Link between local scale BC emissions and large scale atmospheric solar absorption

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Introduction
Roughly half of the world's population relies on solid fuels (wood, animal dung, crop residues and coal) for daily household energy needs.Cooking with these fuels emits significant amount of smoke (comprising mainly of soot and semi-volatile organics) due to incomplete combustion.For most part, cooking is done in the kitchen microenvironment with poor ventilation causing extensive build-up of smoke; resulting in the exposure to high levels of particulate matter which causes adverse health effects (Sauvain et al., 2006;Smith et al., 2004;Schwarze et al., 2006).This indoor smoke escapes outdoors and leads to atmospheric brown clouds (ABCs) (Ramanathan et al., 2001a).
Black carbon (BC), a major component of smoke, strongly absorbs sunlight in the atmosphere and is considered to be the second largest contributor to global warming after CO 2 (Ramanathan and Carmichael, 2008;Jacobson, 2010).BC significantly impacts the regional and global climate through the disruption of monsoon, retreat of glaciers, arctic sea ice and mountain glaciers (Ramanathan et al., 2001a;Lau et al., 2008;Menon et al., 2002Menon et al., , 2010;;Flanner et al., 2009;Pettus, 2009).Because of its positive atmospheric radiative forcing (i.e., warming) and relatively short residence time in the atmosphere (few days to weeks) compared to CO 2 (lifetime of more than 100 yr), reducing BC emissions presents unique opportunities for delaying the impacts of climate change (Ramanathan and Wallack, 2008;Molina et al., 2009;Ramanathan and Xu, 2010).Organic carbon (OC), co-emitted along with BC, was previously known to have negligible solar absorption and thus assumed to have only a cooling effect (Andreae and Gelencser, 2006).However, studies have shown that some OC fractions (referred to as brown carbon) emitted mostly during biomass burning show strong wavelength dependence of absorption in the ultraviolet and visible region (<600 nm) (Kirchstetter et al., 2004), thus adding to positive atmospheric radiative forcing.

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Full spectively (Venkatraman et al., 2005).Model simulation has shown that replacing traditional methods of cooking (i.e., burning biomass fuel in mud stove) with improved cook stoves may significantly reduce atmospheric BC burden over South and East Asia (Ramanathan and Carmichael, 2008).The Indo-Gangetic Plains (IGP), situated along the southern edge of the Himalayan region and spanning across the north-eastern parts of India, is one of the most densely populated regions on earth.It is characterized by large anthropogenic emissions that include biofuel emissions from rural households, thermal power plants and industries, causing a widespread layer of ABCs over the region (Ramanathan and Ramana, 2005).MODIS aerosol optical depth indicates that the IGP region is subjected to a heavy loading of the pollution layer (Fig. 1).Project Surya is the first field study designed to demonstrate the potential of mitigating biomass BC emissions on slowing down global warming and reducing negative health effects (Ramanathan and Balakrishnan, 2007).The first (or pilot) phase of Project Surya was started in October 2009 in a rural village located in the IGP region in northern India.
The first phase observations were devoted to baseline measurements of BC concentration and aerosol optical properties from both indoor and outdoor.This is the third in a series of 4 papers on the first phase study.The first paper (Ramanathan et al., 2011) deals with a cell-phone based BC monitoring system for large scale (e.g.100-300 households) measurements.The second paper (Rehman et al, 2011) explored the link between indoor and outdoor BC concentration.The fourth paper (Kar et al., 2011) investigates different commercially available improved cook stoves in cutting down BC emissions.This study documents the baseline BC measurements on diurnal, daily and seasonal time scales and examines the source dependent aerosol light absorption characteristics.As one of the main goals of Project Surya is to document the impact of BC mitigation on regional climate, this study also integrates the surface data collected in the village with other ground-based network and satellite observations to probe the link between local-scale emissions and regional-scale atmospheric BC solar absorption.Introduction

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Full  26• N, 81 • E) located in the IGP region (Fig. 1).The Surya village (denoted as SVI 1 from hereafter) is nearly 3 km away from a national highway, about 2 km from a state highway, and is located within 15 km radius of an industrial zone.
The SVI 1 has around 485 households in seven close by hamlets.We conducted experiments in the largest hamlet that has around 200 households.Most of the households use biomass as cooking fuel.Outdoor fires (for relief during the cold winter) and occasional open burning of crop residue are the other major sources of biomass originated aerosol apart from cooking.Vehicular and industrial emissions are the fossil fuel sources in the region.

