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PHOTOMETRIC ANALYSIS OF THE OCTOBER 2010 HAZE EVENT OVER SINGAPORE.pdf
 

PHOTOMETRIC ANALYSIS OF THE OCTOBER 2010 HAZE EVENT OVER SINGAPORE.pdf

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    PHOTOMETRIC ANALYSIS OF THE OCTOBER 2010 HAZE EVENT OVER SINGAPORE.pdf PHOTOMETRIC ANALYSIS OF THE OCTOBER 2010 HAZE EVENT OVER SINGAPORE.pdf Presentation Transcript

    • Photometric analysis of the October 2010 haze event over Singapore by S.V. Salinas, B.N. Chew and S.C. Liew IGARSS 2011, 24th - 29th Vancouver, CanadaCentre for Remote Imaging, Sensing and Processing
    • October 2010 Haze over SingaporeCentre for Remote Imaging, Sensing and Processing
    • October 2010 Haze over SingaporeCentre for Remote Imaging, Sensing and Processing
    • Overview Vegetation fires are a normal phenomenon in the South–East–Asia region. Tropical wild fires can occur thought the year and they are specially common during the dry season months (June–November). The severity of vegetation fires (bio–mass burning) can be greatly by human intervention. According the the Global Fire Emissions Database (GFED), during the period 1997–2006, there were two major fire episodes in Indonesia (1997, 2006) and two minor episodes (2002, 2004). During the disastrous 1997 bio–mass burning episode, the equivalent of 13–to–40 % of the mean annual global carbon emissions from fossil fuels were released into the atmosphereCentre for Remote Imaging, Sensing and Processing
    • Overview • On 15th October 2010, persistent smoke–fire activity over central Sumatra, province of Riau was detected. • The prevailing south- westerly to westerly winds carried in smoke haze from the fires in Sumatra over Singapore and peninsular Malaysia. • According to a press release of NEA, on 19th October, the 24- hr PSI 1 at 4pm was 56 and classified as a moderate event. By 6pm, the 3-hr PSI has increased to 78 approaching unhealthy levels.Centre for Remote Imaging, Sensing and Processing
    • Atmospheric Super-site in Singapore • Established under the cooperative framework of the Seven South-East Asian Studies (7-SEAS) program initiated by NASA and the Office of Naval Research (ONR). • Situated in National University of Singapore (NUS). • Main Site on Block E2 rooftop (1.3 N 103.7 E / 79 m). • Secondary Site on Block S2S rooftop (~ 340 m away from Main Site).Centre for Remote Imaging, Sensing and Processing
    • The AERONET network Perform observations of direct and diffuse transmitted radiation at more than 180 locations worldwide. AERONET radiometers measure total columnar optical depth and sky radiance using 2 different observation sequences: almucantar and principal plane scans. Singapores Sun-photometer performs measurements at six spectral bands i.e. [0.340, 0.380, 0.440, 0.500, 0.675, 0.870, 1020] nm.Centre for Remote Imaging, Sensing and Processing
    • The MPLNET network • Part of NASA’s MPLNET network. • Compact and eye-safe LIDAR. • Determines heights of aerosols and clouds by measuring time-of-flight from transmission of laser pulses to reception of returned signals. Optically Thin Cirrus Local Aerosols within Boundary Transported Smoke Layer LayerCentre for Remote Imaging, Sensing and Processing
    • Methodology and data processing • The aerosol optical depth (AOD) at wavelength (λ) is one of the standard parameters derived from Sun-photometers. • AOD (τ_a) and its first (α) and second (α) spectral derivatives respect to wavelength, are often used to describe the interaction of aerosol particles present on a given particle size distribution (PSD). • The first derivative which is also known as the Angstrom exponent (α), can provide a useful measure of the average aerosol dimensions in the sub– and super– micrometer particle size range. • The Angstrom exponent itself is influenced by particle number variations of the two fundamental modes (fine and coarse). • The second derivative (α) provides a useful means to test the departure from linearity which is inherent from the formulation of the Angstrom law, it also is a useful indicator of particle size.Centre for Remote Imaging, Sensing and Processing
    • Methodology and data processing • By starting from the basic assumption that the PSD can be represented as a bi–modal distribution, O’Neill and collaborators were able to extract the fine (τ_f ) and coarse mode (τ_c ) optical depth from the spectral shape of the total AOD (τ_a = τ_f + τ_c ). • Their scheme, known as the spectral decomposition algorithm (SDA), was essentially dependent on the fact that the coarse mode spectral variation is approximately neutral. • Once the fine mode fraction (η = τ_f /τ_a ) is know, then fine mode equivalent of aerosol optical depth and Angstrom exponent number can be readily extracted.Centre for Remote Imaging, Sensing and Processing
