- Email: [email protected]
Trends in aerosol optical depth for cities in India
ARTICLE IN PRESS
Atmospheric Environment 41 (2007) 7524–7532 www.elsevier.com/locate/atmosenv
Trends in aerosol optical depth for cities in India William Porcha,, Petr Chyleka, Mavendra Dubeya, Steven Massieb a
Los Alamos National Laboratory, MS-J577, Los Alamos, NM 87545, USA b National Center for Atmospheric Research, Boulder, CO, USA
Received 19 January 2007; received in revised form 28 March 2007; accepted 21 May 2007
Abstract Recent analysis of trends in global short-wave radiation measured with pyranometers in major cities in India support a decrease in solar radiation in many of those cities since 1990. Since direct and diffuse radiation measurements include cloud effects, spring and summer dust and the variable summer monsoon rains, we concentrate in this paper on wintertime (November–February) aerosol optical depth measurements. The aerosol optical depth is derived from cloud-free turbidity measurements beginning in the 1960s and more recent sun photometer direct aerosol optical depth measurements. We compare the sun photometer derived trends with the pyranometer-derived trends using a radiative transfer model. These results are then compared to total ozone mapping spectrometer (TOMS) satellite-derived regional aerosol optical depths from 1980 to 2000. The results show that inclusion of the earlier turbidity measurements helps to establish an increasing regional turbidity trend. However, most of the increasing trend is confined to the larger cities in the Ganges River Basin of India (mainly Calcutta and New Delhi) with other cities showing a much less increase. Regional satellite data show that there is an increasing trend in aerosol off the coast of India and over the Ganges River Basin. The increase over the Ganges River Basin is consistent with population trends over the region during 1980–2000. r 2007 Elsevier Ltd. All rights reserved. Keywords: Atmospheric aerosols; Climate; Trends; Global dimming; Radiation transfer
1. Introduction Recent studies related to ‘‘global dimming’’ (e.g. Stanhill and Cohen, 2001) have increased interest in atmospheric aerosol trends. Because of the relatively short residence time of most atmospheric aerosols (3–7 days), trends are much more difficult to establish than for atmospheric gases such as CO2. Dutton et al. (2006) have shown that little or no trend in aerosol is apparent in background aerosol (Porch et al., 1970) measured at the same stations Corresponding author.
E-mail address: [email protected] (W. Porch). 1352-2310/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2007.05.055
that confirm an increasing trend in CO2. Schwartz (2005) has also used astronomical extinction measurements in Chile to show no appreciable trends except those that are related to volcanic eruptions. This is consistent with an earlier assessment of aerosol trends by Ellsaesser (1975). A recent paper by Mishchenko et al. (2007) has shown that there appears to be a decreasing trend in aerosol since about 1995 from AVHRR satellite data over the oceans from the Global Aerosol Climatology Project. Lack of evidence of an increasing global trend in aerosol does not imply that there are no regional trends in aerosol. Ramanathan et al. (2005) reported an extensive study of regional trends in
ARTICLE IN PRESS W. Porch et al. / Atmospheric Environment 41 (2007) 7524–7532
India including decreasing trends in measured and predicted solar radiation. The measurements come from the Global Energy Balance Archive (GEBA) (Gilgen and Ohmura, 1999). We examine these trends in India in more detail in this paper. Because decreasing solar radiation can be affected by increasing clouds as well as aerosol, we focus in this paper on sun photometer measurements of turbidity and aerosol optical depth (AOD). We also focus on the winter months (November–February) to lessen the effect of spring and summer dust and the variable monsoon. These observations are used with a radiation transfer model (Dave`, 1972) to attempt to isolate the aerosol trends from solar radiation trends. These results are then compared with AOD trends from total ozone mapping spectrometer (TOMS) satellite data (Massie et al., 2004). 2. Early turbidity observations Analyses of trends always depend strongly on the time range of the data set. Mani et al. (1973) and Ganesan (1973) describe turbidity observations that begin in 1958 at Poona and New Delhi and are supplemented in 1967–1969 at nine other sites in major cities (Table 1). These cities fortunately overlap with most of the cities in the GEBA data set. Both these papers document a strong upward trend in turbidity up to 1969. Turbidity b is related to AOD at 0.5 mm through the formula AODð0:5 mmÞ ¼ b la ¼ b 2:46,
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where l is the wavelength of the light (0.5 mm) and a is the wavelength exponent (in these studies 1.3 was used). This implies an increase in AOD (0.5 mm) from 0.09 in 1957 to a peak value in New Delhi of AOD (0.5 mm) of about 0.25 in 1969. This is less than the values observed today of about 0.4 (as will be shown later). The increase at Poona was from 0.05 in 1958 to about 0.2 in 1969. These are annual average comparisons. In the comparisons that follow we will focus on winter averages (November– February). 3. Comparisons with GEBA data The GEBA database contains pyranometer measurements of global (direct and diffuse) solar radiation for 11 cities in India from 1957 to 1990. Solar radiation fluxes from these cities range from 150 to 250 W m2 averaged over the winter months. Figs. 1–3 show the estimated winter period trends in AOD (0.5 mm) from the GEBA network along with the turbidity derived values from the early network. The locations of these cities on a map of India are shown in Fig. 5. Also shown in these figures are the AOD (0.5 mm) winter period values derived from the AERONET sun photometer network from 1999 to 2005 and winter period data derived from the TOMS satellite from 1980 to 2000 (described in Section 4). Since clouds affect the solar radiation observed in the GEBA data, the effect of clouds must be
Table 1 City locations used in this study Station ID
GEBA
31 grid for satellite analysis
City name
Longitude (East)
Latitude (North)
Altitude (m)
Longitude (1E)
Latitude (1N)
AHM CAL GOA JDP MDS NGP DLH PNA SHO TRV VSK
Ahmadabad Calcutta Goa Jodhpur Madras Nagpur New Delhi Poona Shillong Trivandrum Vishakhapatnam
721380 881200 731490 73110 801110 79130 771120 731510 911530 761570 831140
23140 221320 151290 261180 13100 21160 281350 181320 251340 81290 171430
55 4 55 217 10 308 212 555 1600 60 41
71–74 87–90 72–75 72–75 79–82 78–81 76–79 72–75 90–93 75–78 82–85
21–24 21–24 14–17 25–28 12–15 20–23 27–30 17–20 24–27 7–10 16–19
MALE GOA KAN
AERONET Male Goa Kanpur
731320 731490 801210
41120 151290 261270
2 55 142
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PNAw GOAw
0.6
India West Coast Trends
w = winter average
TRVw
GOAw
AHMw PNAwTOMS
0.5
GOAwTOMS TRVwTOMS
AOD 500 nm
0.4
AHMwTOMS
MALEw
0.3 MALEw MALEw
0.2 TRV
0.1
BHVw AHMw PNAw
GOAw
0 1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Year
Fig. 1. Trends in aerosol optical depth at 0.5 mm (AOD) from turbidity measurements in 1968, AERONET sun-photometer data after 2000 (Male and Goa), and interpreted from global radiation trends from the GEBA stations up to 1990 for west coast cities during winter (November–February).
