IASTA-2010
A–P–11
Effect of Dust and Rain Events on Aerosol Optical Properties and Radiation
R Latha1, B S Murthy1, S Jyotsna2, S Manoj Kumar2, S Dipu1 and G Pandithurai1
1 Indian Institute of Tropical Meteorology, Pune
2 Birla Institute of Technology, Ranchi
A case study is presented in terms of aerosol optical depth (AOD), single scattering albedo (SSA), and volume size distribution using Prede skyradiometer measurements at Ranchi during March and April 2009. Solar radiation is measured with Kipp & Zonen radiometer.
A rain event on March 21st reduced AOD at all wavelengths and the reduction is from 0.55- 0.35 at 500nm on the next day (fig.1). Similarly SSA on 22nd at all wavelengths except 1020nm show an increase indicating less absorbing aerosols in the atmosphere, increase at 500nm is about 0.07 (0.9-0.97) (fig. 2). Angstrom exponent, a measure of aerosol size shows an increase from 1.15 to 1.29, due to an effective washout of larger particles. Volume size distribution is more or less bimodal and March 21 has (fig. 3) more concentration of larger size particles compared to the day after rain. Concentration of smaller particle remains roughly the same. Forenoon of March 21st was clear and hence short wave radiation till 12 noon is higher and with lesser fluctuations than that of 22nd as it was a slightly cloudy day. The peak in radiation got diminished due to cloud effect.
Figure 1. AOD variations during a rain event: it rained on March 21 evening and the reduction in AOD due to washout is visible the next day
A dust event April 2nd around 1400 hrs is studied for its optical properties and its comparative effect on reduction in radiation. AOD increased at all wavelengths showing
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Figure 2. Single scattering albedo depicts cleaner atmosphere the day after rain.
Figure 3. Volume size distribution on March 21 and 22 showing reduction in bigger particle fraction.
an increase by 0.9, with a corresponding reduction in SSA from 0.90 to 0.84 at 1020nm showing highest variation. Volume size distribution indicates that the particle size is larger during the event in the coarse mode at 5.7 micron with about double concentration to that of the previous day. While the variation in solar radiation from 14:05 to 14:18 is 33 W/m-2 on the previous day it is 88 W/m-2 during dust event, it is also noticeable that the peak radiation is also diminished by about 50 W/m-2 for the dust event day. It is also noticeable that the peak in radiation also diminished by 50w/m-2 for the day compared to the previous day. An increase in wind speed for the period is evident during the occurrence of event.
The observations show that washout is more effective on larger particles and the dust event is capable of inducting a reduction in radiation for a short while probably comparable to a thin cloud. More events are being studied to confirm the consistency of the results.
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Figure 4. AOD, SSA and Volume size distribution on the previous day of dust event, for the period 13-15 hrs.
Figure 5. AOD, SSA and Volume size distribution on the dust event day, for the period 13-15 hrs.
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Figure 6. Variation in radiation and wind speed from 14hrs to 14.5hrs on the dust event day and on the previous day
References
Che, H, H. Shi, A .Uchiyama, A. Yamazaki, H. Chen, P. Goloub and X, Zhang (2007) Intercomparison between aerosol optical properties by a PREDE skyradiometer and CIMEL sunphotometer over Beijing, China,
Atmos. Chem. Phys. Discuss., 7, 16023-16053.
Prasad, A.K and R. P, Singh (2007) Changes in aerosol parameters during major dust storm events (2001-2005) over Indo-Gangetic plains using AERONET and MODIS data, J .Geophy. Res., 112,doi10.1029/ 2006JD0007778.
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A–P–12
Aerosol Properties of the Regions Around Goa
Madhubala Talaulikar, T. Suresh, Ancy Rodrigues, Shaikh Bilaloddin, and Prakash Chauhan*
National Institute of Oceanography, Dona-Paula, Goa - 403004
*Space Application Centre, Ahmedabad
Email: mtalaulikar@gmail.com
Aerosols have gained equal importance compared to green house gases due to their impact on the climate. After the revelation of Asian Brown Cloud from various
| studies conducted, and considering the | ||
| importance of aerosols, it has prompted to | ||
| examine the aerosols at regional scale. Here we | ||
| present the aerosol properties of the | ||
| measurements carried-out from 2000 –2009 at | ||
| the coastal Konkan regions, which include south | ||
| of Maharashtra (Ratnagiri and Malvan), Goa | ||
| and Karnataka (Karwar, Murdeshwar and | ||
| Malpe). The mean aerosol optical depths at | ||
| 500nm of the regions, AOD(500) is 0.44(±0.16) | ||
| and the Angstrom exponent is 1.33 (±0.4). | The | |
| mean aerosol optical depths at 500nm, AOD | ||
| (500) are 0.493, 0.462, 0.432, 0.496, 0.533, and | ||
| 0.557 for the region of Ratnagiri, Malvan, Goa, | ||
| Karwar, Murudeshwar and Malpe respectively. | ||
| Figure 1 | There is a distinct seasonal variations observed | |
| with relatively higher aerosols being observed | ||
| during the summer (AOD (500) = 0.5) than | ||
| winter (AOD (500) = 0.4). The Angstrom | ||
| exponents also showed a well-defined pattern | ||
| indicating smaller particles being abundant | ||
| during winter (a = 1.52) and relatively coarser | ||
| particles during summer (a = 1.12). | (See | |
| Fig.1).The mean Angstrom exponents are 1.50, | ||
| 1.42, 1.31, 1.41, 1.344, and 1.41 for Ratnagiri, | ||
| Malvan, Goa, Karwar, Murudeshwar and | ||
| Malpe respectively. | ||
| Gradient of AOD with latitude is observed | ||
| and this gradient is found to reverse with | ||
| summer and winter seasons. The gradient of | ||
| Figure 2 | AOD is positive with increasing latitude during | |
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winter and the reverse pattern in observed during summer. (See Fig. 2).
One of the notable features observed for the region of Goa was inter-annual variation of Angstrom exponent with a steady increase in the Angstrom exponent, indicative of the abundance of smaller particles. (See Fig.3).
| Figure 3 | Figure 4 |
The diurnal variations are also seen with relatively low aerosols during evening. The particle size distributions measured also confirmed of these seasonal pattern. We have also looked at the effect of rain on the variation of aerosol and also the scavenging effect on the particle size distributions. A positive correlation was observed between the summer monsoon and the Angstrom exponent. (SeeFig.4)
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A–P–13
A Study of the Aerosol Characteristics over Patiala
Manjit Singh, Deepti Sharma and Darshan Singh
Physics Department, Punjabi University,Patiala-147002
Manjit99@aol.in
Introduction
Atmospheric aerosols influence the earth’s radiation balance by scattering and /or absorbing the sunlight (Charlson et. al. 1992). Furthermore, aerosols have an indirect effect by acting as cloud condensation nuclei resulting in a change in the optical properties and lifetime of clouds in the atmosphere. Patiala (lat; 300 20’N, long. 760 24’E) is situated in the northwest part of Indo-Gangetic plains where significant seasonal variations in AOD, aerosol mass concentration and their optical properties are expected due to increased anthropogenic activities. This region experiences four dominant seasons each year: winter (December-March), pre-monsoon (April-June), monsoon (July-September) and post- monsoon (October-November). During pre-monsoon season, air mass carries dust particles by southwesterly winds from Thar Desert (Sikka D.R. 1997) and during post-monsoon season, atmosphere is loaded with black carbon due to large scale biomass burning of paddy residue in the fields. Under ISRO-GBP “ARFI” project; measurements of aerosols optical depth (AOD) by Multi-Wavelength Radiometer (MWR) and mass concentration by High Volume Sampler (HVS) have been carried out over Patiala since April 2006 (Manjit Singh et.al. 2008). The present paper highlights the temporal variations in the aerosol characteristics over Patiala from April 2006 to October 2009.
