Prediction of Indirect Indicators of a Grass-Based Diet by Milk Fourier Transform Mid-Infrared Spectroscopy to Assess the Feeding Typologies of Dairy Farms.

This research aims to develop a predictive model to discriminate milk produced from a cattle diet either based on grass or not using milk mid-infrared spectrometry and the month of testing (an indirect indicator of the feeding ration). The dataset contained 3,377,715 spectra collected between 2011 and 2021 from 2449 farms and 3 grazing traits defined following the month of testing. Records from 30% of the randomly selected farms were kept in the calibration set, and the remaining records were used to validate the models.

LCA Capability Roadmap: Product System Model Description and Revision.

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.

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget.

Machine learning for toxicity characterization of organic chemical emissions using USEtox database: Learning the structure of the input space.

Toxicity characterization of chemical emissions in Life Cycle Assessment (LCA) is a complex task which usually proceeds via multimedia (fate, exposure and effect) models attached to models of dose-response relationships to assess the effects on target. Different models and approaches do exist, but all require a vast amount of data on the properties of the chemical compounds being assessed, which are hard to collect or hardly publicly available (especially for thousands of less common or newly developed chemicals), therefore hampering in practice the assessment in LCA. An example is USEtox, a consensual model for the characterization of human toxicity and freshwater ecotoxicity.

Emergy evaluation using the calculation software SCALE: case study, added value and potential improvements.

This paper reports the emergy-based evaluation (EME) of the ecological performance of four water treatment plants (WTPs) using three different approaches. The results obtained using the emergy calculation software SCALE (EMESCALE) are compared with those achieved through a conventional emergy evaluation procedure (EMECONV), as well as through the application of the Solar Energy Demand (SED) method. SCALE's results are based on a detailed representation of the chain of technological processes provided by the lifecycle inventory database ecoinvent®.