Contribution of Visitors to the Indoor PM in the National Library in Prague, Czech Republic

Ludmila Mašková1*, Jiří Smolík1, Tereza Travnickova1, Jaromir Havlica1,2, Lucie Ondráčková1, Jakub Ondráček1

1 Institute of Chemical Process Fundamentals of the CAS, Rozvojova 135, 165 02, Prague 6, Czech Republic 2 University of Jan Evangelista Purkinje, Ceske mladeze 8, 400 96 Usti nad Labem, Czech Republic

ABSTRACT

Temporal and spatial variation of size resolved particulate matter (PM) was measured in the Baroque Library Hall of the National Library in Prague during four intensive campaigns by an Aerodynamic Particle Sizer and three DustTrak instruments. The analysis showed, the indoor air can be considered as well mixed and therefore the simple mass balance model was used to estimate basic parameters (ventilation rate, deposition rates and penetration factors). The results revealed that the movement of visitors during visiting hours is the main source of indoor coarse PM. Mass emission rates, estimated from the comparison of measured and modelled data indicates the visitors should contribute about 50 g of coarse particles yearly, which is about 35% of the total load of indoor PM.

Keywords: Indoor source; Deposition; Penetration; Library.

INTRODUCTION measurements covered monitoring of indoor and outdoor airborne PM, gaseous pollutants and climatic parameters Indoor air quality in libraries and archives is a key point and determination of chemical composition of PM. of preventive conservation and received recently a growing Moreover, spatial variation of indoor PM was also monitored. scientific interest (Llyod et al., 2007; Thickett et al., 2007; The purpose of these measurements was to obtain detailed Andělová et al., 2010; Fenech et al., 2010; López-Aparicio information on indoor air quality in the library before et al., 2011; Mašková et al., 2015; Andretta, et al., 2016; revitalization of Clementinum. The revitalization, planned Vichi et al., 2016). Particulate matter (PM) pose different for 2010–2018 includes also a construction of new air- risks for stored books and manuscripts such as soiling conditioned depositories located on the same floor as BLH. (Baer and Banks, 1994, Brimblecombe and Grossi, 2004), Results of gaseous pollutants monitoring and PM abrasion (Nazaroff and Cass, 1991), chemical degradation composition revealed, that infiltration of ammonium nitrate (Bartl et al., 2016), and moistening (Hatchfield, 2005). from the outdoor air and shift to the equilibrium to the gas Previous studies showed that the estimation of the PM phase were the reason for the high concentrations of ammonia behavior became a crucial issue for the air quality evaluation measured inside BLH (Andělová et al., 2010; López-Aparicio (Liu and Nazaroff, 2001; Li and Chen, 2003; Hussein et et al., 2011). Temporal variation of size resolved indoor al., 2006; Chen and Zhao, 2011; Lai et al., 2012; Hussein, and outdoor PM showed that main source of indoor coarse 2014; Mølgaard et al., 2014; Střižík et al., 2014; Hussein PM are visitors and fine PM infiltration from the outdoor et al., 2015a, b). environment (Chatoutsidou et al., 2015). Similar effect has In the period 2009–2010 we performed detailed indoor been already described in several studies related to indoor air quality measurements in an old Baroque Library Hall air quality in museums (e.g., Camuffo et al., 1999; Worobiec (BLH), located in Clementinum historical complex in Prague. et al., 2008; Wang et al., 2015; Xiu et al., 2015). Further, Founded in 1232, the Clementinum is one of the largest the time behavior of PM10 concentrations measured in various building complexes in Europe. Since 1930 it is currently in parts of the hall by 3 DustTrak instrument showed that, for use as the National Library of the Czech Republic. The the purpose of modelling, the indoor environment can be considered as well mixed. The assumption of ideal mixing was verified by multi-compartment modelling (Takkunen et al., 2011). The time and size resolved PM number * Corresponding author. concentration data were also used to estimate particle Tel.: +420 220 390 203; Fax: +420 220 920 661 penetration factor P and deposition rate k. The estimation E-mail address: [email protected] was based on comparison of measured and modelled data,

