How efficient are bioretention cells in controlling phosphorus and nitrogen enrichment of urban stormwater? Insights from the International stormwater best management practice database
Bibliographic record
Abstract
Bioretention cells (BRCs) are a common technology to reduce stormwater runoff volumes and peak flows. BRCs have also been proposed as a best management practice (BMP) to control the export of contaminants from urban landscapes, including the macronutrients phosphorus (P) and nitrogen (N). To determine whether bioretention systems are effective in mitigating P and N enrichment of urban stormwater runoff, we extracted hydrologic and nutrient concentration data for over 400 precipitation events across more than 30 BRCs from the International Stormwater BMP Database. The concentration data included total P (TP), soluble reactive P (SRP), total N (TN), and dissolved inorganic N (DIN). Among the BRCs included in our analysis, 74 and 89 % exhibited average concentrations of TP and SRP that were higher in the surface outflow than in the inflow, respectively. However, the corresponding outflow loads of TP and SRP were generally lower, mainly because of reductions in surface runoff volumes. By contrast, BRCs exhibited on average lower outflow TN concentrations (median reduction of 21 %) while DIN concentrations were similar between outflow and inflow. Hence, because they are generally more efficient in reducing N than P loads, BRCs tended to decrease the TN:TP and DIN:SRP ratios of stormwater runoff, potentially altering nutrient limitation patterns in receiving aquatic ecosystems. Changes to P and N speciation were also prevalent, with BRCs typically increasing the SRP:TP and (NO 3 – +NO 2 – ):NH 4 + ratios. Random forest modeling identified inflow concentrations and BRC age as key variables modulating the changes in TP, SRP, and TN concentrations between inflow and outflow. For DIN, the BRC’s storage volume and drainage area also emerged as an important explanatory variable. Overall, our findings imply that the impacts of BRCs on the P and N concentrations, speciation, and loads of urban runoff are highly variable. Although the P and N loads in surface runoff are usually reduced by BRCs, the implications for downstream nutrient limitation and potential groundwater quality deterioration deserve further attention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".