w = winter average
India East Coast Trends 0.6
0.5
AOD 500 nm
0.4
0.3 CALw
VSKw
0.2
CALw MDSw
VSKw MDSw
0.1
VSKwTOMS CALwTOMS MDSwTOMS
0 1960
1965
1970
1975
1980
1985 Year
1990
1995
2000
2005
2010
Fig. 2. Trends in aerosol optical depth at 0.5 mm (AOD) from turbidity measurements in 1968 and interpreted from global radiation trends from the GEBA stations up to 1990 for east coast cities during winter (November–February).
ARTICLE IN PRESS W. Porch et al. / Atmospheric Environment 41 (2007) 7524–7532
0.9 0.8
AOD 500 nm
0.7 0.6
w = winter average
India Central Trends
1
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DLHw NGPw JDPw SHOw DLHwTOMS NGPwTOMS
KANw
JDPwTOMS SHOwTOMS
0.5 0.4 0.3 0.2 JDPw
0.1
DLHw NGPw SHOw
0 1950
1960
1970
1980
1990
2000
2010
Year
Fig. 3. Trends in aerosol optical depth at 0.5 mm (AOD) from turbidity measurements in 1968, AERONET sun-photometer data after 2000 (for Kanpur) and interpreted from global radiation trends from the GEBA stations up to 1990 for central cities during winter (November–February). Total Flux @500nm W/m2
Model Results Surface Global Solar Fluxes
900
Tropical Clean - 578 Tau 0.15 - 476 Tau 0.4 - 436
Tropical(Clean)
800
Tau@500nm 0.15
700
Tau@500nm 0.4
W/m**2/um
600 500 400 300 200 100 VSK 0 0
0.5
1
1.5
2
2.5
3
wavelength (um)
Fig. 4. Model results used to estimate cloud ratio at each site and estimate aerosol optical depth at 0.5 mm from GEBA global radiation measurements and trends. The upper curve assumes no clouds and uses the AFCRL Tropics model for the vertical distribution of aerosol, water vapor and ozone. A zenith angle of 601 and a surface albedo of 0.1 are also assumed. The aerosol is assumed to have real and imaginary indexes of refraction of 1.5 and 0.1, respectively. A lognormal distribution is assumed with rm of 0.1 mm and s of 0.69. The concentration of aerosol in the first 2 km above the surface is varied to produce an aerosol optical depth at 0.5 mm of 0.15 and 0.4.
separated from the observed diffuse and direct solar radiation trends by comparing calculated cloud-free and observed values using a radiation transfer code
(Dave`, 1972). This code includes molecular scattering, aerosol multiple scattering as well as molecular absorption from ozone and water vapor, and covers
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wavelengths from 0.415 to 2.45 mm. The cloud-free solar radiation is estimated using the AFCRL Tropics model atmosphere (McClatchey et al., 1978) and an assumed AOD (0.5 mm) of about 0.15 based on the results from the turbidity network in 1968 in Figs. 1–3. Fig. 4 shows the results of the radiation transfer model calculations of the global solar radiation flux. These results assume a clean tropical cloud-free model and aerosols distributed in the first 2 km above the surface resulting in a calculated AOD (0.5 mm) of 0.15 and 0.4. The integrated fluxes over the visible and infrared wavelengths shown in Fig. 4 are used to derive the AOD (0.5 mm) shown in Figs. 1–3. The aerosol was assumed to have a log normal distribution with a geometric median radius (rm) of 0.1 mm, standard deviation (s) of 0.69, a real and complex index of refraction of 1.5 and 0.1, respectively. This assumed index of refraction represents a combination of sulfate aerosols (1.430i) and Carbon C1 (1.550.015i) used in the TOMS satellite aerosol retrievals (Torres et al., 2002) described in Section 4. A surface albedo of 0.1 and a zenith angle of 601 are also assumed. Table 2 shows the fractional effect of cloudiness derived from the ratio of modeled cloud-free flux and the maximum winter period solar radiation observed at each station. These ratios are close to what one would expect from a cloud albedo effect of 0.5. With the cloud effect at each site estimated, we can then use the radiation transfer model to determine the relationship between reduced solar flux and AOD at 0.5 mm (Figs. 1–3). The highest solar radiation flux during the period was assumed to correspond to the value AOD (0.5 mm) of 0.15. For some of the stations the maximum solar radiation occurred closer to 1990 than earlier in the series (e.g., the cities of Ahmedabad in winter (AHMw) in 1989 and Trivandrum (TRVw) in 1988) and is reflected in a lack of an increasing trend at these sites. India city aerosol trends in Figs. 1–3 show that there are some cities such as New Delhi, Calcutta, and Poona with distinct upward trends. The trends from the other cities are much less distinct. More recent wintertime measurements of AOD from the Aerosol Climatology Project of the Indian Space Research Organization Geosphere Biosphere Program show results similar in magnitude to the higher values of AOD (0.5 mm) shown in Figs. 1–3 of about 0.4 (Moorthy et al., 2005; Niranjan et al., 2005). Data from this project was used in the evaluation of the aerosol climate model MIRAGE
Table 2 Fractional decrease in global solar radiation estimated to be due to clouds using a radiation transfer model at each city Station ID
City name
Cloud ratio
AHM CAL GOA JDP MDS NGP DLH PNA SHO TRV VSK
Ahmadabad Calcutta Goa Jodhpur Madras Nagpur New Delhi Poona Shillong Trivandrum Vishakhapatnam
0.49 0.45 0.57 0.48 0.50 0.49 0.45 0.53 0.44 0.53 0.50
Table 3 Parametric study of the effect of aerosol size and absorption on AOD (0.5 mm) derived from GEBA data from the radiation transfer model Aerosol rm (mm)
Aerosol ni
AOD (0.5 mm)