Instrumentation
Observations were classified as indoor and outdoor measurements.For indoor observations, concentration of real-time BC and integrated elemental carbon (EC) were measured in the kitchen microenvironment in selected SVI 1 households.Real-time BC was measured using a single wavelength (880-nm) microAeth Model AE51 (Magee Scientific, Berkeley, CA).Three AE51 instruments (MA158, MA160, and MA165) were used for indoor BC measurement.The flow rate used for sampling was 50 mlpm with a time base of 1 min.Also 24-h indoor integrated aerosol samples were collected on quartz filter using a novel cell phone based BC monitoring system (BC CBM).These filter samples were subjected to EC/OC analysis using thermal-optical EC/OC analyzer (Schauer et al., 2003).Details of indoor sampling and analysis using BC CBM and AE51 were given in Ramanathan et al., (2011) andRehman et al. (2011).
Outdoor measurements consist of measuring real-time BC concentration and aerosol scattering coefficient to understand the aerosol heating and cooling proper-Introduction

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Full ties predominated by biomass aerosols.For this purpose, we chose sampling site at the center of the SVI 1 (denoted as VC site).We also measure BC at the northeast corner of the SVI 1 (denoted as NEV site) to understand aerosol spatial variability in the village.In addition, one-week observations of BC and aerosol scattering coefficient were also conducted at the highway (nearest traffic junction from the SVI 1) during 19-27 November 2009 using AE42 and nephelometer to understand fossil fuel contribution.Both AE42 and AE31 were operated with a flow rate set at 2 lpm and measurement frequency of 2 min.Nephelometer was operated at a sample flow of 5 lpm.The scattering response of the nephelometer was calibrated using CO 2 as a span gas and filtered air as zeroing gas.Nephelometer has different illumination sensitivity for coarse and fine particles because of truncation of forward scattering; the instrument cannot detect forward scattered light between 0-7 degrees (Anderson and Ogren, 1998).However, we did not use any correction factor to account for angular truncation error of nephelometer data, since illumination function in the ECHOTEC nephelometer deviates significantly from other commercially available nephelometers (M üller et al., 2009).The instruments at both VC and NEV sites were deployed on the roof under the shade.The air sampling inlet was mounted at a height of ∼10 m above the ground; stainless steel tubing was used for sample intake.The inlet system was designed to prevent entry of raindrops or insects in the sample stream.BC measurements were tested with and without inlet system to check any particle loss.The slope and correlation coefficient of the comparison between BC measurement with and without inlet system (plot not shown here) were found as 0.99 and R 2 = 0.78, respectively, suggesting minimal Introduction

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Full particle loss.

Data processing and validation
AE31 and AE42 aethalometers measures attenuation of the light beam at seven different wavelengths (370, 470, 520, 590, 660, 880 and 950 nm) after transmitted through aerosols that are being continuously deposited on a quartz fiber filter.The aethalometer manufacturer (Magee Scientific) calibrates the instrument based on the assumption that the change in aerosol light attenuation coefficient (m −1 ) is proportional to BC concentration (g m −3 ) through a constant called specific absorption cross section (m 2 g −1 ).
The 880 nm channel is recommended by the manufacturer for BC measurement.However, due to aerosol-filter interactions (such as multiple light scattering effects within the filter and the "shadowing" effect due to filter loading), the aethalometer observed aerosol attenuation coefficient is larger than the actual air-borne aerosol absorption coefficient (Arnott et al., 2005;Schmid et al., 2006).Correction methods are well documented in recent literature to obtain the actual air-borne aerosol absorption coefficient from aethalometer aerosol attenuation coefficient data (Arnott et al., 2005;Schmid et al., 2006).The present data analysis follows the Schmid et al. (2006) method to derive air-borne aerosol light absorption coefficient at seven wavelengths from the aethalometer data.The derived aerosol light absorption coefficient is then converted to BC concentration by dividing with a specific absorption cross section value.A wide range of values have been reported for specific absorption cross section (2-25 m 2 g −1 ) for ambient BC aerosols depending upon the source, location, and age of the aerosol; we used a value of 10 m 2 g −1 for 880-nm channel, the value often found in literature for air-borne BC particle (Schwarz, 2008;Ram and Sarin, 2009).We used the same approach for correcting data from AE51 instruments.We first checked the response of aethalometer to pure biomass and fossil fuel combustion aerosol.For this purpose AE31 instrument was operated for about an hour near a biomass cook stove and a diesel vehicle exhaust.Figure 2 shows the wavelength dependence of the normalized light absorption coefficient for both the sources.Introduction

