Nature of Forest Fires in Uttarakhand:Frequency, Size and Seasonal Patterns in Relation to Pre-Monsoonal Environment

Assessment of forest fire emissions in Uttarakhand State, India, using Open Geospatial data and Google Earth Engine

In the recent past, forest fires have increased due to the changing climate pattern. It is necessary to analyse and quantify various gaseous emissions so as to mitigate their harmful effects on air pollution. Satellite remote sensing data provides an opportunity to study the greenhouse gases in the atmosphere. The multispectral sensor of the Tropospheric Monitoring Instrument (Sentinel-5) is capable of recording the reflectance of wavelengths vital for measuring the atmospheric concentrations of methane, formaldehyde, aerosol, carbon monoxide, etc., at a spatial resolution of 0.01°. The present study utilized the Google Earth Engine (GEE) platform to study the emissions caused by forest fires in four districts of Uttarakhand State of India, which witnessed unprecedented fires in April-May 2021. All the datasets were ingested in GEE, which has the capability to analyse large datasets without the need to download them. The pre-fire period chosen was September 2020; the fire period was February-May 2021, and the post-fire period was June 2021. The variables chosen were aerosol absorbing index (AAI), carbon monoxide (CO) and nitrogen dioxide (NO2). The climate parameter temperature (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) and precipitation (from Climate Hazards Group InfraRed Precipitation (CHIRPS) Pentad) were also studied for the period mentioned. The results indicate a different trend for emissions in each district. For AAI, maximum emissions were noted in district Nainital followed by Almora, Tehri Garhwal and Garhwal. For CO emissions, the most affected district was Almora followed by Nainital, Garhwal and Tehri Garhwal. For NO2 emissions, the most affected district was Garhwal, followed by Nainital, Tehri Garhwal and Almora. Delta Normalized Burn Ratio was computed from Sentinel data (difference of pre-fire and post-fire images) to assess the burnt area severity. The Delta Normalized Burn Ratio values observed that the district with the most burnt area is Garhwal, followed by Nainital, Almora and Tehri Garhwal. The elevated temperatures and scanty rainfall patterns regulated the intensity and duration of forest fire. Monitoring the gaseous emissions as a consequence of forest fire in the GEE platform is much easier and more convenient at a regional level. Such data is much needed for mitigation measures to be implemented in time.

Chir pine and banj oak responses to pre-monsoon drought across slope aspects and positions in Central Himalaya

The difference in maintaining a safety margin with regard to hydraulic conductance between pine and oak species influences their distribution in a region. Chir pine (Pinus roxburghii) and banj oak (Quercus leucotrichophora) are the principal species of Central Himalayan forests between 1000 and 2000 m elevations. Nearly 80% of annual precipitation of ~ 1400 mm in the region occurs during monsoon, from mid-June to September, whereafter droughts of varying length and intensity are common. The main objective of the study is to find out the responses of these two evergreen tree species to pre-monsoon (March to mid-June) water stress and topographical heterogeneity that occur in Central Himalaya. We measured soil and tree water potential and osmotic adjustment across five seasons on three slope positions, namely, hill base, mid-slope, and hill top, on north and south slope aspects. Chir pine showed an early response to pre-monsoon drought by restraining daily change in Ψ to 0.89 MPa, while predawn Ψ (Ψ_PD) was still moderate (isohydric tendency). In contrast, the daily reduction in Ψ of banj oak kept on increasing up to 1.49 MPa, despite severely low Ψ_PD (anisohydric tendency). In both tree species, Ψ was invariably lower on south aspect than north aspect and declined from hill base to hill top. Such responses to slope aspect and position, however, were relatively less apparent in chir pine, which tended to maintain a wide safety margin when under stress. As for soil Ψ, banj oak site retained monsoon rainwater more effectively than chir pine.

