Publications by authors named "Richard Stumpf"

29 Publications

  • Page 1 of 1

The Lake Erie HABs Grab: A binational collaboration to characterize the western basin cyanobacterial harmful algal blooms at an unprecedented high-resolution spatial scale.

Harmful Algae 2021 08 23;108:102080. Epub 2021 Jul 23.

Civil and Environmental Engineering, Michigan Technological University, 1400 Townsend Dr., Houghton, MI 49931, USA.

Monitoring of cyanobacterial bloom biomass in large lakes at high resolution is made possible by remote sensing. However, monitoring cyanobacterial toxins is only feasible with grab samples, which, with only sporadic sampling, results in uncertainties in the spatial distribution of toxins. To address this issue, we conducted two intensive "HABs Grabs" of microcystin (MC)-producing Microcystis blooms in the western basin of Lake Erie. These were one-day sampling events during August of 2018 and 2019 in which 100 and 172 grab samples were collected, respectively, within a six-hour window covering up to 2,270 km and analyzed using consistent methods to estimate the total mass of MC. The samples were analyzed for 57 parameters, including toxins, nutrients, chlorophyll, and genomics. There were an estimated 11,513 kg and 30,691 kg of MCs in the western basin during the 2018 and 2019 HABs Grabs, respectively. The bloom boundary poses substantial issues for spatial assessments because MC concentration varied by nearly two orders of magnitude over very short distances. The MC to chlorophyll ratio (MC:chl) varied by a factor up to 5.3 throughout the basin, which creates challenges for using MC:chl to predict MC concentrations. Many of the biomass metrics strongly correlated (r > 0.70) with each other except chlorophyll fluorescence and phycocyanin concentration. While MC and chlorophyll correlated well with total phosphorus and nitrogen concentrations, MC:chl correlated with dissolved inorganic nitrogen. More frequent MC data collection can overcome these issues, and models need to account for the MC:chl spatial heterogeneity when forecasting MCs.
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http://dx.doi.org/10.1016/j.hal.2021.102080DOI Listing
August 2021

Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States.

Water Res 2021 Aug 24;201:117377. Epub 2021 Jun 24.

U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, USA.

This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency's Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses (n = 84) submitted as part of the U.S. Environmental Protection Agency's fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016 through 2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.
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http://dx.doi.org/10.1016/j.watres.2021.117377DOI Listing
August 2021

Cyanobacterial bloom phenology in Saginaw Bay from MODIS and a comparative look with western Lake Erie.

Harmful Algae 2021 03 27;103:101999. Epub 2021 Feb 27.

Horn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD United States.

Saginaw Bay and western Lake Erie basin (WLEB) are eutrophic catchments in the Laurentian Great Lakes that experience annual, summer-time cyanobacterial blooms. Both basins share many features including similar size, shallow depths, and equivalent-sized watersheds. They are geographically close and both basins derive a preponderance of their nutrient supply from a single river. Despite these similarities, the bloom phenology in each basin is quite different. The blooms in Saginaw Bay occur at the same time and place and at the same moderate severity level each year. The WLEB, in contrast, exhibits far greater interannual variability in the timing, location, and severity of the bloom than Saginaw Bay, consistent with greater and more variable phosphorus inputs. Saginaw Bay has bloom biomass that corresponds to relatively mild blooms in WLEB, and also has equivalent phosphorus loads. This result suggests that if inputs of P into the WLEB were reduced to similarly sized loads as Saginaw Bay the most severe blooms would be abated. Above 500 t P input, which occur in WLEB, blooms increase non-linearly indicating any reduction in P-input at the highest inputs levels currently occurring in the WLEB, would yield disproportionately large reductions in cyanobacterial bloom intensity. As the maximum phosphorus loads in Saginaw Bay lie just below this inflection point, shifts in the Saginaw Bay watershed toward greater agriculture uses and less wetlands may substantially increase the risk of more intense cyanobacterial blooms than presently occur.
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http://dx.doi.org/10.1016/j.hal.2021.101999DOI Listing
March 2021

Physical drivers facilitating a toxigenic cyanobacterial bloom in a major Great Lakes tributary.

Limnol Oceanogr 2020 Dec 24;65(12):2866-2882. Epub 2020 Jul 24.

Department of Biological Sciences, Bowling Green State University, Bowling Green, OH 43403, USA.

