Dry Weather Events Research Articles

The Impact of Combined Sewer Overflows on Pharmaceutical and Illicit Drug Levels in New York/New Jersey Waterways.

Pharmaceuticals and drugs of abuse are organic micropollutants of emerging concern in both surface and groundwater worldwide. These compounds are considered to be pseudo-persistent because of their continuous release into water systems. The presence of these compounds in the environment at any concentration poses a potential risk to nontarget organisms. The main sources of these contaminants are wastewater treatment plants (WWTPs) and combined sewer overflows (CSOs). The primary goal of our study was to identify and quantify a panel of 28 commonly prescribed pharmaceuticals (mood-altering drugs, cardiovascular drugs, antacids, antibiotics) and high-prevalence drugs of abuse (cocaine, amphetamines, opioids, cannabis) in river water samples collected from 19 locations in the Hudson and East rivers in New York City. The second goal was to investigate the possible source (WWTP or CSOs) of these micropollutants. Samples were collected weekly from May to August 2021 (n = 224) and May to August 2022 (n = 232), and placed at -20 °C until analysis by liquid chromatography-tandem mass spectrometry. The most frequently detected analytes in 2021 were metoprolol (n = 206, 92%), benzoylecgonine (n = 151, 67%), atenolol (n = 142, 63%), and methamphetamine (n = 118, 53%), and in 2022 the most frequently detected were methamphetamine (n = 194, 84%), atenolol (n = 177, 76%), metoprolol (n = 177, 76%), and 2-ethylene-1,5-dimethyl-3,3-diphenylpyrrolidine (n = 159, 69%). Measured concentrations ranged from the limit of detection (0.50-5.00 ng/L) to 103 ng/L. More drugs and higher concentrations were detected in water contaminated by Enterococci (>60 most probably number) and after rainfall, indicating the influence of CSOs. The presence of drugs in samples with little to no Enterococci and after dry weather events indicates that WWTPs contribute to the presence of these substances in the river, probably due to a low removal rate. Environ Toxicol Chem 2024;43:1592-1603. © 2024 SETAC.

A novel multi-objective scheduling model for grid-connected hydro-wind-PV-battery complementary system under extreme weather: A case study of Sichuan, China

Affected by extreme hot and dry weather events, the power supplied by hydropower is seriously insufficient in Sichuan province during the summer of 2022, causing severe power shortage and incalculable economic losses for the society. Therefore, a novel multi-objective scheduling model based on grid-connected hydro-wind-solar-battery energy resources combining flexible reserves is proposed to collaboratively guarantee the power supply reliability of both the contracted long-distance power transmission and the local electricity demand under extreme hot and dry weather. The intermittent nature of water inflow, wind speed, solar irradiance, and load is considered, and the multi-scenarios are produced using Latin Hypercube Sampling method. In this work, thermal plants are regarded as flexible reserves for easing the load shedding level of local load. The McCormick's Envelope method is implemented to linearize the power production model of the hydropower station. A multi-objective model, including minimum penalty cost of load shedding and carbon dioxide emission, is proposed to achieve the economic-environmental equilibrium of the power system. The proposed multi-objective optimal hybrid energy complementary strategy is transformed into a single objective model via ε-constraint method, and the fuzzy satisfying method is introduced to select the best compromise solution in the Pareto Front. The meteorological information of the summer of 2022 is collected to verify the effectiveness of this proposed mixed-integer-linear-programming energy complementary model based on a hydropower station on the Jinsha River in Sichuan province, China. Numerical experiments demonstrate that the proposed model is efficient and can enhance the reliability of real-world power systems under extreme hot and dry weather. A set of policy suggestions have been provided for Sichuan province to develop the power grid to face the extreme weather effect.

