The removal of microorganisms and organic micropollutants from wastewater during infiltration to aquifers after irrigation of farmland in the Tula Valley, Mexico

The Tula Valley receives untreated wastewater from Mexico City for agricultural irrigation, half of which infiltrates to aquifers from where drinking water is extracted. Samples of wastewater and infiltrated water from three areas of the valley were analyzed for microorganisms, organic micropollutants, and some basic parameters. Concentrations of microorganisms in the infiltrated water were generally very low but the incidence of fecal coliforms (present in 68% of samples), somatic bacteriophages (36%), Giardia spp. (14%), and helminth eggs (8%) suggested a health risk. Organic micropollutants, often present at high concentrations in the wastewater, were generally absent from the infiltrated water except carbamazepine which was in 55% of samples (up to 193 ng/L). There was no correlation between carbamazepine concentrations and the presence of microorganisms but highest concentrations of carbamazepine and boron coincided. A treatment such as nanofiltration would be necessary for the infiltrated water to be a safe potable supply.     

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments.