1、Zero-Energy Removal of Ozone in Residences Elliott Gall Jeffrey A. Siegel, PhD Richard Corsi, PhD, PE Student Member ASHRAE Member ASHRAE ABSTRACT Ozone is present indoors largely as a result of transport from outdoors. Conventional strategies to remove ozone require energy and thus are not appropri
2、ate for zero-energy buildings. We explore the use of passive reactive materials (PRMs), indoor surfaces that remove ozone with no additional energy input and without producing byproducts, to reduce indoor ozone concentrations. This work presents the results of a Monte Carlo simulation to assess the
3、ozone removal effectiveness of active and passive methods of indoor ozone removal. We compare two different PRMs to stand-alone activated carbon filtration and HVAC filtration. Housing stock data for approximately 100 homes in Houston, TX are taken from the literature to calculate energy and materia
4、l requirements to achieve 50% and 80% indoor ozone removal effectiveness in these homes. Model results indicate that to achieve 50% ozone removal in half of the homes requires approximately 30 kWh and 5 kWh per home each day for stand-alone filtration and HVAC filtration, respectively. To achieve th
5、is same level of indoor ozone reduction with PRMs requires 75 m2 (807 ft2) for activated carbon cloth and 200 m2 (2153 ft2) of unpainted gypsum wallboard. These results indicate that PRM use represents a viable option for zero-energy control of indoor ozone. INTRODUCTION Indoor air quality (IAQ) is
6、of increasing concern due to the large number of pollutants present indoors, many with adverse impacts on human health and comfort. Mandates to improve building energy efficiency, such as the Department of Energys (DOE) goal to achieve net zero-energy in 50% of U.S. commercial buildings by 2050 (DOE
7、 2010) complicate strategies to improve indoor air quality. Energy efficiency goals have resulted in green building protocols that specify the reduction of building ventilation, responsible for as much as 25% of building energy demand (Liddament et al. 1995). These reductions in ventilation result i
8、n increased concentrations of pollutants of indoor origin, as well as increases in concentrations of indoor chemical reaction products (Weschler 2004). These reductions in ventilation may lead to adverse health effects, as Wargocki et al. (2000) found health, productivity and comfort benefits have b
9、een correlated with increased ventilation. However, removal of indoor pollutant results in similar benefits (Wargocki et al. 1999), and if cleaning can is achieved in a zero-energy manner, complement zero-energy building goals. Many health risks have been associated with indoor environments and indo
10、or ozone exposure has received significant attention in the last decade due to correlations of outdoor ozone levels with increases in daily mortality (Bell et al. 2006), asthma morbidity (McConnell et al. 2002), its ability to drive indoor gas-phase chemistry (Weschler 2000), and its reactivity with
11、 indoor surfaces (Wang and Morrison 2010). Indoor intake of ozone is substantial, accounting for 25-60% of the total dose for a typical American (Weschler 2006). Furthermore, the products of indoor ozone initiated chemistry, such as formaldehyde and secondary organic aerosols are health hazards. Red
12、ucing concentrations of indoor pollutants with health and comfort impacts, like ozone, while accomplishing critical energy efficiency goals, requires new approaches to indoor air cleaning. This aim is identified as a necessary milestone on the roadmap to net zero-energy buildings promulgated by the
13、National Institute of Standards and Technology (NIST). This LV-11-C050 2011 ASHRAE 4112011. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions, Volume 117, Part 1. For personal use only. Additional reproduction, distribu
14、tion, or transmission in either print or digital form is not permitted without ASHRAES prior written permission.roadmap highlights a mid-term need to develop “passive air-cleaning” technologies and a long-term need to consider “whole building IAQ” (NIST 2010). Passive reactive materials (PRMs), intr
15、oduced previously by Kunkel et al. (2010), present an approach to achieving both goals. Surface reactions play an important role in indoor chemistry, and are largely responsible for why indoor concentrations of ozone are lower than outdoor concentrations. PRMs are indoor surfaces that are optimized
16、to remove indoor pollutants. An ideal PRM reacts with harmful pollutants to generate no or only benign reaction by-products, and does so in a manner that requires no additional energy input beyond ordinary building operation. Kunkel et al. (2010) observed two promising PRMs, activated carbon cloth (
17、ACC) and gypsum wall-board (GWB), which were placed on walls in an experimental test house (Kunkel et al. 2010). To place the indoor air cleaning potential of these PRMs in context, PRMs are contrasted with active ozone removal methods by comparing air cleaning requirements of both active and passiv