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Full The spectrally dependent aerosol absorption coefficient is given by a power law relationship σ λ = C λ −AAE , where σ λ is the aerosol absorption coefficient at wavelength (λ), C a constant, and AAE is the absorption Angstrom exponent (Kirchstetter et al., 2004).Biomass aerosol show high absorption in the UV and visible regions compared to fossil fuel aerosol.In the present study AAE of absorption coefficient was calculated by the negative slope of absorption vs. wavelength in a log-log plot (for wavelengths 370 to 950 nm).Our results show that the mean AAE value of biomass was observed as 2.2; while for fossil fuel the value was 1.17.The observed aethalometer response is in close agreement with earlier reported values (Bergstrom et al., 2007;Kirchstetter et al., 2004).
It is essential to check the BC measurement precision among AE31, AE42, and three AE51 aethalometers for the same ambient air sample.Figure 3 shows the individual comparisons among different aethalometers.All three AE51 (MA158, MA160, MA165) were tested for precision in a rural household kitchen environment near a cook stove after connecting parallel to each other with a single inlet.Figure 3a-c shows comparisons among three AE51 instruments.BC measurements from all three AE51 agreed well with each other (slope ranging from 0.9 to 0.97, and correlation coefficient R 2 ranging from 0.98 to 0.99).Figure 3d-f show comparison of BC measurements of co-located aethalometers AE 31, AE42 and AE51 (model MA160).The slope of intercomparison ranged from 0.87 to 0.99 and R 2 ranged from 0.79 to 0.88, indicating good agreement with each other.
Finally we compared the ambient BC measurement from AE31 (used as a representative of aethalometer measurement) at VC with standard EC measurement from thermal-optical method.Figure 4 shows the comparison between aethalometer AE31 measured BC and thermal-optical measured EC in filters collected using BC CBM system running simultaneously with AE31.The slope and R 2 of the comparison were found as 0.86 and 0.52, which is well within the range observed by many earlier studies.In our results BC is found to be 14 % lower compared to EC. Partly this could be attributed to loss of BC data during frequent aethalometer tape advance, especially Introduction

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Full during peak BC concentration.In a typical observation day, 10-15 % BC data was lost due to tape advance.

Daily and monthly variation of BC concentrations in the SVI 1
Figure 5 shows the daily and monthly mean variations of BC concentrations at the VC site from November 2009 to May 2010.Daily mean BC concentration at VC during the study period varied from 3 to 56 µg m −3 with a mean value of 14.6±7.5 µg m −3 .BC concentrations were found to be higher during the winter (or dry) season (December to February) compared to the pre-monsoon season (March to May).The highest monthly mean BC concentration at VC was observed in December (22.5±5.2 µg m −3 ), and after a gradual decrease to a lower value in March (8.7±2.4 µg m −3 ), the concentrations were found to increase again to 16±3.9 µg m −3 in April.High BC concentrations in winter may be attributed to increase in the intensity of outdoor fires (for relief during the cold winter) and meteorological conditions like low wind speeds and low level inversion.The effects of meteorological conditions are further explained in Sect.5.1.The rise in ambient BC concentrations in April could be attributed to an increase in open burning activity (Beegum et al., 2009).This is further supported by the fire activity data from MODIS (plot not shown here) which showed that during the study period fire pixel count in the region (29-24 Full Figure 6 shows the seasonal mean diurnal variation of ambient BC concentration at VC.The diurnal variation of BC in all four seasons showed similar trend; with twice daily maximum in BC concentration in the morning between 06:00 and 09:00 LT and in the evening between 17:00 and 20:00 LT closely coinciding with the morning and evening cooking hours in the village.BC concentrations decreased gradually from morning to noon due to increase convective activity, reaching its minimum value between 12:00 and 15:00 LT.As the night progresses anthropogenic activities are reduced, and as a result peak BC concentration gradually decreases.The morning and evening peak BC concentrations during the monsoon season were very low compared to other seasons (dry, pre-monsoon and post-monsoon).

