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Furthermore, most of these data include a temporal dimension, often inextricably linked to the spatial one by the underlying physical process that the data represent. In this context, data is measured by instruments or generated by simulations before being processed by software and the resulting information or knowledge being saved in computers. 10.1007/s00477-022-02257-4 22 Tian D, He X, Srivastava P, Kalin L. A hybrid framework for forecasting monthly reservoir inflow based on machine learning techniques with dynamic climate forecasts, satellite-based data, and climate phenomenon information. [Extracted from the article]

Purpose: Life cycle assessment (LCA) practitioners face many challenges in their efforts to describe, share, review, and revise their product system models, and to reproduce the models and results of others. Current life cycle inventory modeling techniques have weaknesses in the areas of describing model structure, documenting the use of proxy or non-ideal data, specifying allocation, and including modeler’s observations and assumptions—all affecting how the study is interpreted and limiting the reuse of models. Moreover, LCA software systems manage modeling information in different and sometimes non-compatible ways. Practitioners must also deal with licensing, privacy/confidentiality of data, and other issues around data access which impact how a model can be shared.Methods: This letter was prepared by a working group of the North American Life Cycle Assessment Advisory Group to support the UNEP-SETAC Life Cycle Initiative’s Flagship Activity on Data, Methods, and Product Sustainability Information. The aim of the working group is to define a roadmap of the technical advances needed to achieve easier LCA model sharing and improve replicability of LCA results among different users in a way that is independent of the LCA software used to compute the results and does not infringe on any licensing restrictions or confidentiality requirements. This is intended to be a consensus document providing the state of the art in this area, with milestones for research and implementation needed to resolve current issues.Results and Conclusions: The roadmap identifies fifteen milestones in three areas: “describing model contents,” “describing model structure,” and “collaborative use of models.” The milestones should support researchers and software developers in advancing practitioners’ abilities to share and review product system models. [ABSTRACT FROM AUTHOR]

Purpose: Evaluation of soil functionality in Life Cycle Assessment (LCA) has progressively gained importance, although only a small cluster of studies deliver detailed guidelines on how to calculate quantified indicators. In addition, there is a lack of bibliography assessing impacts on the pedosphere due to spatially differentiated land use changes (LUC). In this study, an automated geospatial simulation of LUC based on crop rotation probabilities in Luxembourg was implemented in the programming environment R. Furthermore, this method based on coupling LCA and geographic information system (GIS) was used to calculate changes in soil functionality by implementing both the soil organic carbon (SOC) method and the Land Use Indicator Value Calculation Tool (LANCA®). The developed R script was then applied to a case study dealing with maize production for bioenergy purposes in Luxembourg. Methods: On the one hand, geo-referenced crop information in Luxembourg for the period 2005-2011 was used to calculate the estimated probability in which crop rotation occurs in combination with maize expansion to meet bioenergy production requirements by 2020. On the other hand, geo-referenced information for a wide range of parameters relevant in assessing soil functionality was stored in a geospatial database and mapped using R's geospatial data manipulation, analysis and visualisation capabilities. The geospatial data were used as input for the R LANCA® model, which calculates the environmental impacts associated with the five indicators considered in the model (erosion resistance, physicochemical filtration, mechanical filtration, biotic production and groundwater replenishment) for all the cultivated areas in Luxembourg. Results and discussion: The application of the two models demonstrated the significant differences in soil functionality in Luxembourgish arable land, namely between the north and south of the country. Spatial differentiation was found to be important in all indicators, except biotic production and physicochemical filtration, in which the availability of more detailed datasets and more specific methods is a must. Finally, the coupling of GIS and LCI data proved to be an interesting tool for estimating transition probabilities in crop rotation and, therefore, useful in forecasting suitable areas to implement future agricultural policies. Conclusions: GIS and LCI data coupling may constitute an interesting pathway to combine environmental impact assessment and spatial differentiation, provided that further improvements are performed in the method, including important soil parameters or farmer behaviour. In addition, the spatial mapping of environmental impacts can provide important support in terms of policy-making, conservation of natural resources, landscape, or agricultural planning. [ABSTRACT FROM AUTHOR]

