Assessment of the treatment efficiency of an urban stormwater pond and its impact on the natural downstream watercourse

Evaluation of pollutant removal efficiency of urban stormwater wet ponds and the application of machine learning algorithms

Wet ponds have been extensively used for controlling stormwater pollutants, such as sediment and nutrients, in urban watersheds. The removal of pollutants relies on a combination of physical, chemical, and biological processes. It is crucial to assess the performance of wet ponds in terms of removal efficiency and develop an effective modeling scheme for removal efficiency prediction to optimize water quality management. To achieve this, a two-year field program was conducted at two wet ponds in Calgary, Alberta, Canada to evaluate the wet ponds' performance. Additionally, machine learning (ML) algorithms have been shown to provide promising predictions in datasets with intricate interactions between variables. In this study, the generalized linear model (GLM), partial least squares (PLS) regression, support vector machine (SVM), random forest (RF), and K-nearest neighbors (KNN) were applied to predict the outflow concentrations of three key pollutants: total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Generally, the concentrations of inflow pollutants in the two study ponds are highly variable, and a wide range of removal efficiencies are observed. The results indicate that the concentrations of TSS, TN, and TP decrease significantly from the inlet to outlet of the ponds. Meanwhile, inflow concentration, rainfall characteristics, and wind are important indicators of pond removal efficiency. In addition, ML algorithms can be an effective approach for predicting outflow water quality: PLS, GLM, and SVM have shown strong potential to capture the dynamic interactions in wet ponds and predict the outflow concentration. This study highlights the complexity of pollutant removal dynamics in wet ponds and demonstrates the potential of data-driven outflow water quality prediction.

Using fluorescence index (FI) of dissolved organic matter (DOM) to identify non-point source pollution: The difference in FI between soil extracts and wastewater reveals the principle

Traceability and quantification of agricultural non-point source pollution are of great significance to water pollution management in watersheds. In this study, fluorescence components and indices of dissolved organic matter (DOM) in the river, wastewater and soil extracts from different land use types were analyzed to screen indicators that can identify non-point source pollution in 15 independent small watersheds located at the southern Qinling piedmont (China). The results showed that DOM fluorescence components in soil extracts among different land uses didn't have significant differences. The values of humification index (HIX) did not vary obviously between soil extracts and wastewater, with the mean values ranging from 3.4 to 3.9. However, the average value of fluorescence index (FI) of effluent wastewater was about 2.1 and did not change significantly through treatment. The FI values of soil extracts were generally between 1.5 and 1.7. The FI values in most river waters were just between the FI values of wastewater and soil extracts. This phenomenon indicated that FI could be used as an indicator to distinguish point source and non-point source pollution. Besides, the correlation analysis showed a significant positive relationship between the non-point source pollution calculated by FI and δ¹⁵N. The relationship was different in January and July, but further confirmed the reliability of using FI to quantify non-point source pollution. This study demonstrated the feasibility of using FI to identify non-point source pollution. When combined with handheld fluorescence spectrometers and unmanned aerial vehicle-mounted fluorescence spectrometers, this method may be adopted more widely.

Distribution of heavy metals influenced by pumped storage hydropower in abandoned mines: Leaching test and modelling simulation

Renewable energy generation varies frequently, making it difficult to match electricity demand. Pumped storage hydropower plants can alleviate this problem by reducing the unevenness of renewable energy generation. It is a new exploration of energy storage methods to construct pumped storage hydropower plants by using underground goaf of abandoned mines and mining subsidence water area. However, the construction of lower reservoirs using underground goaf areas of abandoned mines can lead to potential heavy metal pollution. To assess the impact of using abandoned mines for pumped storage hydropower on the downstream surface water environment, this work first analyzed the release characteristics of heavy metals from underground goaf and surface dump through field sampling and leaching tests, then constructed a water-environment model of the downstream surface water based on the experimental results and water environment theory, and finally simulated and analyzed the impact of underground pollutants pumped to the surface on downstream surface water-quality in typical hydrological years. The maximum error between the simulated values and measured values of the hydrodynamic model was 0.1, and the overall error was within a reasonable range (±0.2 m). The comparison between simulated values and measured values of heavy metal concentration in water quality model showed RMSE values ranged from 0.003 to 0.81, with an average of 0.4; the SI ranged from 0.84 to 0.95, with an average of 0.89. During the simulation of low, normal, and high flow years, pollution downstream was concentrated near the drainage outlet, and the underground pollutants pumped to the surface influenced the concentration of heavy metals there. After a period of drainage, the concentration of heavy metals decreased. Drainage volume was an important factor affecting the concentration of heavy metals downstream surface water. These results prove that the water environment model established based on MIKE21 is reliable and can provide guidance for the simulation and control of heavy metal pollution in the utilization of abandoned mines for pumped storage hydropower. This work provides a reproducible idea and method to assess the impact of using abandoned mines and mining subsidence water area for pumped storage hydropower on downstream surface water and ensure the safety of the ecological environment.