Comparison of SVI 1 BC with previous measurements in the region
In the past decade, there have been many observational campaigns and long-term monitoring studies for BC measurements in different parts of India covering urban, rural, costal, marine and high altitude environments (see Table 1).Reported BC concentration over Indian cities were found to be quite high compared to cities in other parts of the world (Ganguly et al., 2006;Latha and Badarinath, 2005;Babu and Moorthy, 2002).The observed BC concentrations in India showed large spatial variations depending on the location (Table 1); with mainland BC concentrations (especially urban centers and IGP region) being much higher than those at high altitude and island stations.Total and BC aerosol concentrations were 5-10 times higher over the IGP region compared with non-IGP locations (Nair et al., 2007;Beegum et al., 2009).The observed daily mean and diurnal variation of BC concentrations at SVI 1 are within the range of reported values in the region (Beegum et al., 2009).Introduction

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Time series of aerosol scattering and absorption coefficient
Figure 7a shows the daily mean variation of aerosol scattering and absorption coefficient at VC during the study period.Aerosol scattering coefficient showed an increasing trend from the post monsoon season to winter season, and then a decreasing trend from winter towards the monsoon season.Aerosol absorption coefficient followed a similar trend as BC (Fig. 5) but unlike the scattering coefficient trend, it did not have a maximum during winter.The winter time peak in the scattering coefficient coincides with a corresponding peak in the relative humidity (daily mean RH shown in Fig. 7b), thus implying hygroscopic growth of the aerosol (Pan et al., 2009).Layer of non-absorbing coating (such as water vapour) on BC aerosol is also known to enhance its absorption.However, with the increase in the size of aerosol with increasing relative humidity, enhance scattering due to much larger aerosol surface area is likely to offset enhance absorption.
The aerosol single scattering albedo (SSA), which is the ratio of scattering to the extinction coefficient, is one of the important parameters that determine the impact of aerosols on radiative forcing.Figure 7c illustrates the daily mean variation of surface SSA at VC along with columnar SSA (from AERONET) at adjacent urban center Kanpur (26.30 N,80.31 E). Between January and March, VC and Kanpur SSA were in a similar range with values ranging between 0.7 and 0.95.However, in the other months VC SSA values were mostly less than 0.8 compared to Kanpur columnar SSA.When SSA<0.9, aerosol significantly heats the atmosphere and reduces solar radiation at the surface, thus causing large impact on regional climate and the hydrological cycle (Ramanathan et al., 2001a;Krishnan and Ramanathan, 2002;Menon et al., 2002).
Figure 8 shows the diurnal variation of aerosol absorption, scattering coefficient, along with SSA for VC and the highway.The aerosol scattering and RH absorption coefficient showed a similar diurnal pattern at VC and the highway, with slightly higher values observed at highway.SSA values were observed to be high in the afternoon Introduction

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Full time between 12:00 and 15:00 LT for both the VC and the highway locations even though the RH was observed very low.During noon time secondary aerosol production through photochemical processes may be enhance light-scattering, which may reflected in high SSA (Yan et al., 2008).Further SSA showed decreasing trend in evening hours and then increased towards night time.The absorbing aerosols (BC) are emitted directly from combustion sources (cook stoves, vehicles), whereas some of the scattering aerosols are formed by gas to particle conversion process (Lyamani et al., 2010).This delay in the formation processes of absorbing and scattering aerosol and an increase in BC emission from cook stoves and vehicles may cause the dip in SSA in the evening hours.Similar processes should also effect morning peak emission hours, however the SSA did not show any dip, and this need further investigation.

