Indo-Asian pollution during INDOEX: Microphysical particle properties and single-scattering albedo inferred from multiwavelength lidar observations

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D19, 4600, doi: /2003jd003538, 2003 Indo-Asian pollution during INDOEX: Microphysical particle properties and single-scattering albedo inferred from multiwavelength lidar observations Detlef Müller, Kathleen Franke, Albert Ansmann, and Dietrich Althausen Institute for Tropospheric Research, Leipzig, Germany Frank Wagner Universität München, München, Germany Ground Truth Center Oberbayern, Germering, Germany Received 26 February 2003; revised 6 May 2003; accepted 29 May 2003; published 7 October [1] We present for the first time a comprehensive data set of vertically resolved physical particle properties, and the single-scattering albedo at 532 nm, derived from multiwavelength lidar observations of pollution plumes advected from India and Southeast Asia out over the tropical Indian Ocean during the northeast monsoon. The parameters follow from the inversion of optical data that were obtained from six-wavelength aerosol lidar observations at Hulhule Island (4.1 N, 73.3 E), Maldives, in the framework of the Indian Ocean Experiment (INDOEX) (February/March 1999) and three follow-up campaigns in July and October 1999 and in March Effective particle radii were 0.20 ± 0.08 mm for pollution plumes above 1-km height, advected during the northeast monsoon. Volume concentrations ranged from 6 to 44 mm 3 cm 3, and surface-area concentrations were mm 2 cm 3. The particles showed substantial absorption when advected from northern India. The imaginary part of the wavelength-independent complex refractive index was as large as 0.045i. The respective mean value was 0.022i ± 0.014i for observations during the northeast monsoon. The mean real part was 1.54 ± The mean single-scattering albedo at 532 nm was 0.90 ± Values were as low as 0.8 during advection of air from northern India. On average, less absorbing particles were advected from southern India and Southeast Asia. The numbers indicate that the major contributor to the observed pollution from northern India is absorbing soot-like material from, e.g., fossil fuel and firewood burning. The effective radius was well correlated with the Ångström exponents of the underlying extinction spectra. Strong correlation of the single-scattering albedo was found not only with respect to the imaginary part of the complex refractive index but also with respect to the particle extinction-to-backscatter ratio. A comparison to Ångström exponents and single-scattering albedo obtained from Sun photometer and satellite observations showed good representativity of the lidarderived quantities. Comparison with results from airborne in situ observations showed substantial deviations of Ångström exponents and single-scattering albedo. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0345 Atmospheric Composition and Structure: Pollution urban and regional (0305); 0365 Atmospheric Composition and Structure: Troposphere composition and chemistry; 1630 Global Change: Impact phenomena; 1640 Global Change: Remote sensing; KEYWORDS: lidar, microphysics, INDOEX Citation: Müller, D., K. Franke, A. Ansmann, D. Althausen, and F. Wagner, Indo-Asian pollution during INDOEX: Microphysical particle properties and single-scattering albedo inferred from multiwavelength lidar observations, J. Geophys. Res., 108(D19), 4600, doi: /2003jd003538, Introduction [2] Müller et al. [2001a, 2001b] and Franke et al. [2003] presented a detailed characterization of optical particle properties over the tropical Indian Ocean on the basis of Copyright 2003 by the American Geophysical Union /03/2003JD003538$09.00 observations with a six-wavelength aerosol lidar. The measurements were performed during the Indian Ocean Experiment (INDOEX; 15 February to 25 March 1999) [Ramanathan et al., 2001], and three follow-up campaigns in July/October 1999, and March The observations were made at Hulhule Island (4.1 N, 73.3 E) which is the international airport of the Maldives. The Maldives are located approximately 700 km off the southern tip of the AAC 3-1

2 AAC 3-2 MÜLLER ET AL.: POLLUTION DURING INDOEX Indian subcontinent, and are affected by changing airflows during the course of the year, as the result of the northeast monsoon in northern hemispheric winter, and the southwest monsoon during northern hemispheric summer. Consequently, aerosols from highly different source regions are advected across the tropical Indian Ocean. [3] Müller et al. [2001a] presented general geometrical characteristics and seasonal patterns of the observed particle plumes. Franke et al. [2003] focused on detailed vertical characterizations of spectrally resolved Ångström exponents and lidar ratios, and their relationship to emissions in India. In this paper we present the physical particle properties which were inferred from these optical data sets by means of an inversion scheme. For the first time, an extensive parameter set of physical particle properties and the singlescattering albedo on a vertical scale is presented for pollution plumes from South and Southeast Asia. The importance of such parameter sets for the assessment of climate forcing by anthropogenically produced particles is given by the latest Intergovernmental Panel on Climate Change report [Intergovernmental Panel on Climate Change (IPCC), 2001]. [4] The following section 2 briefly describes the inversion scheme. Section 3 presents the measurements. In section 4 we discuss the findings. Section 5 summarizes the findings. 2. Methodology 2.1. Inversion Scheme [5] The inversion scheme which is used for the retrieval of the microphysical particle properties has been specifically designed for the processing of combined data sets of six backscatter and two extinction coefficients. This combination of data is provided by the six-wavelength aerosol lidar of the Institute for Tropospheric Research [Althausen et al., 2000]. Backscatter coefficients at 355, 400, 532, 710, 800, and 1064 nm, as well as extinction coefficients at 355 and 532 nm serve as input for the inversion code. A detailed description of the inversion algorithm is given elsewhere [Müller et al., 1999a, 1999b, 2000a]. The algorithm numerically solves the equations which relate the optical data to the underlying physical quantities: g i ðlþ ¼ Z rmax r min K i ðr; m; l; sþ 3 4r vr ðþdr; i ¼ a; b: ð1þ [6] The backscatter coefficients at wavelength l are denoted by g b (l). The extinction coefficients are written as g a (l). The volume concentration of particles per radius interval dr is described by the term v(r). The terms K b (r, m, l, s) and