Observations and Results
Spectral AOD values and columnar water vapor were estimated following the Langley Plot technique applied on the spectral extinction measurements made by MWR. Mean spectral AOD at all wavelengths is minimum (0.15-0.6) during winter and is maximum (0.3-1.3) during post-monsoon (Fig 1 a-d). However during pre-monsoon season AOD at longer wavelengths is higher than other seasons indicating the dominance of the coarse dust particles due to wheat threshing and frequent dust storms. On the other hand, AOD is highest at shorter wavelengths during post-monsoon season mainly due to submicron black carbon aerosols produced by burning of paddy residue. Though spectral AOD is minimum during winter but its spectral variations are similar to that during post monsoon indicating that same type of aerosols still persist but with diminishing concentration.
Angstrom Parameters
Spectral variation of AOD is primarily determined by the aerosol size distribution, which is governed by the sources present in the atmosphere. Angstrom parameter a that indicates the aerosol size distribution is computed from a linear fit of log (AOD) versus log (wavelength) according to Angstrom relation (Angstrom, 1964)
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Figure 1. Seasonal variation of spectral AOD
Where is turbidity coefficient and a is wavelength exponent. Fig. 2 shows that a has high values (1.0-1.8) from October to February and decreases thereafter and becomes minimum (0.3-0.8) in May and June for all the years. This shows the dominance of fine particles during post-monsoon and winter seasons probably due to high concentration of black carbon and high loading of coarse particles due to dust storms in pre-monsoon season. However, turbidity parameter is high during pre-monsoon as well as post–
Figure 2. Temporal Variation of Angstrom Parameters
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monsoon season showing high aerosol loading but it is minimum in winter for all the years under study.
Suspended Particulate Matter (SPM)
Particle mass concentration measurements were made with HVS that separates the fine and coarse particles viz. RSPM and NRSPM. Monthly mean variations of RSPM and NRSPM are shown in fig 3. Mass concentration of RSPM is low (100-150 μgm/m3) during pre-monsoon season and high (330-500μgm/m3) during post-monsoon and winter seasons. NRSPM varies from (50-600 μgm/m3) and is highest during pre-monsoon season. NRSPM may jump to 750 μgm/m3 during sever dust storms.
Figure 3. Temporal variation of SPM (μgm/m3)
Conclusion
Mean monthly spectral AOD shows significant seasonal variations over all the years of study. Post-monsoon and winter seasons are dominated by fine particles but coarse particles dominate during pre-monsoon season. Dust storms and biomass burning have significant effect on the spectral AOD variations over Patiala. Angstrom parameters and SPM also exhibit significant seasonal variation over the period of study.
Acknowledgement
Present work has been carried out under ISRO-GBP (ARFI) project. Financial help rendered by ISRO is highly acknowledged.
References
1.Angstrom A., The parameters of atmospheric turbidity, Tellus, 16, (1964) 64-75.
2.Charlson R. J. et.al, Climate forcing by anthropogenic aerosols, Science, 255, (1992) 423-430.
3.Manjit Singh et.al., Aerosol characteristics at Patiala during ICARB- 2006, J. Earth Sys. Sci. 117, S1, (2008) 407-411.
4.Sikka D.R., Desert climate and its dynamics, Curr. Sci., 72(1), (1997) 35-46.
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A–P–14
Retrieval of Background Mesospheric Dust Density Profiles from Experimental Electron and Positive Ion Density Profiles
N. Srinivas
Department of Post Graduate Studies in Physics (Mysore University) Government Autonomous College, Mandya-571401, India.
(On Deputation from Maharani’s Science College for Women (Mysore University), Mysore-570 005)
ABSTRACT : A detailed heterogeneous ion-chemistry model has been developed for a mesosphere where the role of dust/aerosols, as both sink and source for electrons and ions, has been included in the ion-chemistry of the region. This model is seen to have several applications in the studies of ion-chemistry and dynamics of the region and also in the studies of atmospheric electrical parameters. In the present study, a method is used to retrieve the effective size and steady state background density of mesospheric aerosols (both charged and neutral) from a set of simultaneously observed total positive ion and electron density profiles. The results presented are for an equatorial quiet daytime mesospheric condition of the atmosphere in the height range of 60—78 km.
Introduction
Mesosphere is one of the difficult regions for measurements because of its accessibility to only to rocket-borne techniques. This region is characterized by a wide variety of positive and negative ions including free electrons.
The in-situ measured electron concentrations in the mesosphere do not, in general, agree with the electron densities computed from the conventional ion-chemistry models of the region (Srinivas et al., 2007 and several references therein).
Considerable quantity of dust/aerosol particles of meteoric origin is known to be present in the mesosphere (Reid, 1990, for example). However, measurements regarding dust density and size are generally not available, particularly over equatorial latitudes (the location of interest to this study). These mesospheric particles are capable of having important role to play in the ion-chemistry, both as source and sink for electrons and ions, in the region (Parthasarathy, 1976; Reid, 1990; Srinivas et al., 1997; Kopnin, 2004; Ignatov, 2005). Therefore it is necessary to treat the mesosphere as a medium of dusty plasma, instead of treating it as a pure ionic plasma (Srinivas, et al., 2007).
With this background a detailed heterogeneous ion-chemistry model (HIC model) has been developed (Srinivas, 2008). This model, treating dust as an integral part of the meso- spheric environment, uses measured electron density as one of the inputs (other inputs include ionization rates, temperature, neutral species densities, etc.) to compute the steady state background neutral and charged dust concentrations for an assumed effective size of dust.
In the present study, this model has been employed to compute both the effective size and density of charged and neutral dust/aerosols by using a set of simultaneously measured
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total positive ion and free electron density profiles as input to the model. The results presented are for an equatorial daytime mesosphere under quiet solar conditions. The height range of interest to this study is 60—78 km.
Figure 1. Block diagram of the HIC Model (Srinivas, 2008) used in this study
Model, Methodology and Results
A block diagram of the HIC model is shown in Fig. 1. The model includes the relevant processes involving dust (photoionization of dust, dust-ion/electron attachment, electron/ ion detachment from dust and charged dust-electron/ion recombination processes) into the conventional detailed ion-chemistry of the mesosphere. This model considers only singly charged dust ions except for the case of dust-electron attachment. In connection with dust-electron attachment, dust is allowed to carry multiple charges up to 15 elementary charges per particle. This is possible since the mobility of electrons is more than those of ions by more than two orders of magnitude under mesospheric conditions.
The method of computing various dust densities has been the same as described by Srinivas et al. (2007). However, in the present study, a set of simultaneously observed electron and total positive ion densities of Chakrabarty et al.(1989) is used as input to the model. These profiles are shown in Fig. 2.
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The process of computation is performed in three stages. In the first stage, the steady state dust density profiles and the total positive ion density profile corresponding to the electron density profile (Fig. 2) are computed for various assumed dust sizes in the range of 1-100 nm. In this study the computed total positive ion density [N+] is seen to show a dependence on the assumed aerosol/dust size (r). This is evident from Fig. 3. This result (Fig. 3) is seen to be because of a requirement of dust as effectively a source of positive ions for establishing steady state. This, in turn, is possible if r is increased in the model.
In the second stage of computations, iteration is performed on the dust size (radius) so that the output total positive ion density matches with the experimental positive ion density at any given altitude of interest. Thus, a profile showing the height variation of the effective size of dust (shown in Fig. 3) is obtained.
In the final stage of computations, the charged and neutral dust densities corresponding to the dust size profile obtained in the previous stage are computed. These profiles are shown in Fig.4. Thus the background charged and neutral dust density profiles are derived from the experi-mental height profiles of [e] and [N+].
From Fig. 4 it is clear that, for establishing steady state, the effective dust size varies in the range of about 80 nm (at 60 km) to a few nanometer (at 76 km) . This is generally in agreement with the information available about the size of mesospheric particulates. However, keeping in view that at low latitudes large particles are unlikely to be present, the large values of r in Fig. 4 are indicative of a relatively large number of small particles.