The Maumee River is the primary source for nutrients fueling seasonal -dominated blooms in western Lake Erie's open waters though such blooms in the river are infrequent. The river also serves as source water for multiple public water systems and a large food services facility in northwest Ohio, USA. On 20 September 2017, an unprecedented bloom was reported in the Maumee River estuary within the Toledo metropolitan area, which triggered a recreational water advisory. Here we (1) explore physical drivers likely contributing to the bloom's occurrence, and (2) describe the toxin concentration and bacterioplankton taxonomic composition. A historical analysis using ten-years of seasonal river discharge, water level, and local wind data identified two instances when high-retention conditions occurred over ≥10 days in the Maumee River estuary: in 2016 and during the 2017 bloom. Observation by remote sensing imagery supported the advection of cyanobacterial cells into the estuary from the lake during 2017 and the lack of an estuary bloom in 2016 due to a weak cyanobacterial bloom in the lake. A rapid-response survey during the 2017 bloom determined levels of the cyanotoxins, specifically microcystins, in excess of recreational contact limits at sites within the lower 20 km of the river while amplicon sequencing found these sites were dominated by . These results highlight the need to broaden our understanding of physical drivers of cyanobacterial blooms within the interface between riverine and lacustrine systems, particularly as such blooms are expected to become more prominent in response to a changing climate.
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http://dx.doi.org/10.1002/lno.11558DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7942401PMC
December 2020

Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data.

Sci Total Environ 2021 Jun 30;774:145462. Epub 2021 Jan 30.

Consolidated Safety Services Inc., Fairfax 22030, USA; National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring 20910, USA.

Widespread occurrence of cyanobacterial harmful algal blooms (CyanoHABs) and the associated health effects from potential cyanotoxin exposure has led to a need for systematic and frequent screening and monitoring of lakes that are used as recreational and drinking water sources. Remote sensing-based methods are often used for synoptic and frequent monitoring of CyanoHABs. In this study, one such algorithm - a sub-component of the Cyanobacteria Index called the CI, was validated for effectiveness in identifying lakes with toxin-producing blooms in 11 states across the contiguous United States over 11 bloom seasons (2005-2011, 2016-2019). A matchup data set was created using satellite data from MEdium Resolution Imaging Spectrometer (MERIS) and Ocean Land Colour Imager (OLCI), and nearshore, field-measured Microcystins (MCs) data as a proxy of CyanoHAB presence. While the satellite sensors cannot detect toxins, MCs are used as the indicator of health risk, and as a confirmation of cyanoHAB presence. MCs are also the most common laboratory measurement made by managers during CyanoHABs. Algorithm performance was evaluated by its ability to detect CyanoHAB 'Presence' or 'Absence', where the bloom is confirmed by the presence of the MCs. With same-day matchups, the overall accuracy of CyanoHAB detection was found to be 84% with precision and recall of 87 and 90% for bloom detection. Overall accuracy was expected to be between 77% and 87% (95% confidence) based on a bootstrapping simulation. These findings demonstrate that CI has utility for synoptic and routine monitoring of potentially toxic cyanoHABs in lakes across the United States.
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http://dx.doi.org/10.1016/j.scitotenv.2021.145462DOI Listing
June 2021

Less Agricultural Phosphorus Applied in 2019 Led to Less Dissolved Phosphorus Transported to Lake Erie.

Environ Sci Technol 2021 01 6;55(1):283-291. Epub 2020 Dec 6.

Purdue Libraries and School of Information Studies, Purdue University, West Lafayette, Indiana 47906, United States.

Extreme precipitation events affect water quantity and quality in various regions of the world. Heavy precipitation in 2019 resulted in a record high area of unplanted agricultural fields in the U.S. and especially in the Maumee River Watershed (MRW). March-July phosphorus (P) loads from the MRW drive harmful algal bloom (HAB) severity in Lake Erie; hence changes in management that influence P export can ultimately affect HAB severity. In this study, we found that the 2019 dissolved reactive P (DRP) load from March-July was 29% lower than predicted, while the particulate P (PP) load was similar to the predicted value. Furthermore, the reduced DRP load resulted in a less severe HAB than predicted based on discharge volume. The 29% reduction in DRP loss in the MRW occurred with a 62% reduction in applied P, emphasizing the strong influence of recently applied P and subsequent incidental P losses on watershed P loading. Other possible contributing factors to this reduced load include lower precipitation intensity, altered tillage practices, and effects of fallow soils, but more data is needed to assess their importance. We recommend conservation practices focusing on P application techniques and timing and improving resiliency against extreme precipitation events.
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http://dx.doi.org/10.1021/acs.est.0c03495DOI Listing
January 2021

Dynamics of an intense Alexandrium catenella red tide in the Gulf of Maine: satellite observations and numerical modeling.

Harmful Algae 2020 11 26;99:101927. Epub 2020 Oct 26.

Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC, 27695.

