Department of Earth, Marine and Environmental Sciences, Institute of Marine Science, University of North Carolina at Chapel Hill, Morehead City, North Carolina, United States of America.
PLoS One. 2024 Apr 19;19(4):e0299254. doi: 10.1371/journal.pone.0299254. eCollection 2024.
Estuarine water quality is declining worldwide due to increased tourism, coastal development, and a changing climate. Although well-established methods are in place to monitor water quality, municipalities struggle to use the data to prioritize infrastructure for monitoring and repair and to determine sources of contamination when they occur. The objective of this study was to assess water quality and prioritize sources of contamination within Town Creek Estuary (TCE), Beaufort, North Carolina, by combining culture, molecular, and geographic information systems (GIS) data into a novel contamination source ranking system. Water samples were collected from TCE at ten locations on eight sampling dates in Fall 2021 (n = 80). Microbiological water quality was assessed using US Environmental Protection Agency (U.S. EPA) approved culture-based methods for fecal indicator bacteria (FIB), including analysis of total coliforms (TC), Escherichia coli (EC), and Enterococcus spp. (ENT). The quantitative microbial source tracking (qMST) human-associated fecal marker, HF183, was quantified using droplet digital PCR (ddPCR). This information was combined with environmental data and GIS information detailing proximal sewer, septic, and stormwater infrastructure to determine potential sources of fecal contamination in the estuary. Results indicated FIB concentrations were significantly and positively correlated with precipitation and increased throughout the estuary following rainfall events (p < 0.01). Sampling sites with FIB concentrations above the U.S. EPA threshold also had the highest percentages of aged, less durable piping materials. Using a novel ranking system combining concentrations of FIB, HF183, and sewer infrastructure data at each site, we found that the two sites nearest the most aged sewage infrastructure and stormwater outflows were found to have the highest levels of measurable fecal contamination. This case study supports the inclusion of both traditional water quality measurements and local infrastructure data to support the current need for municipalities to identify, prioritize, and remediate failing infrastructure.
由于旅游业、沿海开发和气候变化的影响，全球范围内的河口水质正在下降。尽管已经有完善的方法来监测水质，但市政当局在利用这些数据优先考虑监测和修复基础设施以及确定污染来源方面仍面临困难。本研究的目的是通过将培养物、分子和地理信息系统 (GIS) 数据结合到一个新的污染来源排名系统中，评估北卡罗来纳州博福特镇溪河口 (TCE) 的水质并确定污染来源的优先级。在 2021 年秋季的 8 个采样日的 10 个位置从 TCE 采集了 80 个水样。使用美国环保署 (EPA) 批准的基于培养的方法评估水质微生物指标，包括总大肠菌群 (TC)、大肠杆菌 (EC) 和肠球菌属 (ENT) 的分析。使用液滴数字 PCR (ddPCR) 定量微生物源追踪 (qMST) 人源粪便标记物 HF183 进行定量。将这些信息与环境数据和 GIS 信息相结合，详细说明附近的污水、化粪池和雨水基础设施，以确定河口中潜在的粪便污染来源。结果表明，FIB 浓度与降水呈显著正相关，并在雨后整个河口范围内增加 (p < 0.01)。FIB 浓度高于 EPA 阈值的采样点也具有最高比例的老化、耐用性较低的管道材料。使用一种新的排名系统，结合每个站点的 FIB、HF183 和污水基础设施数据的浓度，我们发现最靠近最古老污水基础设施和雨水出口的两个站点发现了最高水平的可测量粪便污染。这个案例研究支持将传统水质测量和当地基础设施数据相结合，以支持市政当局目前确定、优先考虑和修复失效基础设施的需求。
