1,720,982 research outputs found
Impact on air quality of the covid-19 lockdown in the urban area of Palermo (Italy)
Full text linkAt the end of 2019, the first cases of coronavirus disease (COVID-19) were reported in Wuhan, China. Thereafter, the number of infected people increased rapidly, and the outbreak turned into a national crisis, with infected individuals all over the country. The COVID-19 global pandemic produced extreme changes in human behavior that affected air quality. Human mobility and production activities decreased significantly, and many regions recorded significant reductions in air pollution. The goal of our investigation was to evaluate the impact of the COVID-19 lockdown on the concentrations of the main air pollutants in the urban area of Palermo (Italy). In this study, the trends in the average concentrations of CO, NO2, O3, and PM10 in the air from 1 January 2020 to 31 July 2020 were compared with the corresponding average values detected at the same monitoring stations in Palermo during the previous five years (2015–2019). During the lockdown period (10 March–30 April), we observed a decrease in the concentrations of CO, NO2, and particulate matter (PM)10, calculated to be about 51%, 50%, and 45%, respectively. This confirms that air pollution in an urban area is predominantly linked to vehicular traffic
A Stochastic Sigma Model for GLONASS Satellite Pseudorange
No full textThe GLONASS (Global Navigation Satellite System) is a satellite positioning system able to provide various number of air, marine, and any other type of users with all-weather three-dimensional positioning, velocity measuring and timing anywhere in the world or near-earth space.
As known, a GLONASS receiver performs passive measurements of pseudoranges and pseudorange rate of at least four GLONASS satellites as well as receives and processes navigation messages contained within navigation signals of the satellites. The navigation message supplies the satellites position both in space and in time. Combined processing of the measurements and the navigation messages of the four (three) GLONASS satellites allows user to determine three (two) position coordinates, three (two) velocity vector constituents, and to refer user time scale to the national reference time UTC(SU).
The purpose of this work is to define a stochastic model for pseudorange variances of GLONASS satellites able to provide its estimation. This evaluation is made for all satellites as a function of the elevation, independently of the user position, starting from real data. To achieve this goal a suitable software tool MATLAB® is developed. The tool is able to create a GLONASS sky from the broadcast ephemeris, to compute the pseudorange error and to process it.
The used data are extracted from observation and navigation RINEX files (containing both GPS and GLONASS measures)
From the known receiver position and the computed satellite coordinates, the geometric range is obtained and compared with the pseudorange measurement, in order to achieve the pseudorange variance and build the model.
In order to validate the sigma stationary stochastic model, the results are compared with further data obtained from different stations.
The purpose of this work is the creation of a σ model particularly adapted in application as personal navigation device, characterized by the need of a real-time positioning and by a low computational power. The accuracy in real-time positioning can be improved, using a weighted least square (WLS) method for GNSS (GPS, GLONASS and in the future GALILEO or other feasible systems) measurements.