Preliminary Model-Based Evaluation of Water Conservation Strategies in a Semi-Arid Urban Zone

The U.S. Environmental Protection Agency stormwater management model was applied to a semi-arid urban micro watershed. The sub-catchment’s current features were modeled as scenario A, while the insertion of a set of LID technologies (rain barrels, bioretention cells, permeable pavement, and infiltration trenches) was represented as scenario B. A third scenario (C), considering only the most feasible LID technologies, was also modeled. All the scenarios were evaluated under two representative storm events (30 and 9 mm in two consecutive days, and 39 mm of rainfall in one day) occurred during the sampling performed in this study. Water quality was also simulated for a 30-mm storm event and compared against field assessment results after a real 30-mm storm event. Through the model, the inefficiency of current evacuation methods after 30- and 39-mm storm events was demonstrated. Simulation of scenario B showed that LID technologies could satisfactorily diminish peak flows generated by the selected storm events as well as runoff-conveyed pollution, while the realistic scenario allowed a lower but satisfactory hydrological performance and almost the same runoff quality than scenario B. This preliminary study could contribute to spread awareness about the benefits of LID technologies in semi-arid urban areas of the developing world.

Contamination of Urban Stormwater Pond Sediments: A Study of 259 Legacy and Contemporary Organic Substances

Stormwater ponds improve water quality by facilitating the sedimentation of particles and particulate contaminants from urban runoff. Over time, this function entails the accumulation of contaminated sediments, which must be removed periodically to maintain a pond's hydraulic and treatment capacity. In this study, sediments from 17 stormwater sedimentation facilities from four Swedish municipalities were analyzed for 259 organic substances likely to be found in the urban environment. A total of 92 substances were detected in at least one sample, while as many as 52 substances were detected in a single sample. A typical profile of urban contamination was identified, including polychlorinated biphenyls, polycyclic aromatic hydrocarbons, organotins, aliphatic hydrocarbons, phthalates, aldehydes, polybrominated diphenyl ethers, perfluorinated substances, and alkylphenols. However, levels of contamination varied greatly between ponds, influenced heavily by the dilution of urban pollutants and wear particles from other sources of particles such as eroded soil, sand, or natural organic matter. For 22 of 32 samples, the observed concentrations of at least one organic substance exceeded the regulatory threshold values derived from toxicity data for both sediment and soil.

Mineralogical evidence of unfavorable geochemical interactions between urban runoff pollutants and filter materials in low-impact systems

We report on the geochemical interactions between a synthetic urban runoff (SUR) and the minerals of materials used in a multi-layered column filter (soil, sand, gravel, and tezontle) at the laboratory scale, which mimicked an unvegetated low-impact development (LID) system. After five 8 h infiltration cycles using the SUR, the average concentrations of Pb and Mn decreased slightly at the column outlet, as did HCO₃^-, SO₄^2-, and Na⁺, whereas Mg increased and Cl^-, Ca²⁺, and K⁺ were only detected at the outlet. The filter materials were comprised of silicates, Mn-bearing oxides (hausmannite and manganite), carbonates (calcite), chlorides (sylvite), and sulfates (anglesite, lanarkite, barite, and epsomite). PHREEQC modeling allowed the identification of the geochemical processes that occurred in the filter. The results showed the removal capacity of the filter materials through the formation of secondary minerals such as rhodochrosite (MnCO₃) and the over-saturation of anglesite (PbSO₄), and also showed that they may mobilize ions from the upper to the interior layers (as Mg²⁺ from epsomite, MgSO₄·7H₂O, and Ba²⁺ from barite, BaSO₄). We highlight the importance of knowing the geological nature of filter materials used in LID systems because they may lead to the geogenic mobilization of toxic contaminants to the environment.

Nonpoint source pollution

A comprehensive review of the research papers published in 2018 focusing on nonpoint source (NPS) pollution is presented in this review article. The identification of pollution from different sources and estimation of NPS pollution using various models are summarized in this review paper. Various innovative techniques are also examined to abate NPS pollution. PRACTITIONER POINTS: The non-point source pollution in 2018 is systematically reviewed and documented. This review evaluates and summarizes the identification, quantification, reduction, and management of NPS pollution. Future perspectives of NPS pollution research are discussed.

Urban stormwater characterization, control, and treatment

This review summarizes over 250 studies published in 2018 related to the characterization, control, and management of urban stormwater runoff. The review covers three broad themes: (a) quantity and quality characterization of stormwater, (b) control and treatment of stormwater runoff, and (c) implementation and assessment of watershed-scale green stormwater infrastructure (GSI). Each section provides an overview of the 2018 literature, common themes, and future work. Several themes emerged from the 2018 literature including exploration of contaminants of emerging concern within stormwater systems, characterization and incorporation of vegetation-driven dynamics in stormwater control measures, and the need for interdisciplinary perspectives on the implementation and assessment of GSI. PRACTITIONER POINTS: Over 250 studies were published in 2018 related to the characterization, control, and treatment of stormwater. Studies cover general stormwater characteristics, control and treatment systems, and watershed-scale assessments. Trends in 2018 include treatment trains, vegetation dynamics, and interdisciplinary perspectives.