Surface radiation (W m2)
0.1 small 0.1
0.0 no abs. 0.0
0.15 0.40
483 454 29 difference
0.1 small 0.1
0.01 abs 0.01
0.15 0.40
476 436 40 difference
0.3 large 0.3
0.0 no abs. 0.0
0.15 0.40
476 437 39 difference
0.3 large 0.3
0.01 abs. 0.01
0.15 0.40
462 402 60 difference
Cloud-free conditions, a surface albedo of 0.1 and a log-normal size distribution with a geometric s of 0.69 are assumed.
(Ghan et al., 2001). The model assumptions that we used to derive the AOD from pyranometer data are rather crude and would be improved if they were more site-specific and included cloud variation and gas absorbers such as NO2; however, these observations were not available to us. We conducted a model parametric study to better understand the importance of aerosol size and absorption variation on these results (Table 3). The effect of changing the aerosol size and absorption affects the modeled global surface radiation under cloud-free conditions by about 30 W m2. Since clouds decrease this difference by
ARTICLE IN PRESS W. Porch et al. / Atmospheric Environment 41 (2007) 7524–7532 Table 4 Preliminary values of decadal changes associated with single 31 31 latitude–longitude boxes associated the locations based on TOMS satellite data City
% Change per decade
2s fit error
Significant
Ahmadabad Calcuttta Goa Jodhpur Madras Nagpur New Delhi Poona Shillong Trivandrum Vishakhapatnam
5.64 17.2 2.94 9.81 1.54 8.88 20.4 3.49 2.99 8.08 1.87
7.36 6.20 6.29 14.8 3.54 15.8 13.1 6.69 12.7 8.80 8.56
n Y n n n n Y n n n n
The trends for the Calcutta and New Delhi regions are statistically significant. The changes are calculated for winter months (November–February).
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about half and the observed solar radiation values at the cities varied by 50–100 W m2 from year to year, it is more likely that variable meteorological conditions such as ventilation (e.g. Porch and Ellsaesser, 1977), and precipitation are more important than variable aerosol properties along with growing aerosol sources contributing to the overall trend.
4. Trend analysis using satellite data Satellite observations from 1980 to 1999 from the TOMS satellite (Massie et al., 2004) help put these observations in a larger temporal and spatial context. The period 1990–1999 is covered by the TOMS data which is not presently available from the GEBA network. The TOMS measurements give the changes in column ozone and AODs from 1979
Fig. 5. Decadal change in aerosol optical depth at 0.5 mm over a 31 grid in percent interpreted from TOMS satellite data. Only regions for which statistically significant positive changes (2s) are indicated in the graph. The changes in AOD (0.5 mm) are most apparent in the Ganges basin, and offshore of India. The GEBA cities are shown as filled-in circles and the AERONET stations are open circles.
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to the present over a 11 spatial scale, with a data gap from 1994 to mid-1996 (Torres et al., 2002). The TOMS aerosol record is unique in its ability to detect aerosol over land. Other satellite observations, such as the advanced very high resolution radiometer (AVHRR) and the moderate resolution imaging spectral-radiometer (MODIS), have difficulty retrieving desert dust optical depths over land due to the high reflectivity of land surfaces. The dark surface albedo of land surfaces free of ice and snow at the TOMS near ultraviolet wavelengths allows for improved detection of aerosol over land. TOMS AOD data are available on a 11 11 global grid. The grid coordinates corresponding to the cities in the GEBA database are shown in Table 1. The AOD (0.5 mm) values observed from the TOMS satellite are shown as colored boxes in Figs. 1–3. These figures show a general increasing trend in AOD (0.5 mm) consistent with the results of Ramanathan et al. (2005) for decreasing solar isolation. Offsets where the data overlap (e.g., the GEBA and TOMS data for Calcutta for the early 1980s) are due to the differences in the measurement system locations and spatial representativity. Most of these data show no significant trend over the period
1980–1999 (Table 4). This is consistent with the AOD (0.5 mm) results from the analysis of the GEBA data. By themselves and without the earlier results from the turbidity network, these results would imply that the aerosol trends over India cities represent more of a local trend rather than a regional trend. However, the regional trends become more apparent when the greater region of India is included. Fig. 5 shows the regions of significant trends of AOD (0.5 mm) from the TOMS satellite data. While most of the west coast and lower east coast regions are blank (implying no significant trend), the Ganges River Basin, Northeastern India including Calcutta, and the eastern and western ocean regions beyond the coasts show significant upward trends. As stated earlier, this lack of a significant trend over other regions during the period 1980–2000 is not due to difficulty in discriminating aerosol over land surfaces with the TOMS satellite. The increase in the Ganges River Basin is consistent with the very high values of AOD (0.5 mm) observed from the AERONET data from Kanpur in Fig. 3. It is important to realize that the Ganges River Basin in winter is subject to occasional fog episodes which significantly raise the AOD (Ganguly et al., 2006).