In July 2009, an unusually intense bloom of the toxic dinoflagellate Alexandrium catenella occurred in the Gulf of Maine. The bloom reached high concentrations (from hundreds of thousands to one million cells L) that discolored the water and exceeded normal bloom concentrations by a factor of 1000. Using Medium Resolution Imaging Spectrometer (MERIS) imagery processed to target chlorophyll concentrations (>2 µg L), patches of intense A. catenella concentration were identified that were consistent with the highly localized cell concentrations observed from ship surveys. The bloom patches were generally aligned with the edge of coastal waters with high-absorption. Dense bloom patches moved onshore in response to a downwelling event, persisted for approximately one week, then dispersed rapidly over a few days and did not reappear. Coupled physical-biological model simulations showed that wind forcing was an important factor in transporting cells onshore. Upward swimming behavior facilitated the horizontal cell aggregation, increasing the simulated maximum depth-integrated cell concentration by up to a factor of 40. Vertical convergence of cells, due to active swimming of A. catenella from the subsurface to the top layer, could explain the additional 25-fold intensification (25 × 40=1000-fold) needed to reach the bloom concentrations that discolored the water. A model simulation that considered upward swimming overestimated cell concentrations downstream of the intense aggregation. This discrepancy between model and observed concentrations suggested a loss of cells from the water column at a time that corresponded to the start of encystment. These results indicated that the joint effect of upward swimming, horizontal convergence, and wind-driven flow contributed to the red water event, which might have promoted the sexual reproduction event that preceded the encystment process.
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http://dx.doi.org/10.1016/j.hal.2020.101927DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680504PMC
November 2020

Atmospheric correction for satellite-derived bathymetry in the Caribbean waters: from a single image to multi-temporal approaches using Sentinel-2A/B.

Opt Express 2020 Apr;28(8):11742-11766

Different atmospheric correction (AC) procedures for Sentinel-2 satellites are evaluated for their effectiveness in retrieving consistent satellite-derived bathymetry (SDB) over two islands in the Caribbean (Buck and Culebra). The log-ratio method for SDB, which allows use of minimal calibration information from lidar surveys (25 points in this study), is applied to several Sentinel-2A/B scenes at 10 m spatial resolution. The overall performance during a one-year study period depends on the image quality and AC. Three AC processors were evaluated: ACOLITE Exponential model (EXP), ACOLITE Dark Spectrum Fitting model (DSF), and C2RCC model. ACOLITE EXP and ACOLITE DSF produce greater consistency and repeatability with accurate results in a scene-by-scene analysis (mean errors ∼1.1 m) for depths up to 23 m (limit of lidar surveys). In contrast, C2RCC produces lower accuracy and noisier results with generally higher (>50%) errors (mean errors ∼2.2 m), but it is able to retrieve depth for scenes in Buck Island that have moderately severe sunglint. Furthermore, we demonstrate that a multi-temporal compositing model for SDB mapping, using ACOLITE for the input scenes, could achieve overall median errors <1 m for depths ranging 0-23 m. The simple and effective compositing model can considerably enhance coastal SDB estimates with high reliability and no missing data, outperforming the traditional single image approaches and thus eliminating the need to evaluate individual scenes. The consistency in the output from the AC correction indicates the potential for automated application of the multi-scene compositing technique, which can apply the open and free Sentinel-2 data set for the benefit of operational and scientific investigations.
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http://dx.doi.org/10.1364/OE.390316DOI Listing
April 2020

Measurement of Cyanobacterial Bloom Magnitude using Satellite Remote Sensing.

Sci Rep 2019 12 4;9(1):18310. Epub 2019 Dec 4.

Consolidated Safety Services Inc., Fairfax, VA, 22030, USA.

Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatiotemporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio (USA) respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Sentinel-3 Ocean Land Color Imager (OLCI) data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.
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http://dx.doi.org/10.1038/s41598-019-54453-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892802PMC
December 2019

HABscope: A tool for use by citizen scientists to facilitate early warning of respiratory irritation caused by toxic blooms of Karenia brevis.

PLoS One 2019 20;14(6):e0218489. Epub 2019 Jun 20.

National Oceanic and Atmospheric Administration, National Ocean Service, Center for Coastal Fisheries and Habitat Research, Beaufort, North Carolina, United States of America.

Blooms of the toxic microalga Karenia brevis occur seasonally in Florida, Texas and other portions of the Gulf of Mexico. Brevetoxins produced during Karenia blooms can cause neurotoxic shellfish poisoning in humans, massive fish kills, and the death of marine mammals and birds. Brevetoxin-containing aerosols are an additional problem, having a severe impact on beachgoers, triggering coughing, eye and throat irritation in healthy individuals, and more serious respiratory distress in those with asthma or other breathing disorders. The blooms and associated aerosol impacts are patchy in nature, often affecting one beach but having no impact on an adjacent beach. To provide timely information to visitors about which beaches are low-risk, we developed HABscope; a low cost (~$400) microscope system that can be used in the field by citizen scientists with cell phones to enumerate K. brevis cell concentrations in the water along each beach. The HABscope system operates by capturing short videos of collected water samples and uploading them to a central server for rapid enumeration of K. brevis cells using calibrated recognition software. The HABscope has a detection threshold of about 100,000 cells, which is the point when respiratory risk becomes evident. Higher concentrations are reliably estimated up to 10 million cells L-1. When deployed by volunteer citizen scientists, the HABscope consistently distinguished low, medium, and high concentrations of cells in the water. The volunteers were able to collect data on most days during a severe bloom. This indicates that the HABscope can provide an effective capability to significantly increase the sampling coverage during Karenia brevis blooms.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218489PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586399PMC
February 2020

Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations.

