IASTA-2010

A–P–1

A Study on Distribution of Particulate Matter Concentrations with Different Sizes Along with Horizontal Distance from Highway

Anshumala Sharmaa and Ajay Tanejaa,b

a School of Chemical Sciences, Department of Chemistry, St. John’s College, Agra, India

b Department of Chemistry, Institute of Basic Sciences, Dr. B. R.Ambedkar University, Agra, India Email: amsharma_13@yahoo.co.in, ataneja5@hotmail.com

ABSTRACT : In the present study, PM10, PM2.5 and PM1.0 concentrations were simultaneously measured near national highway (NH-2) using GRIMM (portable aerosol spectrometer) to detect the distribution of concentrations of PM with different sizes and possible causes. A significant decrease in the concentrations of PM10, PM2.5 and PM1.0 was found within 0-100m distance and the decrease in concentration becoming less significant along with the increasing distance. The roadside Particle levels were found higher than the levels prescribed by CPCB and WHO. The low value of fine to coarse particle size ratio implies that fine and ultrafine particle contributed small proportion of the total PM10 mass near highway because sand dust transport caused by dust events during the sampling period contributed more to coarse than to fine particle pollution. The fine to coarse particle size ratio increases slightly along with the increasing distance from the highway because compared with finer particles, coarse particles are heavier and cannot be suspended easily in the air for a long time.

Keywords : PM10, PM2.5, PM1.0, particle size ratio, correlation, highway.

Introduction

Over the past two decades there has been a rapid increase in urbanization and industrialization in many cities of India. With this has come a dramatic increase in the number and density of motor vehicles (Taneja et al., 2008). With rapid urbanization and corresponding increase in traffic, there has been growing evidence that ambient concentration level of PM is also high (He et al., 2001; Wang et al., 2005). Atmospheric particulate matter (PM) affects climate, environment, visibility and health through a great variety of processes (Pope et al., 2002). Dockery and Pope (1994) reported that for each 10μg/m3 increase in concentration of PM10 there is an estimate of increase in mortality of 0.6-1.6%. The health impact of finest particulate (PM2.5, PM1) is greater because it can be inhaled deep into the unciliated and alveolar sections of the lungs. PM size generally ranges from 0.01 to 100 μm. Particles with different sizes deposit in different sections of the human respiratory system and have various effects on human health (Berico et al., 1997). Compared with coarse particles, fine particles do more harm to human health, the reason being that most fine particles are not only toxic material themselves, but also carriers and reactants for toxic and harmful substances (Wang et al., 2009). Hyper concentration of PM takes place mainly on the National highways and major connecting roads of the cities where vehicle traffic is very high. Particulate matter (PM) pollution near major roads was often found to be more severe than urban background since resuspended road dust considered to be

61

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

the most important source of PM10 whereas motor vehicle emissions constitute the significant source of fine particles, such as PM2.5 and PM1.0 (Wu et al., 2002). Therefore, it is necessary to quantify the particle emission levels with different size fraction (PM10, PM2.5 and PM1.0), and also to determine particle behavior after emissions, as they are transported away from the road. This paper describes the distribution of airborne coarse particles (PM10) and fine and sub micrometer particles (PM2.5 and PM1.0) near a national highway. Also, the study attempts to acquire particle size distribution, including the contributions of PM2.5 and PM1.0 to the total PM10 mass, separately at the highway.

Experimental techniques

Agra, the city of Taj is located in north- central region (27o10’N 78 o 02’E) of India. Three national highways, NH-2, NH-3 and NH-11, cross the city. NH-2 is one of the busiest highways which connect Delhi to Kanpur. Sampling was carried out at four different distances i.e. A1 (0 m), A2 (100 m), A3 (250 m), A4 (500 m), lying perpendicular to NH-2. The present study was conducted from April - June 2009. Monitoring of pollutants was carried out for 24 hours. The frequency of observations was twice a week at each distance. Grimm 31- Channel Portable Aerosol Spectrometer model No. 1.109 was selected for measuring the concentration of PM10, PM2.5, and PM1.0 at a flow rate of 1.2 Liter/ minute ± 5% constant with controller for continuous measurement. The instrument works on the principal of scattering of light to measure the particle concentrations.

Results and discussion

A significant decrease in the concentrations of PM10, PM2.5 and PM1.0 as the distance from the highway increases was observed. The 24 hour averaged mean, standard deviation, maximum and minimum values of PM10, PM2.5 and PM1.0 are given in table 1. We applied T-test for comparing mean-values of particles obtained at different distances. The p-value for PM10, PM2.5 and PM1.0 at 0-100 m was = 0.05 which signifies 95% difference in their mean values.

Table 1. 24-hour averaged ambient roadside concentrations (μg/m3) of particulate matter

62

IASTA-2010

The p-value increases from 100-250 m and 250-500 m which signifies that difference in their mean values becomeing less significant on increasing distance from highway. The 24 hour average values were compared with standards. The average concentrations of PM10 were found 3.90, 2.19, 2.10, 2.01 times and of PM2.5 were found 2.60, 1.90, 1.58, 1.30 times higher, at 0m, 100m, 250m and 500m respectively, than the standards prescribed by WHO. The 24 hour average concentrations of PM10 were found 1.95, 1.09, 1.05, 1.00 times 0m, 100m, 250m and 500m and of PM2.5 were found 1.08 times higher at 0m than the standard prescribed by CPCB. However no standard has been set for PM1.0. The arithmetic mean ratios of PM2.5/PM10 at the four distances ranges between 0.33 and 0.43 and of PM1.0/PM10 ranges between 0.20 and 0.30 (table 2). The small ratios of fine and sub-micrometer particles in total PM10 mass is most likely attributed to the strong dust events during the sampling period apart from the contribution of local sources including vehicle tailpipe exhaust and re-suspended road dust. This difference between coarse and fine particles indicates that sand dust events in summer carry much coarser than fine particles. Further the value of fine to coarse particle size ratio increases slightly on moving away from the highway since the mass of a fine particle is relatively small and can suspend in the air for a long time. Therefore fine particle concentrations are mainly affected by atmospheric diffusion conditions. Compared with fine particles, coarse particles are heavier and cannot be suspended easily in the air for a long time. Thus their concentrations mainly depend on the variation of local emission.

Table 2. Size distribution of particulate matter concentrations near highway

Conclusion

A negative association between average PM10, PM2.5 and PM1.0 concentration and the distance from the highway was observed. The significance of difference in particle

Table 3. Comparison of roadside PM concentrations (μg/m3) with previous research

63

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

concentrations was decreasing along with increasing distance from the highway. The Particle levels were found higher than the prescribed standards of CPCB and WHO. The low values of arithmetic mean ratio of PM2.5/ PM10 and PM1.0/PM10 suggests that fine particles and small sub-micrometer particles contributed small part of PM10 mass at the roadside in Agra due to dust intrusions during the sampling period. Moreover the increase in the particle size ratio along with the distance from the highway was mainly due to difference in diffusion behaviors of coarse and fine particles in the atmosphere.

Acknowledgement

Financial support by Department of Science and Technology (DST, Project no. SR/S4/ AS: 262/05) New Delhi is acknowledged. We are also thankful to Dr. F. M. Prasad, Principal, St. John’s College and Dr. Ashok Kumar, Head, Department of Chemistry, St. John’s College, Agra for providing us the necessary facilities.

References

1.Taneja, A., Saini, R. and Masih, A., 2008. Indoor air quality of houses located in the urban environment of Agra, India. Ann. N.Y. Acad. Sci., 1-18.

2.He, K. B., Yang, F. M., Ma, Y., Zhang, Q., Yao, X., Chan, C. K., Cadle, S., Chan, T. and Mulawa, P., 2001.The characteristics of PM2.5 in Beijing, China. Atmospheric environment 35, 4959-4970.

