Pure water and resource recovery from municipal wastewater using high-rate activated sludge, reverse osmosis, and mainstream anammox: A pilot scale study

IF 11.4 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2024-09-13 DOI:10.1016/j.watres.2024.122443

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Abstract

In response to the escalating global water scarcity and the high energy consumption associated with traditional wastewater treatment plants, there is a growing demand for transformative wastewater treatment processes that promise greater efficiency and sustainability. This study presents an innovative approach for municipal wastewater treatment that integrates high-rate activated sludge with membrane bio-reactor (HRAS-MBR), reverse osmosis (RO) and partial nitrification-anammox (PN/A). With an influent of 8.4 m³/d, the HRAS-MBR demonstrated a removal efficiency of approximately 85 % for chemical oxygen demand (COD), with over 70 % of it being recovered for energy production. The RO system achieved a recovery rate of 75 % for the influent, producing pure water with an electrical conductivity of 50 μS/cm. Concurrently, it concentrated ammonia, thereby enhancing the effectiveness of the PN/A process for nitrogen removal in the mainstream, resulting in a removal efficiency exceeding 85 %. Notably, the HRAS-MBR achieved significant phosphorus removal without chemical additives, attributed to the presence of influent calcium and magnesium ions. Overall, this integrated system reduced the net energy consumption for reclaimed water production by about 26 % compared to conventional methods. Additionally, the new process produced a revenue of 0.75 CNY/m³, demonstrating considerable economic and environmental benefits. This pilot-scale study offers a viable alternative for wastewater treatment and water reuse in water-scarce regions, contributing to sustainable water resource management.

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利用高速活性污泥法、反渗透法和主流厌氧法从城市污水中回收纯净水和资源：中试规模研究

为应对全球日益严重的水资源短缺问题和传统污水处理厂的高能耗问题，人们对有望提高效率和可持续性的变革性污水处理工艺的需求与日俱增。本研究介绍了一种创新的城市污水处理方法，它将高速率活性污泥与膜生物反应器（HRAS-MBR）、反渗透（RO）和部分硝化-氨氧化（PN/A）集成在一起。在进水量为 8.4 立方米/天的情况下，HRAS-MBR 对化学需氧量 (COD) 的去除率约为 85%，其中超过 70% 的 COD 被回收用于能源生产。反渗透系统对进水的回收率达到 75%，产生的纯水电导率为 50 μS/cm。与此同时，它还浓缩了氨，从而提高了 PN/A 工艺在主流中脱氮的效果，使脱氮效率超过 85%。值得注意的是，HRAS-MBR 在不使用化学添加剂的情况下实现了显著的除磷效果，这归功于进水钙镁离子的存在。总体而言，与传统方法相比，这种集成系统将再生水生产的净能耗降低了约 26%。此外，新工艺产生的收益为 0.75 元人民币/立方米，显示了可观的经济和环境效益。这项中试规模的研究为缺水地区的废水处理和中水回用提供了一种可行的替代方法，有助于水资源的可持续管理。

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来源期刊

Water Research 环境科学-工程：环境

CiteScore

20.80

自引率

9.40%

发文量

1307

审稿时长

38 days

期刊介绍： Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.