J Great Lakes Res 2019 Jun;45(3):413-433

School of Geographic Sciences, Key Laboratory of Geographic Information Science, East China Normal University, Shanghai, China.

We analyzed 37 satellite reflectance algorithms and 321 variants for five satellites for estimating turbidity in a freshwater inland lake in Ohio using coincident real hyperspectral aircraft imagery converted to relative reflectance and dense coincident surface observations. This study is part of an effort to develop simple proxies for turbidity and algal blooms and to evaluate their performance and portability between satellite imagers for regional operational turbidity and algal bloom monitoring. Turbidity algorithms were then applied to synthetic satellite images and compared to in situ measurements of turbidity, chlorophyll-a (Chl-a), total suspended solids (TSS) and phycocyanin as an indicator of cyanobacterial/blue green algal (BGA) abundance. Several turbidity algorithms worked well with real Compact Airborne Spectrographic Imager (CASI) and synthetic WorldView-2, Sentinel-2 and Sentinel-3/MERIS/OLCI imagery. A simple red band algorithm for MODIS imagery and a new fluorescence line height algorithm for Landsat-8 imagery had limited performance with regard to turbidity estimation. Blue-Green Algae/Phycocyanin (BGA/PC) and Chl-a algorithms were the most widely applicable algorithms for turbidity estimation because strong co-variance of turbidity, TSS, Chl-a, and BGA made them mutual proxies in this experiment.
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http://dx.doi.org/10.1016/j.jglr.2018.09.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7433802PMC
June 2019

Science meets policy: A framework for determining impairment designation criteria for large waterbodies affected by cyanobacterial harmful algal blooms.

Harmful Algae 2019 01 10;81:59-64. Epub 2018 Dec 10.

F.T. Stone Laboratory, The Ohio State University, 878 Bayview Ave. P.O. Box 119, Put-In-Bay, OH, 43456, USA; Ohio Sea Grant College Program, The Ohio State University, 1314 Kinnear Rd., Research Area 100, Columbus, OH, 43212, USA.

Toxic cyanobacterial harmful algal blooms (cyanoHABs) are one of the most significant threats to the security of Earth's surface freshwaters. In the United States, the Federal Water Pollution Control Act of 1972 (i.e., the Clean Water Act) requires that states report any waterbody that fails to meet applicable water quality standards. The problem is that for fresh waters impacted by cyanoHABs, no scientifically-based framework exists for making this designation. This study describes the development of a data-based framework using the Ohio waters of western Lake Erie as an exemplar for large lakes impacted by cyanoHABs. To address this designation for Ohio's open waters, the Ohio Environmental Protection Agency (EPA) assembled a group of academic, state and federal scientists to develop a framework that would determine the criteria for Ohio EPA to consider in deciding on a recreation use impairment designation due to cyanoHAB presence. Typically, the metrics are derived from on-lake monitoring programs, but for large, dynamic lakes such as Lake Erie, using criteria based on discrete samples is problematic. However, significant advances in remote sensing allows for the estimation of cyanoHAB biomass of an entire lake. Through multiple years of validation, we developed a framework to determine lake-specific criteria for designating a waterbody as impaired by cyanoHABs on an annual basis. While the criteria reported in this manuscript are specific to Ohio's open waters, the framework used to determine them can be applied to any large lake where long-term monitoring data and satellite imagery are available.
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http://dx.doi.org/10.1016/j.hal.2018.11.016DOI Listing
January 2019

Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking source waters.

Ecol Indic 2017 Sep;80:84-95

National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring, MD, USA.

Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking source waters because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection, In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentine1-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs >1 hectare in area. Results from this study show that 5.6 % of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7 % of waterbodies were resolvable when a three by three pixel (3×3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3×3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organization's (WHO) high threshold for risk of 100,000 cells mL. The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1 %) and Grand Lake St. Marys, OH (83 %) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.
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http://dx.doi.org/10.1016/j.ecolind.2017.04.046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145495PMC
September 2017

Evaluating the portability of satellite derived chlorophyll-a algorithms for temperate inland lakes using airborne hyperspectral imagery and dense surface observations.

Harmful Algae 2018 06 15;76:35-46. Epub 2018 May 15.

