The impact of stormwater biofilter design and operational variables on nutrient removal - a statistical modelling approach

Real time control of stormwater biofilters improves the removal of organic chemicals

Biofilters are among the most popular nature-based systems for treating stormwater and delivering multiple environmental benefits. However, as a passive system, their performance tends to be inconsistent in removing emerging organic contaminants produced by anthropogenic activities that can be persistent, mobile, and toxic. Thus, in this study, real time control (RTC) of stormwater biofilters is introduced to enhance the removal of a diverse range of organic chemicals. Laboratory columns were employed to investigate the performance of five RTC strategies, i.e., dynamic soil moisture control (RTC-Moisture), infiltration rate control (RTC-IR), pre-drain (RTC-PreDrain), fully unsaturated (RTC-UnSat), and fully saturated (RTC-FulSat). These RTC strategies were tested under varying rainfall sizes, as well as dry and wet conditions. Additionally, the study examined the accumulation of organic chemicals in the media. The results revealed that RTC-Moisture, RTC-IR, and RTC-PreDrain were the top three performing strategies, which achieved a significantly higher removal rate than Non-RTC biofilters for the majority of tested organic chemicals (p-value < 0.05). The best RTC strategy, RTC-Moisture, not only had the highest overall performance (average removal rate of 76.1 %) but was also least affected by various rainfall events. Despite a better chemical removal found in RTC-Moisture and RTC-PreDrain, there was no significant overall increase in the accumulation of organic chemicals within the media (p-value > 0.05) when compared to Non-RTC biofilters. This may indicate that the biodegradation process could be promoted in the well-performing RTC biofilters. This study confirms the possibility of using RTC strategies to enhance organic chemical removal in stormwater biofilters.

Urban Stormwater Phosphorus Export Control: Comparing Traditional and Low-impact Development Best Management Practices

Data from the International Stormwater Best Management Practices (BMP) Database were used to compare the phosphorus (P) control performance of six categories of stormwater BMPs representing traditional systems (stormwater pond, wetland basin, and detention basin) and low-impact development (LID) systems (bioretention cell, grass swale, and grass strip). Machine learning (ML) models were trained to predict the reduction or enrichment factors of surface runoff concentrations and loadings of total P (TP) and soluble reactive P (SRP) for the different categories of BMP systems. Relative to traditional BMPs, LIDs generally enriched TP and SRP concentrations in stormwater surface outflow and yielded poorer P runoff load control. The SRP concentration reduction and enrichment factors of LIDs also tended to be more sensitive to variations in climate and watershed characteristics. That is, LIDs were more likely to enrich surface runoff SRP concentrations in drier climates, when inflow SRP concentrations were low, and for watersheds exhibiting high impervious land cover. Overall, our results imply that stormwater BMPs do not universally attenuate urban P export and that preferentially implementing LIDs over traditional BMPs may increase TP and SRP export to receiving freshwater bodies, hence magnifying eutrophication risks.

Review of trace organic chemicals in urban stormwater: Concentrations, distributions, risks, and drivers

Urban stormwater, increasingly seen as a potential water resource for cities and towns, contains various trace organic chemicals (TrOCs). This study, conducted through a comprehensive literature review of 116 publications, provides a detailed report on the occurrence, concentration distribution, health, and ecological risks of TrOCs, as well as the impact of land use and rainfall characteristics on their concentrations. The review uncovers a total of 629 TrOCs detected at least once in urban stormwater, including 228 pesticides, 132 pharmaceutical and personal care products (PPCPs), 29 polycyclic aromatic hydrocarbons (PAHs), 30 per- and polyfluorinated substances (PFAS), 28 flame retardants, 24 plasticizers, 22 polychlorinated biphenyls (PCBs), nine corrosion inhibitors, and 127 other industrial chemicals/intermediates/solvents. Concentration distributions were explored, with the best fit being log-normal distribution. Risk assessment highlighted 82 TrOCs with high ecological risk quotients (ERQ > 1.0) and three with potential health risk quotients (HQ > 1.0). Notably, 14 TrOCs (including six PAHs, five pesticides, three flame-retardants, and one plasticizer) out of 68 analyzed were significantly influenced by land-use type. Relatively weak relationships were observed between rainfall characteristics and pollutant concentrations, warranting further investigation. This study provides essential information about the occurrence and risks of TrOCs in urban stormwater, offering valuable insights for managing these emerging chemicals of concern.