In this study, it is seen that the positively charged dust [D+] comes primarily from the photoionization channel. Comparison
Figure 2. Experimental electron and total positive ion density profiles used as input to the model
Figure 3. Model computed total positive ion density for various dust size. Experimental [N+] are shown for comparison
Figure 4. Dust effective size variation with height, and the corresponding charged, neu- tral and total dust density profiles derived. from the model
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of the dust profiles (Fig. 4) indicates that, at heights below about 70 km, most of the dust remains in a photoionized state. And at all heights (60—78 km) photoionized dust is considerably more than the electron-attached dust [DZe] for any given altitude. However, considering the fact that dust particles can carry multiple charges (up to Z=15) in the model, the role of dust as a sink for electrons becomes comparable to the role of dust as a source of electrons through photoionization (i.e., [D+]).
In Fig. 4, both charged and neutral (and hence the total) dust density profiles show layered structures. Such layered structures are shown to have a role to play in the enhancements of Low Latitude MST radar echoes (LME’s) observed over Gadanki (Srinivas et. al., 2006, 2007; Srinivas, 2008). Thus the results of this study highlight the importance of dust not only in the studies of the ionic plasma, but also in the studies of radio wave propagation in the mesosphere.
Acknowledgements
The author is grateful to the University Grants Commission, New Delhi, India for financial support to this research work under Letter No. MRP(S)-047/07-08/KAMY004/ UGC-SWRO Dated 28 March 2008.
References
1. Srinivas, N., Prasad, B.S.N., Jayati Datta and Chakravarty, S.C., Application of heterogeneous mesospheric ion-chemistry model to MST radar echoes over low latitude, Adv. Space Res., 39: 1256-– 1266, 2007.
2.Reid, G.C., Ice particles and electron “bite-outs” at the summer polar mesopause, J. Geophys. Res., 95: 13891—13896, 1990.
3.Parthasarathy, R., Mesopause dust as a sink of ionization, Journal of Geophysical Research, 81: 2392— 2396, 1976.
4.Srinivas, N., Prasad, B.S.N. and Lastovicka, J., A heterogeneous ion-chemical model for the upper mesosphere., Indian J. Radio & Space Phys., 26: 264—273, 1997.
5.Kopnin, S. I., Kosarev, I.N., Popel, S.I. and Yu, M.Y., Localized structures of nanosize charged dust grains in Earth’s middle atmosphere, Planet. Space. Sci., 52: 1187—1194, 2004.
6.Ignatov, A.M., Basics of dusty plasma, Plasma Phys. Reports, 31:52—63, 2005.
7.Srinivas, N., A detailed ion-aerosol/dust model study of an equatorial mesosphere, Research Project Report No. Phy/1-2008, Submitted to the University Grants Commission, New Delhi, India, Maharani’s Science College for Women, Mysore, India-570 005, April 2008.
8.Chakrabarty, D. K., Beig, G., Sidhu, J. S. and Das, S. R., Fine scale structure and turbulence parameter of the equatorial middle atmosphere, J. Atmos. Terr. Phys., 51: 19-17, 1989.
9.Subbaraya, B.H., Prakash, S. and Gupta, S.P., Electron densities in the equatorial lower ionosphere from the langmuir probe experiments conducted at Thumba during the years 1966—1978. Scientific report ISRO-PRL-SR-15-83, Indian Space Research Organization, Bangalore, India, 1983.
10.Srinivas, N., Prasad, B.S.N., Jayati Datta and Chakravarty, S. C., A model study on the role of dust/ aerosols in the equatorial mesosphere, Paper presented at the MST-11 International Workshop held during 11—14 Dec. 2006 at the National Atmospheric Research Laboratory, Tirupati, India.
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A–P–15
Influence of Charged Dust/Aerosol on the Electrical Conductivity and MST Radar Echoes in the Low Latitude Mesosphere
N.Srinivas1,2, M.S. Chandrashekara3, H.N. Ranganatha Rao1 and S.B.
Appajigowda1
1 Department of Physics, Maharani’s Science College for Women (University of Mysore)JLB Road, Mysore-570 005, India
2Working at the Dept. of PG Studies in Physics (University of Mysore), Government Autonomous College, Mandya-570401, India
3 Dept. of Studies in Physics, University of Mysore, Manasagangotri, Mysore-570006, India
ABSTRACT : Considerable quantities of small dust/aerosol particles of meteoric origin are present in the mesosphere at all heights and latitudes. These particles are known to have a role to play in various aspects related to both physics and chemistry of the region. Due to electron attachment and photo-ionization these particles can produce electron density fluctuations that lead to an enhancement in the MST radar echo strength. Due to electron/ion-attachment the dust/aerosols can considerably alter the electrical conductivity of the mesosphere. The charge separations produced by the falling charged dust/aerosol particles can lead to the often-observed high electric fields, particularly in the lower mesosphere.
In the present study, using a heterogeneous ion-chemistry model of the mesosphere (Srinivas, 2008) the possibility of the influence of positively and negatively charged sub-visible (1-30 nm) dust/aerosol particles on the electrical conductivity and MST radar echo enhancements are studied. The results presented are for an equatorial quiet daytime mesosphere in the height range of 60 to 90 km.
Introduction
Mesosphere is a region where considerable amount of dust/aerosol particles of meteoric origin are present. These particles are normally sub-visible (r < 30 nm), particularly over low latitudes. Directly measured information on the size and density distribution of these mesospheric particles are currently not available, particularly over low latitudes. However, the steady state number density of these particles (including charged and neutral particles) may be computed from the height profiles of experimental electron density (Srinivas, 2008), for an assumed dust/aerosol size.
Mesospheric particles have an active role in the chemistry and physics of the region. The ability of these particles to attach to free electrons and their ability to release electrons due to photo-detachment and photo-ionization makes them a source for electron density fluctuation (Srinivas et al., 2007; Srinivas, 2008, and several references therein). Thus dust particles are important in understanding the constantly observed (and being observed) enhancements in the strengths of the Low Latitude Mesospheric echoes (LMEs) (see Datta et al., 2004; Kamala et al., 2003 for example).
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The ability of dust particles of becoming a source and/or sink for electrons and ions makes them important in understanding the electrical parameters, such as, conductivity, electric field, etc. of the region. Obviously, these particles can reduce the electrical conductivity by decreasing the effective mobility of ions in their vicinity, thereby increasing the electric field strengths.
The importance of the role of dust in the MST radar echo enhancement mechanism and in the conductivity of the mesosphere depends on the fraction of charge carried by the dust/aerosol at any given height. These fractions are denoted by P+ and P- in the present study. Cho et al.(1992) have shown that, for positively charged dust to be important in producing MST radar echo enhancement, P+ is required to be greater than or equal to 0.6. Negatively charged dust is shown to become important when P- = 0.3 (Havnes, 2002). Electrical conductivity due to charged dust is shown to be important when the fractions P- and P+ are greater than or equal to 0.5 (Zadorozhny, 2001). Thus, by identifying the regions satisfying these criteria it is possible to appreciate the importance of dust/aerosols in relation to electrical conductivity and MST radar echoes in the mesosphere.
Figure 1. Heterogeneous ion-chemistry model (Srinivas, 2008) used in this study.
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Model, methodology and results
The heterogeneous ion-chemistry model (Srinivas, 2008) used in the present study is shown in Fig. 1. This model computes various dust-related parameters, such as, charged and neutral dust densities (including multiply charged dust due to electron attachment), average charge per particle, etc. in addition to computing the ion composition of the mesosphere. The model uses experimental electron density as one of the inputs in addition to other normally used inputs, such as, temperature, neutral species concentrations, ion production rates, etc. In the model, P+ and P- parameters defined by the equations
Where [D+] is the photo-ionized dust density, [DZe] is the density of dust carrying Z charges per particle and [N-] & [e] are the densities of the total negative ions and electrons respectively. The experimental electron density profiles of Subbaraya et al.(1983) are used in this study. The results of P+ and P- parameters corresponding to 1, 10 and 30 nm dust, for both winter and summer seasons, are shown in this paper (Fig. 2).