Absorption Angstrom exponent
It has been shown earlier (Kirchstetter et al., 2004) that the spectral dependence of light absorption can be used to distinguish aerosols originating from fossil fuel and biomass fuel combustion.The presence of brown carbon (light absorbing OC mainly from biomass combustion) enhances the aerosol light absorption in the blue and the ultraviolet region (λ<600 nm).Understanding the spectral dependence of aerosols is important in order to properly account for their absorption in radiative transfer models.Figure 9a and b show the normalized aerosol light absorption of aerosol at highway and the VC during cooking and non-cooking hours.Also shown in the figure are our observed aethalometer response (from Sect.2.3) to biomass (wood in cookstove) and fossil fuel (diesel) combustion aerosol, along with the previously published (Kirchstetter et al., 2004) observations.Clearly distinct aerosol light absorption pattern can be seen for biomass and fossil fuel sources aerosol.Both published and observed Aethalometer response data indicate that the normalized aerosol light absorption at 370 nm is ∼5 times higher compared to the 700 nm for biomass combustion sources and ∼2 times higher for fossil fuel combustion sources.Aerosol light absorption falling in between the two extremes of biomass and fossil fuel absorption pattern will be indicative of 21330 Introduction

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Full mixing of aerosol from the two sources.Normalized aerosol light absorption at both VC (Fig. 9b) and the highway (Fig. 9a) location indicates that the aerosol sources are influenced by both biomass and fossil fuel sources; with VC normalized aerosol light absorption falling closer to pure biomass absorption line, suggesting higher contribution of biomass aerosol.Interestingly, at the highway aerosol light absorption showed enhanced absorption in shorter wavelength during cooking hours compare to noncooking hours, strongly suggesting influence of biomass cooking activity on highway aerosol.During non-cooking hours the normalized aerosol light absorption at highway was closer to pure fossil fuel absorption line indicating the dominance of fossil fuel (diesel) generated aerosol.
Several studies have found that aerosols originating from fossil fuel combustion show weaker dependence on spectral light absorption, with the absorption Angstrom exponent (AAE) value close to 1 (Bergstrom et al., 2007;Kirchstetter et al., 2004).However for aerosol emitted from biomass burning, the values of the AAE have been reported between 1.5 and 3; a value of 2 often considered as a mean (Bergstrom et al., 2007;Kirchstetter et al., 2004).An AAE value between 1 and 2 could be indicative of aerosol of mixed origin, i.e., fossil and biomass fuel.The mean AAE values for the VC and the highway are found as 1.81 and 1.61, respectively.It is understandable that the lower value was observed at the highway since fossil fuel contribution was higher there compared to other locations.The higher value observed at the VC is due to high contribution of aerosol from biomass combustion sources, as almost all households use biomass as cooking fuel.The AAE values at VC showed a similar diurnal pattern as BC (Fig. 10), with two prominent peaks -one in the morning hours of 06:00-09:00 LT and the other during the evening hours of 17:00-20:00 LT.BC peaks depend on sources and meteorology conditions, whereas the AAE peaks indicate relatively different contributions from sources during that time.Peak values of AAE at VC during cooking hours reached between 2.0 and 2.2, suggesting that biomass contribution was most dominant during this period.The major biomass burning activities during this time were observed to be cooking and winter outdoor fires.The highway AAE showed slight Introduction

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Full diurnal variation with values in the range of 1.4-1.7.The highway AAE peaks were not sharp but the values increased slightly during cooking hours, indicating some influence from cooking.However, the AAE range suggests that there was a contribution from biomass sources.
5 Local to regional scale linkages