3.Wang, Y., Zhuang, G., Tang, A., Yuan, H., Sun, Y., Chen, S. and Zheng, A., 2005. The ion chemistry and the source of PM2.5 aerosol in Beijing. Atmospheric environment 39, 3771-3784.

4.Pope, C. R., Burnett, R., M. J., T., Calle, E., Krewski, D., Ito, K. and Thurston, G., 2002. Lung cancer, cardiopulmonary mortality, and long term exposure to fine particulate air pollution. Journal of American Medical Association 287, 1132-1141.

5.Dockery, D. W., Pope, C. A III., 1994. Acute respiratory effects of particulate air pollution. Annual revision public health 1999 15, 107-132.

6.Berico, M., Luciani, A. and Formignani, M., 1997. Atmospheric aerosol in an urban area- measurements of TSP and PM10 standards and pulmonary deposition assessments. Atmospheric environment 31, 3659- 3665.

7.Wang, S., Feng, X., Zeng, X., Ma, Y. and Shang, K., 2009. A study on variations of concentrations of particulate matter with different sezes in Lanzhou, China. Atmospheric environment 43, 2823-2828.

8.Wu, Y., Hao, J., Fu, L., Whang, Z. and Tang, U., 2002. Vertical and Horizontal profiles of airborne particulate matter near major roads in Macao, China. Atmospheric environment 36, 4907-4917.

9.Chan, L. Y. and Kwok, W. S., 2001. Roadside Suspended particulates at heavily trafficked urban sites of Hong Kong – seasonal variation and dependence on meteorological conditions. Atmospheric environment, 35, 3177-3182.

10.Lee, S. C., Cheng, Y., Ho, K. F., Cao, J. J., Louie, P. K. K., Chow, J. C. and Watson, J. G., 2006. PM1.0 and PM2.5 Characteristics in the road side environment of Hong Kong. Aerosol Science and Technology, 40, 157-165.

11.Edvardsson, K., Magnusson, R., 2009. Monitoring of dust emission on gravel roads: Development of a mobile methodology and examination of horizontal diffusion. Atmospheric environment, 43, 889-896.

12.National ambient air quality standards, Central Pollution Control Board, 2009.

13.WHO global air quality guidelines, 2006, http://www.euro.who.int/document%20/E87950.pdf.

64

IASTA-2010

A–P–2

A Study on Optical and Physical Properties of Aerosols at a Semi-arid Urban site, Tirupati During Summer Monsoon Season

B. Suresh Kumar Reddy*, G. Balakrishnaiah, K. Raghavendra Kumar, K. Rama Gopal, K. Narasimhulu and R.R. Reddy

Aerosol Atmospheric Research Laboratory, Department of Physics,

Sri Krishnadevaraya University,Anantapur-515055

*Email: boreddysuresh@gmail.com

Introduction

Aerosols play an important role in changing the climate by absorbing or scattering of solar radiance. Studies have been revealed that atmospheric aerosols play a vital role in many processes in the Geosphere-Biosphere system, which affects our life either directly or indirectly. There aerosols play an important role in the radiative forcing, atmospheric chemistry and cloud microphysics.

Optical properties of atmospheric aerosols can vary greatly depending on environmental conditions as well as local sources. In a given location, aerosols are characterized by their concentration, their size distribution, their size, their chemical composition and their vertical profile. In the urban surroundings the sources of aerosol particles are more complex. Vehicular and other traffic, anthropogenic combustion products, industrial emissions, dust and fine particles are the important sources of air pollution in the urban environment. Physical properties of aerosols are strong functions of their sources, which are widely distributed and highly variable from one region to other.

Tirupati (13.61oN, 79.4oE, 161m asl), a pilgrim holy centre for devotees of Lord Sri Venkateswara is situated in the southern peninsular in India at the south tip of Andhra Pradesh, which represents a semi arid urban area surrounded by major industrial and agricultural activities. The town owes its existence to the sacred temple of Lord Sri Venkateswara situated on the seven hills (Tirumala) adjoining it. The town is considered to be a high profile centre for education, tourism (about 60,000 visitors per day due to pilgrimage) and business with a population of 3.5 lakhs. A continental type of climate with three distinct seasons: winter, summer and monsoon prevail in the region (Chandra Mouli et al., 2005).

Methodology

Ground based intensity measurement of direct solar radiation under clear sky conditions as a function of solar zenith angle has been made at Sri Venkateswara University, Tirupati for the study of atmospheric aerosols. The instruments consist of a Sun photometer (Microtops-II, Solar Light Company, USA), 10-channel Quartz Crystal Microbalance (QCM)

65

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

(California Measurements Inc., USA) and dual wavelength Aethelometer (Magee Scientific, USA). Intensity measurements of direct solar radiation are carried out on all clear sky days in Tirupati during month of May 2009. Details of the measurements, errors and uncertainties in the error budget estimation are reported in earlier papers (Kumar et al., 2010).

Results and Discussions

The spectral variation of aerosol optical depth (AOD, tp) in the month of May 2009 is shown in Fig. 1.The AOD values are averaged for each day of month May and standard deviations are calculated. A specific wavelength dependence of AOD i.e., decreases of AOD with increase of wavelength, which is consisted with the Mie scattering theory for aerosol particles, which can be clearly seen from the Fig.1. High AOD values are observed at 380 nm suggest dominance of accumulation mode particles loading over the study area. Similar spectral variation has been observed in other studies over Indian region (Moorthy et al., 1988; Kumar et al., 2009a). When tp decreases as increases, the characteristics of aerosols are continental. On the other hand, a flat spectrum can be considered as the contribution of larger particles (Junge, 1963). The spectral variation has become shallower during April and May due to the relative increase in tp at the near infrared wavelengths. The very high values of AOD (close to 1 and above) noticed in the present study may possibly due to the presence of optically thin high altitude clouds in the experimental region. This may also be attributed due to the steadily heated land surface and the temperature starts rising and strong convection develops due to the local depressions, which are formed especially in the afternoon (Kumar et al., 2009a).

Figure 1. Spectral variations of daily mean AOD in month of May 2009 over observation site, Tirupati

The Angstrom wavelength exponent (a), which represents the size distribution and Turbidity coefficient ( ), which represents aerosol loading have been derived from/the plot of logarithm of AOD verses logarithm of wavelength. These aerosol optical and physical parameters computed for the observation period as shown in Fig.2. It is evident

66

IASTA-2010

67

IASTA-2010

As night progresses, due to reduction in the anthropogenic activity, there is a reduction in the mass concentrations during early hours which subsequently increases with the increase in the anthropogenic activity during the morning hours. However, with the local sunrise and subsequent land surface heating, the confinement of aerosol breaks leading to the dispersion and decrease in the surface concentration takes place due to the aerosol ventilation. The heating of the land surface increases the convective activity, vertical mixing and dilution of near surface aerosol concentration. This type of diurnal variation is weak during summer months since the nocturnal boundary layer during this season does not come down to low altitudes and hence the diurnal ratios between the early morning high aerosol concentration and the noon time minimum remains low. (Babu and Moorthy, 2002).

Acknowledgements

The authors are grateful to ISRO-GBP, Bangalore and DST, New Delhi for providing financial assistance to carry out this work.

References

Babu, S.S., Satheesh, S.K., Moorthy, K.K., 2002. Aerosol radiative forcing due to enhanced black carbon at an urban site India. Geophys. Res Lett 29, 1880-92.

Chandra Mouli, P., Venkata Mohan, S., Jaya Rama Reddy, S., 2005. Rain water chemistry at a regional representative urban site: Influence of terrestrial sources on ion composition. Atmospheric Environment 39, 999-1008.

Junge C.E., 1963. Air Chemistry and Radioactivity. New York: Academic press.

Mahesh Kumar, R.S., Devara P.C.S., Raj P.E., Tiwari Y.K., Pandithurai G. and Saha S.K.,et al., 2002. Synthesis of aerosol optical depth data over a tropical urban station. Proc. Conference on “Aerosol remote sensing in global change & Atmospheric pollution” (IASTA 2002), Thiruvananthapuram, September, 18-20; p27-30.