Recent Climate Change in the Lake Kyoga Basin, Uganda: An Analysis Using Short-Term and Long-Term Data with Standardized Precipitation and Anomaly Indexes

Climate change (CC) is now a global challenge due to uncertainties on the drivers and the multifaceted nature of its impacts. It impacts many sectors such as agriculture, water supply, and global economies through temperature and precipitation, affecting many livelihoods. Although there are global, regional, and national studies on CC, their application to determine local CC occurence mitigation and adaptation measures is not ideal. Therefore, this study aimed to determine climate change trends in Lake Kyoga Basin using standardized precipitation and anomaly indexes. Short-term (39 years, 1981–2020) and long-term (59 years, 1961–2020) monthly data from eight strategic meteorological stations were acquired from the Uganda National Meteorological Authority and supplemented with satellite and model reanalysis climate datasets. Change in precipitation was determined by SPI-6, while SAI determined change in temperature. The Mann–Kendall test was used to determine the trend significance. Whereas two (Serere and Lira) long-term data stations showed significant changes in precipitation, all the short-term data stations showed a significant increasing trend. Decadal relative rainfall anomaly increased from 85.6–105 in 1981–1990 to 92.0–120.9 in 2011–2020, while mean temperature anomaly increased from 0.2–0.6 °C to 1.0–1.6 °C in the same period. The frequency of severe wet weather events was more than for dry weather events in many stations, indicating an increase in precipitation. Maximum, mean, and minimum temperatures increased, with resultant warmer nights. The findings showed that the Lake Kyoga basin is experiencing climate change, with both temperature and rainfall increasing spatially and temporarily. Climate change affects agriculture, which is the main economic activity, and causes the destruction of infrastructure from floods, landslides, and mudslides. The results of this study are helpful in pointing out climate change-affected areas, and hence for designing mitigation and adaption strategies for local communities by policy and decision-makers from relevant stakeholders.

Human Fecal Contamination Corresponds to Changes in the Freshwater Bacterial Communities of a Large River Basin.

ABSTRACTMicrobial water quality is generally monitored by culturable fecal indicator bacteria (FIB), which are intended to signal human health risk due to fecal pollution. However, FIB have limited utility in most urbanized watersheds as they do not discriminate among fecal pollution sources, tend to make up a small fraction of the total microbial community, and do not inform on pollution impacts on the native ecosystem. To move beyond these limitations, we assessed entire bacterial communities and investigated how bacterial diversity relates to traditional ecological and human health-relevant water quality indicators throughout the Milwaukee River Basin. Samples were collected from 16 sites on 5 days during the summer, including both wet and dry weather events, and were processed by 16S rRNA gene amplicon sequencing. Historical water quality at each sampling location, as opposed to upstream land use, was associated significantly with bacterial community alpha diversity. Source partitioning the sequence data was important for determining water quality relationships. Sewage-associated bacterial sequences were detected in all samples, and the relative abundance of sewage sequences was strongly associated with the human Bacteroides fecal marker. From this relationship, we developed a preliminary threshold for human sewage pollution when using bacterial community sequence data. Certain abundant freshwater bacterial sequences were also associated with human fecal pollution, suggesting their possible utility in water quality monitoring. This study sheds light on how bacterial community analysis can be used to supplement current water quality monitoring techniques to better understand interactions between ecological water quality and human health indicators.IMPORTANCE Surface waters in highly developed mixed-use watersheds are frequently impacted by a wide variety of pollutants, leading to a range of impairments that must be monitored and remediated. With advancing technologies, microbial community sequencing may soon become a feasible method for routine evaluation of the ecological quality and human health risk of a water body. In this study, we partnered with a local citizen science organization to evaluate the utility of microbial community sequencing for identifying pollution sources and ecological impairments in a large mixed-use watershed. We show that changes in microbial community diversity and composition are indicative of both long-term ecological impairments and short-term fecal pollution impacts. By source partitioning the sequence data, we also estimate a threshold target for human sewage pollution, which may be useful as a starting point for future development of sequencing-based water quality monitoring techniques.

