Spatio-Temporal Variation and Deposition of Fine and Coarse Particles During the Commonwealth Games in Delhi

Spatio-Temporal Variation and Deposition of Fine and Coarse Particles during the Commonwealth Games in Delhi

Ali Kaushar, Dilip Chate*, Gufran Beig, Reka Srinivas, Neha Parkhi, Trupti Satpute, Saroj Sahu, Sachin Ghude, Santosh Kulkarni, Divya Surendran, Hanumant Trimbake, Dinesh Kumar Trivedi

Indian Institute of Tropical Meteorology, Pune - 411 008, India

ABSTRACT

The Indian Government implemented the project “System of Air quality Forecasting And Research (SAFAR)” for the “Commonwealth Games” 2010 in Delhi. It was adopted by the Global Urban Research Meteorology and Environment of World Meteorological Organization as its pilot project. We used data from a dense network of stations built over 2500 km2 in Delhi under the SAFAR project to investigate temporal and spatial variations of fine (PM2.5) and coarse (PM10–2.5) particles, and discuss their deposition and the airborne mass fractions that were retained after a certain amount of time. The 24-hour coarse particle (PM10–2.5) means during the Games period were always above the National Ambient Air Quality 3 3 Standard NAAQS (100 μg/m ) at all the sites except the airport. In still air, initial PM10–2.5 can reach below 50 μg/m by 3 deposition in an hour. The 24-hour PM2.5 means reveal that they were either around or below the NAAQS (60 μg/m ) at some sport complexes, whereas they fluctuated between 60 and 80 μg/m3 at the other sites.

Keywords: Air-quality; Aerosol deposition; PM2.5 and PM10–2.5; Pollutants source; Vehicular emissions; CWG-2010.

INTRODUCTION Delhi is the seventh most populous megacity in the world, where more than 100,000 petrol and diesel consuming Adequate understanding of spatio-temporal variability of vehicles add annually to the roads (Department of Transport, particulate matters (coarse and fine particles) and their sink Delhi, 2007). After the Summer Olympic Games-2008 in mechanisms is needed to know their impact in health hazards Beijing, China (Wang et al., 2010), the Commonwealth and climate change (Colbeck et al., 2011, Tsai et al., 2011, Games (CWG-2010) was one of the biggest recent sports Gugamsetty et al., 2012). Gugamsetty et al. (2012) have event in Delhi, India. During the CWG-2010, many studied source apportionment of the particulate matters at international athletes joined the sports events and the air Shinjung station in New Taipei City, Taiwan. Based on the quality was a major concern to which several efforts were chemical information, they identified five source types viz., taken up by the Indian Government and researchers. The soil dust, vehicle emissions, sea salt, industrial emissions regulatory authorities of the government took strict actions and secondary aerosols. Tsai et al. (2011) have studied for the reduction of emissions of air pollutants from industry, physicochemical properties of particulate matters at Inland road traffic, and construction sites. New compressed Natural and Offshore sites over South-eastern Coastal Region of Gas (CNG) buses and radio taxis were fleeted in Delhi. Taiwan Strait. They have found that the most abundant ionic Heavy vehicles were banned from entering Delhi, and 2– – + species of PM were SO4 , NO3 , and NH4 and the most separate lanes were dedicated for the athletes to cut down common chemical compounds were ammonium sulfate on vehicular emissions along those corridors. New metro lines ((NH4)2SO4) and ammonium nitrate (NH4NO3). On the were introduced for travellers of sports complexes. Coal other hand, in Lahore, Pakistan, Colbeck et al. (2011) have based power plants were closed down and additional natural shown that coarse (PM10–2.5) and fine (PM2.5) particles was gas was consumed at the power plants. With the timely significantly high on road side mainly due to re-suspension implementation of aforementioned norms, the Delhi’s air of dust and from automobile exhausts. quality could be improved during the Games period. These measures for clean air during the Games provide a rare opportunity for assessment of the impact of pollution emissions on the air quality of the National Capital Region * Corresponding author. Tel.: 00912025904257; (NCR) of Delhi. The current levels of air pollutants and Fax: 00912025865142 predicting air quality well in advance is required for knowing E-mail address: [email protected] the immediate health hazard in any city. A sustainable

