Urban water, sewer, and road infrastructures are simultaneously facing renewal demands, necessitating more cost-efficient rehabilitation strategies. Coordinating interventions across co-located assets can lower long-term expenditures, yet strategic-level modelling approaches remain limited. This study evaluates two such methods: joint cohort survival analysis (JCSA), which models either separate or systematic coordination, and the multi-utility rehabilitation modeller (MURM), which introduces a coordination window to represent intermediate policies. Both methods were applied to residential street cohorts constructed in Luleå, Sweden, during 1965–1975. The results indicate that JCSA and MURM produce consistent outcomes under no-coordination and systematic coordination scenarios. In contrast, under moderate coordination, MURM predicts substantially lower accumulated capital costs (€50.5 m) than JCSA (€58.8 m), corresponding to a 12–17% reduction. These findings demonstrate the analytical advantages of MURM for strategic asset management, offering decision-makers a more realistic representation of coordination policies and their long-term financial implications.

Urban runoff carries a variety of compounds many of which are largely unknown organic pollutants occurring in low concentrations. This study combines analyses targeting known contaminants (metals, phthalates and nonylphenols, octylphenols and their ethoxylates) with effect-based methods that indicate the mixture effects of known and unknown substances. The potential chemical hazard of roof runoff was investigated during a rain event sampled in June in Luleå, northern Sweden. The investigation included measures of oxidative stress response, aryl hydrocarbon (AhR) activation, and endocrine disruption (androgenic, antiandrogenic and estrogenic effects) of the dissolved and the particulate phases in the water. In the runoff, significant metal release from copper (5320 μg Cu/L), zinc (8690 μg Zn/L) and galvanized roofs (8050 μg Zn/L) was observed, whereas for organic compounds only DINP (280 μg/L) and DEHP (1.8 μg/L) were detected from one of the PVC roofs. Results on biological effects showed cytotoxic interference for most samples and genotoxicity for all samples. For each assay, specific effects were detected in ≥50 % of the samples except for androgenic activity. Most commonly, oxidative stress and AhR activity were observed. For oxidative stress, the range of BEQ concentrations was <14–131 μg/L tBHQeq (dissolved phase) and 9.04–50.8 μg/L tBHQeq (particulate phase). For AhR activity, the range was <0.427–5.8 ng/L TCDDeq (dissolved phase) and 0.383–23.5 ng/L TCDDeq (particulate phase). Particles accounted for a high share of activity in runoff for the AhR assay (>70 % for majority of samples), whereas for the other assays the share was more variable. Results of this study suggest that chemicals present in the roof runoff may cause biological effects that are higher compared to drinking water samples and in similar ranges to those previously reported for stormwater from larger catchments for oxidative stress and AhR activity.

Adoption of sensor-based on-site monitoring in urban-water engineering enables the collection of high-resolution data, but malfunctions and environmental disturbances can pose a serious challenge in uptake and use, as they result in data gaps and loss of information. One solution to handle these data gaps is the use of machine-learning (ML) algorithms. This study compared widely used deterministic interpolation methods and data-driven methods – particularly neural networks – for reconstructing extended data gaps in urban runoff quality time series. The analysis is based on runoff water quality data from a small and relatively homogeneous section of an urban road. While simpler interpolation methods achieved high overall accuracy, ML models outperformed the simpler methods during highly dynamic periods – those that are typically more challenging to capture and often of particular interest in stormwater management contexts. The findings highlight both the limitations and the potential of each approach, emphasizing the particular importance of understanding context and data conditions when selecting the most suitable method for the task.

Stormwater bioretention systems are primarily designed to manage stormwater quality as well as restore more natural hydrology during less intense rainfall events. Thus, design modifications are required to manage intense rain events resulting from climate change. This study examined 54 bioretention system design combinations by varying four design factors: filter media fraction of the total soil depth (i.e. filter media + drainage gravel layer), hydraulic conductivity of the filter media, ponding depth, and storage connection diverting surface water to the storage layer through a pipe. Using a calibrated field-scale Storm Water Management Model (SWMM), the performance of these designs was assessed for volume reduction during common rain events, peak flow reduction during a 10-year return interval rain event (180 mm, 1 h), and the number of overflows in a year. Using a storage connection consistently improved performance, enhancing volume reduction by up to 32% and reducing overflow events (up to 11 of 29), as expected since the storage layer provides additional high-porosity detention. Higher filter media fractions (85%) improved volume reduction during common rain events by approximately 50%. Interestingly, lower fractions (15%) were more beneficial for reducing overflow events (in about 17 out of 29 events annually), suggesting that higher porosity and drainage can sometimes prevent excessive surface ponding. These findings underscore the potential of bioretention system designs to enhance climate resilience and emphasize the need for a balanced approach that improves volume reduction during common rain events while also reducing overflow events during high-intensity rainfall.

As urbanization accelerates, stormwater management in cities has shifted from focusing strictly on water quantity to addressing water quality. Traditionally implemented systems, such as stormwater ponds, while offering effective solutions, often require large land areas to implement, making them impractical for dense urban environments. Underground stormwater systems, like EcoVault, offer a more compact solution; however, they lack scientific studies under real-world conditions to prove their effectiveness in treating pollutants. This study evaluates the treatment performance of two parallel EcoVault systems with the same design, consisting of a sedimentation step and a filtration step. These facilities were retrofitted into two different stormwater sewer networks draining two urban catchments. The systems were assessed for their ability to treat total suspended solids, metals, nutrients, and organic pollutants from urban runoff. Over 15 rain events, the average total suspended solids (TSS) removal rate was 40% for EcoVault A and 46% for EcoVault B. The removal rates for metals varied, with EcoVault B showing better performance for average metal treatment (53% for Cu and 58% for Zn). However, neither EcoVault system removed dissolved metals, often with an increase of dissolved metal concentration in the effluent. The filtration step did not contribute to pollutant treatment, likely due to clogging and high hydraulic loading rates. The study highlighted the potential of underground stormwater treatment in areas with limited space availability, while identifying challenges such as treatment of dissolved pollutants.