Moorthy, K.K., Nair, P.R. and Moorthy, B.V.K., 1988. A study on Aerosol Optical Depth at a coastal station, Trivandrum. Indian J Radio & Space Physics 1988, 17, 16-22.

Niranjan, K., Srikanth, V., Madhavan, B.L. and Moorthy, K.K., 2006. Winter time aerosol characteristics at a north Indian site Kharagpur in the Indo-Gangetic plains located at the out flow region into Bay of Bengal. J. Geophys Res., 111, D24209. dio:1029/2006JD007635.

Kumar, K.R., Narasimhulu, K., Balakrishnaiah, G., Suresh Kumar Reddy, B., RamaGopal, K., Reddy, R.R., Satheesh, S.K., Krishna Moorthy, K. and Suresh Babu, S., 2010. A study on the variations of Optical and Physical properties of aerosols over a tropical semi-arid station during grass land fire. Atmospheric Research 95, 77-87.

Kumar, K.R., Narasimhulu, K., Balakrishnaiah, G., Suresh Kumar Reddy, B., RamaGopal, K., Reddy, R.R., Krishna Moorthy, K. and Suresh Babu, S., 2009b.Size segregated mass concentration and size distribution of near surface aerosols over a tropical Indian semi-arid region, Anantapur: Impact of long range transport. Science of the Total Environment 2009b, 407, 5589-5604.

Kumar, K.R, Narasimhulu, K., Reddy, R.R., RamaGopal, K., Siva Sankara Reddy, L., Balakrishnaiah, G., Krishna Moorthy, K. and Suresh Babu, S., 2009a. Temporal and spectral characteristics of aerosol optical depths in a semiarid region of southern India. Science of the Total Environment 407, 2673-2688.

69

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

A–P–3

The Relationship between aerosols and lightning over India

D. M . Lal and S. D. Pawar

Indian Institute of tropical meteorology, Pune

Abstract : In recent years the effect of urbanization on local convection and lightning has been studied very extensively. It has been proposed that the urban effect is mainly a combination of a thermodynamic effect due to the differential heating of the surface over the city called as heat island effect and an increase of the pollution concentration in the local atmosphere caused mainly by human activities called as aerosol effect. It has been found that aerosols influence the cloud microphysics, precipitation and also cloud electrification. However systematic relationship of aerosols with precipitation and lightning has not been established due to complex correlations.

Here we have analyzed the 8 years data of total lightning, AOD and rainfall over two inland and two coastal metropolitan cities of India to study the effect of aerosols on lightning. The lightning and rainfall data is taken from TRMM satellite and AOD data is taken from MODIS satellite. Figure 1 shows trends of AOD over these cities from 2001 to 2008.

Figure 1. Variation of AOD over 4 metropalitans in India from 2001-2008

70

IASTA-2010

71

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

A–P–4

Influence of Tropical Cyclones on Aerosol Properties over Indian Region

D. V. Mahalakshmi, Shailesh Kumar Kharol, Anu Rani Sharma and K. V. S. Badarinath

Atmospheric Science Section, National Remote Sensing Centre,

Dept. of Space.Govt. of India, Balanagar, Hyderabad – 500 625, India

Email : badrinath_kvs@nrsc.gov.in

Introduction

In India fierce tropical cyclones occur during the pre-monsoon (spring), early monsoon (early summer), or post-monsoon (fall) periods. Tropical cyclones originating in both the Bay of Bengal and the Arabian Sea often attain velocities of more than 100 kmh-1 and cause intense rain and tidal waves as they cross the Indian coast. In the present study, we report the changes in aerosol properties at Hyderabad, India, associated with severe cyclonic storm “Aila” occurred during the last week of May, 2009 over Bay of Bengal. It is the first cyclone in the month of May to cross West Bengal after 1989.

Datasets and Methodology

The measurements for the case study were carried out in the premises of the National Remote Sensing Centre (NRSC) campus at Balanagar (17o.28’ N and 78o.26’ E) located within the Hyderabad urban center during cyclone period. Synchronous and continuous observations of columnar Aerosol Optical Depth (AOD) were carried out using a handheld multi-channel sun-photometer (Microtops-II, Solar Light Co., USA) at six wavelength bands centered on 380, 440, 500, 675, 870 and 1020 nm. In addition, MM5 mesoscale model derived meteorological parameters during cyclone period were analysed.

Results and Disscussion

Figure 1a shows the track of cyclone “Aila” over the Bay of Bengal occurred during 24- 25 May, 2009, struck the coast of West Bengal close to Sagar Island on 25 May, 2009 lay centered at 21.5 o N and 88.5o E. The cyclone Aila as referred by IMD, is the severe cyclonic storm experienced over the BOB, with an estimated central sea level pressure of 967hPa and associated maximum wind of 100 to 110kmph. Aila moved towards North throughout its life cycle and affected 1,000 acres of cropland in Orissa state. Figure 1b shows the true color Terra-MODIS image on 25 May, 2009 when the central part of the cyclone was moving towards the northeastern part of the Bay of Bengal. Figure – 1c shows the analysed wind speed and direction derived by MM5model at 700 hPa (3000 m) on 24th May, 2009. The wind direction is a persistent northwesterly flow in the Northern part of India (Ganges valley) and low in the middle part. The anticlockwise wind direction field clearly shows the presence of the

72

IASTA-2010

cyclone in the northern part of Bay of Bengal (BoB), associated with strong winds.

Figure 1. (a) ‘Aila’ cyclone Track over Bay of Bengal during May, 2009, (b) Terra-MODIS true color composition showing the presence of dust plume over the region on 25th May, 2009 and (c) wind speed and direction derived by MM5model at 700 hPa (3000 m) on 24th May, 2009

Significant variations in aerosol properties were observed over urban region of Hyderabad, India which are mainly driven by changes in synoptic meteorological conditions associated with ’Aila’ cyclone. Day-to-day variations in AOD at 500nm (AOD500) and Ångström exponent “a” during 22 to 27 May, 2009 are shown in Figure – 2 (a & b). AOD500 values showed remarkable decrease during the cyclone period. These large variations in aerosol loading were attributed mainly to the changes in wind speed and direction bringing marine air masses over the region on 24th May. Despite the uplifting of

73

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

soil particles near the surface, the higher winds during cyclone period act as a ventilation tool for the whole atmospheric column resulting in lower AODs over the study area.

Figure 2. AOD500 and a380-870 variations over the urban region of Hyderabad, India during the cyclone period

Conclusions

The aerosol properties over the urban region of Hyderabad, India, were analyzed during an intense cyclone storm over the Bay of Bengal in the end of May 2009. The analysis of results suggested a significant decrease in columnar aerosol optical depth and a-Ångström values suggesting presence of coarse-mode aerosols probably from dust and sea salt during the cyclone.

Acknowledgements

The authors thank Director, NRSC and Dy. Director (RS&GIS-AA) for necessary help at various stages and ISRO-GBP for funding the project.