Vertical variations and transport of aerosol
The fundamental mechanism for local to regional scale propagation of pollution is to vertically transport (e.g.pumping by cumulus convection) from the surface layer to the free troposphere above, then from there carried by faster winds to other regions.The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides high-resolution vertical distribution of aerosol and clouds and offers a unique opportunity to study vertical transport of aerosol.The CALIPSO lidar instrument known as CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) measures the depolarized aerosol back-scattered light at two wavelengths (532 and 1064 nm). Figure 11 shows the monthly mean CALIOP LIDAR level-2 extinction profiles from the grid (26-
During the monsoon season (June -September), air flow in the lower troposphere is predominantly westerly over India, which brings a large influx of moist air from the Arabian Sea.During the post monsoon season (October-November) the westerly flow weakens in the lower troposphere and the easterly flow sets in.From the postmonsoon to the dry (winter) season (December-February), the daily mean surface temperatures gradually decreases, reaching minimum values in the dry season.Fair weather conditions with clear skies and dry conditions exist during the dry season.As shown in Fig. 11 for the post-monsoon season, the aerosols were mostly confined within ∼2 km from the surface with maximum seasonal extinction coefficient value of ∼0.5 km −1 (observed during the month of November at ∼0.5 km altitude).Almost no Introduction

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Regional scale correlations
Aerosol optical depth (AOD) is a measure of the columnar extinction of light due to aerosol and is also measure of the total number of aerosol in the column.The vast IGP region has higher AOD values than the rest of India during all seasons (Ramanathan and Ramana, 2005;Ramana et al., 2004;Chung et al., 2010).MODIS (Moderateresolution Imaging Spectroradiometer) level-3 AOD data was used to quantify aerosol column content at SVI 1 and regional mean of IGP (denoted as "IGP MODIS").The region considered for IGP MODIS is shown as dashed line in Fig. 1. Figure 12  two prominent peaks -during the winter (December-January) and the pre-monsoon period (March-May).The winter peak is attributed to biomass burning and anthropogenic activities, whereas the pre-monsoon peak is influenced by dust aerosol from the western Thar Desert (Prasad et al., 2007).Aerosol during winter is found to be of a highly absorbing nature (Tripathi et al., 2005;Ganguly et al., 2009).
The NASA AERONET began a four-year intensive field campaign on April 2008, called TIGERZ, to measure aerosol microphysical and optical properties over India.We considered mean of six TIGERZ AERONET stations (shown in Fig. 1) data in IGP region (denoted as "IGP AERONET") to study local to regional aerosol propagation, by inter-comparing aerosol column optical properties between Kanpur (local) vs. IGP AERONET.Errors in AERONET SSA and AAOD were estimated to be high for lower AOD values and dependent on solar zenith angles (Dubovik et al., 2002).For this study, we consider level-1.5 data points as valid for AOD 675 nm >0.2 and solar zenith angle between 45 • -75 • during November 2009-May 2010.
Figure 13a-f illustrates the comparison between local to regional scale AOD, SSA, AAOD, Angstrom exponent of the AOD (AE), and Angstrom exponent of AAOD (AAE c ). MODIS AOD at SVI 1 was correlated with IGP MODIS AOD with R 2 = 0.72 and slope = 0.97 (Fig. 13a).Similarly, AERONET AOD at Kanpur (local scale) was correlated with IGP AERONET AOD with R 2 = 0.62 and slope = 0.92 (Fig. 13b).We observed similar correlation between local (SVI 1) to IGP MODIS AOD for individual months (Fig. 14).This indicates that the column aerosol content was symmetrically spread over the region during all seasons.The AE is usually used to describe the spectral dependence of the aerosol optical depth on wavelength.The AE is a useful quantity to assess the particle size of atmospheric aerosol, ranging from 4 for very small particles (AE >1 for fine particle dominance) to 0 for very large particles (AE <1 for coarse particle dominance).In the present study AE was calculated by the negative slope of AOD vs. wavelength in a log-log plot (for wavelengths 437 to 1020 nm).Local scale AE was correlated with IGP AERONET AE with R 2 = 0.79 and slope = 0.89 (Fig. 13c), indicating that particle dominance -either fine or coarse -is identical with Introduction

