The effects of sulfathiazole (STA) on Escherichia coli with glucose as a growth substrate was investigated to elucidate the effect-based reaction of sulfonamides in bacteria and to identify biomarkers for bacterial uptake and effect. The predominant metabolite was identified as pterine-sulfathiazole by LC-high resolution mass spectrometry. The formation of pterine-sulfathiazole per cell was constant and independent of the extracellular STA concentrations, as they exceeded the modeled half-saturation concentration KMS of 0.011 μmol L−1. The concentration of the dihydrofolic acid precursor para-aminobenzoic acid (pABA) increased with growth and with concentrations of the competitor STA. This increase was counteracted for higher STA concentrations by growth inhibition as verified by model simulation of pABA dynamics. The EC value for the inhibition of pABA increase was 6.9 ± 0.7 μmol L−1 STA, which is similar to that calculated from optical density dynamics indicating that pABA is a direct biomarker for the SA effect.

The Intermediate Dynamic Model for Metals (IDMM) is a model for prediction of the pools of metals (Ni, Cu, Zn, Cd, Pb) in topsoils of catchments resulting from deposition of metals from the atmosphere. We used the model to simulate soil metal pools from 1400 onwards in ten UK catchments comprising semi-natural habitats, and compared the results with present day observations of soil metal pools. Generally the model performed well in simulating present day pools, and further improvements were made to simulations of Ni, Cu, Zn and Cd by adjusting the strength of metal adsorption to the soils. Some discrepancies between observation and prediction for Pb appeared to be due either to underestimation of cumulative deposition, or to overestimation of the metal pool under ‘pristine’, pre-industrial conditions. The IDMM provides a potential basis for large scale assessment of metal dynamics in topsoils.

A regional chemical transport model was implemented to simulate the Respirable Suspended Particulate Matter (PM10) concentration in order to study the impact of long–range transport of air pollutants over megacity Delhi with due consideration to different geographical domains extending up to entire Asia and corresponding emissions. PM10 concentration levels over megacity Delhi remain persistently high, often exceeding the ambient air quality standards. A chemical transport model namely Weather Research and Forecasting (WRF) model Version 3.2 coupled with chemistry module (WRF/Chem) was utilized with nested domains for this purpose, subsequent to model evaluation for the period during June, 2010 that includes extremely high PM10 concentrations. A highly satisfactory model performance was interpreted based on the several statistical parameters as per the current state of the science and their recommended values. Based on model simulations representing different geographical domains encompassing Asia, India, North India and Delhi and their corresponding emissions, it was clearly reflected that contributions due to emissions of the megacity Delhi alone is 11%–41% and thus remaining (59%–89%) proportion is expected to be contributed from the sources outside of the Delhi region which is significant. It is demonstrated that the WRF/Chem model performs well for a sub–tropical urban airshed though there is scope of improvement for the consistent under– prediction with more refined emission inventories. Nevertheless, this model could be implemented to assess the long– range transport of pollutants so as to adequately address the influence of the remote sources outside the urban airshed. This can serve as an important tool towards planning and implementing the regulatory policies for air pollution control for more effective outcomes.

As an unwanted by-product in the power plants, cooling water (CW) discharge may induce harmful effects on the coastal environment. In this paper, to accurately predict the CW transport in the Daya Bay, China, we develop a three-dimensional hydrodynamic and temperature model to simulate the transport of the CW from nuclear power plant into coastal waters. Specifically, we use the flow velocity produced by the model to locate Lagrangian coherent structures (LCSs) hidden in ocean surface currents. Result show that the transport of the CW is quite strongly tied to the simulated LCSs. The LCSs constitute fluid barriers that accurately demarcate potential pathway for CW transport. Thus, LCSs in velocity fields from a coastal model is an extremely useful way to monitor and interpret the transport of CW.

On June 4 and 17, 2011, separate oil spill accidents occurred at two oil platforms in the Bohai Sea, China. The oil spills were subsequently observed on different types of satellite images including SAR (Synthetic Aperture Radar), Chinese HJ-1-B CCD and NASA MODIS. To illustrate the fate of the oil spills, we performed two numerical simulations to simulate the trajectories of the oil spills with the GNOME (General NOAA Operational Modeling Environment) model. For the first time, we drive the GNOME with currents obtained from an operational ocean model (NCOM, Navy Coastal Ocean Model) and surface winds from operational scatterometer measurements (ASCAT, the Advanced Scatterometer). Both data sets are freely and openly available. The initial oil spill location inputs to the model are based on the detected oil spill locations from the SAR images acquired on June 11 and 14. Three oil slicks are tracked simultaneously and our results show good agreement between model simulations and subsequent satellite observations in the semi-enclosed shallow sea. Moreover, GNOME simulation shows that the number of ‘splots’, which denotes the extent of spilled oil, is a vital factor for GNOME running stability when the number is less than 500. Therefore, oil spill area information obtained from satellite sensors, especially SAR, is an important factor for setting up the initial model conditions.

Marine water quality monitoring is performed for compliance with regulatory issues, trend detection, model validation and assessment of the effectiveness of adopted policies. As the end users are managers and policy makers, the objectives should be of practical interest and the answers should reduce the uncertainty concerning environmental impact, supporting planning and decision making. Simple and clearcut answers on environmental issues require synthesis of the field information using statistics, simulation models and multiple criteria analysis (MCA). Statistics is easy to apply whereas simulation models enable researchers to forecast future trends as well as test different scenarios. MCA allows the co-estimation of socio-economic variables providing a compromise between scientists’ and policy makers’ priorities. In addition, stakeholders and the public have the right to know and participate. This article reviews marine water quality monitoring principles, design and data analysis procedures. A brief review of international conventions of regional seas is also included.

A flat plate serpentine reactor modified from ultraviolet disinfection pool in municipal wastewater treatment plants was developed for the removal of 17-ethinylestradiol (EE2) for the first time. The photocatalytic degradation performance of EE2 was investigated in this serpentine reactor under different conditions such as inlet concentrations, loaded catalyst concentrations, incident radiations fluxes, and flow velocities. More than 98 % of EE2 was removed under certain conditions within 120 min. An integrated model including a six-flux adsorption–scattering model and a modified flow diffusion model was established to investigate the effect of radiation field and flow velocities, respectively. A satisfactory agreement was observed between the model simulation and experimental results, showing a potential for design and scale-up of photocatalytic reactor for wastewater treatment.