Using Data Mining To Assess Environmental Impacts of Household Consumption Behaviors.

Household consumption is a main driver of economy and might be regarded as ultimately responsible for environmental impacts occurring over the life cycle of products and services. Given that purchase decisions are made on household levels and are highly behavior-driven, the derivation of targeted environmental measures requires an understanding of household behavior patterns and the resulting environmental impacts. To provide an appropriate basis in support of effective environmental policymaking, we propose a new approach to capture the variability of lifestyle-induced environmental impacts. Lifestyle-archetypes representing prevailing consumption patterns are derived in a two-tiered clustering that applies a Ward-clustering on top of a preconditioning self-organizing map. The environmental impacts associated with specific archetypical behavior are then assessed in a hybrid life cycle assessment framework. The application of this approach to the Swiss Household Budget Survey reveals a global picture of consumption that is in line with previous studies, but also demonstrates that different archetypes can be found within similar socio-economic household types. The appearance of archetypes diverging from general macro-trends indicates that the proposed approach might be useful for an enhanced understanding of consumption patterns and for the future support of policymakers in devising effective environmental measures targeting specific consumer groups.

A mathematical model to predict the effect of heat recovery on the wastewater temperature in sewers.

Raw wastewater contains considerable amounts of energy that can be recovered by means of a heat pump and a heat exchanger installed in the sewer. The technique is well established, and there are approximately 50 facilities in Switzerland, many of which have been successfully using this technique for years. The planning of new facilities requires predictions of the effect of heat recovery on the wastewater temperature in the sewer because altered wastewater temperatures may cause problems for the biological processes used in wastewater treatment plants and receiving waters. A mathematical model is presented that calculates the discharge in a sewer conduit and the spatial profiles and dynamics of the temperature in the wastewater, sewer headspace, pipe, and surrounding soil. The model was implemented in the simulation program TEMPEST and was used to evaluate measured time series of discharge and temperatures. It was found that the model adequately reproduces the measured data and that the temperature and thermal conductivity of the soil and the distance between the sewer pipe and undisturbed soil are the most sensitive model parameters. The temporary storage of heat in the pipe wall and the exchange of heat between wastewater and the pipe wall are the most important processes for heat transfer. The model can be used as a tool to determine the optimal site for heat recovery and the maximal amount of extractable heat.

Obtaining natural-like flow releases in diverted river reaches from simple riparian benefit economic models.

We propose a theoretical river modeling framework for generating variable flow patterns in diverted-streams (i.e., no reservoir). Using a simple economic model and the principle of equal marginal utility in an inverse fashion we first quantify the benefit of the water that goes to the environment in relation to that of the anthropic activity. Then, we obtain exact expressions for optimal water allocation rules between the two competing uses, as well as the related statistical distributions. These rules are applied using both synthetic and observed streamflow data, to demonstrate that this approach may be useful in 1) generating more natural flow patterns in the river reach downstream of the diversion, thus reducing the ecodeficit; 2) obtaining a more enlightened economic interpretation of Minimum Flow Release (MFR) strategies, and; 3) comparing the long-term costs and benefits of variable versus MFR policies and showing the greater ecological sustainability of this new approach.

Automatic reactor model synthesis with genetic programming.

Successful modeling of wastewater treatment plant (WWTP) processes requires an accurate description of the plant hydraulics. Common methods such as tracer experiments are difficult and costly and thus have limited applicability in practice; engineers are often forced to rely on their experience only. An implementation of grammar-based genetic programming with an encoding to represent hydraulic reactor models as program trees should fill this gap: The encoding enables the algorithm to construct arbitrary reactor models compatible with common software used for WWTP modeling by linking building blocks, such as continuous stirred-tank reactors. Discharge measurements and influent and effluent concentrations are the only required inputs. As shown in a synthetic example, the technique can be used to identify a set of reactor models that perform equally well. Instead of being guided by experience, the most suitable model can now be chosen by the engineer from the set. In a second example, temperature measurements at the influent and effluent of a primary clarifier are used to generate a reactor model. A virtual tracer experiment performed on the reactor model has good agreement with a tracer experiment performed on-site.

Identification of industrial wastewater by clustering wastewater treatment plant influent ultraviolet visible spectra.

A procedure is proposed which allows the detection of industrial discharge events at the inlet of a wastewater treatment plant without the need for measurements performed at the industry, for special equipment and for exact knowledge of the industrial sewage. By performing UV/Vis measurements at the inlet of a plant and analyzing them with a two-staged clustering method consisting of the self-organizing map algorithm and the Ward clustering method, typical sewage clusters can be found. In an experiment performed at a mid-sized Swiss plant, one cluster of a cluster model with five clusters could be attributed to an industrial laundry. Out of 95 laundry discharging events measured in a validation period, 93 were correctly detected by the proposed algorithm, two were false positives and five were false negatives.

Simulation of the wastewater temperature in sewers with TEMPEST.

TEMPEST is a new interactive simulation program for the estimation of the wastewater temperature in sewers. Intuitive graphical user interfaces assist the user in managing data, performing calculations and plotting results. The program calculates the dynamics and longitudinal spatial profiles of the wastewater temperature in sewer lines. Interactions between wastewater, sewer air and surrounding soil are modeled in TEMPEST by mass balance equations, rate expressions found in the literature and a new empirical model of the airflow in the sewer. TEMPEST was developed as a tool which can be applied in practice, i.e., it requires as few input data as possible. These data include the upstream wastewater discharge and temperature, geometric and hydraulic parameters of the sewer, material properties of the sewer pipe and surrounding soil, ambient conditions, and estimates of the capacity of openings for air exchange between sewer and environment. Based on a case study it is shown how TEMPEST can be applied to estimate the decrease of the downstream wastewater temperature caused by heat recovery from the sewer. Because the efficiency of nitrification strongly depends on the wastewater temperature, this application is of practical relevance for situations in which the sewer ends at a nitrifying wastewater treatment plant.