LIDAR detection of forest fire smoke above Sofia

LIDAR detection of forest fire smoke above Sofia Ivan Grigorov*, Atanaska Deleva, Dimitar Stoyanov, Nikolay Kolev and Georgi Kolarov Institute of Electronics – Bulgarian Academy of Sciences, 72 Tzarigradsko Shose Blvd., 1784-Sofia, Bulgaria ABSTRACT The distribution of aerosol load in the atmosphere due to two forest fires near Sofia (the capital city of Bulgaria) was studied using two aerosol lidars which operated at 510.6 nm and 1064 nm. Experimental data is presented as 2Dheatmaps of the evolution of attenuated backscatter coefficient profiles and mean profile of the aerosol backscatter coefficient, calculated for each lidar observation. Backscatter related Angstrom exponent was used as a criterion in particle size estimation of detected smoke layers. Calculated minimal values at altitudes where the aerosol layer was observed corresponded to predominant fraction of coarse aerosol. Dust-transport forecast maps and calculations of backward trajectories were employed to make conclusions about aerosol’s origin. They confirmed the local transport of smoke aerosol over the city and lidar station. DREAM forecast maps predicted neither cloud cover, nor Saharan load in the air above Sofia on the days of measurements. The results of lidar observations are discussed in conjunction with meteorological situation, aiming to better explain the reason for the observed aerosol stratification. The data of regular radio sounding of the atmosphere showed a characteristic behavior with small differences of the values between the air temperature and dew-point temperature profiles at aerosol smoke layer altitude. So the resulting stratification revealed the existence of atmospheric layers with aerosol trapping properties. Keyword list: Lidar remote sensing, lidar data processing, inversion algorithm for atmospheric backscatter/extinction coefficient retrieval, background noise removal.

1. INTRODUCTION Natural or human-induced forest fires represent a constant threat to ecological systems, infrastructures, human health and lives. Fires draw increasing attention in recent years in relation to the global carbon cycle 1. Although forest fires are basically local phenomena, they can also contribute to changes of the atmosphere on a regional or even global scale by generating large amounts of aerosol particles2-5. The study of trace gases and aerosol load in the atmosphere by ground based stations with high technological performance, represent a main goal of the project ACTRIS (Aerosols, Clouds, and Trace gases Research Infra Structure Network)6. ACTRIS is funded within the EC 7th Framework Program under "Research Infrastructures for Atmospheric Research". The European Aerosol Research Lidar Network (EARLINET 7), consisting of 27 lidar stations, among which Sofia lidar station, performs coordinated measurements and analyses of the atmospheric aerosol distribution and transport. Described below results of observations of forest fire smoke in the air, made by Sofia lidar station on July 3, 2012, and August 22, 2013 are performed in the frame of EARLINET activities. The vertical atmospheric backscatter coefficient profiles are retrieved by inversion algorithm of Klett-Fernald8, 9. Since the magnitude of the backscattered radiation is proportional to the aerosol density, the variation of the backscatter lidar signal in time and space illustrate the temporal evolution and the stratification of observed aerosol field. Calculated backscatter coefficient profiles at 1064 nm and 510.6 nm are used to derive Angstrom coefficient as a function of altitude and thus to estimate roughly the particle size distribution10. The results of lidar measurements are discussed in conjunction with meteorological situation, aiming to better explain the reason for the observed aerosol stratification. In order to estimate the origin of the aerosol layers, observed by the lidars, we calculated backward air-mass trajectories by using the HYSPLIT model11 (HYbrid Single-Particle Lagrangian Integrated Trajectory) through the READY system on the site of Air Resource Laboratory of NOAA (National Oceanic and Atmospheric Administration), USA. The calculations of backward air mass trajectories give a plot of the road that the air mass traversed for a chosen time period before arriving to the lidar station. Additional information about the origin of the detected aerosol layers is obtained from the forecast maps of dust load in the atmosphere, made by the Forecast system of Barcelona Supercomputing Centre (BSC), Spain12, accessible via Internet. These maps give an image of the wind direction and speed, position of cloud fields and magnitude of dust load in the atmosphere above North Africa and Europe. * e-mail: [email protected] 18th International School on Quantum Electronics: Laser Physics and Applications, edited by Tanja Dreischuh, Sanka Gateva, Alexandros Serafetinides, Proc. of SPIE Vol. 9447, 94470U · © 2015 SPIE CCC code: 0277-786X/15/$18 · doi: 10.1117/12.2178791 Proc. of SPIE Vol. 9447 94470U-1 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 01/09/2015 Terms of Use: http://spiedl.org/terms