This study investigated the relationship between biological effects and contamination profiles in sediments from 17 stormwater sedimentation facilities across four Swedish municipalities. Sediment extracts were examined using a battery of in vitro bioassays targeting five modes of action: aryl hydrocarbon (AhR), estrogenic (ER), androgenic (AR), antiandrogenic (AntiAR) receptors, and oxidative stress (Nrf2) activities, along with cytotoxicity. Significant differences in biological activities across cities aligned with patterns in previously characterized profiles of 259 urban-sourced organic substances. Concentrations of bioactive substances correlated positively with biological activities; however, they explained only a limited fraction (typically <10%) of the observed effects, suggesting the influence of unmonitored substances. Among the examined substances, polycyclic aromatic hydrocarbons and alkylphenols were the most prominent drivers of chemically explained biological activities across end points. A masking effect between AR and AntiAR was revealed, with negative correlations between AR responses and agonist concentrations indicating dominance of antiandrogenic activity. Cytotoxicity rankings across samples did not align with acute toxicity previously measured on the same sediments using Microtox. However, overall cytotoxicity correlated significantly with chemical contamination indicators. These findings highlight the relevance of effect-based tools in capturing mixture effects in stormwater sediments and support their integration alongside chemical analysis in sediment quality assessments.

Urban areas are affected by anthropogenic activities that cause pollutant load on receiving water bodies. Stormwater bioretention are popular and effective in removing pollutants. The main water quality treatment processes are filtration and adsorption in the top layer (0-10 cm) of the filters. So far, few in-field studies have evaluated effects of cold climate and de-icing salt on bioretention for treating metals. Thus, a comprehensive study of total and dissolved metal removal (Cd, Cr, Cu, Ni, Pb and Zn) in a bioretention system for management of road runoff from the European highway E4 was carried out. Three different filter configurations were examined: a sand filter (SF), a vegetated sand filter (BF) and a vegetated sand filter with chalk additive (BFC). The results show a general trend of significant metal removal in all three filters, BFC, BF and SF, both under impact of high (Cl⁻ > 210 mg/l) and low (Cl⁻ ≤ 98.2 mg/l) chloride concentrations. For total metal concentrations, the results show that removal was most efficient in filter BFC, then BF and least efficient in filter SF. For metals such as Cu, Ni and Pb, this may indicate that better removal could be achieved using vegetated filters with chalk additives that affect pH. For dissolved metals, there is a tendence of Cr, Cu, Ni, Pb and Zn removal in filter BFC when lower chloride impact. With higher chlorides concentrations, there tended to be a release of metals from the filters.

Modeling bioretention systems using the Storm Water Management Model (SWMM) is a common practice. However, there is limited observational evidence to determine how accurately and reliably the model performs. This study compared the measured outflow from the underdrain of four bioretention systems with SWMM modeling results, providing critical insights into the models’ applicability and limitations. Results indicated that prior to calibration, the SWMM captures peak flow characteristics and the shape of hydrographs reasonably well. However, calibration improved the performance for flow peaks, resulting in better Nash-Sutcliffe efficiency, for example, from 0.25 to 0.70 in bioretention cell S1. Also, the uncertainty in outflow predictions varied between different bioretention systems, with the width of the uncertainty band varying by up to a factor 2.5 between the systems with the most and least uncertainty in the model predictions. This study found SWMM to be a reliable tool for modeling bioretention hydrology, with reliability varying between systems and improving notably after calibration.

Changes in stormwater, snowmelt and copper roof runoff quality on circulation through seven different pipe materials (polyvinyl chloride (PVC), polypropylene (PP), glassliner (GL), feltliner (FL), galvanized steel (GS), new concrete (NC) and old concrete (OC)) are explored for a range of parameters including total, dissolved and truly dissolved metals. Circulation through all pipe materials led to increases in pH, with levels of other basic physico-chemical parameters relatively unaffected. Both increases and decreases in all Cu, Pb and Zn fractions were observed for PVC, PP, FL and GL pipes whilst circulation through GS increased total, dissolved and truly dissolved Zn. In contrast, circulation through NC and OC led to decreases in all metal fractions (with some exceptions for dissolved and truly dissolved Cu). Overall, results indicate that contact with pipe materials can impact stormwater pollutant concentrations, and thus has implications for achieving compliance with the EU Water Framework Directive.

Exterior building materials contribute to stormwater runoff pollution but knowledge of how ecological impacts may vary between different types of building materials remains limited. This study combined chemical analyses of runoff from seven different building surface materials with toxicological response analyses as a contribution to addressing this knowledge gap. Results indicate a range of inorganic (e.g. copper, zinc) and organic substances (e.g. diisononyl phthalate, DINP, and nonylphenol) are mobilised by runoff, with concentrations varying between differing materials and rain events by up to three orders of magnitude. Toxicological analysis involving algae, daphnids and fish embryos, indicated that acute and chronic effects also varied between building materials and events, as well as species. For example, copper sheet runoff (maximum concentration 2900 µg/L) exhibited the strongest acute toxic effect on all three test organisms (≥80 % effect irrespective of event and species). Chronic reproductive effects were reported for Daphnia magna on exposure to PVC and bitumen felt roof runoff. Results show that runoff from several building surface materials commonly found in urban areas can cause acute and chronic effects on aquatic organisms. Findings could support users to identify environmentally sustainable building materials as a contribution to reducing pollution emissions from cities to receiving waters.