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

Centre for Remote Imaging, Sensing and Processing

by

S.V. Salinas, B.N. Chew and S.C. Liew

Photometric analysis of the October 2010 haze

event over Singapore

IGARSS 2011, 24th - 29th Vancouver, Canada


October 2010 Haze over Singapore


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 atmosphere

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 Singaporeand 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.

Overview


• 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).

Atmospheric Super-site in Singapore


Perform observations of direct and diffuse transmitted radiation at more than 180 locations worldwide.

AERONET radiometer's measure total columnar optical depth and sky radiance using 2 different observation sequences: almucantar and principal plane scans.

Singapore's Sun-photometer performs measurements at six spectral bands i.e.[0.340, 0.380, 0.440, 0.500, 0.675, 0.870, 1020] nm.

The AERONET network


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

Transported Smoke Layer

Local Aerosols within

Boundary Layer


Methodology and data processing

•The aerosol optical depth (AOD) at wavelength ( ) is one λof the standard parameters derived from Sun-photometers.

•AOD ( _a) and its first ( ) and second ( ') spectral τ α αderivatives 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 ( ), can provide a useful measure of the αaverage 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 ( ') provides a useful means to αtest the departure from linearity which is inherent from the formulation of the Angstrom law, it also is a useful indicator of particle size.



•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 ( _f ) and coarse mode τ( _c ) optical depth from the spectral shape of τthe total AOD ( _a = _f + _c ).τ τ τ

•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 ( = _f / _a ) is η τ τknow, then fine mode equivalent of aerosol optical depth and Angstrom exponent number can be readily extracted.



•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 ( > 0.75 and 1.1 < ' < 2.0) was α − αemployed.

•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 _a = P^(2) (ln )]. τ λ

•Subsequently, parameters such as and ' and its fine/coarse α αmode counterparts were computed at a reference wavelength of 500 nm.


Hot spot fire detection and in-situ PM2.5 measurements for

October 2010


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).



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).



FIG(3) : PM2.5 measurements at Singapore super-site (07th-July to 30th-July). Concurrent MODIS detected fire counts for the same period.



FIG(4) : 7-day Back trajectory computations for day 21st. Thanks to Tom L. Kucsera (GESTAR/USRA) at NASA/Goddard.



FIG(5) : 7-day Back trajectory computations for day 24th. Thanks to Tom L. Kucsera (GESTAR/USRA) at NASA/Goddard.


Bio–mass burning smoke over Singapore: Photometric and Lidar

data description


AOD and Angstrom exponent distributions for Oct. 2010

FIG(6) : Combined Angstrom exponent and aerosol optical depth statistics and concentration for Oct. haze event.


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.



FIG(8) : LIDAR NRB vertical profile. Three AOD and aerosol extinction profiles are shown.



FIG(9) : Fine and coarse mode AOD and Angstrom number retrievals (left), fine mode fraction ratios. For this case no LIDAR times were available.



FIG(10) : Fine and coarse mode AOD and Angstrom number retrievals (left), fine mode fraction ratios. LIDAR times shown as vertical lines.



FIG(11) : LIDAR NRB vertical profile. A single AOD and aerosol extinction profile is shown.


Aerosol classification for smoke event of Oct. 2010

FIG(12) : Aerosol classification chart shows elevated fine mode fractions for days 16th , 20th and 24th.


Aerosol climatology for smoke event of Oct. 2010

FIG(13) : AERONET inversions : Aerosol size distribution for selected dates.


Aerosol climatology for smoke event of Oct. 2010

FIG(14) : AERONET inversions : Single scattering albedo.


Summary

• During October 2010, persistent smoke fire activity over central Sumatra, was detected.

• There was a substantial degradation of air quality and reduced visibility.

• The greatest impact of the October 2010 smoke event was between days 14th to 24th (PM2.5 > 40.5μgr./m3).

• Critical parameters such asthe classical Angstrom number, its fine mode version together with the fine mode fraction consistently indicate the presence of fine sub-micron particles.

• Trajectory analysis indicated the presence of both, fresh and aging smoke.

• LIDAR retrievals showed profiles consistent with highly absorbing particles such as those from bio-mass burning.

• Model inversions showed high concentration of very fine particles of the order of 0.4 micron or less.

• Particulate single scattering albedo show the presence of highly absorbing particles.

• Large difference in SSA showed different fuel sources, combustion phases and aerosol aging.

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

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