MODIS derived fire characteristics and aerosol optical depth variations during the agricultural residue burning season, north India.

Agricultural residue burning is one of the major causes of greenhouse gas emissions and aerosols in the Indo-Ganges region. In this study, we characterize the fire intensity, seasonality, variability, fire radiative energy (FRE) and aerosol optical depth (AOD) variations during the agricultural residue burning season using MODIS data. Fire counts exhibited significant bi-modal activity, with peak occurrences during April-May and October-November corresponding to wheat and rice residue burning episodes. The FRE variations coincided with the amount of residues burnt. The mean AOD (2003-2008) was 0.60 with 0.87 (+1σ) and 0.32 (-1σ). The increased AOD during the winter coincided well with the fire counts during rice residue burning season. In contrast, the AOD-fire signal was weak during the summer wheat residue burning and attributed to dust and fossil fuel combustion. Our results highlight the need for 'full accounting of GHG's and aerosols', for addressing the air quality in the study area.

Fire risk evaluation using multicriteria analysis--a case study.

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.

Spatial patterns in vegetation fires in the Indian region.

In this study, we used fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to characterize spatial patterns in fire occurrences across highly diverse geographical, vegetation and topographic gradients in the Indian region. For characterizing the spatial patterns of fire occurrences, observed fire point patterns were tested against the hypothesis of a complete spatial random (CSR) pattern using three different techniques, the quadrat analysis, nearest neighbor analysis and Ripley's K function. Hierarchical nearest neighboring technique was used to depict the 'hotspots' of fire incidents. Of the different states, highest fire counts were recorded in Madhya Pradesh (14.77%) followed by Gujarat (10.86%), Maharastra (9.92%), Mizoram (7.66%), Jharkhand (6.41%), etc. With respect to the vegetation categories, highest number of fires were recorded in agricultural regions (40.26%) followed by tropical moist deciduous vegetation (12.72), dry deciduous vegetation (11.40%), abandoned slash and burn secondary forests (9.04%), tropical montane forests (8.07%) followed by others. Analysis of fire counts based on elevation and slope range suggested that maximum number of fires occurred in low and medium elevation types and in very low to low-slope categories. Results from three different spatial techniques for spatial pattern suggested clustered pattern in fire events compared to CSR. Most importantly, results from Ripley's K statistic suggested that fire events are highly clustered at a lag-distance of 125 miles. Hierarchical nearest neighboring clustering technique identified significant clusters of fire 'hotspots' in different states in northeast and central India. The implications of these results in fire management and mitigation were discussed. Also, this study highlights the potential of spatial point pattern statistics in environmental monitoring and assessment studies with special reference to fire events in the Indian region.

Biophysical and anthropogenic controls of forest fires in the Deccan Plateau, India.

Forest fires constitute one of the most serious environmental problems in several forested regions of India. In the Indian sub-continent, relatively few studies have focused on the assessment of biophysical and anthropogenic controls of forest fires at a landscape scale and the spatial aspects of these relationships. In this study, we used fire count data sets from satellite remote sensing data covering 78 districts over four different states of the Deccan Plateau, India, for assessing the underlying causes of fires. Spatial data for explanatory variables of fires pertaining to topography, vegetation, climate, anthropogenic and accessibility factors have been gathered corresponding with fire presence/absence. A logistic regression model was used to estimate the probability of the presence of fires as a function of the explanatory variables. Results for fire area estimates suggested that, of the total fires covering 47,043km(2) that occurred during the year 2000 for the entire Indian region, 29.0% occurred in the Deccan Plateau, with Andhra Pradesh having 13.5%, Karnataka 14.7%, Kerala 0.1%, and Tamilnadu 1.15%. Results from the logistic regression suggest that the strongest influences on the fire occurrences were the amount of forest area, biomass densities, rural population density (PD), average precipitation of the warmest quarter, elevation (ELE) and mean annual temperature (MAT). Among these variables, biomass density (BD) and average precipitation of the warmest quarter had the highest significance, followed by others. These results on the best predictors of forest fires can be used both as a strategic planning tool to address broad scale fire risk concerns, and also as a tactical guide to help forest managers to design fire mitigation measures at the district level.

Case study of a dust storm over Hyderabad area, India: its impact on solar radiation using satellite data and ground measurements.

According to the Earth Observatory dust outbreaks are considered as natural hazards, which affect the ecosystems and human life. The main objective of this study is to assess and monitor the movement of aerosols and pollutants from local or other sources, both natural and anthropogenic, using a combination of ground-based monitoring and satellite data. The turbid and polluted atmosphere in the densely-populated area of Hyderabad, India is further degradated from dust outbreaks originated from Thar desert. A dust event occurred during 10th to 11th April 2006 in the northwest region of India; its plume substantially spreaded across the downwind direction affecting the study region. Using both irradiance measurements and satellite data this dust event is investigated. The analysis shows a significant change in Aerosol Optical Depth (AOD), Aerosol Index (AI) and aerosol-particle size during the dust event. The Aerosol Optical Depth in the dusty day is about 0.2 higher than the previous non-dusty days, while the Angström exponent rapidly decreases when the dust plume affected the study area. The surface PM concentrations show enhanced values during the dusty day directly influenced by the dust deposition. There is also a remarkable decrease in ground-reaching global radiation, UV erythemal (UV(ery)) and other irradiance components. The analysis suggested that the use of the diffuse-to-direct-beam ratio is the most appropriate parameter for the dust monitoring since its values at the longer wavelengths are not affected by the solar zenith angle.

