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In this work, a wireless data acquisition system for seismic noise array measurements is presented. The developed system is composed of a series of nodes and a central server arranged in a point-to-multipoint topology. The nodes consist of a CC3200 microcontroller, an analog-to-digital converter, and a low-noise conditioning circuit designed specifically to register seismic noise, and which is connected to the seismic sensor. As a server, a Raspberry Pi 4B has been used that will receive the samples from the nodes via Wi-Fi and will save them in files. It also incorporates a Web interface developed with JavaScript node.js technology that allows to configure the number of nodes as well as different options, to start and stop the records, and to view in real time the different signals received from the nodes. The system can be deployed anywhere since each of the nodes use independent batteries as a power supply. In addition, it is possible to operate the system remotely if internet connectivity is available. The prototype has been tested in four different locations in the Alicante province (southeast Spain), demonstrating its suitability for seismic noise array measurements. [ABSTRACT FROM AUTHOR]

The present study evaluates ground-based downward surface shortwave radiation (R s) over the coastal region of Alicante (Southeastern Spain). Hourly measurements collected over the eleven-year period 2010-2020 are used. Two weather stations located over the region capital, Alicante, have been selected as representative of urban and suburban typologies. Two additional weather stations far from the city have been selected representing rural typologies. R s is significantly reduced over the urban station during the morning hours within the winter season compared to the observations recorded over the suburban and rural stations, with a global mean difference of -81 and -120 W/m2 at 10 LT, respectively. However, no significant differences are obtained during the midday sun, with a global mean difference of -20 W/m2 between the urban and rural stations. With the aim of explaining these differences, the current paper investigates the relationship between R s and different air pollutants: NO x , SO 2 , and fine particulate matter (PM 2.5 and PM 10) as well as the wind field measured at the urban and suburban stations. The results found in this work point towards a close relationship between R s and NO x concentrations annual cycles, which are also influenced by the prevailing wind circulations observed over the study area. A global mean NO x concentration of 107 µg/m3 is observed over the urban station at 10 LT during the winter season. In contrast, these high concentrations are significantly reduced over the suburban station, with global mean value of 40 µg/m3 at 10 LT, for this period of the year. [Display omitted] [ABSTRACT FROM AUTHOR]