Planning

Project Objectives

Theme A
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Monitoring Pool Status

Task A-1: Measurement of Parameters and DBPs in water and air

  • Review literature to identify key parameters of interest and corresponding health guidelines and measurement methods
  • Develop sampling schedule and conduction of sampling campaigns in winter and summer at each of the five ISPs
  • Install real-time sensors in ISPs to monitor key water quality indicators

Task A-2: Development of Predictive Models

  • Develop and validate Computational Fluid Dynamics (CFD) models of pool air and water to track transfer of DBPs
  • Integrate indoor air characteristics to develop relationships between DBPS in air and water, water temperature, air temperature, humidity and air change rate, and number of occupants
  • Validate data from real time sensors with manually measured data
Theme B
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Monitoring Building Energy Use and Occupant Experience

Task B-1: Building energy and air quality performance assessment

  • Development of Building Energy Models (BEMs) for each of the considered ISPs utilizing architectural and operational data
  • Use existing operational guidelines along with annual energy bills and real-time energy use data for calibration and validation of models

Task B-2: Occupant Surveys

  • Conduct surveys of users to gather data on perceptions of thermal comfort, odor, humidity level, frequency and duration of pool use, etc.
  • Couple results with Indoor Environmental Quality (IEQ) data to analyze demographic responses and relationships to provide information on acceptable indoor conditions for Task C-1
Theme C
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Developing Optimal Operation Strategies using WHEN

Task C-1: Human health risk, environmental, and economic assessments

  • Use information generated in Themes A and B to evaluate human health risks from DBPs
  • Perform lifecycle analysis of the ISPs to assess the environmental and economic performance/impacts of ISPs 

Task C-2  Dynamic simulation testbed of facility energy system

  • Develop dynamic simulation of the ISP facility energy systems to provide information about indoor air and pool water conditions
  • Use real-time data recorded from CoK2 location to calibrate the model to test proposed operational strategies as an ‘actual’ system

Task C-3: Development of Optimal Operational Strategies and Dashboard

  • Develop and analyze a comprehensive WHEN-based performance model using energy use, thermal comfort, and health risk data from results of Task C-1
  • Use optimization results to assess the feasibility of net-zero energy and emissions status
  • Design an “ePool” dashboard for the monitoring of real time parameters of ISP facilities and projected emissions using the sensors installed in the CoK2 facility as a demonstration

Key Deliverables and Benefits

  1. Healthy and Sustainable swimming pool demonstration site for BC and Canada
  2. Real-time monitoring system for water quality, air quality, and energy use in swimming pools
  3. Health risk map of swimming pools with mitigation measures
  4. Optimal pool operational strategies and best management practices to reduce human health risks, energy use, and GHG emissions
  5. ePool dashboard

Mockup

Sampling/Equipment

Sampling and equipment related activities will include the following:

  1. Acquiring automated, real-time monitoring systems capable of tracking key water quality indicators such as pH, temperature, chlorine levels, and DBP concentrations.
  2. Utilization of manually-operated devices for periodically validating the automated sensor data. These devices would include portable probes and spectrophotometric kits for specific measurements.
  3. Ensuring the necessary protective and safety gear for all personnel involved in the project. This includes chemical resistant gloves, safety goggles, and lab coats.

Software/Methodology

Our project methodology and software usage will comprise of:

  1. Using Computational Fluid Dynamics (CFD) software like ANSYS Fluent or COMSOL Multiphysics for developing the predictive models of the aquatic center environment.
  2. Adopting statistical software such as R or Python libraries for the validation of the sensor data and correlational analysis of DBPs with other variables.
  3. Implementing project management software like MS Project or JIRA to ensure efficient coordination, tracking of project milestones and tasks.