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program of air quality monitoring and forecasting system, PM2.5 and PM10–2.5 mass concentration during CWG-2010 the network of Air Quality Monitoring Stations (AQMS) with from the study area under SAFAR and to analyze links Automatic Weather Station (AWS) under ''SYSTEM OF AIR between these particles and wind, temperature and relative QUALITY FORECASTING AND RESEARCH'' (SAFAR), humidity in Delhi. With deposition velocities of fine and was built exclusively for CWG-2010 covering Delhi-NCR coarse particles, airborne mass fractions of these particles (http://safar.tropmet.res.in/). For air quality forecasting, a high retained after the elapse time are projected at breathing resolution (1.67 km × 1.67 km) emission inventory of major height as a case study. air pollutants was developed for a domain of ~70 km × 65 km (~4500 km2) covering Delhi and its surrounding regions Study Area (Sahu et al., 2011). Also, the breakpoints classification (as The study area is AQMS and AWS network of SAFAR the best estimations under the given constraints) has been in Delhi-NCR (Commonwealth Games, CWG-2010) developed for different pollutants by Beig and Ghude, comprising of sports complexes, airport and residential (2010) for reporting the Air Quality Index (AQI) of Delhi sites as shown in Fig. 1. It may be noted in the figure that during CWG-2010 (http://safar.tropmet.res.in/). Altogether, IITM, Delhi (1) is residential area, Palam-IGI (9) is airport the system has displayed both observed and forecasted levels site and Yamuna Sports Complex (YSC) (2), Indira Gandhi (24 hours in advance) of air quality at various key locations Sports Complex, IGSC (3), Major Dhyan Chand National of Delhi on wireless LCD and LED display boards in terms Stadium, MDNS (4), Thyagaraj Sports Complex (6), of the AQI during CWG-2010. Further analysis of PM2.5 Common Wealth Game Village, CWGV (7), University of and PM10 data and influence of wind speed, temperature and Delhi, DU (educational cum sports site) (8) and Talkatora relative humidity on variations in fine and coarse particles is Garden, NDMC (10) are sports complexes; hereafter they presented in this paper. will be referred as (1), (2), (3), (4), (6), (7), (8), (9) and (10). The difference between integrated mass of aerosols up to aerodynamic diameter 10 μm (PM10) and up to 2.5 μm (PM2.5) MEASUREMENT TECHNIQUE AND DATA represents coarse fraction (PM10–2.5). Statistical analysis of ANALYSIS air pollution data for coarse (PM10–2.5) and fine (PM2.5) particles and meteorological parameters across a network The present study is based on measurements of the of AQMS and AWS under SAFAR during Games period concentration of atmospheric aerosols with cutoff (CWG-2010) can serve a long term strategic vision for aerodynamic diameters up to 10 μm (PM10) and 2.5 μm improvement of air quality in Delhi. With the purpose, the (PM2.5); and meteorological parameters like wind speed, objectives of the present study are to project time series of air temperature and relative humidity.

Fig. 1. Area shows Network setup under SAFAR for atmospheric measurements.

750 Kaushar et al., Aerosol and Air Quality Research, 13: 748–755, 2013

PM10 and PM2.5 were continuously monitored using Beta Microcomm-ESD, UK). The temperature sensor used has Attenuation Monitor (BAM-1020; Met One Instruments, Inc, resolution of 1°F with accuracy ± 1°F. Relative humidity USA) which uses the industry-proven principle of beta ray (RH) sensor used with this system has accuracy ± 3%. The attenuation. The measurement principle involves emission, wind sensor measures wind speed in the range 0–56 m/s by a small 14C (carbon-14) element, of a constant source with an accuracy of ± 0.45 m/s and resolution better than of high-energy electrons known as beta rays through a spot 0.045 m/s. Data from all the measurement sites in and around of clean glass fiber filter tape. These beta rays are detected Delhi city were stored in computerized data acquisition and counted by a sensitive scintillation counter to determine system located at a centralized hub (IITM, Delhi). a zero reading. The BAM-1020 automatically advances this spot of tape to the sample nozzle, where a vacuum pump RESULTS then pulls a measured and controlled amount of dust-laden air through the filter tape loading it with ambient dust. This Time Series of PM10–2.5 and PM2.5 during Commonwealth dirty spot is placed back between the beta source and the Game Period detector thereby causing an attenuation of the beta ray Daily average values of PM10–2.5 and PM2.5 mass signal which is used to determine the mass of the particulate concentrations based on their observations in the Delhi-NCR matter on the filter tape and the volumetric concentration region during 23 September–24 October, 2010 are presented of particulate matter in the ambient air. The instrument in Fig. 2. The above period includes Commonwealth Games measures concentration of ambient aerosols with a resolution period (3–14 October 2010; from day number 276 to 287 in of 0.1 μg/m3 and lower detection limit of around 1 μg/m3. the figure) also. The particulate data for the locations 2 and 3 Span check of the instrument is automatic and is verified were not available for the periods except that for the CWG- hourly (Kindly see BAM-1020 Operation Manual for more 10 period and so these two plots contain daily average details). concentrations only for the CWG-10 period. It may be seen Wind speed, air temperature and relative humidity were in the figure that the mean coarse particles (PM10–2.5) mass measured using an AWS system (Model, ME-1310; concentrations was higher than fine (PM2.5) particles on