Acclimatization of a sequencing batch vertical oxidation pond with simulated agricultural wastewater using duckweed as vegetation: analysis of efficiency, Biomass, and Soil properties

Vertical oxidation pond operated in sequencing batch mode (HRT: 1.25 day) with duckweed as the vegetation was used to acclimatize with simulated agricultural wastewater. The maximum removal rate of urea [371 g/(m3.d)] and COD [222.4 g/(m3.d)] were observed at moderate concentrations of urea (500 mg/L), N-P-K (60 mg/L), and pesticide (20 mg/L). Inhibition and toxicity posed by higher concentrations, decreased the removals of urea (83% to 61%), COD (81% to 51%), and TDS (76% to 50%) at the end of the acclimatization. Steady removal (> 99%) of PO43--P was observed during acclimatization. Effluent pH increased due to the generation of NH4+-N (maximum 370 ± 5 mg/L) from the assimilation of urea. Oxidation of ammonia led to the maximum generation of NO2--N and NO3--N of 10 mg/L and 9 mg/L, respectively. Particles less than 300 μm increased, and both specific gravity (from 2.62 to 2.42) and maximum dry density (from 1.73 to 1.30 g/cm3) of the base soil decreased with an increase in urea, N-P-K, and pesticide. Reactor biomass increased (1.42 to 1.90 g/L) up to initial concentrations of urea (500 mg/L), N-P-K (60 mg/L), and pesticide (20 mg/L), then decreased (1.68 g/L) with an increase in concentration.

Soil properties and functional genes in nitrogen removal process of bioretention

The effects of different soil properties on hydrology and nitrogen removal were studied in a simulated bioretention system. Soil capacity of permeability and water retention, changes in the soil environment, leachate concentrations at the surface and bottom layers, quantification of N removal from soil, microorganism and plant by 15N isotope tracer technique, and functional genes abundance at different depths were evaluated. The results showed that shallow root plants, soil compaction, and low organic matter content were not conducive to the infiltration of bioretention systems. In the 72 h experiment, compaction (especially surface compaction) and planting of herbaceous plants (Ophiopogon japonicus) were not beneficial to the removal of TN, TP, and COD. Adding an appropriate amount of organic matter also affects nitrogen and phosphorus removal. In the process of denitrification, the order of the ability to remove nitrogen is soil adsorption > microbial assimilation > plant uptake. The contribution of soil denitrification is affected by soil compaction, compaction location, plant species and organic matter content. The abundance of 16S rRNA, nitrifying, denitrifying and nrfA genes decreased with soil depth. More copies of genes in topsoil were thought to be due to sufficient nutrients, aerobic condition, anaerobic microsites and submerged state. Soil compaction, organic matter content and plant species affected nitrification, denitrification and DNRA gene characteristics.

Insights into the transport and bio-degradation of dissolved inorganic nitrogen in the biochar-pyrite amended stormwater biofilter using dynamic modeling

The stormwater biofilter is a prevailing green infrastructure for urban stormwater management, but it is less effective in dissolved nitrogen removal, especially for nitrate. The mechanism that governs the nitrate leaching and performance stability of stormwater biofilters is poorly understood. In this study, a water quality model was developed to predict the ammonium and nitrate dynamics in a biochar-pyrite amended stormwater biofilter. The transport of dissolved nitrogen species was described by advection-dispersion models. The kinetics of adsorption and pyrite-based autotrophic denitrification are included in the model and simulated with a steady-state saturated flow. The model was calibrated and validated using eleven storm events. The modeling results reveal that the contribution of pyrite-based autotrophic denitrification to nitrate leaching alleviation improves with the increased drying duration. The nitrate removal efficiency was affected by a series of design parameters. Pyrite filling rate has a minor effect on nitrate removal promotion. Service area ratio and submerged zone depth are the key parameters to prevent nitrate leaching, as they influence the emergence and discharge time of nitrate breakthrough. The high inflow volume (high service area ratio) and small submerged zone can lead to earlier and increased discharge of peak nitrate otherwise the peak nitrate could be retained in the submerged zone and denitrified during the drying period. The developed mechanistic model provides a useful tool to evaluate the treatment ability of stormwater biofilters under varying conditions and offers a guideline for biofilter design optimization.

