[1] The Indo-Gangetic Plain (IGP) encompasses a vast area, (accounting for $21% of the land area of India), which is densely populated (accommodating $40% of the Indian population). Highly growing economy and population over this region results in a wide range of anthropogenic activities. A large number of thermal power plants (most of them coal fed) are clustered along this region. Despite its importance, detailed investigation of aerosols over this region is sparse. During an intense field campaign of winter 2004, extensive aerosol and atmospheric boundary layer measurements were made from three locations: Kharagpur (KGP), Allahabad (ALB), and Kanpur (KNP), within the IGP. These data are used (1) to understand the regional features of aerosols and BC over the IGP and their interdependencies, (2) to compare it with features at locations lying at far away from the IGP where the conditions are totally different, (3) to delineate the effects of mesoscale processes associated with changes in the local atmospheric boundary layer (ABL), (4) to investigate the effects of long-range transport or moving weather phenomena in modulating the aerosol properties as well as the ABL characteristics, and (5) to examine the changes as the season changes over to spring and summer. Our investigations have revealed very high concentrations of aerosols along the IGP, the average mass concentrations (M T ) of total aerosols being in the range 260 to 300 mg m À3 and BC mass concentrations (M B ) in the range 20 to 30 mg m À3 (both $5 to 8 times higher than the values observed at off-IGP stations) during December 2004. Despite, BC constituted about 10% to the total aerosol mass concentration, a value quite comparable to those observed elsewhere over India for this season. The dynamics of the local atmospheric boundary layer (ABL) as well as changes in local emissions strongly influence the diurnal variations of M T and M B , both being inversely correlated with the mixed layer height (Z i ) and the ventilation coefficient (V c ). The share of BC to total aerosols is highest ($12%) during early night and lowest ($4%) in the early morning hours. While an increase in the V c results in a reduction in the concentration almost simultaneously, an increase in Z imax has its most impact on the concentration after $1 day. Accumulation mode aerosols contributed $90% to the aerosol concentration at ALB, $77 % at KGP and 74% at KNP. The BC mass mixing ratio was $10% over all three locations and is comparable to the value reported for Trivandrum, a tropical coastal location in southern India. This indicates presence of submicron aerosols species other than BC (such as sulfate) over KGP and KNP. A cross-correlation analysis showed that the changes in M B at KGP is significantly correlated with those at KNP, located $850 km upwind, and ALB after a delay of $7 days, while no such delay was seen between ALB and KNP. Back trajectory analyses show an enhancement in M B associated with trajectories arriving from west, the farther from to the west they arr...

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Abstract. The Ångström exponent, α, is often used as a qualitative indicator of aerosol particle size. In this study, aerosol optical depth (AOD) and Ångström exponent (α) data were analyzed to obtain information about the adequacy of the simple use of the Ångström exponent for characterizing aerosols, and for exploring possibilities for a more efficient characterization of aerosols. This was made possible by taking advantage of the spectral variation of α, the so-called curvature. The data were taken from four selected AERONET stations, which are representative of four aerosol types, i.e. biomass burning, pollution, desert dust and maritime. Using the least-squares method, the Ångström-α was calculated in the spectral interval 340–870 nm, along with the coefficients α1 and α2 of the second order polynomial fit to the plotted logarithm of AOD versus the logarithm of wavelength, and the second derivative of α. The results show that the spectral curvature can provide important additional information about the different aerosol types, and can be effectively used to discriminate between them, since the fine-mode particles exhibit negative curvature, while the coarse-mode aerosols positive. In addition, the curvature has always to be taken into account in the computations of Ångström exponent values in the spectral intervals 380–440 nm and 675–870 nm, since fine-mode aerosols exhibit larger α675–870 than α380–440 values, and vice-versa for coarse-mode particles. A second-order polynomial fit simulates the spectral dependence of the AODs very well, while the associated constant term varies proportionally to the aerosol type. The correlation between the coefficients α1 and α2 of the second-order polynomial fit and the Ångström exponent α, and the atmospheric turbidity, is further investigated. The obtained results reveal important features, which can be used for better discriminating between different aerosol types.