K a (r, m, l, s) denote the kernel efficiencies of backscatter and extinction for single particles, respectively. The efficiencies depend on the radius r of the particles, on their complex refractive index m, on the wavelength l of the interacting light, as well as on the shape s of the particles. Mie-scattering theory [Bohren and Huffman, 1983] is used for the calculation of the efficiencies of particles of spherical shape. [7] The 8 optical input data create a system of 8 integral equations, which are described by equation (1). This system is solved numerically for the investigated volume size distribution in the radius range from r min to r max, which are set to 0.01 and 10 mm, respectively. The applied technique is Tikhonov s regularization with constraints [Tikhonov and Arsenin, 1977]. In the first step, the volume size distribution in equation (1) is approximated by a linear combination of 8 weighted base functions, which have a triangular shape on a semi-logarithmic scale. These base functions are located next to each other on the radius grid. In this way they define a so-called inversion window. The weight factors then are determined for each of the base functions. The width and position of the base functions is varied. In this way, 50 different inversion windows within the size range from 0.01 to 10 mm are tested for the reconstruction of the particle size distribution. The numerical solution procedure is highly instable. For that reason generalized cross-validation [Craven and Wahba, 1979; Golub et al., 1979] is applied as a stabilizing factor in the solution process. Constraints such as positive number concentration and smoothness of the particle concentration distribution are introduced in addition. [8] The inversion code tests 420 different wavelengthand size-independent complex refractive indices, which are contained within the kernel functions in equation (1). The real part takes values of 1.33, 1.35 to 1.8 in steps of The imaginary part takes values of 0, to 0.01 in steps of , 0.01 to 0.1 in steps of 0.01, and 0.1 to 0.7 in steps of 0.1. Mean values of the complex refractive index for the wavelength range from to mm automatically follow in connection with the accepted volume concentration distributions. The volume size distribution and the complex refractive index are then used for the calculation of the single-scattering albedo at 532 nm with a Mie-scattering code [Bohren and Huffman, 1983]. [9] The inversion results in profiles of the volume size distribution. Out of 21,000 possible solutions for the volume size distribution less than 100 generally comply with the imposed constraints. These solutions are accepted as final solution space. In dependence of data quality, a deviation of 10 20% between the input optical data and those calculated from the retrieved microphysical particle properties serves as final constraint. A deviation of approximately 5 10% of the input particle lidar ratios at 355 and 532 nm to the back-calculated values serves as another constraint, which was not used in the original version of the code [Müller et al., 1999a]. [10] Profiles of effective radius, surface-area, and volume concentration are calculated from the respective profiles of the volume size distribution. Number concentration in general gives no reasonable results, if mean particle size drops below approximately 0.15 mm. Because this value was found for many of the cases presented here no number concentrations will be given. An error analysis, which followed from simulations with synthetic as well as experimental data, showed that for realistic measurement errors of 20% the effective radius may be retrieved with an accuracy of 20 30%, volume and surface-area concentration with an accuracy of 50%, and the imaginary part to its correct order of magnitude [Müller et al., 1999b, 2000a;

3 MÜLLER ET AL.: POLLUTION DURING INDOEX AAC 3-3 Wandinger et al., 2002]. The real part is overestimated by as much as 0.1. The uncertainty of the single-scattering albedo is less than Data Processing [11] A detailed description of the retrieval of the optical particle parameters has been given elsewhere [Müller et al., 2001a; Masonis et al., 2002; Franke et al., 2003]. For the inversion of the optical data the respective profiles of the optical parameters were split into layers of variable depth of m. For each of these layers the individual data points of each profile were averaged. Thirty-five backscatter and extinction spectra were used for the analysis. Twentysix of these spectra represent the conditions during the polluted northeast monsoon. [12] Some measurements only provided backscatter coefficients at 355, 532, and 710 nm, because of a laser failure in March These reduced data sets were also used for the inversion. The inversion code initially has been developed to process the fixed number of backscatter and extinction coefficients provided by IfT s six-wavelength lidar. Müller et al. [2001c] presented results of a slightly modified version of the code, which allows one to handle a data set consisting of backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. In the case of the reduced data sets used here, the missing backscatter information at 1064 nm could be replaced by the backscatter information at 710 nm. Detailed simulation studies on the performance characteristics have not been done yet. Simulations with an advanced version of the present code [Veselovskii et al., 2002] showed that the inversion code can handle a set of input data of variable wavelengths. First tests however also indicate that in particular the missing optical information at 1064-nm wavelength destabilizes the inversion algorithm, and may even involve a systematic shift of the derived quantities. It presently is difficult to give a general quantification of this uncertainty, as it depends on the actual properties of the investigated particle size distributions. Sensitivity studies will be performed in future work. 3. Measurements 3.1. Case Study From 10 March 1999 [13] In the period from 8 March to 11 March 1999, a strong pollution outbreak was observed [Franke et al., 2003]. Backward trajectories showed that before 8 March 1999 the airflow above 1-km height was coming from Southeast Asia, whereas in the following days air was advected from northern India. Figure 1 shows the measurement example from 1457 to 1700 UTC on 10 March The optical properties were discussed by Franke et al. [2003]. Figure 1a shows the Ångström exponents, calculated from the lidar data for the wavelength range from 400 to 532 nm, and from 532 to 800 nm, respectively, and the lidar ratio at 532 nm. The physical parameters are shown in Figures 1b 1d. Each plot also shows