Vender specific data. This dataset is associated with the following publication: Mash , H. Effect of chlorination on the protein phosphatase inhibition activity for several microcystins. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 95: 230-239, (2016).

This data set contains supporting information for an article titled: Impact of Water Quality and Operational Factors on Microcystin Removal by Powdered Activated Carbon. This article was published in AWWA Water Science. The article abstract is as follows: The feasibility of using a 26-1 fractional factorial design to screen the relative importance of six water quality and operational factors in the removal of microcystin-LR (MC-LR) by PAC was evaluated through jar testing. The factors were: PAC type, PAC dose, TOC concentration, turbidity, alum dose, and timing of PAC versus coagulant application. Follow-up tests were performed to examine the interaction of PAC dose and TOC concentrations. All MC-LR analyses were performed by ELISA and LC/MS/MS. The top three effect magnitudes were the same by ELISA and LC/MS/MS: PAC dose > PAC type > PAC application time. Correlation coefficients between removals estimated by ELISA and LC/MS/MS were > 0.9 (p << 0.05). With both methods, the effects of PAC type and dose were found to be markedly larger than the other factors. The follow-up tests indicated a greater impact of PAC dose at higher NOM concentrations. Factorial designs are not commonly used to plan drinking water jar test experiments. The results generated in this study were plausible with respect to the existing body of adsorption knowledge, thus helping to demonstrate the feasibility of the factorial approach. This dataset is associated with the following publication: Alexander, M., T. Waters, M. McNeely, T. Speth, and N. Dugan. Impact of water quality and operational factors on microcystin removal by powdered activated carbon. AWWA Water Science. John Wiley & Sons, Inc., Hoboken, NJ, USA, 6(3): 1372, (2024).

(1) qPCR and RT-qPCR for cyanotoxin producing genes, and (2) some water quality parameters. This dataset is associated with the following publication: Duan, X., C. Zhang, I. Struewing, X. Li, H. Allen, and J. Lu. Cyanotoxin-encoding genes as powerful predictors of cyanotoxin production during harmful cyanobacterial blooms in an inland freshwater lake: Evaluating a novel early-warning system. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 830: 154568, (2022).

(1) qPCR and RT-qPCR for cyanotoxin producing genes, and (2) some water quality parameters. This dataset is associated with the following publication: Duan, X., C. Zhang, I. Struewing, X. Li, H. Allen, and J. Lu. Cyanotoxin-encoding genes as powerful predictors of cyanotoxin production during harmful cyanobacterial blooms in an inland freshwater lake: Evaluating a novel early-warning system. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 830: 154568, (2022).

Water sample data collected and curated by Ohio State University's Stone Laboratory and others between 2013 and 2024 in Lake Erie. The samples were collected in part of several projects funded by various state (Ohio EPA and Ohio Sea Grant) and federal agencies (US EPA, NSF, NIH, NOAA). The program column describes who or why the samples were collected. The captains program is a partnership between Stone Lab and the Lake Erie Charter Boat Association in which the captains collect water samples and Stone Lab analyzes them (https://ohioseagrant.osu.edu/products/4c0k6/charter-boat-captains-help-monitor-lake-erie-water-quality). The SL Buoy program is a high temporal resolution dataset of grab samples paired with a high temporal resolution sonde data attached to a buoy (https://doi.org/10.1007/s11356-018-2612-z). The HABs Grab were high spatial resolution samples collected on two days during peak blooms of 2018 and 2019 (https://doi.org/10.1016/j.hal.2021.102080). The flow-through program was an attempt to collect water quality data throughout the winter by pumping lake water into the research building at Stone Lab. Programs Stone Lab and UToledo were samples collected by Stone Lab and UT Lake Erie Center from research vessels at routinely monitored locations. Samples were analyzed for chlorophyll a (an indicator of algae biomass), microcystins (a group of toxins produced by cyanobacteria), total phosphorus and nitrogen (indicators of maximum biomass potential), dissolved nitrate, phosphate, and silicate (nutrients available for algae), and total suspended solids (mass of all particulates in the water).

Supplemental information for UV-Chlorine treatment manuscript. This dataset is associated with the following publication: Kong , M., E. Passa, T. Sanan, A. Mohammed, A. Forster, P. Justen, A. Delacruz, J. Westrick, K. O'Shea, B. Ren, M. Nadagouda, J. Yadav, X. Duan, S. Richardson, and D. Dionysiou. Guarding drinking water safety against harmful algal blooms: Could UV/Cl2 treatment be the answer?. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 59(2): 1421-1433, (2025).

Measured concentrations in octanol-water phase partitioning of microcystin congeners. This dataset is associated with the following publication: McCord, J., J. Lang, D. Hill, M. Strynar, and N. Chernoff. pH dependent octanol–water partitioning coefficients of microcystin congeners. JOURNAL OF WATER AND HEALTH. IWA Publishing, London, UK, 16(3): 340-345, (2018).

Measured concentrations in octanol-water phase partitioning of microcystin congeners. This dataset is associated with the following publication: McCord, J., J. Lang, D. Hill, M. Strynar, and N. Chernoff. pH dependent octanol–water partitioning coefficients of microcystin congeners. JOURNAL OF WATER AND HEALTH. IWA Publishing, London, UK, 16(3): 340-345, (2018).

Site-specific multiple linear regression models were developed for eight sites in Ohio—six in the Western Lake Erie Basin and two in northeast Ohio on inland reservoirs--to quickly predict action-level exceedances for a cyanotoxin, microcystin, in recreational and drinking waters used by the public. Real-time models include easily- or continuously-measured factors that do not require that a sample be collected. Real-time models are presented in two categories: (1) six models with continuous monitor data, and (2) three models with on-site measurements. Real-time models commonly included variables such as phycocyanin, pH, specific conductance, and streamflow or gage height. Many of the real-time factors were averages over time periods antecedent to the time the microcystin sample was collected, including water-quality data compiled from continuous monitors. Comprehensive models use a combination of discrete sample-based measurements and real-time factors. Comprehensive models were useful at some sites with lagged variables (< 2 weeks) for cyanobacterial toxin genes, dissolved nutrients, and (or) N to P ratios. Comprehensive models are presented in three categories: (1) three models with continuous monitor data and lagged comprehensive variables, (2) five models with no continuous monitor data and lagged comprehensive variables, and (3) one model with continuous monitor data and same-day comprehensive variables. Funding for this work was provided by the Ohio Water Development Authority and the U.S. Geological Survey Cooperative Water Program.

Water samples were collected by charter boat captains and Stone Lab scientists in order to track the water quality of Lake Erie. Samples were analyzed for chlorophyll a (an indicator of algae biomass), microcystins (a group of toxins produced by cyanobacteria), total phosphorus and nitrogen (indicators of maximum biomass potential), dissolved nitrate, phosphate, and silicate (nutrients available for algae), and total suspended solids (mass of all particulates in the water). These data are available in .xlsx format.