Free water surface constructed wetlands: Review of pollutant removal performance and modeling approaches

Author:

Gaballah Mohamed S.1ORCID,Yousefyani Hooshyar1,Karami Mohammadjavad1,Lammers Roderick W.1

Affiliation:

1. Central Michigan University

Abstract

Abstract

Free water surface constructed wetlands (FWSCWs) for the treatment of various wastewater types have evolved significantly over the last few decades. With an increasing need and interest in FWSCWs applications worldwide due to their cost-effectiveness and other benefits, this paper reviews recent literature on FWSCWs' ability to remove different types of pollutants (i.e., nutrients, heavy metals, antibiotics, and pesticides) that may co-exist in wetland inflow, and discusses approaches for simulating hydraulic and pollutant removal processes. A bibliometric analysis of recent literature reveals that China has the highest number of publications, followed by the USA. The collected data show that FWSCWs can remove an average of 61.6%, 67.8%, 54.7%, and 72.85% of inflowing nutrients, heavy metals, antibiotics, and pesticides, respectively. Optimizing each pollutant removal process requires specific design parameters. Removing heavy metal requires the lowest hydraulic retention time (HRT) (average of 4.78 days), removing pesticides requires the lowest water depth (average of 0.34 meters), and nutrient removal requires the largest system size. Vegetation, especially Typha spp. and Phragmites spp., play an important role in FWSCWs' system performance, making significant contributions to the removal process. Various modeling approaches (i.e., black-box and process-based) were comprehensively reviewed, revealing the need for including the internal process mechanisms related to the biological processes along with plants spp., that supported by a further research with field study validations. This work presents a state-of-the-art, systematic, and comparative discussion on the efficiency of FWSCWs in removing different pollutants, main design factors, the vegetation, and well-described models for performance prediction.

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3