the profile of the particle backscatter coefficient at 532 nm. We selected two height layers, i.e., from 1300 to 1650 m and from 2190 to 2340 m, for the following discussion. The latter height range describes the conditions in the center of the lofted pollution plume, whereas the first height range Figure 1. Measurement from 1457 to 1700 UTC on 10 March (a) Profile of the backscatter coefficient at 532 nm (solid line), the Ångström exponents for the wavelength range from nm (closed circles) and for the wavelength range from nm (open circles), and the particle lidar ratio at 532 nm (crosses). (b) Effective radius (closed circles) and single-scattering albedo (open circles). (c) Volume (closed circles) and surface-area (open circles) concentration. (d) Real part (closed circles) and imaginary part (open circles) of the complex refractive index. Vertical error bars denote the height ranges across which the optical data were averaged for the inversion. Accordingly, these error bars denote the height uncertainty for the derived parameters. Horizontal error bars denote statistical uncertainty. represents the conditions at the minimum backscatter of the plume. [14] The Ångström exponent in the wavelength range from 400 to 532 nm is of the order of It increases with height, as suggested by the mean values. The respective numbers for the Ångström exponent in the wavelength range from 532 to 800 nm are approximately 1.4. Ångström exponents above one indicate the presence of small particles. Figure 1b presents the effective radius for the respective height layers. Values of 0.14 ± 0.02 mm and 0.12 ± 0.03 mm

4 AAC 3-4 MÜLLER ET AL.: POLLUTION DURING INDOEX are found for the two height ranges. In contrast to the increase of the Ångström exponents the respective decrease of effective radius with height is insignificant. [15] The lidar ratio at 532 nm slightly increases with height from 51 sr to 60 sr. The lidar ratio depends on the absorption properties of the particles, and their mean size [Ansmann et al., 2002a; Müller et al., 2002; Franke et al., 2003]. Because particle size stays constant in the two height layers presented here, the slight increase of the lidar ratio points to an increase of particle absorption with height. [16] The assumption of absorbing particles is confirmed by the single-scattering albedo at 532 nm, which is shown in Figure 1b. Values are 0.93 ± 0.07 and 0.85 ± 0.07 in the two height ranges. Values below 0.9 are characteristic for comparably strong absorbing particles. Such low values of the single-scattering albedo were a general feature of air masses advected from northern India. [17] According to backward trajectory analysis, the air masses that arrived over Hulhule at 1500-m height had predominantly crossed less populated regions over Myanmar before turning to the southwest over the Bay of Bengal and southern India [Franke et al., 2003]. The air masses were moving at heights between 3 and 4.5 km. In contrast, the air mass that arrived at 2300-m height originated from the polluted Indian subcontinent, and passed over central parts of India at heights of 3 5 km above ground. The air mass then crossed the southern tip of India at heights of km above ground. [18] The results for the lidar ratio and the single-scattering albedo are also correlated with the complex refractive index. Figure 1d shows that the imaginary part increases with height from 0.015i ± 0.018i to 0.035i ± 0.02i. The real part increases with height from 1.53 ± 0.15 to 1.62 ± 0.1. [19] Figure 1c shows a large variability of volume and surface-area concentration. Volume concentration increased from approximately 16 ± 6 mm 3 cm 3 at the minimum of the particle backscatter peak to 30 ± 4 mm 3 cm 3 at the maximum of the backscatter peak around 2000-m height. Surface-area concentration increased from 360 ± 170 mm 2 cm 3 to 770 ± 180 mm 2 cm Air-Mass-Related Properties [20] Franke et al. [2003] identified pollution connected to three different advection channels that prevailed above 1-km height during the INDOEX Intensive Field Phase (INDOEX-IFP) and the campaign in March Pollution was advected from Southeast Asia (channel 1), from northern India (channel 2), and from southern India (channel 3). According to the backward trajectories, channel 1 includes all air masses which never were over the Indian subcontinent, or crossed only the southernmost part of India, before ending at Hulhule. Channel 2 includes the air masses which crossed northern India, and travelled out over the Bay of Bengal north of 16.5 N. In the case of channel 3 the air masses mainly crossed southern portions of India. [21] These clusters showed different optical properties. Lidar ratios of sr at 532 nm were frequently observed for plumes from northern India, indicating strongly light absorbing particles [Franke et al., 2001, 2003]. Southeast Asian plumes showed lidar ratios around 50 sr. The lowest values below 50 sr, on average, were found for air masses advected from southern India. These lidar ratios point to the advection of less absorbing aerosols from Southeast Asia and southern India. Ångström exponents for extinction in the wavelength range from 400 to 532 nm were for northern Indian pollution, and for southern Indian pollution. Larger values of were found for particle plumes from Southeast Asia. These numbers indicate that particles from Southeast Asia, on average, were smaller than particles from the Indian subcontinent. Two additional advection channels characterize the measurements of marine dominated conditions in July 1999 and October 1999 [Franke et al., 2003]. Air was transported from the southern Indian Ocean to the lidar site. One channel was defined by backward trajectories representing air masses that moved solely over the Indian Ocean before arriving at the lidar site. In the second case, the air masses in part had moved over eastern Africa before observation. In some cases air was also advected from the Arabian peninsula to the field site. [22] Our classification differs from the one provided by other observation platforms in the INDOEX area, e.g., the Kaashidhoo Climate Observatory (KCO) at the island of Kaashidhoo (4.97 N, E), Maldives [Lobert and Harris, 2002], and the National Oceanic and Atmospheric Administration (NOAA) Research Vessel Ronald H. Brown [Mühle et al., 2002]. It has to be observed that these sites were mainly performing in situ surface observations. Emphasis accordingly was put on air mass classification for the conditions close to the ground. Kaashidhoo was also influenced by air advected from the north and northwest across the Arabian Sea during the INDOEX-IFP, which is in strong contrast to the conditions above 1-km