Development of dose-response functions for historic paper degradation using exposure to natural conditions and multivariate regression

Abstract

Many collections of documents, manuscripts, and works of art on paper are prone to degradation due to a complex interplay of extrinsic and intrinsic factors. The aim of this study was to examine the simultaneous effect of multiple degradation agents on selected non-model types of paper in natural environments, and the relative effect of environmental parameters (heat, humidity, light and pollution) compared to material parameters (pH, fibre composition and presence of additives). An exposure experiment was set up to investigate visual and chemical changes of 12 different types of paper in real time in different environmental conditions over a 1.5-year period at 11 sites across Europe and North Africa, sheltered from UV light and precipitation. Suitable environmental monitoring equipment, such as data loggers and gas samplers, and analytical methods to characterise sample degradation, specifically spectrocolorimetry and capillary viscometry, were used to estimate alterations in visual appearance and degree of cellulose polymerisation, which are the most important properties of paper in the heritage context. Multiple linear regression and principal component regression were used to interpret the large volume of data and calculate a set of dose-response functions. The results of this study not only suggested that most of the considered variables are of significance in relation to changes in colour and in average molecular weight, but also revealed a number of meaningful interactions between these variables. Based on the assessment of the relative contributions of environmental and material-related variables to the natural ageing processes of paper, the dose-response functions proposed in this study enable prioritisation of degradation factors in environmental management of paper-based collections and in historic paper degradation studies; however, further work is required to increase accuracy and understanding of the chemistry of degradation.

Characterisation and durability of contemporary unsized Xuan paper

“…4b are substantial, a trend towards higher brightness is observed during the experiment. This corroborates previous findings that paper without optical brighteners, such as the unsized Xuan papers in this study, tend to become brighter when exposed to daylight (Pastorelli et al 2019) XP10 suggest that sun bleaching may not have been entirely replaced by chemical bleaching in the twentieth century.…”

The application of machine learning in nanoparticle treated water: A review

“…MLR possesses the ability to determine the relative influence of predictor variables on the criterion value as well as the ability to conduct the identification of outliers or anomalies [45]. Yet, the limitation of MLR is it suffers from collinearity, is sensitive to outliers, and is only applicable to linear datasets [46,47]. In addition, ANN is employed to predict the performance evaluation of the reactions of the organic matter.…”

Chemo-mechanical ageing of paper: effect of acidity, moisture and micro-structural features

“…In the literature, different modeling approaches have been proposed for the prediction of degradation of historic paper. The approaches commonly rely on dose-response functions that describe the time-evolution of the degree of polymerization, as affected by various degradation factors, such as the temperature, relative humidity, air pollutants, and the acidity of the paper [22,23,24,25,12,26]. The dependency on these degradation factors is established by performing dedicated experiments or using existing data.…”