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Abstract. A compilation of data from several cruises between 1998 and 2013 was used to derive polynomial fits that estimate total alkalinity (A T ) and total dissolved inorganic carbon (C T ) from measurements of salinity and temperature in the Mediterranean Sea surface waters. The optimal equations were chosen based on the 10-fold cross-validation results and revealed that second-and third-order polynomials fit the A T and C T data respectively. The A T surface fit yielded a root mean square error (RMSE) of ± 10.6 µmol kg −1 , and salinity and temperature contribute to 96 % of the variability. Furthermore, we present the first annual mean C T parameterization for the Mediterranean Sea surface waters with a RMSE of ± 14.3 µmol kg −1 . Excluding the marginal seas of the Adriatic and the Aegean, these equations can be used to estimate A T and C T in case of the lack of measurements. The identified empirical equations were applied on the 0.25 • climatologies of temperature and salinity, available from the World Ocean Atlas 2013. The 7-year averages (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) showed that A T and C T have similar patterns with an increasing eastward gradient. The variability is influenced by the inflow of cold Atlantic waters through the Strait of Gibraltar and by the oligotrophic and thermohaline gradient that characterize the Mediterranean Sea. The summer-winter seasonality was also mapped and showed different patterns for A T and C T . During the winter, the A T and C T concentrations were higher in the western than in the eastern basin. The opposite was observed in the summer where the eastern basin was marked by higher A T and C T concentrations than in winter. The strong evaporation that takes place in this season along with the ultra-oligotrophy of the eastern basin determines the increase of both A T and C T concentrations.

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The composition of the air has been visibly altered as a result of human activity, resulting in what we term air pollution. It is no longer necessary to prove the effects on ecosystems and human health. Under these conditions, governments all around the world are working to address this issue, notably in the area of real-time air quality monitoring. The implementation of a data provider is a necessary step in achieving this goal. In that case, this study presents a hardware and software solution to provide a low-cost deployable device to acquire environmental data related to AP such as CO, CO₂, NH₃, and NO₂, along with temperature and humidity. In addition to an user interface development, a complete circuit layout and a set of software criteria are set up to ensure a reliable implementation, data collection, and network communications. The results demonstrated that the device is capable of effectively obtaining real-time data. The analysis results indicate a link between environmental conditions and parameter values. This system deployment will ultimately contribute to providing a more elaborate mapped data distribution, according to a better understanding of our environment.<br /><br />