1714 Mašková et al., Aerosol and Air Quality Research, 16: 1713–1721, 2016 however no unique solution was found (Chatoutsidou et al., a.m. and finish differently by the season. A blueprint of the 2015). This is probably due to a nearly linear inverse BLH is shown in Fig. 1. relationship between particle penetration and deposition that occur simultaneously (Bennet and Koutrakis, 2006). There Data Collection are several studies that tried to determine P and k separately A preliminary test of indoor coarse PM behavior was by increasing the indoor PM concentrations significantly. carried out in spring 2008, followed by three intensive This was achieved either by opening of windows and doors campaigns in spring, summer and winter 2009. In the first and measurement of subsequent decay of particles indoors test temporal variation of indoor coarse PM was monitored after windows and doors were closed (Vette et al., 2001; using an Aerodynamic Particle Sizer (APS, model 3321, Chao et al., 2003; Smolík et al., 2005) or by resuspension TSI, USA), located at distance about 5 m from the route activities indoors followed again by period of particle for visitors (see Fig. 1), that measured particle number decay (Thatcher and Layton, 1995; Thatcher et al., 2003). concentrations for 52 specific size bins in effective size In preliminary tests, performed in BLH in spring 2008 range 0.5–20 µm. In addition temperature, relative humidity we measured concentrations of coarse PM and CO2 close and CO2 concentration were measured by an Indoor Air to the visitor’s route. One week measurements showed Quality Monitor PS32 (Sensotron, Poland). In 2009 the strong influence of visitors who periodically increased intensive campaigns measurements were performed using concentrations of both pollutants at the beginning and the APS located at distance about 15 m from the route for during visiting hours followed by decay after. Further two visitors (see Fig. 1). The instrument sampled from both inside unidentified activities occurred indoors during these tests and outside BLH using its own sampling train provided with that increased PM concentrations significantly. However, an electrically actuated three-way ball valve connected to those data have not been analysed since both episodes have common programmable controller that used an SMPS voltage been considered as untypical for standard activities in BLH sent by Condensation Particle Counter (CPC, model 3775, and only indoor concentrations were measured. The present TSI, USA) as a signal for switching. The APS was operated study examined if those data would help to determine P with 5 L min–1 flow rate and used 3 min scan, followed by and k values separately. 2 minutes delay necessary to separate samples and flush sampling train after valve switching. Eventually two five EXPRIMENTAL AND METHODS minute sampling cycles for indoor sampling followed by two five-minute cycles for outdoor sampling were used. Data Sampling Site were collected using Aerosol Instrument Manager software Sampling site has already been described in previous (AIM v.8.0, TSI, USA), where particle losses inside sampling studies (Andělová et al., 2010; López-Aparicio et al., 2011; trains were incorporated. Chatoutsidou et al., 2015) and so only details related to this In addition spatial distribution of indoor PM was measured study are mentioned. PM concentrations were measured in an with three Dust Trak instruments (DT, model 8520, TSI, old BLH of the National Library (Clementinum historical USA) during summer and winter 2009. One DT instrument complex) located in the Old Town of Prague in the city was located just at the visitor's route at height about 0.3 m centre. The interior of the BLH remained intact since the above floor (DT Visitors), two others were located at the 18th century when it was opened. It houses over 20,000 sampling point at the height about 1 m (DT Centre) and 7 m volumes of mostly foreign theological literature dating (DT Gallery) above the floor (see Fig. 1). DT monitored from the 16th century until recent times stored in original PM10 mass concentrations by detection of scattered light wooden shelves. The hall is decorated with ceiling frescoes and measured particles from 0.1 to 10 µm based on optical and holds also a collection of geographical and astronomical diameter with one minute interval. globes. The BLH has natural ventilation through small openings in the building, windows, and doors. All windows Indoor Mass Balance Model with double glass and covered by curtains are closed while The indoor particle concentration for a well-mixed air the doors are open only for visiting purposes. Approximate volume can be described using a zero-dimensional dynamic indoor geometrics of the BLH are presented in Table 1. mass balance model for a given size of particles I (Nazaroff, There are 4 entrances to the BLH, 2 at the north side and 2004; Hussein and Kulamala, 2008): 2 at the south side. At the north side the entrances lead from hallway, which serves as a storage room and as an in d()CSiit out in entrance for librarians and restorers. The south side doors Pai CkCiii() t ( a ) () t , i 1 ... N , lead to the lobby of the BLH and serve as an entrance and dtV exit for visitors. Visitors enter the Hall in groups of max. (1) 25 people with a guide, tours run only along the south side in of the Hall. Sightseeing tours took place every day from 10 where t is the time [h], Ci (t) is the indoor particle

Table 1. Approximate indoor geometrics of the BLH. Upward surface (m2) Downward surface (m2) Vertical surface (m2) Room volume (m3) 900 900 1700 3500

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Fig. 1. Blueprint of Baroque Library Hall.