74

IASTA-2010

A–P–5

Vertical Aerosol Profiles over Athens During Intense Dust Events in Winter

D.G. Kaskaoutis1, H.D. Kambezidis1, P.T. Nastos2, Shailesh Kumar Kharol3, Anu Rani Sharma3 and K.V.S. Badarinath3

1Atmospheric Research Team,Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Lofos Nymphon, P.O. Box 20048, GR-11810 Athens, Greece

2University of Athens, Department of Geology and Geoenvironment, University campus GR-15784 Athens Greece

3Atmospheric Science Section, National Remote Sensing Centre, Dept. of Space, Govt. of India, Balanagar, Hyderabad – 500 625, India

Introduction

The Sahara desert is the most important dust source in the world. Exports of dust plumes to the North Atlantic and Mediterranean Sea occur throughout the year. The occurrence of Sahara dust (SD) events above eastern Mediterranean has a marked seasonal cycle, with a spring maximum and a winter minimum. Nevertheless, under the influence of favorable synoptic situations, e.g. strong south winds in a cyclonic circulation, intense SD events also occur in winter with a duration of 1 or two days. Therefore, there is a growing interest in examining the spatio-temporal aerosol dust distribution over Eastern Mediterranean and coastal Greece due to their proximity to the North African arid regions. Three dust events with high aerosol optical depth (AOD) values have been observed over Athens on 4, 6-7 February and 5-6 March 2009. These dust events were well captured by the satellite observations and are investigated in the present study by means of ceilometer vertical profiles, CALIPSO observations and model DREAM predictions. The main goal of this study is the investigation via vertical-profiling instrumentation and modeling of 3 dust events in winter, a period that is uncommon for such phenomena. The ground-based measurements are in good agreement with the satellite ones as well as the model predictions.

Instrumentation and Data Collection

The ceilometer used in the present study is a Vaisala CL31 model. It is equipped with an InGaAs MOCVD pulsed laser, emitting at 910 nm and having an energy per pulse of 1.2 J. The emission frequency is 10 kHz while the pulse duration is 100 ns. The elastically backscattered radiation is collected by a lens. The inner part of the lens is used for the alignment of the instrument and for the laser emission, while the outer part is used for the collection and focusing of the backscattered radiation onto the receiver. The separation between the two areas is achieved by an oblique mirror. The lidar data are acquired and stored by a 60 MHz digital processor and a hard disk. With this system vertical profiles of the aerosol backscatter coefficient can be obtained from 5 m up to 7.5 km at 930 nm. The CL31 is a new instrument located at the Actinometric station of the National Observatory of Athens and has been calibrated during a 2-day campaign against a quality assured

75

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

aerosol profiles provided by a Raman Lidar (Tsaknakis et al., 2009). The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) provide new insight of the role of clouds and atmospheric aerosols (airborne particles) in regulating Earth’s weather, climate, and air quality. CALIPSO has a 98o-inclination orbit and flies at an altitude of 705 km providing daily global maps of the vertical distribution of aerosols and clouds. The CALIPSO satellite carries a polarization-sensitive lidar Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), which provides profiles of backscatter coefficient at 532 and 1064 nm.

In the last years, an integrated modeling system, the Dust Regional Atmospheric Modeling (DREAM) model (http://www.bsc.es/projects/earthscience/DREAM/) (Nickovic et al., 2001) is widely used to simulate the 3-dimensional field of the dust concentration and its cycle in the atmosphere. The dust model takes into account all the major processes of dust life cycle, such as dust production, convection and advection, as well as wet and dry deposition, while it has been extensively used and validated for the identification of dust events in the Mediterranean (e.g. Perez et al., 2006; Amiridis et al., 2009).

Results and Discussion

The ceilometer-derived vertical profiles of aerosol backscatter coefficient are shown in Fig. 1a, b for the dusty days, 6 February and 6 March 2009. The observed vertical aerosol profiles are averaged at a time interval of 6 hours. On 6 February a defined aerosol plume is shown between 1 and 4 km associated with enhanced values of the backscatter coefficient. Large aerosol backscatter coefficient values near the ground are observed on 6 March. It was observed that the SD event in March was more intense causing strong limitation to visibility and very high values of AOD. However, the enhanced low-level values have not a strong signal above the boundary layer, although they remain high and comparable in magnitude with the previous case, at altitudes up to 2 km. Figure 2 (a – c) show the temporal variation of the vertical backscatter profiles for 4 February and 5-6 March, respectively. The half-hour time averaged values were used for the preparation of these figures. On 4 February the large backscatter values are observed within the first km with

Figure 1 (a – b). Vertical profiles of the aerosol backscatter coefficient taken at Athens on 6 February 2009 (a) and 6 March 2009 (b). The profiles are time-averaged during the 6-hr interval (06-12:00 LST), while the bars express one standard deviation of the mean

76

IASTA-2010

some hints of increased values above. On 5th and 6th March, the backscatter values are higher, also detected at the lower tropospheric layer. However, during some limited time intervals, there are hints of vertically increased values characteristic of long-range transported dust plume. It must be noted that the influence of clouds was removed from the backscatter retrievals and during the noon hours there is increased uncertainty due to lower signal-to-noise ratio. Nevertheless, the consistency of the results between ceilometer and Raman Lidar renders it as a powerful tool for monitoring the vertical profile of dust aerosols.

Figure 2 (a – c). Temporal variation of the vertical profile of the backscatter coefficient at Athens on 4 February 2009 using half hour time intervals

The DREAM predictions for the vertical profile of dust concentration for 6 February (12:00 UTC) and 6 March (06:00 UTC) are shown in Figs. 3 (a – b). One can observe the good agreement between the ceilometer and DREAM vertical profiles on 6 February when both show a dust layer between 1 and 3 km. Similarly to the ceilometer measurements, DREAM predicts larger concentration of dust particles on 6 March mainly detected within a thick dust layer between 1 and 4 km. The 6-hr averaged vertical profiles obtained by the ceilometer do not show a clear dust layer above the boundary layer, but agree in the enhanced aerosol backscatter values. The CALIPSO-derived total attenuated backscatter at 532 nm and the Vertical Feature Mask (VFM) data products were used to identify the position of dust along the overpass trajectory. A typical example of the vertical distribution

77

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

Figure 3. Vertical profiles of the dust concentration values as predicted by DREAM model on 6 February (12 UTC) and 6 March (06 UTC)

of the dust plume over the study region during nighttime on 5 February 2009 is shown in Fig. 4. The nighttime pass of CALIPSO was above Balkan countries, west Greece, eastern Mediterranean and Sahara. Fig. 4 shows an extended aerosol layer covering nearly the whole satellite track extending up to a height of 3–5 km. Limiting the analysis over Libya, eastern Mediterranean and Greece (24o –37o N, 15o-19o E), this aerosol layer exhibits a high total attenuated backscatter at 532 nm, reaching to 0.05-0.06 km-1sr-1. This aerosol layer, which corresponds to the dust plume, is generated over the Sahara desert at about

Figure 4. CALIPSO observations of the total attenuated backscatter at 532 nm at nighttime of 5 February 2009

78

IASTA-2010

24oN, 15oE near the borders of Libya, Chad and Niger. After its exposure it is elevated covering about 3-km in depth and is moving northwards. As the dust layer moves towards Greece its intensity seems to decrease while its vertical extend is limited to lower altitudes, within the first 2 km.

Conclusions

Vertical profiles of aerosols during intense dust events in winter were measured over Greece by means of ceilometer located at Athens, CALIPSO observations and model DREAM predictions. The instruments, ground-based and space-borne, identified intense dust plumes within the first two km of the troposphere, while the model predictions were in close agreement with those observations. The overall results showed that the newly established ceilometer can constitute a powerful tool for the detection of dust or other long-range transport of aerosols.

References

Amiridis, V., Kafatos, M., Perez, C., Kazadzis, S., Gerasopoulos, E., Mamouri, R.E., Papayannis, A., Kokkalis, P., Giannakaki, E., Basart, S., Daglis, I. and Zerefos, C., 2009. The potential of the synergistic use of passive amd active remote sensing measurements for the validation of a regional dust model. Annales Geophysicae, 27, 3155-3164.

Nickovic, S., Kallos, G., Papadopoulos, A. and Kakaliagou, O., 2001. A model for prediction of desert dust cycle in the atmosphere. J. Geophys. Res. 106: 18113-18130.

Pérez, C., Nickovic, S., Baldasano, J.M., Sicard, M., Rocadenbosch, F. Cachorro, V.E., 2006. A long Saharan dust event over the western Mediterranean: Lidar, Sun photometer observations and regional dust modeling. J. Geophys. Res. 111, D15214, doi:10.1029/2005JD006579.