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Full the regional scale.The local scale SSA was correlated with the IGP AERONET SSA with R 2 = 0.52 and slope = 1.01 (Fig. 13d), indicating that the relative contribution of scattering and absorbing aerosol haave a similar fraction at the regional and the local scale.AAE c is a good indicator of sources of absorbing aerosols.AAE c is observed to be near 3 for dust aerosols, near 1 for urban and industrial aerosols, and greater than 1 for biomass aerosols (Bergstrom et al., 2007;Russell et al., 2010).In the present study AAE c was calculated by the negative slope of AAOD vs. wavelength in a log-log plot (for wavelengths 437 to 1020 nm).The local scale AAE c correlated with IGP AERONET AAE c with R 2 = 0.52 and slope = 1.06 (Fig. 13f), indicating that local to regional sources of observing aerosols are similar.
The observed AE of the IGP AERONET was in the range of 0.1-1.6 indicating varying aerosol compositions, including dust domination to fine particles from biomass, urban and industrial sources.Particularly, during April-May 2010, AE was in the range of 0.1-0.8indicating dust influence, perhaps due to soil erosion or dust transport from neighbouring desert regions (Fig. 15).Prasad et al. (2007) reported similar AE values during April-June over the IGP region and AE <0.2 for a high dust event.The wavelength-dependence of the absorption of mineral dust depends on its composition, primarily hematite and certain clays.The AAE of Saharan dust particles was in the range of 1-2 (Collaud Coen et al., 2004).The results of this study show few data points with AE<0.2 and AAE >1, indicating that occasionally IGP has regionally influenced dust transport.The high occurrence of AE >1 and AAE >1 values suggests that the IGP region is mainly influenced by urban and biomass sources (Fig. 15).

Regional scale atmospheric radiative forcing
The Indian Ocean Experiment (INDOEX) documented for the first time (Ramanathan et al., 2001a) the haze-induced reduction in surface solar radiation and large atmospheric absorption at the regional scale and its importance in the hydrological cycle.Regionally, the absorbing haze reduced surface solar radiation by an amount comparable to 50 % of the total ocean heat flux, and nearly doubled the lower tropospheric solar heat-21335 Introduction

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Full ing (Ramanathan et al., 2001) over the Indian Ocean during December to April.The haze-induced reduction in surface solar radiation (surface forcing at −23 W m −2 ) is 3 times as large as the reflected solar radiation at TOA (TOA forcing at −7 W m −2 ) for clear skies and a consequence of large atmospheric absorption (Ramanathan et al., 2001).However, the haze over the Indian Ocean is a layer of pollutants and particles from natural and anthropogenic sources that are transported from nearby continental land regions.To quantify haze influence on regional and local climate, several observational studies were conducted over mainland regions.One such observation is a seasonal and diurnal average reduction in surface solar radiation observed about 32±5 W m −2 over the IGB, using data collected over Kathmandu, Nepal, for a threeyear mean (2001)(2002)(2003) in the months of October to May (Ramanathan and Ramana, 2005).
To quantify clear sky atmospheric aerosol radiative forcing in the IGP region, cloudscreened monthly mean Kanpur AERONET measured spectral AOD, spectral SSA, column water vapor, ozone, monthly CALIPSO extinction profiles and solar zenith angle were used as inputs to the Monte Carlo Aerosol Cloud Radiation (MACR) model.The MACR is a photon transport radiative transfer algorithm described by Podgorny et al. (2000).Several case studies have proven that MACR calculations had a good agreement with observations (Ramanathan et al., 2001a(Ramanathan et al., , 2007;;Ramana and Ramanathan, 2006).The observed monthly mean of 674 nm AOD was in the range of 0.35-0.65,with a maximum of ∼0.65 being observed in April and May 2010 and a minimum of ∼0.35 observed in March 2010 (Fig. 16).The SSA was observed at a minimum of ∼0.83 at 674 nm in April 2010 (Fig. 16).Calculated clear sky atmospheric aerosol forcing efficiencies were between +41 W m −2 and +66 W m −2 , SSA at 0.92 to 0.83 at 670 nm wavelength, respectively (Fig. 16).Maximum forcing efficiencies were observed in April.Clear-sky atmospheric aerosol forcing was in the range of +22 W m −2 to +42 W m −2 with a mean of +29 W m −2 (Fig. 16).The present study estimated atmospheric aerosol forcing values are within the range of reported values for the IGP region by Dey and Tripathi (2008) and Ramana et al., (2004).Introduction

