Degradation of sulfonamides in water by direct UV photolysis and UV/H2O2 processes
Shi, Mark Guanyu
Date of Issue2017-12-15
School of Civil and Environmental Engineering
Public concerns have been raised to the antibiotics over the past decades, due to their continuous consumption and adverse impacts to environment and human health. Sulfonamide (SA) are a common group of antibiotics used in the treatment of humans and animals, which cannot be removed by the conventional water treatment process effectively. The degradation of 15 SAs was investigated by direct UV photolysis and UV/H2O2 processes using a low-pressure UV Hg lamp emitting at 254nm. Degradation rate constants of SAs by direct UV photolysis were calculated. The low first-order rate constants of SAs (k < 0.1 min-1) indicate that direct UV photolysis is inefficient in removing most SAs. There is a good relationship between quantum yield (ϕ) and degradation rates of SAs. For example, SNL with the largest quantum yield (31.42 x 10-3 mol·E-1), shows the largest degradation rate constant (0.2715 min-1) by UV photolysis. Similarly, SMN, with the smallest quantum yield (0.46 x 10-3 mol·E-1) shows the smallest degradation rate constant (0.0035 min-1) by UV photolysis. The degradation rates of SAs were affected by their structure. SAs with simple structures degrade more efficiently than those with hexa-heterocycle and penta-heterocycle structures (simple structure>hexa-heterocycle>penta-heterocycle). The removal of SAs by UV/H2O2 process is more efficient than direct UV photolysis, for the first-order rate constants of SAs by UV/H2O2 process are 3 to 25 times higher compared with that of UV photolysis. Para-chlorobenzoic acid (pCBA) was used to calculate the second-order rate constants of HO· with SAs, indicating a result of (0.45–4.285) x 10-9 M-1s-1. Quantitative structure-activity relationship (QSAR) models for both UV photolysis and UV/H2O2 processes were calculated based on the obtained first-order rate constants and descriptors of the SAs. The optimal models contain all 12 molecular descriptors, with a high squared regression coefficient of 0.9348 and 0.9554, respectively.
Final Year Project (FYP)
Nanyang Technological University