From Fig. 2 it may be observed that P+ exceeds 0.5 for heights below about 78 km, whereas, P– = 0.5 occurs for heights above about 80 km. Thus, the influence of positively charged dust on the electrical conductivity appears to be important at heights below 78 km, whereas, influence of negatively charged dust on the electrical conductivity is important
Figure 2. Height profiles of P+ and P- parameters derived from the model
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at heights above about 80 km. Keeping in view that high electric fields are often observed in the lower mesosphere, this study indicates a possible influence of positively charged dust on the electrical conductivity, and hence on the electric field, in the lower mesosphere.
The values of P+ = 0.6 and P– = 0.3 occur at heights below 78 km and below 80 km, respectively, for both summer and winter seasons (Fig. 2). Thus, following the findings of Cho et al. (1992) and Havnes (2002), charged dust has a possible role in the radar echo enhancements in the low latitude mesosphere only below 80 km. It may be noted that the relatively strong and most frequent LMEs are observed throughout the year (daytime) in the lower mesospheric region (below 78 km) (see Kamala et al., 2003; Srinivas et al., 2007, for example). Thus the results of this study are supported by experimental observations of LMEs.
The results of this study emphasize the importance of dust particles in the studies of enhancement in the strengths of LMEs and also in the studies of mesospheric electric fields and conductivities.
Acknowledgements
One of the authors (NS) is grateful to the University Grants Commission, New Delhi, India for financial support to this research work under Letter No. MRP(S)-047/07-08/ KAMY004/UGC-SWRO Dated 28 March 2008.
References
1.Srinivas, N., A detailed ion-aerosol/dust model study of an equatorial mesosphere, Research Project Report No. Phy/1-2008, Submitted to the University Grants Commission, New Delhi, India, Maharani’s Science College for Women, Mysore, India-570 005, April 2008.
2.Srinivas, N., Prasad, B.S.N., Jayati Datta and Chakravarty, S.C., Application of heterogeneous mesospheric ion-chemistry model to MST radar echoes over low latitude, Adv. Space Res., 39: 1256-– 1266, 2007.
3.Datta, J., Chakravarty, S.C. and B.S.N. Prasad., Indian mst radar: mesospheric studies, Current Science, 81:661, 2001.
4.Kamala, S., Narayana Rao, D., Chakravarty, S.C., Datta, J. and Prasad, B. S. N., Vertical structure of mesospheric echoes from the indian mst radar, J. Atmos. Solar Terr. Phys., 65: 71, 2003.
5.Cho, J. Y. N., Hall, T. M. and Kelly, M. C., On the role of aerosols in polar mesosphere summer echoes, J. Geophys. Res. 97: 875, 1992.
6.Havnes, O., Dusty plasmas in the ionosphere and its environment. In proceedings: Third International
| Conference on the Physics of Dusty Plasmas, No. 0-7354-0106—3/02, pages 13—21, | American |
| Institute of Physics, 2002. |
7.Zadorozhny, A. M., Effects of charged dust on the mesospheric electrical structure, Adv. Space Res., 28: 1059—1064, (2001).
8.Subbaraya, B.H., Prakash, S. and Gupta, S.P., Electron densities in the equatorial lower ionosphere from the langmuir probe experiments conducted at Thumba during the years 1966—1978. Sci. report ISRO-PRL-SR-15-83, Indian Space Research Organization, Bangalore, India, 1983.
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A–P–16
Number Density Characteristics of Ultrafine Aerosols over Kothi in the Kullu Valley of the North West Himalayan Region, India
Nand L. Sharma1,*, Jadish C. Kuniyal2, Mahavir Singh3, Manum Sharma2 and Raj P. Guleria2.
1Department of Physics, Govt. Postgraduate College, Kullu 175 101, Himachal Pardesh, India 2G.B. Pant Institute of Himalayan Environment & Development, Himachal Unit, Mohal-Kullu, 175 126, Himachal Pradesh, India
3Department of Physics, Himachal Pradesh University, Shimla 171 005, Himachal Pardesh,India
*Corresponding Author: E-mail :< nlsharmakullu@hotmail.com>
Introduction
The study of ultra fine particles at a particular place is important aspect of aerosol science as the impacts of these particles in health related problems and climate changes are scientifically proven world over. The particles of various sizes are generated by different sources in atmosphere and there is also a rapid process of recombination, nucleation etc. going on in atmosphere. The particles of size larger than 1μm are called coarse or super micron particles which are mostly generated by dust resulting from excavation, blowing wind etc (Satheesh et al., 2004). The particles larger than 2.5 μm are generally removed by upper respiratory tract (Hansen, 2007) and are not much harmful to health. The suspended particles of size smaller than 1μm are called fine or submicron particles (Ahammed et al., 2007). The finer particles called accumulation mode (1μm to 0.1 μm) particles are dangerous as they penetrate in to lungs and produce many respiratory problems (Berico et al., 1997). The still finer particle of size ranging from 0.1μm to few nanometer called ultrafine are most lethal to health as they penetrate deep into lung during inhalation resulting depression, anxiety and many other neurological effects (Oberdorster et al., 2004). In this communication we present number density studies of ultrafine particles and their correlation with vehicular traffic conducted at Kothi in Kullu-Manali area during March to December 2008.
Experimental Site and Methodology
The sampling site Kothi (320 19’N, 770 11’E, 2530m amsl) located at high altitude on mountainous slope is last inhabited village at northern end of Kullu valley. It is about 100m from main highway NH-21 which goes through the nearby famous snow sites of Gulaba, Rohtang pass (3978m, amsl) etc to Leh. The local population of this village is 567 while the population of entire Kullu valley which constitutes Kullu & Manali subdivisions of Kullu district, part of Sadar Division of Mandi District; is 221,858 (census of India, 2001). Being an important tourist destination of north India, thousands of tourists flock to Kullu-Manali area of Himalayas during summer (Kuniyal et al., 2005). In winter local anthropogenic activity is low but tourist traffic is increasing years to years. The vehicular traffic mainly consists of tourists and military supply vehicles. The local vehicles are also increasing as according to
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RTO (regional transport office) data every year about 3000 new vehicles of all types are registered at various subdivision of this valley. Our 6AM to 6PM vehicle survey conducted on NH-21 near Kothi indicates that about 1400 vehicles on average, every day ply on it although for most of winter months this area is under snowfall.
The regular midnight to midnight measurements of particle density at every hour were taken using Condensation Particle Counter of Poll-tech make that can count particle of size ranging from 10Å to 200Å. As the efficiency and cut sizes performance for silver, ammonium sulphate and sodium chloride by water based CPC are better than butanol based CPC under increased streamline flow and condition of super saturation (Mordas et al., 2008) so we used water based CPC during present study. The ambient air particles from the atmosphere are sampled into the sampling chamber where moist blotting paper provides the saturated atmosphere. Adiabatic expansion of the air due to sudden connection of the sampling chamber to the evacuated auxiliary chamber through the quick opening valve results in super saturation and consequent fog formation in the sampling chamber.
The reduction in the intensity by sucked in air is measure of particle density which is displayed by c a l i b r a t e d computerized display provided in this instrument.This instrument can count from 102 to 107 nuclei per cm3 with 10% of accuracy with suction rate of 10litre/min.
Figure 1. Time series of hourly variations of particle density of three sizes
Results & Conclusions
Figure 1 shows hourly variations of ultra fine
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particles of various sizes for all 72 measurement days from March to December 2008.
