Using causal maps to support ex-post assessment of social impacts of dams

This paper presents the results of an ex-post assessment of two important dams in Brazil. The study follows the principles of Social Impact Management, which offer a suitable framework for analyzing the complex social transformations triggered by hydroelectric dams. In the implementation of this approach, participative causal maps were used to identify the ex-post social impacts of the Porto Primavera and Rosana dams on the community of Porto Rico, located along the High Paraná River. We found that in the operation of dams there are intermediate causes of a political nature, stemming from decisions based on values and interests not determined by neutral, exclusively technical reasons; and this insight opens up an area of action for managing the negative impacts of dams.

Combined simulation-optimization methodology for the design of environmental conscious absorption systems

This work addresses the optimization of ammonia–water absorption cycles for cooling and refrigeration applications with economic and environmental concerns. Our approach combines the capabilities of process simulation, multi-objective optimization (MOO), cost analysis and life cycle assessment (LCA). The optimization task is posed in mathematical terms as a multi-objective mixed-integer nonlinear program (moMINLP) that seeks to minimize the total annualized cost and environmental impact of the cycle. This moMINLP is solved by an outer-approximation strategy that iterates between primal nonlinear programming (NLP) subproblems with fixed binaries and a tailored mixed-integer linear programming (MILP) model. The capabilities of our approach are illustrated through its application to an ammonia–water absorption cycle used in cooling and refrigeration applications.

Simultaneous environmental and economic process synthesis of Isobutane Alkylation

This multidisciplinary study concerns the optimal design of processes with a view to both maximizing profit and minimizing environmental impacts. This can be achieved by a combination of traditional chemical process design methods, measurements of environmental impacts and advanced mathematical optimization techniques. More to the point, this paper presents a hybrid simulation-multiobjective optimization approach that at once optimizes the production cost and minimizes the associated environmental impacts of isobutane alkylation. This approach has also made it possible to obtain the flowsheet configurations and process variables that are needed to manufacture isooctane in a way that satisfies the above-stated double aim. The problem is formulated as a Generalized Disjunctive Programming problem and solved using state-of-the-art logic-based algorithms. It is shown, starting from existing alternatives for the process, that it is possible to systematically generate a superstructure that includes alternatives not previously considered. The optimal solution, in the form a Pareto curve, includes different structural alternatives from which the most suitable design can be selected. To evaluate the environmental impact, Life Cycle Assessment based on two different indicators is employed: Ecoindicator 99 and Global Warming Potential.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Isobutane Alkylation Process Synthesis by means of Hybrid Simulation-Multiobjective Optimization

Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the general public. For the resolution of the problem we employed a hybrid simulation- optimization methodology, i.e., the superstructure of the process was developed directly in a chemical process simulator connected to a state of the art optimizer. The model was formulated as a GDP and solved using a logic algorithm that avoids the reformulation as MINLP -Mixed Integer Non Linear Programming-. Our research gave us Pareto curves compounded by three different configurations where the LCA has been assessed by two different parameters: global warming potential and ecoindicator-99.

Vinasse application to sugar cane fields. Effect on the unsaturated zone and groundwater at Valle del Cauca (Colombia)

Extensive application of vinasse, a subproduct from sugar cane plantations for bioethanol production, is currently taking place as a source of nutrients that forms part of agricultural management in different agroclimatic regions. Liquid vinasse composition is characterised by high variability of organic compounds and major ions, acid pH (4.7), high TDS concentration (117,416–599,400 mg L− 1) and elevated EC (14,350–64,099 μS cm− 1). A large-scale sugar cane field application is taking place in Valle del Cauca (Colombia), where monitoring of soil, unsaturated zone and the aquifer underneath has been made since 2006 to evaluate possible impacts on three experimental plots. For this assessment, monitoring wells and piezometers were installed to determine groundwater flow and water samples were collected for chemical analysis. In the unsaturated zone, tensiometers were installed at different depths to determine flow patterns, while suction lysimeters were used for water sample chemical determinations. The findings show that in the sandy loam plot (Hacienda Real), the unsaturated zone is characterised by low water retention, showing a high transport capacity, while the other two plots of silty composition presented temporal saturation due to La Niña event (2010–2011). The strong La Niña effect on aquifer recharge which would dilute the infiltrated water during the monitoring period and, on the other hand dissolution of possible precipitated salts bringing them back into solution may occur. A slight increase in the concentration of major ions was observed in groundwater (~ 5% of TDS), which can be attributed to a combination of factors: vinasse dilution produced by water input and hydrochemical processes along with nutrient removal produced by sugar cane uptake. This fact may make the aquifer vulnerable to contamination.

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.

Bioindicators as metrics for environmental monitoring of desalination plant discharges

Development of desalination projects requires simple methodologies and tools for cost-effective and environmentally-sensitive management. Sentinel taxa and biotic indices are easily interpreted in the perspective of environment management. Echinoderms are potential sentinel taxon to gauge the impact produced by brine discharge and the BOPA index is considered an effective tool for monitoring different types of impact. Salinity increase due to desalination brine discharge was evaluated in terms of these two indicators. They reflected the environmental impact and recovery after implementation of a mitigation measure. Echinoderms disappeared at the station closest to the discharge during the years with highest salinity and then recovered their abundance after installation of a diffuser reduced the salinity increase. In the same period, BOPA responded due to the decrease in sensitive amphipods and the increase in tolerant polychaete families when salinities rose. Although salinity changes explained most of the observed variability in both indicators, other abiotic parameters were also significant in explaining this variability.