An Investigation of the Relationships between Rainfall Conditions and Pollutant Wash-Off from the Paved Road

Effects of rainfall characteristics on runoff quality parameters within an industrial sector in Tennessee, USA

The relationship between rainfall characteristics and pollutant discharge has rarely been investigated in industrial sectors. To address this need, we investigated the pollutant concentrations of surface runoff and the correlation between pollutant discharge and rainfall characteristics using the self-reported stormwater quality data collected under the Tennessee Multi-Sector Permit program for two industrial facilities in West Tennessee. The variation of certain stormwater quality parameters over this period was utilized as an indicator to evaluate the effectiveness of control measures implemented at these two facilities. Furthermore, the Water Quality Index (WQI) as an indicator to assess the temporal changes in stormwater quality at industrial facilities was determined using the Weighted Sum (WSM) and Canadian Council of Ministers of the Environment (CCME) methods. The principal component analysis (PCA) and Pearson correlation coefficient were utilized to understand the correlation between runoff quality parameters, rainfall characteristics, and the sources of pollutants. The results demonstrated lower WQI indices using the WSM method compared to the CCME method. The data analysis revealed that 93.1%, 100%, 86.2%, and 48.3% of Al, Mg, Cu, and Fe experienced a concentration greater than the benchmark level, respectively. There was a significant relationship between Total suspended solids (TSS) and Al, Chemical Oxygen Demand (COD), Fe, oil and grease (O&G), and Zn concentrations. As a result, TSS could be a priority pollutant for designing various best management practices (BMPs) and low impact developments (LIDs). The result of the PCA and Pearson correlation coefficient showed that Al concentration made a significant correlation with the rainfall depth and rainfall duration. This analysis also illustrated that biochemical oxygen demand (BOD₅), COD, and O&G concentrations were highly correlated with antecedent dry days (ADDs). However, pH was more related to rainfall depth and rainfall intensity. This study informs both regulatory agencies and industry stakeholders regarding the importance of evaluating self-reported stormwater quality data.

Environmental emissions and pollution characteristics of mosquitocides for the control of dengue fever in a typical urban area

Mosquitocides are frequently used to control the spread of dengue fever in tropical and sub-tropic urban regions worldwide, resulting in their discharge into the environment via rainfall runoff, causing adverse effects on ecological health. This study quantitatively evaluated mosquitocide emissions and environmental pollution in a typical urban district in China affected by the dengue fever epidemic, using a method combining market surveys, monitoring campaigns and SWMM (storm water management model) modelling tools. During the assessment period, the total mosquitocide usage in the urban district reached 6334 kg, with an estimated load of 56.55 g entering the receiving environment via rainfall runoff, 91.04 % of which occurred in the rainy season. Monitoring results indicated that the initial 0.5-1 h was the main period of mosquitocide wash off into the receiving water. Environmental mosquitocide pollution levels were found to be affected by the mosquitocide type and the time interval between mosquitocide application and precipitation events. The measured environmental concentrations of mosquitocides in this study were generally higher than those areas unaffected by the dengue fever epidemic. The modelled mosquitocide concentrations were in accordance with monitoring results. The finding of this study are important for assessing the environmental impact of dengue fever control activities, while also providing valuable baseline data for the effective environmental management of mosquitocides.

Synergistic effect of drought and rainfall events of different patterns on watershed systems

The increase in extreme climate events such as flooding and droughts predicted by the general circulation models (GCMs) is expected to significantly affect hydrological processes, erosive dynamics, and their associated nonpoint source (NPS) pollution, resulting in a major challenge to water availability for human life and ecosystems. Using the Hydrological Simulation Program–Fortran model, we evaluated the synergistic effects of droughts and rainfall events on hydrology and water quality in an upstream catchment of the Miyun Reservoir based on the outputs of five GCMs. It showed substantial increases in air temperature, precipitation intensity, frequency of heavy rains and rainstorms, and drought duration, as well as sediment and nutrient loads in the RCP 8.5 scenario. Sustained droughts followed by intense precipitation could cause complex interactions and mobilize accumulated sediment, nutrients and other pollutants into surface water that pose substantial risks to the drinking water security, with the comprehensive effects of soil water content, antecedent drought duration, precipitation amount and intensity, and other climate characteristics, although the effects varied greatly under different rainfall patterns. The Methods and findings of this study evidence the synergistic impacts of droughts and heavy rainfall on watershed system and the significant effects of initial soil moisture conditions on water quantity and quality, and help to guide a robust adaptive management system for future drinking water supply.