PM2.5 PM10-2.5 300 IITM Delhi 1 YSC 2 IGSC 3 250 200

150 100 50

) 0 3 300

g/m MDNS 4 Tyagraj 6 CWGV 7

 250 200

150 100 50 0

300 Concentration ( DU 8 Airport 9 NDMC10 250 200

150 100 50 0 2 0 8 6 2 0 8 6 2 0 8 6 27 28 28 29 27 28 28 29 27 28 28 29

Day number of a year Fig. 2. Daily average concentration of aerosols during 23 September–24 October 2010 at different locations in Delhi. Note: The above period includes the Commonwealth Games period (3–14 October 2010; from day number 276 to 287) at Delhi.

Kaushar et al., Aerosol and Air Quality Research, 13: 748–755, 2013 751 opening day of CWG-2010 (3rd October) over the locations season. During the period after the Games, coarse particles (2), (3), (4), (6), (7), (8) and during 8/9th to 14th October, show nearly same concentration as during the CWG but 2010 (i.e., during day number 281/282 to 287) over the the fine particles show escalated concentration level after locations (2), (3), (4), (6), (7), (8) and (10). The mass of the Games. The average concentration of the fine particles coarse particles showed always higher concentration than before the CWG, during the CWG and after the CWG is that of fine particles at location (4). This result is attributed ~85, 113 and 117 μg/m3. It means that the fine particulates to vehicle-driven roadside dust and wind-blown dust which concentration had increased by 4 μg/m3 immediately after mostly remains in the lower layer of the atmosphere. On the CWG. This increase is attributed mainly to vehicular the other hand, at location (9), mass of fine particles showed and industrial emissions. Tiwari et al. (2012) have reported always higher values. This is mainly because of the emission that, during the period from day number 276 to 287 of the of pollutants from the airplanes and light vehicles and less year 2007, the minimum and the maximum concentration of 3 suspension of soil dust due to less heavy vehicles activity PM2.5 in Delhi were ~100 and ~300 μg/m and of PM10–2.5 in this outer area of Delhi as the location (9) is an airport were 125 and 200 μg/m3 respectively. On the other hand location much away from the main city. Another important the present minimum and maximum concentration of PM2.5 3 feature seen in the figure is the occurrence of higher on average were ~62 and 178 μg/m and of PM10–2.5 were 3 concentration of PM2.5 than PM10–2.5 during 3–9 October ~31 and ~77 μg/m respectively. There are a few other (i.e., during day number 276–282) at locations 1 and 10. publications which also show that the fine and the coarse The reason lies in the fact that both these locations are particulates concentrations in Delhi are much larger than situated in the areas where soil oriented dust suspension in those reported during the Commonwealth Games period the boundary layer is normally less than those at many other (Tiwari et al., 2009; Perrino et al., 2011; Tiwari et al., locations due to the areas mostly being covered by concrete, 2012). The above comparison and the other scientific works tar or plants. Location 1 is a forest cover area where plants on the subject confirm that the control measures taken by may reduce coarse particles suspension by intercepting them. the Government of India to reduce the emission during the Thus emission of fine particles and gases from the vehicles Commonwealth Games period were effective. and conversion of these gases to particles by gas-to-particle conversion mechanism may be the main reason for more Influence of Meteorological Parameters on PM10–2.5 and concentration of PM2.5 than PM10–2.5 at these locations. PM2.5 National Ambient Air Quality (NAAQ) Standards using Fig. 3 presents relationship of ambient aerosols (PM10–2.5 Beta attenuation system for continuous monitoring of PM2.5 and PM2.5) with wind speed, temperature and relative 3 3 and PM10 are set to 60 μg/m and 100 μg/m for 24-hour humidity based on their regression analysis. It may be noted average respectively (http://cpcb.nic.in/National_Ambient_ here that while regressing the fine and the coarse particles Air_Quality_Standards.php). It is seen in Fig. 2 that daily concentration on wind speed, temperature