height. Figure 2 of Lobert and Harris [2002] gives an overview of the different advection channels that prevailed in different heights for an 11-year period. The Ron Brown covered a vast area of the Indian Ocean during its INDOEX cruise. For that reason a more detailed differentiation of air masses was necessary. A respective map showing the cruise track is given by Quinn et al. [2002]. An overview of the wind conditions near the surface during the INDOEX-IFP is provided by Verver et al. [2001]. [23] Figure 2 presents the results for effective radius, single-scattering albedo, and complex refractive index for the measurements from 2 March 1999 and 7 March These examples are representative for the advection of air from Southeast Asia. Figure 3 gives examples of advection from northern India, i.e., the measurements from 17 March and 24 March 1999 and from 19 March Figure 4 presents the measurements from 15 March and 17 March 2000 as examples from the southern India cluster. The results for the microphysical particle parameters of the southern India cluster in Figure 4 have to be considered with caution, because of the laser failure during the respective measurement period. As mentioned in section 2.2, the use of the reduced data set increases the uncertainty of the derived parameters. The increased uncertainty can be seen for example from the results on 15 March 2000 (Table 1). [24] The optical properties for 2 March 1999, 24 March 1999, and 17 March 2000 were presented by Franke et al. [2003], and will be considered in the following discussion. Mean Ångström exponents at short wavelengths were , , and for these three measurement cases. For comparison, a mean effective radius of 0.15 ±

5 MÜLLER ET AL.: POLLUTION DURING INDOEX AAC 3-5 Much larger mean values of 0.026i 0.034i are found for the example of northern India. The example from southern India gives a much lower imaginary part of 0.004i ± 0.003i. Similar real parts in the range from 1.44 to 1.58 and from 1.47 to 1.54 are found for the example of 2 March 1999 and 24 March 1999, respectively. The example from 17 March 2000 gives a lower real part of 1.34 ± [28] Table 1 summarizes the results for the effective radius, volume- and surface-area concentration. The table also include results of measurements previously published [Müller et al., 2000b, 2001b]. The table shows the strong Figure 2. Effective radius, single-scattering albedo, and the complex refractive index for the measurements (a) from 1456 to 1516 UTC on 2 March 1999 and (b) from 1407 to 1618 UTC on 7 March Arrows indicate that the error bar for imaginary part is at 0. The meaning of the symbols is the same as in Figure mm was found for the example of advection from Southeast Asia. Considerably larger mean values of 0.28 ± 0.09 mm are given for advection from northern India, and 0.38 ± 0.04 mm for advection from southern India. [25] The measurements presented in Figures 2 4 show that effective radii on average were smaller during advection of air from Southeast Asia, compared with the conditions during advection from the Indian subcontinent. A similar conclusion in terms of cluster mean Ångström exponents has been drawn by Franke et al. [2003]. [26] Differences were also found for the single-scattering albedo. The example from 2 March 1999 shows a value of approximately 1. The particle lidar ratio at 532 nm is approximately sr. For comparison, the mean single-scattering albedo varies around in the case of advection from northern India on 24 March The lidar ratio varies between 60 and 90 sr. A large single-scattering albedo of 0.97 was found for the example of southern India on 17 March The lidar ratio of sr is lowest for the three cases considered here. [27] The differences seen for the single-scattering albedo are also valid for the complex refractive index. Imaginary parts are less than 0.005i for the example of Southeast Asia. Figure 3. Effective radius, single-scattering albedo, and complex refractive index for the measurements (a) from 1429 to 1706 UTC on 17 March 1999, (b) from 1415 to 1515 UTC on 24 March 1999, and (c) from 1522 to 1728 UTC on 19 March The meaning of the symbols is the same as in Figure 1.

6 AAC 3-6 MÜLLER ET AL.: POLLUTION DURING INDOEX Figure 4. Effective radius, single-scattering albedo, and complex refractive index for the measurements (a) from 1413 to 1513 UTC on 15 March 2000 and (b) from 1415 to 1515 UTC on 17 March The meaning of the symbols is the same as in Figure 1. variability of the aerosol conditions, not only in dependence of the advection channels but also within each advection channel. Effective radii varied by a factor of 4, volume and surface-area concentration by a factor of 8. [29] The different source regions determine the differences in the optical properties. Franke et al. [2003] give a detailed discussion on that. Possible reasons are (1) differences in the removal processes of large particles by, e.g., precipitation along the different advection paths, (2) differences in the strength of small-scale and mesoscale convective lifting along the different advection paths, which may have lead to the injection of large marine particles into the lofted particle layers, (3) the presence of large amounts of soil dust in Indian air masses, (4) different aging processes, and (5) a different fraction of biomass-burning particles. [30] In particular, the latter point is the most likely reason for the observed differences of the lidar ratios. Franke et al. [2003] pointed to the comparably high amount of absorbing material advected from northern India to the field site. High absorption is reflected in large lidar ratios. The result of highly absorbing aerosols is supported by linking the lidar observations with backward trajectory to emission inventories for India [Reddy and Venkataraman, 2002a, 2002b]. It is shown that the sulfur-dioxide/bc ratio (BC = black carbon), or its conversion to the ammonium-sulfate/bc ratio, is considerably lower for aerosol emission fluxes from northern India compared with those from southern India [Franke et al., 2003]. Typical values are 3 10 for the latter. Similar conditions as for southern India also hold for Thailand, which is the main contributor in Indochina, and for east Asia [Streets and Waldhoff, 1998]. An inventory of carbonaceous emissions presented by Cooke et al. [1999] also shows a strong contribution of black carbon to total carbonaceous emissions over Thailand and China. [31] As for the optical properties, the microphysical particle properties also show differences. Case studies for Southeast Asian aerosols and Indian aerosols which relate the observed microphysical properties to the specifics of the source regions are given