Tsaknakis, G., Amiridis, V., Kambezidis, H., Papayannis, A., Kokkalis, P., Mamouri, R.E., Kaskaoutis, D., Georgousis, G., Avdikos, G., 2009. Intercomparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece. 8th International Symposium on Troposheric Profiling: Integrations of Needs, Technologies and Applications, 18-23 October 2009, Delft, The Netherlands.

79

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

A–P–6

Dissimilarities in Maximum and Minimum Temperature Trends over India and its Possible Linkages to Aerosols

D.R. Kothawale and K. Krishna Kumar

Indian Institute of Tropical meteorology, Pune, India

(kotha@tropmet.res.in)

Abstract : Atmospheric aerosols could cause a negative climate forcing that can modulate the regional surface temperature trends in a significant way. The asymmetry in maximum and minimum temperature trends over the Indian region has been a feature that stands out in the context of global temperature trends. Keeping in view these facets, in this study we examine dissimilarities of temperature trends over space and time over the Indian region, to look for signatures of aerosols influence. North of 20°N (North India) and South of 20°N (South India) temperatures series have been prepared for dry and wet season the period 1901-2007 and the trends were examined for different periods i.e. 1901-2007, 1901-50, 1951-1990 and 1951-2007 to isolate aerosols influence on temperatures. The period 1951 onwards is considered as post industrial period where emission of green house gases and aerosols are continuously increasing.

Introduction

Increase in greenhouse gases viz., CO2, CH4, CFCs, N2O etc. and water vapour in the atmosphere are mainly responsible for the temperature warming, while aerosols in the atmosphere through their negative radiative forcing are responsible for lowering the land surface temperature due to decline in solar radiation reaching the earth’s surface because of atmospheric aerosols. The aerosol optical depth over northern parts of India is found to be higher than over southern parts of India due to the proximity of the region to the source of natural aerosols from the deserts and also due to higher growth rate of population, urbanization and industrialization.

Data and Analysis

The gridded (0.5 Lat. X 0.5 Lon.) monthly maximum and minimum temperature data for the period 1901-2007 have been used in this analysis . The gridded data have been prepared from well spread 121 stations over the India region. Temperature series for the Dry season (previous year November + December + current year January + February + March + April + May ) and Wet season (June + July + August + September + October) have been constructed. North and south India temperature regions are delineated based on aerosol concentration. Very high level of aerosol optical depth is observed over the whole of Ganges-river basin which covers a major part of north India and the rest is considered as South India (Reddy and Venkataraman, 2002a & 2002b).

Results

Both North and South India dry season maximum temperature shows significant warming trend of 0.8C and 1.0C per hundred years during the period 1901-2007. However,

80

IASTA-2010

dissimilarity is observed during 1951-1990, the North India shows decreasing trend and south India shows increasing trend, while trends are positive in recent period 1991-2007. Spatial and temporal dissimilarities in trend clearly point to role of aerosols in lowering temperature trends over northern India

References

Reddy, M. S. and Venkataraman, C., (2002a) , Inventory of aerosol and sulfur dioxide emissions from India: I Fossil fuel combustion, Atmos. Environ., 36,699-712

Reddy, M. S. and Venkataraman, C., (2002b) , Inventory of aerosol and sulfur dioxide emissions from India: II Biomass combustion, Fossil fuel combustion, Atmos. Environ., 36,677-697..

81

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

A–P–7

Measurement of the Atmospheric Aerosol Number Concentration over Roorkee, India

Deepti Saxena1, R Yadav1, Adarsh Kumar2* and Jagdish Rai3

1 Department of Physics, Meerut College, Meerut, UP, India – 250 002

2 Department of Physics, Apeejay College of Engineering, Sohna, Gurgaon, Haryana, India –122 103 3 Department of Physics, Indian Institute of Technology, Roorkee, India – 247 667

*Corresponding Author : Dr Adarsh Kumar (E mail : adarsh_phy@yahoo.co.in)

ABSTRACT : The atmospheric aerosol number concentration has been measured at Roorkee (29º 52’ N, 77º 53’ E, 275 m above mean sea level) in northern India during April-July 2007 at a height of 9 m above ground level. The aerosol number concentration having different sizes (0.3- 0.5, 0.5-1.0, 1.0-2.0 and 2.0-5.0 m) in summer season (April-July 2007) has been analyzed, and the daily variation of aerosol number concentration has been related to selected meteorological parameters like as relative humidity, temperature, rainfall and wind speed. The measurements were carried out with an optical partical counter. The aerosol number concentration for upper size ranges (1.0-2.0 and 2.0-5.0 m) is maximum in June and minimum in July. The aerosol number concentration in small size ranges (0.3-0.5 and 0.5-1.0 m) decreases significantly till the end of July.

Keywords : Aerosols; Optical Particle counter; Temperature; Relative humidity; Rain fall

Results

Figure 1. Time variation (IST) of average number concentration of aerosols in season (April-July, 2007) for lower size range

82

IASTA-2010

Figure 2. Time variation (IST) of average number concentration of aerosols in season (April-July, 2007) for upper size range

Figure 3. Daily variation of average number concentration of aerosols in season (April-July, 2006) for smaller size ranges ((0.3-0.5 & 0.5-1.0 m)

83

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

Figure 4. Daily variation of average number concentration of aerosols in season (April-July, 2006) for bigger size ranges (1.0-2.0 & 2.0-5.0 m)

(a)

(b)

Figure 5. The daily mean average number concentration of aerosols in summer season (April –July, 2007)

84

IASTA-2010

(a)

(b)

(c)

(d)

Figure 6. The daily mean average of meteorological parameters (temperature, RH, wind speed and rain fall) in summer season (April-July, 2007)

References

1.Aher, G. R. and V. V. Agashe, 1997, Effect of premonsoon scenario on aerosols at Pune, TROPMET’97, IISc, Bangalore, India, 31-32.

2.Bansal, M. K. and T. S. Verma, 1998, Aerosol measurements at Roorkee relating to the total solar eclipse of 24 October 1995, Indian Journal of Radio & Space Physics, 27, 260-265.

3.Byrne, M. A.and S. G. Jennings, 1993, Scavenging of sub-micrometer aerosol particles by water drops, Atmospheric Environment, Part A 27, 2099-2105.

85

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

4.Devara, P. C. S. and P. E. Raj, 1998, A lidar study of atmospheric aerosols during two contrasting monsoon season, Atmosfera, 11, 199-204.

5.McCormick, M. P., T. J. Swissler, W. P. Chu and W. H. Fuller, 1978, Post-volcanic stratospheric aerosol decay as measured by Lidar, Journal of Atmospheric Science, 35, 1296-1303.

7.Pahwa, D. R., S. P. Singhal and L. T. Khemani, 1994, Study of aerosols at Delhi, Mausam, 45(1), 49-56.

8.Parameswarn, K. and G. Vijaykumar, 1994, Effect of atmospheric relative humidity on aerosol size distribution, Indian Journal of Radio & Space Physics, 23, 175-188.

9.Pranesha, T. S. and A. K. Kamra, 1996, Scavenging of aerosol particles by large water drops, 1-Natural case, Journal of Geophysical Research, 101, 23373-23381.

10.Sharma, D. K., J. Rai, M. Israil and P Singh, 2003, Summer variations of the atmospheric aerosol number concentration over Roorkee, India, Journal of Amospheric & Solar-Terrestrial Physics, 65, 1007- 1019.

11.Shaw, G E, 1988, Aerosol-size temperature relationship, Geophysical Research Letters, 15, 133-135.

12.Singh, N, 1985, Role of atmospheric ions on condensation and cloud formation processes, Ph D Thesis, University of Roorkee, India.

13.Singh, A. K., J. Rai, S. Niwas, A. Kumar and A. Rai, 1997, Measurements of aerosols during monsoon at Roorkee, TROPMET’97, IISc, Bangalore, 77.