Fig. 6. The population change per decade from 1990 to 2000 derived from the Columbia University digital population atlas, which tabulates population in 5-year increments from 1995 to 2005. The majority of the population is concentrated in the Ganges basin. The largest changes in population took place also in this basin from 1995 to 2005.
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AOD Over India (October to February) 0.4
0.45
0.35
12to15N
15to18N
18to21N
21to24N
AOD
24to27N 0.3
0.25
0.2 2000
2001
2002
2003
2004
2005
2006
2007
Fig. 7. Recent trends in winter aerosol optical depth (AOD) at 0.5 mm MODIS satellite data stratified by latitude over India showing that the latitude with increasing trend is from 241 to 271 North which corresponds to the Ganges River Basin analogous to the region of increasing trend in Fig. 5.
The results in Fig. 5 appear consistent with population trends in India illustrated in Fig. 6. This figure shows that most of the population change in India has occurred in the Ganges River Basin over the last decade. This implies that the increasing aerosol trends are associated with residential biomass combustion, electricity production by coal processing, and transportation combined with the ability of a basin region to trap pollution during the winter months. Industrial development outside the Ganges River Basin region appears to having less of an effect at least during the winter months. The aerosols generated in the Ganges River Basin region are apparently transported east and west and affect larger scale ocean regions. In order to see if more recent data support the Ganges River Basin as the region of greatest AOD increase, we have analyzed wintertime MODIS satellite data in latitude bands across India. These results are shown in Fig. 7. At least over this short period, the band of latitudes covering the Ganges River Basin represents the only region to exhibit an upward trend.
few of the cities have shown a significant increasing trend in aerosols over the last 20 years. Inclusion of aerosol data from an early turbidity network reports in 1968 (Ganesan, 1973; Mani et al., 1973) helps make the aerosol increases more apparent. TOMS satellite data analysis of the larger India region shows that regional trends are concentrated in the Ganges River Basin and North Eastern India including Calcutta. This is consistent with population changes in India and possible topographic trapping of pollutants. The aerosol in these regions apparently spill out over the oceans beyond the West and Southern East Coasts. These details in regional trend assessment are important to future efforts to understand sources and sinks of regional pollution and possible mitigation strategies. Acknowledgments We would like to thank H. Gilgen for maintaining and allowing us to use data from the GEBA database, and B. Holben and R.P. Singh for the maintenance and operation of the AERONET sites in India, and N. Laulainen for his assistance.
5. Conclusions Aerosol optical depths (at 0.5 mm) have been shown to be highly variable in winter months (November–February) over cities in India. Only a
References Dave`, J.V., 1972. Development of programs for computing characteristics of ultraviolet radiation. Technical
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Report-Scaler Case, FSC-72-0009 NASA, Greenbelt, MD, 1972, p. 43. Dutton, E.G., Nelson, D.W., Stone, R.S., Longenecker, D., Carbaugh, G., Harris, J.M., Wendell, J., 2006. Decadal variations in surface solar irradiance as observed in a globally remote network. Journal of Geophysical Research 111, D19101. Ellsaesser, H.W., 1975. The upward trend in airborne particles that isn’t. The Changing Global Environment. D. Reidel Publ., Dordretch, Holland, pp. 235–269. Ganesan, H.R., 1973. Atmospheric turbidity over India. Indian Journal of Meteorology and Geophysics 24, 413–424. Ganguly, D., Jayaraman, A., Rajesh, T.A., Gadhavi, H., 2006. Wintertime aerosol properties during foggy and nonfoggy days over urban center Delhi and their implications for shortwave radiative forcing. Journal of Geophysical Research 111 (D15217), 1–15. Ghan, S., Laulainen, N., Easter, R., Wagener, R., Nemesure, S., Chapman, E., Zhang, Y., Leung, R., 2001. Evaluation of aerosol direct radiative forcing in MIRAGE. Journal of Geophysical Research 106 (D6), 5295–5316. Gilgen, H., Ohmura, A., 1999. The global energy balance archive. Bulletin of the American Meteorological Society 80, 831–850. Mani, A., Chacko, O., Iver, N.V., 1973. Atmospheric turbidity over India from solar radiation measurements. Solar Energy 14 (2), 185–195. Massie, S.T., Torres, O., Smith, S.J., 2004. Total ozone mapping spectrometer (TOMS) observations of increases in Asian aerosol in winter from 1979 to 2000. Journal of Geophysical Research 109, D18211. McClatchey, R.A., Fenn, R.W., Selby, J.E.A., Votz, F.E., Garing, J., 1978. Optical properties of the atmosphere. Handbook of Optics. Optical Society of America, 14-1, p. 65. Mishchenko, M.I., Geogdzhayev, I.V., Rossow, W.B., Cairns, B., Carlson, B.E., Lacis, A.A., Liu, L., Travis, L.D., 2007. Long-