–3 concentration [# m ], Pi is the penetration factor penetration from outdoors can be neglected we could reduce –1 (dimensionless), a is the ventilation rate [h ], ki is the the mass balance Eq. (1) into (Hussein et al., 2009a, b): –1 deposition rate [h ], Si is the emission rate of particles –1 3 [# h ], V is volume of the space under study [m ] and N is a dCtin in i   in where t is the time [h], C (t) is the indoor particle ()akCt  ii. (2) i dt concentration [# m–3], C out(t) is the outdoor particle number i of particles size fractions. The Eq. (1) assumes that the For period without indoor sources, without deposition concentration of indoor particles is a result of particle (k = 0) and with ideal penetration factor P = 1 similar mass penetration from outdoors, deposition on indoor surfaces, i balance equation can be written for carbon dioxide: exfiltration from indoors to outdoors and emissions from indoor sources and ignores coagulation and phase change d()Ctin processes. CO2 in out aC(()())CO22 t  C CO t (3) In the case indoor concentrations are increased significantly dt so that decay by deposition and exfiltration dominates and in out simultaneously emissions from indoor sources and particle where CtCO2 () and CtCO2 () are indoor and outdoor

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concentrations of CO2 in dependence on time, respectively. Temporal variability of coarse PM and CO2 measured in Eq. (1) can be solved by using discreet time steps: preliminary tests performed in 2008 is shown in Fig. 3. As can be seen both PM and CO2 concentrations periodically

out Si increase at the beginning of visiting tours and reach aPCii t j katt  maximum value at the end of visits, followed by decay. From Ctin V 1 eijj1 mod,ij   (4) the Fig. 3 it can be also seen two episodes with resuspension kai  activities that raised the indoor PM concentrations in kattijj 1 Ctij1 e , substantially. The peak concentration achieved after the first event was about an order of magnitude higher than peak in concentrations reached after the visits and about 4 times where Ctmod,i  is calculated indoor concentration. Eq. (2) has analytical solution in the following form: higher than average outdoor concentrations measured during three campaigns in 2009. ak()ln(()/) tt1 CtCin in , (5) 0,0ii Estimation of Ventilation Rate Since value of Cout has not been measured, it was where t is the initial time and Cin is the indoor CO2 0 i,0 gradually chosen from the interval 〈400, 600〉 ppm and concentrations measured at t0. subsequently, the coefficient of ventilation rate was obtained Further, assuming the outdoor concentration of carbon out by the least square method applied on the Eq. (6). The final out dioxide CCO2 is constant, integration of Eq. (3) yields: values of parameters (a, CCO2 ) were chosen on the base of minimal cumulative standard deviation of the used 1 in out in out –1 att()ln((())/(0222,02 CCO tC  CO C CO  C CO )), (6) interpolation. The average value a = 0.13 h was stable with the relative standard deviation (RSD) approximately in where CCO2,0 is indoor concentration of carbon dioxide 14%. The same average value was found in spring campaign measured at time t0. in 2009 (Chatoutsidou et al., 2015).

