A System Dynamics Approach to Evaluating Sludge Management Strategies in Vinasse Treatment: Cost-Benefit Analysis and Scenario Assessment

TL;DR

This paper introduces a System Dynamics Model to evaluate costs and scenarios for vinasse sludge management in Chile's alcohol industry, aiding decision-making for sustainable treatment strategies.

Contribution

It presents the first SDM tailored to industrial sludge management, incorporating variables like transport, coagulant use, and temperature for scenario analysis.

Findings

Model helps estimate costs of different management strategies.

Scenario analysis informs optimal vinasse treatment options.

Calibrated with real industry data for practical relevance.

Abstract

In the Chilean local alcohol industry (pisco indus- try), for one liter of alcohol produced 10-15 liters of vinasse as the main wastewater of the process. To comply with industrial waste regulations, vinasse must be stored, which enables evaporation, leaving behind a residual sludge. However, treating vinasse remains an environmental and industrial challenge, having a high nutrient concentration and acidity that can degrade soil quality and harm surrounding vegetation. While previous studies have modeled sludge generation and transport in urban water systems, research on industrial wastewater, such as the alcohol industry, remains limited, affecting the search for opportunities to improve the treatment process.. This paper proposes a System Dynamics Model (SDM) to assess the costs associated with three management strategies: natural drying of vinasse, relocation to an alternative site, and implementation of a coagulation- flocculation treatment to accelerate sludge production. This paper makes two contributions. First, we describe a pioneer SDM applicable to sludge management, which includes variables such as sludge transport, coagulant quantity, and ambient temperature to make hypothetical scenarios that affect the treatment processes of vinasse. Second, we present the expected results of the associated costs of the scenarios proposed in the model, helping decision-makers to manage vinasse. The model is calibrated with historical data provided by a company in the North of Chile, helping to improve the decision-making for vinasse treatment.