term satellite record reveals likely aerosol trend. Science 315, 1543. Moorthy, K.K., Sunilkumar, S.V., Pillai, P.S., Parameswaran, K., Nair, P.R., Ahmed, Y.N., Ramgopal, K., Narasimhulu, K., Reddy, R.R., Vinoj, V., Satheesh, S.K., Nirajan, K., Rao, B.M., Brahmanandam, P.S., Saha, A., Badarinath, K.V.S., Kiranchand, T.R., Latha, K.M., 2005. Wintertime spatial characteristics of boundary layer aerosols over peninsular India. Journal of Geophysical Research 110, D08207. Niranjan, K., Rao, B.M., Brahmanandam, P.S., Madhavan, B.L., Sreekanth, V., Moorthy, K.K., 2005. Spatial characteristics of aerosol physical properties over the northeastern parts of peninsular India. Annales Geophysicae 23, 3219–3227. Porch, W.M., Ellsaesser, H.W., 1977. Cyclic trends in Los Angeles fine particulates. Journal of Air Pollution Control Association 27 (2), 134–137. Porch, W.M., Charlson, R.J., Radke, L.F., 1970. Atmospheric aerosol: does a background level exist? Science 170, 315–317. Ramanathan, V., Chung, C., Kim, D., Bettge, T., Buja, L., Kiehl, J.T., Washingtonz, W.M., Fu, Q., Sikka, D.R., Wild, M., 2005. Atmospheric brown clouds: impacts on South Asian climate and hydrological cycle. Proceedings of the National Academy of Sciences 102 (15), 5326–5333. Schwartz, R.D., 2005. Global dimming: clear-sky atmospheric transmission from astronomical extinction measurements. Journal of Geophysical Research 110, D14201. Stanhill, G., Cohen, S., 2001. Global dimming, a review of the evidence for a widespread and significant reduction in global radiation with a discussion of its probable causes and possible agricultural consequences. Agricultural and Forest Meteorology 107, 255–278. Torres, O., Bhartia, P.K., Herman, J.R., Sinyuk, A., Ginoux, P., Holben, B., 2002. A long-term record of aerosol optical depth from TOMS observations and comparison to AERONET measurements. Journal of Atmospheric Science 59, 398–413.
Atmospheric Environment 41 (2007) 7524–7532 www.elsevier.com/locate/atmosenv
Trends in aerosol optical depth for cities in India William Porcha,, Petr Chyleka, Mavendra Dubeya, Steven Massieb a
Los Alamos National Laboratory, MS-J577, Los Alamos, NM 87545, USA b National Center for Atmospheric Research, Boulder, CO, USA
Received 19 January 2007; received in revised form 28 March 2007; accepted 21 May 2007
Abstract Recent analysis of trends in global short-wave radiation measured with pyranometers in major cities in India support a decrease in solar radiation in many of those cities since 1990. Since direct and diffuse radiation measurements include cloud effects, spring and summer dust and the variable summer monsoon rains, we concentrate in this paper on wintertime (November–February) aerosol optical depth measurements. The aerosol optical depth is derived from cloud-free turbidity measurements beginning in the 1960s and more recent sun photometer direct aerosol optical depth measurements. We compare the sun photometer derived trends with the pyranometer-derived trends using a radiative transfer model. These results are then compared to total ozone mapping spectrometer (TOMS) satellite-derived regional aerosol optical depths from 1980 to 2000. The results show that inclusion of the earlier turbidity measurements helps to establish an increasing regional turbidity trend. However, most of the increasing trend is confined to the larger cities in the Ganges River Basin of India (mainly Calcutta and New Delhi) with other cities showing a much less increase. Regional satellite data show that there is an increasing trend in aerosol off the coast of India and over the Ganges River Basin. The increase over the Ganges River Basin is consistent with population trends over the region during 1980–2000. r 2007 Elsevier Ltd. All rights reserved. Keywords: Atmospheric aerosols; Climate; Trends; Global dimming; Radiation transfer
1. Introduction Recent studies related to ‘‘global dimming’’ (e.g. Stanhill and Cohen, 2001) have increased interest in atmospheric aerosol trends. Because of the relatively short residence time of most atmospheric aerosols (3–7 days), trends are much more difficult to establish than for atmospheric gases such as CO2. Dutton et al. (2006) have shown that little or no trend in aerosol is apparent in background aerosol (Porch et al., 1970) measured at the same stations Corresponding author.