Residential catchments to coastal waters: Forms, fluxes, and mechanisms of phosphorus transport

Controlling phosphorus (P) loss from land to water bodies is of immense scientific and societal interest and scrutiny. We investigated P forms in a longitudinal gradient in three typical urban junctions: stormwater from a residential catchment, pond discharges from a stormwater retention pond, and 13 coastal waters (rivers and estuary). Concentrations of total P (TP) were 122.7 ± 99.1 μg/L in the stormwater, 89.7 ± 35.8 μg/L in the pond discharges, and 212.1 ± 51.2 μg/L in 13 coastal water sites. Lower P concentrations in pond discharges reflect P attenuation in the stormwater pond, and higher P concentrations in surface waters are likely attributed to the additional contributing P sources in the watershed. Dissolved reactive P (DRP) was 38% of TP load in stormwater and 46% of TP concentrations in surface water sites, whereas particulate unreactive P (PUP) was 52% of TP load in pond discharges. The first-flush strength of P forms in the stormwater indicated the dominance of particulate P over dissolved P. More particulate P was transported in the early stages of storms due to the runoff of P associated with sediment, plant materials, and built up on impervious surfaces. Whereas more dissolved P was transported in the later stages of storms likely due to the flushing of P, as exacerbated by greater runoff amounts, from the landscape sources, i.e., grass clippings, tree leaves, and soil. In the pond discharges, DRP was a minor form suggesting its utilization by bacteria and algae in the pond. The high concentration and proportion of DRP in surface waters suggest an abundance of bioavailable P in urban waters. These results imply that treatment designs in urban areas should consider ways to remove P in urban landscapes focusing on attenuating P before the initiation of runoff and discharge to surface waters to protect downstream water quality.

Supervised Machine Learning for Estimation of Total Suspended Solids in Urban Watersheds

Machine Learning (ML) algorithms provide an alternative for the prediction of pollutant concentration. We compared eight ML algorithms (Linear Regression (LR), uniform weighting k-Nearest Neighbor (UW-kNN), variable weighting k-Nearest Neighbor (VW-kNN), Support Vector Regression (SVR), Artificial Neural Network (ANN), Regression Tree (RT), Random Forest (RF), and Adaptive Boosting (AdB)) to evaluate the feasibility of ML approaches for estimation of Total Suspended Solids (TSS) using the national stormwater quality database. Six factors were used as features to train the algorithms with TSS concentration as the target parameter: Drainage area, land use, percent of imperviousness, rainfall depth, runoff volume, and antecedent dry days. Comparisons among the ML methods demonstrated a higher degree of variability in model performance, with the coefficient of determination (R2) and Nash–Sutcliffe (NSE) values ranging from 0.15 to 0.77. The Root Mean Square (RMSE) values ranged from 110 mg/L to 220 mg/L. The best fit was obtained using the AdB and RF models, with R2 values of 0.77 and 0.74 in the training step and 0.67 and 0.64 in the prediction step. The NSE values were 0.76 and 0.72 in the training step and 0.67 and 0.62 in the prediction step. The predictions from AdB were sensitive to all six factors. However, the sensitivity level was variable.

