Inconsistency of PCA-based water quality index - Does it reflect the quality?

The formalization of a stable water quality index (WQI) from measured hydrogeochemical parameters is essential for the identification and classification of water resources. In the principal component analysis (PCA) based WQI approach, the parameter weight is derived using either PC loading or rotated factor loading from a large number of samples pooled for WQI measurement. The PCA-based approach is paradoxical, as the calculated WQI rating of a sample would rather be dependent on the size, and composition of the population. Though this issue is well anticipated, no attempt has been made to regularize or measure the extent of WQI disagreement. In the present study, the WQI of 106 groundwater samples analyzed for 12 different hydrochemical parameters were modelled using PC loading or rotated factor loading (referred to as PCQ-1, PCQ-2, respectively) approach. Analysis reveals PCQ-1 to be positively biased in 78 % of samples and rating disagreements were evident in 9.43 % of samples. WQI of the data set was estimated using repeated (1000) random non-overlapping 2 to 5-fold data partitioning (containing 21 to 83 samples in each fold) adopting either an in-sample (test set) or out-sample (train set) modelling approach. The mean of WQI deviations in repeated resampling from the reference (i.e., using the entire dataset) has been positive in most of the samples using the PCQ-1 model, irrespective of the fold partition size. The median root mean square deviation values of the data set increased with the number of fold partitioning for in-sample calibration for both PCQ-1 and PCQ-2 approaches. The exclusion of a single water quality parameter from the PCA model can cause up to a 60 % deviation of the WQI score in some water samples. The cross-validation and Monte Carlo resampling approach can serve as a framework to test the stability of PCA-based WQI.

Batch biodegradation of para-nitrophenol using Arthrobacter chlorophenolicus A6.

The present study reports the kinetics of p-nitrophenol (PNP) biodegradation by Arthrobacter chlorophenolicus A6 in batch shake flasks for initial PNP concentrations in the range of 25-225 mg l(-1). Results of batch growth kinetics of A. chlorophenolicus A6 at various initial PNP concentrations revealed that the culture followed substrate inhibition kinetics with estimated decay coefficient value of 0.0132 h(-1). Biokinetic constants involved in the process were estimated by fitting the experimental data to several substrate inhibition kinetics models available from the literature. Among the models tested, Webb model fitted the experimental data best with the least root mean square error value, and the estimated model constants values were µ = 0.161 h(-1), K (i) = 128 mg l(-1), K (s) = 60.15 mg l(-1), and K = 100 mg l(-1). In addition, observed and theoretical yield coefficients, maintenance energy, and specific growth rate of the culture at various initial PNP concentrations were also investigated in the study.