E-mail address: [email protected] (W. Porch). 1352-2310/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2007.05.055
that confirm an increasing trend in CO2. Schwartz (2005) has also used astronomical extinction measurements in Chile to show no appreciable trends except those that are related to volcanic eruptions. This is consistent with an earlier assessment of aerosol trends by Ellsaesser (1975). A recent paper by Mishchenko et al. (2007) has shown that there appears to be a decreasing trend in aerosol since about 1995 from AVHRR satellite data over the oceans from the Global Aerosol Climatology Project. Lack of evidence of an increasing global trend in aerosol does not imply that there are no regional trends in aerosol. Ramanathan et al. (2005) reported an extensive study of regional trends in
ARTICLE IN PRESS W. Porch et al. / Atmospheric Environment 41 (2007) 7524–7532
India including decreasing trends in measured and predicted solar radiation. The measurements come from the Global Energy Balance Archive (GEBA) (Gilgen and Ohmura, 1999). We examine these trends in India in more detail in this paper. Because decreasing solar radiation can be affected by increasing clouds as well as aerosol, we focus in this paper on sun photometer measurements of turbidity and aerosol optical depth (AOD). We also focus on the winter months (November–February) to lessen the effect of spring and summer dust and the variable monsoon. These observations are used with a radiation transfer model (Dave`, 1972) to attempt to isolate the aerosol trends from solar radiation trends. These results are then compared with AOD trends from total ozone mapping spectrometer (TOMS) satellite data (Massie et al., 2004). 2. Early turbidity observations Analyses of trends always depend strongly on the time range of the data set. Mani et al. (1973) and Ganesan (1973) describe turbidity observations that begin in 1958 at Poona and New Delhi and are supplemented in 1967–1969 at nine other sites in major cities (Table 1). These cities fortunately overlap with most of the cities in the GEBA data set. Both these papers document a strong upward trend in turbidity up to 1969. Turbidity b is related to AOD at 0.5 mm through the formula AODð0:5 mmÞ ¼ b la ¼ b 2:46,
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where l is the wavelength of the light (0.5 mm) and a is the wavelength exponent (in these studies 1.3 was used). This implies an increase in AOD (0.5 mm) from 0.09 in 1957 to a peak value in New Delhi of AOD (0.5 mm) of about 0.25 in 1969. This is less than the values observed today of about 0.4 (as will be shown later). The increase at Poona was from 0.05 in 1958 to about 0.2 in 1969. These are annual average comparisons. In the comparisons that follow we will focus on winter averages (November– February). 3. Comparisons with GEBA data The GEBA database contains pyranometer measurements of global (direct and diffuse) solar radiation for 11 cities in India from 1957 to 1990. Solar radiation fluxes from these cities range from 150 to 250 W m2 averaged over the winter months. Figs. 1–3 show the estimated winter period trends in AOD (0.5 mm) from the GEBA network along with the turbidity derived values from the early network. The locations of these cities on a map of India are shown in Fig. 5. Also shown in these figures are the AOD (0.5 mm) winter period values derived from the AERONET sun photometer network from 1999 to 2005 and winter period data derived from the TOMS satellite from 1980 to 2000 (described in Section 4). Since clouds affect the solar radiation observed in the GEBA data, the effect of clouds must be
Table 1 City locations used in this study Station ID
GEBA
31 grid for satellite analysis
City name
Longitude (East)
Latitude (North)
Altitude (m)
Longitude (1E)
Latitude (1N)
AHM CAL GOA JDP MDS NGP DLH PNA SHO TRV VSK
Ahmadabad Calcutta Goa Jodhpur Madras Nagpur New Delhi Poona Shillong Trivandrum Vishakhapatnam
721380 881200 731490 73110 801110 79130 771120 731510 911530 761570 831140
23140 221320 151290 261180 13100 21160 281350 181320 251340 81290 171430
55 4 55 217 10 308 212 555 1600 60 41
71–74 87–90 72–75 72–75 79–82 78–81 76–79 72–75 90–93 75–78 82–85
21–24 21–24 14–17 25–28 12–15 20–23 27–30 17–20 24–27 7–10 16–19
MALE GOA KAN
AERONET Male Goa Kanpur
731320 731490 801210
41120 151290 261270
2 55 142
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PNAw GOAw
0.6
India West Coast Trends
w = winter average
TRVw
GOAw
AHMw PNAwTOMS
0.5
GOAwTOMS TRVwTOMS
AOD 500 nm
0.4
AHMwTOMS
MALEw
0.3 MALEw MALEw
0.2 TRV
0.1
BHVw AHMw PNAw
GOAw
0 1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Year
Fig. 1. Trends in aerosol optical depth at 0.5 mm (AOD) from turbidity measurements in 1968, AERONET sun-photometer data after 2000 (Male and Goa), and interpreted from global radiation trends from the GEBA stations up to 1990 for west coast cities during winter (November–February).
w = winter average
India East Coast Trends 0.6
0.5
AOD 500 nm
0.4
0.3 CALw
VSKw
0.2
CALw MDSw
VSKw MDSw
0.1
VSKwTOMS CALwTOMS MDSwTOMS
0 1960
1965
1970
1975
1980
1985 Year
1990
1995
2000
2005
2010
Fig. 2. Trends in aerosol optical depth at 0.5 mm (AOD) from turbidity measurements in 1968 and interpreted from global radiation trends from the GEBA stations up to 1990 for east coast cities during winter (November–February).
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0.9 0.8
AOD 500 nm
0.7 0.6
w = winter average
India Central Trends
1
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DLHw NGPw JDPw SHOw DLHwTOMS NGPwTOMS
KANw
JDPwTOMS SHOwTOMS
0.5 0.4 0.3 0.2 JDPw
0.1
DLHw NGPw SHOw
0 1950
1960
1970
1980
1990
2000
2010
Year
Fig. 3. Trends in aerosol optical depth at 0.5 mm (AOD) from turbidity measurements in 1968, AERONET sun-photometer data after 2000 (for Kanpur) and interpreted from global radiation trends from the GEBA stations up to 1990 for central cities during winter (November–February). Total Flux @500nm W/m2
Model Results Surface Global Solar Fluxes
900
Tropical Clean - 578 Tau 0.15 - 476 Tau 0.4 - 436
Tropical(Clean)
800
Tau@500nm 0.15
700
Tau@500nm 0.4
W/m**2/um
600 500 400 300 200 100 VSK 0 0
0.5
1
1.5
2
2.5
3
wavelength (um)
Fig. 4. Model results used to estimate cloud ratio at each site and estimate aerosol optical depth at 0.5 mm from GEBA global radiation measurements and trends. The upper curve assumes no clouds and uses the AFCRL Tropics model for the vertical distribution of aerosol, water vapor and ozone. A zenith angle of 601 and a surface albedo of 0.1 are also assumed. The aerosol is assumed to have real and imaginary indexes of refraction of 1.5 and 0.1, respectively. A lognormal distribution is assumed with rm of 0.1 mm and s of 0.69. The concentration of aerosol in the first 2 km above the surface is varied to produce an aerosol optical depth at 0.5 mm of 0.15 and 0.4.
