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WSU Indoor Air Quality (IAQ) Project

An Examination of Indoor Air Quality in Residential Homes Using Fine-Scale Temporal Measurements and Future Climate Model Simulations

Python code archive for the doctoral dissertation research conducted at Washington State University's Laboratory for Atmospheric Research (LAR). The framework uses NIST CONTAM multizone simulations driven by downscaled climate projections and atmospheric chemistry model outputs to evaluate how future climate conditions affect indoor air quality in U.S. residential buildings.

Overview

  • Multizone IAQ simulations using NIST CONTAM across 19 U.S. cities and five residential building archetypes
  • Climate forcing from CMIP5 models under RCP 4.5 and RCP 8.5 scenarios, downscaled via MACA
  • Outdoor contaminant boundary conditions (PM2.5, O3, HCHO) from WRF-CMAQ
  • Present-day baseline meteorology from NOAA Integrated Surface Hourly (ISH) observations
  • Simulation outputs written to netCDF for post-processing and analysis

Research Scope

Cities Studied

City State Latitude Longitude Altitude (m)
Atlanta GA 33.75 -84.39 273
Birmingham AL 33.52 -86.80 140
Boston MA 42.36 -71.06 43
Buffalo NY 42.89 -78.88 183
Chicago IL 41.88 -87.63 181
Cincinnati OH 39.10 -84.51 147
Corpus Christi TX 27.80 -97.40 2
Dallas TX 32.78 -96.80 131
Denver CO 39.74 -104.99 1647
Los Angeles CA 34.05 -118.24 93
Miami FL 25.76 -80.19 7
Minneapolis MN 44.98 -93.27 264
Nashville TN 36.16 -86.78 182
New York NY 40.71 -74.01 10
Phoenix AZ 33.45 -112.07 331
Seattle WA 47.61 -122.33 79
St. Louis MO 38.63 -90.20 165
Washington DC 38.91 -77.04 63
Worcester MA 42.26 -71.80 146

Residential Building Archetypes

Building archetypes are drawn from the NIST Collection of U.S. Housing Stock (Persily et al., 2006).

Model ID Description
AH-1 Apartment
DH-1 Detached house, type 1
DH-3 Detached house, type 3
House-5 Single-family house
MH-1 Mobile home

Climate Scenarios

Scenario Description
Historical baseline NOAA ISH observed meteorology
RCP 4.5 Intermediate greenhouse gas stabilization pathway
RCP 8.5 High-end emissions pathway

Simulated Contaminants

Contaminant Source Reported Units
PM2.5 WRF-CMAQ µg/m³
Ozone (O3) WRF-CMAQ ppb
Formaldehyde (HCHO) WRF-CMAQ ppb

Repository Structure

py-contam-graduateproject/
├── documentation/
│   ├── contamOnAeolus.md              # Notes for running CONTAM on the WSU aeolus HPC cluster
│   ├── SIM_file_format.txt            # CONTAM binary .sim file format reference
│   ├── isd-history-IAQ.csv            # NOAA ISH station list for project cities
│   ├── isd-history.csv                # Full NOAA ISH station inventory
│   ├── ish-format-document.pdf        # NOAA ISH data format specification
│   └── ish-qc.pdf                     # NOAA ISH quality control documentation
│
└── python/
    ├── contam_input.py                # Reads meteorological and contaminant data;
    │                                  # writes CONTAM weather and species input files
    ├── contam_output.py               # Parses binary CONTAM .sim output files;
    │                                  # extracts airflow, node pressures, and concentrations
    ├── runContam.py                   # Batch simulation driver across cities,
    │                                  # building types, and climate scenarios
    ├── iaq_cities.csv                 # City coordinates, altitude, and time zone lookup
    ├── vrs.csv                        # Ventilation rate schedules
    │
    ├── aqs/                           # EPA Air Quality System data retrieval tools
    ├── cmaq/                          # WRF-CMAQ contaminant file generation
    ├── CMIP5/                         # CMIP5 model ranking and selection
    ├── graphics/                      # Visualization scripts
    ├── houses/                        # Building-specific CONTAM file generation
    │                                  # and simulation output processing
    ├── maca/                          # MACA climate data processing and
    │                                  # CONTAM weather file generation
    └── utilities/                     # General-purpose utilities: NOAA ISH ingestion,
                                       # WRF data reading, pressure correction

