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Using Multi-media Modeling to Investigate Conditions Leading to Harmful Algal Blooms (ITM 2018)
Citation:
Astitha, M., C. Nowakowski, P. Vahos, E. Cooter, AND C. Tang. Using Multi-media Modeling to Investigate Conditions Leading to Harmful Algal Blooms (ITM 2018). ITM 2018 - 36th International Technical Meeting on Air Pollution Modelling and its Application, Ottawa, CANADA, May 14 - 18, 2018.
Impact/Purpose:
According to EPA (2016), nutrient pollution is common in US lakes with 40% having excessive levels of total phosphorus and 35% having excessive levels of total nitrogen. In addition, a dramatic 18.2% decline in the percentage of oligotrophic lakes (<10 μg/L of total phosphorus) was found as an important difference in lake condition between 2007 and 2012. This study examines the impact of nutrient loadings on water quality in Lake Erie as a demonstration of using models to predict chlorophyll α concentrations.
Description:
Clean water for drinking and sanitary purposes is a precondition for human health and well-being and essential for ecosystem health and survival (WMO, 2013). Water quality is influenced by both non-point pollution from farming activities and point-source pollution from sewage treatment and industrial discharge as principal sources. For agriculture, the key pollutants are nutrients, pesticides, sediment and faecal microbes. According to the United States (US) Environmental Protection Agency (EPA; 2016), nutrient pollution is common in US lakes with 40% having excessive levels of total phosphorus and 35% having excessive levels of total nitrogen. In addition, a dramatic 18.2% decline in the percentage of oligotrophic lakes (<10 μg/L of total phosphorus) was found as an important difference in lake condition between 2007 and 2012. This study examines the impact of nitrogen deposition on water quality in Lake Erie as a demonstration of using models to predict chlorophyll α concentrations. We used linked and coupled physical models to examine relationships among environmental variables across multiple sources and pathways. Because these models link emission sources with meteorology and the pollutant concentrations found in the environment, they shed new light on the complex interactions of these chemicals and chemical mixtures. We used the broad range of variables available from these models, representing meteorology, hydrology, atmospheric processes, landscape characteristics, and agriculture management practices, to examine relationships with available dissolved oxygen and chlorophyll α concentrations measured in Lake Erie. We found that inorganic nitrogen (N) fertilizer applied to crops and atmospheric N deposition were the strongest nutrient loading predictors of dissolved oxygen and chlorophyll α concentrations measured in Lake Erie. Further, we were able to examine the relationships of oxidized and reduced forms of N deposition, and dry and wet N deposition. The results of this analysis will be presented at the conference.