Spatial distribution of forest fires and controlling factors in Andhra Pradesh, India using SPOT satellite datasets.

Fires are one of the major causes of forest disturbance and destruction in several dry deciduous forests of southern India. In this study, we use remote sensing data sets in conjunction with topographic, vegetation, climate and socioeconomic factors for determining the potential causes of forest fires in Andhra Pradesh, India. Spatial patterns in fire characteristics were analyzed using SPOT satellite remote sensing datasets. We then used nineteen different metrics in concurrence with fire count datasets in a robust statistical framework to arrive at a predictive model that best explained the variation in fire counts across diverse geographical and climatic gradients. Results suggested that, of all the states in India, fires in Andhra Pradesh constituted nearly 13.53% of total fires. District wise estimates of fire counts for Andhra Pradesh suggested that, Adilabad, Cuddapah, Kurnool, Prakasham and Mehbubnagar had relatively highest number of fires compared to others. Results from statistical analysis suggested that of the nineteen parameters, population density, demand of metabolic energy (DME), compound topographic index, slope, aspect, average temperature of the warmest quarter (ATWQ) along with literacy rate explained 61.1% of total variation in fire datasets. Among these, DME and literacy rate were found to be negative predictors of forest fires. In overall, this study represents the first statewide effort that evaluated the causative factors of fire at district level using biophysical and socioeconomic datasets. Results from this study identify important biophysical and socioeconomic factors for assessing 'forest fire danger' in the study area. Our results also identify potential 'hotspots' of fire risk, where fire protection measures can be taken in advance. Further this study also demonstrate the usefulness of best-subset regression approach integrated with GIS, as an effective method to assess 'where and when' forest fires will most likely occur.

Seasonal variations of PM10 and PM2.5 particles loading over tropical urban environment.

The extent to which airborne particles penetrate into the human respiratory system is determined mainly by their size, with possible health effects. The research over the scientific evidence of airborne particles to adverse health effects has been intensified in recent years. In the present study particulate matter (PM), PM10 and PM2.5 have been analysed from Quartz Crystal Microbalance (QCM) impactor for the period of January to December over the tropical urban environment, Hyderabad, India. The diurnal variation of PM, PM10 and PM2.5 shows a primary peak at 03:00 local time (LT) and then secondary peak at 10:00 LT followed by a nocturnal peak at 20:00 LT. Seasonal variations of PM, PM10 and PM2.5 suggest that the concentrations have been observed to be maximum during winter and minimum during monsoon. Average values of PM10 and PM2.5 concentrations have been found to be -26 microgm(-3) and -18 microgm(-3) under ambient conditions over the study area. The results suggest that the PM10 concentrations were found to be well below the standards set by several environmental agencies whereas PM2.5 concentrations were found to be quite critical.

Factors influencing aerosol characteristics over urban environment.

Atmospheric aerosols are an important contributing factor to turbidity in urban areas besides having impact on health. Aerosol characteristics show a high degree of variability in space and time as nthropogenic share of total aerosol loading is quite substantial and is essential to monitor the aerosol features over long time scales. In the present study extensive observations of columnar aerosol optical depth (AOD), total columnar ozone (TCO) and precipitable water content (PWC) have been carried over a tropical urban city of Hyderabad, India. Significant variations of AOD have been observed during course of the day with low values of AOD during morning and evening hours and high values during afternoon hours. Spectral variation of AOD exhibits high AOD at smaller wavelengths and vice versa except a slight enhancement in AOD at 500 nm. Anomalies in AOD, particulate matter and black carbon concentrations have been observed during May, 2003. Back trajectory analysis of air mass during these episodes suggested variation in air mass trajectories. Analysis of the results suggests that air trajectories from land region north of study area cause high loading of atmospheric aerosols. The results are discussed in the paper.

Climatic controls of vegetation vigor in four contrasting forest types of India--evaluation from National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer datasets (1990-2000).

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R2=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.

Shortwave radiative forcing efficiency of urban aerosols--a case study using ground based measurements.

