PREVENTIVE CONSERVATION IN THE NATURAL SCIENCES MUSEUM OF BARCELONA (NAT): MONITORING ENVIRONMENTAL CONDITIONS OF ZOOLOGICAL COLLECTIONS 1
1,2
3
Quesada, J. ; Garcia- Franquesa, E. ; Díaz-Lorca, A. ; Pérez- Azcárate, M.
1
1
Museu de Ciències Naturals de Barcelona (MCNB), Barcelona, Catalonia (Spain). 2 Author’s correspondence: Eulàlia Garcia Franquesa. Museu de Ciències Naturals de Barcelona, Passeig Picasso s/n, 08003 Barcelona, Catalonia (Spain). Email:
[email protected] 3. Institut Mediterrani d’Estudis Avançats (CSIC-UIB), Esporles, Illes Balears (Spain)
ABSTRACT The objective was to establish a monitoring scheme to measure T and RH in the storerooms at the NAT in order to follow the evolution of these parameters over time, from 2005 to 2010. We analyzed averages, maximum and minimum, the daily, monthly and yearly fluctuations, and the effect of isolation. Results showed that the ranges of variation of T, but not RH, exceeded the standard values, especially in the warmer months. We found significant differences between and within storerooms. The isolation of the sample seems to be effective for humidity. In general, T is the main factor that is currently beyond the recommended values. Solutions include air conditioning, arranging the collection according to the sensitivity of the samples to temperature. KEYWORDS Monitoring scheme, temperature, relative humidity, storerooms, isolation.
INTRODUCTION A cornerstone in collection management is maintenance of the specimen over time in order to preserve optimal conditions and to ensure stability. Thus, a basic issue in preventive conservation of museum specimens is the control of the pernicious environmental factors. These factors are mainly RH, T, light, dust, vibration and pests (Mathias 1994). In the case of T and RH, conservation of specimens requires some standardized environmental conditions (Table1) as these factors are frequently the causes of destruction of biological collections or vehicles of biological pests (Michalski 2006). RH is a damaging factor that is well known to affect biological collections as water contained in air may facilitate swelling or shrinking, accelerate biodeterioration (i.e. chemical reactions) or serve as a basis for biological activity (Staniforth 1984; Mathias 1994). This factor is closely related to T, which is another factor that affects biological collection (Thompson 1986). T acts in combination with RH, swelling, shrinking and also facilitating pest appearance or accelerating chemical and biological deterioration. Controlling these factors to preserve biological collections is therefore essential. Both variables must be controlled in standardized values to minimise deleterious effects. Several standard levels have been proposed to date to create an ideal atmosphere, although a consensus is difficult to find as ideal limits may vary depending on factors such as climatic conditions (i.e. tropical countries, Teygeler 2001) or particular country recommendations. It is therefore mandatory to control these environmental conditions over time to ensure they remain within that recommended limits (Mathias 1994, Waller 1994) (TABLE 1). If either of these variables are found to be outside these limits, steps should be taken to guarantee collections conservation (Mathias, 1994). The aim of this study was to establish a monitoring scheme to measure the T and RH in the storerooms and exhibition at the NAT so as to follow the evolution of these parameters over time and to discuss the best management measures for zoological collections. Monitoring these environmental variables will allow us to answer particular questions: 1) Are T and RH within the range of values recommended by the literature? 2) Are there any differences among the spaces where the biological collections are stored?. 3) Are there any kinds of daily or seasonal fluctuations in the spaces where the biological collections are stored? 4) Are specimens effectively isolated from environmental variables? MATERIAL AND METHODS a) General procedures and data collection We established a monitoring program to control RH and T in 27 spaces distributed throughout the NAT during the years 2005 to © 2010. We used a set of data-loggers (TESTO ) placed in the conservation spaces. These data-loggers were located inside cabinets were the specimen were stored, and outside the cabinet. These digital data-loggers are programmed to collect and accumulate RH and T at defined times. We scheduled these devices to collect data every two hours. To maximize the use of data-logger in the spaces, we measured the third and fourth floors for the first and third week of each month, and the second and first floors in the second and fourth weeks. Once the data were collected, we downloaded them to a database. We analyzed the T and RH mean, maximum and minimum values, the daily, monthly and yearly fluctuations, and the effect of isolation of the samples respect to external T and RH.