separated from the observed diffuse and direct solar radiation trends by comparing calculated cloud-free and observed values using a radiation transfer code
(Dave`, 1972). This code includes molecular scattering, aerosol multiple scattering as well as molecular absorption from ozone and water vapor, and covers
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wavelengths from 0.415 to 2.45 mm. The cloud-free solar radiation is estimated using the AFCRL Tropics model atmosphere (McClatchey et al., 1978) and an assumed AOD (0.5 mm) of about 0.15 based on the results from the turbidity network in 1968 in Figs. 1–3. Fig. 4 shows the results of the radiation transfer model calculations of the global solar radiation flux. These results assume a clean tropical cloud-free model and aerosols distributed in the first 2 km above the surface resulting in a calculated AOD (0.5 mm) of 0.15 and 0.4. The integrated fluxes over the visible and infrared wavelengths shown in Fig. 4 are used to derive the AOD (0.5 mm) shown in Figs. 1–3. The aerosol was assumed to have a log normal distribution with a geometric median radius (rm) of 0.1 mm, standard deviation (s) of 0.69, a real and complex index of refraction of 1.5 and 0.1, respectively. This assumed index of refraction represents a combination of sulfate aerosols (1.430i) and Carbon C1 (1.550.015i) used in the TOMS satellite aerosol retrievals (Torres et al., 2002) described in Section 4. A surface albedo of 0.1 and a zenith angle of 601 are also assumed. Table 2 shows the fractional effect of cloudiness derived from the ratio of modeled cloud-free flux and the maximum winter period solar radiation observed at each station. These ratios are close to what one would expect from a cloud albedo effect of 0.5. With the cloud effect at each site estimated, we can then use the radiation transfer model to determine the relationship between reduced solar flux and AOD at 0.5 mm (Figs. 1–3). The highest solar radiation flux during the period was assumed to correspond to the value AOD (0.5 mm) of 0.15. For some of the stations the maximum solar radiation occurred closer to 1990 than earlier in the series (e.g., the cities of Ahmedabad in winter (AHMw) in 1989 and Trivandrum (TRVw) in 1988) and is reflected in a lack of an increasing trend at these sites. India city aerosol trends in Figs. 1–3 show that there are some cities such as New Delhi, Calcutta, and Poona with distinct upward trends. The trends from the other cities are much less distinct. More recent wintertime measurements of AOD from the Aerosol Climatology Project of the Indian Space Research Organization Geosphere Biosphere Program show results similar in magnitude to the higher values of AOD (0.5 mm) shown in Figs. 1–3 of about 0.4 (Moorthy et al., 2005; Niranjan et al., 2005). Data from this project was used in the evaluation of the aerosol climate model MIRAGE
Table 2 Fractional decrease in global solar radiation estimated to be due to clouds using a radiation transfer model at each city Station ID
City name
Cloud ratio
AHM CAL GOA JDP MDS NGP DLH PNA SHO TRV VSK
Ahmadabad Calcutta Goa Jodhpur Madras Nagpur New Delhi Poona Shillong Trivandrum Vishakhapatnam
0.49 0.45 0.57 0.48 0.50 0.49 0.45 0.53 0.44 0.53 0.50
Table 3 Parametric study of the effect of aerosol size and absorption on AOD (0.5 mm) derived from GEBA data from the radiation transfer model Aerosol rm (mm)
Aerosol ni
AOD (0.5 mm)
Surface radiation (W m2)
0.1 small 0.1
0.0 no abs. 0.0
0.15 0.40
483 454 29 difference
0.1 small 0.1
0.01 abs 0.01
0.15 0.40
476 436 40 difference
0.3 large 0.3
0.0 no abs. 0.0
0.15 0.40
476 437 39 difference
0.3 large 0.3
0.01 abs. 0.01
0.15 0.40
462 402 60 difference
Cloud-free conditions, a surface albedo of 0.1 and a log-normal size distribution with a geometric s of 0.69 are assumed.
(Ghan et al., 2001). The model assumptions that we used to derive the AOD from pyranometer data are rather crude and would be improved if they were more site-specific and included cloud variation and gas absorbers such as NO2; however, these observations were not available to us. We conducted a model parametric study to better understand the importance of aerosol size and absorption variation on these results (Table 3). The effect of changing the aerosol size and absorption affects the modeled global surface radiation under cloud-free conditions by about 30 W m2. Since clouds decrease this difference by
ARTICLE IN PRESS W. Porch et al. / Atmospheric Environment 41 (2007) 7524–7532 Table 4 Preliminary values of decadal changes associated with single 31 31 latitude–longitude boxes associated the locations based on TOMS satellite data City
% Change per decade
2s fit error
Significant
Ahmadabad Calcuttta Goa Jodhpur Madras Nagpur New Delhi Poona Shillong Trivandrum Vishakhapatnam
5.64 17.2 2.94 9.81 1.54 8.88 20.4 3.49 2.99 8.08 1.87
7.36 6.20 6.29 14.8 3.54 15.8 13.1 6.69 12.7 8.80 8.56
n Y n n n n Y n n n n
The trends for the Calcutta and New Delhi regions are statistically significant. The changes are calculated for winter months (November–February).