2. TECHNICAL EQUIPMENT Both ground-based aerosol lidars of Laser Radar Laboratory of the Institute of Electronics of the Bulgarian Academy of Sciences (LRL IE-BAS) were presented in our previous works. First lidar system13 is equipped with a CuBr-vapor laser, emitting at wavelength of 510.6 nm, and a detecting system working in photon-counting mode. Second lidar uses an Nd:YAG laser, at wavelengths 1064 nm and 532 nm, and analog mode of registration14. Another important difference between the two lidars is the slope of sounding path. The radiation of the lidar with CuBr-vapor laser is directed vertically, while this of the lidar with Nd:YAG laser is inclined at 32 degrees to the horizon (Fig.1). Therefore the sounding paths of the lidars diverge with the height increase. For example, at 5 km altitude above ground level (AGL) the distance between the probed volumes of the two lidars is ~8 km.

=Et 1

Fig.1. Photos of the CuBr-vapor (left) and Nd:YAG laser based (right) aerosol lidars at Sofia Earlinet Station

We compared the data of lidars to the data of ceilometer measurement (CHM 15k ceilometer) and meteorological radiosounding15 and found synchronous behavior of atmospheric parameters measured with all appliances.

Fig.2.Photos of the forest fires observed by Sofia lidar station: A) in Vitosha–mountain, on July 03, 2012; B) at North of Sofia, on August 22, 2013.

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3. LIDAR MEASUREMENTS ON JULY 03, 2012 DURING THE FOREST FIRE IN VITOSHA MOUNTAIN Sofia is located at about 550 m above sea level, in a natural basin surrounded by mountains. Vitosha-mountain, located South-West of Sofia, is a national park and one of his protected areas was affected by spontaneous forest fire in 2012. A photo of the fire on July 03, 2012, when the smog was most intensive, is displayed on Fig.2.A. Lidar measurement, Sofia, July 03, 2012 C

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Fig.3. Lidar measurement on July 03-d, 2012. A) heatmap of attenuated backscatter at wavelength 1064 nm; B) heatmap of attenuated backscatter at wavelength 510.6 nm; C) derived backscatter profiles at both wavelengths and estimated errors of measurement; D) backscatter related Angstrom exponent and estimated error of calculations.

Observations of smog plume propagation above Sofia where performed with both lidars of the LRL IE-BAS. Fig.3 represents the results of these observations. On Fig.3.A and Fig.3.B are shown color diagrams (heatmaps) of attenuated backscatter coefficient, derived from the lidar signals. These diagrams visualize the time evolution of the smoke layer, marked as dark brown band in both figures at altitude ~1.5 km above ground level (AGL). The areas of low aerosol concentrations (incl. the clear atmosphere) are presented in blue color. Calculated by inversion algorithm10, 11 profiles of the atmospheric backscatter coefficient for both wavelengths (1064 nm and 510.6 nm), and the estimated errors of measurement, are presented on Fig.3.C. The profiles are calculated for the overlapping time interval of measurement of both lidars, from 07:50 h to 08:45 h UTC. Both lidars registered a peak of backscattered signal at the same altitude. It means, during this time interval the observed fire smoke propagated at ~1.5 km AGL beyond Sofia. Using both backscatter coefficient profiles we calculated the profile of backscatter-related Angstrom exponent, given by the equation: 1064   tot ( H )  exp  510   .6 ( H )   tot  AngExp ( H )   ,  1064  exp  510.6     

(1)

1064 510.6 ( H ) and  tot ( H ) are the calculated values of backscatter coefficient at altitude H, for wavelength where  tot

1064 =1064 nm and 510.6 =510.6 nm respectively. The index tot indicates total value of calculated backscatter coefficient, including molecular and aerosol backscatter. The Angstrom coefficient can be used as an indicator of the particle size of the observed by both lidars aerosol layers. Low values of the Angstrom exponent indicate larger aerosol particles size. The Angstrom exponent profile, presented on Fig.3.D has minimal values of ~0.17 at the altitude of the smoke layer. Thus, the fraction of large aerosol particles was predominant in the observed layers at ~1.5 km AGL. Above this altitude the values of Angstrom exponent profile remain close to 4, as it can be expected to a backscattering in clear and almost molecular atmosphere, having in mind that


1064   mol  ( 510.6 ) 4 ( H )   exp  510 exp   .6 ( H )   ( 1064 ) 4 mol       1064   1064  exp  510.6  exp  510.6         

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1064 510.6 In Eq.(2)  mol ( H ) and  mol ( H ) are the values of molecular backscatter coefficient at altitude H, for the wavelengths of both lidars.