Data Mining Application in Assessment of Weather-Based Influent Scenarios for a WWTP: Getting the Most Out of Plant Historical Data

Since the introduction of environmental legislations and directives, the impact of combined sewer overflows (CSO) on receiving water bodies has become a priority concern in water and wastewater treatment industry. Time-consuming and expensive local sampling and monitoring campaigns are usually carried out to estimate the characteristic flow and pollutant concentrations of CSO water. This study focuses on estimating the frequency and duration of wet-weather events and their impacts on influent flow and wastewater characteristics of the largest Italian wastewater treatment plant (WWTP) located in Castiglione Torinese. Eight years (viz. 2009–2016) of historical data in addition to arithmetic mean daily precipitation rates (PI) of the plant catchment area are elaborated. Relationships between PI and volumetric influent flow rate (Qin), chemical oxygen demand (COD), ammonium (N-NH4), and total suspended solids (TSS) are investigated. A time series data mining (TSDM) method is implemented with MATLAB computing package for segmentation of time series by use of a sliding window algorithm (SWA) to partition the available records associated with wet and dry weather events. According to the TSDM results, a case-specific wet-weather definition is proposed for the Castiglione Torinese WWTP. Two significant weather-based influent scenarios are assessed by kernel density estimation. The results confirm that the method suggested within this study based on plant routinely collected data can be used for planning the emergency response and long-term preparedness for extreme climate conditions in a WWTP. Implementing the obtained results in dynamic process simulation models can improve the plant operational efficiency in managing the fluctuating loads.

Climate, CO<sub>2</sub> and human population impacts on global wildfire emissions

Abstract. Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.Here, we present a series of 124 simulations with the LPJ–GUESS–SIMFIRE global dynamic vegetation–wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations use Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models. These were combined with two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs) to assess the sensitivity of emissions to the effect of climate, CO2 and humans. In addition, two alternative parameterisations of the semi-empirical burned-area model were applied. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load and faster litter turnover in a warmer climate.

Biofilm resilience to desiccation in groundwater aquifers: A laboratory and field study

Groundwater is used as a precious resource for drinking water worldwide. Increasing anthropogenic activity is putting increasing pressure on groundwater resources. One impact of increased groundwater abstraction coupled with increasing dry weather events is the lowering of groundwater levels within aquifers. Biofilms within groundwater aquifers offer protection to the groundwater by removing contaminants entering the aquifer systems from land use activities. The study presented investigated the impact of desiccation events on the biofilms present in groundwater aquifers using field and laboratory experiments. In both field and laboratory experiments a reduction in enzyme activity (glucosidase, esterase and phosphatase) was seen during desiccation compared to wet controls. However, comparing all the data together no significant differences were seen between either wet or desiccated samples or between the start and end of the experiments. In both field and laboratory experiments enzyme activity recovered to start levels after return to wet conditions. The study shows that biofilms within groundwater systems are resilient and can withstand periods of desiccation (4months).

Stochastic Simulation Model for the Spatial Characterization of Lung Cancer Mortality Risk and Study of Environmental Factors

This paper presents a study in which the lung cancer risk in males was characterized based on a simulation model of mortality rates. Block sequential sim- ulation of mortality rates, measured in counties of different sizes, was implemented and applied to a normal grid of continental Portugal with high spatial resolution. The uncertainty in the mortality rate measurements, directly related to differences in the population size of each county, was integrated in a block direct sequential simulation through Poisson kriging of local means and variances. Three age groups were exam- ined: 50-59, 60-69, and 70-79 years. After the continuous geographic patterns of lung cancer risk were obtained, factors potentially associated with the main areas of risk were analyzed for southern Portugal. Thus, a defined class of land use and dry weather events, related to airborne particulate matter, were found to be associated with high-risk areas, resulting in high local spatial correlation patterns in all three age groups.

