Differences in microcystin production and genotype composition among Microcystis colonies of different sizes in Lake Taihu

The cyanobacterium Microcystis, which occurs as colonies of different sizes under natural conditions, can produce toxic microcystins (MCs). To monitor the toxicity and assess the risk of Microcystis blooms in Lake Taihu, it is important to investigate the relationship between MC production and Microcystis colony size. In this study, we classified Microcystis collected from Zhushan Bay of Lake Taihu during blooms into four classes with size of <50 μm, 50–100 μm, 100–270 μm and >270 μm and studied their differences in MC production and genetic structure. The results showed that colonies with size of <50, 50–100, 100–270 and >270 μm produced 12.2 ± 11.2%, 19.5 ± 7.9%, 61.3 ± 12.6%, and 7.0 ± 9.6% of total MC, respectively. The proportion of cell density of colonies with size of 50–100, 100–270 and >270 μm was positively correlated with MC concentration during blooms, while that of colonies with size of <50 μm was negatively correlated. The MC cell quota tended to be higher during blooms in colonies with larger size except that of colonies with size of 100–270 μm was higher than that of colonies with size of >270 μm from June 11 to September 16. Colonies with size of <50 μm showed the highest proportion of the less toxic MC congener MC-RR, and colonies with size of >100 μm showed higher proportion of the most toxic MC congener MC-LR than colonies with size of <100 μm. Real-time PCR indicated that larger colonies had higher proportion of potential toxic genotype. Principal component analysis of PCR-denaturing gradient gel electrophoresis profile showed that cpcBA and mcyJ genotype compositions were different between colonies with size of <50 μm and colonies with size of >50 μm, and cpcBA genotype composition was also different among colonies with size of 50–100 μm, 100–270 μm and >270 μm. These results indicated that MC cell quota and congener composition were different in Microcystis colonies with different sizes in Lake Taihu during blooms, and the differences in MC production in colonies with different size resulted chiefly from the difference in their genotype composition. Therefore, the authorities of water quality monitoring and drinking water supply service in Lake Taihu should be alert that the toxicity of Microcystis colony with different size was different during blooms, and the high abundance of colonies larger than 50 μm could be an indicator of relatively high bloom toxicity.     

Formation of carbonaceous and nitrogenous disinfection by-products from the chlorination of Microcystis aeruginosa

Formation of carbonaceous disinfection by-products (C-DBPs), including trihalomethanes (THMs), haloacetic acids (HAAs), haloketones (HKs), chloral hydrate (CH), and nitrogenous disinfection by-products (N-DBPs), including haloacetonitriles (HANs) and trichloronitromethane (TCNM) from chlorination of Microcystis aeruginosa, a blue-green algae, under different conditions was investigated. Factors evaluated include contact time, chlorine dosages, pH, temperature, ammonia concentrations and algae growth stages. Increased reaction time, chlorine dosage and temperature improved the formation of the relatively stable C-DBPs (e.g., THM, HAA, and CH) and TCNM. Formation of dichloroacetonitrile (DCAN) followed an increasing and then decreasing pattern with prolonged reaction time and increased chlorine dosages. pH affected DBP formation differently, with THM increasing, HKs decreasing, and other DBPs having maximum concentrations at certain pH values. The addition of ammonia significantly reduced the formation of most DBPs, but TCNM formation was not affected and 1,1-dichloropropanone (1,1-DCP) formation was higher with the addition of ammonia. Most DBPs increased as the growth period of algal cells increased. Chlorination of algal cells of higher organic nitrogen content generated higher concentrations of N-DBPs (e.g., HANs and TCNM) and CH, comparable DCAA concentration but much lower concentrations of other C-DBPs (e.g., THM, TCAA and HKs) than did natural organic matter (NOM).     

Use of three-dimensional excitation and emission matrix fluorescence spectroscopy for predicting the disinfection by-product formation potential of reclaimed water

This study was undertaken to demonstrate the feasibility of using three-dimensional excitation-emission matrix (3DEEM) fluorescence spectroscopy for the determination of chlorination disinfection by-product (DBP) precursors and the disinfection by-product formation potential (DBPFP) of reclaimed water samples. Two major DBP precursors were examined in this study, including humic acid (HA) and fulvic acid (FA). The 3DEEM fluorescence results obtained from various reclaimed water samples indicated that the reclaimed water samples were rich in fulvic acid-like substances that were associated with two main peaks (Ex/Em = 235-245/420-440 nm, and Ex/Em = 330-340/410-430 nm) in the fluorescence spectrum. The results also illustrated that the wavelength location of peak fluorescence intensity of a reclaimed water sample was independent of the influent water quality and the wastewater treatment process used in the reclamation plant. As a result, the peak fluorescence intensity and the wavelength location of the peak were used to identify the species of DBP precursors and their concentrations in the reclaimed water sample. Four regression models were then developed to relate the peak fluorescence intensity of the water sample to its DBPFP, including the formation potential of trihalomethane (THMFP) and the formation potential of haloacetic acid (HAAFP). The regression models were verified using the measured DBPFP results of a series of reclaimed water samples. It was found that the regression modeling results matched the measured DBPFP values well, with prediction errors below 10%. Therefore, the use of 3DEEM fluorescence spectroscopy together with the developed regression models in this study can provide a reliable and rapid tool for monitoring the quality of reclaimed water. Using this method, water quality could be monitored online, without utilizing the lengthy conventional DBPFP measurement.