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D.L. Marrin   Dr.  Senior Scientist or Principal Investigator 
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D.L. Marrin published an article in April 2019.
Top co-authors
Joan Sabaté

80 shared publications

School of Public Health. Loma Linda University, Loma Linda, CA 92350, USA

Ujué Fresán

11 shared publications

School of Public Health, Hall Loma Linda University, Loma Linda, CA, USA

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Publications
Article 0 Reads 0 Citations Water Footprint of Meat Analogs: Selected Indicators According to Life Cycle Assessment Ujué Fresán, D. L. Marrin, Maximino Alfredo Mejia, Joan Saba... Published: 09 April 2019
Water, doi: 10.3390/w11040728
DOI See at publisher website ABS Show/hide abstract
Animal-based products reportedly have substantial water footprints. One alternative to meat products is meat analogs, which are processed plant-based foods mimicking real meat products. As data for the water footprints of meat analogs are limited, the present study assesses their water consumption and their potential for contributing to eutrophication and ecotoxicity in fresh and marine receiving waters. Life cycle assessments, which encompassed the generation of ingredients to the packaging of products, were performed for 39 meat analogs. Estimates for consumptive water use, ecotoxicity, and eutrophication are reported per ton of product and per kilogram of protein. On average, 3800 m3 of water were consumed per ton of product, whereas 0.56 kg P equivalents. and 12 kg 1,4-DCB (1,4-dichlorobenzene)) equivalents. were potentially released to terrestrial freshwaters and 2.2 kg N equivalents. and 7 kg 1,4-DCB equivalents. to marine waters. The predominant driver for water consumption and marine ecotoxicity was processing the meat analogs, whereas producing the raw ingredients was the main driver for freshwater toxicity and eutrophication. For reducing the use of and potential impacts on water, meat analogs may represent a viable alternative to processed meat products.
CONFERENCE-ARTICLE 12 Reads 0 Citations A Pattern-Based Approach to Evaluating Water Quality D.L. Marrin Published: 16 November 2017
Proceedings, doi: 10.3390/ecws-2-04945
DOI See at publisher website ABS Show/hide abstract

As water quality evaluations continue to expand in number of analytes and frequency of measurements, a challenge arises as how to present these data in a manner that can best be used to guide remedial actions and inform water resource decisions. Graphic artists have developed visualization techniques using colors, textures and layers that enhance people’s accessibility to and understanding of data. However, beyond just visual data enhancement, the use of hierarchically arranged spatial patterns or sequentially arranged temporal patterns can provide a means of discerning trends, anomalies and correlations among water quality parameters that would otherwise be difficult to distinguish. A related approach includes comparing actual water quality patterns with either ideal patterns (generated by models) or abstract patterns (created from theories) as a check on their practicality and relevance to the observed datasets. Finally, assessing the connectivity of water quality patterns as a coherent network, rather than as isolated data points, can expose potential feedback loops, counterintuitive or disproportionate effects, and data limitations. Pattern connectivity is also consistent with a systems interpretation of water quality, which may reveal subtle interactions among the water quality components or parameters. Perhaps the greatest advantage of pattern-based approaches is their usefulness to non-scientists (e.g., managers, stakeholders), who often misinterpret or are confused by the language, symbols, mathematics, and graphics appearing in technical reports and journal articles.

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