Experimental research into emission of ultra fine dusts as harbingers of volcanic seismic events

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1 Experimental research into emission of ultra fine dusts as harbingers of volcanic seismic events F. Patania, A. Gagliano, F. Nocera & V. Lauretta Energy and Environment Division of D.I.I.M., Engineering Faculty of University of Catania (Italy) Abstract Usually the history of a volcano is marked by the alternation of brief intervals of eruptive activity and long periods of apparent inactivity. During the long periods of pseudo-inactivity, there are evident symptoms that the volcano is still active, e.g. fumaroles, hot springs and gaseous emissions. The variation in intensity of previous phenomena may be used for a possible forecasting of forthcoming volcanic-seismic events. The aim of the present research was to use the variation in emissions of ultra fine dusts in the period of pseudo inactivity to obtain an index able to forecast the possible volcanic eruption, or volcanic seismic event, some time before it occurs. Thus we conducted a long-term monitoring campaign near some volcanic faults on the slopes of Mt. Etna (Sicily) measuring: - variation in concentration of ultra fine dusts (PMx) in the air; - meteoclimatic parameters such as temperature, relative humidity, direction and intensity of wind; - seismic parameters such as magnitude and length of seismic events. From the systematic analysis of data acquired over two years of monitoring, it was possible to develop composite parameters termed Seismicity of Period (I m ) and Forced Peak (FP). Correlating MI, FP, and the measured mean daily concentration of PM 10 in the air, it was possible to determine the required index able to forecast possible seismic volcanic events. Research is currently in progress to refine the index which could be utilized not only to forecast possible seismic volcanic events, but also as a key to give early warning to the Civil Protection Agency so that they can be ready in time should an eruptive event occur. The present paper regards the results of the monitoring campaign, the analysis methodology and the development of the index. Keywords: volcanic-seismic event, PM correlation index.

112 Air Pollution XII 1 Investigated area, measurement equipment and investigation methodology Measurements were made in some zones on the slopes of Etna volcano in proximity to faults (1) (2): In

2 112 Air Pollution XII 1 Investigated area, measurement equipment and investigation methodology Measurements were made in some zones on the slopes of Etna volcano in proximity to faults (1) (2): In the Dalia area (Biancavilla) located, with reference to the central crater, in the south-west of the mountain, and the Vena area (Piedimonte) in the north-east. Figures 1 and 2, show respectively the investigated zones and the faults present on the mountain. The following equipment was used to acquire the required data: Babuc ABC: meteoclimatic steady stations to control meteoclimatic parameters during the measurement period. Envirocheck Grimm Model 107: analyser of ultra fine dust concentrations (PM 10, P 2,5, PM 1 ) based on 90 diffusion of laser ray (scattering). Figure 1: Areas of investigation.

Air Pollution XII 113 Miran 1B2: portable air meter analyser of CO 2 concentrations, based on the interference of measured gas with infrared radiation.

3 Air Pollution XII 113 Miran 1B2: portable air meter analyser of CO 2 concentrations, based on the interference of measured gas with infrared radiation. The registration of single datum by this equipment was based on regular time intervals for each measurement typology: - Fine dusts: 10 minutes - CO 2 : 10 minutes - Meteoclimatic data: 1 hour. The measurement campaign was conducted from August 2001 to October All acquired data was processed and analysed on a spreadsheet. Fine dust data was analysed using the powerful Grimm 174 software. CO 2 data was analysed using MS3200f computer program able, for each reference time interval, to elaborate: minimum value, mean term and maximum value. Babuc ABC directly outputs meteoclimatic data in ASCII format. Figure 2: The faults present on the mountain. 2 Acquired data and post-processing With reference to data measured in the Dalia area from to , we observed:

4 114 Air Pollution XII - Very irregular wind velocity, generally varying between 0.7 m/s and 3.9 m/s, with a maximum peak value of 5.6 m/s. - Typical seasonal temperature trend varying between -6 C and 7 C. - Daily CO 2 concentration varying from 420 ppm to 490 ppm. The highest values were found during the night and the lowest values during the day, in accordance with the processes of chlorophyll photosynthesis. - Very low values of PM concentration, varying daily around 20 Figure 3 and 4 show examples of the daily trend of CO 2 and PM x, respectively, measured during a day in which seismic events occurred. PMx 45,00 40,00 35,00 30,00 25,00 20,00 pm 10 pm 2.5 pm 1.0 md 1.5 md 2.1 md ,00 10,00 5,00 0, hour Figure 3: Example of daily PMi trend measured during a day with seismic events. With reference to data measured in the Vena area (from to ), we observed: - Regular trend of wind direction: from E-SE in the morning, from W- NW at midday, from E- SE at night. - Typical seasonal temperature trend, varying between -5 C and 25 C - Daily CO 2 varying between 500 ppm and 600 ppm in the months of April-May and 440 to 540 ppm in June-July. The highest values were found during the night and the lowest during the day, in accordance with the trend of chlorophyll photosynthesis processes, as above. - Daily PMi concentration varying between 15 and 50. There were also isolated cases of very high PMi concentration values (150 ), but these were mainly caused by local human interference.

5 Air Pollution XII 115 CO ppm min average max md 1.7 md 1.4 md 2 md 2 md 1.8 md hour Figure 4: Example of daily CO 2 trend measured during a day with seismic events. Figures 5 and 6 give examples of the daily CO 2 and PMi trends, respectively, measured during a day in which one or more seismic events occurred. Post processing of whole values for each day of measurement was summarised in tabular form with reference to parameters: - peak values of CO 2 concentration - peak values of PM concentration - magnitude of seismic-events during the time of measurements - velocity and direction of wind Acquired data shows that there is no evident correlation of maximum values of CO 2 and PM concentrations with seismic-events. In fact, it was noted that seismic-events sometimes occur before and sometimes after the presence of peak values and, moreover, that peak values do not vary significantly during days with a significant presence of seismic activity of appreciable magnitude. More thorough analysis subsequently performed on data of PM 10 concentrations alone drew attention to some phenomena of particular interest with regard to correlation between PM concentrations in the air and seismic events. We termed this relation I m, Seismicity of Period I m = n i= 1 n where: I m (i) = average of seismic magnitudes of i-day n = number of consecutive days investigated I m () i (1)

6 116 Air Pollution XII PMx pm 10 pm 2.5 pm 1.0 md ,00 45,00 40,00 35,00 30,00 25,00 20,00 15,00 10,00 5,00 0, hour Figure 5: Example of daily PMi trend measured during a day with seismic event. CO 2 ppm hour min value average value max value md 1.2 md 1.2 Figure 6: Example of daily CO 2 trend measured during a day with seismic events.

7 Air Pollution XII 117 We compared the daily mean PM 10 concentrations with the Seismicity of Period, as shown in Figure 7, and noticed that an increasing (or decreasing) trend in PM 10 concentration is correlated to an increasing (or decreasing) trend in I m. An attempt was made to interpolate the acquired data using mathematical regression without appreciable results. Not only were very low correlation indices found, but the data does not repeat with the same law over different measurement periods, changing greatly for each time period investigated. Given that short period analysis (monthly) did not define any clearly identifiable correlation between PM 10 concentrations and seismic events, we proceeded to analyse phenomena over three-month period. We termed Force Peak (FP) the value of PM 10 concentration found between a period of at least three consecutive days of increasing concentration and one of at least three days of decreasing concentration. The FP were then correlated with the significant seismic events, i.e. greater than 2 on the Richter scale ,00 1,80 1,60 1,40 1,20 1,00 0,80 magnetude pm 10 Im Lineare (pm 10) Lineare (Im) day 0,60 0,40 0,20 0,00 y(pm 10) = 0,8197x + 21,408 r=0,615 y = 0,0015x + 1,4328 r=0,123 Figure 7: Example of correlation between PM10 and Im. In this way, it was possible to construct a correlation graph, correlating the mean daily trend in PM 10 concentration with mean daily magnitude (Figure 8), with both mean and maximum magnitude (Figure 9), and with the daily number of seismic events (Figure 10). Analysis of the above graphs prompted the following considerations: - An FP of PM 10 is followed by significant seismic activity - FP of PM 10 are followed, in 90% of cases, by significant seismicvolcanic activity within three days. - The constant increase in daily main value of PM 10 after an FP is matched by an increase in seismic activity and, in some cases, as well as earthquakes of increasing magnitude, there is also an increasing number of seismic swarms.