14.Singh, A. K., S. Niwas, A. Kumar, J. Rai and M.J. Nigam, 1999, Variation of atmospheric aerosols and electrical conductivity at Roorkee during the total solar eclipse of October 1995, Indian Journal of Radio & Space Physics, 28, 1-10.

15.Sparmacher, H., K. Fullberg and H. Bonko, 1993, Scavenging of aerosol particles: particle-bound radionuclides-experimental. Atmospheric Environment, Part A, 27, 605-618.

16.Vakeva, M., K. Hameri, T. Puhakka, E. D. Nilsson, H. Hohti and J. M. Makela, 2000, Effect of meteorological process on aerosol particle size distribution in an urban background area, Journal of Geophysical Research, 105, 9807-9821.

17.Zhang, X. Y., R. Arimoto, J. J. Cao, S. A. Zhi, D. Wang, 2001, Atmospheric dust aerosol over Tibetan Plateau, Journal of Geophysical Research, 106, 18471-18476.

86

IASTA-2010

A–P–8

Assessment of Solid and Gaseous Particles in Ambient Air at Two Urban and One Semi-Urban Site in Himachal Pradesh, India

Harinder K. Thakur1, Jagdish C. Kuniyal1*, Kesar Chand1

and Dinesh C. Pandey2

1G.B. Pant Institute of Himalayan Environment and Development, Himachal Unit, Mohal-Kullu-175 126 (H.P.),India.

2Department of Geography, DSB Campus, Kumaun University, Nainital-243 002 (U.K.), India

*Corresponding author : E-mails: jckuniyal@rediffmail.com / kuniyaljc@yahoo.com

Introduction

Ever increasing solid and gaseous particles (aerosols) dispersed in the ambient air are the main sources of deterioration of pristine air environment in the Himalayan or any other mountain topography of the world today. Due to large extent of human interferences with high discharge of these aerosols in the atmosphere, especially in sprawling urban towns, weakened the repairable capacity of nature, and results in as an adverse weather/ climatic, visibility and health effects. Some of the studies on air quality in the Himalaya reveal that concentration of existing level of these aerosols have been increased considerably (Gagananda et al. 2005, Kuniyal et al. 2005, Kuniyal et al. 2007, Kuniyal et al. 2009). The present study is focused on the assessment of solid and gaseous particles and their concentrations in terms of total suspended particulate matter below 100 micron (TSP), particulate matter below 10 micron in size (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2) and ammonia (NH3) in the urban and semi-urban environment of the Himalaya. This present study was conducted in pre-monsoon and post-monsoon period of the year 2009.

Study Sites and Methodology

To assess the ambient air quality, the present three experimental sites were selected in two urban towns, Bilaspur (Lat. 31020.342’N, Lon. 76045.704’E, Alt. 556 m) and Mandi (Lat. 31042.505’N, Lon. 76055.974’E, Alt. 760 m) and in a semi-urban site, Keylong (Lat. 32034.240’N, Lon. 76002.054’E, Alt. 3100 m) in Himachal Pradesh. Altitudinally, these sites also represent the three important mountain ranges (Shiwalik, Lesser and Greater) of the Western Himalaya. According to the 2001 Census, Bilaspur is having 13,058 human populations in an area of 10.68 km2. While at Mandi and Keylong, populations are 26,858 and 1,977 with an area of 4.26 and 2 km2 respectively (Anonymous, 2001). Each monitoring site was selected in a manner as to represent almost the central part of the site’s locality. According to the surroundings, the site at Bilaspur falls under residential locality, Mandi is under residential cum commercial locality and Keylong is under rural locality. These experimental sites were free from any of the restrictions in air flow. TSP, PM10, SO2, NO2

87

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

and NH3 were monitored twice (in pre-monsoon and post-monsoon) in a week’s land campaign mode. The 8 hours duration sampling on diurnal basis (0000 to 0800 hr, 0800 to 1600 hr and 1600 to 0000 hr) was exposed using Respirable Dust Sampler (RDS APM- 460 NL, make Envirotech) and High Volume Sampler (HVS APM- 430, make Envirotech) with regular and simultaneous monitoring at each site. The exposed samples, which has completed more than 75% of the total duration of 8 hr sampling were considered to obtain results and those could not completed this duration due to electricity failure or other technical faults were rejected. On the basis of filtration-gravimetric methods to obtain the TSP and PM10 concentration, Whatman Glass Microfibre Filter GF/A (20.3×25.4 cm) with pore size of 0.25 micron was used. Trace gases like SO2, NO2 and NH3 were monitored with the help of thermo electrically cooled impinger box, attached to HVS and RDS. The colourimetric determination, using modified West and Gaeke Method (Potassium Tetra Chloromercurate-TCM method) for SO2 (West and Gaeke, 1956), Jacob and Hochheiser Method for NO2 (Jacobs and Hochheiser, 1958) and modified Nesslers Reagent Method for NH3 was used to analyze these trace gases. To find out the possible reasons for the certain pollution episodes due to heavy loading of aerosols in the airmass, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used (Draxler and Rolph, 2003).

Results and Discussions

The solid particles (TSP and PM10) in these three selected Himalayan sites were found high as compared to gaseous pollutants. During observations, TSP and PM10 have crossed their permissible limits (TSP=200 μg m-3, PM10=100 μg m-3 set by CPCB) at all the sites in both the sampling periods. On diurnal basis highest concentration of TSP and PM10 was found between 1600 hr to midnight followed by 0800 hr to 1600 hr and lowest between midnight to morning 0800 hr in both the seasons, except at Mandi in post-monsoon period. During this period at Mandi, the increase in concentration of TSP and PM10 was found from midnight to up to the 1600 hr and then a little bit of decrease in the sampling of 1600 hr to midnight. TSP was recorded ever highest with 418 μg m-3 on 29th June 2009 between 1600 to 0000 hr at Bilaspur while, PM10 was 112.5 μg m-3 on 2nd November 2009 between 1600 hr to 0000 hr at Mandi. The highest mean concentration of TSP was recorded 180.3±18.1 μg m-3 at Bilaspur in pre-monsoon (Fig. 1). This value for PM10 remained 69.1±4.4 μg m-3 at Mandi in post-monsoon (see Fig. 1). Keylong, a site in the cold desert, showed TSP concentration too high compared to PM10 during pre-monsoon when the region was dry and the frequent dust storms were observed. However, the gaseous pollutants like SO2, NO2 and NH3 were recorded far below the permissible limits (80 μg m-3 for SO2 and NO2, and 400 μg m-3 for NH3 set by CPCB) at all the study sites. The highest concentration of SO2 in both the sampling seasons was recorded with 18.2 μg m-3 at Bilaspur between midnight to morning 0800 hr in pre-monsoon. NO2 remained highest with 23.9 μg m-3 at Bilaspur during 1600 hr to 0000 hr in post-monsoon. This value for NH3 recorded with 62.2 μg m-3 at Mandi between midnight to morning 0800 hr. The highest mean concentration of SO2, NO2 and NH3 was recorded with 4.4±1 μg m-3 at Bilaspur in pre-monsoon, 13.4±1.3 μg m-3 again at Bilaspur in post-monsoon and 32.9±3.7 μg m-3 at Mandi in pre-monsoon (see Fig. 1). TSP and PM10 concentrations were greatly influenced by the local sources such as vehicles and visitors’ influx, biomass burning (fuel wood, dried cow dung cakes, agricultural waste, etc.), coal and solid waste burning, gen sets especially during light failure and dust blown from nearby unmetalled roads, affecting

88

IASTA-2010

adversely the air quality. However, the long-range transport sources through air mass movement from outside regions can also be considered to be contributing to the existing concentrations of these aerosols in the region.

Fig. 1(a&b) Mean concentration of TSP and PM10 , and (c&d) SO2, NO2 and NH3 during pre-monsoon and post- monsoon periods, 2009

Conclusion

The concentrations of TSP and PM10 have crossed the National Ambient Air Quality Standard at all the sites in both the sampling duration, which is a matter of serious concern for these sprawling urban and semi-urban localities of the ecologically sensitive parts of the Himalaya. There is a need to aware the local communities regarding the future consequences of polluted air and to adopt pollution free technologies.

