Systematic Analysis Of Pollution Generation And Prevention

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A generalized industrial manufacturing plant is illustrated in Figure 2. As shown, mass and energy flow enter the manufacturing processes, which include raw materials, energy (e.g., heat and electricity), water used for manufacture and/or cooling purpose, and air. In order to enhance chemical reactions, catalysts, which may be very expensive (e.g., rhodium, gold, and silver), are added into the reactors. The inflow can include the above substances and energy. Through the manufacture, profitable products are produced, together with byproducts and wastes. Byproducts have their own values only when they are used for adjustable applications; otherwise, they can become wastes.

Wastes can be categorized as harmless or harmful. The former essentially does not have an environmental impact, while the latter is important. Identification of harmful wastes, design of new manufacturing processes, and retrofits of existing plants can be conducted with help of knowledge-based approaches and/or numerical optimization approaches. Conceptual tools have also been used in the development stages of a design. A hierarchical decision procedure described by Douglas is a good example [17].

The knowledge-based system, sometimes called an expert system, is a system of rules based on an area of expert proven knowledge. It also can be used for hierarchical design and review procedures. Computer programs based on the system can simulate human thought processes and can therefore be used to design cleaner manufacturing facilities to produce less polluted (or greener) products. This system is essentially dependent upon a long-term accumulation of experts' knowledge. It can be used for new plant design as well as retrofit of an old plant. More recently, Halim and Srinivasan [18] developed an intelligent system for qualitative waste minimization analysis. A knowledge-based expert system, called ENVOP Expert was used to identify practical and cost-effective P2 programs. A case study of the hydrodealkylation process was tested with satisfactory results.

Figure 2 Illustration of manufacture production and subsequent waste generation.

Numerical optimization approaches are based on several considerations, such as energy consumption and mass transfer. Economic analysis together with consumption of both energy and mass have been incorporated by some researchers.

The well-cited pinch analysis (or pinch technology) originally developed based on fundamental thermodynamics has been used to analyze heat flows through industrial processes. It can be used for reduction of energy consumption. It also can be used to minimize wastewater in process industries [19]. Through water reuse and/or other the internal rearrangements in the manufacturing facility, the emission of waste to the environment can therefore be minimized. This approach was used for P2 in a citrus plant [20]. An initial diagnosis indicated that the maximum theoretical freshwater consumption or wastewater generation was reduced by 31%.

Single- and multi-objective optimization approaches have been used in the analysis of pollution prevention. The integration approach has been used in pollution prevention/ wastewater minimization programs [21-24]. The fundamentals of the approach are optimization/minimization of capital and operating costs with minimum waste production and energy consumption. A series of case studies is available in the literature. For example, Parthasarathy and Krishnagopalan [25] used mass integration for the systematic reallocation of aqueous resources in a Kraft pulp mill. An optimal allocation of chloride in different streams throughout the plant was achieved, which led to a built-up concentration below undesirable levels. More importantly, the freshwater requirement was reduced by 57%. For more technical information on P2 and case histories see Chapter 1.


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16. Krewer, UB.; Liauw, M.A.; Ramakrishna, M.; Babu, M.H,; Raghavan, K.V. Pollution prevention through solvent selection and waste minimization. Indust. Engng Chem. Res. 2002, 41, 4534.

17. Douglas, J.M. Process synthesis for waste minimization. Indust. Engng Chem. Res. 1992, 31(1), 238.

18. Halim, I.; Srinivasan, R. Integrated decision support system for waste minimization analysis in chemical processes. Environ. Sci. Technol2002, 36, 1640.

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20. Thevendiraraj, S.; Klemes, J.; Paz, D.; Aso, G.; Cardenas, G.J. Water and wastewater minimization study of a citrus plant Res. Conserv. Recycling2003, 37, 227.

21. El-Halwagi, M.M. Pollution Prevention Through Process Integration: Systematic Design Tools; Academic Press: San Diego, 1997.

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23. Savelski, M.J.; and Bagajewicz, M.J. On the optimality conditions of water utilization systems in process plants with single contaminants. Chem. Engng Sci. 2000, 55, 5035.

24. Bagajewicz, M.; Rodera, H.; Savelski, M. Energy efficient water utilization systems in process plants. Comput. Chem. Engng 2002, 26, 59.

25. Parthasarathy, G.; Krishnagopalan, G. Systematic reallocation of aqueous resources using mass integration in a typical pulp mill. Adv. Environ. Res. 2001, 5, 61.

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