Storm runoff differentially influences the nutrient concentrations and microbial contamination at two distinct beaches in northern China

A lag bloom pattern of phytoplankton after freshwater input events revealed by daily samples during summer in Qinhuangdao coastal water, China

Phytoplankton blooms have become a global concern due to their negative impacts on public health, aquaculture, tourism, and the economic stability of coastal regions. Therefore, elucidating the shifts in phytoplankton community structure and abundance, as well as their environmental drivers, is crucial. However, existing studies often fail to capture the detailed dynamics of phytoplankton blooms and their environmental triggers due to low temporal observation resolution. In this study, high temporal resolution (daily) samples were collected over 43 days to investigate the influence of environmental factors on phytoplankton in Qinhuangdao in the summer. During the observation period, a total of 45 phytoplankton species were identified, comprising 26 Bacillariophyta species, 16 Dinophyta species, 2 Euglenophyta species, and 1 Chromophyta species. Interestingly, a lag bloom pattern of phytoplankton behind freshwater input was observed across day-to-day samples. Phytoplankton blooms typically lagged 1-3 days behind periods of decreased salinity and nutrient input, suggesting that freshwater influx provides the foundational materials and benefits for these blooms. Moreover, the phytoplankton blooms were triggered by six dominant species, i.e., Chaetoceros spp., Pseudo-nitzschia delicatissima, Skeletonema costatum, Protoperdinium spp., Leptocylindrus minimus, Pseudo-nitzschia pungens, and Thalassiosira spp. Consequently, the succession of phytoplankton showed a predominant genera shift in the following sequence: Nitzschia, Protoperdinium, and Prorocentrum - Skeletonema - Pseudo-nitzschia - Gymnodinium - Leptocylindrus. Besides that, a deterministic process dominated phytoplankton community assembly across time series, and DIP is a key factor in shifting the phytoplankton community structures in this area. In summary, our study offers high-resolution observations on the succession of phytoplankton communities and sheds light on the complex and differentiated responses of phytoplankton to environmental factors. These findings enhance our understanding of the dynamics of phytoplankton blooms and their environmental drivers, which is essential for the effective management and mitigation of their adverse impacts.

Fecal bacteria contamination in the Adriatic Sea: Investigating environmental factors and modeling to manage recreational coastal waters

This study is based on assessing fecal indicator bacteria contamination along meteorological, hydrological and physical-chemical variables after high rainy events during the summer period. The study focused on four different coastal sites in the western and eastern Adriatic coast characterized by various geomorphological and hydrological features, levels of urbanization and anthropogenic pressures, with the aim of finding appropriate and effective solutions to ensure the safety and sustainability of tourism and public health. Detailed in-situ survey revealed a wide range of fecal indicator bacterial (FIB) across the different river mouths with concentrations of E. coli ranging from 165 to 6700 CFU 100 mL-1. It was found that nitrogen compounds track microbial load and acted as tracers for fecal contaminants. Further, a modelling tool was also used to analyze the spatial and temporal distribution of fecal pollution at these coastal sites. The integrated monitoring through high frequent survey in river waters and modeling framework allowed for the estimation of fecal indicator bacterial load at the river mouth and examination of fecal pollutant dispersion in recreational waters, considering different scenarios of fecal dispersion along the coast. This study formed the basis of a robust decision support system aimed at improving the management of recreational areas and ensuring the protection of water bodies through efficient management of bathing areas.

Predictive modeling of microbiological seawater quality in karst region using cascade model

This paper presents an in-depth analysis of seawater quality measurements during the bathing seasons from year 2009 to 2020 in the city of Rijeka, Croatia. Due to rare occurrences of measurements with less than excellent water quality, considered dataset is deeply imbalanced. Additionally, it incorporates measurements under the influence of submerged groundwater discharges (SGD), which were observed in some bathing locations. These discharges were previously thought to dry up during the summer season and are now suspected to be one of the causes of increased Escherichia coli values. Consequently, and in view of the fact that the accuracy of prediction models can be significantly influenced by temporal and spatial variation of the input data, a novel cascade prediction modeling strategy was proposed. It consists of a sequence of prediction models which tend to identify general environmental conditions which confidently lead to excellent bathing water quality. The proposed model uses environmental features which can rather easily be estimated or obtained from the weather forecast. The model was trained on a highly biased dataset, consisting of data from locations with and without SGD influence, and for the time period spanning extremely dry and warm seasons, extremely wet seasons, as well as normal seasons. To simulate realistic application, the model was tested using temporal and spatial stratification of data. The cascade strategy was shown to be a good approach for reliably detecting environmental parameters which produce excellent water quality. Proposed model is designed as a filter method, where instances classified as less-than-excellent water quality require further analysis. The cascade model provides great flexibility as it can be customized to the particular needs of the investigated area and dataset specifics.