22 Department of Physics and Geosciences, Texas A&M Kingsville, Kingsville, TX, 23 78363-8202, USA. Electronic address:

This study evaluated the performances of twenty-nine algorithms that use satellite-based spectral imager data to derive estimates of chlorophyll-a concentrations that, in turn, can be used as an indicator of the general status of algal cell densities and the potential for a harmful algal bloom (HAB). The performance assessment was based on making relative comparisons between two temperate inland lakes: Harsha Lake (7.99 km) in Southwest Ohio and Taylorsville Lake (11.88 km) in central Kentucky. Of interest was identifying algorithm-imager combinations that had high correlation with coincident chlorophyll-a surface observations for both lakes, as this suggests portability for regional HAB monitoring. The spectral data utilized to estimate surface water chlorophyll-a concentrations were derived from the airborne Compact Airborne Spectral Imager (CASI) 1500 hyperspectral imager, that was then used to derive synthetic versions of currently operational satellite-based imagers using spatial resampling and spectral binning. The synthetic data mimics the configurations of spectral imagers on current satellites in earth's orbit including, WorldView-2/3, Sentinel-2, Landsat-8, Moderate-resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS). High correlations were found between the direct measurement and the imagery-estimated chlorophyll-a concentrations at both lakes. The results determined that eleven out of the twenty-nine algorithms were considered portable, with r values greater than 0.5 for both lakes. Even though the two lakes are different in terms of background water quality, size and shape, with Taylorsville being generally less impaired, larger, but much narrower throughout, the results support the portability of utilizing a suite of certain algorithms across multiple sensors to detect potential algal blooms through the use of chlorophyll-a as a proxy. Furthermore, the strong performance of the Sentinel-2 algorithms is exceptionally promising, due to the recent launch of the second satellite in the constellation, which will provide higher temporal resolution for temperate inland water bodies. Additionally, scripts were written for the open-source statistical software R that automate much of the spectral data processing steps. This allows for the simultaneous consideration of numerous algorithms across multiple imagers over an expedited time frame for the near real-time monitoring required for detecting algal blooms and mitigating their adverse impacts.
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http://dx.doi.org/10.1016/j.hal.2018.05.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159815PMC
June 2018

Performance metrics for the assessment of satellite data products: an ocean color case study.

Opt Express 2018 Mar;26(6):7404-7422

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multi-metric and user-dependent approach that can be applied within science, modeling, and resource management communities.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5894891PMC
http://dx.doi.org/10.1364/OE.26.007404DOI Listing
March 2018

Mobile device application for monitoring cyanobacteria harmful algal blooms using Sentinel-3 satellite Ocean and Land Colour Instruments.

Environ Model Softw 2018 ;109:93-103

National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Athens, GA, 30605, USA.

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near realtime to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.
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http://dx.doi.org/10.1016/j.envsoft.2018.08.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781247PMC
January 2018

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing.

Harmful Algae 2017 07 14;67:144-152. Epub 2017 Jul 14.

Ocean Ecology Laboratory, NASA Goddard Space Flight Center, 8800 Greenbelt Rd., Greenbelt, MD 20771, USA. Electronic address:

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization's (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.
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http://dx.doi.org/10.1016/j.hal.2017.06.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6084444PMC
July 2017

Ecophysiological Examination of the Lake Erie Microcystis Bloom in 2014: Linkages between Biology and the Water Supply Shutdown of Toledo, OH.

Environ Sci Technol 2017 Jun 8;51(12):6745-6755. Epub 2017 Jun 8.

Department of Microbiology, University of Tennessee , Knoxville, Tennessee 37996, United States.

Annual cyanobacterial blooms dominated by Microcystis have occurred in western Lake Erie (U.S./Canada) during summer months since 1995. The production of toxins by bloom-forming cyanobacteria can lead to drinking water crises, such as the one experienced by the city of Toledo in August of 2014, when the city was rendered without drinking water for >2 days. It is important to understand the conditions and environmental cues that were driving this specific bloom to provide a scientific framework for management of future bloom events. To this end, samples were collected and metatranscriptomes generated coincident with the collection of environmental metrics for eight sites located in the western basin of Lake Erie, including a station proximal to the water intake for the city of Toledo. These data were used to generate a basin-wide ecophysiological fingerprint of Lake Erie Microcystis populations in August 2014 for comparison to previous bloom communities. Our observations and analyses indicate that, at the time of sample collection, Microcystis populations were under dual nitrogen (N) and phosphorus (P) stress, as genes involved in scavenging of these nutrients were being actively transcribed. Targeted analysis of urea transport and hydrolysis suggests a potentially important role for exogenous urea as a nitrogen source during the 2014 event. Finally, simulation data suggest a wind event caused microcystin-rich water from Maumee Bay to be transported east along the southern shoreline past the Toledo water intake. Coupled with a significant cyanophage infection, these results reveal that a combination of biological and environmental factors led to the disruption of the Toledo water supply. This scenario was not atypical of reoccurring Lake Erie blooms and thus may reoccur in the future.
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http://dx.doi.org/10.1021/acs.est.7b00856DOI Listing
June 2017

Global solutions to regional problems: Collecting global expertise to address the problem of harmful cyanobacterial blooms. A Lake Erie case study.

