Biomonitoring using a moss species Barbula lambaranensis is an economical method for continuous assessment of atmospheric metal pollution. However, frequent measurement of common heavy metals such as Zn, Cd, Cr, Pb, Cu and Ni in moss can be costly for monitoring large areas. Thus, the aim of the study was to use the surrogate approach to reduce the number of heavy metals required for monitoring. The study found that the Zn load in moss was higher; Pb, Cu and Ni loads were moderate; while Cd and Cr were relatively lower across the study sites. Further, the following surrogates were identified based on PCA: Cu for Cr; Pb for Cd, Cu and Ni; and Cu and Pb for Zn. Quantitative relationships between surrogate loads and the loads of other heavy metals were developed by performing Multiple Linear Regression on a data set constructed using a four level full factorial design. The equations had a relative prediction error and standard error of cross validation below 25% and 1.5%, respectively, indicating that the equations are accurate. However, the cross validated coefficient of determination is relatively low suggesting that the precision of prediction using the equations is low, possibly due to the influence of factors such as climatic conditions on bioaccumulation of heavy metals by moss. Nevertheless, the developed equations can be useful for preliminary investigations.