Comparative LCA of decentralized wastewater treatment alternatives for non-potable urban reuse.

Municipal wastewater (WW) effluent represents a reliable and significant source for reclaimed water, very much needed nowadays. Water reclamation and reuse has become an attractive option for conserving and extending available water sources. The decentralized approach to domestic WW treatment benefits from the advantages of source separation, which makes available simple small-scale systems and on-site reuse, which can be constructed on a short time schedule and occasionally upgraded with new technological developments. In this study we perform a Life Cycle Assessment to compare between the environmental impacts of four alternatives for a hypothetical city's water-wastewater service system. The baseline alternative is the most common, centralized approach for WW treatment, in which WW is conveyed to and treated in a large wastewater treatment plant (WWTP) and is then discharged to a stream. The three alternatives represent different scales of distribution of the WW treatment phase, along with urban irrigation and domestic non-potable water reuse (toilet flushing). The first alternative includes centralized treatment at a WWTP, with part of the reclaimed WW (RWW) supplied back to the urban consumers. The second and third alternatives implement de-centralized greywater (GW) treatment with local reuse, one at cluster level (320 households) and one at building level (40 households). Life cycle impact assessment results show a consistent disadvantage of the prevailing centralized approach under local conditions in Israel, where seawater desalination is the marginal source of water supply. The alternative of source separation and GW reuse at cluster level seems to be the most preferable one, though its environmental performance is only slightly better than GW reuse at building level. Centralized WW treatment with urban reuse of WWTP effluents is not advantageous over decentralized treatment of GW because the supply of RWW back to consumers is very costly in materials and energy. Electricity is a major driver of the impacts in most categories, pertaining mostly to potable water production and supply. Infrastructure was found to have a notable effect on metal depletion, human toxicity and freshwater and marine ecotoxicity. Sensitivity to major model parameters was analyzed. A shift to a larger share of renewable energy sources in the electricity mix results in a dramatic improvement in most impact categories. Switching to a mix of water sources, rather than the marginal source, leads to a significant reduction in most impacts. It is concluded that under the conditions tested, a decentralized approach to urban wastewater management is environmentally preferable to the common centralized system. It is worth exploring such options under different conditions as well, in cases which new urban infrastructure is planned or replacement of old infrastructure is required.

A coupled model tree (MT) genetic algorithm (GA) scheme for biofouling assessment in pipelines.

A computerized learning algorithm was developed for assessing the extent of biofouling formations on the inner surfaces of water supply pipelines. Four identical pipeline experimental systems with four different types of inlet waters were set up as part of a large cooperative project between academia and industry in Israel on biofouling modeling, prediction, and prevention in pipeline systems. Samples were taken periodically for hydraulic, chemical, and biological analyses. Biofilm sampling was done using Robbins devices, carrying stainless steel coupons. An MT-GA, a hybrid model combining model trees (MTs) and genetic algorithms (GAs) in which the sampled input data are selected by the proposed methodology, was developed. The method outcome is a set of empirical linear rules which form a model tree, iteratively optimized by a GA and verified using the dataset resulting from the empirical field studies. Good correlations were achieved between modeled and observed cell coverage area within the biofilm. Sensitivity analysis was conducted by testing the model's response to changes in: (1) the biofilm measure used as output (target) variable; (2) variability of GA parameters; and (3) input attributes. The proposed methodology provides a new tool for biofouling assessment in pipelines.

A preliminary coupled MT-GA model for the prediction of highway runoff quality.

Pollutants accumulated on road pavement during dry periods are washed off the surface with runoff water during rainfall events, presenting a potentially hazardous non-point source of pollution. Estimation of pollutant loads in these runoff waters is required for developing mitigation and management strategies, yet the numerous factors involved and their complex interconnected influences make straightforward assessment impossible. Data-driven models (DDMs) have lately been used in water and environmental research and have shown very good prediction ability. The proposed methodology of a coupled MT-GA (model tree-genetic algorithm) model provides an effective, accurate and easily calibrated predictive model for EMC (event mean concentration) of highway runoff pollutants. The models were trained and verified using a comprehensive data set of runoff events monitored in various highways in California, USA. EMCs of Cr, Pb, Zn, TOC and TSS were modeled, using different combinations of explanatory variables. The models' prediction ability in terms of correlation between predicted and actual values of both training and verification data was mostly higher than previously reported values. Sensitivity analysis was performed to examine the relative significance of each explanatory variable and the models' response to changes in input values.