Stefano Parracino

New ground-based lidar enables volcanic CO2 flux measurements.

There have been substantial advances in the ability to monitor the activity of hazardous volcanoes in recent decades. However, obtaining early warning of eruptions remains challenging, because the patterns and consequences of volcanic unrests are both complex and nonlinear. Measuring volcanic gases has long been a key aspect of volcano monitoring since these mobile fluids should reach the surface long before the magma. There has been considerable progress in methods for remote and in-situ gas sensing, but measuring the flux of volcanic CO2—the most reliable gas precursor to an eruption—has remained a challenge. Here we report on the first direct quantitative measurements of the volcanic CO2 flux using a newly designed differential absorption lidar (DIAL), which were performed at the restless Campi Flegrei volcano. We show that DIAL makes it possible to remotely obtain volcanic CO2 flux time series with a high temporal resolution (tens of minutes) and accuracy (<30%). The ability of this lidar to remotely sense volcanic CO2 represents a major step forward in volcano monitoring, and will contribute improved volcanic CO2 flux inventories. Our results also demonstrate the unusually strong degassing behavior of Campi Flegrei fumaroles in the current ongoing state of unrest.

Interoperability solutions between smartphones and Wireless Sensor Networks

The work aims at discussing possible engineering solutions to guarantee the interoperability between smartphones and WSN under high mobility levels. The paper discusses an application scenario where some of the most interesting standards for WSNs can be effectively employed together with smartphones. The architectures supporting interoperable smartphone/WSN systems, considering network topology and functionalities of the nodes are presented together with current network solutions for interoperability.

Automatic localization of backscattering events due to particulate in urban areas

Particulate matter (PM), emitted by vehicles in urban traffic, can greatly affect environment air quality and have direct implications on both human health and infrastructure integrity. The consequences for society are relevant and can impact also on national health. Limits and thresholds of pollutants emitted by vehicles are typically regulated by government agencies. In the last few years, the interest in PM emissions has grown substantially due to both air quality issues and global warming. Lidar-Dial techniques are widely recognized as a costeffective alternative to monitor large regions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable, automatic monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi-Event Locator (UMEL), is applied to the problem of automatically indentifying the time location of peaks in Lidar measurements for the detection of particulate matter emitted by anthropogenic sources like vehicles. The method developed is based on Support Vector Regression and presents various advantages with respect to more traditional techniques. In particular, UMEL is based on the morphological properties of the signals and therefore the method is insensitive to the details of the noise present in the detection system. The approach is also fully general, purely software and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data acquired during an experimental campaign in the field in Rome.

Real-time vehicle emissions monitoring using a compact LiDAR system and conventional instruments: first results of an experimental campaign in a suburban area in southern Italy

Abstract. Urban air pollution causes deleterious effects on human health and the environment. To meet stringent standards imposed by the European Commission, advanced measurement methods are required. Remote sensing techniques, such as light detection and ranging (LiDAR), can be a valuable option for evaluating particulate matter (PM), emitted by vehicles in urban traffic, with high sensitivity and in shorter time intervals. Since air quality problems persist not only in large urban areas, a measuring campaign was specifically performed in a suburban area of Crotone, Italy, using both a compact LiDAR system and conventional instruments for real-time vehicle emissions monitoring along a congested road. First results reported in this paper show a strong dependence between variations of LiDAR backscattering signals and traffic-related air pollution levels. Moreover, time-resolved LiDAR data averaged in limited regions, directly above conventional monitoring stations at the border of an intersection, were found to be linearly correlated to the PM concentration levels with a correlation coefficient between 0.75 and 0.84.