Solid-liquid partitioning and variation of palladium in rainfall runoff

Palladium (Pd) is most widely used in the production of automotive catalytic converters that serve to reduce toxic emissions from motor vehicles. The aim of this study was to analyze the solid-liquid partitioning and dynamic variation of Pd in rainfall runoff. The results showed that the partition coefficients (K) of Pd ranged from 0.05 to 8.55. Transport via suspended particulate matter as the main carrier was the main form of Pd migration in rainfall runoff. Pd phase distribution exhibited complex dynamic variations. The variation in Pd could be roughly divided into three categories, namely the W, M and N types, and the semi-U type was also observed. Rainfall characteristics and microenvironmental factors had a profound effect on Pd phase distribution in the first flush runoff. Under the influence of multifactor coupling, the impact of water quality parameters such as pH, Eh and Cl^- on Pd partitioning was significantly weakened.

Daily Samples Revealing Shift in Phytoplankton Community and Its Environmental Drivers during Summer in Qinhuangdao Coastal Area, China

Rapid urbanization and economic development in coastal regions have significantly increased coastal nutrient pollution and remarkably changed the phytoplankton community and developed some species into bloom, resulting in large economic losses and serious threats to public health. Therefore, it is indispensable to reveal the shift in the phytoplankton community and phytoplankton abundance, and phytoplankton’s environmental drivers. However, previous studies could not present the details of the environmental drivers of phytoplankton due to samples being collected with low temporal resolution. Here, high-temporal-resolution (daily) samples were collected to investigate the influence of environmental factors on phytoplankton in Qinhuangdao for 44 days. Phytoplankton communities showed a rapid succession, with predominant genera changing in the order Skeletonema–Chaetoceros–Skeletonema–Thalassiosira. Similarly, Thalassiosira pacifica, Skeletonema costatum, Chaetoceros tortissimus, and Chattonella marina were identified as the dominant species and were abundant in 0–1.27 × 107 cells·L−1, 0–9.34 × 106 cells·L−1, 0–6.49 × 106 cells·L−1, and 0–3.64 × 106 cells·L−1, respectively. Moreover, inflows facilitate the rapid succession of the phytoplankton community. Dissolved inorganic phosphorus (DIP) was found to remarkably influence the succession of phytoplankton communities and the bloom of the top three dominant species, i.e., Thalassiosira pacifica, Skeletonema costatum, and Chaetoceros tortissimus. Overall, our results provide high-temporal-resolution observations of phytoplankton community succession and reveal its environmental drivers. This contributes to our current understanding of the occurrence of algae blooms and supports the development of management strategies to control algae bloom in coastal waters.

Suspended particles are hotspots for pathogen-related bacteria and ARGs in coastal beach waters of northern China

Marine suspended particles are unique micro-habitats for diverse microbes and also hotspots of microbially metabolic activities. However, the association of bacterial pathogens, especially those carrying antibiotic resistance genes (ARGs), with these particles remain largely unknown in coastal habitats. This study investigated the distribution of pathogen-related bacteria and ARGs in particle-associated (PA) and free-living (FL) fractions of samples collected at three coastal beaches using NextGen sequencing and qPCR. Suspended particles were found to harbor significantly higher abundances of bacteria of pathogen-related genera and ARGs than their counterparts. Functional analysis of microbial community suggested that antibiotic biosynthetic pathways were also more abundant among PA microbiome comparing to FL microbial community, which further facilitated the spread of ARGs. Additionally, 13 pathogen-related genera co-occurred with ARG in PA fraction while only 2 pathogen-related genera co-occurred with ARGs in FL fraction. Overall, our research revealed suspended particles harbored more abundant pathogen-related genera and ARGs comparing with surrounding waters. Thus, suspended particles are hotspots for pathogen-related genera and ARGs and may pose a greater threat to human health in coastal beach.