Harmful Algae 2016 04;54:223-238

Department of Microbiology, University of Tennessee, 1414 West Cumberland Avenue, Knoxville, TN, 37996-0845, USA.

In early August 2014, the municipality of Toledo, OH (USA) issued a 'do not drink' advisory on their water supply directly affecting over 400,000 residential customers and hundreds of businesses (Wilson, 2014). This order was attributable to levels of microcystin, a potent liver toxin, which rose to 2.5μgL in finished drinking water. The Toledo crisis afforded an opportunity to bring together scientists from around the world to share ideas regarding factors that contribute to bloom formation and toxigenicity, bloom and toxin detection as well as prevention and remediation of bloom events. These discussions took place at an NSF- and NOAA-sponsored workshop at Bowling Green State University on April 13 and 14, 2015. In all, more than 100 attendees from six countries and 15 US states gathered together to share their perspectives. The purpose of this review is to present the consensus summary of these issues that emerged from discussions at the Workshop. As additional reports in this special issue provide detailed reviews on many major CHAB species, this paper focuses on the general themes common to all blooms, such as bloom detection, modeling, nutrient loading, and strategies to reduce nutrients.
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http://dx.doi.org/10.1016/j.hal.2016.01.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5230759PMC
April 2016

Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria.

Harmful Algae 2016 04;54:160-173

Cooperative Institute for Limnology & Ecosystem Research (CILER), Ann Arbor, MI, USA.

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments - since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins - especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.
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http://dx.doi.org/10.1016/j.hal.2016.01.005DOI Listing
April 2016

Spatial and temporal patterns in the seasonal distribution of toxic cyanobacteria in Western Lake Erie from 2002-2014.

Toxins (Basel) 2015 May 12;7(5):1649-63. Epub 2015 May 12.

National Centers for Coastal Ocean Science, National Oceanic and Atmospheric Administration, 1305 East-West Highway, Silver Spring, MD 20910, USA.

Lake Erie, the world's tenth largest freshwater lake by area, has had recurring blooms of toxic cyanobacteria for the past two decades. These blooms pose potential health risks for recreation, and impact the treatment of drinking water. Understanding the timing and distribution of the blooms may aid in planning by local communities and resources managers. Satellite data provides a means of examining spatial patterns of the blooms. Data sets from MERIS (2002-2012) and MODIS (2012-2014) were analyzed to evaluate bloom patterns and frequencies. The blooms were identified using previously published algorithms to detect cyanobacteria (~25,000 cells mL-1), as well as a variation of these algorithms to account for the saturation of the MODIS ocean color bands. Images were binned into 10-day composites to reduce cloud and mixing artifacts. The 13 years of composites were used to determine frequency of presence of both detectable cyanobacteria and high risk (>100,000 cells mL-1) blooms. The bloom season according to the satellite observations falls within June 1 and October 31. Maps show the pattern of development and areas most commonly impacted during all years (with minor and severe blooms). Frequencies during years with just severe blooms (minor bloom years were not included in the analysis) were examined in the same fashion. With the annual forecasts of bloom severity, these frequency maps can provide public water suppliers and health departments with guidance on the timing of potential risk.
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http://dx.doi.org/10.3390/toxins7051649DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4448166PMC
May 2015

Categorizing the severity of paralytic shellfish poisoning outbreaks in the Gulf of Maine for forecasting and management.

Deep Sea Res 2 Top Stud Oceanogr 2014 May;103:277-287

New Hampshire Department of Environmental Services, Concord, NH 03302, USA.

Development of forecasting systems for harmful algal blooms (HABs) has been a long-standing research and management goal. Significant progress has been made in the Gulf of Maine, where seasonal bloom forecasts are now being issued annually using cyst abundance maps and a population dynamics model developed for that organism. Thus far, these forecasts have used terms such as "significant", "moderately large" or "moderate" to convey the extent of forecasted paralytic shellfish poisoning (PSP) outbreaks. In this study, historical shellfish harvesting closure data along the coast of the Gulf of Maine were used to derive a series of bloom severity levels that are analogous to those used to define major storms like hurricanes or tornados. Thirty-four years of PSP-related shellfish closure data for Maine, Massachusetts and New Hampshire were collected and mapped to depict the extent of coastline closure in each year. Due to fractal considerations, different methods were explored for measuring length of coastline closed. Ultimately, a simple procedure was developed using arbitrary straight-line segments to represent specific sections of the coastline. This method was consistently applied to each year's PSP toxicity closure map to calculate the total length of coastline closed. Maps were then clustered together statistically to yield distinct groups of years with similar characteristics. A series of categories or levels was defined ("Level 1: Limited", "Level 2: Moderate", and "Level 3: Extensive") each with an associated range of expected coastline closed, which can now be used instead of vague descriptors in future forecasts. This will provide scientifically consistent and simply defined information to the public as well as resource managers who make decisions on the basis of the forecasts.
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http://dx.doi.org/10.1016/j.dsr2.2013.03.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112480PMC
May 2014

Interannual variability of cyanobacterial blooms in Lake Erie.