Episodic surges in titanium dioxide engineered particle concentrations in surface waters following rainfall events

Quantifying and characterizing engineered particles in environmental systems is key for assessing their risk but remains challenging and requires the distinction between natural and engineered particles. The objective of this study was to characterize and quantify the concentrations of titanium dioxide engineered particles in the Broad River, Columbia, South Carolina, United States during and following rainfall events. The elemental ratio distributions of Ti/Nb, Ti/Fe, and Ti/Al, determined on a single particle basis using inductively coupled plasma-time of flight-mass spectrometry (SP-ICP-TOF-MS), were similar between samples during the different rainfall events, indicating that naturally occurring particles had the same elemental ratios and origin. Therefore, the changes in the Ti/Nb ratios in the bulk water samples were attributed to the introduction of titanium dioxide engineered particles into the Broad River with urban runoff during and following rainfall events. The total concentrations of Ti, Fe, Al, Nb, Ce, and La in the Broad River followed the same trend of rise and fall as the discharge/runoff. The elemental ratios of Ti/Nb were higher (e.g., 330 to 565) than the average crustal values (e.g., 320) and the natural background elemental ratios in surface waters in Columbia, SC (e.g., 266.4 ± 8.9), suggesting contamination with titanium dioxide engineered particles. The concentration of titanium dioxide engineered particles were estimated by mass balance calculations using total titanium concentrations and increases in Ti/Nb ratios above the natural background ratios. The concentrations of titanium dioxide engineered particles in the Broad River varied between 20 and 140 μg TiO₂ L^-1 following rainfall events. The source of titanium dioxide was attributed to urban runoff due to the absence of sewage contamination as indicated by the low size of the gadolinium anomaly. The findings of this study demonstrate that urban runoff is a major source of titanium dioxide engineered particles to urban rivers, which results in episodic high concentrations of titanium dioxide engineered particles, which may pose environmental risks during and following rainfall events. This study also highlights the importance of determining the temporal variations in engineered particle concentrations in surface waters for a more comprehensive risk assessment of engineered particles.

A Framework for Assessing Modeling Performance and Effects of Rainfall-Catchment-Drainage Characteristics on Nutrient Urban Runoff in Poorly Gauged Watersheds

Protection of surface water quality plays a crucial role for sustainable urban watershed management since the wash-off from impervious contaminated surfaces generates transport phenomena from a range of pollutants (like nutrients, such as total nitrogen (Ntot) and total phosphorus (Ptot)). This leads to the consequent reduction of water quality, and to phenomena, such as eutrophication and the presence of algae blooms. For this reason, a comprehensive understanding of nutrient build-up and wash-off is essential for efficient stormwater treatment design. However, data scarcity could represent one of the main limitations in this context. This manuscript presents a methodological framework able to tackle such limitations by an in-depth investigation of the main factors that influence the build-up and wash-off from impervious surfaces, including rainfall, watershed, and drainage-network characteristics. The outcomes highlight the key role played by the antecedent dry period, among the rainfall characteristics, and the width of the overland flow path, among the catchment/drainage characteristics. It is also confirmed as appropriate to use suspended solids as a surrogate for the investigation of the behavior of other pollutant species. Additionally, the capability of this approach in assessing modeling performance was successfully tested. The results of the present study are expected to contribute valuable knowledge for defining effective management strategies to minimize stream pollution and protect the health of aquatic ecosystems in urban watersheds characterized by data scarcity.

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.

Temporal variability of suspended solids in construction runoff and evaluation of time-paced sampling strategies

The construction sites have been considered the type of land use with the highest pollution potential, especially due to the erosion of exposed soil surfaces. The runoff monitoring of the construction site was carried out since June 2011 through December 2015. Based on land use land cover (LULC) classification, the monitoring period was divided into active and post-construction phases. Total suspended solids (TSS) showed evident inter-phase variability in average annual event mean concentration (AAEMC) and wash-off pattern. We suggested that stringent runoff control measures should be adopted during active construction phase. Similarly, Personalized Computer Storm Water Management Model (PCSWMM) was applied to evaluate the performance of the time-paced discrete and composite sampling scheme in continuously changing LC scenario. It was found that even though the time-paced composite sampling scheme is more cost effective, it showed lower performance in EMC estimation when compared with the time-paced discrete sampling approach. The results also showed that the storm event monitored at a time discrete frequency of 5 min, 10 min, and 15 min, the maximum expected mean bias will be under the accepted level of 10% of the true EMC value. We concluded that construction phase-specific modifications in sampling scheme provides a view to generate near accurate estimates.