Outflow risks of antibiotic-resistant bacteria in stormwater bioretention cells: understanding roles of adsorption and transmission

In this study, lab-scale bioretention cells were designed for the investigation of antibiotic-resistant bacteria (ARB) outflow profiles at different depths, effects of adsorption and transmission, as well as modelling evaluation of ARB outflow risks using the common decay models (e.g., first-order decay models). ARB outflow was first found in the upper layers (after 100 days of the operation) with the lowest transmission frequencies of antibiotic resistance. Although the adsorption of ARB onto the substrate and its surface biofilms was effective with the maximum amount of ARB adsorbed (Qmax) reaching 108 CFU/g of the substrate and 107 CFU/g of biofilms, ARB outflow was detected in the bottom outlets after over 4 months of operation, reflecting that there was still a risk of antibiotic resistance through the treatment of bioretention cells. ARB outflow for both upper and middle outlets could be well described by third-order polynomial equations with correlation coefficients 0.9067 (p = 0.0002) and 0.9780 (p < 0.0001), respectively, where there were both positive and negative relationships between outflow ARB and inflow ARB, confirming the combined action of mechanisms blocking ARB outflow (e.g., substrate adsorption) and promoting ARB outflow (like transmission). These suggested two potential controlling approaches for ARB outflow from stormwater bioretention cells.

Developing nitrogen removal models for stormwater bioretention systems

Bioretention systems have the potential of simultaneous runoff volume reduction and nitrogen removal. Internal water storage (IWS) layers and real-time control (RTC) strategies may further improve performance of bioretention systems. However, optimizing the design of these systems is limited by the lack of effective models to simulate nitrogen transformations under the influences of IWS design and environment conditions including soil moisture and temperature. In this study, nitrogen removal models (NRMs) are developed with two complexity levels of nitrogen cycling: the Single Nitrogen Pool (SP) models and the more complex 3 Nitrogen Pool (3P) models. The 0-order kinetics, 1st order kinetics, and the Michaelis-Menten equations are applied to both SP and 3P models, creating six different NRMs. The Storm Water Management Model (SWMM), in combination with each NRM, is calibrated and validated with a lab dataset. Results show that 0-order kinetics are not suitable in simulating nitrogen removal or transformations in bioretention systems, while 1st order kinetics and Michaelis-Menten equation models have similar performances. The best performing NRM (referred to as 3P-m) can accurately predict nitrogen event mean concentrations in bioretention effluent for 20% more events when compared to SWMM. When only calibrated with soil moisture conditions in bioretention systems without internal storage layers, 3P-m was sufficiently adaptable to predict cumulative nitrogen mass removal rates from systems with IWS or RTC rules with less than ±7% absolute error, while the absolute error from SWMM prediction can reach -23%. In general, 3P models provide higher prediction accuracy and improved time series of biochemical reaction rates, while SP models improve prediction accuracy with less required user input for initial conditions.

Real-time control technology for enhancing biofiltration performances and ecosystem functioning of decentralized bioretention cells

Urban stormwater management has become a major issue over the last decades for flood prevention as well as water resource preservation. The development of green infrastructures such as bioretention systems since the 1990s has often been reported as an effective means of runoff mitigation with subsequent conveyed pollutant capture. Nevertheless, climate change involving more frequent extreme weather events as well as the variety of emerging pollutants in urban runoff have put an increasing strain on bioretention processes. Within this context, this mini-review deals with the opportunity of upgrading vegetated bioretention systems with active control technology to enhance their pollutant treatment capacity through proper control of critical bioretention operational variables and relying on improved ecological functioning and resilience. It is envisioned that such nature-based solutions hybridized with real-time control technology would help to improve stormwater reuse for more sustainable urban water management within the nexus of water-energy-food and greenhouse gases in future cities.