For GPS measurements, several suitable σ models for the WLS implementation are already in use; for GLONASS (or GLONASS-GPS together) the same is not available. So the need of studies about this topic
PANG-NAV: a tool for processing GNSS measurements in SPP, including RAIM functionality
No full textGlobal Navigation Satellite Systems (GNSSs) are theoretically able to provide accurate, three-dimensional, and continuous positioning to an unlimited number of users. An important shortcoming of GNSS is the lack of integrity, defined as the ability of a system to provide timely warnings in case of malfunction; this problem is especially felt in safety-of-life applications such as aviation. A common way to fill this gap is the use of Receiver Autonomous Integrity Monitoring (RAIM) techniques, which are able to provide integrity information by analyzing redundant measurements. A possible RAIM functionality is the ability to identify, and so discard, anomalous measurements; this functionality has made RAIM very useful also in case of severe signal degradation, such as in urban or dense vegetation areas, where blunders are common. PANG-NAV is a tool, developed by the PArthenope Navigation Group, able to process GNSS measurements (from RINEX files) in order to obtain a position solution. The core of PANG-NAV is the single point positioning (SPP) technique, including a RAIM functionality. A multi-constellation solution, with GPS and Galileo, can be provided. Both static processing and kinematic processing are possible, and in cases where ground truth is available, error analysis can be carried out
FTIR spectral analysis of PM10 and PM2.5 particulate matter over the urban area of Palermo (Italy) during normal days and Saharan events
No full textThe principal sources of particulate matter in Palermo urban area are gasoline and diesel-powered vehicles, domestic heating, resuspension of soil dust and a geogenic source which includes soil erosion, marine aerosol and sporadic Saharan events. Annual average PM10 and PM2.5 concentrations result 27.8±9.8 and 21.3±5.1g/m3. The highest mass levels, 246 and 65 g/m3 respectively for PM10 and PM2.5, were observed during Saharan events. For the present study, which uses the ATR-FTIR spectroscopy to provide insights on the chemical composition of airborne particulate matter, a total of 89 filters were collected: 13 PM10 filters from a sub-urban background station, 36 PM10 and 40 PM2.5 filters from a sampling site exposed to heavy traffic. ATR-FTIR spectra were aquired with a Tensor 27 (Bruker Optics) FTIR spectrometer operating in the infrared (370-7500 cm−1) region. After correction for the background spectrum all the analyzed spectra showed vibrational frequencies at 616 and 1088, 813 and 1352, 1414 cm-1, corresponding to SO42-, NO3- and NH4+ ions, respectively. The simultanea presence of these ions, confirmed by LC and UV-VIS techniques, suggests the formation of secondary particulate of ammonium nitrates and sulphates. The peak at 778 cm-1 was attributed to geogenic CO32- ions derived from erosion of local carbonate rocks. PO43- ions, identified by the peak at 535 cm-1, were detected in suburban samples as well as in urban samples and they are indicative of contamination from phosphate industries of North Africa although their origin from pollen grains cannot be ruled out. FTIR also identified several organic functional groups, although specific organic molecules could not be identified. The broad band in the aliphatic stretching region (2800–3000 cm-1) with sharp peaks at 2850, 2920 and 2952 cm-1, was attributed to aliphatic C-H vibrations. The urban filters exposed to SW and SE winds (from North Africa) are characterised by peaks at 913cm-1, 3620 and 3698 cm-1, indicative of OH-stretching in clay and also peaks at 3404 and 3545 cm-1 typical of gypsum
Mass levels, crustal component and trace elements in PM10 in Palermo, Italy.
No full textResults concerning the levels and elemental compositions of daily PM10 samples collected at four air quality monitoring
sites in Palermo (Italy) are presented. The highest mean value of PM10 concentrations (46 mgm 3, with a peak value of
158 mgm 3) was recorded at the Di Blasi urban station, and the lowest at Boccadifalco station (25 mgm 3), considered as a
sub-urban background station. Seventeen elements (Al, As, Ba, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, Pb, Sb, Sr, U, V, Zn) were
measured by ICP-MS. Al and Fe showed the highest concentrations, indicating the significant contribution of soil and
resuspended mineral particles to atmospheric PM10. Ba, Cr, Cu, Mn, Mo, Ni, Pb, Sb, V and Zn had higher concentrations
at the three urban sampling sites than at the sub-urban background station. Besides soil-derived particles, an R-mode
cluster analysis revealed a group of elements, Mo, Cu, Cr, Sb and Zn, probably related to non-exhaust vehicle emission,
and another group, consisting of Ba, As and Ni, which seemed to be associated both with exhaust emissions from road
traffic, and other combustion processes such as incinerators or domestic heating plants. The results also suggest that Sb, or
the association Sb–Cu–Mo, offers a way of tracing road traffic emissions
Implementation and Testing of EGNOS Full-Scale dynamic trials onboard HSC (High Speed Craft)
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Analisi del contenuto di metalli in traccia nella frazione PM10 del particolato atmosferico della città di Palermo.
No full textTime series of PM2.5, PM2.5–10, PM10 and their interrelationships in the airborne particulate matter from Palermo.
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