Acknowledgement

The authors are obliged to the Director, G.B. Pant Institute of Himalayan Environment and Development, Kosi-Katarmal, Almora, Uttarakhand for providing necessary facilities. Authors also express their gratitude to Deputy Commissioner, Lahaul & Spiti district and Municipal Council’s authorities of Bilaspur and Mandi town for their cooperation and providing facilities during field study.

References

Anonymous (2001) Census report, Government of India, pp.32-45.

Draxler, R.R., Rolph, G.D. (2003) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) software, NOAA; Air Resour. Lab., Silver Spring, Md. (available at http://www.arl.noaa.gov/ready/ hysplit4.html).

89

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

Gajananda, Kh., Kuniyal, J.C., Momin, G.A., Rao, P.S.P., Safai, P.D., Tiwari, S., Ali, K. (2005) Trend of atmospheric aerosols over the northwestern Himalayan Region, India, Atmospheric Environment 39(27): 4817-4825.

Jacobs, M.B., Hochheiser, S. (1958) Continuous sampling and ultra micro determination of nitrogen oxide in air analyst, Chemistry 30: 426-428.

Kuniyal, J.C., Alpana Thakur, Thakur, H.K., Sharma, S., Pant, P., Rawat, P.S. and Moorthy, K.K. (2009) Aerosol optical depths at Mohal-Kullu in the northwestern Indian Himalayan high altitude station during ICARB, Journal of Earth System Science 118(1): 41-48.

Kuniyal, J.C., Momin, G.A., Rao, P.S.P., Safai, P.D., Tiwari, S., Ali, K. and Gajananda, Kh. (2005) Aerosols behaviour in sensitive areas of the northwestern Himalaya: A case of Kullu-Manali tourist complex, India, Indian Journal of Radio & Space Physics 34(5): 332-340.

Kuniyal, J.C., Rao, P.S.P., Momin, G.A., Safai, P.D., Tiwari, S. and Ali, K. (2007) Trace gases behaviour in sensitive areas of the northwestern Himalaya: A case study of Kullu-Manali tourist complex, India,

Indian Journal of Radio & Space Physics 36(3): 197-203.

West, P.W., Gaeke, G.C. (1956) Fixation of sulphur dioxide as sulfitomercurate (11) and subsequent colorimetric determination, Analytical Chemistry 28: 1916-1819.

90

IASTA-2010

A–P–9

Seasonal Variations in PM10 and PM2.5 Loading at New Delhi: A Case Study Based on Two Years Observation Data

Khem Singh1, Arvind K. Jha1, Z. H. Khan2 and Prabhat K. Gupta1

1Chemical Metrology Section, National Physical Laboratory, New Delhi -12

2Department of Physics, Jamia Millia Islmia, New Delhi - 25

Email: khem008@nplindia.org

Introduction

The role of atmospheric aerosols, particularly its anthropogenic component, which contribute to most of the accumulation mode fraction, is assuming increasingly importance. The concentrations as well as the size distribution of aerosols in the atmosphere are affected by various source processes, removal processes like washout and rainout (Flossmann et al., 1985; Byrne and Jennings, 1993), by aging and by particle growth due to humidity changes (Hanel. 1976). Atmospheric aerosols have several environmental impacts, like; polluting the ambient causing acid rain, reducing visibility, affecting radiation balance, modifying cloud property and causing health related problems (Angstrom, 1964;

Sanhueza, 2001).

Measurement on mass-size distribution of atmospheric aerosol was made at NPL, New Delhi during December 2005 to January 2008 to understand the seasonal variation in their size distribution. We discuss the size distribution in three different seasons: summer (March-June), monsoon (July-October) and winter (November-February).

Experimental

The experiments were performed at National Physical Laboratory (NPL), New Delhi, as one of the sites, which is located at Latitude 28038’N and longitude 77010’E. Aerosol particles were collected using 8-stage Anderson Cascade Impactor with size bins 0-0.4, 0.4-0.7, 0.7-1.1, 1.1-2.1, 2.1-3.3, 3.3-4.7, 4.7-5.8, 5.8-9.0, = 9.0 m at a flow rate of 28.3 LPM. Aerosol samples were collected on the pre-treated and pre-weighed quartz filter papers. Normally the sampling period was kept about 72 hours to get sufficient aerosol material.

Results and Discussions

Average concentration of PM10 and PM2.5 during study period is observed to be 310±176g m-3 and 140±82 g m-3 respectively (Fig. 1). The highest concentration of PM10 (874±53g m-3) and PM2.5 (368±27 g m-3) was observed in the month of June 2006, whereas the low concentration of PM10 (64 g m-3) and PM2.5 (29 g m-3) was observed in the month of September 2007. Higher concentration of PM10 (424 g m-3) observed in the month of December 2005 which was reduces to 130 g m-3 in the month of February 2006 and then again increased during June 2006 (874 g m-3). The concentrations

91

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

further become lowest (144 g m-3) during July 2006.Fig. 1 shows that the concentration of PM10 is again increases in December 2006 (397 g m-3), November 2007 (535 g m-3), and March 2007 (467 g m-3) with the lower value during September 2007 (64 g m-3). The similar trend was observed for PM2.5 concentration obtained.

Figure 1. PM10 and PM2.5 variation

Fig. 2 shows that the aerosol mass loading is enhanced in winter 2006-07 (359±33 g m-3) and 2007-08 (395±134 g m-3) as compared to summer 2006 (337±150 g m-3) and 2007 (346±171 g m-3). During monsoon the aerosol loading is comparatively lower because of the washout by rain. The aerosol mass loading in monsoon period 2006 was 254±96 g m-3 and in 2007 was 230±128 g m-3. An increasing trend of aerosol loading is observed during summer and winter, whereas decreasing trend during monsoon. Aerosol loading in summer 2007 is more than the summer 2006. During winter 2007-08 the aerosol loading is more than the successive previous years 2006-07 and 2005-06 observations. The same trend is observed for PM2.5. It is observed that the concentration of PM2.5 increased from 2006 to 2008. PM2.5 concentration in summer 2007 is higher (146±128 g m-3) than summer 2006 (117±59 g m-3) and winter 2007-08 values (195±63 g m-3) is higher than winter 2006-07 (171±27 g m-3) and winter 2005-06 (126±83 g m-3) values.

Figure 2. Seasonal variation of PM10 and PM2.5 at Delhi during summer

92

IASTA-2010

The PM2.5 to PM10 ratio for entire study period varies in the range of 0.38 to 0.55, with an average value of 0.45 ± 0.06. The ratio reaching maximum (0.55) during winter 2005-06 and minimum (0.38) in summer 2007 indicates that, PM2.5 contribution in winter is more as compare to the summer. In summer, because of the frequent dust storm events, coarse particles are more dominant than that of fine particles. During winter as the boundary layer is low, and the emission remain trapped in near surface, hence fine particle emitted from vehicle, power plants and industries contributes more than the coarse particle, which settle down faster as compared to summer seasons, when boundary layer is high and mixing is proper.

In order to study the correlations between PM10 and PM2.5, regression analysis was carried out. The regression results are illustrated in Fig. 3, where a clear correlation can be seen between PM10 and PM2.5. It may be seen from the figure that there is a very good correlation between PM10 and PM2.5 (r2 = 0.9159) implying that variation in PM10 is due to the variation in PM2.5. Thus, PM10 may adequately act as a surrogate for PM2.5. The good correlation between different size fractions can be attributed to the process of transport in atmosphere by winds which carry the PM.

Figure 3. Correlation between PM10 and PM2.5.