Advanced signal processing based on support vector regression for lidar applications

The LIDAR technique has recently found many applications in atmospheric physics and remote sensing. One of the main issues, in the deployment of systems based on LIDAR, is the filtering of the backscattered signal to alleviate the problems generated by noise. Improvement in the signal to noise ratio is typically achieved by averaging a quite large number (of the order of hundreds) of successive laser pulses. This approach can be effective but presents significant limitations. First of all, it implies a great stress on the laser source, particularly in the case of systems for automatic monitoring of large areas for long periods. Secondly, this solution can become difficult to implement in applications characterised by rapid variations of the atmosphere, for example in the case of pollutant emissions, or by abrupt changes in the noise. In this contribution, a new method for the software filtering and denoising of LIDAR signals is presented. The technique is based on support vector regression. The proposed new method is insensitive to the statistics of the noise and is therefore fully general and quite robust. The developed numerical tool has been systematically compared with the most powerful techniques available, using both synthetic and experimental data. Its performances have been tested for various statistical distributions of the noise and also for other disturbances of the acquired signal such as outliers. The competitive advantages of the proposed method are fully documented. The potential of the proposed approach to widen the capability of the LIDAR technique, particularly in the detection of widespread smoke, is discussed in detail.

Early detection of volcanic hazard by lidar measurement of carbon dioxide

Abstract Volcanic gases give information on magmatic processes. In particular, anomalous releases of carbon dioxide precede volcanic eruptions. Up to now, this gas has been measured in volcanic plumes with conventional measurements that imply the severe risks of local sampling and can last many hours. For these reasons and for the great advantages of laser sensing, the thorough development of volcanic lidars has been undertaken at ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development). In fact, lidar profiling allows one to scan remotely volcanic plumes in a fast and continuous way, and with high spatial and temporal resolution. A differential absorption lidar instrument will be presented in this paper: BILLI (BrIdge voLcanic LIdar). It is based on injection-seeded Nd:YAG laser, double-grating dye laser, difference frequency mixing and optical parametric amplifier. BILLI is funded by the ERC (European Research Council) project BRIDGE (BRIDging the gap between Gas Emissions and geophysical observations at active volcanos). It scanned the gas emitted by Pozzuoli Solfatara (Naples, Italy) and Stromboli Volcano (Sicily, Italy) during field campaigns carried out from October 13 to 17, 2014, and from June 24 to 29, 2015, respectively. Carbon dioxide concentration maps were retrieved remotely in few minutes in the crater areas. To our knowledge, it is the first time that carbon dioxide in a volcanic plume is retrieved by lidar. This result represents the first direct measurement of this kind ever performed on active volcanos and shows the high potential of laser remote sensing in early detection of volcanic hazard.

Detection and monitoring of pollutant sources with Lidar/Dial techniques

Its well known that air pollution due to anthropogenic sources can have adverse effects on humans and the ecosystem. Therefore, in the last years, surveying large regions of the atmosphere in an automatic way has become a strategic objective of various public health organizations for early detection of pollutant sources in urban and industrial areas.The Lidar and Dial techniques have become well established laser based methods for the remote sensing of the atmosphere. They are often implemented to probe almost any level of the atmosphere and to acquire information to validate theoretical models about different topics of atmospheric physics. They can also be used for environment surveying by monitoring particles, aerosols and molecules.The aim of the present work is to demonstrate the potential of these methods to detect pollutants emitted from local sources (such as particulate and/or chemical compounds) and to evaluate their concentration. This is exemplified with the help of experimental data acquired in an industrial area in the south of Italy by mean of experimental campaign by use of pollutants simulated source. For this purpose, two mobile systems Lidar and Dial have been developed by the authors. In this paper there will be presented the operating principles of the system and the results of the experimental campaign.

