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Constructed Wetlands (CW) are Nature-Based Solutions for wastewater treatment. Although being a sustainable, eco-friendly, and low-cost technology, CW has some operative limitations because its efficiency regarding wastewater treatment depends on several uncontrolled variables. Besides many design options, the main mechanisms of pollutant removal depend on wastewater composition and environmental variables. Thus, optimization of CW operation requires the simultaneous knowledge of a large set of parameters. Moreover, control of wastewater flow rate, the single manipulable variable, requires nearly real-time knowledge of those parameters’ variation. This work introduces the question of the effects of daily variation in the variables affecting CW efficiency and describes the EcoModZHC project, which aims the creation of a smart framework for real-time monitoring of CW. The EcoModZHC framework is based on water quality and environment variables sensors, supported by data acquisition and processing layers. Preliminary results demonstrated that daily variation of water quality is significant, causing deviations in the efficiency computation when traditional low-frequency sampling and laboratory analysis are applied. In addition, the EcoModZHC framework includes the control of a photovoltaic battery-assisted system, enabling the energetic autonomy of the complete CW system comprising the set of probes, pumps, and data acquisition and communication hardware.

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Development of a Smart Framework to Continuously Monitor Constructed Wetland Efficiency

  • 会议论文

  • 发表日期：

    2025年

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  • Henrique Pinho,
  • Manuel Barros,
  • Pedro Matos,
  • Carlos Ferreira,
  • Pedro Neves,
  • Dina Mateus

摘要

Constructed Wetlands (CW) are Nature-Based Solutions for wastewater treatment. Although being a sustainable, eco-friendly, and low-cost technology, CW has some operative limitations because its efficiency regarding wastewater treatment depends on several uncontrolled variables. Besides many design options, the main mechanisms of pollutant removal depend on wastewater composition and environmental variables. Thus, optimization of CW operation requires the simultaneous knowledge of a large set of parameters. Moreover, control of wastewater flow rate, the single manipulable variable, requires nearly real-time knowledge of those parameters’ variation. This work introduces the question of the effects of daily variation in the variables affecting CW efficiency and describes the EcoModZHC project, which aims the creation of a smart framework for real-time monitoring of CW. The EcoModZHC framework is based on water quality and environment variables sensors, supported by data acquisition and processing layers. Preliminary results demonstrated that daily variation of water quality is significant, causing deviations in the efficiency computation when traditional low-frequency sampling and laboratory analysis are applied. In addition, the EcoModZHC framework includes the control of a photovoltaic battery-assisted system, enabling the energetic autonomy of the complete CW system comprising the set of probes, pumps, and data acquisition and communication hardware.