and relative average of PM2.5 concentration were around or even below humidity we have considered spatial average values of these their NAAQ standard (60 μg/m3) during 10th to 12th October, parameters (averaged over 9 data sets of AQMS and AWS 2010 (i.e., during day number 283 to 285), at nearly all the in the Delhi-NCR during games period). This is because of locations except at (8) and (9) where the concentration the uniformity in the prevailing weather condition over the remained nearly always higher than NAAQ standard. High whole region of Delhi-NCR during October. emissions of fine particles from the transport sector nearby It is well documented that the region of Delhi-NCR is Delhi University (8) and airport premises (9) could be located far inland off the major water reservoirs like the responsible for levels of fine particles above their NAAQ Bay of Bengal and the Arabian Sea. After monsoon season standard. It is found that, on spatial average, the PM2.5 (June–September), the general weather in Delhi is concentration was below NAAQ standard on ~9% occasions characterized by hot days with low humidity and cool and at or below 80 μg/m3 on about 27% occasions during nights with appreciable humidity. The condition favors CWG-10. It is location 4 where, on spatial average, lowering of inversion layer during this month. The climate frequency of occurrence of less concentration than NAAQ of this area clearly shows the influence of its inland standard is maximum (~5%). The coarse particles (PM10–2.5) position and the air over this region is mostly dry. Winds concentration crossed their NAAQ standard (100 μg/m3) during October are generally light and predominantly from during Games period for all locations except for airport site westerly/northwesterly direction and tend to northerly in (9). At airport site, the PM10–2.5 concentration remained below the afternoon (India Meteorological Department (IMD), NAAQ standard for most of the time. The concentrations at 1991). Thus there is little chance of spatial variation in the locations 1 and 10 moved around the NAAQ standard (i.e., values of meteorological parameters in the Delhi region. The around 100 μg/m3). But at remaining locations, except at only weather phenomena which influences this persisting location 9, the concentration of coarse particles remained weather condition and causing rainfall in the region during much higher for most of the observational period. October is the Western Disturbances (WD). But this also A remarkable point noticed in the figure is that particulate covers the whole region of Delhi and the meteorological concentration during the period (from day number 266 to condition over the Delhi region during October again 275) before the Commonwealth Games is a little less than remains uniform. Though not shown for brevity, the present that during the Games period. This is due to washout of the weather data also verifies existence of uniform scenario of particulate matters by continuous rain of the monsoon the weather parameters in this region.

752 Kaushar et al., Aerosol and Air Quality Research, 13: 748–755, 2013

180 180 180 R = 0.24, N = 12, P = 0.46 R = - 0.24, N = 12, P = 0.45 R = 0.01, N = 12, P = 0.95 Result not significant Result not significant Result not significant 170 170 170 ) 3 160 160 160 g/m

 150 150 150 (

140 140 140 10-2.5 130

PM 130 130

120 120 120

110 110 110 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 26.4 26.7 27.0 27.3 27.6 27.9 28.2 50 55 60 65 70

220 220 220 R = -0.82, N = 12, P = 0.1 R = 0.43, N = 12, P = 0.17 R = 0.92, N = 12, P = 1.79159E-5 3 3 200  PM (g/m ) = 33.4 WS (m/sec) - 791.6 200 PM (g/m ) = 6.8 RH (%) - 293.8 PM2.5 (g = - 57.7 WS(m/sec) + 148.7 200 2.5 2.5 180 180 180

160 160 160 ) 3 140 140 140 g/m

 120 120 120 (

2.5 100 100 100

PM 80 80 80

60 60 60

40 40 40 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 26.4 26.7 27.0 27.3 27.6 27.9 28.2 50 55 60 65 70 o Wind speed (m/sec) Temperature ( C) Relative humidty (%)

Fig. 3. Relationship of PM10–2.5 and PM2.5 with meteorological parameters during Commonwealth Games (3–14 October 2012) at Delhi.