Data Sources

Source Description Role
MACA Multivariate Adaptive Constructed Analogs Downscaled temperature, humidity, and wind speed for RCP 4.5 and 8.5
WRF-CMAQ Weather Research and Forecasting + Community Multiscale Air Quality Outdoor PM2.5, O3, and HCHO boundary conditions
NOAA ISH Integrated Surface Hourly Observed meteorological data for historical baseline runs
CMIP5 Coupled Model Intercomparison Project Phase 5 GCM selection for MACA downscaling

Dependencies

The code was developed in Python and executed on the Washington State University aeolus HPC cluster. Key packages:

  • numpy, scipy — numerical computation
  • netCDF4 — reading and writing simulation output files
  • pandas — tabular data handling
  • matplotlib — visualization

No environment file is included in this repository. See documentation/contamOnAeolus.md for notes on the HPC setup used during the project.

Authors

Framework developed by: Von P. Walden, Washington State University, Laboratory for Atmospheric Research (v.walden@wsu.edu)

Analyses conducted by: Nathan M. Lima, Washington State University (Ph.D., Engineering Science, 2022)

Questions or comments: Open an issue or reach out via GitHub.

Acknowledgments

This work was funded by the U.S. Environmental Protection Agency (EPA) Science to Achieve Results (STAR) grant program. Contributions from Brian K. Lamb, Yunha Huangfu, Patrick T. O'Keeffe, William M. Kirk, Stephanie N. Pressley, B. Tommy Jobson, and EPA collaborators Christopher G. Nolte and Tanya L. Spero are gratefully acknowledged.

Simulations were run on the aeolus high-performance computing cluster at Washington State University.

Citation

Dissertation

Lima, N. M. (2022). An Examination of Indoor Air Quality in Residential Homes Using Fine-Scale Temporal Measurements and Future Climate Model Simulations [Dissertation, Washington State University]. ProQuest. https://www.proquest.com/openview/975cbdf830bc026b3190b2a201cd17c0/

Conference Papers

Lima, N. M., Huangfu, Y., Walden, V. P., Kirk, W. M., Lamb, B. K., Jobson, B. T., Pressley, S. N., O'Keeffe, P. T., Musser, A., Nolte, C. G., Spero, T. L., & Toombs, K. (2018, July 23). Simulations of indoor air quality based on future climate conditions. The 15th Conference of the International Society of Indoor Air Quality.

Lamb, B. K., Huangfu, Y., Lima, N. M., O'Keeffe, P. T., Cook, D. J., Kirk, W. M., Lin, B., Pressley, S. N., Walden, V. P., & Jobson, B. T. (2017, October 5). Integrated measurements and model of indoor air quality. Northwest Regional Modeling Consortium, Richland, WA.

References

  • CONTAM — NIST Multizone Modeling Software
  • MACA — Multivariate Adaptive Constructed Analogs
  • WRF-CMAQ — Community Multiscale Air Quality Modeling System
  • NOAA ISH — NOAA Integrated Surface Database
  • CMIP5 — Coupled Model Intercomparison Project Phase 5
  • Persily, A. K., Musser, A., & Leber, D. (2006). A collection of homes to represent the U.S. housing stock (NIST IR 7330). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.IR.7330

About

Python workflow for NIST CONTAM indoor air quality simulations across 19 U.S. cities and five residential building types. Integrates WRF-CMAQ, MACA climate projections, and NOAA weather data to assess climate change impacts on indoor exposures. Ph.D. in Engineering Science, WSU, 2022 (adviser: Von P. Walden).

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