The meteorological weather situation during our study is shown on Fig.4. We compared the results of our lidar measurements with the data of ceilometer CHM 15k measurements, performed on the same day. On Fig.4.A is presented the ceilometer data as a heat-map of the intensity of the backscattered signal at wavelength 1064 nm. It can be seen clearly the most intensive signal, colored in red according to the ceilometer color scale, backscattered from aerosol layer at altitude ~1.5 km at nine o’clock. So, the ceilometer measurement confirms well the lidar measurement results. Moreover, the low intensity of backscattered signal at altitudes below the smoke plume at nine o’clock reveals the absence of aerosol load in the atmosphere below the smoke plume that explains the relatively big values of calculated Meteo -Data, Sofia, July 03, 2012

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Fig.4. Meteorological conditions during the lidar measurement on July 03 -d, 2012. A) heatmap of attenuated backscatter at wavelength 1064 nm derived from Ceilometer CHK-15; B) data from regular radio-sounding on July 03-d, 2012, at 12 h UTC; C) calculated by HYSPLIT-model backward air mass trajectories. Angstrom exponent profiles till 1.5 km altitude AGL (Fig.3.D). The ceilometer was located at a distance of 7 km from the lidar station16. Therefore we concluded the fire smoke plume above Sofia on July 03, 2012, had large dimensions and covered a big part of the town. On Fig.4.B is presented the data of regular radio-sounding. Profiles of three atmospheric parameters are displayed: the temperature, the dew-point temperature and the relative humidity. An apparent abrupt change in the behavior of the three parameters at altitude 1.5 km AGL is observed, an inversion of the temperature, accompanied by abrupt increase of the relative humidity from 30% to 60% reflects in a close approach of the values of dew-point temperature to the atmospheric temperature. These changes of the atmospheric parameters marked the existence of a layer possessing favorable characteristics for to take the smoke aerosol layer at this altitude. A reference to the dust-transport forecast maps of Barcelona Supercomputing Center (BSC) did not predicted neither cloud cover, nor Saharan dust load in the air above Sofia. Calculated HYSPLIT backward air mass trajectories showed air mass transport in general from North-East to South-West, from regions free of dust load in the atmosphere (Fig.4.C). Upon the analysis of the results of lidar measurement, the information about aerosol layer’s origin, its altitude above ground, and persistence during lidar observations, we made the conclusion that the aerosol layer observed at ~1.5 km AGL was due to the forest fire in Vitosha Mountain and it covered a significant area above Sofia because of the specific meteorological situation.


4. LIDAR MEASUREMENT ON 22 AUGUST, 2013 DURING THE FOREST FIRE TO THE NORTH OF SOFIA During August 2013 a spontaneous fire burned near a village, located at distance of ~10 km from Sofia (Fig.2.B). Again we performed observations of the smoke plume by the two lidars, using wavelengths 1064 nm and 510.6 nm. Results of our lidar measurements are shown on Fig. 5. As on Fig.3, the time evolution of aerosol layers in the atmosphere during the lidar observations is presented in terms of heat-maps of attenuated backscatter (Fig.5.A and Fig.5.B). The most dense aerosol layers were detected at altitude of ~2.5-3 km AGL, marked with darkest brown band on the figures. The calculated backscatter coefficient profiles for the overlapping time interval of measurement of both lidars, from 10:40 h to 12:40 h UTC, are presented on Fig.5.C. Both profiles have their most high values at altitude 2.9 km AGL. The calculated by Eq.(1) backscatter related Angstrom exponent profile has the behavior displayed on Fig.5.D. The local minimum at altitude 2.9 km reveals the presence of coarse fraction aerosol predominantly. As difference with the calculated backscatter related Angstrom exponent profile for the case of July 03, 2012, the values below the smoke plume altitude remain small (~0.7 at altitude 1.75 km AGL), indicating an aerosol load with particle of large size near A

