A Bayesian risk assessment framework for microcystin violations of drinking water and recreational standards in the Bay of Quinte, Lake Ontario, Canada

Kelly, Noreen E.; Javed, Aisha; Shimoda, Yuko; Zastepa, Arthur; Watson, Susan B.; Mugalingam, Shan; Arhonditsis, George B.

doi:10.1016/j.watres.2019.06.005

Cited by 32 publications

(16 citation statements)

References 53 publications

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“…Michalak et al [50] found that the combined effect of calm wind conditions, reduced lake mixing, increased nutrient loading and increased precipitation may have facilitated a record-breaking Microcystis bloom in Lake Erie in 2011, and furthermore, predicted increases in the frequency of such events in the future (50% increase in large storms with precipitation >30 mm under future climate models). Recently, Kelly et al [51], found that lower wind speed (≤37 km/hr), combined with an increase in eutrophication indicators (Chl a , nutrients) and temperature, were associated with the increased probability of total MC concentrations exceeding drinking water standards (1.5 µg/L) in the Bay of Quinte. Given the decline in wind speed observed in recent years in the Laurentian Great Lakes region (Figure S4) and predictions of higher total annual precipitation [52], the increase in MC-LA dominating blooms may very well continue.…”

Section: Discussionmentioning

confidence: 99%

Meteorological and Nutrient Conditions Influence Microcystin Congeners in Freshwaters

Taranu

Pick

Creed

et al. 2019

Toxins

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Cyanobacterial blooms increasingly impair inland waters, with the potential for a concurrent increase in cyanotoxins that have been linked to animal and human mortalities. Microcystins (MCs) are among the most commonly detected cyanotoxins, but little is known about the distribution of different MC congeners despite large differences in their biomagnification, persistence, and toxicity. Using raw-water intake data from sites around the Great Lakes basin, we applied multivariate canonical analyses and regression tree analyses to identify how different congeners (MC-LA, -LR, -RR, and -YR) varied with changes in meteorological and nutrient conditions over time (10 years) and space (longitude range: 77°2′60 to 94°29′23 W). We found that MC-LR was associated with strong winds, warm temperatures, and nutrient-rich conditions, whereas the equally toxic yet less commonly studied MC-LA tended to dominate under intermediate winds, wetter, and nutrient-poor conditions. A global synthesis of lake data in the peer-reviewed literature showed that the composition of MC congeners differs among regions, with MC-LA more commonly reported in North America than Europe. Global patterns of MC congeners tended to vary with lake nutrient conditions and lake morphometry. Ultimately, knowledge of the environmental factors leading to the formation of different MC congeners in freshwaters is necessary to assess the duration and degree of toxin exposure under future global change.

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Section: Discussionmentioning

confidence: 99%

Meteorological and Nutrient Conditions Influence Microcystin Congeners in Freshwaters

Taranu

Pick

Creed

et al. 2019

Toxins

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“…MC is water-soluble, heat-resistant, and has a strong toxicity that cannot be removed by boiling at a high temperature (7). After being absorbed by flora and fauna, this toxin is transferred to the human body via the food chain and is widely distributed in water, and thus, endangers the ocean ecology (8). MC-LR is a hepatotoxic cyanotoxin that acute and chronic exposure to this toxin in addition to liver cancer in human beings can have harmful effects on the kidney, heart, and the gastrointestinal tract (9).…”

Section: Introductionmentioning

confidence: 99%

The performance of TiO₂ /NaY-zeolite nanocomposite in photocatalytic degradation of Microcystin-LR from aqueous solutions: Optimization by response surface methodology (RSM)

Ebrahimi

Jafari

Ebrahimpour

et al. 2020

Environ Health Eng Manag

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Background: Microcystin (MC) is a hepatotoxic and carcinogenic toxin that is generated by cyanotoxins which can have adverse effects on the human health. Therefore, it is very important to remove it from the environment. This study was performed to investigate the efficiency of titanium dioxide (TiO 2)/ NaY-zeolite (T/N-Z) nanocomposite for removal of MC-LR under ultraviolet light. Methods: In the present study, T/N-Z nanocomposite was synthesized using the hydrothermal method. Specification of the photocatalysts was determined by the field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR) spectra. The response surface methodology (RSM) was used to survey the effects of operating variables such as pH, contact time, and catalyst dose on the removal of MC-LR. The MC-LR concentration was measured by high-performance liquid chromatography (HPLC). Results: It was revealed that the increase of contact time and catalyst dose had a positive effect on enhancing the removal efficiency of MC-LR, but pH had a negative effect. Finally, the maximum MC-LR removal efficiency was 97.63%, which occurred at pH = 5, contact time = 120 min, and catalyst dose = 1.2 g/L. Conclusion: In general, T/N-Z composite in aqueous solutions under the UV light can easily decompose MC-LR and it can also be proposed as an efficient composite for removal of MC-LR from contaminated water.

