DYNAMIC PROGRAMMING FOR OPTIMAL CAPACITY EXPANSION OF WASTEWATER TREATMENT PLANTS1

ABSTRACT: A dynamic programming procedure for the planning and operation of a wastewater treatment plant over a long period of time is presented. In order to meet increased demands for wastewater treatment in the future, the expansion of existing plants must be considered. Dynamic programming is employed to determine the optimal schedule of expansion at each plant, simultaneously determining an optimal operating policy (treatment level). The optimal schedule of expansion at each plant depends on the following: (1) the shape of the projected wastewater demand function; (2) the interest rate used; (3) the locations and capacities of the facilities available; and (4) the rates of increase of the costs of construction, labor, chemicals, and electric power. An example illustrating the use of the procedure is presented.     

USE OF A PREDICTIVE MODEL IN EVALUATING WATER CONSUMPTION CONSERVATION1

ABSTRACT: The effectiveness of water conservation policies on reduction of water consumption was evaluated by use of a multiple regression predictive model. Data were obtained from eight Iowa communities, with regard to water consumption and water conservation policies adopted during the drought of 1977. The proposed model, which takes precipitation, temperature, month effects, and uniqueness of communities into account, is considered superior to the use of simple percent changes in evaluating the significance of reduction in water consumption due to conservation efforts. Among the variety of policies reviewed, mandatory policies with per capita restrictions were found to be most effective. However, voluntary conservation policies also resulted in significant reduction in some communities located in close proximity to other communities with severer water shortages. High credibility of local governments as to water shortage information was singled out as the most important factor in successful conservation by water resource policymakers of these communities. Use of the proposed predictive model for water consumption was demonstrated. Recommendations regarding future water conservation were made.     

Review of ozone and temperature lidar validations performed within the framework of the Network for the Detection of Stratospheric Change

The use of assimilation tools for satellite validation requires true estimates of the accuracy of the reference data. Since its inception, the Network for Detection of Stratospheric Change (NDSC) has provided systematic lidar measurements of ozone and temperature at several places around the world that are well adapted for satellite validations. Regular exercises have been organised to ensure the data quality at each individual site. These exercises can be separated into three categories: large scale intercomparisons using multiple instruments, including a mobile lidar; using satellite observations as a geographic transfer standards to compare measurements at different sites; and comparative investigations of the analysis software. NDSC is a research network, so each system has its own history, design, and analysis, and has participated differently in validation campaigns. There are still some technological differences that may explain different accuracies. However, the comparison campaigns performed over the last decade have always proved to be very helpful in improving the measurements. To date, more efforts have been devoted to characterising ozone measurements than to temperature observations. The synthesis of the published works shows that the network can potentially be considered as homogeneous within +/-2% between 20-35 km for ozone and +/-1 K between 35-60 km for temperature. Outside this altitude range, larger biases are reported and more efforts are required. In the lower stratosphere, Raman channels seem to improve comparisons but such capabilities were not systematically compared. At the top of the profiles, more investigations on analysis methodologies are still probably needed. SAGE II and GOMOS appear to be excellent tools for future ozone lidar validations but need to be better coordinated and take more advantage of assimilation tools. Also, temperature validations face major difficulties caused by atmospheric tides and therefore require intercomparisons with the mobile systems, at all sites.     

Trace-metal detoxification in the ventral caeca of Orchestia gammarellus (Crustacea: Amphipoda)

The talitrid amphipod crustacean Orchestia gammarellus (Pallas) was collected from metal-contaminated (Dulas Bay, Gironde) and control (Millport) sites in the UK and France. Irrespective of site of origin, the amphipods showed the same physiological mechanism of trace-metal detoxification, involving the ventral caeca. Copper was always present in lysosomal residual bodies in the ventral caeca. Following laboratory exposure to zinc and cadmium, the lysosomes usually contained both copper and zinc but cadmium was not detectable. The lysosomal copper concentration is positively correlated to that of sulphur, while the concentration of lysosomal zinc is related to that of phosphorus. Results are interpreted in terms of the differential rates of turnover of metallothioneins chelating copper, zinc or cadmium. Received: 9 February 1999 / Accepted: 2 December 1999     

Process design for the environment: A multi-objective framework under uncertainty

Designing chemical processes for the environment requires consideration of several indexes of environmental impact including ozone depletion, global warming potentials, human and aquatic toxicity, photochemical oxidation, and acid rain potentials. Current methodologies, such as the generalized waste reduction algorithm (WAR), provide a first step towards evaluating these impacts. However, to address the issues of accuracy and the relative weights of these impact indexes, one must consider the problem of uncertainties. Environmental impacts must also be weighted and balanced against other concerns, such as their cost and long-term sustainability. These multiple, often conflicting, goals pose a challenging and complex optimization problem, requiring multi-objective optimization under uncertainty. This paper will address the problem of quantifying and analyzing the various objectives involved in process design for the environment. Towards this goal, we proposed a novel multi-objective optimization framework under uncertainty. This framework is based on new and efficient algorithms for multi-objective optimization and for uncertainty analysis. This approach finds a set of potentially optimal designs where trade-offs can be explicitly identified, unlike cost-benefit analysis, which deals with multiple objectives by identifying a single fundamental objective and then converting all the other objectives into this single currency. A benchmark process for hydrodealkylation (HDA) of toluene to produce benzene modeled in the ASPEN simulator is used to illustrate the usefulness of the approach in finding environmentally friendly and cost-effective designs under uncertainty.