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Conclusions
Most of the earlier BC studies in the region dealt with the urban environment and do not accurately represent the rural emission scenario.The present study reports on ambient aerosol optical characteristics in rural IGP locations.The ambient BC concentration at the Project Surya village was observed in the range of 3.2-56 µg m −3 .The BC concentration reached the maximum during the winter, and gradually decreased towards the pre-monsoon period.Rural BC concentrations were well within the limits of observed urban BC, suggesting that rural emissions play as significant role as urban emissions in regional climate.The ambient BC diurnal variation based on cooking patterns indicates that BC emissions from cook stoves are a major source of ambient BC.This is further validated by Rehman et al. ( 2011) from aerosol absorption properties and EC/OC fraction.The observed Angstrom exponent of the absorption coefficient (AAE) for SVI 1 was greater than 1.6 in all four seasons, suggesting a significant biomass contribution.The SSA was observed in the range 0.7-0.9 at the surface, which indicates a highly absorbing aerosol.The estimated mean aerosol atmospheric forcing was observed at 29 W m −2 .Local to regional scale column optical properties were found to be well correlated, indicating that emission contributions from biomass and fossil fuel have similar influence in the whole region.Introduction

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Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | s observational campaign was started on 15 October 2009 in a typical Indian rural village ( Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 3.2 Diurnal variation of BC in the SVI 1 Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 4 Characteristics of solar absorption by BC Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | aerosol layer was observed above ∼3 km during the post-monsoon season.The observed BC concentration at the surface was 13.8±7.6µg m −3 in post monsoon season.During the dry season, low level inversions leads to shallower aerosol layer compared to the pre-monsoon season resulting in accumulation of pollutants near the surface.This is clearly seen in Fig.11; the extinction coefficient reached its highest values of ∼1.7 km −1 at ∼0.5 km altitude during the month of December in the dry season.Also no aerosol layer were observed above ∼2 km in the winter season compared to ∼3 km for post-monsoon season further suggesting suppression of vertical transport of aerosol layer during winter.This is reflected in the surface BC concentration which reaches a maximum (16.3±8.8 µg m −3 ) in the winter.During the pre-monsoon season (March-May) the weather is very hot and dry, with deep boundary layer and maximum daytime temperature reaching as high as 45 • C.During this season, dust content in the atmosphere is high, as well as open burning activities (forest fires and crop residue burning) are common.The monthly mean extinction profiles indicate that the aerosol layer is transported as high as ∼5 km due to vertical mixing and convection, resulting lower BC concentration (12.7±5 µg m −3 ) at the surface.
illustrates the daily variation of AOD at SVI 1 (MODIS) and Kanpur (AERONET).The SVI 1 AOD showed a similar trend with neighbouring (130 km away from SVI 1) urban centre Kanpur.Comparison between SVI 1 AOD and Kanpur AOD (plot not shown here) yielded slope of 0.89 and R 2 of 0.55.Seasonal AOD variations in the IGP region show Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 13 .
Fig. 13.Comparison of daily mean IGP MODIS and IGP AERONET to local (Kanpur and SVI 1) scale aerosol optical properties for the period November 2009 to May2010.AOD represents aerosol optical depth , AAOD represents absorption aerosol optical depth, SSA represents single scattering albedo, AE represents Angstrom exponent of AOD and AAE c represents Angstrom exponent of AAOD.IGP AERONET was calculated from the mean of six AERONET sites located in India and Nepal (see Fig. 1).The IGP MODIS represents the mean of the AOD over the region shown as dashed line in Fig. 1.

Fig. 15 .
Fig. 15.Scatter plot of IGP AERONET daily mean Angstrom exponent of AOD (AE) and daily mean Angstrom exponent of AAOD (AAE) for the IGP region.IGP AERONET was calculated from the mean of six AERONET sites located in India and Nepal (see Fig. 1).
The distance between the NEV and VC sites is approximately 250m.At NEV, real-time BC concentration measurements were started on 15 October 2009 us-