Aerosols reduce the surface reaching solar flux by scattering the incoming solar radiation out to space. Various model studies on climate change suggest that surface cooling induced by aerosol scattering is the largest source of uncertainty in predicting the future climate. In the present study measurements of aerosol optical depth (AOD) and its direct radiative forcing efficiency has been presented over a typical tropical urban environment namely Hyderabad during December, 2003. Measurements of AOD have been carried out using MICROTOPS-II sunphotometer, black carbon aerosol mass concentration using Aethalometer, total aerosol mass concentration using channel Quartz Crystal Microbalance (QCM) Impactor Particle analyser and direct normal solar irradiance using Multifilter Rotating Shadow Band Radiometer (MFRSR). Diurnal variation of AOD showed high values during afternoon hours. The fraction of BC estimated to be approximately 9% in the total aerosol mass concentration over the study area. Results of the study suggest -62.5 Wm(-2) reduction in the ground reaching shortwave flux for every 0.1 increase in aerosol optical depth. The results have been discussed in the paper.

Regional inventory of soil surface nitrogen balances in Indian agriculture (2000-2001).

Nitrogen regulates several ecological and biogeochemical processes and excess reactive nitrogen in the environment can lead to pollution problems, including the deterioration of air quality, disruption of forest processes, acidification of lakes and streams, and degradation of coastal waters. Much of the excess nitrogen inputs are related to food and energy production. An important step to understanding the sources of nitrogen and ultimately defining solutions to excess nitrogen is to describe the geographic distribution of agricultural nitrogen contributions from different regions. In this study, soil surface nitrogen loads were quantified for different states of India for the period 2000-2001. Nearly 35.4 Tg of nitrogen has been estimated as inputs from different sources, with output nitrogen from harvested crops of about 21.20 Tg. The soil surface nitrogen balance, estimated as inputs minus outputs, is found to be about 14.4 Tg surplus from the agricultural land of India. Livestock manure constituted a major percentage of total inputs (44.06%), followed by inorganic fertilizer (32.48%), atmospheric deposition (11.86%) and nitrogen fixation (11.58%). Nitrogen balance varied from deficit to surplus for different states. The highest nitrogen surplus was found in Uttar Pradesh (2.50 Tg) followed by Madhya Pradesh (1.83 Tg), Andhra Pradesh (1.79 Tg), etc. A negative nitrogen balance was found in Orissa (-0.01 Tg), Andaman Nicobar Islands (-0.32 Tg) and for some of the northeastern states. Major fertilizer consumption states were found to be Tamilnadu (204 kg/ha), Haryana (132 kg/ha), Punjab (148 kg/ha), followed by others. Similarly, nitrogen inputs from total livestock excretions were found to be high for Kerala (616 kg/ha), Jammu and Kashmir (389 kg/ha), Tamil Nadu (338 kg/ha), etc. The average nitrogen surplus of about 54 kg/ha observed for the agricultural land of the entire country of India is comparatively higher than the average surplus of about 31 kg/ha reported for European countries. These results, obtained from nutrient mass balance calculations, will be useful to formulate nutrient management plans relating to fertilizer usage, livestock management and for adopting some best management strategies at a state level in India.

Characterization of aerosols and its radiative impacts over urban and rural environments--a case study from Hyderabad and Srisailam.

In the troposphere anthropogenic aerosol emissions are increasing in recent decades, which can influence the earth's climate. The present study addresses the characterization of aerosols and their radiative impacts over urban (Hyderabad) and rural (Srisailam) environments by using aerosol optical depth (AOD) measurements from MICROTOPS-II sunphotometer. AOD measurements over the urban site showed high values compared to the rural site. Over the urban environment aerosol forcing at the surface is as high as -42 W m(-2) and at the top of the atmosphere (TOA) is +10 W m(-2) whereas at the rural environment aerosol forcing at the surface has been observed to be -11 W m(-2) and at TOA it is observed to be +5.7 W m(-2). The difference between TOA and the surface forcing over the urban environment is +32 W m(-2) and over the rural environment is +5.3 W m(-2), which shows the absorption capacity of the respective atmospheres.

Characterization of aerosols from biomass burning--a case study from Mizoram (Northeast), India.

Physical and optical properties of biomass burning aerosols in Northeastern region, India analyzed based on measurements made during February 2002. Large spatial extent of Northeastern Region moist tropical to moist sub-tropical forests in India have high frequency of burning in annual dry seasons. Characterization of resultant trace gases and aerosols from biomass burning is important for the atmospheric radiative process. Aerosol optical depth (AOD) observed to be high during burning period compared to pre- and post-burning days. Peak period of biomass burning is highly correlated with measured AOD and total columnar water vapor. Size distribution of aerosols showed bimodal size distribution during burning day and unimodal size distribution during pre- and post-burning days. Size distribution retrievals from biomass burning aerosols show dominance of accumulation mode particles. Weighted mean radius is high (0.22 microm) during burning period. Columnar content of aerosols observed to be high during burning period in addition to the drastic reduction of visibility. During the burning day Anderson sampler measurements showed dominance of accumulation mode particles. The diurnal averaged values of surface shortwave aerosol radiative forcing af biomass burning aerosols varies from -59 to -87 Wm(-2) on different days. Measured and modeled solar irradiances are also discussed in the paper.