RESULTS AND DISCUSSION Estimation of Deposition Rate In the next step deposition rates ki were estimated using For analysis of coarse particle behavior we use data from data for exponential decay observed on 20 May 2008, when in preliminary test performed in 2008 and measurements of indoor concentrations Ci were significantly elevated. For spatial variability of indoor PM10 and temporal variability this purpose data of the upper part of decay curve were of indoor/outdoor coarse PM measured in 2009 (see Fig. 1). fitted for different size fractions using the least square method Results of spatial variability of PM10, measured by three by Eq. (5). However, there were very low concentrations DT are shown in Fig. 2. It should be mentioned that one for particles larger than about 2.5 µm resulting in insufficient instrument was located just in the area of visiting tours and counts to provide adequate count statistic and therefore thus should monitor predominantly PM generated by visitors. these data were excluded. The values of ki as a function of Two others were located at a distance approximately 15 m particle size found from the fit are compared with results from the visitors. As can be seen temporal variability of for four sizes fractions found from the best fit between the PM10 measured by all instruments exhibits the same trend measured indoor concentrations and the obtained modelled indicating that for purpose of modelling the indoor air can indoor concentrations (Chatoutsidou et al., 2015) in Fig. 4. be considered as well-mixed. This was confirmed also by Shown are also deposition rates for fine particles estimated the multi-compartment modelling (Takkunen et al., 2011). from SMPS measurements performed in spring 2009. As

Fig. 2. Time series of PM10 concentrations measured by 3 DustTrak instruments.

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Fig. 3. Temporal variation of indoor coarse PM and CO2 concentrations measured in spring 2008. can be seen both methods give practically the same results parabolic type of expression suggested by Fuchs (1964) for in the size range where both measurements overlap. Note penetration through a crack resulting from gravitational also that measurements with significantly elevated indoor settling. The penetration factors are compared with results concentrations were performed in spring 2008 while of analysis based on the best fit method (Chatoutsidou et measurements evaluated by best fit method were performed al., 2015) in Fig. 5, where results for fine particles based in spring 2009. It indicates quite stable conditions in BLH. on SMPS measurements are also shown. As can be seen For particle sizes larger than about 1 µm the deposition there is continuity with results for fine particles but large rate ki relates to settling velocity VS (Lai and Nazaroff, difference for coarse particles. This can be caused again by 2000): low concentrations of larger particles during night and also by broad size bin (3–20 µm) considered for particles > 3 µm in previous analysis. Comparison with data on penetration Au kVis , (7) factor published by other authors has been presented in the V previous paper (Chatoutsidou et al., 2015). If we compare results of both analyses, the data from elevated indoor where Au is the area of all upward-facing horizontal concentration resemble results obtained from experiments surfaces. This should differ from floor area since there are in laboratories, while data from the best fit resemble results shelves with books on all walls of ground-floor and gallery obtained from experiments in real buildings (Chen and and furniture including collection of geographical and Zhao, 2011). astronomical globes but should be constant for all coarse particles. Thus to estimated it we calculated parameter Estimation of Visitors Influence Au/V using experimentally determined deposition rates and In order to estimate impact of visitors inside the library gravitational settling velocity assuming that all particles ventilation rate a, deposition rates ki and penetration factors –3 are spheres with density of 2 g cm . The results showed Pi determined in the previous part were used to model that the parameter Au/V is constant with the average value particulate emissions resulting from the movement of visitors –1 0.42 m and the RSD is approximately 3%. This confirms during visiting hours. Since ki was determined only for size that settling was the primary deposition mechanism for range 1–2.5 µm it was extrapolated to larger sizes using coarse particles. Deposition rates, modelled with this Eq. (7). For this purpose the full set of data, including visiting parameter using three-layer model (Hussein et al., 2012), hours was used and deviation between modelled values are shown in Fig. 4. in in Ctmod,i  calculated by Eq. (4) and measured values Cti  was minimized for Si = 0 out of visiting hours and Si = Estimation of Penetration Factor const in visiting hours. The results showed that visitors emit 6 –1 Now that we know both a and ki values for all measured on average 5 × 10 # min in the size interval 0.7–10 µm. particle sizes, reduced indoor mass balance model Eq. (2) was The estimated particle number emission rates were converted used with data from night-time non-source periods to obtain to mass emission rates assuming that all particles are spherical the size dependence of the penetration factor. Optimizing with density 2 g cm–3. The average emission rates calculated in modelled values Ctmod,i  calculated by Eq. (4) for Si/V = 0 for four size intervals PM0.7–10 as the sum of mass emission in with measured values Cti  for P  0,1 we obtained the rates for differentiated size bins are given in Table 2. dependence of the penetration factor on the particle size, As can be seen the most of the particle mass generated shown in Fig. 5. As can be seen results for particles larger during visiting hours was larger than 1 µm in diameter. than about 2 µm exhibited larger scatter probably due to This agree well with observation of Thatcher and Layton very low concentrations of these particles during night. (1995), Abt et al. (2000) and Hussein et al. (2015a) who Thus for the next analysis the data were extrapolated using found that movement in the indoor environment significantly

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Fig. 4. Deposition rate as a function of particle size.