by Müller et al. [2001b]. The strong absorption of particles from northern India is reflected in the comparably large imaginary parts of the complex refractive index. The single-scattering albedo on average was lowest for these particles. Much lower imaginary parts were found for particles from Southeast Asia and southern India. The single-scattering albedo in such cases often exceeded [32] It has to be kept in mind that the number of measurement cases used for the microphysical particle characterization of the pollution plumes is much smaller than the number of cases used for the optical characterization. We selected 27 cases from 11 measurement days. 120 cases from 37 measurement days were available for the optical characterization of the pollution plumes [Franke et al., 2003]. In addition, the uncertainties of the microphysical parameters are larger. A generalization of the results therefore has to be considered with caution. [33] Fuel consumption in terms of biomass burning by far exceeds the use of fossil fuel in India [Dickerson et al., 2002; Reddy and Venkataraman, 2002a, 2002b]. Franke et al. [2003] discussed that large areas in northern and central parts of India, and along the east coast of southern India are characterized by a comparably low ratio of fossil fuel to biomass combustion. Respective information is drawn from highly resolved emission inventory data [Venkataraman et al., 1999; Reddy and Venkataraman, 2000, 2002a, 2002b]. Franke et al. [2003] showed that large Ångström exponents >1.5 mostly were related to air masses advected from Southeast Asia. In contrast, values <1 in most cases indicated particles from India. Effective radii on average were smallest for air masses advected from Southeast Asia. Particles from India on average were larger. In particular southern India showed very large values, see Table 1. However, it has to be kept in mind that in these cases only a reduced optical data set was used for the inversion, see section 2.2. The large amount of biomass combustion, made up of fuelwood, crop waste, dung cake, etc., in India leads to large particles with mm in diameter, compared with a diameter of mm for particles from diesel combustion [Venkataraman and Rao, 2001]. The contribution of biomass burning to total fuel consumption is approximately 25% in Thailand, 34% in the Philippines, and 25% in China [Streets and Waldhoff, 1998]. The mean particle size of Southeast Asian particles in this case should be smaller compared to the mean particle size from India. [34] Maximum BC contents of 15 20% of the fine particle mass were found in elevated Indian aerosol plumes [Novakov et al., 2000]. Chemical analysis of particles

7 MÜLLER ET AL.: POLLUTION DURING INDOEX AAC 3-7 Table 1. Physical Particle Parameters and Respective Standard Deviations for Pollution Observed During the Northeast Monsoon a Date Airflow Height, m r eff, mm v, mm 3 cm 3 s, mm 2 cm 3 18 February 1999 SEA 1325 ± ± ± ± February 1999 SEA 2000 ± ± ± ± 37 2 March 1999 SEA 1320 ± ± ± ± 15 2 March 1999 SEA 2125 ± ± ± ± 7 7 March 1999 SEA 1065 ± ± ± ± 50 7 March 1999 SEA 1488 ± ± ± ± March 1999 NI 1475 ± ± ± ± March 1999 NI 2265 ± ± ± ± March 1999 NI 1575 ± ± ± ± March 1999 NI 2275 ± ± ± ± March 1999 NI 1390 ± ± ± ± March 1999 NI 1925 ± ± ± ± March 1999 NI 2375 ± ± ± ± March 1999 NI 900 ± ± ± ± March 1999 NI 1700 ± ± ± ± March 1999 NI 2100 ± ± ± ± March 1999 NI 2500 ± ± ± ± March 1999 NI 2900 ± ± ± ± March 1999 NI 3300 ± ± ± ± March 2000 SI 1364 ± ± ± ± March 2000 SI 2234 ± ± ± ± March 2000 SI 1885 ± ± ± ± 4 19 March 2000 NI 1215 ± ± ± ± 9 19 March 2000 NI 1650 ± ± ± ± March 2000 NI 1400 ± ± ± ± March 2000 NI 2200 ± ± ± ± 80 a Standard deviation for the measurement heights denotes the height range across which optical data were averaged for the inversion. Here, r eff denotes the effective radius, v denotes the volume concentration, and s denotes the surface-area concentration. SEA means that backward trajectories indicated transport of air masses from Southeast Asia. NI and SI was characterized by transport of air from northern India and southern India, respectively. Results for the measurements on 18 February 1999 are discussed by Müller et al. [2001b]. Results for the measurements on 25 March 1999 are discussed by Müller et al. [2000b, 2001b]. The measurement from 22 March 2000 is presented by Müller et al. [2001b]. collected aboard the National Center for Atmospheric Research (NCAR) C-130 aircraft showed high concentrations of carbonaceous aerosol and pollution-derived inorganic species in heights up to 3.5 km [Gabriel et al., 2002; Mayol-Bracero et al., 2002]. Carbonaceous aerosols contributed 40 60% to the overall determined fine aerosol mass, i.e., for particle diameters <1 mm. Gabriel et al. [2002] report a fraction of 16% of black carbon. Aircraft observations showed that the contribution of carbon to total aerosol mass increased with height. [35] As mentioned before, other reasons may also be responsible for the differences in particle size. Coarse-mode soil particles from arid and semi-arid regions of India, as well as road dust, and mineral particles from the Arabian peninsula might be responsible for some of the observed large mean particle sizes. Measurements of the particle depolarization ratio however did not indicate a significant contribution from this particle component. It is not clear yet in what way aging effects may have caused a modification of particle size through condensation and liquid-phase chemical reactions. Strong forest fire activity in India and Indochina in the month of March [Goloub and Arino, 2000] may also lead to an increase in mean particle size. Large effective radii of approximately 0.25 mm were found in forest fire plumes which had travelled from northwestern Canada to Europe within six days [Wandinger et al., 2002] Correlation Analysis [36] Figures 5 7 show results of a correlation analysis for the physical particle parameters, including several optical Figure 5. (a) Effective radius versus Ångström exponent for the short-wavelength range from nm (closed circles) observed during INDOEX. Also shown are results for Ångström exponents in the wavelength range from nm observed during ACE 2 [Müller et al., 2002] (open circles). Parameters in the legend are from linear regression analysis according to the formula y = a + bx. Parameters are given for the INDOEX results, and for all data points shown. The correlation coefficients are given in the text. Results for ACE 2 are discussed in detail by Ansmann et al. [2002a] and Müller et al. [2002]. (b) Effective radius versus particle lidar ratio at 532 nm for polluted conditions during INDOEX (closed circles), and during ACE 2 (open circles).

