>Purpose</h4>While many examples have shown unsustainable use of freshwater resources, existing LCIA methods for water use do not comprehensively address impacts to natural resources for future generations. This framework aims to (1) define freshwater resource as an item to protect within the Area of Protection (AoP) natural resources, (2) identify relevant impact pathways affecting freshwater resources, and (3) outline methodological choices for impact characterization model development.<h4> ...[more]

PMID: 31501640

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Project description:BackgroundA plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language.MethodsA Natural Language Processing engine which can "translate" free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at ( http://calchas.ics.forth.gr/ ).ResultsFor our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either individually or as a set of tools forming a computational pipeline. The results were compared with those obtained from an automated discovery of candidate biomedical tools. For the evaluation of the results, precision and recall measurements were used. Our results indicate that the proposed framework has a high precision and low recall, implying that the system returns essentially more relevant results than irrelevant.ConclusionsThere are adequate biomedical ontologies already available, sufficiency of existing NLP tools and quality of biomedical annotation systems for the implementation of a biomedical resources discovery framework, based on the semantic annotation of resources and the use on NLP techniques. The results of the present study demonstrate the clinical utility of the application of the proposed framework which aims to bridge the gap between clinical question in natural language and efficient dynamic biomedical resources discovery.

Project description:A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.

Project description:ObjectiveElectronic medical records (EMRs) are increasingly repurposed for activities beyond clinical care, such as to support translational research and public policy analysis. To mitigate privacy risks, healthcare organizations (HCOs) aim to remove potentially identifying patient information. A substantial quantity of EMR data is in natural language form and there are concerns that automated tools for detecting identifiers are imperfect and leak information that can be exploited by ill-intentioned data recipients. Thus, HCOs have been encouraged to invest as much effort as possible to find and detect potential identifiers, but such a strategy assumes the recipients are sufficiently incentivized and capable of exploiting leaked identifiers. In practice, such an assumption may not hold true and HCOs may overinvest in de-identification technology. The goal of this study is to design a natural language de-identification framework, rooted in game theory, which enables an HCO to optimize their investments given the expected capabilities of an adversarial recipient.MethodsWe introduce a Stackelberg game to balance risk and utility in natural language de-identification. This game represents a cost-benefit model that enables an HCO with a fixed budget to minimize their investment in the de-identification process. We evaluate this model by assessing the overall payoff to the HCO and the adversary using 2100 clinical notes from Vanderbilt University Medical Center. We simulate several policy alternatives using a range of parameters, including the cost of training a de-identification model and the loss in data utility due to the removal of terms that are not identifiers. In addition, we compare policy options where, when an attacker is fined for misuse, a monetary penalty is paid to the publishing HCO as opposed to a third party (e.g., a federal regulator).ResultsOur results show that when an HCO is forced to exhaust a limited budget (set to $2000 in the study), the precision and recall of the de-identification of the HCO are 0.86 and 0.8, respectively. A game-based approach enables a more refined cost-benefit tradeoff, improving both privacy and utility for the HCO. For example, our investigation shows that it is possible for an HCO to release the data without spending all their budget on de-identification and still deter the attacker, with a precision of 0.77 and a recall of 0.61 for the de-identification. There also exist scenarios in which the model indicates an HCO should not release any data because the risk is too great. In addition, we find that the practice of paying fines back to a HCO (an artifact of suing for breach of contract), as opposed to a third party such as a federal regulator, can induce an elevated level of data sharing risk, where the HCO is incentivized to bait the attacker to elicit compensation.ConclusionsA game theoretic framework can be applied in leading HCO's to optimized decision making in natural language de-identification investments before sharing EMR data.

Project description:Consumer-resource interactions are a central issue in evolutionary and community ecology because they play important roles in selection and population regulation. Most consumers encounter resource variation at multiple scales, and respond through phenotypic plasticity in the short term or evolutionary divergence in the long term. The key traits for these responses may influence resource acquisition, assimilation and/or allocation. To identify candidate genes, we experimentally assayed genome-wide gene expression in pond and lake Daphnia ecotypes exposed to alternate resource environments. One was a simple, high-quality laboratory diet, Ankistrodesmus falcatus. The other was the complex natural seston from a large lake. In temporary ponds, Daphnia generally experience high-quality, abundant resources, whereas lakes provide low-quality, seasonally shifting resources that are chronically limiting. For both ecotypes, we used replicate clones drawn from a number of separate populations. We compared gene expression in whole Daphnia pulex that had been raised in the lab for 10 days, and then exposed to alternate resource environments for 24 hours. One resource environment was a 24 hour continuation of the lab resource, a satiating level of Ankistrodesmus falcatus. The alternate environment was the natural seston present in the epilimnion of Lake Murray, South Carolina. Two ecotypes were analyzed, one adapted to large lakes, and one adapted to temporary ponds. For each ecotype, eight replicate clones were used. Clones of the lake ecotype were isolated from eight independent lakes, clones of the pond ecotype were isolated from six different ponds. The total number of arrays is 16 (8 replicate clones x 2 ecotypes) x 2 resource environments). Total RNA was extracted from eight whole organisms pooled together. Pools were then converted to cDNA and labelled with a single round of amplification. For array hybridizations, samples from the two resource environments were paired for each clone, and dyes were swapped across clones.

Dataset Information

Defining freshwater as a natural resource: A framework linking water use to the area of protection natural resources.

Publications

Defining freshwater as a natural resource: A framework linking water use to the area of protection natural resources.

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