PLoS One 2012 1;7(8):e42444. Epub 2012 Aug 1.

National Oceanic and Atmospheric Administration (NOAA), National Centers for Coastal Ocean Science, Silver Spring, Maryland, United States of America.

After a 20-year absence, severe cyanobacterial blooms have returned to Lake Erie in the last decade, in spite of negligible change in the annual load of total phosphorus (TP). Medium-spectral Resolution Imaging Spectrometer (MERIS) imagery was used to quantify intensity of the cyanobacterial bloom for each year from 2002 to 2011. The blooms peaked in August or later, yet correlate to discharge (Q) and TP loads only for March through June. The influence of the spring TP load appears to have started in the late 1990 s, after Dreissenid mussels colonized the lake, as hindcasts prior to 1998 are inconsistent with the observed blooms. The total spring Q or TP load appears sufficient to predict bloom magnitude, permitting a seasonal forecast prior to the start of the bloom.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042444PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409863PMC
February 2013

An approach to developing numeric water quality criteria for coastal waters using the SeaWiFS Satellite Data Record.

Environ Sci Technol 2012 Jan 5;46(2):916-22. Epub 2012 Jan 5.

U.S. EPA National Health and Environmental Effects Research Laboratory, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, Florida 32561, United States.

Human activities on land increase nutrient loads to coastal waters, which can increase phytoplankton production and biomass and associated ecological impacts. Numeric nutrient water quality standards are needed to protect coastal waters from eutrophication impacts. The Environmental Protection Agency determined that numeric nutrient criteria were necessary to protect designated uses of Florida's waters. The objective of this study was to evaluate a reference condition approach for developing numeric water quality criteria for coastal waters, using data from Florida. Florida's coastal waters have not been monitored comprehensively via field sampling to support numeric criteria development. However, satellite remote sensing had the potential to provide adequate data. Spatial and temporal measures of SeaWiFS OC4 chlorophyll-a (Chl(RS)-a, mg m(-3)) were resolved across Florida's coastal waters between 1997 and 2010 and compared with in situ measurements. Statistical distributions of Chl(RS)-a were evaluated to determine a quantitative reference baseline. A binomial approach was implemented to consider how new data could be assessed against the criteria. The proposed satellite remote sensing approach to derive numeric criteria may be generally applicable to other coastal waters.
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http://dx.doi.org/10.1021/es2014105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287117PMC
January 2012

Estimating cyanobacterial bloom transport by coupling remotely sensed imagery and a hydrodynamic model.

Ecol Appl 2011 Oct;21(7):2709-21

NOAA, Center for Coastal Monitoring and Assessment, 1305 East-West Highway, Silver Spring, Maryland 20910, USA.

The ability to forecast the transport of harmful cyanobacterial blooms in the Laurentian Great Lakes is beneficial to natural resource managers concerned with public health. This manuscript describes a method that improves the prediction of cyanobacterial bloom transport with the use of a preoperational hydrodynamic model and high temporal resolution satellite imagery. Two scenarios were examined from separate cyanobacterial blooms in western Lake Erie, USA. The first scenario modeled bloom position and extent over the span of 13 days. A geographic center, or centroid, was calculated and assigned to the bloom from observed satellite imagery. The bloom centroid was projected forward in time, and the projected position was compared to the final observed bloom centroid. Image pixels flagged as cyanobacterial bloom were compared between the initial image and the final image, and this was assumed as persistence. The second bloom scenario was modeled for a period of 12 days, and the results were framed in an ecological context in an effort to gain further understanding of cyanobacterial bloom dynamics. These modeling techniques can be incorporated into an operational forecasting system.
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http://dx.doi.org/10.1890/10-1454.1DOI Listing
October 2011

Adjustment of ocean color sensor calibration through multi-band statistics.

Opt Express 2010 Jan;18(2):401-12

NOAA National Ocean Service, Silver Spring, Maryland 20910, USA.