8 AAC 3-8 MÜLLER ET AL.: POLLUTION DURING INDOEX SINGLE-SCAT. ALBEDO (a) a = 0.99 (0.04) b = (0.0006) all a = 1.02 (0.02) b = (0.0004) (b) a = 0.99(0.01) b = - 3.8(0.3) all a = 0.99(0.004) b = - 4.1(0.2) LIDAR RATIO (sr) REFR. INDEX, REAL PART REFR. INDEX, IMAG. PART Figure 6. Single-scattering albedo at 532 nm versus (a) particle lidar ratio at 532 nm and (b) the real part and (c) the imaginary part of the complex refractive index. The meaning of the symbols and the regression parameters is the same as in Figure 5. The correlation coefficients are given in the text. Also shown are the results for the clean-marine case from 20 June 1997 observed during ACE 2 (open triangles) [see Müller et al., 2000a, 2002], and clean marine cases observed on 9 July, 14 October, and 16 October 1999 during INDOEX (closed triangles). The case from 16 October 1999 is discussed by Müller et al. [2001b]. (c) parameters presented by Franke et al. [2003]. A simple linear regression fit was applied to each of the parameter sets. The parameters of slope and intercept are given in the respective legend of each figure. Also shown for comparison are results from six-wavelength lidar measurements performed during the Aerosol Characterization Experiment (ACE) 2 [Ansmann et al., 2001, 2002a; Müller et al., 2002]. ACE 2 aimed at the characterization of pollution advected from the European continent out over the North Atlantic Ocean [Raes et al., 2000; Russell and Heintzenberg, 2000]. The lidar observations were made in Sagres (37 N, 9 W), Portugal, in June/July [37] Figure 5a shows that effective radius increases with decreasing Ångström exponents. A correlation coefficient of approximately 0.65 ( p < 0.001) was found, if all inversion results obtained for INDOEX and ACE 2 were considered. The parameter p gives the probability that the correlation coefficient is zero. The correlation is explained by the fact that the spectral slope of the extinction coefficient, which determines the Ångström exponents, is mostly influenced by particle size. The correlation coefficient marginally decreases to 0.64, if only the INDOEX results are considered. [38] Figure 5b shows a wide scatter of effective radii from approximately mm for the range of lidar ratios found from INDOEX. In the case of the ACE-2 results the scatter is even larger. A reason for the lower correlation of effective radius to lidar ratio, compared with the correlation to the Ångström exponents, may be the fact that the particle lidar ratio is also controlled by the particle complex refractive index. [39] According to Figure 6a the single-scattering albedo increases with decreasing lidar ratio. The single-scattering albedo covers a wide range of values from 1 to 0.75, which points to the highly variable amount of black carbon in these particles. As outlined in the preceding section, the variability of the single-scattering albedo may also result from a variable influence of mineral particles and/or marine particles, as well as differences in particle aging effects. The results from pollution observed during INDOEX show a low correlation of 0.42 ( p = 0.025). If all results from INDOEX and ACE 2 are considered, the correlation only slightly increases to 0.49 ( p < ). Franke et al. [2003] argued on the basis of Mie-scattering calculations that a significant increase of the lidar ratio should occur, if the ratio of particle absorption to the scattering coefficients and/ or the particle size distribution changes significantly. Several reasons may be responsible for the low correlation found here. In the case of ACE 2 the range of lidar ratios and single-scattering albedos is rather limited. In combination with the uncertainties of 10 20% for these parameters the correlation may be diminished. It has to be observed that the INDOEX observations include three different source regions, which differ in their aerosol properties. The correlation for particles from these source regions may be different. The low number of cases for each source region at the moment does not permit a proper correlation analysis. In Figure 6 of Müller et al. [2002] we reported a correlation Figure 7. (a) Particle lidar ratio at 532 nm versus (a) the real part and (b) the imaginary part of the complex refractive index. The meaning of the symbols is the same as in Figures 5 and 6.

