Abstract
Sludge conditioning by the Fenton process can effectively reduce sludge water content. The Fenton process has ideal dewaterability at different initial pH levels. However, the difference in the initial pH levels can lead to variations in conditioner dosage, resulting in different environmental impacts and economic pressures. This study provides insights into the role of the life cycle linked response surface methodology (LC-RSM) framework in revealing optimal solutions with both environmental and economic performance in different combinations of conditioners. Response surface methodology (RSM) was used to construct a model of sludge dewatering by the Fenton process, and life cycle assessment and life cycle cost were used to quantify the environmental and economic performance of all conditioning solutions in the model. The LC-RSM optimization solution was 6%–68% and 15%–70% lower than the RSM recommended solution in terms of environmental impacts and economic costs, respectively. For specific impact categories, such as global warming potential, the LC-RSM optimization solution was 19%–56% lower than the RSM recommended solution. In addition, the total environmental impact of the different conditioner combinations ranged between 4.1 and 7.8 Pt and 3.2–6.7 Pt at 53% and 58% of the sludge target water content, respectively. Surprisingly, the environmental impact of the solution with superior dewatering performance (53%) was lower than that of the solution with poor dewatering performance (58%) in many cases. The above results show that the LC-RSM optimization solution has better environmental and economic performance compared to RSM. In addition, the environmental impacts and economic costs of different solutions with the same water content target vary widely, which may lead to comparing sludge conditioning procedures with different targets in an unfair environment. Therefore, a unified platform for comparison is needed, and LC-RSM can provide support. This study can assist decision-makers in identifying the best solution for both environmental and economic performance in a multivariate system and stimulate further discussion on how to compare different processes on a more uniform platform.