Antibiotic proliferation in the environment and their persistent nature is an issue of global concern as they induce antibiotic resistance threatening both human health and the ecosystem. Antibiotics have therefore been categorized as emerging pollutants. Fluoroquinolone (FQs) antibiotics are an emerging class of contaminants that are used extensively in human and veterinary medicine. The recalcitrant nature of fluoroquinolones has led to their presence in wastewater, effluents and water bodies. Even at a low concentration, FQs can stimulate antibacterial resistance. The main sources of FQ contamination include waste from pharmaceutical manufacturing industries, hospitals and households that ultimately reaches the wastewater treatment plants (WWTPs). The conventional WWTPs are unable to completely remove FQs due to their chemical stability. Therefore, the development and implementation of more efficient, economical, convenient treatment and removal technologies are needed to adequately address the issue. This review provides an overview of the technologies available for the removal of fluoroquinolone antibiotics from wastewater including adsorptive removal, advanced oxidation processes, removal using non-carbon based nanomaterials, microbial degradation and enzymatic degradation. Each treatment technology is discussed on its merits and limitations and a comparative view is presented on the choice of an advanced treatment process for future studies and implementation. A discussion on the commercialization potential and eco-friendliness of each technology is also included in the review. The importance of metabolite identification and their residual toxicity determination has been emphasized. The last section of the review provides an overview of the policy interventions and regulatory frameworks that aid in retrofitting antibiotics as a central key focus contaminant and thereby defining the discharge limits for antibiotics and establishing safe manufacturing practices.

The effects of atmospheric pollution on plant species richness (nₛₚ) are of widespread concern. We carried out a modelling exercise to estimate how nₛₚ in British semi-natural ecosystems responded to atmospheric deposition of nitrogen (Ndₑₚ) and sulphur (Sdₑₚ) between 1800 and 2010. We derived a simple four-parameter equation relating nₛₚ to measured soil pH, and to net primary productivity (NPP), calculated with the N14CP ecosystem model. Parameters were estimated from a large data set (n = 1156) of species richness in four vegetation classes, unimproved grassland, dwarf shrub heath, peatland, and broadleaved woodland, obtained in 2007. The equation performed reasonably well in comparisons with independent observations of nₛₚ. We used the equation, in combination with modelled estimates of NPP (from N14CP) and soil pH (from the CHUM-AM hydrochemical model), to calculate changes in average nₛₚ over time at seven sites across Britain, assuming that variations in nₛₚ were due only to variations in atmospheric deposition. At two of the sites, two vegetation classes were present, making a total of nine site/vegetation combinations. In four cases, nₛₚ was affected about equally by pH and NPP, while in another four the effect of pH was dominant. The ninth site, a chalk grassland, was affected only by NPP, since soil pH was assumed constant. Our analysis suggests that the combination of increased NPP, due to fertilization by Ndₑₚ, and decreased soil pH, primarily due to Sdₑₚ, caused an average species loss of 39% (range 23–100%) between 1800 and the late 20th Century. The modelling suggests that in recent years nₛₚ has begun to increase, almost entirely due to reductions in Sdₑₚ and consequent increases in soil pH, but there are also indications of recent slight recovery from the eutrophying effects of Ndₑₚ.

Small-scale experiments performed at SINTEF, Norway in 2011–12 led to the development of a modified Weber scaling algorithm. The algorithm predicts initial oil droplet sizes (d₅₀) from a subsea oil and gas blowout. It was quickly implemented in a high number of operational oil spill models used to predict fate and effect of subsea oil releases both in academia and in the oil industry.This paper presents experimental data from large-scale experiments generating oil droplet data in a more realistic multi-millimeter size range for a subsea blow-out. This new data shows a very high correlation with predictions from the modified Weber scaling algorithm both for untreated oil and oil treated by dispersant injection.This finding is opposed to earlier studies predicting significantly smaller droplets, using a similar approach for estimating droplet sizes, but with calibration coefficients that we mean are not representative of the turbulence present in such releases.

A coupled 3D hydrodynamic-ecological model was applied to the Santa Marta Coastal Area (SMCA, Colombian Caribbean) to provide insights into the role of external stressors (e.g. wastewater outfall and upwelling) on the water quality and benthic – pelagic coupling. The model was calibrated and validated based on benthic metabolic measurements, satellite–derived chlorophyll-a (Chl-a) and sea surface temperature (SST) maps, field and literature water quality data. The model was able to reproduce the complex dynamics and fast transitions of temperature, nutrients, and phytoplankton, including the stratification and mixing periods during the non-upwelling (NUPW) and upwelling (UPW) seasons. Wide and fast changes in the temperatures and the highly flushed environment prevented excess phytoplankton growth and nutrient accumulation in the benthic and pelagic compartments. The model proved to be a reliable research tool to analyze the interactive effects of upwelling and untreated wastewater on the functioning of a tropical bay.