127 research outputs found

    Development of an Agricultural Primary Productivity Decision Support Model: A Case Study in France

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    Agricultural soils provide society with several functions, one of which is primary productivity. This function is defined as the capacity of a soil to supply nutrients and water and to produce plant biomass for human use, providing food, feed, fiber, and fuel. For farmers, the productivity function delivers an economic basis and is a prerequisite for agricultural sustainability. Our study was designed to develop an agricultural primary productivity decision support model. To obtain a highly accurate decision support model that helps farmers and advisors to assess and manage the provision of the primary productivity soil function on their agricultural fields, we addressed the following specific objectives: (i) to construct a qualitative decision support model to assess the primary productivity soil function at the agricultural field level; (ii) to carry out verification, calibration, and sensitivity analysis of this model; and (iii) to validate the model based on empirical data. The result is a hierarchical qualitative model consisting of 25 input attributes describing soil properties, environmental conditions, cropping specifications, and management practices on each respective field. An extensive dataset from France containing data from 399 sites was used to calibrate and validate the model. The large amount of data enabled data mining to support model calibration. The accuracy of the decision support model prior to calibration supported by data mining was ~40%. The data mining approach improved the accuracy to 77%. The proposed methodology of combining decision modeling and data mining proved to be an important step forward. This iterative approach yielded an accurate, reliable, and useful decision support model for the assessment of the primary productivity soil function at the field level. This can assist farmers and advisors in selecting the most appropriate crop management practices. Embedding this decision support model in a set of complementary models for four adjacent soil functions, as endeavored in the H2020 LANDMARK project, will help take the integrated sustainability of arable cropping systems to a new level

    Stomach cancer and occupational exposure to asbestos: a meta-analysis of occupational cohort studies

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    BACKGROUND: A recent Monographs Working Group of the International Agency for Research on Cancer concluded that there is limited evidence for a causal association between exposure to asbestos and stomach cancer. METHODS: We performed a meta-analysis to quantitatively evaluate this association. Random effects models were used to summarise the relative risks across studies. Sources of heterogeneity were explored through subgroup analyses and meta-regression. RESULTS: We identified 40 mortality cohort studies from 37 separate papers, and cancer incidence data were extracted for 15 separate cohorts from 14 papers. The overall meta-SMR for stomach cancer for total cohort was 1.15 (95% confidence interval 1.03–1.27), with heterogeneous results across studies. Statistically significant excesses were observed in North America and Australia but not in Europe, and for generic asbestos workers and insulators. Meta-SMRs were larger for cohorts reporting a SMR for lung cancer above 2 and cohort sizes below 1000. CONCLUSIONS: Our results support the conclusion by IARC that exposure to asbestos is associated with a moderate increased risk of stomach cancer

    Challenge clusters facing LCA in environmental decision-making—what we can learn from biofuels

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    Purpose Bioenergy is increasingly used to help meet greenhouse gas (GHG) and renewable energy targets. However, bioenergy’s sustainability has been questioned, resulting in increasing use of life cycle assessment (LCA). Bioenergy systems are global and complex, and market forces can result in significant changes, relevant to LCA and policy. The goal of this paper is to illustrate the complexities associated with LCA, with particular focus on bioenergy and associated policy development, so that its use can more effectively inform policymakers. Methods The review is based on the results from a series of workshops focused on bioenergy life cycle assessment. Expert submissions were compiled and categorized within the first two workshops. Over 100 issues emerged. Accounting for redundancies and close similarities in the list, this reduced to around 60 challenges, many of which are deeply interrelated. Some of these issues were then explored further at a policyfacing workshop in London, UK. The authors applied a rigorous approach to categorize the challenges identified to be at the intersection of biofuels/bioenergy LCA and policy. Results and discussion The credibility of LCA is core to its use in policy. Even LCAs that comply with ISO standards and policy and regulatory instruments leave a great deal of scope for interpretation and flexibility. Within the bioenergy sector, this has led to frustration and at times a lack of obvious direction. This paper identifies the main challenge clusters: overarching issues, application and practice and value and ethical judgments. Many of these are reflective of the transition from application of LCA to assess individual products or systems to the wider approach that is becoming more common. Uncertainty in impact assessment strongly influences planning and compliance due to challenges in assigning accountability, and communicating the inherent complexity and uncertainty within bioenergy is becoming of greater importance. Conclusions The emergence of LCA in bioenergy governance is particularly significant because other sectors are likely to transition to similar governance models. LCA is being stretched to accommodate complex and broad policy-relevant questions, seeking to incorporate externalities that have major implications for long-term sustainability. As policy increasingly relies on LCA, the strains placed on the methodology are becoming both clearer and impedimentary. The implications for energy policy, and in particular bioenergy, are large

