Modeling impacts of dynamic ventilation strategies on indoor air quality of offices in six US cities

Abstract A potential source of energy savings in buildings is demand controlled ventilation (DCV), or dynamic modulation of the ventilation rate based on current occupancy. The impact of DCV on indoor air quality (IAQ) has not been investigated over a large range of indoor air processes or under the revised ventilation rate procedure (VRP) introduced in ASHRAE Standard 62.1-2004, which reduced per-occupant rates and added a constant per-area rate. A transient, multi-contaminant model of an area-normalized US office was created, and best estimates for distributions of model inputs across the US office sector were developed and used in a six city Monte Carlo simulation of dynamic ventilation strategies, including DCV and morning flushes. DCV implementation had a very minor effect on concentrations of ozone, particles, and carbon dioxide. The greatest effect was on daytime mean and peak concentration of total volatile organic compounds (TVOC). TVOC daytime means increased by 7–10% and peaks increased by 10–14%, depending on city. Adding a medium intensity morning flush to DCV almost completely mitigated the increase in mean concentration and reduced the peak concentration below the fixed ventilation baseline in most cases. Differences among offices due to input variations were far greater than changes observed from implementing DCV, and a sensitivity analysis indicated that the TVOC emission rate was more influential than the ventilation strategy. The distribution-based, sector-wide Monte Carlo method developed here should also be useful for assessing other ventilation strategies and input parameter impacts and informing the development of IAQ guidelines.

[1]  Andrew K. Persily,et al.  Analysis of Ventilation Data from the U.S. Environmental Protection Agency Building Assessment Survey and Evaluation (BASE) Study , 2004 .

[2]  Tunga Salthammer,et al.  Critical evaluation of approaches in setting indoor air quality guidelines and reference values. , 2011, Chemosphere.

[3]  Thomas E McKone,et al.  Indoor particulate matter of outdoor origin: importance of size-dependent removal mechanisms. , 2002, Environmental science & technology.

[4]  Andrew K. Persily,et al.  State-ofthe-Art Review of CO 2 Demand Controlled Ventilation Technology and Application , 2003 .

[5]  S. T. Taylor,et al.  CO~2-Based DCV Using 62.1-2004 , 2006 .

[6]  Andrew K. Persily,et al.  Simulations of indoor air quality and ventilation impacts of demand controlled ventilation in commercial and institutional buildings , 2003 .

[7]  M. L. Laucks,et al.  Aerosol Technology Properties, Behavior, and Measurement of Airborne Particles , 2000 .

[8]  Tao Lu,et al.  A novel and dynamic demand-controlled ventilation strategy for CO2 control and energy saving in buildings , 2011 .

[9]  William W. Nazaroff,et al.  Effectiveness of urban shelter-in-place. III: Commercial districts , 2008 .

[10]  Olivier Ramalho,et al.  Reactions between ozone and building products: Impact on primary and secondary emissions , 2007 .

[11]  Charles J Weschler,et al.  Reactions of ozone with human skin lipids: Sources of carbonyls, dicarbonyls, and hydroxycarbonyls in indoor air , 2010, Proceedings of the National Academy of Sciences.

[12]  Peter V. Hobbs,et al.  Aerosol-Cloud-Climate Interactions , 1993 .

[13]  C J Weschler,et al.  Ozone in indoor environments: concentration and chemistry. , 2000, Indoor air.

[14]  Wanyu Rengie Chan Assessing the effectiveness of shelter -in -place as an emergency response to large-scale outdoor chemical releases , 2006 .

[15]  David E. Burmaster,et al.  Residential Air Exchange Rates in the United States: Empirical and Estimated Parametric Distributions by Season and Climatic Region , 1995 .

[16]  M S Waring,et al.  Particle loading rates for HVAC filters, heat exchangers, and ducts. , 2008, Indoor air.

[17]  Bing Liu,et al.  U.S. Department of Energy Commercial Reference Building Models of the National Building Stock , 2011 .

[18]  De-Ling Liu,et al.  Modeling pollutant penetration across building envelopes , 2001 .

[19]  G. Morrison,et al.  Setting Maximum Emission Rates from Ozone Emitting Consumer Appliances in the United States and Canada , 2010 .

[20]  J. E. Janssen,et al.  Ventilation for acceptable indoor air quality , 1989 .

[21]  C. Chao,et al.  Development of a dual-mode demand control ventilation strategy for indoor air quality control and energy saving , 2004 .

[22]  Standard 62 . 1-2004 System Operation : Dynamic Reset Options , .

[23]  Ruprecht Jaenicke,et al.  Chapter 1 Tropospheric Aerosols , 1993 .

[24]  D. Underwood Open DDC Systems: Obstacles and How to Avoid Them , 2006 .

[25]  Terry Brennan,et al.  Mitigating the Impacts of Uncontrolled Air Flow on Indoor Environmental Quality and Energy Demand in Non-Residential Buildings , 2006 .

[26]  Yin Hang,et al.  CO2-based demand controlled ventilation under new ASHRAE Standard 62.1-2010: a case study for a gymnasium of an elementary school at West Lafayette, Indiana , 2011 .

[27]  W. A. Beckman,et al.  Demand-Controlled Ventilation in a Multi-Zone Office Building , 1994 .

[28]  G. Morrison,et al.  Ozone-initiated secondary emission rates of aldehydes from indoor surfaces in four homes. , 2006, Environmental science & technology.

[29]  Nabil Nassif CO2-BASED DEMAND-CONTROLLED VENTILATION CONTROL STRATEGIES FOR MULTI-ZONE HVAC SYSTEMS , 2011 .

[30]  Shengwei Wang,et al.  In-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation strategy in a multi-zone office building , 2011 .