Spatial distribution of aerosol black carbon over India during pre-monsoon season

Aerosol black carbon (BC) mass concentrations ([BC]), measured continuously during a mutli-platform field experiment, Integrated Campaign for Aerosols gases and Radiation Budget (ICARB, March–May 2006), from a network of eight observatories spread over geographically distinct environments of India, (which included five mainland stations, one highland station, and two island stations (one each in Arabian Sea and Bay of Bengal)) are examined for their spatio-temporal characteristics. During the period of study, [BC] showed large variations across the country, with values ranging from 27 μg m^?3 over industrial/urban locations to as low as 0.065 μg m^?3 over the Arabian Sea. For all mainland stations, [BC] remained high compared to highland as well as island stations. Among the island stations, Port Blair (PBR) had higher concentration of BC, compared to Minicoy (MCY), implying more absorbing nature of Bay of Bengal aerosols than Arabian Sea. The highland station Nainital (NTL), in the central Himalayas, showed low values of [BC], comparable or even lower than that of the island station PBR, indicating the prevalence of cleaner environment over there. An examination of the changes in the mean temporal features, as the season advances from winter (December–February) to pre-monsoon (March–May), revealed that: (a) Diurnal variations were pronounced over all the mainland stations, with an afternoon low and a nighttime high; (b) At the islands, the diurnal variations, though resembled those over the mainlands, were less pronounced; and (c) In contrast to this, highland station showed an opposite pattern with an afternoon high and a late night or early morning low. The diurnal variations at all stations are mainly caused by the dynamics of local Atmospheric Boundary Layer (ABL). At the entire mainland as well as island stations (except HYD and DEL), [BC] showed a decreasing trend from January to May. This is attributed to the increased convective mixing and to the resulting enhanced vertical dispersal of species in the ABL. In addition, large short-period modulations were observed at DEL and HYD, which appeared to be episodic. An examination of this in the light of the MODIS-derived fire count data over India along with the back-trajectory analysis revealed that advection of BC from extensive forest fires and biomass-burning regions upwind were largely responsible for this episodic enhancement in BC at HYD and DEL.     

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.     

Soil surface nitrogen losses from agriculture in India: A regional inventory within agroecological zones (2000–2001)

We present soil surface nitrogen (N) budgets for the agricultural sector of India, calculated as inputs minus outputs over 21 agroecological zones (AEZ), for 2000–2001. Nearly 35.4 Tg N was input from different sources, with output from harvested crops of about 21.2 Tg N. Soil surface N balance for agricultural lands showed a surplus of about 14.4 Tg. Livestock manure constituted 44% of total inputs, followed by 32.5% from inorganic fertilizer, 11.9% from atmospheric deposition and 11.6% from N fixation. Though the N balance was negative in some states, due to aggregation of states in agroecological regions, all regions showed surplus N loads, with a range of about 19–110 kg/ha. The lowest loads were found for AEZ 17 in the Eastern Himalaya, with 19 kg/ha surplus, and the highest surplus N load in AEZ 7 with 111 kg/ha in Deccan plateau and the Eastern Ghats. Temporal trends in fertilizer consumption from 1950–2000 for India suggested a massive increase of ～47-fold, whereas production of major crops, rice, wheat and maize, increased nearly ～4.0-, 10- and 6-fold, respectively. Fertilizer consumption patterns were highly concentrated in Tamilnadu (204.6 kg/ha), Haryana (132.0 kg/ha) and Punjab (148.6 kg/ha). The paper addresses the role of agricultural intensification and its implications for water quality in agroecological regions of India.     

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.     

Trends in food production and nitrous oxide emissions from the agriculture sector in India: environmental implications

We studied trends in food production and nitrous oxide emissions from India's agricultural sector between 1961 and 2000. Data from Food and Agricultural Statistics (FAO) have been gathered covering production, consumption, fertilizer use and livestock details. IPCC 1996 revised guidelines were followed in studying the variations in N₂O-N emissions. Results suggest that total N₂O-N emissions (direct, animal waste and indirect sources) increased ~6.1 times from ~0.048 to ~0.294 Tg N₂O-N, over 40 years. Source-wise breakdown of emissions from 1961–2000 indicated that during 1961 most of the N₂O-N inputs were from crop residues (61%) and biological nitrogen fixation (25%), while during 2000 the main sources were synthetic fertilizer (~48%) and crop residues (19%). Direct emissions increased from ~0.031 to ~0.183 Tg. It is estimated that ~3.1% of global N₂O-N emissions comes from India. Trends in food production, primarily cereals (rice, wheat and coarse grains) and pulses, and fertilizer consumption from 1961–2000 suggest that food production (cereals and pulses) increased only 3.7 times, while nitrogenous fertilizer consumption increased ~43 times over this period, leading to extensive release of nitrogen to the atmosphere. From this study, we infer that the challenge for Indian agriculture lies not only in increasing production but also in achieving production stability while minimizing the impact to the environment, through various management and mitigation options.     

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.