On close examination of hourly variation of particle density of all measurement days for particles of every size range we find that density as small as 200 N/cm3 to as large as 2, 00,000 N/cm3was obtained; a trend found at various hilly forest sites (Kulmala et al., 2007). Also it is seen that for all three size modes most of time particle density lies below 20,000 N/cm3 except few peaks due to nucleation bursts (NB); a process of sudden conversion of atmospheric precursor gases into large numbers of ultrafine particles (Kulmala et al., 2004). The 20nm aitken mode density is slightly more than 3nm nucleation mode which is also slightly more than 1nm nucleation mode values.
Figure 2. Annual average hourly variation of (a) particle density of three sizes (b) Vehicles
On yearly basis when particle density is averaged over all the ten months at each particular hour of day it comes out to be as shown in figure 2 (a). From figure 2(a) and (b) we find that particle concentration is almost constant throughout the day showing slight jumps in morning and evening peak tourist times (Ahammed et al., 2007). It is because of almost constant vehicular flow throughout the day as evident from fig 2(b) except early morning hours. In all the three size ranges, it has been observed that concentration is slightly high during peak tourist traffic hours i.e. 900-1100 hours then decreases slightly becoming small around 1300 hours. It then again picks up reaching maximum around 1400-1500 hours. These results are similar to trend found in high hill stations Malampuzha and Sulthan Bathry of Kerala (Varikoden et al., 2008) with peaks not so much predominant as at our site. The variations are also similar to those found at flat hill station Mohal (Sharma et al., 2009) but have morning peak later and evening earlier by about two hours due to tourists reaching later and returning earlier from snow site near Kothi. The annual variation of 24 hour average particle density for each size range is as shown in figure 3 (a) while annual vehicular movement data is shown in fig 3(b).
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Figure 3. Monthly (a) 24hr particle density average (b) vehicle movements per day at Kothi
The comparison of figure 3(a) and (b) shows almost same trend of particle density and vehicular movement except for March and September. Both rise from April become maximum in peak summer month of July and then decrease in rainy season and further decrease in winter months. The abnormal rise of particle density in March may be due to use of fuel wood for heating & cooking purposes due to snow fall while in October the vehicular movement and particle density is abnormally large due to month long International Kullu Dussehra in valley. Relatively more value of particle density in rainy season of August and September can be due to foggy conditions (Payara and Mohan, 2007) and frequency of large number of NB as seen clearly in fig 1. In winter comparatively low value can be due to frequent rains causing wash out/rain out effect and scavenging of fine particles to form cloud condensation nuclei (Satheesh et al., 2004).
The annual correlation analysis excluding abnormal March and September months, shows high correlation value of 0.8161 (Ps<0.01) 0.7581(Ps<0.02) & 0.7799 (Ps<0.02) for 200 Å, 30 Å and 10 Å sized particle density and vehicular flow (Goyal & Sharma, 1963). The annual 24 hour average for entire study period was found to be 13116±2022, 12234±1863 and 11241±1762 N cm-3 respectively for of 200 Å, 30 Å and 10 Å particle size respectively. It may be pointed out that studies conducted in 2008 at Mohal-Kullu (1154 m amsl, local population 18306) gave annual particle density as 18045±1212, 16811±2790 and 15407±3109 N/cm3 respectively for of 200 Å, 30 Å and 10 Å particle size respectively (Sharma et al., 2009). It is only about 27% more than the values at Kothi although Mohal is semirural while Kothi is purely rural. The result indicates therefore impact of tourists as well as local vehicles on the increase of fine particulate matter in valley.
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Acknowledgement
Authors are indebted to the Director, GB Pant Institute of Himalayan Institute of Environment and Development, Kosi-Katarmal, Almora (Uttarakhand) for providing necessary facilities to conduct present study.
References
Ahammed, Y.N., Arya, B.C., Kumar, A., Shukla, D.K., and Haque, I. (2007) Size distribution characteristics of atmospheric aerosols over an urban site, New Delhi, India, (Indian Aerosol Science & Technology Association) IASTA Bulletin (India), 18: 1&2, 58-60.
Berico, M., Luccinni, A. and Formignani, M.,(1997) Atmospheric aerosols in an urban area- Measurement of TSP & PM10 standards and pulmonary deposition assessments; Atmos. Environ., 31, 3659-3665.
Census of India (2001): Population Totals, Director of Census Operation part-2, Govt. of Himachal Pradesh, Shimla, India, pp1-79.
Goyal, J.K. and Sharma, J.N. (1963) Mathematical Statistics, Krishna Prakashan Mandir, Meerut (India), pp 378- 476 & table VI, X.
Hansen, A.D.A. (2007) Emerging trends in Aerosols: Technology and Applications, IASTA Bulletin (India), 18: 1&2:109-112.
Kulmala, M., Vehkamaki, H., Petaja, T., Dal Maso, M., Lauri, A., Kerminen, V.M., Birmili, W. and McMurry, P.H. (2004) Formation and growth rates of ultrafine atmospheric particles: a review of observations.
J. Aerosol Sci. 35: 143-176.
Kulmala, M., Riipinen, I., Sipilia, M., Manninen, H., Petaja, T., Junninen H., Dal Maso, M., Mordas, G., Mirme, A., Vana, M., Hirsikko, A., Laakso, L., Harrison, R. M., Hanson, I., Leung, C., Lehtinen, K. E. J. and Kerminen, V.M. (2007a) Towards direct measurement of atmospheric nucleation, Science, 318, 89–92,
Kuniyal, J.C., Gajananda, Kh., Momin, G.A., Rao, P.S.P., Safai, P.D. and Ali, K. (2005) Trend of atmospheric aerosols over north western Himalayan region, India, Atmos. Environ., 39 (27):4817-4825.
Oberdorster, G., Sharp, Z., Atudorei, V., Eder, A., Gelin, R., Kreyling, W. and Cox, C. (2004) Translocation of inhaled ultrafine particles to brain, Inhal. Toxicol. 16:437-445.
Payara, S. and Mohan, M. (2007) Analysis of Aerosol number concentration spectrum during fog over Delhi,
IASTA (Indian Aerosol Science& Technology Association) Bulletin (India), 18: 1&2: 230-233.
Satheesh, S.K., Moorthy, K.K. and J. Srinivasan (2004) Introduction to Aerosols and impacts on atmosphere: Basic concepts, ISRO-GBP Scientific Report SR-5, pp1-100.
Sharma, N.L., Kuniyal, J.C., Singh, M., Negi, A.K., Singh, K. and Sharma, P., (2009) Number concentration characteristics of ultrafine aerosols (atmospheric nanoparticles/aitken nuclei) during 2008 over western Himalayan region Kullu-Manali, India, Indian Journal of radio & space physics,38,326-337.
Varikoden, H., Sasikumar, V., Sampath, S., Muralidas, S. and Mohankumar, G. (2008) Diurnal and spatial variation of condensation particles in Kerala, South India. Current Science, 94(2): 233-237.
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A–P–17
Temporal and Spectral Features of Atmospheric Aerosols at
Pune
S. D. More1, G. R. Aher2 and P. Pradeep Kumar1
1Dept. of Atmospheric and Space Sciences, University of Pune, Pune 411 007,
2Dept. of Physics, Nowrosjee Wadia College, Pune 411 001.
email : dsanjaymore@gmail.com
Introduction
Atmospheric aerosols affect the Earth’s radiation budget and climate through their direct interaction with solar radiation (so called aerosol direct effect) and indirectly through their interaction with clouds (Chylek et al., 2006). Aerosols have a complicated non-uniform physical and chemical and highly variable temporal and spatial distribution. The large temporal variation in optical properties is due to prevailing atmospheric conditions as well as due to diffusion and aging processes such as humidification, coagulation, scavenging by precipitation and gas –to-particle conversions processes (Pandithurai et al.,2007).