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Fig.5. Lidar measurement on August 22, 2013. A) heatmap of attenuated backscatter at wavelength 1064 nm; B) heatmap of attenuated backscatter at wavelength 510.6 nm; C) derived backscatter profiles at both wavelengths and estimated errors of measurement; D) backscatter related Angstrom exponent and estimated error of calculations.

the ground. Beyond the smoke aerosol layer at ~3 km, the values of the backscatter related Angstrom exponent profile fluctuate near 4, accordingly to Eq.(2). On Fig.6 are presented details about atmospheric meteorological parameters, measured on the same day. Ceilometer data on Fig.6.A presents the existence of an aerosol layer at altitude ~2.9-3 km, where the smoke plume was detected in accord with the lidar observations for the time interval 10:40 h to 12:40 h UTC. Furthermore, a significant aerosol load below the smoke plume was observed by the ceilometer, which comes as a confirmation of the low values of Angstrom exponent from lidar measurements. The aerosol layers near the ground contained coarse fraction particles. We can highlight that the ceilometer measurement confirms well the lidar measurement results. The atmospheric temperature and dew-point temperature profiles together with the atmospheric relative humidity, as measured by a radio-sound at midday, are presented on Fig.6.B. An inversion in the behavior of the atmospheric temperature was observed at altitude ~3.1 km AGL and the relative humidity increased till ~100% at this altitude. The dew point temperatures became close to the temperature of the atmosphere and had overlapping values at 2.8-3.1 km AGL. At such atmospheric conditions all aerosol particles were well humidified and formed condensation nucleus. So the most dense aerosol layer was observed by both lidars at this altitude. Calculated backward air mass trajectories are presented on Fig.6.C and similarly to those, calculated for the lidar observations on July 03, 2012, showed air mass transport from North-East to South-West, from regions free of mineral or maritime dust load in the atmosphere. Since the BSC forecasts maps do not predicted any Saharan dust transport over Bulgaria, one can conclude that the observed atmospheric aerosol layers were due to the smoke transport of the local forest fires.


MeteoData, Sofia, August 22, 2013

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5. CONCLUSIONS In this article are presented and commented the results of lidar observations of an unusual aerosol load in the atmosphere above Sofia, due to the propagation of a smoke plume of forest fires near the city. The observations were performed with two lidar, at wavelengths 1064 nm and 510.6 nm on July 03, 2012 and August 22, 2013. Calculated atmospheric backscatter coefficient profiles for the time intervals of simultaneous measurement of both lidars were analyzed and profiles of backscatter related Angstrom exponent (Eq.(1)) were derived. The retrieved minimal values (0.17 at altitude 1.5 km AGL for the case of July 03, 2012, and 1.74 at altitude 2.9 km AGL for the case of August 22, 2013), indicate the presence of coarse particle fractions in the observed smoke aerosol layers. The results of ceilometer measurements on these days confirm the lidar observations and give additional information about the aerosol stratification in the Planetary Boundary Layer (PBL) for a larger time intervals, than the lidar measurements. Ceilometer data was used to explain the differences of the behavior of calculated backscatter related Angstrom exponents for altitudes below the smoke plume for the two days of measurements. The analyses of lidar observations are made in conjunction with the meteorological conditions, on the base of regular radio-sounding data. For both days of measurements we found similar changes with altitude of the atmospheric parameters (temperature, dew point temperature and relative humidity). These characteristic changes in the behavior of the atmospheric parameters denounced a formation of trap-layer for the smoke plume, and we observed it just at this altitude. The retrieved transport history of air masses propagation toward Sofia, by using HYSPLIT model backward trajectories calculations, showed the absence of long way dust transport from other sources. Upon this information we concluded the detected aerosol layers were smoke plume of the forest fires near the town.

6. ACKNOWLEDGEMENTS This work is supported by the project of FP7 “Aerosols, Clouds, and Trace gases Research Infrastructure Network” (ACTRIS), grant agreement No 262254 and the Bulgarian Science Fund. The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT model for air mass transport and dispersion and/or READY website used in this publication. The authors express their gratitude to the Department of Atmospheric engineering of Wyoming University (USA), for the rich database of atmospheric radio sounding profiles, used in this publication.


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