Lidar and Dial application for detection and identification: A proposal to improve safety and security

Nowadays the intentional diffusion in air (both in open and confined environments) of chemical contaminants is a dramatic source of risk for the public health worldwide. The needs of a high-tech networks composed by software, diagnostics, decision support systems and cyber security tools are urging all the stakeholders (military, public, research & academic entities) to create innovative solutions to face this problem and improve both safety and security. The Quantum Electronics and Plasma Physics (QEP) Research Group of the University of Rome Tor Vergata is working since the 1960s on the development of laser-based technologies for the stand-off detection of contaminants in the air. Up to now, four demonstrators have been developed (two LIDAR-based and two DIAL-based) and have been used in experimental campaigns during all 2015. These systems and technologies can be used together to create an innovative solution to the problem of public safety and security: the creation of a network composed by detection systems: A low cost LIDAR based system has been tested in an urban area to detect pollutants coming from urban traffic, in this paper the authors show the results obtained in the city of Crotone (south of Italy). This system can be used as a first alarm and can be coupled with an identification system to investigate the nature of the threat. A laboratory dial based system has been used in order to create a database of absorption spectra of chemical substances that could be release in atmosphere, these spectra can be considered as the fingerprints of the substances that have to be identified. In order to create the database absorption measurements in cell, at different conditions, are in progress and the first results are presented in this paper.

Lidar detection of carbon dioxide in volcanic plumes

Volcanic gases give information on magmatic processes. In particular, anomalous releases of carbon dioxide precede volcanic eruptions. Up to now, this gas has been measured in volcanic plumes with conventional measurements that imply the severe risks of local sampling and can last many hours. For these reasons and for the great advantages of laser sensing, the thorough development of volcanic lidar has been undertaken at the Diagnostics and Metrology Laboratory (UTAPRAD-DIM) of the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA). In fact, lidar profiling allows one to scan remotely volcanic plumes in a fast and continuous way, and with high spatial and temporal resolution. Two differential absorption lidar instruments will be presented in this paper: BILLI (BrIdge voLcanic LIdar), based on injection seeded Nd:YAG laser, double grating dye laser, difference frequency mixing (DFM) and optical parametric amplifier (OPA), and VULLI (VULcamed Lidar), based on injection seeded Nd:YAG laser and optical parametric oscillator (OPO). The first one is funded by the ERC (European Research Council) project BRIDGE and the second one by the ERDF (European Regional Development Fund) project VULCAMED. While VULLI has not yet been tested in a volcanic site, BILLI scanned the gas emitted by Pozzuoli Solfatara (Campi Flegrei volcanic area, Naples, Italy) during a field campaign carried out from 13 to 17 October 2014. Carbon dioxide concentration maps were retrieved remotely in few minutes in the crater area. Lidar measurements were in good agreement with well-established techniques, based on different operating principles. To our knowledge, it is the first time that carbon dioxide in a volcanic plume is retrieved by lidar, representing the first direct measurement of this kind ever performed on an active volcano and showing the high potential of laser remote sensing in geophysical research.

First tests of a multi-wavelength mini-DIAL system for the automatic detection of greenhouse gases

Considering the increase of atmospheric pollution levels in our cities, due to emissions from vehicles and domestic heating, and the growing threat of terrorism, it is necessary to develop instrumentation and gather know-how for the automatic detection and measurement of dangerous substances as quickly and far away as possible. The Multi- Wavelength DIAL, an extension of the conventional DIAL technique, is one of the most powerful remote sensing methods for the identification of multiple substances and seems to be a promising solution compared to existing alternatives. In this paper, first in-field tests of a smart and fully automated Multi-Wavelength mini-DIAL will be presented and discussed in details. The recently developed system, based on a long-wavelength infrared (IR-C) CO2 laser source, has the potential of giving an early warning, whenever something strange is found in the atmosphere, followed by identification and simultaneous concentration measurements of many chemical species, ranging from the most important Greenhouse Gases (GHG) to other harmful Volatile Organic Compounds (VOCs). Preliminary studies, regarding the fingerprint of the investigated substances, have been carried out by cross-referencing database of infrared (IR) spectra, obtained using in-cell measurements, and typical Mixing Ratios in the examined region, extrapolated from the literature. First experiments in atmosphere have been performed into a suburban and moderately-busy area of Rome. Moreover, to optimize the automatic identification of the harmful species to be recognized on the basis of in cell measurements of the absorption coefficient spectra, an advanced multivariate statistical method for classification has been developed and tested.