    An increased response to experimental muscle pain is related to psychological status in women with chronic non-traumatic neck-shoulder pain

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    <p>Abstract</p> <p>Background</p> <p>Neck-shoulder pain conditions, e.g., chronic trapezius myalgia, have been associated with sensory disturbances such as increased sensitivity to experimentally induced pain. This study investigated pain sensitivity in terms of bilateral pressure pain thresholds over the trapezius and tibialis anterior muscles and pain responses after a unilateral hypertonic saline infusion into the right legs tibialis anterior muscle and related those parameters to intensity and area size of the clinical pain and to psychological factors (sleeping problems, depression, anxiety, catastrophizing and fear-avoidance).</p> <p>Methods</p> <p>Nineteen women with chronic non-traumatic neck-shoulder pain but without simultaneous anatomically widespread clinical pain (NSP) and 30 age-matched pain-free female control subjects (CON) participated in the study.</p> <p>Results</p> <p>NSP had lower pressure pain thresholds over the trapezius and over the tibialis anterior muscles and experienced hypertonic saline-evoked pain in the tibialis anterior muscle to be significantly more intense and locally more widespread than CON. More intense symptoms of anxiety and depression together with a higher disability level were associated with increased pain responses to experimental pain induction and a larger area size of the clinical neck-shoulder pain at its worst.</p> <p>Conclusion</p> <p>These results indicate that central mechanisms e.g., central sensitization and altered descending control, are involved in chronic neck-shoulder pain since sensory hypersensitivity was found in areas distant to the site of clinical pain. Psychological status was found to interact with the perception, intensity, duration and distribution of induced pain (hypertonic saline) together with the spreading of clinical pain. The duration and intensity of pain correlated negatively with pressure pain thresholds.</p

    Low carbon technology performance vs infrastructure vulnerability: Analysis through the local and global properties space

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    Renewable energy technologies, necessary for low-carbon infrastructure networks, are being adopted to help reduce fossil fuel dependence and meet carbon mitigation targets. The evolution of these technologies has progressed based on the enhancement of technology-specific performance criteria, without explicitly considering the wider system (global) impacts. This paper presents a methodology for simultaneously assessing local (technology) and global (infrastructure) performance, allowing key technological interventions to be evaluated with respect to their effect on the vulnerability of wider infrastructure systems. We use exposure of low carbon infrastructure to critical material supply disruption (criticality) to demonstrate the methodology. A series of local performance changes are analyzed; and by extension of this approach, a method for assessing the combined criticality of multiple materials for one specific technology is proposed. Via a case study of wind turbines at both the material (magnets) and technology (turbine generators) levels, we demonstrate that analysis of a given intervention at different levels can lead to differing conclusions regarding the effect on vulnerability. Infrastructure design decisions should take a systemic approach; without these multilevel considerations, strategic goals aimed to help meet low-carbon targets, that is, through long-term infrastructure transitions, could be significantly jeopardized

    Technische Zusammenfassung

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    Die Technische Zusammenfassung des APCC-Sonderberichts ″Landnutzung und Klimawandel in Österreich″ umfasst die Kernbotschaften der Kapitel 1–9. In ihr sind die Hauptaussagen zu den sozioökonomischen und klimatischen Treibern der Landnutzungsänderungen, zu den Auswirkungen von Landnutzung und -bewirtschaftung auf den Klimawandel, zu Minderungs- und Anpassungsoptionen im Kontext nachhaltiger Entwicklungsziele sowie zu Synergien, Zielkonflikten und Umsetzungsbarrieren von Klimamaßnahmen enthalten

    Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass‐loss rate and stabilization

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    The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models
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