Assessment of Spatio-Temporal Variability of Faecal Pollution along Coastal Waters during and after Rainfall Events

More than 80% of wastewaters are discharged into rivers or seas, with a negative impact on water quality along the coast due to the presence of potential pathogens of faecal origin. Escherichia coli and enterococci are important indicators to assess, monitor, and predict microbial water quality in natural ecosystems. During rainfall events, the amount of wastewater delivered to rivers and coastal systems is increased dramatically. This study implements measures capable of monitoring the pathways of wastewater discharge to rivers and the transport of faecal bacteria to the coastal area during and following extreme rainfall events. Spatio-temporal variability of faecal microorganisms and their relationship with environmental variables and sewage outflow in an area located in the western Adriatic coast (Fano, Italy) was monitored. The daily monitoring during the rainy events was carried out for two summer seasons, for a total of five sampling periods. These results highlight that faecal microbial contaminations were related to rainy events with a high flow of wastewater, with recovery times for the microbiological indicators varying between 24 and 72 h and influenced by a dynamic dispersion. The positive correlation between ammonium and faecal bacteria at the Arzilla River and the consequences in seawater can provide a theoretical basis for controlling ammonium levels in rivers as a proxy to monitor the potential risk of bathing waters pathogen pollution.

Evaluation of E. coli in sediment for assessing irrigation water quality using machine learning

Fresh produce irrigated with contaminated water poses a substantial risk to human health. This study evaluated the impact of incorporating sediment information on improving the performance of machine learning models to quantify E. coli level in irrigation water. Field samples were collected from irrigation canals in the Southwest U.S., for which meteorological, chemical, and physical water quality variables as well as three additional flow and sediment properties: the concentration of E. coli in sediment, sediment median size, and bed shear stress. Water quality was classified based on E. coli concentration exceeding two standard levels: 1 E. coli and 126 E. coli colony forming units (CFU) per 100 ml of irrigation water. Two series of features, including (FIS) and excluding (FES) sediment features, were selected using multi-variant filter feature selection. The correlation analysis revealed the inclusion of sediment features improves the correlation with the target standards for E. coli compared to the models excluding these features. Support vector machine, logistic regression, and ridge classifier were tested in this study. The support vector machine model performed the best for both targeted standards. Besides, incorporating sediment features improved all models' performance. Therefore, the concentration of E. coli in sediment and bed shear stress are major factors influencing E. coli concentration in irrigation water.

Water quality integrated system: A strategic approach to improve bathing water management

In the Adriatic Sea, massive rainfall events are causing flooding of rivers and streams, with severe consequences on the environment. The consequent bacterial contamination of bathing water poses public health risks besides damaging tourism and the economy. This study was conducted in the framework of WATERCARE, an EU Interreg Italy-Croatia Project, which aims at reducing the impact of microbial contamination on Adriatic bathing water due to heavy rainfall events drained in the local sewage network and; enhancing the quality of local waters; and providing support for the decision-making processes regarding the management of bathing water in line with EU regulations. The study involved the development of an innovative water quality integrated system that helps meet these objectives. It consists of four components: a real time hydro-meteorological monitoring system; an autosampler to collect freshwater samples during and after significant rainfall events; a forecast system to simulate the dispersion of pollutants in seawater; and a real-time alert system that can predict the potential ecological risk from the microbial contamination of seawater. The system was developed and tested at a pilot site (Fano, Italy). These preliminary results will be used to develop guidelines for urban wastewater and coastal system quality assessments to contribute to develop policy actions and final governance decisions.

Loading, transport, and treatment of emerging chemical and biological contaminants of concern in stormwater

Stormwater is a largely uncontrolled source of pollution in rural and urban environments across the United States. Concern regarding the growing diversity and abundance of pollutants in stormwater, as well as their impacts on water quality, has grown significantly over the past several decades. In addition to conventional contaminants like nutrients and heavy metals, stormwater is a well-documented source of many contaminants of emerging concern, which can be toxic to both aquatic and terrestrial organisms and remain a barrier to maintaining high quality water resources. Chemical pollutants like pharmaceuticals and personal care products, industrial pollutants such as per- and polyfluoroalkyl substances, and tire wear particles in stormwater are of great concern due to their toxic, genotoxic, mutagenic and carcinogenic properties. Emerging microbial contaminants such as pathogens and antibiotic resistance genes also represent significant threats to environmental water quality and human health. Knowledge regarding the transport, behavior, and the remediation capacity of these pollutants in runoff is key for addressing these pollutants in situ and minimizing ecosystem perturbations. To this end, this review paper will analyze current understanding of these contaminants in stormwater runoff in terms of their transport, behavior, and bioremediation potential.

