Key Takeaways & Executive Findings
- •• • S1 (centralized undifferentiated) exhibits the highest environmental impact, with indicators 1.4–6.7 times those of S2 or S3, driven by electrode consumption and electricity use for large water volumes. • • S3 (distributed differentiated) achieves a 62% cost reduction compared to S1, primarily by simplifying the pipe network and reducing construction and maintenance costs. • • S3 yields the lowest life cycle environmental impact, particularly in non-biological resource depletion, primary energy consumption, and global warming potential. • • Optimizing electroflocculation reactor design to reduce electrode and electricity consumption can further lower environmental and economic burdens, enhancing sustainability.
Abstract
Fluoride pollution poses a serious threat to public health worldwide, particularly in dispersed residential areas where high-fluoride groundwater is the primary drinking water source. Electroflocculation-based defluorination is a preferable treatment option, but its environmental and economic impacts vary with the water supply scheme. This study established three schemes: centralized undifferentiated (S1), centralized differentiated (S2), and distributed differentiated (S3). Life cycle environmental impact and life cycle cost assessments were conducted. Results show that S1 has the largest negative environmental impact, with indicators ranging from 1.4 to 6.7 times those of S2 or S3, primarily due to electrode consumption and electricity usage. S3 exhibits the lowest water supply cost, achieving a 62% cost reduction compared to S1. The distributed differentiated scheme (S3) offers both lower life cycle environmental impact and the lowest life cycle cost, making it the most advantageous option for dispersed residential areas. This study provides a systematic basis for selecting optimal water supply schemes, promoting the practical application of electroflocculation defluorination in such regions.
1. Introduction
Fluoride contamination of groundwater remains a critical public health issue in dispersed residential areas, where centralized water infrastructure is often infeasible. Traditional defluorination methods, such as coagulation with aluminum salts, suffer from high energy and chemical costs, limiting their scalability. Electroflocculation has emerged as a promising alternative due to its high efficiency, environmental friendliness, and economic viability, yet its performance is highly dependent on the water supply scheme. Existing studies have largely focused on qualitative comparisons of single schemes, lacking systematic quantification of environmental and economic trade-offs.
This study addresses this gap by applying life cycle assessment (LCA) and life cycle cost (LCC) to compare three water supply schemes: centralized undifferentiated (S1), centralized differentiated (S2), and distributed differentiated (S3). The key innovation lies in quantifying the environmental and economic impacts of electroflocculation under different scales of water treatment and distribution. The findings demonstrate that distributed differentiated supply (S3) significantly reduces both environmental burden and cost, offering a practical solution for remote communities. This evidence-based approach provides a scientific foundation for selecting optimal water supply schemes, thereby facilitating the deployment of electroflocculation defluorination in dispersed residential areas.
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FENG Jianheng, CHEN Mingru, GUO Xu, YU Zhancheng, ZHOU Binlong, ZHOU Lü (2026). Selection of Water Supply Schemes for Groundwater Defluorination by Electroflocculation in Dispersed Residential Areas. Journal of Environmental Engineering Technology. https://doi.org/10.13205/j.hjgc.202608014
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Frequently Asked Questions
What are the specific environmental impact indicators that differentiate S1 from S2 and S3, and how do they quantify the trade-offs?
The study reports that S1's environmental impact indicators range from 1.4 to 6.7 times those of S2 or S3, with the largest contributions from electrode consumption and electricity usage. This quantification highlights that centralized undifferentiated treatment of large water volumes amplifies resource depletion and global warming potential, whereas differentiated schemes reduce treatment volume and associated impacts.
How does the 62% cost reduction in S3 compare with potential increases in maintenance or operational complexity?
The 62% cost reduction in S3 is primarily attributed to simplified pipe networks, which lower construction and maintenance costs. While distributed systems may require more decentralized management, the study indicates that the overall life cycle cost remains lowest, suggesting that operational complexity does not offset the economic benefits.
What are the key factors driving the environmental impact in electroflocculation systems, and how can they be mitigated?
Electrode consumption and electricity usage are the primary drivers. The study suggests optimizing reactor design to reduce electrode and energy consumption, which would proportionally lower environmental impacts across all schemes, particularly in S1 where treatment volumes are largest.
How does the choice of water supply scheme affect the scalability of electroflocculation for varying population densities?
The study focuses on dispersed residential areas, where S3 (distributed differentiated) is most advantageous. For denser populations, centralized schemes might become more efficient, but the findings indicate that for dispersed areas, distributed systems offer superior environmental and economic performance, guiding scalability decisions.
What are the limitations of the life cycle assessment in this study, and how might they influence the generalizability of the results?
The study does not specify system boundaries or data sources in the provided text, but typical LCA limitations include regional variability in electricity grids and material production. The results are specific to the context of dispersed residential areas in China, and extrapolation to other regions should account for local factors.
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