1
b) Data analysis To analyze whether RH or T were outside standard limits we evaluated whether the mean, the maximum and the minimum levels per month for each factor in each storeroom. This also allowed to us analyze whether there were seasonal fluctuations over the years. To determine whether there were statistically significant differences among the different spaces we performed an Analysis of Variance (ANOVA) where we used the mean (RH, T) value per month as a dependent variable, and the space, the floor and the orientation as fixed factors. This analysis allowed us to determine whether there were statistical differences among the different spaces floors and cardinal points on the basis that variance of RH and T within a species was smaller than the variance found among spaces. To analyze the daily differences in each room we calculated the difference between the maximum and the minimum values of RH and T in a day. We hence calculated the mean and the maximum variation in a day per each store and we made a Pareto graph to determine which store had the highest daily variation. To evaluate validity of the isolation measures to avoid humidity and temperatures effects we classified the locations where dataloggers were placed into three categories: data-loggers in open spaces without door (Isolation 0), closed spaces (Isolation 1) and data-loggers spaces within a cabinet (Isolation 2). We then performed an analysis of variance with a single factor (one way-ANOVA) where the dependent variable was RH or T and the isolation level was fixed factor. RESULTS a) Are T and RH within the range of values recommended by the literature? Our results showed that in all our spaces the temperature was the factor that did not fit within the recommended parameters (Table 1) (FIG. 1). In all the spaces we found a circannual pattern where the temperature of this parameter went beyond the recommended levels in spring and summer (FIG. 1). b) Are there any differences among the spaces where the biological collections are stored? We also found statistical differences between rooms (T: F(32, 36069)=396.15 ;p>0.001; RH: T: F(32, 36069)=787.15; p>0.001), although all rooms had the same pattern: the winter months tended to fit the standard parameters but the hotter periods did not. It is remarkable that even when some spaces were acclimatized, the environmental influence was not avoided. The parameter humidity did fit the standard conditions but there was also a fluctuation between months in each room. The only exceptions were two spaces that suffered a water leak in spring and summer of 2008. c) Are there any daily or seasonal fluctuations in the spaces where the biological collections are stored? In relation to daily changes, the main problem was that, to date, there are no standards levels to say when a daily change may be dangerous for zoological collections. For this reason, we only considered differences between spaces. Regarding temperature, we found that, on average, the fluctuating daily average temperature was higher than 2 ºC (Mean ± Standard Deviation: 2.1± 1.7ºC) (range margin allowed 13-15° C). It is remarkable that the maximum values of circadian fluctuation occurred in most spaces on the first floor, where the zoological collections were exposed and where there were large windows. The remaining spaces did not exceed the 2 ºC margin (FIG. 2), although in all cases the maximum temperature exceeded the recommended temperature. The most significant fluctuation was 5.9º C in one day. Respect to RH, the average humidity was very low (mean ± standard deviation: 2.94± 2.90ºC) in relation to the most demanding range provided by standards (20 ºC for organic compounds (Table 1). We did not find any pattern to explain the order found in the Pareto graphic respect to RH (FIG.2). We found that the maximum fluctuation in one day was more than 25 ºC (26.1ºC). d) Is the specimen isolation from environmental variables effective? The isolation level of zoological collections had a marginal effect on temperature. Data-loggers that were placed in more “hidden” spaces (i.e. within a cabinet) had weaker relationships with external temperatures than those that were more exposed (Isolation0, and Isolation-1 categories), although the differences were not significant (ANOVA one way, F (2,21)= 1.68; p= 0.21). Regarding RH, isolation of the samples seemed to be effective for this parameter, because data-loggers that were placed in more “hidden” spaces (Isolation 2) showed a less significant relationships with external temperature than those that were more exposed (ANOVA one way, F(2,21)= 4.05; p< 0.05) (FIG. 3).
DISCUSSION In general terms, T is the factor that currently exceeds the recommended standard values in the storerooms and exhibition at Castell dels Tres Dragons of the NAT. This is not surprising, as this building was not specifically designed to house a museum and the temperature of the building varies according to the outside temperature (Diaz-Lorca et al. 2008). However, we found significant differences between spaces and over time within a room. Winter months tended to fit the ideal parameters, but the problem arose in the spring-summer months (FIG. 1). Acclimatizing the rooms may be the first solution. Since we found differences between rooms, one solution might be to rearrange the zoological collections in terms of the samples sensitivity to temperature (i.e. shrinkage). The effect of the temperature in itself is not a danger, but it influences the RH values and it is therefore indirectly harmful for the specimens (Uribe, 1999). In other words, although the temperature values are of concern, the effects of inadequate RH are more deleterious than the incorrect T values (Staniforth, 1984; Uribe 1999).
