Increasing levels of dissolved organic matter (DOM) in watercourses in the Northern hemisphere is mainly due to reduced acid rain, climate change, and changes in agricultural practices. However, their impacts vary in time and space. To predict how DOM respond to changes in environmental pressures we need to differentiate between allochthonous and autochthonous sources, as well as identify anthropogenic DOM. In this study we distinguish between allochthonous, autochthonous, and anthropogenic sources of DOM in a diverse watercourse network using DOM characterization tools and by assessing effects of land cover on water quality. Main sources of DOM are forests discharging allochthonous humic DOM, autochthonous fulvic DOM, and runoff from urban sites and fish farms with high levels of anthropogenic DOM rich in protein like material. Specific UV absorbency (sUVa) distinguish allochthonous DOM from autochthonous and anthropogenic DOM. Anthropogenic DOM differ from autochthonous fulvic DOM by containing elevated levels of protein like material. DOM from fishponds is distinguished from autochthonous and sewage DOM by having high sUVa. DOM characteristics thus provide valuable tools for deconvoluting the various sources of DOM allowing water resource managers to predict future trends in DOM and detect anthropogenic sources of DOM.

A thermodynamic analysis of population dynamics and of sustainability provides rigor to many important issues. In this work, the “system Society” is analysed in connection with the “system Environment” using an exergy metric, and the method includes an internalization of the Externalities (Capital, Labour, Environmental effects) conducted on the basis of a “system+ environment” balance. In this perspective, this study investigates the Late Pleistocene extinction of the Homo Neandertalensis, which took place in a geologically short time and in the presence of a competing species, the Homo Sapiens. The case in study is not trivial, and its choice not casual: in those times, the only factor that could lead to an advantage of one group over the other was their respective resource use intensity. A specific indicator, the Exergy Footprint, is here applied to measure the total amount of primary resources required to produce a certain (material or immaterial) commodity, including the resources needed for the physical survival of the individuals. On the basis of the available data, the results show that the EF of the Neandertal was higher than that of the Sapiens, and that, both species sharing the same ecological niche in a time of dwindling resources, the less frugal was also more fragile in an evolutionary sense.

The aim of this paper is to evaluate the surface concentration of nitrogen dioxide (NO2) inferred from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (S5P/TROPOMI) NO2 tropospheric column densities over Central Europe for two time periods, the summer of 2019 and the winter of 2019-2020. Simulations of the NO2 tropospheric vertical column densities and surface concentrations from the LOng-Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) chemical transport model are also applied in the methodology. More than two hundred in-situ air quality monitoring stations, reporting to the European Environment Agency (EEA) air quality database, are used to carry out comparisons with the model simulations and the space-borne inferred surface concentrations. Stations are separated into seven types (urban traffic, suburban traffic, urban background, suburban background, rural background, suburban industrial and rural industrial) in order to examine the strengths and shortcomings of the different air quality markers, namely the NO2 vertical column densities and NO2 surface concentrations. S5P/TROPOMI NO2 surface concentrations are inferred by multiplying the fraction of the satellite and model NO2 vertical column densities with the model surface concentrations. The estimated inferred TROPOMI NO2 surface concentrations are examined further with the altering of three influencing factors: the model vertical levelling scheme, the versions of the TROPOMI NO2 data and the air mass factors applied to the satellite and model NO2 vertical column densities. Overall, the inferred TROPOMI NO2 surface concentrations show a better correlation with the in-situ measurements for both time periods and all station types, especially for the industrial stations (R>0.6) in winter. The calculated correlation for background stations is moderate for both periods (R~0.5 in summer and R>0.5 in winter), whereas for traffic stations it improves in the winter (from 0.20 to 0.50). After the implementation of the air mass factors from the local model, the bias is significantly reduced for most of the station types, especially in winter for the background stations, ranging from +0.49% for the urban background to +10.37% for the rural background stations. The mean relative bias in winter between the inferred S5P/TROPOMI NO2 surface concentrations and the ground-based measurements for industrial stations is about -15%, whereas for traffic urban stations it is approximately -25%. In summertime, biases are generally higher for all station types, especially for the traffic stations (~ -75%), ranging from -54% to -30% for the background and industrial stations.