Life cycle analysis applied to analytical methods for the detection of waterborne pathogens

Abstract

The Carbon Footprint (CFP) of novel analytical methods for waterborne pathogens detection is calculated to evaluate their environmental impact compared to the conventional methods used so far in drinking water analysis. These new-flanged methods are developed under the EU project Aquavalens that has as objective the development of sustainable technologies to provide water system managers with tools to better control the safety of water supplies and their impact on public health.The sources of primary data for the CFP calculation were the project partners, who were at same time part of the non-expert audience of the Life Cycle Assessment to whom the results are addressed. The new analytical methods are based on the use of two types of pathogen detection products, hereinafter referred to as analytical products: an on-line monitoring device and two ready-to-use kits for molecular detection techniques. These products were designed and manufactured by the producer partners of the project and they were tested experimentally in six European locations by different end-users partners. Specific questionnaires were designed to obtain flows of materials, energy and wastes associated to the analysis of one water sample, with special attention to packaging in the production of the analytical products and transport and energy consumption during the analytical procedure conducted.The use phase was identified as the major contributor to the CFP along the whole life cycle of the new analytical products. Up to 66% reduction was calculated for the Aquavalens analytical methods in relation to conventional methods when pathogens from the three groups (bacteria, protozoa and viruses) were analysed. The parametric variability calculated through Monte Carlo simulation showed the effect of different praxis and management during sampling and laboratory work. The collection of the samples, and specifically the transport to and from the sampling points to the laboratory, was found to be the most determinant contributor in the total CFP. Besides, the analysis considered alternative scenarios for the type of vehicle used in the sampling transport and different electricity production mixes.