18、e strategies using Monte Carlo analysis of approximately 100 homes in Houston, Texas. METHODOLOGY The effectiveness of three indoor ozone removal strategies in approximately 100 homes in Houston, TX, were determined in this study. Homes were initially part of the Relationship of Indoor, Outdoor and
19、Personal Air (RIOPA) investigation (Weisel et al. 2005). Three indoor ozone removal strategies were considered in this paper are: 1) active ozone removal by stand-alone activated carbon air filters (denoted in text by filter), 2) active ozone removal in HVAC systems with activated carbon filtration
20、(denoted in text by HVAC), and 3) passive ozone removal by PRMs. A Monte Carlo approach was applied to a mass balance analysis of the RIOPA Texas homes. This method results in distributions of energy requirements for HVAC and filter and surface area requirements for PRMS to achieve ozone removal eff
21、ectiveness values of 50% and 80%. This paper contrasts the two active indoor ozone removal methods with two PRMs, ACC and GWB. The mass balance utilized for these ozone removal strategies is shown in Equation 1: ( )( )PRMVAdPRMffHVACCADRfilterPRMHVACfilterBGVAdovRfVQRVQRRRRvCC=+=, (1) Effectiveness
22、for active and passive systems was calculated using Equation 2 (Miller-Leiden et al. 1996): WOWCC= 1 (2) Ozone removal effectiveness has a value of unity when the removal strategy is perfectly effective at removing indoor ozone and a value of zero when the removal strategy has no impact on indoor oz
23、one. In this paper, is set to values of 50% and 80% effectiveness, proposed elsewhere as minimum and recommended air purifier effectiveness values, respectively (Shaughnessy and Sextro 2006). By setting Rfilter, RHVAC, RPRM in the denominator of Equation 1 equal to zero, CWO in Equation 2 can be cal
24、culated. Required filter clean air delivery rate (QCADR) was calculated by setting RPRM and RHVAC in Equation 1 equal to zero, inserting Equation 1 for CW in Equation 2, and solving for QCADR. This process was repeated for RHVAC and RPRM and where HVAC runtime (f) and PRM area (A) were calculated, r
25、espectively. Solving Equation 1 requires assumptions of a home as a well-mixed contiguous volume as well as a time-averaged solution to address varying outdoor ozone concentrations. Energy implications associated with stand-alone filtration and HVAC filtration consider only direct energy inputs for
26、equipment operation. PRM placement in homes is assumed to add ozone removal capacity above background levels, that is, PRMs do not reduce ozone transport to existing surfaces. Simulation inputs are summarized in Table 1. 5000 iterations were conducted in the analysis, the point at which model output
27、 distributions did not deviate as determined by visual inspection of overlays. A distribution of air exchange rates in Houston RIOPA homes was calculated from Weisel et al. (2005) with descriptive parameters shown in Table 1. Background ozone removal was assumed as a weighted average of ozone remova
28、l values in a private residence with and without HVAC 412 ASHRAE Transactionsoperation (Sabersky et al. 1979). Homes were assumed to follow residential cooling HVAC runtime ratios reported by Stephens et al. (2010), implying that background indoor ozone removal was 2.9 hr-1 for 75% of the time and 5
29、.4 hr-1 for 25% of the time. A lognormal distribution of Houston RIOPA house volumes was calculated from Weisel et al. (2005). Deposition velocity to PRMs was calculated from a power law relationship of experimentally determined data at varying airspeeds from data presented by Kunkel et al. (2010).
30、Indoor airspeeds with and without HVAC operation, published by Matthews et al. (1989), were input to this power law relationship as a bounded uniform distribution. This allowed a randomized input to Equation 1 of deposition velocities to PRMs at realistic indoor airspeeds with and without HVAC opera
31、tion. Energy inputs for stand-alone filtration were calculated by multiplying CADR by power efficacy (filter) reported by Waring et al. (2008). This assumes that the CADRs for the hypothetical ozone removing stand-alone filters in this paper have equivalent CADRs as they do for particle removal. Thi
32、s assumption was made due to limited data on stand-alone filters for ozone, however, the high reactivity of ozone implies these CADRs are likely also achievable for ozone. Energy inputs for HVAC filtration were calculated by multiplying typical HVAC fan efficacies (HVAC) and flow rates per volume (Q
33、f/V ) reported by Stephens et al. (2010) and home volume. The daily energy associated with normal operation (0.25) was subtracted from this value. Ozone removal efficiencies associated with HVAC filtration (f) were assumed as 81%, based on an average efficiency reported by Gundel et al. (2002) for a