A new approach for the definition of extreme anomalous hot and dry weather events in Israel

Se analizan eventos anómalos extremos de tiempo cálido y seco en Israel basado en una nuevadefinición para tales eventos. Se proponen cuatro umbrales de condiciones extremas climáticas cálidasy secas. En este sentido, un día anómalo extremo caliente y seco se define cuando se cumplen doscondiciones: La puntuación estándar de la temperatura está por encima de uno de los cuatro umbralesy la puntuación estándar de la humedad relativa es inferior a uno de los cuatro umbrales. La conclusiónprincipal de este estudio es que las diferencias de temperatura y humedad relativa en diversas regionesgeográficas requieren una nueva definición para anomalía extrema de clima cálido y seco basado enuna base regional y no en uno único para todo el país a través del año. Mediante el establecimiento devarios grados de eventos extremos anómalos de clima cálido y seco y en base a la media mensual y ladesviación estándar de los valores de temperatura máxima y mínima y los valores de humedad relativapara cada región, se puede obtener una definición más precisa de tales eventos. Este enfoque puede serutilizado en todo el mundo y pueden servir para analizar posibles cambios climáticos.

Delivery and Frequency Distributions of Combined Wastewater Collection System Wet and Dry Weather Loads

Combined wastewater collection systems continue to serve as a common urban conveyance method in urban areas of Europe and older urban areas of the United States. This study uses combined wastewater collection system monitoring data from the urbanizing Liguori catchment and channel in Cosenza (Italy) to illustrate event-based delivery and distribution of conveyed pollutant indices. Motivated by recent European Union (EU) discharge control legislation, this study specifically differentiates the event-based delivery of these indices between dry and wet-weather flows. Although the relatively steady to diurnal-variable delivery phenomena in dry weather flows are known, transport limiting phenomena for wet-weather hydrology and mass delivery typically are not known for the same catchment. Limiting categories of transport for a pollutant phase are generated by variables such as flow volume and duration, stream power, hydrograph parameters, and previous dry hours (PDH). Transport limitations of wet and dry weather events from the 414-ha catchment were analyzed and characterized as limited by mass indices (first-order, first flush transport) or limited by flow (zero-order transport). Results indicated significant concentration differences between mass- and flow-limited events. Higher concentrations were associated with mass-limited events. Frequency distributions of flow, total suspended solids (TSS), chemical oxygen demand (COD), and five-day biochemical oxygen demand (BOD5) were consistently exponential for wet-weather and mass-limited events. In contrast, flow, TSS, and BOD5 concentrations were distributed normally for flow-limited events. Results indicated a reasonable linear relationship between discharged TSS, COD, and BOD5 (biochemical oxygen demand) for Liguori Channel discharges into the Crati River. Wet-weather event transport was predominately mass-limited for TSS, COD, and BOD5.

Characterizing the Quality of Effluent and Other Contributory Sources During Peak Wet Weather Events

This study evaluates the impacts of blending practices at municipal wastewater treatment plants on effluent and receiving water quality, and estimates public health risks associated with recreation in surface waters receiving blended flows. Field samples were collected at four municipal wastewater treatment plants for in-plant processes and receiving waters during wet weather blending, wet weather non-blending, and dry weather events. Laboratory analyses for Giardia, Cryptosporidium , viruses (adenovirus, enteric viruses, rotavirus, norovirus), pathogen indicator organisms (fecal coliform E. coli , enterococcus, and male specific coliphage), and other water quality parameters were performed on these samples. Field sample results for the East Bay Municipal Utility District's (EBMUD) Main Wastewater Treatment Plant were used to develop a hydrodynamic and water quality computer models to predict receiving water conditions and a quantitative microbial risk assessment (MRA) to evaluate increased risks of gastrointestinal and respiratory infections for people recreating in waters receiving blended flows. EBMUD field sampling results indicated that Giardia and adenovirus concentrations in plant final effluent increased during wet weather blending events in comparison to non-blending events, and so receiving water modeling was conducted for these organisms. T-test results indicated that the differences between blending and non-blending were not considered to be statistically significant for any of the pathogen and indicator organisms except Giardia cysts (enumeration). Additionally, TSS, cBOD5 and particle concentrations from final effluent grab samples also appeared higher during blending events, but no increase was observed in VOC levels during these periods, and no NPDES permit limits were exceeded. An estimate of the incremental annual number of infections associated with blending practices at EBMUD's wastewater treatment plant was developed based on two pathogens (adenovirus and Giardia spp.) and three exposure sites. Estimated individual risk per exposure event for people recreating in waters receiving blended flows were greater by about an order-of-magnitude (10x) at the EBMUD MWWTP Outfall location and less than an order-of-magnitude (10x) at three other exposure sites, than if these blended flows received full secondary biological treatment during wet weather conditions. Thus the relative increase of annualized risk appeared negligible, at less than one infection annually assuming 100 exposure events per day for 30 blending days per year. This title belongs to WERF Research Report Series . ISBN: 9781843392989 (Print) ISBN: 9781780403533 (eBook)

