Abstract
Biochemical methane potential (BMP) test is a key analytical technique to assess the implementation and optimisation of anaerobic biotechnologies. However, this technique is characterised by long testing times (from 20 to >100days), which is not suitable for waste utilities, consulting companies or plants operators whose decision-making processes cannot be held for such a long time. This study develops a statistically robust mathematical strategy using sensitivity functions for early prediction of BMP first-order model parameters, i.e. methane yield (B0) and kinetic constant rate (k). The minimum testing time for early parameter estimation showed a potential correlation with the k value, where (i) slowly biodegradable substrates (k≤0.1d−1) have a minimum testing times of ≥15days, (ii) moderately biodegradable substrates (0.1<k<0.2d−1) have a minimum testing times between 8 and 15 days, and (iii) rapidly biodegradable substrates (k≥0.2d−1) have testing times lower than 7days.
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