Modelling the Quality of Bathing Waters in the Adriatic Sea

The aim of this study is to develop a relocatable modelling system able to describe the microbial contamination that affects the quality of coastal bathing waters. Pollution events are mainly triggered by urban sewer outflows during massive rainy events, with relevant negative consequences on the marine environment and tourism and related activities of coastal towns. A finite element hydrodynamic model was applied to five study areas in the Adriatic Sea, which differ for urban, oceanographic and morphological conditions. With the help of transport-diffusion and microbial decay modules, the distribution of Escherichia coli was investigated during significant events. The numerical investigation was supported by detailed in situ observational datasets. The model results were evaluated against water level, sea temperature, salinity and E. coli concentrations acquired in situ, demonstrating the capacity of the modelling suite in simulating the circulation in the coastal areas of the Adriatic Sea, as well as several main transport and diffusion dynamics, such as riverine and polluted waters dispersion. Moreover, the results of the simulations were used to perform a comparative analysis among the different study sites, demonstrating that dilution and mixing, mostly induced by the tidal action, had a stronger effect on bacteria reduction with respect to microbial decay. Stratification and estuarine dynamics also play an important role in governing microbial concentration. The modelling suite can be used as a beach management tool for improving protection of public health, as required by the EU Bathing Water Directive.

Response of palladium in receiving water bodies to rainfall-runoff

Palladium (Pd) is widely used in automotive catalytic converters to reduce toxic gas emissions. The input of Pd in the rainfall-runoff is an important contributing factor to the accumulation of Pd in receiving water bodies. In this study, the Meishe River in Haikou, Hainan Province, China, was used as the research area, and palladium (Pd) was selected as the target pollutant. This study explored the response of Pd in the receiving water body to rainfall-runoff and to analyze the influencing factors. The results showed that the dissolved Pd concentration in the receiving water body had a corresponding relationship with that in rainfall-runoff. The response of suspended Pd in the receiving water body to rainfall-runoff was closely related to the location of the drainage outlet. Compared with that of suspended Pd, the response of dissolved Pd in the receiving water body to that in the rainfall-runoff was more obvious. Seven meters downstream from the outfall was the most sensitive response distance of dissolved Pd in receiving water bodies to rainfall-runoff, and the response time was approximately 0-10 min. The suspended Pd at 3 m downstream from the outfall also had a certain response to the rainfall-runoff, and the response time was approximately 15-25 min. The response time of the suspended Pd in the receiving water body depended largely on the first flush ability of the runoff. There was a moderately positive correlation between the dissolved Pd and Cl^- in the receiving water body (r = 0.687; p < 0.05). The effects of pH, Eh, and total suspended solids (TSS) on suspended Pd were reduced in the response process of the receiving water body. The synergistic effect of multiple factors increased the uncertainty of the Pd response.

Response of prokaryotic communities to extreme precipitation events in an urban coastal lagoon: A case study of Yundang lagoon, China

Increasing extreme precipitation events (EPEs) can induce biogeochemical disturbances in the coastal lagoon ecosystems. Very little is known about the response of prokaryotic communities to such influences, which are the key components mediating the biogeochemical cycling in lagoons. Here 16S rRNA gene amplicon sequencing and high-through quantitative PCR (HT-qPCR) were employed to investigate the distribution of prokaryotic communities and fecal indicator genes in the surface waters of Yundang lagoon, Xiamen, China during EPEs, respectively. Prokaryotic communities from rainwaters, influents (IFs) and effluents (EFs) from a nearby wastewater treatment plant were also characterised. The results indicated a significant variation in the composition of lagoon prokaryotic communities compared with rainwaters, IFs and EFs. Multivariate and phylogenetic signal analyses revealed that environmental filtering, mainly controlled by salinity, was the major ecological process responsible for the temporal succession of lagoon prokaryotic communities during EPEs. Moreover, the pollution indicator taxa (based on amplicon sequencing) and fecal indicator genes (based on HT-qPCR) demonstrated that EPEs may induce sewage overflows and fecal pollution (mainly from humans and dogs), resulting in an increase in the relative abundance of pollution indicator taxa and genes in Yundang lagoon. Network analysis illustrated that the number of network edges and keystone species decreased along the sampling times, implying that EPEs-induced disturbances may affect prokaryotic species associations. Taken together, this study provides an enhanced understanding of the responses of lagoon prokaryotic communities to EPEs-induced disturbances.