Conclusion

In Delhi pollution is episodic, during summer one sees dust pollution and in winter there is smog. Dust aerosols from the neighboring deserts are transported over northern India during summer. The presence of aerosols controls the cooling or heating of the Earth surface and the warming and cooling of atmosphere. Over the Delhi during off set of the summer dust particles has been known to increase, indicating increase in coarser particles due to dust storms, which rise dust and transport from Thar desert and adjoining regions. The sources of the dust were evaluated from the backward trajectory analysis.

An increasing trend of aerosol loading is observed during summer and winter, whereas decreasing trend during monsoon. In summer, because of the frequent dust storm events, coarse particles are more dominant than that of fine particles and during winter the boundary layer is low, and the emission remain trapped in near surface, hence fine

93

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

particle emitted from vehicle, power plants and industries contributes more than the coarse particle, which settle down faster as compared to summer seasons, when boundary layer is high and mixing is proper.

Acknowledgement

Author is thankful to the Director National Physical Laboratory, New Delhi, for his continuous help and support.

Reference

1.Hanel, G., 1976. The properties of atmospheric aerosol particles as a function of the relative humidity at thermodynamic equilibrium with the surrounding moist air. Adv. Geophys, 19, 73-188.

2.Angstrom, A., 1964. The parameters of atmospheric turbidity. Tellus 16, 64-75.

3.Byrne, M. Jennings, S. G., 1993. Scavenging of submicrometre aerosol particles by water drops. Atoms. Evniron. 27A, 142099-142133.

4.Flossmann, F. I., Hall, W. D. and Prupacher, H. R., 1985. Atherotical study of the wet removal of atmospheric pollutants: part I. The redistribution of aerosol particles Kagawa, J., 1984. Health effects of air pollutants and their management. Atmos. Environ. 29, 3465-3475.

5.Sanhueza, E., 2001. Hydrochloric acid from Chlorocarbons: a significant global source of background rain acidity. Tellus 53B, 122-132.

94

IASTA-2010

A–P–10

Variation of Aerosol Optical Properties over Delhi during Pre and Post-monsoon season

Kirti Soni, Sachchidanand Singh, Tarannum Bano, R. S.Tanwar, Shambhu Nath and B. C. Arya

Radio and Atmospheric Sciences Division, National Physical Laboratory, New Delhi, India

soniks@nplindia.org

Introduction

Atmospheric aerosols have been recognized as one of the important factors in determining global climate effects [IPCC 2001, 2007]. Aerosols particles suspended in the atmosphere influence the Earth’s climate in a direct as well as indirect manner. Atmospheric aerosols in high concentrations can affect our health by damaging the human respiratory system and at the same time reduces the visibility. Depending on the microphysical properties of these suspended particulates, it will involve in the energy transfer process by absorption and scattering of both solar radiation and emission from Earth’s surface. (Cheng et al., 2006). We present results on various physical and optical properties of aerosols measured over Delhi and discuss their variability’s in pre-monsoon and post-monsoon season. Aerosol parameters such as Aerosol optical depth (AOD), Absorption coefficient, Scattering Coefficient, Single scattering Albedo (SSA) and Angstrom parameters have been studied.

Observational site and Experimental Details

The observational site, National Physical Laboratory (NPL : 28.64N, 77.17E 235amsl) is situated in central part of the Delhi. Delhi has a semi- arid climate with extreme weather conditions. During peak summers, temperature rises even beyond 450C and in winter temperatures may fall to below 30C. In the pre-monsoon period (April – June), frequent dust storms from western and north - western desert regions cause large scale loading of aerosols over Delhi.

Regular measurements of aerosol optical depth, absorption coefficient and scattering coefficient have been made using Microtop II sunphotometer, (Model no. 4078(5) manufactured by Solar Light, Inc.) Aethalometer (AE-42, Magee Scientific) and Nephelometer (NGN-3A, OPTEC Inc, USA) respectively during year 2008.

Result and Discussion

Figure (1) represents variations in daily average absorption coefficient scattering coefficient and single scattering albedo (SSA) during pre-monsoon and post-monsoon seasons. At the middle visible wavelength (0.55 m), average SSA was 0.63±0.06 for pre- monsoon season and 0.74±0.03 during the post-monsoon season. However, large variations in average absorption and scattering coefficients were seen during these seasons. The average values were found to be 62.47 ± 21.27(pre-monsoon),

95

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

189.65 ± 85.94 (post- monsoon) Mm-1 for absorption and 110.46 ± 36.15(pre-monsoon), 565.59 ± 274.59 (post-

Figure 1. Daily average variation of Absorption Coefficient, Scattering Coefficient and Single Scattering Albedo (SSA) during year 2008 and 2009 in pre-monsoon and post-monsoon season

96

IASTA-2010

monsoon) Mm-1 for scattering coefficients respectively. This clearly indicates the dominance of scattering components during post-monsoon season. Water-soluble inorganic compounds such as sulphates, nitrates etc. and some organic carbon (OC) are mainly scatter radiation [Charlson et al., 1992, J.E. Penner 1995. On the other hand black carbon and dust particles have absorbing nature. The major sources of NO3- and SO4- in the atmosphere are emitted from different anthropogenic activities. Both NO3- and SO42- are mainly produced as secondary aerosols in the process of coal combustion, biomass burning and vehicular emissions [Seinfeld and Pandis, 1998, Rastogi and Sarin, 2005]. Figure (2) shows the average daily variation of AOD and Angstrom parameters during the post-monsoon and pre-monsoon seasons. Average value of a during the post-monsoon period of observation was found to be a >1, which is higher than pre-monsoon (a <1) season. Higher values of a>1 are observed during post-monsoon season, represents dominance of fine mode particles. This may be due to the increased activities related to biomass/biofuel burning. During the pre-monsoon a<1 values, indicates the presence of coarse mode particles because dust storms occur in April –May. The high values during post-monsoon compare to pre- monsoon indicates relatively turbid atmosphere.

Summary

Continuous measurements of Scattering coefficient, Absorption coefficient, Aerosol Optical Depth were carried out over Delhi, India, for the period of April 2008 to March 2009. The analysis of the results suggested that –

z Scattering coefficient, Absorption coefficient and SSA were higher in the post monsoon season than those in pre-monsoon.

zFine mode particles are dominating in the post –monsoon season and coarse mode particles in pre-monsoon .

zPre-monsoon optical properties over Delhi are attributed to transport of dust from desert.

Figure 2. Daily average variation of Aerosol optical depth at 500nm, Angstrom coefficient (Alpha), Angstrom turbidity coefficient (Beta) and water vapor during year 2008 and 2009 in pre-monsoon and post-monsoon season

97

AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

References

1.Cheng, A.Y.S., Chan M.H., Yang X., 2006: Study of aerosol optical thickness in Hong Kong, validation, results, and dependence on meteorological parameters. Atmospheric Environment, 40 4469-4477

2.Charlson, R.J., S.E. Schwartz, J.M. Hales, R.D. Cess, J.A. Coakley, Jr., J.E. Hansen, and D.J. Hoffman, 1992: Climate forcing by anthropogenic aerosols. Science, 255, 423-430

3.Penner et al., 1994. J.E. Penner, R.J. Charlson, J.M. Hales, N.S. Laulainen, R. Leifer, T. Novakov, J.A. Ogren, L.F. Radke, S.E. Schwartz and L. Travis, Quantifying and minimizing uncertainty of climate forcing by anthropogmie aerosols. Bull. Am. Meteorol. Soc. 75 (1994), pp. 375–400

4.Rastogi and Sarin. Aerosol and Air Quality Research, 2006Atmospheric Abundances of Nitrogen Species in Rain and Aerosols Over a Semi-arid Region: Sources and Deposition Fluxes Vol. 6, No. 4, pp. 406-417,

5.John H. Seinfeld and Spyros N. Pandis Atmospheric Chemistry and Physics, From : Air Pollution to Climate Change, John Wiley, New York, 1998, xxvii pp., ISBN 0-471-17815-2

98