34、ctivated carbon filtration of ozone over the first two months of filter use. Ozone removal efficiencies for PRMs and stand-alone filtration are incorporated into deposition velocity values and stand-alone filtration CADR assumptions, respectively. Table 1. Monte Carlo simulation inputs Variable1 Val
35、ue2 Reference Air exchange rate GM = 0.5 hr-1, GSD = 2.13 Weisel et al. (2005) HVAC off BG ozone removal (vdA/V)BG, off 2.9 hr-1 HVAC on BG ozone removal (vdA/V)BG, on 5.4 hr-1 Sabersky et al. (1979) HVAC runtime f 0.25 Stephens et al. (2010) Volume V GM = 271 m3, GSD = 1.64 (GM = 9563 ft3, GSD = 58
36、) Weisel et al. (2005) ACC deposition velocity vd, ACCm hr-1 vd, ACC = 36.6x0.29x= m s-1 Kunkel et al. (2010) ACC deposition velocity vd, ACCft hr-1 vd, ACC = 84.8x0.29x= ft s-1 Kunkel et al. (2010) GWB deposition velocity vd, GWB m hr-1 vd. GWB = 19.5x0.41, x= m s-1 Kunkel et al. (2010) GWB deposit
37、ion velocity vd, GWBft hr-1 vd. GWB = 39.1x0.41x= ft s-1 Kunkel et al. (2010) HVAC off indoor airspeed xHVAC off 0.015 - 0.58 m s-1 (0.05 - 0.19 ft s-1) Matthews et al. (1989) HVAC on indoor airspeed xHVAC on 0.057 - 0.155 m s-1 (0.19 - 0.51 ft s-1) Matthews et al. (1989) Stand-alone filtration effi
38、cacy filter 1.09 W m-3 hr-1 (0.11 Btu ft-3) Waring et al. (2008) HVAC fan efficacy HVAC 0.29 W m-3 hr-1 (0.029 Btu ft-3) Stephens et al. (2010) Fan flowrate per house volume Qf/V 4.64 hr-1 Stephens et al. (2010) HVAC filter efficiency f 0.81 Gundel et al. (2002) 1: HVAC = heating, ventilation and ai
39、r conditioning, BG = background, ACC = activated carbon cloth, GWB = gypsum wall board 2: GM = Geometric mean, GSD = Geometric standard deviation 2011 ASHRAE 413RESULTS AND DISCUSSION Cumulative distribution functions (CDFs) describe the likelihood that a random variable will be found at less than a
40、 specified value. CDFs allow many variables to be incorporated into a statement describing the probability of Houston RIOPA homes achieving a given ozone removal effectiveness. CDFs of effectiveness for stand-alone filtration, HVAC filtration, and PRMs are shown for 50% and 80% ozone removal effecti
41、veness in Figure 1. In active systems, model results indicate that achieving 50% ozone removal in half of the Houston subset of RIOPA homes requires approximately 30 kWh and 5 kWh each day for stand-alone filtration and HVAC filtration, respectively. Achieving 80% ozone removal in 75% of these homes
42、 requires increases in daily energy use of 195 kWh and 55 kWh per day for stand-alone filtration and HVAC filtration, respectively. In passive systems, the model illustrates that achieving 50% ozone removal in half of homes would require approximately 200 m2 (2153 ft2) of GWB and approximately 75 m2
43、 (807 ft2) of ACC. Increasing ozone removal effectiveness to 80% for 75% of the homes increases PRM area required to 500 m2 (5382 ft2) and 1390 m2 (14962 ft2) for ACC and GWB, respectively. This model assumes that stand-alone air filters can be added to an environment until QCADR in the environment
44、achieves a specified ozone removal effectiveness. In practice, this represents a serious limitation to the use of stand-alone filters for indoor ozone control. Achieving 50% removal in 50% of homes would require approximately six stand-alone filters operating simultaneously on high-speed. The intrus
45、iveness and noise of these units would prevent this option from being considered by many homeowners. Doubling the QCADR per unit, in line with the higher efficiency stand-alone filter described by Waring et al. (2008), would halve the number of units necessary, however likely at additional cost per
46、unit. Furthermore, since an identical flow is required, noise concerns may not be significantly alleviated. Achieving higher removal effectiveness in more homes would require corresponding increases in the number of stand-alone filtration units. Figure 1. Ozone removal effectiveness for stand-alone
47、filtration, heating, ventilation and air conditioning (HVAC) filtration, activated carbon (AC) PRMs, and gypsum wallboard (GWB) PRMs. (A) reports cumulative frequencies associated with achieving 50% ozone removal effectiveness. (B) reports cumulative frequencies associated with achieving 80% ozone r
48、emoval effectiveness. Black lines (active removal) correspond with the left (primary) axis while gray lines (passive removal) correspond with the right (secondary) axis. HVAC systems move large quantities of air, and theoretically present a viable option for substantial indoor ozone control, however
49、 important hurdles may complicate their performance in this regard. Energy considerations appear more favorable than stand-alone filtration. However, HVAC energy demand calculations assume HVAC run-time fractions can 414 ASHRAE Transactionsincrease unbounded, beyond a theoretical limit of 1 (or 100% fan run-time), until Qf is sufficient to achieve a set ozone removal effectiveness. HVAC run-time fractions greater than 1 imply that a large