Adsorption Characteristics of Phosphate Based on Al-Doped Waste Ceramsite: Batch and Column Experiments

Phosphorus widely existing in rainfall and wastewater impacts the water environment. In this study, sludge, cement block, and coal fly ash were employed as ceramsite material to synthesize Al-doped waste ceramsite (Al-ceramsite) for removing phosphate (PO₄^3--P) from aqueous solutions. Batch static adsorption-desorption experiments were designed to investigate the effect of various parameters such as Al-ceramsite dosage, PO₄^3--P concentration, temperature, initial pH, coexisting ions, and desorbents on the removal of PO₄^3--P. Also, the fate of PO₄^3--P removal efficiency in actual rainwater was studied through dynamic adsorption column experiments using Al-ceramsite. Results showed that Al-ceramsite could remove PO₄^3--P efficiently under the optimum parameters as follows: Al-ceramsite dosage of 40 g/L, initial PO₄^3--P concentration of 10 mg/L, temperature of 25 °C, and pH of 5. Besides that, the Al-ceramsite could completely remove PO₄^3--P in actual rainwater, and the effluent PO₄^3--P concentration was lower than the environmental quality standards for surface water Class Ⅰ (0.02 mg/L). The adsorption characteristics of Al-ceramsite on PO₄^3--P by X-ray photoelectron spectroscopy (XPS) were further explained. As a result, ligand exchange and complexation were confirmed as the main PO₄^3--P removal mechanism of Al-ceramsite. Thus, Al-ceramsite was prepared from industrial waste and has shown excellent potential for phosphorus removal in practical applications.

Air Pollutants Removal Using Biofiltration Technique: A Challenge at the Frontiers of Sustainable Environment

Air pollution is a central problem faced by industries during the production process. The control of this pollution is essential for the environment and living organisms as it creates harmful effects. Biofiltration is a current pollution management strategy that concerns removing odor, volatile organic compounds (VOCs), and other pollutants from the air. Recently, this approach has earned vogue globally due to its low-cost and straightforward technique, effortless function, high reduction efficacy, less energy necessity, and residual consequences not needing additional remedy. There is a critical requirement to consider sustainable machinery to decrease the pollutants arising within air and water sources. For managing these different kinds of pollutant reductions, biofiltration techniques have been utilized. The contaminants are adsorbed upon the medium exterior and are metabolized to benign outcomes through immobilized microbes. Biofiltration-based designs have appeared advantageous in terminating dangerous pollutants from wastewater or contaminated air in recent years. Biofiltration uses the possibilities of microbial approaches (bacteria and fungi) to lessen the broad range of compounds and VOCs. In this review, we have discussed a general introduction based on biofiltration and the classification of air pollutants based on different sources. The history of biofiltration and other mechanisms used in biofiltration techniques have been discussed. Further, the crucial factors of biofilters that affect the performance of biofiltration techniques have been discussed in detail. Finally, we concluded the topic with current challenges and future prospects.

Antibiotic resistance genes removals in stormwater bioretention cells with three kinds of environmental conditions

Recently, increasing attention has been paid to antibiotic resistance genes (ARGs) in stormwater runoff. However, there is still no available literature about ARGs removals through stormwater bioretention cells. Batch experiments were conducted to investigate target ARGs (bla_TEM, tetR and aphA) removals under three environmental conditions, including substrate (weight ratios of sand to soil), hydraulic loading rate (HLR) and submerged area depth. The target ARGs removals were the largest (more than 5 log in the bottom outlets) in bioretention cells with 8:2 ratio of sand to soil, HLR 0.044 cm³/cm²/min and 150 mm of submerged area depth. The proportion for both iARGs and eARGs had little effect on target ARGs removals (expect extracellular bla_TEM), although distributions of target ARGs were different in substrate layers. Adsorption behavior tests indicated that both kinetics and isotherms of target ARGs adsorption by biofilms were more suitable to explain their best removals for bioretention cells with 8:2 ratio of sand to soil than that by substrate. At phylum and genus levels, there were respectively 6 dominant microflora related significantly to target ARGs levels, and their relationships changed obviously under different environmental conditions, suggesting that regulating the dominant microflora (like Verrucomicrobia and Actinobacteria) could be feasible to change ARGs removals.