    • Methodology and data processing • For the October 2010 haze event we have extracted one month non–cloud screened AERONET level 1.0 data. • Since the SDA algorithm can be considered as a partial cloud screening technique, no further cloud screening protocols were applied; instead restrictions based on the Angstrom number and its derivative (α > 0.75 and −1.1 < α < 2.0) was employed. • However, the entire data set was quality assured according to AERONET-SDA level 2.0 standards in which five of the seven available photometer channels were included (bounded by the 380–870 nm channel range). • As a requirement for SDA, measured AOD was fitted to a 2nd– degree polynomial in log–log space [ln τ_a = P^(2) (ln λ)]. • Subsequently, parameters such as α and α and its fine/coarse mode counterparts were computed at a reference wavelength of 500 nm.Centre for Remote Imaging, Sensing and Processing
    • Hot spot fire detection and in- situ PM2.5 measurements for October 2010Centre for Remote Imaging, Sensing and Processing
    • Trans-boundary smoke fires and PM2.5 measurements FIG(1) : Fire detection by MODIS Rapid Response System. Most smoke fire hot spots were located at the region of Sumatra, province of Riau, Indonesia (Courtesy of 7-SEAS data repository).Centre for Remote Imaging, Sensing and Processing
    • Trans-boundary smoke fires and PM2.5 measurements FIG(2) : Fire detection by MODIS Rapid Response System. Most smoke fire hot spots were located at the region of Sumatra, province of Riau, Indonesia (Courtesy of 7-SEAS data repository).Centre for Remote Imaging, Sensing and Processing
    • Trans-boundary smoke fires and PM2.5 measurements FIG(3) : PM2.5 measurements at Singapore super-site (07th-July to 30th-July). Concurrent MODIS detected fire counts for the same period.Centre for Remote Imaging, Sensing and Processing
    • Trans-boundary smoke fires and PM2.5 measurements FIG(4) : 7-day Back trajectory computations for day 21st. Thanks to Tom L. Kucsera (GESTAR/USRA) at NASA/Goddard.Centre for Remote Imaging, Sensing and Processing
    • Trans-boundary smoke fires and PM2.5 measurements FIG(5) : 7-day Back trajectory computations for day 24th. Thanks to Tom L. Kucsera (GESTAR/USRA) at NASA/Goddard.Centre for Remote Imaging, Sensing and Processing
    • Bio–mass burning smoke over Singapore: Photometric and Lidar data descriptionCentre for Remote Imaging, Sensing and Processing
    • AOD and Angstrom exponentdistributions for Oct. 2010 FIG(6) : Combined Angstrom exponent and aerosol optical depth statistics and concentration for Oct. haze event.Centre for Remote Imaging, Sensing and Processing
    • Temporal evolution of fine mode event: 16 Oct. 2010 FIG(7) : Fine and coarse mode AOD and Angstrom number retrievals (left), fine mode fraction ratios. LIDAR times shown as vertical lines.Centre for Remote Imaging, Sensing and Processing
    • Temporal evolution of fine mode event: 16 Oct. 2010 FIG(8) : LIDAR NRB vertical profile. Three AOD and aerosol extinction profiles are shown.Centre for Remote Imaging, Sensing and Processing
    • Temporal evolution of fine mode event: 20 Oct. 2010 FIG(9) : Fine and coarse mode AOD and Angstrom number retrievals (left), fine mode fraction ratios. For this case no LIDAR times were available.Centre for Remote Imaging, Sensing and Processing
    • Temporal evolution of fine mode event: 24 Oct. 2010 FIG(10) : Fine and coarse mode AOD and Angstrom number retrievals (left), fine mode fraction ratios. LIDAR times shown as vertical lines.Centre for Remote Imaging, Sensing and Processing
    • Temporal evolution of fine mode event: 24 Oct. 2010 FIG(11) : LIDAR NRB vertical profile. A single AOD and aerosol extinction profile is shown.Centre for Remote Imaging, Sensing and Processing
    • Aerosol classification for smoke event of Oct. 2010 FIG(12) : Aerosol classification chart shows elevated fine mode fractions for days 16th , 20th and 24th.Centre for Remote Imaging, Sensing and Processing
    • Aerosol climatology for smoke event of Oct. 2010 FIG(13) : AERONET inversions : Aerosol size distribution for selected dates.Centre for Remote Imaging, Sensing and Processing
    • Aerosol climatology for smoke event of Oct. 2010 FIG(14) : AERONET inversions : Single scattering albedo.Centre for Remote Imaging, Sensing and Processing
    • Summary • During October 2010, • Trajectory analysis indicated persistent smoke fire activity the presence of both, fresh over central Sumatra, was and aging smoke. detected. • LIDAR retrievals showed • There was a substantial profiles consistent with highly degradation of air quality and absorbing particles such as reduced visibility. those from bio-mass burning. • The greatest impact of the • Model inversions showed high October 2010 smoke event concentration of very fine was between days 14th to particles of the order of 0.4 24th (PM2.5 > 40.5μgr./m3). micron or less. • Critical parameters such as • Particulate single scattering the classical Angstrom albedo show the presence of number, its fine mode version highly absorbing particles. together with the fine mode • Large difference in SSA fraction consistently indicate showed different fuel sources, the presence of fine sub- combustion phases and micron particles. aerosol aging.Centre for Remote Imaging, Sensing and Processing