Weather parameters and surface heating affect the production of aerosols giving rise to systematic temporal behavior. The surface weather parameters and the processes in the atmospheric boundary layer seem to have important role in the pattern of aerosol variability (Nair and Krishna Moorthy, 1995; Aher et al., 2000). Information on the temporal variability of aerosol parameters such as aerosol optical thickness (AOT), Angstrom exponent, and size distributions are of vital importance for various applications including validation of satellite aerosol retrievals, radiative forcing calculations and study of aerosol- cloud interactions.
Ground-based measurements via sunphotometer or sky-radiometers offer a more reliable way to perform multispectral remote measurements of aerosol optical properties. In the present work, the MICROTOPS –II Sunphotometer (Version 5.5) has been operated from the terrace of the Dept. of Environmental Sciences, University of Pune to study temporal and spectral features of AOT and to determine columnar aerosol size spectra.
Methodology
AOT has been measured at spectral channels centered at 440, 500, 675, 870 and 1020 nm wavelengths by employing MICROTOPS- II sunphotometer. Observations are carried out on clear sky days from 8:30 Hrs to 17:00 Hrs IST at about 10 min interval during 2008-09. From the data, temporal (on diurnal scale) and spectral variation of AOT is studied. Columnar size spectra of aerosol are obtained by numerically inverting the spectral variation of AOT (King et al., 1978). The results are discussed in the following.
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Results and Discussion
Diurnal Variation of AOT
The phenomenon of diurnal variation of AOT at Pune during the period from November to – May is found to be of 3 types viz.,(I) High AOT in morning with steady decrease in afternoon (II) High AOT in morning with small peak during afternoon and (III) AOT low in morning and high in afternoon. Fig.1 (a, b & c) shows typical diurnal variations of these types observed at wavelengths 440,500,675,870 and 1020 nm. Figure also indicates daily mean AOT values at each wavelength along with its std. error. AOT data on November 5, 2008 (Fig.1a) shows that AOT is low between 9:00 to 10:15 hrs and it increases to a maximum value which is about 37% to 54 % higher as compared to its daily average value at 440 and 1020 nm respectively. In terms of equivalent AOT rise, this is 0.16 and 0.10 respectively at these
wavelengths. AOT remains around its daily average value except a small peak at 12:30 hrs.
In type II diurnal variation, on January 21, 2009 (Fig.1b), at 440 nm, AOT is lower than mean value by about – 2.3 to 18.6% in the morning. It increases to a daily primary maximum value around 10:52 hrs which is about 37% higher than corresponding mean value. Rise to peak is prominent at 440, 500, and 675 nm whereas it is less prominent at 870 and 1020 nm. AOT shows sharp fall in value around 13:30 hrs after which it increases to produce secondary maximum during the day. There is once again a rapid decrease in AOT around 16:00 hrs. Diurnal variation of the third kind (Fig. 1c) is normally seen on summer days. Analysis show that AOT magnitude varies by about 0.5% to 6% with reference to the corresponding daily mean value. This happens till noon time. Thus, it is evident that AOT values are almost constant at all the wavelengths till noon time. Sharp enhancement in AOT is observed at 12:40 which is found to decrease afterwards.
Aerosol Optical Thickness
Spectral Variation of AOT and Aerosol Size
Distribution
Spectral variation of AOT is primarily determined by the aerosol size distribution, which is governed by aerosol sources present in the local atmosphere. Many a times, it
Figure 1 (a, b, c). Typical diurnal variation of AOT during 2008-09
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was found that the spectral variations for individual observations are more or less of the same type throughout day. In order to investigate the average picture on the time scales of 1 to 2 hour basis spectral AOT values for nearby 4 to 5 individual observations are grouped together. This process yields mean spectral variation for about 1 to 2 hours. Fig. (2a) depicts such average spectral variation of AOT on a day in month of January. It is seen that the mean variation is decay type with high AOT at 440 nm and low at 1020 nm indicating existence of small size aerosols and single haze distribution. Also, similar type of spectral variation is prevalent almost on all the days of observation during November to May period, although AOT magnitude changes on day-to-day basis due to varied meteorological conditions.
Using mean spectral variations on the time scales of 1- 2 hours, ASDs are obtained by numerically inverting mean variation by following King et al., (1978). Fig.2(b) shows results of this analysis. It is found that in general, the aerosol size range corresponding to the spectral range used in the observations lies between 0.05 m to about 2 m. Also, ASDs are Junge power law type with nc(r) values higher at small particle regime than the corresponding values at large particle size range which is indicative of dominance of small size aerosols.
Figure 2(a,b) Mean spectral variation and the corresponding aerosol size spectra
As seen from aerosol size spectrum analysis, it is found that the observing season 2008- 09 is dominated by small size aerosols. This is also confirmed through the determination of moments of aerosol size distribution function. Results show that <r> lies between 0..21–
0.31 m and reff lies between 0..49– 0.94 m . A small change in <r> and a peak in reff gives maximum value of mL. N t and <r> show exactly apposite behavior during this
period indicating once again, how sensitive N t is to <r>.
Conclusions
AOT is generally high in the morning (FN) and low in the afternoon (AN). This behavior is common on days in winter months implying higher columnar aerosol loading
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in the morning than in the afternoon mainly because of meteorological conditions such as temperature inversions, higher relative humidity and calm winds which are conducive for the for the formation of haze in morning hours. On summer days, AOD is high in afternoon. This is caused by surface heating and strong winds which raise dust in the afternoon hours in addition to anthropogenic aerosols. ASDs are Junge power law type with nc(r) values higher at small particle regime than the corresponding values at large particle size range which is indicative of dominance of small size aerosols.
Acknowledgements
The research project is supported by the UGC, New Delhi under the major research project scheme. The authors thank the Head of the Department of Environmental Sciences, and the Pune University authorities for encouragement.
References
Chylek et al., (2006), Aerosol indirect effect over the Indian Ocean, Geophys. Res. Lett. (USA), 33,L0806, doi: 10.1029/2005GL025397.
Pandithurai et al., (2007), Seasonal asymmetry in diurnal variation of aerosol optical characteristics over Pune, western India, J. Geophys. Res. (USA), 112, D08208, doi: 10.1029/2006JD007803
Nair and Krishna Moorthy(1995), On the association between aerosol optical depth and surface meteorological conditions in a tropical coastal environment, Mausam (India),46, 427-434.
Aher and Agashe (2001), Influence of climatic factors on aerosol optical depth, J. Marine and Atmospheric Res.(India), 2(1),46-50.
King, M. D., Byrne, D. L., Herman, B. M., and Reagan, J. A. (1978), Aerosol size distributions obtained by inversion of spectral optical depth measurements, J. Atmos. Sci.(USA), 35, 2153-2167.
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A–P–18
Numerical Estimation of the Dust Optical Properties over Delhi and Comparison with Experimental Observations
S. K. Mishra, Sachchidanand Singh and D R Nakra
Radio and Atmospheric Sciences Division, National Physical Laboratory, New Delhi, India
mishrask@nplindia.org
Introduction
Aerosol is one of the significant components of the Earth’s atmosphere [Holmes, 2001]. The dust particles in the aerosol are assumed to be spherical and homogeneous during satellite retrieval algorithms [Dubovik and King, 2000]. The above assumptions however, lead to the erroneous retrieval of optical properties and hence the radiative forcing estimation at Earth’s surface and top of atmosphere [Kahnert and Kylling, 2004]. Thus for good retrieval, region specific dust morphology, mineralogy and effect of relative humidity [Semeniuka et al., 2007] should be incorporated. Pure mineral dust particle passes through the pollution and forms a coated dust particle system [Li and Shao, 2008] and interacts with the incoming radiation differently compared to pure dust [Bauer and Koch, 2005; Bauer et al., 2007]. North Indian plains play a significant role in dragging the moisture contents from Arabian Sea and Bay of Bengal (due to strong pressure gradient in between) and hence affect the monsoon activity. So, it is imperative to find the radiative signature of such an atmosphere which would have effects on the monsoon. The experimental observations of optical properties are very limited and very expensive for the spatially girded high resolution observations. In that case, for better understanding of the radiation budget and its possible impacts on monsoon over the region, it is very important to estimate the optical properties of aerosol numerically more accurately, accounting for the above discussed conditions. The optical properties thus obtained will be fed in radiative
transfer model to get the radiative signature of the real atmosphere.
