Erik Lindblom

Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs.

The objective of this paper was to show the potential additional insight that result from adding greenhouse gas (GHG) emissions to plant performance evaluation criteria, such as effluent quality (EQI) and operational cost (OCI) indices, when evaluating (plant-wide) control/operational strategies in wastewater treatment plants (WWTPs). The proposed GHG evaluation is based on a set of comprehensive dynamic models that estimate the most significant potential on-site and off-site sources of CO₂, CH₄ and N₂O. The study calculates and discusses the changes in EQI, OCI and the emission of GHGs as a consequence of varying the following four process variables: (i) the set point of aeration control in the activated sludge section; (ii) the removal efficiency of total suspended solids (TSS) in the primary clarifier; (iii) the temperature in the anaerobic digester; and (iv) the control of the flow of anaerobic digester supernatants coming from sludge treatment. Based upon the assumptions built into the model structures, simulation results highlight the potential undesirable effects of increased GHG production when carrying out local energy optimization of the aeration system in the activated sludge section and energy recovery from the AD. Although off-site CO₂ emissions may decrease, the effect is counterbalanced by increased N₂O emissions, especially since N₂O has a 300-fold stronger greenhouse effect than CO₂. The reported results emphasize the importance and usefulness of using multiple evaluation criteria to compare and evaluate (plant-wide) control strategies in a WWTP for more informed operational decision making.

Uncertainty-based calibration and prediction with a stormwater surface accumulation-washoff model based on coverage of sampled Zn, Cu, Pb and Cd field data

A dynamic conceptual and lumped accumulation wash-off model (SEWSYS) is uncertainty-calibrated with Zn, Cu, Pb and Cd field data from an intensive, detailed monitoring campaign. We use the generalized linear uncertainty estimation (GLUE) technique in combination with the Metropolis algorithm, which allows identifying a range of behavioral model parameter sets. The small catchment size and nearness of the rain gauge justified excluding the hydrological model parameters from the uncertainty assessment. Uniform, closed prior distributions were heuristically specified for the dry and wet removal parameters, which allowed using an open not specified uniform prior for the dry deposition parameter. We used an exponential likelihood function based on the sum of squared errors between observed and simulated event masses and adjusted a scaling factor to cover 95% of the observations within the empirical 95% model prediction bounds. A positive correlation between the dry deposition and the dry (wind) removal rates was revealed as well as a negative correlation between the wet removal (wash-off) rate and the ratio between the dry deposition and wind removal rates, which determines the maximum pool of accumulated metal available on the conceptual catchment surface. Forward Monte Carlo analysis based on the posterior parameter sets covered 95% of the observed event mean concentrations, and 95% prediction quantiles for site mean concentrations were estimated to 470 μg/l ± 20% for Zn, 295 μg/l ± 40% for Cu, 20 μg/l ± 80% for Pb and 0.6 μg/l ± 35% for Cd. This uncertainty-based calibration procedure adequately describes the prediction uncertainty conditioned on the used model and data, but seasonal and site-to-site variation is not considered, i.e. predicting metal concentrations in stormwater runoff from gauged as well as ungauged catchments with the SEWSYS model is generally more uncertain than the indicated numbers.

Examining the biodegradation of endocrine disrupting bisphenol A and nonylphenol in WWTPs

The aim of this work was to examine biodegradation of the endocrine disrupting chemicals bisphenol A (BPA) and nonylphenol (NP) in activated sludge. Experiments were performed in a pilot wastewater treatment plant (WWTP) in Copenhagen, Denmark. During standard operation the BPA concentration was halved whereas the NP concentration was unchanged. Step-addition experiments showed that biomass adaptation to increased BPA and NP concentrations took 10 to more than 40 days depending on temperature, hydraulic retention time, and pre-exposure of the biomass. Mass-balance experiments showed that above 99% of the dosed BPA and 90% of the dosed NP is removed by biodegradation at steady-state. Batch experiments showed that BPA biodegradation occur solely under aerobic conditions. The work is believed to add vital knowledge to our understanding of parameters and processes governing biodegradation of EDCs in WWTPs.

Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data

The objective of this paper is to demonstrate the full-scale feasibility of the phenomenological dynamic influent pollutant disturbance scenario generator (DIPDSG) that was originally used to create the influent data of the International Water Association (IWA) Benchmark Simulation Model No. 2 (BSM2). In this study, the influent characteristics of two large Scandinavian treatment facilities are studied for a period of two years. A step-wise procedure based on adjusting the most sensitive parameters at different time scales is followed to calibrate/validate the DIPDSG model blocks for: 1) flow rate; 2) pollutants (carbon, nitrogen); 3) temperature; and, 4) transport. Simulation results show that the model successfully describes daily/weekly and seasonal variations and the effect of rainfall and snow melting on the influent flow rate, pollutant concentrations and temperature profiles. Furthermore, additional phenomena such as size and accumulation/flush of particulates of/in the upstream catchment and sewer system are incorporated in the simulated time series. Finally, this study is complemented with: 1) the generation of additional future scenarios showing the effects of different rainfall patterns (climate change) or influent biodegradability (process uncertainty) on the generated time series; 2) a demonstration of how to reduce the cost/workload of measuring campaigns by filling the gaps due to missing data in the influent profiles; and, 3) a critical discussion of the presented results balancing model structure/calibration procedure complexity and prediction capabilities.

Dynamic experiments with high bisphenol-A concentrations modelled with an ASM model extended to include a separate XOC degrading microorganism.

The perspective of this work is to develop a model, which can be used to better understand and optimize wastewater treatment plants that are able to remove xenobiotic organic compounds (XOCs) in combination with removal of traditional pollutants. Results from dynamic experiments conducted with the endocrine disrupting XOC bisphenol-A (BPA) in an activated sludge process with real wastewater were used to hypothesize an ASM-based process model including aerobic growth of a specific BPA-degrading microorganism and sorption of BPA to sludge. A parameter estimation method was developed, which simultaneously utilizes steady-state background concentrations and dynamic step response data, as well as conceptual simplifications of the plant configuration. Validation results show that biodegradation of BPA is sensitive to operational conditions before and during the experiment and that the proposed model structure is capable of capturing important characteristics of the observed BPA removal, thus increasing the potential for generalizing knowledge obtained from plant specific experiments.

Dynamic modelling of nitrous oxide emissions from three Swedish sludge liquor treatment systems.

The objective of this paper is to model the dynamics and validate the results of nitrous oxide (N2O) emissions from three Swedish nitrifying/denitrifying, nitritation and anammox systems treating real anaerobic digester sludge liquor. The Activated Sludge Model No. 1 is extended to describe N2O production by both heterotrophic and autotrophic denitrification. In addition, mass transfer equations are implemented to characterize the dynamics of N2O in the water and the gas phases. The biochemical model is simulated and validated for two hydraulic patterns: (1) a sequencing batch reactor; and (2) a moving-bed biofilm reactor. Results show that the calibrated model is partly capable of reproducing the behaviour of N2O as well as the nitritation/nitrification/denitrification dynamics. However, the results emphasize that additional work is required before N2O emissions from sludge liquor treatment plants can be generally predicted with high certainty by simulations. Continued efforts should focus on determining the switching conditions for different N2O formation pathways and, if full-scale data are used, more detailed modelling of the measurement devices might improve the conclusions that can be drawn.

Dose-response effects of omega-3 on platelet aggregation: an observational study

Objective This study aimed to evaluate the dose-response effects of supplemental omega-3 fatty acids on platelet function in healthy volunteers. Methods Twelve healthy volunteers ingested a normal supplemental dose of 1260 mg omega-3 fatty acids daily for 5 days, followed by a high dose of 2520 mg daily for another 5 days. Multiple electrode aggregometry (MEA) with four different agonists was used to measure platelet aggregation before and after the normal- and high-dose regimes. In vitro spiking using physiological doses of omega-3 fatty acids was also performed to determine whether MEA is capable of detecting a platelet-inhibiting effect due to omega-3 fatty acids. Results There were no differences in platelet aggregation measured by the MEA assay in healthy volunteers after intake of either the normal or high dose of omega-3 fatty acids. In the in vitro experiment, a platelet-inhibiting effect of omega-3 fatty acids was shown by an arachidonic acid agonist in MEA . Conclusions Supplemental omega-3 fatty acids do not evoke their positive health effects through inhibition of platelet aggregation measurable with MEA.

Model Reduction Using Neural Networks Applied To The Modeling Of Integrated Urban Wastewater Systems

Simulation of the integrated urban wastewater system is a computationally-demanding task, and performing long-term simulations consequently takes a considerable time. Reduction of simulation times can be achieved by speeding up one or more of the submodels of the integrated system. In this paper the use of a fast neural network model instead of the mechanistic model of the wastewater treatment plant (WWTP) is proposed for this purpose. The neural network is trained on a sequence of treatment plant input/output data generated by the mechanistic model of the WWTP, i.e. it is a reduced model of the original WWTP model. As a result of model substitution a reduction of the simulation time by a factor of 23 was achieved. The results presented in this paper show that the errors introduced by the WWTP model substitution are of an acceptable level, confirming the practical usefulness of the proposed method.