Performance of a constructed wetland as an upstream intervention for stormwater runoff quality management

In most developing countries, stormwater runoff has had significant impacts on aquatic environment by directly causing pollution of receiving water and reduction in treatment performance of wastewater treatment plants. With increasing encroachment on natural wetlands in Uganda, constructed wetlands offer a feasible option for the environment to cope up and buffer the impact of pollutants from the ever-increasing urban masses. This study investigated the performance efficiencies of three configurations (varied by the substrate used) of microcosm wetlands to remove physicochemical parameters from stormwater runoff in Uganda. The parameters monitored included chemical oxygen demand (COD), total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Hydraulic retention times (HRTs) of 2, 4, 6, and 8 days were studied. The mean concentrations of the physicochemical parameters in the runoff were 219.4 ± 12.8 mg/L COD, 77.4 ± 8.3 mg/L TSS, 9.0 ± 0.4 mg/L TN, and 1.6 ± 0.1 mg/L TP. Configuration A, vegetated with cattail (Typha latifolia) and bulrush (Scirpus lacustris), achieved maximum COD removal of 75.9% (HRT = 6 days), TN removal of 72.8% (HRT = 8 days), and TP removal of 62.8% (HRT = 8 days). Configuration C, the control, with no substrate, achieved the highest TSS removal of 75.6%. The results suggest that vegetated microcosm constructed wetlands can potentially be used to pre-treat stormwater within the catchment. However, an upstream sedimentation process unit is required to enhance their performance and to avoid premature clogging of the wetlands by TSS. The pre-treated stormwater reduces pollutant load into wastewater treatment plants and consequently better raw water quality for water treatment plants.

Time series study of weather, water quality, and acute gastroenteritis at Water Safety Plan implementation sites in France and Spain

Water Safety Plans (WSPs), recommended by the World Health Organization since 2004, can help drinking water suppliers to proactively identify potential risks and implement preventive barriers that improve safety. Few studies have investigated long-term impacts of WSPs, such as changes in drinking water quality or public health; however, some evidence from high-income countries associates WSP implementation with a reduction in diarrheal disease. To validate the previously observed linkages between WSPs and health outcomes, this time series study examined site-specific relationships between water-related exposures and acute gastroenteritis rates at three locations in France and Spain, including the role of WSP status. Relationships between control or exposure variables and health outcomes were tested using Poisson regression within generalized additive models. Controls included suspected temporal trends in disease reporting. Exposures included temperature, precipitation, raw water quality, and finished water quality (e.g., turbidity, free chlorine). In France, daily acute gastroenteritis cases were tracked using prescription reimbursements; Spanish data aggregated monthly acute gastroenteritis hospital visits. The models identified several significant relationships between indicators of exposure and acute gastroenteritis. Lag times of 6-9 days (including transit time) were most relevant for hydrological indicators (related to precipitation, runoff, and flow) at the two French sites, indicative of viral pathogens. Flush events (defined as surface runoff after a two-week antecedent dry period) linked to nonpoint source pollution were associated with a 10% increase in acute gastroenteritis rates at one location supplied by surface water. Acute gastroenteritis rates were positively associated with elevated turbidity average or maximum values in finished water at locations supplied by both surface and groundwater, by about 4% per 1-NTU increase in the two-week moving average of daily maxima or about 10% per 0.1 NTU increase in the prior month's average value. In some cases, risk appeared to be mitigated by WSP-related treatment interventions. Our results suggest drinking water exposure is associated with some potentially preventable gastrointestinal illness risk in high-income regions.