Results and discussions
The atmosphere over Delhi comprises of anthropogenic pollution (i.e. SOx, NOx due to industries, vehicles, power plants etc.), mineral dust (from Thar Desert, Rajasthan) and soil particles (local construction and other activities) with their mixed states and sometimes as stratified layers. In the vicinity of the pollution, the pure mineral dust is likely to be coated with pollutants. Because of the low boundary layer height and low relative humidity during winter, the trapped pollution will have high probability to make a coat over the pure dust. In pre-monsoon summer time as the atmosphere is dry and high wind speed along with the increased boundary layer height and high convection, the mineral dust may remain pure and dry without any coating of water vapor or pollutants. In monsoon season when again relative humidity is high and the probability of the dust getting scavenged is more that leaves a greater possibility for local aerosols with water vapor
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coating. Keeping this in mind, the size averaged optical properties for the above mentioned dust system in three different seasons have been numerically estimated using the code developed by Dr. W. Wiscombe based on the work by Toon and Ackerman [1981]. The code computes the scattering and absorption characteristics of a coated dust particulate. The size average optical properties have been estimated using the modeled mono disperse optical properties and measured size distribution. Validation of the modeled optical properties will be done with experimentally measured optical properties using Nepthelometer and Aethalometer operated at NPL, New Delhi campus for all the seasons. The daily average variations of Absorption Coefficient, Scattering Coefficient and Single Scattering Albedo (SSA) during the year 2008 during pre-monsoon and postmonsoon season, obtained through the measurements have already been shown by Soni et al., 2009. The results pertaining to the modeled optical properties (such as Single Scattering Albedo, SSA; Asymmetry parameter, g; and Phase function) of the dust system and its comparison with the observation will be discussed.
References
Bauer and Koch (2005), Impact of heterogeneous sulfate formation at mineral dust surfaces on aerosol loads and radiative forcing in the Goddard Institute for Space Studies general circulation model. Journal of Geophysical Research, 110, D17202, doi:10.1029/2005JD005870.
Bauer et al. (2007), Do sulfate and nitrate coatings on mineral dust have important effects on radiative properties and climate modeling?, J. Geophys. Res., 112, D06307, doi:10.1029/2005JD006977
Dubovik O. and M. D. King (2000), A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res., 105, D16, 20,673-20,696.
Holmes, Hannah; (2001) The Secret Life of Dust. Wiley. ISBN 0-471-37743-0 Kahnert, M., and A. Kylling (2004), Radiance and flux simulations for mineral dust aerosols: assessing the error due to using spherical or spheroidal model particles, J. Geophys Res., 109, D09203.
Soni, K., S. Singh, T Bano, R. S.Tanwar, S. Nath (2009), Variation of aerosol properties and their dependence on meteorological parameters over Delhi during Pre and post-monsoon season, Submitted IASTA- 2010 (This conference)
Li, W. J. and L. Y. Shao, (2008), Observation of nitrate coatings on atmospheric mineral dust particles, Atmos. Chem. Phys. Discuss., 8, 19249–19272.
Semeniuka et al.(2007), Water uptake characteristics of individual atmospheric particles having coatings,
Atmos. Environ., 41, 6225–6235
Toon, O. B., and T. P. Ackerman (1981), Algorithms for the calculation of scattering by stratified spheres, Appl. Opt., 20, 3657– 3660.
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A–P–19
Lidar Measurements of Vertical Aerosol Flux over Pune, India
S. M. Sonbawne, P.C.S. Devara, P. Ernest Raj, K. K. Dani and S.M. Deshpande
Indian Institute of Tropical Meteorology, Pune-411008, India
sunil@tropmet.res.in
Introduction
Aerosols have significant impact on the climate both directly, indirectly. Estimating this impact of aerosol on climate is especially difficult since the effect of aerosol depends on their optical, physical and chemical properties (e.g. concentration, size) which vary significantly in space and time. The turbulent transport of aerosol particles between the surface and the troposphere has a strong influence on atmospheric composition, long range transport, and cloud formation as well as on smog and haze conditions at the ground. Tropospheric aerosols, due to their regional nature, cause the largest uncertainties in associated with anthropogenic activity (IPCC, 2007). Vertical transport or exchange depends in a complicated way on surface characteristics and meteorological conditions. The excessive amounts of trace gases and aerosol particles have been released into the atmosphere due to the fast development of the study area. This has caused irreversible changes/damages to the air quality and climate in the study region. The mechanisms of turbulent transport are not well understood. Therefore, respective observations of lidar determined aerosol profile and vertical wind from RASS are of high interest. In the present paper, we report the results of the vertical particle exchange / transport in the troposphere. For this, the turbulent mass fluxes were obtained from simultaneous measurements with a RASS (vertical wind profile) and an Argon-ion lidar (aerosol profile). The observations were performed at IITM and IMD Pune, India on some typical experimental days during 2005 and 2006.
Experimental Station, Set-up and Data
Pune is an urban continental tropical station located on the lee side of the Western Ghat mountain range and it is about 200km inland to the east of the Arabian sea coast. This station is under the influence of south westerly winds during the monsoon months from June to September and during the other months especially in winter (from December to February) surface-level winds are predominantly easterly or northeasterly. Both the lidar and radar sites are surrounded by hillocks of elevation as high as 760m AMSL.
Argon ion bi-static lidar observations of atmospherics aerosols have been in progress at IITM, Pune since October 1986 (Devara et al., 2002). In these experiments, laser scattered signal strength is collected at different scattering angles, with 50 m height resolution, and converted them into aerosol concentration profiles by employing inversion techniques (Devara and Ernest Raj 1987). A 404 MHz Wind profiler (UHF radar) system has been in operation at IMD, Pune since June 2003. This profiler is situated about 300m away from
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the lidar site. It has average power of 2x105 Wm2 consist of a dual polarized coaxial collinear antenna array, this array produce three beam, two tilted beams one along the east and one along the south and the third beam at zenith (P. Ernest Raj et al 2008). This profiler measures the radial velocities by using the Doppler Beam Swinging (DBS) technique which enables simultaneous measurement of zonal, meridional and vertical components of the wind field in the altitude region from 1.05 to 10 km with a height resolution of 300m. More details on RASS are available in Pant et al. (2005).
Both the lidar and wind profiler have been operated simultaneously on some typical clear-sky days during 2005 and 2006. These concurrent observations have been used to compute the vertical distributions of aerosol flux over Pune.
Method of Analysis
For the calculation of turbulence parameters, we investigate the vertical wind speed and aerosol scattering profile data at specific height levels. For ground-based profile observations, it is assumed that the resolved datasets well represent the spatial average. Then, the flux Fb is given by the product of aerosol concentration profile b and the vertical wind speed w:
Fb= b x w
By definition, updrafts have a positive sign, and positive values of Fb imply upward fluxes (Engelmann et al., 2008). But, in reality, only measurements at 2000 hrs with limited height intervals are possible; the sampling error must always be taken into account in the interpretation of flux observations. Usually, the parameter b represents aerosol
Figure 1. Vertical aerosol concentration profile, Argon-ion lidar data
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concentration. In case of aerosols, the turbulent transport in terms of particle number, volume, or mass is of interest. However, from lidar observations we can only determine particle backscattering with good resolution for turbulence investigations.
Results and Discussions
In the present work, the aerosol and vertical wind measurements made during clear- sky conditions with lidar and RASS from 1km and above (for the reasons explained above) were used for computing the vertical aerosol flux by direct product method. Depending on the wind direction, there were a variety of different surfaces and sources within the measurement footprint, which included an urban land, grassland and residential area and road traffic. It is evident from Figure 1 that the lidar aerosol concentration profiles show higher concentration at lower heights, and an exponential decrease of concentration with increase in height. An interesting feature that can be noted in most of the aerosol concentration profiles considered in the present study is that there are aerosol layer formations between 2.25 and 3.75 km. Such aerosol layers have been reported in the past from this experimental site from Pune (P. Ernest Raj et al., 2008).