Purpose: Consequential Life Cycle Assessment (C-LCA) is a 'system modelling approach in which activities in a product system are linked so that activities are included in the product system to the extent that they are expected to change as a consequence of a change in demand'. Hence, C-LCA focuses on micro-economic actions linked to macro-economic consequences, by identifying the (marginal) suppliers and technologies prone to be affected by variable scale changes in the demand of a product. Detecting the direct and indirect environmental effects due to changes in the production system is not an easy task. Hence, researchers have combined the consequential perspective with different econometric models. Therefore, the aim of this study is to assess an increase in biocrops cultivation in Luxembourg using three different consequential modelling approaches to understand the benefits, drawbacks and assumptions linked to each approach as applied to the case study selected. Methods: Firstly, a partial equilibrium (PE) model is used to detect changes in land cultivation based on the farmers' revenue maximisation. Secondly, another PE model is proposed, which considers a different perspective aiming at minimising a total adaptation cost (so-called opportunity cost) to satisfy a given new demand of domestically produced biofuel. Finally, the consequential system delimitation for agricultural LCA approach, as proposed by Schmidt (Int J Life Cycle Assess 13:350-364, ), is applied. Results and discussion: The two PE models present complex shifts in crop rotation land use changes (LUCs), linked to the optimisation that is performed, while the remaining approach has limited consequential impact on changes in crop patterns since the expert opinion decision tree constitutes a simplification of the ongoing LUCs. However, environmental consequences in the latter were considerably higher due to intercontinental trade assumptions recommended by the experts that were not accounted for in the economic models. Environmental variations between the different scenarios due to LUCs vary based on the different expert- or computational-based assumptions. Finally, environmental consequences as compared with the current state-of-the-art are lame due to the limited impact of the shock within the global trade market. Conclusions: The use of several consequential modelling approaches within the same study may help widen the interpretation of the advantages or risks of applying a specific change to a production system. In fact, different models may not only be good alternatives in terms of comparability of scenarios and assumptions, but there may also be room for complementing these within a unique framework to reduce uncertainties in an integrated way. [ABSTRACT FROM AUTHOR]

Purpose: The matrix method for the solution of the so-called inventory problem in LCA generally determines the inventory vector related to a specific system of processes by solving a system of linear equations. The paper proposes a new approach to deal with systems characterized by a rectangular (and thus non-invertible) coefficients matrix. The approach, based on the application of regression techniques, allows solving the system without using computational expedients such as the allocation procedure. Methods: The regression techniques used in the paper are (besides the ordinary least squares, OLS) total least squares (TLS) and data least squares (DLS). In this paper, the authors present the application of TLS and DLS to a case study related to the production of bricks, showing the differences between the results accomplished by the traditional matrix approach and those obtained with these techniques. The system boundaries were chosen such that the resulting technology matrix was not too big and thus easy to display, but at the same time complex enough to provide a valid demonstrative example for analyzing the results of the application of the above-described techniques. Results and discussion: The results obtained for the case study taken into consideration showed an obvious but not overwhelming difference between the inventory vectors obtained by using the least-squares techniques and those obtained with the solutions based upon allocation. The inventory vectors obtained with the DLS and TLS techniques are closer to those obtained with the physical rather than with the economic allocation. However, this finding most probably cannot be generalized to every inventory problem. Conclusions: Since the solution of the inventory problem in life cycle inventory (LCI) is not a standard forecasting problem because the real solution (the real inventory vector related to the investigated functional unit) is unknown, we are not able to compute a proper performance indicator for the implemented algorithms. However, considering that the obtained least squares solutions are unique and their differences from the traditional solutions are not overwhelming, this methodology is worthy of further investigation. Recommendations: In order to make TLS and DLS techniques a valuable alternative to the traditional allocation procedures, there is a need to optimize them for the very particular systems that commonly occur in LCI, i.e., systems with sparse coefficients matrices and a vector of constants whose entries are almost always all null but one. This optimization is crucial for their applicability in the LCI context. [ABSTRACT FROM AUTHOR]

Over the last decade, researchers paid much attention to concepts such as Design for Environment, Extended Producer Responsibility, Responsible Chain Management, and Eco-design. Many management tools and standards (such as EMAS, ISO 14001, LCA, EPD, Ecolabel) have been developed to support companies in the evaluation and management of their environmental performance and to pursue continual environmental improvement. The more recent development of the aforesaid fields looks at interorganizational environmental management. Such an approach can complement the more traditional intraorganizational corporate environmental management approaches and tools. A typical example of this new trend is the Product Oriented Environmental Management System (POEMS), which represents the natural evolution of the above-mentioned tools, combining the features of EMS, EPD and Ecolabel. Although the structure of the POEMS is still not standardized, many experimental applications have yet been carried out in Europe. In developing a POEMS, a company needs to determine all of the environmental impacts caused at all life-cycle stages of the product and, ideally, to reduce all of them through a continual commitment. The aim of the present study was to perform a survey of the developed POEMS models and to analyze their peculiarities and drawbacks in the application to Small and Medium Enterprises. A case study regarding an Italian winery company is presented. The study analyzes the structure and the activities of the examined firm, in order to estimate direct and indirect environmental impacts following a life-cycle approach. The chosen functional unit is a 0.75-L bottle of red wine. The article also suggests some solutions to improve the environmental performances of the firm’s products. [ABSTRACT FROM AUTHOR]