Natural aging of expanded shale, clay, and slate (ESCS) amendment with heavy metals in stormwater increases its antibacterial properties: Implications on biofilter design

Aging is often expected to decrease the pathogen removal capacity of media because of exhaustion of attachment sites by adsorption of co-contaminants and dissolved organics. In contrast, the adsorption of metals naturally present in stormwater during aging could have a positive impact on pathogen removal. To examine the effect of adsorbed metals on pathogen removal, biofilter media amended with expanded clay, shale, and slate (ESCS) aggregates, a lightweight aggregate, were exposed to metals by intermittently injecting natural stormwater spiked with Cu, Pb, and Zn, and the capacity of aged and unaged media to remove Escherichia coli (E. coli), a pathogen indicator, were compared. Metal adsorption on ESCS media decreased their net negative surface charge and altered the surface properties as confirmed by zeta potential measurement and Fourier-Transform Infrared Spectroscopy (FTIR) analysis. These changes increased the E. coli adsorption capacity of aged media compared with unaged media and decreased overall remobilization of attached E. coli during intermittent infiltration of stormwater. A live-dead analysis confirmed that the adsorbed metals inactivated attached E. coli, thereby replenishing the adsorption capacity. Overall, the results confirmed that natural aging of biofilter media with adsorbed metals could indeed have a net positive effect on E. coli removal in biofilters and therefore should be included in the conceptual model predicting long-term removal of pathogens from stormwater containing mixed pollutants.

Sustainable micropollutant bioremediation via stormwater biofiltration system

Waters contaminated with micropollutants are of environmental and public health concern globally. Stormwater is a significant source of anthropogenic micropollutants to receiving waters. Hence, sustainable stormwater remediation is needed to reduce contamination of waterways. Yet designing sustainable bioremediation solutions, including those targeted to remove micropollutants, is a major scientific challenge. This study aimed to adapt the design of stormwater biofiltration systems, to improve the removal of micropollutants and understand the role of the micropollutant-degrading bacteria in this bioremediation process. We investigated the atrazine removal performance of a prototype biofiltration system, in which the filter media was supplemented with Granulated Activated Carbon (GAC). The prototype biofiltration system completely removed atrazine to below detectable limits, significantly exceeding the GAC's adsorption capacity alone, suggesting other biological processes were present. We showed that atrazine degradation capacity, measured by the kinetics of the trzN gene abundance, was accelerated in the prototype system compared to the standard system (which had no added GAC; 0.8 vs. 0.37 week-1, respectively). Notably, this high level of atrazine removal did not come at the expense of the removal performance of other typical stormwater macropollutants (e.g., nutrients, suspended solids). The prototype biofiltration system showed a proof-of-concept of sustaining microbial remediation of a model micropollutant alongside stormwater macropollutants, which could be used to reduce impacts on receiving waterways and protect our ecosystems and human health.

Unconventional microbial mechanisms for the key factors influencing inorganic nitrogen removal in stormwater bioretention columns

Bioretention systems are environmentally friendly measures to control the amount of water and pollutants in urban stormwater runoff, and their treatment performance for inorganic N strongly depends on various microbial processes. However, microbial responses to variations of N mass reduction in bioretention systems are complex and poorly understood, which is not conducive to management designs. In the present study, a series of bioretention columns were established to monitor their fate performance for inorganic N (NH4+and NO3-) by using different configurations and by dosing with simulated stormwater events. The results showed that NH4+ was efficiently oxidized to NO3-, mainly by ammonia- and nitrite-oxidizing bacteria in the oxic media, regardless of the configurations of the bioretention systems or stormwater conditions. In contrast, NO3- removal pathways varied greatly in different columns. The presence of vegetation efficiently improved NO3-mass reduction through root assimilation and enhancement of microbial NO3- reduction in the rhizosphere. The construction of an organic-rich saturation zone can make the redox potential too low for heterotrophic denitrification to occur, so as to ensure high NO3- mass reduction mainly via stimulating chemolithotrophic NO3- reduction coupled with oxidation of reductive sulfur compounds derived from the bio-reduction of sulfate. In contrast, in the organic-poor saturation zone, multiple oligotrophic NO3- reduction pathways may be responsible for the high NO3- mass reduction. These findings highlight the necessity of considering the variation of N bio-transformation pathways for inorganic N removal in the configuration of bioretention systems.