Figure 2 depicts the vertical aerosol flux variations with height computed for the aerosol profiles shown in Figure 1 coupled with corresponding vertical wind variations obtained from the RASS. The results show positive values indicating upward flux comprises of cleaner air mass in the months of June and August. In the month of October, the values exhibit negative, indicating downward aerosol flux involving dirtier air mass.
Figure 2. Vertical aerosol flux distributions corresponding to the aerosol profiles shown in Figure 1
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Conclusion
The vertical aerosol transport over Pune is investigated by combining the lidar-measured aerosol concentration profiles and radar-measured vertical wind velocity. The results of the study show positive aerosol fluxes (average value of 13.32 cm-2s-1), indicating upward transport of aerosols (clean air) in the month of June, and negative aerosol flux with average values of -0.13 and -3.39 cm-2s-1, implying downward transport of aerosols (polluted air) in the months of August and September, respectively.
References
Devara et al., 2002, Int. Jr. Climatol., 22, 435-449.
Devara P.C.S and Ernest Raj P., 1987, IETE Tech. Rev., 4, 412-415.
Engelmann et al., 2008, Jr. of Atmospheric and Oceanic Technology, 25, 1296-1306. IPCC, 2007, climate change, 2007.
P. Ernest Raj et al., July-2008, Jr. Earth Syst. Sci., 117, S1, 293-302. Pant et al., 2005, Current Science, 88, 761-774.
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A–P–20
Aircraft Observations of Cloud Drop Size Distributions in Different Regions over India During Monsoon 2009
Savita B. Morwal*, R. S. Maheskumar, P. Ernest Raj and J. R. Kulkarni
Indian Institute of Tropical Meteorology, Pune 411 008
*Corresponding Author e-mail: morwal@tropmet.res.in
Introduction
Tropical clouds have high albedos and they decrease the amount of solar energy absorbed by the earth system, reducing heating rates. Slingo (1990) estimated that reducing the effective diameter of stratus cloud droplet sizes would balance the warming due to increased CO2. Studies have shown that size distributions of cloud droplets change with the vertical development of the cloud. Also, the cloud drop spectra showed spatial variability. Warner (1969a; 1969b) has studied in detail the drop size distributions over the Australian coast. Such studies on cloud droplet size distributions, effective radius and their effect on cloud microphysics and dynamics are sparse or non existent in the tropical monsoon clouds occurring over the Indian sub-continent.
Clouds form in the atmosphere when the air becomes supersaturated so that the water vapor condenses on the aerosol particles to form cloud droplets. During cloud formation the number concentration of the cloud droplets depends on the number of aerosols present in the air mass. Therefore, aerosols determine the cloud properties such as number concentration of cloud droplets and their size. The fair weather continental cumulus clouds with no precipitation have relatively narrow drop size spectrum while the continental cumulus clouds which have reached more matured stage of cumulus congetus show much broader cloud drop spectrum (Hobbs et al., 1980). Further, they showed that the cumulus clouds embedded in a stratus layer have much more broader spectrum. The maritime cloud have even broader drop size spectrum as compared to continental clouds (Battan and Reitan, 1957). In the present paper an attempt has been made to examine the characteristics of cloud drop spectra in different regions over India from aircraft observations made during monsoon 2009.
Data
A national level observational experiment called ‘Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX)’ has been conducted over the Indian region during May-September 2009. In this experiment an instrumented aircraft was used to collect in-situ observations of aerosols and cloud microphysical parameters viz. liquid water content, total water content, concentrations of aerosols, Cloud Condensation Nuclei (CCN) and cloud droplets of different sizes, temperature, humidity etc. The different instruments onboard aircraft were AIMMS, Cloud Droplet Probe (CDP), Cloud Imaging Probe (CIP), CCN counter, Gas Analyzer, LWC probe etc. These observations were made
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over different continental and also over the coastal oceanic regions during 17 May – 30 September 2009. The base stations included Pathankot (32.26°N, 75.65°E), Bareilly (28.35°N, 79.41°E), Bengaluru (12.97°N, 77.59°E), Hyderabad (17.38°N, 78.48°E), Pune (18.52°N, 73.85°E) and Guwahati (26.18°N, 91.75°E). Observed cloud drop size distributions and their height variations over these regions are presented and discussed in this paper.
Results and Discussion
Aircraft observations of drop size distributions (DSD) were made using CDP which collects the concentration and liquid water for the cloud drops ranging from 3-50 μm at an interval of 1 sec. Using this data, the mean concentrations for DSD for each cloud traverse at different height intervals have been computed. The DSD spectra for Pathankot (Figure 1, upper panel), which is representative of the dry weather conditions before the onset of the summer monsoon, at heights varying from 4400 – 7400 m showed mono modal (~ 8-12 μm) distribution at all heights. The width of the spectra and concentration of particular size drops after the modal diameter increase slightly with increasing height. The DSD spectra over Bengaluru region (Figure 1, lower panel), which was undertaken over the continental, Western Ghats and coastal regions after the onset of the monsoon, with heights varying from 3100-5500 m showed bimodal distribution (15-18 μm and 22- 28 μm) at all heights. Even though the width of the spectra is very large at all heights, it showed more broadening at higher altitudes. Also, the concentration of particular size drops after the second mode increases slightly with increasing height.
Figure 1.
The appropriate measure of the mean drop size is the effective radius (Re), which is the ratio between the third and the second moment of the cloud droplets size distribution (Stephens 1978). This is indicative of the threshold size of cloud drops below which precipitation hardly forms. Cloud drops at the threshold size grow to raindrops rapidly (Houze, 1993). The height variation of the effective radius for all the cloud traverses over all the stations viz. Pathankot (PKT), Hyderabad (HYD), Bengaluru (BNG), Bareilly (BRL), Guwahati (GHT) and Pune (PNE), with linear fit is shown in Figure 2. The vertical dashed line represents the threshold radius for the initiation of warm rain processes in the tropical clouds. The linear fit line represents the growth rate cloud droplets (micron per km) in
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the vertical, of the smaller cloud drops at lower levels to bigger drops at higher levels. The growth rate (μm/ km) is less at Pathankot (0.67 μm/ km), Hyderabad (0.67 μm/ km) and Bengaluru (0.73 μm/ km) and intermediate at Bareilly (1.13 μm/ km) and Pune (1.31 μm/ km) and maximum at Guwahati (2.39 μm/ km). In other words the conditions are more favorable at lower altitudes for the initiation of the warm cloud processes over north-east (Guwahati) as compared to Pathankot.
Figure 2
Conclusions
The Cloud Drop Size spectra at different stations showed the following:
zSingle mode DSD spectra over Pathankot, Guwahati and Pune
zDSD spectra were double mode at Hyderabad, Bengaluru and Bareilly
zDSD spectra was narrow at lower heights (diameter < 30 μm) and broadens with increasing height. However, spectra were narrow even at higher levels over Pathankot
zDSD spectra were very broad at Bengaluru and Bareilly.
The height variation of effective radius over different stations showed different rates of growth with height (μm/ km). The growth rate is less over Pathankot, Hyderabad and Bengaluru; intermediate at Bareilly and Pune and maximum over Guwahati. The correlation is high over all the stations except Bengaluru. This may probably be due change in the characteristics of the observational region which changes from continental to hilly terrain and to coastal waters.
Acknowledgements
Authors are grateful to the Director, IITM for suggestions and constant encouragement. The authors are thankful to the Ministry of Earth Sciences for extending financial support to the project.
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Houze, R. A. 1993: Cloud Dynamics. pp 573 Academic Press.
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