9 MÜLLER ET AL.: POLLUTION DURING INDOEX AAC 3-9 coefficient of 0.9 for the northern India cluster. Only few measurement cases were available at that stage of data processing. The extended data set for the northern India cluster presented here considerably lowered this correlation of 0.9. Large particles from southern India showed lower absorption compared with particles from northern India. The relationship between single-scattering albedo and lidar ratio in such cases is different from the one for absorbing particles from northern India. The lidar ratio is much more influenced by the combined effect of particle size and imaginary part of the complex refractive index than singlescattering albedo. [40] Figures 6b and 6c show the relationship of the single-scattering albedo to the complex refractive index. Figure 6b shows a wide scatter of real parts. The variability of the real part seems to be less at low single-scattering albedos, if results from INDOEX and ACE 2 are considered together. Figure 6c shows a very strong correlation of the single-scattering albedo with the imaginary part, i.e., the lower the single-scattering albedo the higher the imaginary part. The correlation coefficient is 0.93 (p < 0.001), if all results from INDOEX and ACE 2 are considered. The correlation is 0.94 (p < 0.001) for the INDOEX results. [41] Figure 7 presents the relationship between lidar ratio and complex refractive index. Figure 7a shows a large scatter of the real parts found for INDOEX. The results from ACE 2 show a moderate correlation coefficient of approximately 0.5 (p = ). This difference again could be caused by the fact that aerosols from very different source regions were present during INDOEX. Figure 7b shows the correlation of the lidar ratio with the imaginary part. The correlation is rather weak. The range of imaginary parts increases with increasing lidar ratio. 4. Discussion [42] The results will now be put into the context of other observations made during INDOEX. At the end of this section we will compare our findings to results from several field campaigns conducted in the past years. The Aerosol Characterization Experiment 2, the Tropospheric Aerosol Radiative Forcing Experiment (TARFOX), which took place in the North Atlantic east of the United States [Russell et al., 1999a], and the Lindenberg Aerosol Characterization Experiment (LACE 98), which took place in central Europe [Ansmann et al., 2002b], aimed at the characterization of emissions from some of the highly industrialized regions in the world. The Smoke, Clouds, and Radiation-Brazil experiment (SCAR-B), which took place in the Amazon region [Kaufman et al., 1998], and the Zambia International Biomass Burning Emissions Experiment (ZIBBEE), which took place in the African savanna [Eck et al., 2001b], focused on particle properties from biomass burning Comparison to Other INDOEX Platforms [43] Table 2 presents the mean values of the particle parameters shown in Table 1. Only the mean values of the individual cases were considered for the calculation. Table 2 also shows the mean values from measurements made during the clean periods in July 1999 and October The numbers are based on four individual measurement days. The effective radius is considerably larger during Table 2. Mean Values of the Physical Particle Parameters and the Respective Standard Deviations on the Basis of the Pollution Plumes Observed During INDOEX-IFP and March 2000, as Well as Clean Marine Conditions During July and October 1999 a Pollution Clean Marine r eff, mm 0.20 ± ± 0.19 v, mm 3 cm 3 21 ± ± 9 s, mm 2 cm ± ± 70 m real 1.54 ± ± 0.08 m imag ± ± ssa 0.90 ± ± 0.01 a The uncertainty reflects the variability of the aerosol conditions during the observational period. Here, r eff denotes the effective radius, v denotes the volume concentration, and s denotes the surface-area concentration. m real is the real part and m imag the imaginary part of the complex refractive index. ssa denotes the single-scattering albedo at 532 nm. clean-marine conditions. Volume concentration is 30% lower. Mean surface-area concentration drops by a factor of four. Single-scattering albedo is larger. The complex refractive index is characteristic for the clean marine conditions that prevailed during the southwest monsoon. [44] The effective radius characterizing the northeast monsoon is 0.20 ± 0.08 mm. A similar value is found, if only observations during the INDOEX-IFP are considered. Airborne observations of particle size distributions were conducted aboard the research aircraft Citation [de Reus et al., 2001, 2002]. The aircraft was operated by the Technical University of Delft, Netherlands. Particle counters were used to detect particle number concentration in the radius range from to 1.75 mm. The flight legs covered the height range from within the marine boundary layer up to 12.5 km. The flights were made at a maximum distance of 1500 km from Hulhule airport. A map of the flight tracks is given by de Reus et al. [2001]. A mean effective radius of 0.13 mm was found for the height range from 1 to 3.5 km. The measurements were done at approximately 55% relative humidity. [45] Surface-based observations were made aboard the R/ V Ronald H. Brown. Condensation particle counter, differential mobility particle sizer, and aerodynamic particle sizer were used for measurements of particle number size distribution in the radius range from 0.01 to 2.5 mm [Quinn et al., 2002]. All measurements were performed at 55 ± 5% relative humidity. The following numbers characterize air masses that were advected from the Indian subcontinent in low heights over the Indian Ocean (see Table 2 of Quinn et al. [2002]). The ship was in an area between 4 and 10 N, and between 68 and 73 E during the period considered here. [46] The ship-based observations showed that the marine boundary layer was highly polluted, and contained a comparably low amount of marine particles. Quinn et al. [2002] report mode radii and mode widths for measured particle size distributions. Effective radii calculated from the mean parameters given for the particle size distributions in the accumulation mode, i.e., below 0.5 mm in radius, were approximately 0.21 mm. Air masses were defined as East Indian Subcontinent and Indian Subcontinent by Quinn et al. [2002]. The numbers are in the range of effective radii obtained for the pollution plumes above the marine boundary layer; see Table 2. The ship-based measurements describe particles in their dry state. Quinn et al. [2002] do not provide particle sizes corrected for increasing relative