Machine learning approaches for predicting the performance of stormwater biofilters in heavy metal removal and risk mitigation

The increasing amount of data on biofilter treatment performance over the past decade has made it possible to use data-driven approaches to explore the relationships between biofilter performance and a range of input variables. The knowledge gap lies in lack of models to predict the biofilter performance considering both design and operational variables, especially for heavy metals. In this study, we tested three machine learning (ML) approaches, namely multilinear regression (MLR), artificial neural network (NN), and random forest (RF), to predict biofilter outflow concentrations of heavy metals (Cd, Cr, Cu, Fe, Ni, Pb and Zn) using a range of design and operational factors as input variables. The results show that RF performed relatively better than other two models, with median Nash-Sutcliffe Efficiency (NSE) values of 0.995, 0.317, 0.762, 0.636, 0.726, 0.896 and 0.656 for Cd, Cr, Cu, Fe, Ni, Pb and Zn, respectively during model training. However, all the models were less accurate during model validation, with the better performance found for Cd (average NSE=0.964), Zn (0.530) and Ni (0.393) and poorer performance observed for Cu (0.219), Pb (0.058), Fe (-0.054) and Cr (-0.062). Infiltration rate (IR) and inflow concentration (C_in) were sensitive to all pollutants' removal in biofilters. The ratio of system size to catchment size was also found to be important for Zn, Ni and Cd, while ponding depth was an important variable for Cd. Based on thousands of hypothetical design and operational scenarios (generated using raw data), the best ML models were used to predict the biofilter outflow concentrations and estimate the risk quotient (RQ) values with regards to reuse of treated stormwater for various purposes. Results suggest that biofilters were able to reduce health risks associated with heavy metals in stormwater and therefore produce reliable water fit for reuses such as irrigation, swimming, and toilet flushing. Modelling results showed that biofiltration did not meet the requirements for drinking when Cd contamination exists. Explorative analysis also demonstrated how the key operational and design variables can be optimised to further reduce the health risks that can be fit for drinking purposes (i.e., RQ value <1).

Iron amendments minimize the first-flush release of pathogens from stormwater biofilters

First flush or the first pore volume of effluent eluted from biofilters at the start of rainfall contributes to most pollution downstream because it typically contains a high concentration of bacterial pathogens. Thus, it is critical to evaluate designs that could minimize the release of bacteria during a period of high risk. In this study, we test the hypothesis of whether an addition of iron-based media to biofilter could limit the leaching of Escherichia coli (E. coli), a pathogen indicator, during the first flush. We applied E. coli-contaminated stormwater intermittently in columns packed with a mixture of sand and compost (70:30 by volume, respectively) and iron filings at three concentrations: 0% (control), 3%, and 10% by weight. Columns packed with a mixture of sand and iron (3% or 10%) without compost were used to examine the maximum capacity of iron to remove E. coli. In columns with iron, particularly 10% by weight, the leaching of E. coli during the first flush was 32% lower than the leaching from compost columns, indicating that the addition of iron amendments could decrease first-flush leaching of E. coli. We attribute this result to the ability of iron to increase adsorption and decrease growth during antecedent drying periods. Although the addition of iron filings increased E. coli removal, the presence of compost decreased the adsorption capacity: exposure of 1 g of iron filings to 1 mg of DOC reduces E. coli removal by 8%. The result was attributed to the alteration of the surface charge of iron and blocking of adsorption sites shared by E. coli and DOC. Collectively, these results indicate that the addition of sufficient amounts of iron media could decrease pathogen leaching in the first flush effluent and increase the overall biofilter performance and protect downstream water quality.