2
Relative humidity does not suppose a great problem for biological collections in the NAT. The rooms proved to be within standards levels respect to RH. Its fluctuation does not seem a priori to be explained by temperature, presumably because the RH might be more influenced by rainfall than by fluctuations of the external temperature. However, daily variation in RH may be important in some cases. For this reason, several preventive solutions may be considered. The most effective measure would be to use dehumidifiers. Alternatively, several “hand-made” and cost-effective solutions could be applied, such as keeping zoological samples in hermetic bags (with silica material to buffer changes in RH due to temperature effects) (Thomson 1986). Moreover, we found that the level of isolation is a determinant solution to avoid external factors as RH. These isolation solutions may also be useful for other threats such as animal or fungal infestations not evaluated in this study. Regarding daily fluctuations, the main problem is to define when a change in RH or T is considered harmful. Extreme variation of environmental conditions may increase the harmful consequences of poor management (such as shrinkage, swelling, and embrittling) (Thompson 1986). Obviously, some materials are more sensitive to these threats than others. Hygroscopic material like leather or skin may suffer swelling, while dry materials like bones, horns, ivory or insects may be more sensitive to extreme changes in T or low RH consistently increasing their fragility (Mathias 1999). This is particularly important for temperate zones like the Mediterranean or tropical areas (implied already). However, further studies are necessary to assess the deleterious effects of sudden changes on the different biological materials. Artificial ageing and subsequent modelization may be of interest in future research to clarify this subject. The daily and yearly fluctuations observed in our environmental monitoring scheme suggest that the material in the NAT is subjected to great stress. This is particularly worrying for the extensive chordate and insect collections in the Museum. When a technological solution is impossible (dehumidifiers, air conditioning), the rearrangement of the collections and in situ solutions are appropriate. For instance, the samples should be insulated in the space itself (cabinet to cabinet, specimen to specimen) to minimize the deleterious environmental effects. A stable T of 13 to 15°C and stable humidity below 60% would ensure good preservation of the zoological collection. Besides the temporal patterns, future analysis should study whether there is a spatial factor of relevance, such as the site where the specimens are located. Other harmful factors, such as dust and light, should also be considered. ACKNOWLEDGMENTS The authors would like to thank Glòria Masó, Miguel Prieto and Francesc Uribe for their valuable help and advice in study development. The Meteorological Service at the Generalitat de Catalunya provided the external values of RH and T. This study was funded by the Department of Culture at the Generalitat de Catalunya. REFERENCES Dahlin, E. (2002). Preventive conservation strategies for organic objects in museums, historic buildings and archives. In: 5th ec conference report “cultural heritage research: a Pan European challenge”. Krakovia. 16-18th de May, 2002. Díaz-lorca, A, Quesada, J & Garcia-Franquesa, E. (2008). Anàlisi de les condicions ambientals de l’edifici del Museu de Zoologia: 2005-2007. Museu de Ciències Naturals de Barcelona. Unedited report. Mathias, J. (1994). Housing and maintenance of collections. In: Manual of Natural History Curatorship. Stansfield G.,Mmathias J & Reid, G. London. Museums & Galleries Commission. Michalski, S. (2006). Cómo administrar un Museo: manual práctico. París. ICOM. Staniforth, S. (1984). Environmental conservation. In: Manual of Curatorship. J.M.A Thompson, Ed. London. Butterwoths. pp: 192202. Teygeler. R. (2001). Preservation of archives in tropical climates. an annotated bibliography. 2001, Paris, The Hague, Jakarta, International Council on Archives/National Archives of the Netherlands/National archives of the Republic of Indonesia. Thompson, G. (1986). The museum environment. London : Butterworths. 293 pp. Uribe, F. (1999). Efecte i control de les variables microclimatiques sobre les col·leccions. Inedit document. Waller, R. (1994). Risk management applied to preventive conservation. Preprints of the 15th international congress. Internat. Institute for Conservation of Historic and Artistic Works. 12-1.
3
Figure 1
4
ex te r na l
ar tr ò 1E p . X 2p 2 i SS 2A s al for a a A c 3r t es 2B e04 15 A 1m 58f o 0s a2 r a al 40 a_ 10 ba 9 l 3C len N a 09 17 m ag s1 at 8 ze 3c m s0 _e 8 xt 23 ern 00 sm 30 c1 1 60 sm 7 1x g 0 02 6 cr us S M 33 G 5 11 0 1e 8 x0 1E Xp 1e 8 ap x22 al a lo n 22 es 50 5 1E 29 X 3c 28 p1 A 6a 2 4 9 ar 2b T 4 1 m a ar ar 58 8 m i_ alt ar fo e i_ no ll tip u s 1E t ec X _m 1 a al 2A ac 01 2b olo a3 gia 2B 7a A ltel 19 l 1E alt X2 ell 1E 8A X2 04 2A 22 04 50 93 6
2
Relative Humidity (%) ex
te r
1 na ma l a 24 rtr 01 0 ò 1E p . 9 X 2p 22 i s 2 A 1E ba for Xp 58 a ap alte a ll 2B llon A es 58 fo 1e r a x 1x 22 02 a cr u 1e s x 1E 0 8 1E X28 X1 A 2A 22 01 50 52 3c 9 s0 3r 8 e 1E 04 X2 15 8 3C A 0 N 4 1E 09 X2 17 m 2A ag 04 at ze 4T m 41 _e 8 2B xt e 0s A1 rn al 9a a_ lte ba l l lle 22 n a S a 509 la 36 A ct es 23 3 3 5 0 3c 030 p1 1 2b 6a a3 29 7a ar lte m ll ar i_ fo s1 no 8 te c ar sm a m ar S M g0 i_ G 6 tip u s s 110 _m mc 8 al 16 ac 07 ol og ia
2
Temperature (ºC)
Figure 2 25
20
15
Mean ∆ Máx ∆
10
5
0
70
60
50
40
30
20
10
0
5
Figure 3
Relative Humidity
Relationship Value (R2) spaceextern T (arcsen)
1,4 1,2 1,0 0,8 0,6 0,4 0,2 0
Relationship Value (R2) spaceextern RH (arcsen)
1,44
1
2
1
2
Temperature Isolation level
1,40 1,36 1,32 1,28 1,24 0
Isolation level
6
7