The PM10–2.5 shows statistically insignificant correlation important factor impacting on this mechanism. The important with wind speed (r = 0.24), temperature (r = –0.24) and factors for the occurrence of fine particles in the surface relative humidity (r = 0.1) at 5% level of significance. layer of Delhi region has been lowering of inversion layer Although insignificant, but positive relationship of the and particles left behind after the dispersion of fog. This coarse aerosols with wind speed implies that these aerosols interpretation comes from highly significant relationship of drifted very slowly in the average winds recorded over the the fine aerosols with the relative humidity. Actually, region, but they decreased with the increase in ambient lowering of inversion layer which normally occurs during temperature. No any concrete conclusion can be drawn based this month causes trapping of the fine particles emitted on these relationships as they are statistically insignificant. directly from anthropogenic activities or formed by gas-to- As indicated in Fig. 3, PM2.5 particles show highly particle conversion mechanism. These particles act as cloud significant negative relationship with wind speed with condensation nuclei (CCN) in the boundary layer of the correlation coefficient of –0.85 (statistically significant at atmosphere causing fog formation over the region. When 0.1%). This result is attributed to the fact that when there is sun rises, fog is dispersed leaving the fine mode particles low wind fine particles tend to remain over the region of suspended in the lower layer of the atmosphere. origin and when there is high wind they are drifted vertically as well as horizontally through turbulent transfer Deposition Velocity and Dry Deposition Flux of Aerosol mechanism causing reduction in their concentration in the Particles surface layer of the atmosphere. On the other hand, PM2.5 In still air, gravitational forces on large particles govern shows positive relationship with air temperature (r = 0.43, the air quality by virtue of their significant dry depositions result not significant at 5%) and relative humidity (r = to the surface in absence of rain. We prefer to discuss dry 0.92, significant at better than 0.1%). Insignificant but fair deposition of PM10–2.5 and PM2.5 particles considering terminal positive relationship of PM2.5 with temperature can be fall rates and relaxation times during their downward motion interpreted as, though higher temperature has favored gas- in still air, as no data of three components of winds with to-particle conversion mechanism, this has not been the high resolution (0.05 to 0.1 s) are available during games

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period. Depending on their size and mass, particles in the velocity (vs) as high as ~0.003 m/s over land surface. atmosphere are affected to different degrees by gravitational Deposition velocity for particles in the size range 0.1–2.5 forces. In the absence of significant convection, particles μm (PM2.5) is in the order of 0.0001 m/s. Over land surface (particularly large particles) move toward the surface of the in Delhi, deposition velocity of fine particles (PM2.5) is earth by gravity. The terminal rate of fall of heavy particles assumed to be 0.0001 m/s (Nicholson, 1988) and for coarse (> 2 μm) in still air, due to gravity (Seinfeld and Pandis, ones (PM10–2.5) it is 0.0015 m/s (average vs over the particle 2006) is sizes from 2.5 to 10 μm) to estimate deposition fluxes and airborne mass after elapse of time at breathing height vs = g (1) (Cotton and Levin, 2009). We have considered the case of observed aerosol mass where g is the acceleration due to gravity and  is a relaxation concentration at the sports complex sites YSC (2) and time for a moving particle in air. IGSC (3) for the estimation of deposition flux of the aerosol For particles which follow Stokes law of resistance, masses. The wind speeds at these sites are below the detection limit of the AWS sensors. For typical initial mass 2 D  concentrations of fine and coarse particles at the observational   pp (2) 18 sites (2) and (3), deposition fluxes are plotted in Fig. 4. The deposition fluxes for coarse particles are as high as ten times 2 where, ρp is the density of the particle, Dp is the diameter (~0.25 μg/m /s) over to those for fine particles (< 0.025 of particle and η is the viscosity of air. Particles of size μg/m2/s) at both the sites (2) and (3). Gravitational forces larger than 2 μm (PM10–2.5) tend to have a deposition are opposed by a frictional force that is a function of air

0.4 Running 24h deposition fluxes of PM and PM means, 3-14 October, 2010 PM 2.5 10-2.5 10-2.5 YSC (CWG-2010) PM 0.35 2.5

0.3

0.25 ) -1 s -2 0.2 g m  ( 0.15

0.1

0.05

0 276 277 278 279 280 281 282 283 284 285 286 287 Day of year

Running 24h deposition fluxes of PM and PM means, 3-14 October, 2010 PM 2.5 10-2.5 10-2.5 IGSC (CWG-2010) PM 2.5 0.25

0.2 ) -1 s -2 0.15 g m  ( 0.1

0.05

0 276 277 278 279 280 281 282 283 284 285 286 287 Day of year Fig. 4. Deposition fluxes for typical initial mass concentrations of coarse particles at sites (2) and (3).