Abstract. Aerosols have a significant regional and global effect on climate, which is about equal in magnitude but opposite in sign to that of greenhouse gases. Nevertheless, the aerosol climatic effect changes strongly with space and time because of the large variability of aerosol physical and optical properties, which is due to the variety of their sources, which are natural, and anthropogenic, and their dependence on the prevailing meteorological and atmospheric conditions. Characterization of aerosol properties is of major importance for the assessment of their role for climate. In the present study, 3-year AErosol RObotic NETwork (AERONET) data from ground-based sunphotometer measurements are used to establish climatologies of aerosol optical depth (AOD) and Ångström exponent α in several key locations of the world, characteristic of different atmospheric environments. Using daily mean values of AOD at 500 nm (AOD500) and Ångström exponent at the pair of wavelengths 440 and 870 nm (α 440–870), a discrimination of the different aerosol types occurring in each location is achieved. For this discrimination, appropriate thresholds for AOD500 and α 440–870 are applied. The discrimination of aerosol types in each location is made on an annual and seasonal basis. It is shown that a single aerosol type in a given location can exist only under specific conditions (e.g. intense forest fires or dust outbreaks), while the presence of well-mixed aerosols is the accustomed situation. Background clean aerosol conditions (AOD500<0.06) are mostly found over remote oceanic surfaces occurring on average in ~56.7% of total cases, while this situation is quite rare over land (occurrence of 3.8–13.7%). Our analysis indicates that these percentages change significantly from season to season. The spectral dependence of AOD exhibits large differences between the examined locations, while it exhibits a strong annual cycle.

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential "hotspots" of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing "where and when" forest fires will most likely occur.

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[1] Aerosol measurements over the tropical urban site of Hyderabad, India, provide a way of determining the variability of the aerosol characteristics over a duration of 1 year (October 2007 to September 2008. The meteorological pattern over India, mainly driven by the regional monsoons, has a great effect on the amount and size distribution of the aerosols. Higher aerosol optical depth (AOD) values are observed in premonsoon, while the variability of the Å ngström exponent (a) seems to be more pronounced, with higher values in winter and premonsoon and lower values in the monsoon periods. The AOD at 500 nm (AOD 500 ) is very large over Hyderabad, varying from 0.46 ± 0.17 in postmonsoon to 0.65 ± 0.22 in premonsoon periods. A discrimination of the different aerosol types over Hyderabad is also attempted using values of AOD 500 and a 380 -870 . Such discrimination is rather difficult to interpret since a single aerosol type can partly be identified only under specific conditions (e.g., anthropogenic emissions, biomass burning or dust outbreaks), while the presence of mixed aerosols, without dominance of the coarse or accumulation mode, is the usual situation. According to the analysis the three individual components of differing origin, composition and optical characteristics are (1) an urban/industrial aerosol type composed of aerosols produced locally and all year round by combustion activities in the city or long-range transported (mainly in spring) biomass burning, (2) an aerosol type of mineral origin raised by the wind in the deserts (mainly in premonsoon) or constituting coarse-mode aerosols under high relative humidity conditions mainly in the monsoon period, and (3) an aerosol type with a marine influence under background conditions occurring in monsoon and postmonsoon periods. Nevertheless, the mixed or undetermined aerosol type dominates with percentages varying from 44.3% (premonsoon) to 72.9% (postmonsoon). Spectral AOD and a data are analyzed to obtain information about the adequacy of the simple use of the Å ngström exponent for characterizing the aerosols. This is achieved by taking advantage of the spectral variation of lnAOD versus lnl, the so-called curvature. The results show that the spectral curvature can be effectively used as a tool for aerosol types discrimination, since the fine-mode aerosols exhibit negative curvature, while the coarse-mode particles are positive.

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