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about half and the observed solar radiation values at the cities varied by 50–100 W m2 from year to year, it is more likely that variable meteorological conditions such as ventilation (e.g. Porch and Ellsaesser, 1977), and precipitation are more important than variable aerosol properties along with growing aerosol sources contributing to the overall trend.
4. Trend analysis using satellite data Satellite observations from 1980 to 1999 from the TOMS satellite (Massie et al., 2004) help put these observations in a larger temporal and spatial context. The period 1990–1999 is covered by the TOMS data which is not presently available from the GEBA network. The TOMS measurements give the changes in column ozone and AODs from 1979
Fig. 5. Decadal change in aerosol optical depth at 0.5 mm over a 31 grid in percent interpreted from TOMS satellite data. Only regions for which statistically significant positive changes (2s) are indicated in the graph. The changes in AOD (0.5 mm) are most apparent in the Ganges basin, and offshore of India. The GEBA cities are shown as filled-in circles and the AERONET stations are open circles.
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to the present over a 11 spatial scale, with a data gap from 1994 to mid-1996 (Torres et al., 2002). The TOMS aerosol record is unique in its ability to detect aerosol over land. Other satellite observations, such as the advanced very high resolution radiometer (AVHRR) and the moderate resolution imaging spectral-radiometer (MODIS), have difficulty retrieving desert dust optical depths over land due to the high reflectivity of land surfaces. The dark surface albedo of land surfaces free of ice and snow at the TOMS near ultraviolet wavelengths allows for improved detection of aerosol over land. TOMS AOD data are available on a 11 11 global grid. The grid coordinates corresponding to the cities in the GEBA database are shown in Table 1. The AOD (0.5 mm) values observed from the TOMS satellite are shown as colored boxes in Figs. 1–3. These figures show a general increasing trend in AOD (0.5 mm) consistent with the results of Ramanathan et al. (2005) for decreasing solar isolation. Offsets where the data overlap (e.g., the GEBA and TOMS data for Calcutta for the early 1980s) are due to the differences in the measurement system locations and spatial representativity. Most of these data show no significant trend over the period
1980–1999 (Table 4). This is consistent with the AOD (0.5 mm) results from the analysis of the GEBA data. By themselves and without the earlier results from the turbidity network, these results would imply that the aerosol trends over India cities represent more of a local trend rather than a regional trend. However, the regional trends become more apparent when the greater region of India is included. Fig. 5 shows the regions of significant trends of AOD (0.5 mm) from the TOMS satellite data. While most of the west coast and lower east coast regions are blank (implying no significant trend), the Ganges River Basin, Northeastern India including Calcutta, and the eastern and western ocean regions beyond the coasts show significant upward trends. As stated earlier, this lack of a significant trend over other regions during the period 1980–2000 is not due to difficulty in discriminating aerosol over land surfaces with the TOMS satellite. The increase in the Ganges River Basin is consistent with the very high values of AOD (0.5 mm) observed from the AERONET data from Kanpur in Fig. 3. It is important to realize that the Ganges River Basin in winter is subject to occasional fog episodes which significantly raise the AOD (Ganguly et al., 2006).
Fig. 6. The population change per decade from 1990 to 2000 derived from the Columbia University digital population atlas, which tabulates population in 5-year increments from 1995 to 2005. The majority of the population is concentrated in the Ganges basin. The largest changes in population took place also in this basin from 1995 to 2005.
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AOD Over India (October to February) 0.4
0.45
0.35
12to15N
15to18N
18to21N
21to24N
AOD
24to27N 0.3
0.25
0.2 2000
2001
2002
2003
2004
2005
2006
2007
Fig. 7. Recent trends in winter aerosol optical depth (AOD) at 0.5 mm MODIS satellite data stratified by latitude over India showing that the latitude with increasing trend is from 241 to 271 North which corresponds to the Ganges River Basin analogous to the region of increasing trend in Fig. 5.
The results in Fig. 5 appear consistent with population trends in India illustrated in Fig. 6. This figure shows that most of the population change in India has occurred in the Ganges River Basin over the last decade. This implies that the increasing aerosol trends are associated with residential biomass combustion, electricity production by coal processing, and transportation combined with the ability of a basin region to trap pollution during the winter months. Industrial development outside the Ganges River Basin region appears to having less of an effect at least during the winter months. The aerosols generated in the Ganges River Basin region are apparently transported east and west and affect larger scale ocean regions. In order to see if more recent data support the Ganges River Basin as the region of greatest AOD increase, we have analyzed wintertime MODIS satellite data in latitude bands across India. These results are shown in Fig. 7. At least over this short period, the band of latitudes covering the Ganges River Basin represents the only region to exhibit an upward trend.
few of the cities have shown a significant increasing trend in aerosols over the last 20 years. Inclusion of aerosol data from an early turbidity network reports in 1968 (Ganesan, 1973; Mani et al., 1973) helps make the aerosol increases more apparent. TOMS satellite data analysis of the larger India region shows that regional trends are concentrated in the Ganges River Basin and North Eastern India including Calcutta. This is consistent with population changes in India and possible topographic trapping of pollutants. The aerosol in these regions apparently spill out over the oceans beyond the West and Southern East Coasts. These details in regional trend assessment are important to future efforts to understand sources and sinks of regional pollution and possible mitigation strategies. Acknowledgments We would like to thank H. Gilgen for maintaining and allowing us to use data from the GEBA database, and B. Holben and R.P. Singh for the maintenance and operation of the AERONET sites in India, and N. Laulainen for his assistance.
5. Conclusions Aerosol optical depths (at 0.5 mm) have been shown to be highly variable in winter months (November–February) over cities in India. Only a
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