754 Kaushar et al., Aerosol and Air Quality Research, 13: 748–755, 2013 viscosity, particle velocity and particle diameter. As a result, using Eq. (3) at height h after time t has elapsed with the larger particles settle more quickly than smaller ones. As assumed terminal fall rates for these particles. The mass particle size decreases, the effect of gravity is reduced and concentrations of fine and coarse particles remaining airborne fine particles settle out slowly. In still air, dry deposition at breathing height h (2 m) after one hour are shown in Fig. processes can be responsible for rapid depletion of coarser 5. It is worth to note that mass concentrations of fine particles particles in absence of their emissions sources nearby the deplete in small amount and mostly they (accumulated size measurement sites. range particles) remain airborne after one hour, whereas Under the stable atmospheric conditions, the mass coarser particles settle gravitationally to the surface in concentration (m) of aerosols remaining airborne from the large amount after elapsed time of one hour (Fig. 5). The initial mass concentration m0, at height h after time t can be airborne mass concentrations of PM10–2.5 and PM2.5 as seen expressed as non-dimensional exponential function of vs, in Fig. 5 hold for conditions of still air and no major elapsed time (t) and breathing height (h), pollutant sources nearby to measurement sites. The depleted mass concentrations of fine and coarse particles shown in vts the figure can replenish within no time in case of continuous mm0 exp (3) h supply of these aerosols from emissions through various natural and anthropogenic sources or advection of these Airborne mass concentration of fine (PM2.5) and coarse particles via strong airflows in downwind in the source- (PM10–2.5) aerosols from their typical initial average mass receptor system. The levels of PM10–2.5 and PM2.5 presented concentrations at site IGSC (3) in Delhi are computed in this work may not be raised from a single sector.

250 Running 24h airborne PM means, 3-14 October, 2010 IGSC (CWG-2010) 2.5

PM (Initial) 2.5 200 PM (1 hour) 2.5

) 150 -3 g m 

PM ( 100

0 276 277 278 279 280 281 282 283 284 285 286 287 Day of year 200 Running 24h airborne PM means, 3-14 October, 2010, IGSC (CWG-2010) 10-2.5 PM (Initial) 180 10-2.5 PM (1 hour) 160 10-2.5

140

) 120 -3 g m

 100

PM ( 80

0 276 277 278 279 280 281 282 283 284 285 286 287 Day of year Fig. 5. The mass concentrations of fine and coarse particles remaining airborne at breathing height h (2 m) after one hour.