A Review of Nitrogen Removal for Urban Stormwater Runoff in Bioretention System

One of the best management practices (BMPs) for stormwater quality and quantity control is a bioretention system. The removal efficiency of different pollutants under this system is generally satisfactory, except for nitrogen which is deficient in certain bioretention systems. Nitrogen has a complex biogeochemical cycle, and thus the removal processes of nitrogen are typically slower than other pollutants. This study summarizes recent studies that have focused on nitrogen removal for urban stormwater runoff and discusses the latest advances in bioretention systems. The performance, influencing factors, and design enhancements are comprehensively reviewed in this paper. The review of current literature reveals that a bioretention system shows great promise due to its ability to remove nitrogen from stormwater runoff. Combining nitrification and denitrification zones with the addition of a carbon source and selecting different plant species promote nitrogen removal. Nevertheless, more studies on nitrogen transformations in a bioretention system and the relationships between different design factors need to be undertaken.

Modeling of Heavy Metal (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and PAH Content in Stormwater Sediments Based on Weather and Physico-Geographical Characteristics of the Catchment-Data-Mining Approach

The processes that affect sediment quality in drainage systems show high dynamics and complexity. However, relatively little information is available on the influence of both catchment characteristics and meteorological conditions on sediment chemical properties, as those issues have not been widely explored in research studies. This paper reports the results of investigations into the content of selected heavy metals (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and polycyclic aromatic hydrocarbons (PAHs) in sediments from the stormwater drainage systems of four catchments located in the city of Kielce, Poland. The influence of selected physico-geographical catchment characteristics and atmospheric conditions on pollutant concentrations in the sediments was also analyzed. Based on the results obtained, statistical models for forecasting the quality of stormwater sediments were developed using artificial neural networks (multilayer perceptron neural networks). The analyses showed varied impacts of catchment characteristics and atmospheric conditions on the chemical composition of sediments. The concentration of heavy metals in sediments was far more affected by catchment characteristics (land use, length of the drainage system) than atmospheric conditions. Conversely, the content of PAHs in sediments was predominantly affected by atmospheric conditions prevailing in the catchment. The multilayer perceptron models developed for this study had satisfactory predictive abilities; the mean absolute error of the forecast (Ni, Mn, Zn, Cu, and Pb) did not exceed 21%. Hence, the models show great potential, as they could be applied to, for example, spatial planning for which environmental aspects (i.e., sediment quality in the stormwater drainage systems) are accounted.

Laboratory Evaluation of Eco-Friendly Pervious Concrete Pavement Material Containing Silica Fume

Pervious concretes, such as sustainable pavement materials, have great advantages in solving urban flooding, promoting urban ecological balance, and alleviating urban heat island effect, due to its special porous structure. However, pervious concrete typically has high porosity and low strength. The insufficient strength and poor freeze-thaw durability are important factors that restrict its wide application, especially in seasonal frozen areas. Improving the strength and freeze-thaw resistance of pervious concrete will expand its application. Silica fumes, as an industrial by-product waste and supplementary cementitious material, play an important role in improving concrete performance. The objective of this paper was to study the effects of silica fumes on properties of sustainable pervious concrete. Silica fumes were used to replace cement with the equivalent volume method at different levels (3%, 6%, 9%, and 12%). The control pervious concrete and silica fume-modified pervious concrete mixtures were prepared in the lab. The porosity, permeability, compressive strength, flexural strength, and freeze-thaw resistance properties of all mixtures were tested. The results indicated that the addition of silica fumes significantly improved the strength and freeze-thaw resistance of pervious concrete. The porosity and permeability of all pervious concrete mixtures changed little with the content of silica fumes due to the adoption of the equal volume replacement method.

The Development of a Novel Decision Support System for the Location of Green Infrastructure for Stormwater Management

In order to maximise the benefits of green infrastructure in a city’s structure for urban adaptation to climate change, there is a need to support decision-makers in the urban design domain with adequate information that would help them to locate such green infrastructure in the most suitable places. Therefore, the aim of this study was to develop a novel decision support system (DSS) for the location of green infrastructure. The goal of the designed solution is to inform users about the location of urban hydrological sinks, which gather stormwater in urban watersheds, and the amount of water which could accumulate in each location depending on the defined precipitation and the soil’s moisture conditions. The designed DSS is based on a multicomponent methodology including both atmospheric and soil conditions. The DSS was tested using a sample that presents the results of stormwater accumulation calculations. The obtained results show which green areas are the most suitable locations for green infrastructure solutions and which facility is optimal because of its retention abilities and amount of accumulated stormwater. The application of the designed DSS allows us to maximise the benefits of the implementation of green infrastructure within the existing urban land use. The fully editable component of hydrological conditions allows for testing projections of the potential amount of accumulated water in different precipitation scenarios. The study provides a DSS for use by local authorities which enables them to concentrate actions in order to better adapt cities to climate change and environmental extremes.