8 118 Air Pollution XII - The presence of many FP over a short time interval together with high values of PM 10 concentration, marks a period with seismic events of considerable magnitude, also in accordance with the comments made above using the Seismicity of Period (seismic response to a trend in increasing PM 10 concentration) as analysis parameter. mean magnitude pm 10 magnitude 10,00 9,00 8,00 7,00 6,00 5,00 4,00 3,00 2,00 1,00 0,00 day Figure 8: Mean daily trend in PM10 concentration correlated with mean daily magnitude. mean magnitude maximum magnitude PM 10 10, ,00 8, Magnitude 7,00 6,00 5,00 4,00 3,00 2,00 1, ,00 day 0 Figure 9: Mean daily trend in PM10 concentration correlated with both mean and maximums value of magnitude of seismic event.

9 Air Pollution XII daily seismic event pm Number of events day 0 Figure 10: Mean daily trend in PM 10 concentration correlated with daily number of seismic events. 3 Conclusions The first phase of experimental research led to the development of two new indices to be refined in the near future and validated by further measurement campaigns: - I m = Seismicity of Period qualitatively correlates the trend in PM 10 concentration to the mean seismic magnitude. This index requires further investigation, to be undertaken in the next measurement campaign, in an attempt to determine the mathematical law of correlation. - FP = Force Peak is already effective in correlating seismic volcanic events greater than 2 on the Richter scale with PM 10 concentrations in the air and giving, moreover, both the probability of a seismic-volcanic event (90%) and the time range (3 days) of its occurrence. At the current state of research, the FP index is not, of course, able to single out with deterministic exactness either the day when a seismicvolcanic event will occur or the magnitude of the event. However, it can certainly be used as an early warning (3) (4) for the Civil Protection Agency to be ready to intervene in the, inauspicious, case that the magnitude of the event forecast using the FP technique could be dangerous for the inhabitants of small towns on the foothills of Mt. Etna. From this viewpoint, it could be desirable to built a network of environmental steady stations at targeted points near the faults on the slopes of Etna, Figure 2. These would identify, in real time, the

10 120 Air Pollution XII References occurrence of an FP. The next phase of the research will be to use data acquired in a future measurement campaign in an attempt to correlate I m to FP and thus determine mathematical laws able to also forecast the magnitude of the seismic-volcanic event. [1] Barbano M.S., Cosentino M., Lombardo G., Patane' G., Isoseismal maps of Calabria and Sicily earthquakes (southern Italy), CNR, P.F. Geodinamica, Gruppo "Catalogo dei Terremoti"-1980, Pubb. n [2] Cosentino M., Di Francesco M., Lombardo G., Privitera E., Volcanic activity at Mt. Etna and possible seismological precursors, Proceedings of the International Workshop "Resumed activity in areas of quiescent volcanism: triggers and precursors", Firenze, Per. Mineral [3] Patania, F., Gagliano, A., Nocera, F., Air pollution and urban plan of road traffic: experimental research about situations of environmental health hazard, Urban Transport IX., WIT Press Southampton (U.K.), pp ,2003 [4] Patania, F., Gagliano, A., Nocera, F., Air pollution drop by technique of urban traffic integrated control system in Catania city (Italy), Urban Transport VII, WIT Press, 2001

Monthly Volcanic Activity Report (February 2016)

Monthly Volcanic Activity Report (February 2016) Japan Meteorological Agency Azumayama (Alert Level: 2) Fumarolic activity at the Oana crater has remained at relatively high levels. Aerial observation