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“…Because as the most microcystin monitoring studies report, MCs remain an extremely low value in nonalgal bloom season, or undetectable (Hu et al, 2018; Major et al, 2018; Xue et al, 2018), while other environmental indicators like BOD, ammonia does not have significant seasonal variation. Adding seasonal variables can be helpful for statistical models to tackle with extreme values (Kelly et al, 2019; Yuan & Pollard, 2017).…”

Section: Resultsmentioning

confidence: 99%

“…Based on the environmental factors' effects on MC concentration, many researchers tried to build quantitative models to predict MC concentration by environmental factors. For example, Kelly et al (2019) applied segmented multiple regression to predict MCs based on chlorophyll‐a, wind speed, temperature, total phosphorus, and ammonia monitoring data. Chan et al (2007) also applied an artificial neural network algorithm (ANN) to estimate MCs by SD, WT, RF, pH, DO,

{NO}_{3}^{‐}

{PO}_{4}^{3 ‐}

ratio,

{NO}_{3}^{‐}

{PO}_{4}^{3 ‐}

, and chl‐a.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake

Wang

Yan

et al. 2020

Water Environment Research

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Microcystins (MCs), the algal toxins produced by cyanobacteria, raised a worldwide concern in recent decades. Limited monitoring stations for MCs make it hard to map the MC spatial distribution in certain areas. To tackle such problems, we selected Liangxi River as our research area and developed an integrated model to get spatial continuous MC data without too many sampling sites, which integrates a hydro‐environment model and an artificial neural network algorithm (ANN). The ANN algorithm can estimate concentration MCs via environmental factors. In this paper, we selected chl‐a, TN, TP, NO2‐, NO3‐, NH3‐N, and PO43‐ as stressors. The ANN model we established showed good performances both in train (R2 = 0.8407) and test set (R2 = 0.7543). In the hydro‐environment model, by inputting river geometry and model boundary data, the spatial continuous water quality data could be simulated. The water quality data returned from the hydro‐environmental model were used as input variables of the well‐trained ANN model; the continuous MC data were derived. To evaluate this model on geo‐mapping the MC distribution in Liangxi River, we compared the performance of this model and spatial interpolation on the test set, it turns out the integrated model showed a better performance. © 2020 Water Environment Federation Practitioner points The cost of microcystin (MC) detection is too high for routine monitoring. We integrated regression method and hydro‐environment model to predict MCs. Results derived from spatial interpolation are not robust in unmonitored area. The new integration model can minimize the drawback of spatial interpolation.

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A Bayesian risk assessment framework for microcystin violations of drinking water and recreational standards in the Bay of Quinte, Lake Ontario, Canada

Cited by 32 publications

References 53 publications

Meteorological and Nutrient Conditions Influence Microcystin Congeners in Freshwaters

Meteorological and Nutrient Conditions Influence Microcystin Congeners in Freshwaters

The performance of TiO₂ /NaY-zeolite nanocomposite in photocatalytic degradation of Microcystin-LR from aqueous solutions: Optimization by response surface methodology (RSM)

Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake

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A Bayesian risk assessment framework for microcystin violations of drinking water and recreational standards in the Bay of Quinte, Lake Ontario, Canada

Cited by 32 publications

References 53 publications

Meteorological and Nutrient Conditions Influence Microcystin Congeners in Freshwaters

Meteorological and Nutrient Conditions Influence Microcystin Congeners in Freshwaters

The performance of TiO2 /NaY-zeolite nanocomposite in photocatalytic degradation of Microcystin-LR from aqueous solutions: Optimization by response surface methodology (RSM)

Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake

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The performance of TiO₂ /NaY-zeolite nanocomposite in photocatalytic degradation of Microcystin-LR from aqueous solutions: Optimization by response surface methodology (RSM)