10 AAC 3-10 MÜLLER ET AL.: POLLUTION DURING INDOEX humidity. We assume that the accumulation-mode particles close to the ocean surface are larger at ambient conditions than particles in the lofted pollution plumes. The free troposphere in general is comparably drier (relative humidity <60%) than the marine boundary layer. Effective radii determined from measurements aboard the Citation in the marine boundary layer were on the order of 0.14 mm. This number is considerably smaller than the value derived from the ship measurements near the sea surface. [47] A comparison with the other platforms can be done with respect to the Ångström exponents. A presentation of the Ångström exponents derived from the lidar observations has been given by Franke et al. [2003]. Table 3 summarizes the results for the Ångström exponents. [48] Ångström exponents in the wavelength range from 400 to 532 nm were 1.3 ± 0.3 during the INDOEX-IFP. This number describes the conditions above 1-km height. For comparison, a column value of 0.88 ± 0.31 at nm was found from our Sun photometer (manufactured by Dr. Schulz & Partner GmbH, Buckow, Germany) observations at the lidar site [Wagner et al., 2001]. This value is considerably lower than the one from the lidar observations. It indicates the influence of marine particles below 1-km height. [49] Ångström exponents for the wavelength range from 550 to 700 nm measured aboard the C-130 were 1.69 ± 0.3 and 1.71 ± A map showing the area covered by the C-130 research flights is given by Clarke et al. [2002]. The numbers hold for 40 55% relative humidity [Clarke et al., 2002; Sheridan et al., 2002]. The Ångström exponents describe the conditions below 1-km height, and take account of particles with radii below 1.5 mm. Similarly large Ångström exponents of 1.9 ± 0.46 to 2.03 ± 0.15 are reported for pollution plumes in heights from 1 to 3 km. The lower values in both cases are valid for observations north of 5 N, whereas the upper values refer to observations between 1 S and 5 N. Correction to ambient relative humidity shifts the Ångström exponents to lower values. With respect to observations below 1-km height, numbers are 1.82 ± 0.31 north of 5 N, and 1.83 ± 0.11 between 1 S and 5 N. Values are 1.83 ± 0.52 and 2.24 ± 0.77 in the height range from 1 to 3 km for these two latitude bands [Sheridan et al., 2002]. [50] Ångström exponents were measured for the wavelength range from 450 to 700 nm with an integrating nephelometer aboard the Ron Brown. A value of 1.5 ± 0.25 was found for air masses advected from India [Quinn et al., 2002]. This number holds for particle radii below 10 mm, and a relative humidity of approximately 55%. Sun photometer observations aboard the Ron Brown resulted in Ångström exponents of 1.1 ± 0.17 to 1.29 ± 0.08 (reported as 1.2 ± 0.13 in Table 3) for air masses advected from the Indian subcontinent [Quinn et al., 2002]. The numbers are valid for the wavelength range from 415 to 862 nm. Within the uncertainty limits, the value derived from the in situ measurements aboard the Ron Brown is within the range of 1.3 ± 0.3, which is derived from the lidar observations for the wavelength range from 532 to 800 nm for the period of February/March The numbers from the C-130 are considerably larger than the lidar values. [51] The Sun photometer observations performed at the lidar site yield a comparably low Ångström exponent of Table 3. Mean Values of the Ångström Exponents Derived From the Different Measurement Platforms During INDOEX-IFP a Height Range rh l å Lidar 1 3 km ambient nm 1.3 ± 0.3 Lidar 1 3 km ambient nm 1.13 ± 0.33 SPM/Hulhule column ambient nm 0.88 ± 0.31 SPM/Hulhule column ambient nm 1.1 ± 0.3 SPM/Kaashidhoo column ambient nm 1.24 ± 0.2 SPM/Goa column ambient nm 1.4 ± 0.15 SPM/Ron Brown column ambient nm 1.2 ± 0.13 In situ/ron Brown surface 75% nm 1.3 ± 0.3 C-130 (NIO) 1 3 km ambient nm 1.83 ± 0.52 C-130 (CIO) 1 3 km ambient nm 2.24 ± 0.77 C-130 (NIO) 0 1 km ambient nm 1.82 ± 0.31 C-130 (CIO) 0 1 km ambient nm 1.83 ± 0.11 a Also given are the wavelength range and the relative humidity for which the respective values hold. Here, å denotes the Ångström exponent, rh denotes relative humidity, and SPM denotes Sun photometer. In the case of the in situ platforms, observations were made under dry conditions; that is, relative humidities were at or below 55%. The numbers subsequently were corrected for relative humidity as given in the table. Further information on the corrections is given by Sheridan et al. [2002] (C-130) and Quinn et al. [2002] (R/V Ron Brown). The numbers for the C-130 consider particle radii <1.5 mm. NIO denotes aircraft observation north of 5 N. CIO denotes aircraft observation between 1 S and 5 N. 1.1 ± 0.3 for the wavelength range from 530 to 800 nm for the same period. Ångström exponents of 1.24 ± 0.2 in the wavelength range from 440 to 870 nm were found from Sun photometer observations at Kaashidhoo [Eck et al., 2001a]. Sun photometer observations were also made at Goa (15.48 N, E), at the southwestern coast of India [Léon et al., 2002]. Ångström exponents were 1.4 ± 0.15 in the wavelength range from 440 to 875 nm, and characterize the conditions during advection of pollution from within the Indian subcontinent in March The observations at Goa describe the aerosol conditions in the source regions, and thus may explain the somewhat larger value compared with the Ångström exponents observed at the measurement platforms in the Indian Ocean. Even the Ångström exponents from the Goa site are considerably lower than the values found from the aircraft observations. [52] All the cases presented in Table 3 are based on longterm observations. On a statistical reasoning, the differences, therefore, cannot be only explained by differences in the time periods the observations were made. The difference may more likely be caused by the dry conditions at which particles were detected by the in situ platforms, and errors introduced by the correction to ambient conditions. Cutoff effects of the particle inlet system most likely are another reason for the large Ångström exponents. Lidar observations showed a mean extinction coefficient of 90 ± 59 Mm 1 (Mm = Megameter = 10 6 m) at 532 nm for the column above 1-km height. A mean value of 200 ± 70 Mm 1 was found for the height range from 0 to 1 km. Extinction coefficients of 70 ± 47 Mm 1 to 77 ± 42 Mm 1 at 550 nm were found from C-130 observations in the height range from 1 to 3 km, which is dominated by small anthropogenic pollution. In contrast, extinction coefficients were much lower than the lidar derived values for the height range from 0 to 1 km. In that case, the C-130 values are 84 ± 26 Mm 1 to 121 ± 50 Mm 1 for particle radii <1.5 mm. Obviously the aircraft inlet system rejected the large marine particles [Clarke et al., 2002].