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CONCLUSION Aerosol Air Qual. Res. 12: 476–491. India Meteorological Department (IMD) (1991). Climate of The measurements of coarse and fine particles across the Haryana and Union Territories of Delhi and Chandigarh, nine monitoring sites under SAFAR program clearly Controller of Publication, Delhi. demonstrate the impact of local sources, meteorology and Levin, Z. and Cotton, W.R. (2009). Aerosol Pollution Impact deposition processes on the time series variations of PM10–2.5 on Precipitation: A Scientific Review, Dordrecht, Springer, and PM2.5 during the CWG-2010 in Delhi. During the London. Commonwealth Games, because of the pollution control Nicholson, K.W. (1988). The Dry Deposition of Small policies implemented in and around the city of Delhi, the Particles: A Review of Experimental Measurements. level of coarse (PM10–2.5) and fine (PM2.5) particles plunged Atmos. Environ. 22: 2653–2666. to those close by or even below their NAAQ standards. Perrino, C., Tiwari, S., Catrambone, M., Torre, S.D., Rantica, The pollution reduction measures for the Delhi’s CWG- E. and Canepari, S. (2011). Chemical Characterization 2010 (well before the Games) and washout of air pollutants of Atmospheric PM in Delhi, India, during Different by monsoonal rain till end of the September, 2010 were Periods of the Year Including Diwali Festival. Atmos. effective in reducing atmospheric concentrations of both Pollut. Res. 2: 418–427. coarser and fine particles. Much improved air quality on Sahu, S.K., Beig, G. and Parkhi, N.S. (2011). Emissions most of the days especially along the dedicated lanes Inventory of Anthropogenic PM2.5 and PM10 in Delhi during the CWG-2010 also had apparent relationship with during Common Wealth Games-2010. Atmos. Environ. weather changes (monsoon to post-monsoon transition period 45: 6180–6190. for CWG-2010). Further air pollution modeling studies using Seinfeld, J.H. and Pandis, S.N. (2006). Atmospheric SAFAR network data on important trace gases and aerosol Chemistry and Physics, John Wiley and Sons, Inc., New pollutants are needed to quantify the relative role of the York. emission reduction initiatives and weather changes and the Srivastava, A., Joseph, A.E., Patil, S., More, A., Dixit, R.C. contribution of local versus regional sources to the air and Prakash, M. (2005). Air Toxics in Ambient Air of quality changes in Delhi-NCR. Delhi. Atmos. Environ. 39:59–71. Tiwari, S., Chate, D.M, Srivastava, M.K., Safai, P.D., ACKNOWLEDGEMENT Srivastava, A.K., Bisht, D.S. and Padmanabhamurty, B. (2012). Statistical Evaluation of PM10 and Distribution of Indian Institute of Tropical Meteorology (IITM), Pune is PM1, PM2.5, and PM10 in Ambient Air Due to Extreme supported by the Ministry of Earth Sciences (MoES), Fireworks Episodes (Deepawali Festivals) in Megacity Government of India, New Delhi. Authors sincerely Delhi. Nat. Hazards 61: 521–531. acknowledge the whole hearted support of Prof. B.N. Tiwari, S., Srivastava, A.K., Bisht, D.S., Bano, T., Singh, Goswami, Director IITM, Pune. Authors appreciate the S., Behura, S., Srivastava, M.K., Chate, D.M. and efforts of entire team involved in SAFAR project under the Padmanabhamurty, B. (2009). Black Carbon and Chemical MoES. Characteristics of PM10 and PM2.5 at an Urban Site of North India. J. Atmos. Chem. 62:193–209. REFERENCES Tiwari, S., Chate, D.M., Pragya, P., Ali, K. and Bisht, D.S. (2012). Variations in mass of the PM10, PM2.5 and PM1 Beig, G. and Ghude, S.D. (2010). Scientific Evolution of during the monsoon and the winter at New Delhi. Aerosol Air Quality Standards and Defining Air Quality Index Air Qual. Res. 12: 20–29. for India, Special Scientific Report SAFAR-2010-B, Tsai, H.H., Yuan, C.S., Hung, C.H. and Lin, C. (2011). http://safar. tropmet.res.in/. Physicochemical Properties of PM2.5 and PM2.5–10 at Colbeck, I., Nasir, Z.A., Ahmad, S. and Ali, Z. (2011). Inland and Offshore Sites over Southeastern Coastal Exposure to PM10, PM2.5, PM1 and Carbon Monoxide on Region of Taiwan Strait. Aerosol Air Qual. Res. 11: Roads in Lahore, Pakistan. Aerosol Air Qual. Res. 11: 664–678. 689–695. Wang, T., Nie, W., Gao, J., Xue, L. K., Gao, X. M., Wang, CPCB, New Delhi, India (2007). Annual Report: 2006- X.F., Qiu, J., Poon, C.N., Meinardi, S., Blake, D., Wang, 2007. http://www.cpcp.nic.in/National_Am bient_Air_ S.L., Ding, A.J., Chai, F.H., Zhang, Q.Z. and Wang, W.X. Quality_Satndards.php. (2010). Air Quality during the 2008 Beijing Olympics: DTC, Department of Transport, Delhi Government of Secondary Pollutants and Regional Impact. Atmos. Chem. Delhi (2007). http://transport.delhigovt.nic.in/transport/ Phys. 10: 7603–7615. /tr0g.htm, 3/23/2007. Gugamsetty, B., Wei, H., Liu, C.N., Awasthi, A., Hsu, S.C., Tsai, C.J., Roam, G.D., Wu, Y.C. and Chen C.F. (2012). Received for review, February 23, 2012 Source Characterization and Apportionment of PM10, Accepted, August 20, 2012 PM2.5 and PM0.1 by Using Positive Matrix Factorization.