The presence of per- and polyfluoroalkyl substances (PFAS) in U.S. drinking water has recently garnered significant attention from the media, federal government, and public health professionals. While concerns for PFAS exposure continue to mount, the general public’s awareness and knowledge of the contaminant has remained unknown. This exploratory study sought to fill this data gap by administering a nationwide survey in which the awareness of PFAS and community contamination, awareness of PFAS containing products and intentions to change product use, and awareness and concern about PFAS in drinking water were assessed. The results indicated that almost half the respondents had never heard of PFAS and do not know what it is (45.1%). Additionally, 31.6% responded that they had heard of PFAS but do not know what it is. A large portion of respondents (97.4%) also responded that they did not believe their drinking water had been impacted by PFAS. Demographic association did not influence knowledge of PFAS or levels of concern with PFAS in drinking water. The strongest predictor of PFAS awareness was awareness due to known community exposure. The respondents aware of community exposure were more likely to have knowledge of PFAS sources, change their use of items with potential PFAS contamination, and answer that their drinking water sources were also contaminated with PFAS. Based on the received responses, PFAS information and health risks need to be better communicated to the public to help increase awareness. These efforts should also be coordinated between government agencies, utilities, the research community, and other responsible entities to bolster their effectiveness.

Introduction: Best management practices (BMPs) are important tools for mitigating the impact of non-point source pollutants on water quality. Drivers of the high variance observed in BMP performance field tests are not well documented and present challenges for planning BMP construction and forecasting water quality improvements.Methods: We conducted a systematic review of published nonpoint source water quality BMP studies conducted in the United States and used a meta-analysis approach to describe variance in pollutant removal performance. We used meta-regression to explore how much BMP pollutant removal process, influent pollutant concentration, and aridity effected BMP performance.Results: Despite high variance, we found the BMPs on average were effective at reducing fecal indicator bacteria (FIB), total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) concentrations. We found that influent concentration and interaction effect between the BMP pollutant removal process and aridity explained a substantial amount of variance in BMP performance in FIB removal. Influent concentration explained a small amount of variability in BMP removal of TP and orthophosphate (PO₄). We did not find evidence that any of our chosen variables moderated BMP performance in nitrogen or TSS removal. Through our systematic review, we found inadequate spatial representation of BMP studies to capture the underlying variability in climate, soil, and other conditions that could impact BMP performance.

Evaluating estuary water quality responses to reductions (or increases) in nutrient loading attributed to on the ground management actions can be challenging due to the strong influence of environmental drivers on nutrient loads and non-linear relationships. This study applied generalized additive models to calculate watershed nutrient loads and assess responses in estuary water quality to seasonally-adjusted freshwater inflow and flow-adjusted nutrient loads in Lavaca Bay, Texas. Lavaca Bay is a secondary embayment on the Texas coast displaying early potential for eutrophication and water quality degradation. Use of flow-adjusted nutrient loads allowed the study to evaluate the response in water quality to changes in nutrient loads driven by anthropogenic sources. Cross-validation indicated that, despite data constraints, semiparametric models performed well at nutrient load prediction. Based on these models, delivered annual nutrient loads varied substantially from year to year. In contrast, minimal changes in flow-normalized loads indicate that nutrient loadings were driven by natural variation in precipitation and runoff as opposed to changes in management of nonpoint sources. Models indicated no evidence of long-term changes in dissolved oxygen or chlorophyll-awithin Lavaca Bay. However, site specific long-term increases in both organic and inorganic nitrogen are concerning for their potential to fuel eutrophication. Further analysis found freshwater inflow had strong influences on nutrient and chlorophyll-aconcentrations but there was no evidence that changes in watershed nutrient loading explained additional variation in dissolved oxygen and limited evidence that watershed nutrient loadings explained chlorophyll-a concentrations. In addition to providing a baseline assessment of watershed nutrient loading and water quality responses in the Lavaca Bay watershed, this study provides methodological support for the use of semiparametric models in load regression models and estuary assessments.