Abstract: Antibiotics such as sulfamethoxazole (SFX) are environmentally hazardous after being released into the aquatic environment and challenges remain in the development of engineered prevention strategies. In this work, a mathematical model was developed to describe and evaluate cometabolic biotransformation of SFX and its transformation products (TPs) in an enriched ammonia oxidizing bacteria (AOB) culture. The growth-linked cometabolic biodegradation by AOB, non-growth transformation by AOB and nongrowth transformation by heterotrophs were considered in the model framework. The production of major TPs comprising 4-Nitro-SFX, Desamino-SFX and N-4-Acetyl-SFX was also specifically modelled. The validity of the model was demonstrated through testing against literature reported data from extensive batch tests, as well as from long-term experiments in a partial nitritation sequencing batch reactor (SBR) and in a combined SBR + membrane aerated biofilm reactor performing nitrification/denitrification. Modelling results revealed that the removal efficiency of SFX increased with the increase of influent ammonium concentration, whereas the influent organic matter, hydraulic retention time and solid retention time exerted a limited effect on SFX biodegradation with the removal efficiencies varying in a narrow range. The variation of influent SFX concentration had no impact on SFX removal efficiency. The established model framework enables interpretation of a range of experimental observations on SFX biodegradation and helps to identify the optimal conditions for efficient removal. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: To properly estimate and manage pesticide occurrence in urban rivers, it is essential, but often highly challenging, to identify the key pesticide transport pathways in association to the main sources. This study examined the concentration-discharge hysteresis behaviour (hysteresis analysis) for three pesticides and the parent-metabolite concentration dynamics for two metabolites at sites with different levels of urban influence in a mixed land use catchment (25 km(2)) within the Swiss Greifensee area, aiming to identify the dominant pesticide transport pathways. Combining an adapted hysteresis classification framework with prior knowledge of the field conditions and pesticide usage, we demonstrated the possibility of using hysteresis analysis to qualitatively infer the dominant pesticide transport pathway in mixed land-use catchments. The analysis showed that hysteresis types, and therefore the dominant transport pathway, vary among pesticides, sites and rainfall events. Hysteresis loops mostly correspond to dominant transport by flow components with intermediate response time, although pesticide sources indicate that fast transport pathways are responsible in most cases (e.g. urban runoff and combined sewer overflows). The discrepancy suggests the fast transport pathways can be slowed down due to catchment storages, such as topographic depressions in agricultural areas, a wastewater treatment plant (WWTP) and other artificial storage units (e.g. retention basins) in urban areas. Moreover, the WWTP was identified as an important factor modifying the parent-metabolite concentration dynamics during rainfall events. To properly predict and manage pesticide occurrence in catchments of mixed land uses, the hydrological delaying effect and chemical processes within the artificial structures need to be accounted for, in addition to the catchment hydrology and the diversity of pesticide sources. This study demonstrates that in catchments with diverse pesticide sources and complex transport mechanisms, the adapted hysteresis analysis can help to improve our understanding on pesticide transport behaviours and provide a basis for effective management strategies.(C) 2017 Elsevier Ltd. All rights reserved.