Fate and Transport Modeling of Potential Pathogens: The Contribution From Sediments1

Abstract: Escherichia coli was used as a bacterial tracer for the development, calibration, and validation of a watershed scale fate and transport model to be extended to a suite of reference pathogens (Cryptosporidium, Giardia, Campylobacter, E. coli O157:H7). E. coli densities in water and sediments from the Blackstone River Watershed, Massachusetts, were measured at three sites for a total of five wet weather events and three dry weather events covering three seasons. The confirmed E. coli strains were identified by ribotyping for tracking the sources of E. coli and for determining the association of downstream E. coli isolates with isolates from upstream sediments. A large number of downstream samples were associated with upstream sediment sources of E. coli. E. coli densities ranged from 71 to 6,401 MPN/100 ml in water samples and from 2 to 335 MPN/g in sediments. Pearson correlation analysis revealed significant correlations between E. coli and total coliforms in water (r = 0.777, p < 0.01) and sediments (r = 0.728, p < 0.01). In addition, E. coli concentrations in water were weakly correlated with sediment particle size and sediment concentrations (r = 0.298, p < 0.01). A hydrologic model, WATFLOOD/SPL9, was used to predict the temporal and spatial variation of E. coli in the Blackstone River. The rapid rise of stream E. coli densities was more accurately predicted by the model with the inclusion of sediment resuspension, thus demonstrating the importance of the process.

The effect of two mechanical beach grooming strategies on Escherichia coli density in beach sand at a southwestern Lake Michigan beach

The influence of indicator bacteria associated with beach sands on recreational water quality has become increasingly recognized. Constant wave action may serve as a transport mechanism for delivering bacterial organisms to surface waters resulting in an increased frequency of dry weather advisories. The ability to reduce the concentration of these organisms may serve to improve recreational water quality. To date, few researchers have explored anthropogenic factors affecting the content of Escherichia coli in beach sands. This study explored the influence of mechanical beach grooming on in situ populations of Escherichia coli at a southwestern Lake Michigan beach to determine if an alteration in current beach management practices would serve to reduce the number of dry weather advisories in this community. Preliminary studies conducted during 2001 demonstrated that professional grooming significantly increased Escherichia coli content in beach sands relative to non-groomed or hand raked plots (p < 0.001). This data also suggested that deeper grooming might reduce differences between groomed and non-groomed areas. Subsequently, two mechanical grooming techniques were compared at Racine, WI in 2002: groomed to a depth of 5 to 7 cm with leveling of beach sands and groomed to a depth of 7 to 10 cm without leveling. Escherichia coli content between treatments were significantly correlated (p < 0.009). The density of the bacterium in deeper groomed/unleveled sands was significantly lower in visibly moist or wet but not dry sands (p = 0.038). In 2003, the manner in which beach sands were maintained using the mechanical beach groomer was altered and a follow-up study conducted. A 30 percent reduction in the number of poor water quality advisories due to dry weather events was achieved as a result of these measures. These results demonstrate that mechanical beach grooming may affect Escherichia coli content in beach sands, a potential source of non-point pollution to recreational waters.