Fig. 5. Penetration factor versus particle size.

Table 2. Estimated values of mass emission rates. –1 –1 –1 –1 Season 2009 PM0.5–1 (mg min ) PM1–2.5 (mg min ) PM2.5–5 (mg min ) PM5–10 (mg min ) Spring 0.001 0.012 0.018 0.299 Summer 0.001 0.019 0.027 0.301 Winter 0.002 0.013 0.027 0.305 increased PM concentrations for particles larger than 1 µm. Fig. 6(b) comparison for the 2–3 µm particle fraction, where The estimated mass emission rates agree also with Quian k = 0.2 h–1, P = 0.4 and S = 1.5 × 106 # min–1 and k = 0.6 h–1, et al. (2014) who found (from analysis of data of several P = 0.1 and S = 3.0 × 105 # min–1, respectively. As can be authors) that the walking-induced resuspension emits 107–108 seen both models reproduce well the observed indoor particles per minute giving mass emission rate in range 0.1– concentrations that are influenced mainly by penetration –1 10 mg min . Practically constant value for PM0.7–10 observed from the outdoor air and deposition on indoor surfaces. during all season indicates also stable regime of visits. Thus Fig. 6(c) shows comparison for the 3–5 µm particle fraction, for average 8 visiting hours per day, visitors should contribute where k = 1.5 h–1, P = 0.0 and S = 1.5 × 105 # min–1 i.e., for about 50 g of coarse PM yearly. As found earlier from mass particles that should not penetrate from the outdoor air but size distribution measurements this is about 35% of the total should be generated by the visitors only. As can be seen load of indoor PM (Andělová et al., 2010). model without emission source predicts zero indoor Figs. 6(a)–6(c) provides an example of comparison concentrations while the full model predicts well periodical between indoor concentrations measured in spring 2009 increase caused by visitors followed by decay after visiting and indoor concentrations calculated using values of ki, Pi, hours due to deposition on indoor surfaces. and Si estimated in this analysis. The dash-dot line indicates the measured indoor concentrations, the dash line indicates CONCLUSIONS the concentration of particles counted by the model that does not include the emission source term, and the solid Temporal and spatial variation of size resolved PM line indicates the concentration obtained using the full model, monitoring, performed in the Baroque Library Hall of the which also includes visitors as a source of particles. Fig. 6(a) National Library in Prague during several intensive shows comparison for the 1–2 µm particle fraction and campaigns, revealed that the visitors are the main source of

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Fig. 6. Comparison of indoor measured concentration with modeled concentration of 3 different size fractions: (a) dp = 1–2 m; (b) dp = 2–3 m; (c) dp = 3–5 m. indoor coarse PM. As the previous analysis showed the of T. Travnickova and J. Havlica in this study was supported indoor air can be considered as well mixed, the simple by the grant GACR P105/12/0664 from the Czech Science mass balance model has been used to estimate basic foundation. parameters of the BLH - ventilation rate a, deposition rates ki and penetration factors Pi. The parameters were used to DISCLAIMER model particulate emissions resulting from the movement of visitors during visiting hours. Mass emission rates, None of the authors have any competing interests in the estimated from the comparison of measured and modelled manuscript. data indicates the visitors should contribute about 50 g of coarse PM yearly, which is about 35% of the total load of REFERENCES indoor PM. Abt, E., Suh, H.H., Catalano, P. and Koutrakis, P. (2000). ACKNOWLEDGMENTS Relative contribution of outdoor and indoor particle sources to indoor concentrations. Environ. Sci. Technol. The participation of L. Mašková, J. Smolík, L. Ondráčková 34: 3579–3587. and J. Ondráček in this study was supported by the European Andělová, L., Smolík, J., Ondráčková, L., Ondráček, J., Union 7th framework program HEXACOMM FP7/2007– López-Aparicio, S., Grøntoft, T. and Stankiewicz, J. 2013 under grant agreement N° 315760. The participation (2010). Characterization of airborne particles in the

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