The objective of the study is to provide global grids (0.5°) of revised annual coefficients for the Priestley–Taylor (P-T) and Hargreaves–Samani (H-S) evapotranspiration methods after calibration based on the ASCE (American Society of Civil Engineers)-standardized Penman–Monteith method (the ASCE method includes two reference crops: short-clipped grass and tall alfalfa). The analysis also includes the development of a global grid of revised annual coefficients for solar radiation (R_s) estimations using the respective R_s formula of H-S. The analysis was based on global gridded climatic data of the period 1950–2000. The method for deriving annual coefficients of the P-T and H-S methods was based on partial weighted averages (PWAs) of their mean monthly values. This method estimates the annual values considering the amplitude of the parameter under investigation (ET_o and R_s) giving more weight to the monthly coefficients of the months with higher ET_o values (or R_s values for the case of the H-S radiation formula). The method also eliminates the effect of unreasonably high or low monthly coefficients that may occur during periods where ET_o and R_s fall below a specific threshold. The new coefficients were validated based on data from 140 stations located in various climatic zones of the USA and Australia with expanded observations up to 2016. The validation procedure for ET_o estimations of the short reference crop showed that the P-T and H-S methods with the new revised coefficients outperformed the standard methods reducing the estimated root mean square error (RMSE) in ET_o values by 40 and 25 %, respectively. The estimations of R_s using the H-S formula with revised coefficients reduced the RMSE by 28 % in comparison to the standard H-S formula. Finally, a raster database was built consisting of (a) global maps for the mean monthly ET_o values estimated by ASCE-standardized method for both reference crops, (b) global maps for the revised annual coefficients of the P-T and H-S evapotranspiration methods for both reference crops and a global map for the revised annual coefficient of the H-S radiation formula and (c) global maps that indicate the optimum locations for using the standard P-T and H-S methods and their possible annual errors based on reference values. The database can support estimations of ET_o and solar radiation for locations where climatic data are limited and it can support studies which require such estimations on larger scales (e.g. country, continent, world). The datasets produced in this study are archived in the PANGAEA database (https://doi.org/10.1594/PANGAEA.868808) and in the ESRN database (http://www.esrn-database.org or http://esrn-database.weebly.com).

The monitoring of micropollutants in water compartments, in particular pharmaceuticals and personal care products, has become an issue of increasing concern over the last decade. Their occurrence in surface and groundwater, raw wastewater and treated effluents, along with the removal efficiency achieved by different technologies, have been the subjects of many studies published recently. The concentrations of these contaminants may vary widely over a given time period (day, week, month, or year). In this context, this paper investigates the average concentration and removal efficiency obtained by adopting four different sampling modes: grab sampling, 24-h time proportional, flow proportional and volume proportional composite sampling. This analysis is carried out by considering three ideal micropollutants presenting different concentration curves versus time (day). It compares the percentage deviations between the ideal concentration (and removal efficiencies) and the differently measured concentrations (removal efficiencies) and provides hints as to the best sampling mode to adopt when planning a monitoring campaign depending on the substances under study. It concludes that the flow proportional composite sampling mode is, in general, the approach which leads to the most reliable measurement of concentrations and removal efficiencies even though, in specific cases, the other modes can also be correctly adopted.

The occurrence of micropollutants in wastewater is largely documented as well as the environmental risk posed by their residues in the aquatic environment. Many investigations have been carried out and plan to study and improve their removal efficiency in existing wastewater treatment plants. At the same time, efforts are being made to develop new technologies or upgrade existing ones to increase the removal of a selection of micropollutants. Due to the great variability in their chemical and physical properties, it would be advisable to find representative compounds or identify the factors which most influence the removal mechanisms under specific conditions. This study analyses the removal efficiencies of a great number of micropollutants in wastewater treated in a membrane bioreactor coupled with powdered activated carbon (PAC), which was the subject of a review article we have recently published. The main operational parameters (i.e. PAC dosage, PAC retention time and sludge retention time) and compound physico-chemical properties (i.e. octanol-water distribution coefficient, charge and molecular weight) were first selected on the basis of a dedicated screening step and then an attempt was carried out to clarify their influence on the removal of micropollutants from wastewater during its treatment. To this end, a statistical analysis, mainly based on exploratory methods (cluster analysis and principal component analysis) and regression analysis, was carried out to compare and discuss the different results published in the scientific literature included in the cited review article. It emerged, that, based on the collected dataset, micropollutant charge and LogD_ow seem to play the most important role in the removal mechanisms occurring in MBR coupled with PAC.