The band-by-band vicarious calibration of on-orbit satellite ocean color instruments, such as SeaWiFS and MODIS, using ground-based measurements has significant residual uncertainties. This paper applies spectral shape and population statistics to tune the calibration of the blue bands against each other to allow examination of the interband calibration and potentially provide an analysis of calibration trends. This adjustment does not require simultaneous matches of ground and satellite observations. The method demonstrates the spectral stability of the SeaWiFS calibration and identifies a drift in the MODIS instrument onboard Aqua that falls within its current calibration uncertainties.
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http://dx.doi.org/10.1364/OE.18.000401DOI Listing
January 2010

Skill assessment for an operational algal bloom forecast system.

J Mar Syst 2009 Feb;76(1-2):151-161

NOAA, National Ocean Service, 1305 East-West Highway, 9th floor, Silver Spring, MD 20910, USA.

An operational forecast system for harmful algal blooms (HABs) in southwest Florida is analyzed for forecasting skill. The HABs, caused by the toxic dinoflagellate, Karenia brevis, lead to shellfish toxicity and to respiratory irritation. In addition to predicting new blooms and their extent, HAB forecasts are made twice weekly during a bloom event, using a combination of satellite derived image products, wind predictions, and a rule-based model derived from previous observations and research. These forecasts include: identification, intensification, transport, extent, and impact; the latter being the most significant to the public. Identification involves identifying new blooms as HABs and is validated against an operational monitoring program involving water sampling. Intensification forecasts, which are much less frequently made, can only be evaluated with satellite data on mono-specific blooms. Extent and transport forecasts of HABs are also evaluated against the water samples. Due to the resolution of the forecasts and available validation data, skill cannot be resolved at scales finer than 30 km. Initially, respiratory irritation forecasts were analyzed using anecdotal information, the only available data, which had a bias toward major respiratory events leading to a forecast accuracy exceeding 90%. When a systematic program of twice-daily observations from lifeguards was implemented, the forecast could be meaningfully assessed. The results show that the forecasts identify the occurrence of respiratory events at all lifeguard beaches 70% of the time. However, a high rate (80%) of false positive forecasts occurred at any given beach. As the forecasts were made at half to whole county level, the resolution of the validation data was reduced to county level, reducing false positives to 22% (accuracy of 78%). The study indicates the importance of systematic sampling, even when using qualitative descriptors, the use of validation resolution to evaluate forecast capabilities, and the need to match forecast and validation resolutions.
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http://dx.doi.org/10.1016/j.jmarsys.2008.05.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2902173PMC
February 2009

Florida red tide and human health: a pilot beach conditions reporting system to minimize human exposure.

Sci Total Environ 2008 Aug 27;402(1):1-8. Epub 2008 May 27.

Environmental Health Program, Mote Marine Laboratory, 1600 Ken Thompson Parkway, Sarasota, FL 32436, United States.

With over 50% of the US population living in coastal counties, the ocean and coastal environments have substantial impacts on coastal communities. While many of the impacts are positive, such as tourism and recreation opportunities, there are also negative impacts, such as exposure to harmful algal blooms (HABs) and water borne pathogens. Recent advances in environmental monitoring and weather prediction may allow us to forecast these potential adverse effects and thus mitigate the negative impact from coastal environmental threats. One example of the need to mitigate adverse environmental impacts occurs on Florida's west coast, which experiences annual blooms, or periods of exuberant growth, of the toxic dinoflagellate, Karenia brevis. K. brevis produces a suite of potent neurotoxins called brevetoxins. Wind and wave action can break up the cells, releasing toxin that can then become part of the marine aerosol or sea spray. Brevetoxins in the aerosol cause respiratory irritation in people who inhale it. In addition, asthmatics who inhale the toxins report increase upper and lower airway symptoms and experience measurable changes in pulmonary function. Real-time reporting of the presence or absence of these toxic aerosols will allow asthmatics and local coastal residents to make informed decisions about their personal exposures, thus adding to their quality of life. A system to protect public health that combines information collected by an Integrated Ocean Observing System (IOOS) has been designed and implemented in Sarasota and Manatee Counties, Florida. This system is based on real-time reports from lifeguards at the eight public beaches. The lifeguards provide periodic subjective reports of the amount of dead fish on the beach, apparent level of respiratory irritation among beach-goers, water color, wind direction, surf condition, and the beach warning flag they are flying. A key component in the design of the observing system was an easy reporting pathway for the lifeguards to minimize the amount of time away from their primary duties. Specifically, we provided a Personal Digital Assistant for each of the eight beaches. The portable unit allows the lifeguards to report from their guard tower. The data are transferred via wireless Internet to a website hosted on the Mote Marine Laboratory Sarasota Operations of the Coastal Ocean Observation Laboratories (SO COOL) server. The system has proven to be robust and well received by the public. The system has reported variability from beach to beach and has provided vital information to users to minimize their exposure to toxic marine aerosols.
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http://dx.doi.org/10.1016/j.scitotenv.2008.03.032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2547342PMC
August 2008
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