Batch and Continuous Fixed-Bed Lead Removal Using Himalayan Pine Needle Biochar: Isotherm and Kinetic Studies

Pine needle litter in Himalayan forests leads to forest fires, ground water recharge inhibition, soil acidification and contamination, and stops the growth of grass and plants. This study provides a possible solution for pine needle litter problem by converting it to biochar. Pine needle litter lying on the ground for approximately a month was collected from the Himalayan region. The pine needle litter biochars were generated using slow pyrolysis (residence time, 30 min; heating rate, 10 °C/min) at 350, 450, 550, 650, and 750 °C. Finally, pine needle litter biochar prepared at 550 °C (PNBC550) was selected for sorptive removal of aqueous lead both in batch and column studies. The PNBC550 was characterized for proximate and elemental compositions, crystallinity, surface area, morphology, and functional groups. A BET surface area of 230.9 m2/g was obtained for PNBC550. Batch sorption studies were carried out to study (1) the adsorption versus pH studies (at pH 2 to 7), (2) isotherms (at 10, 25, and 35 °C) to evaluate the temperature effect on the sorption efficiency, and (3) kinetics to reveal the effect of time, adsorbent dose, and initial concentration on the reaction rate. Increasing pyrolysis temperature raised lead sorption up to 550 °C. Lead adsorption increased considerably as pH rose from 2 to a maximum adsorption around pH 5 and above. The sorption data were fitted using different isotherm models and kinetic equations. The Langmuir adsorption capacity increased from 22.93 mg/g at 10 °C to 40.43 mg/g at 35 °C, showing that adsorption was endothermic. Fixed-bed studies were conducted at room temperature with an initial lead concentration of 7.85 mg/L and 4.0 g of PNBC550 at initial pH 5.0 and a flow rate of 3 mL/min. Desorption studies conducted under the same experimental conditions found about 90-93% lead recovery. Development of high-efficiency biochars for lead remediation provides a sustainable solution for the Himalayan pine needle litter problem. The biochars also possess the possible potential for aqueous removal of other metal cations.

Enhancement of carbon monoxide concentration in atmosphere due to large scale forest fire of Uttarakhand

The richly forested Indian state of Uttarakhand experienced widespread forest fires in April to May 2016. The current study examines dispersion of carbon monoxide (CO) from the source regions of forest fire to distant places, using the Lagrangian particle dispersion model, FLEXPART. Atmospheric Infrared Sounder (AIRS) observations revealed that CO columnar concentrations had increased by almost 28 percentage during 24 April to 02 May 2016 with respect to the previous non-burning period of April 2016 at Uttarakhand. It is also seen that there is considerable enhancement of 45 percentage in average columnar concentration of CO during the burning period, compared to that in the previous 5 years as observed by AIRS. In the present study, concentrations of CO at different pressure levels and columnar CO over Uttarakhand during the forest fire event have been simulated using FLEXPART. The area averaged profile of model derived CO has been compared with the profile from AIRS onboard Aqua. Comparison between model derived columnar CO and satellite observations shows good agreement with coefficient of correlation (r) approximately 0.91 over the burnt areas. Further analysis using FLEXPART reveals that the transport of pollutants is towards north-eastern and eastern regions from the locations of forest fire events. Model derived vertical distribution of CO over Tibet, which is situated at the north-east of Uttarakhand, shows significant increase of CO concentration at higher altitudes around 3 km from the mean sea level during the fire event. FLEXPART results show that the emissions from the Uttarakhand fires were transported to Tibet during the study period.

Spatial gradients of polycyclic aromatic hydrocarbons (PAHs) in air, atmospheric deposition, and surface water of the Ganges River basin

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous semi-volatile organic pollutants. Their environmental occurrence is of global concern as some of them are carcinogens, mutagens, and teratogens. In this study, concentrations and distributions of 16 priority PAHs (∑PAHs) were measured in air, atmospheric deposition, and surface water at various locations in Himalayan, Middle, and Lower Reaches of the Ganges River, covering a spatial transect of 2500km, during two seasons (pre-monsoon and monsoon). The concentration of ∑PAHs ranged between 2.2 and 182.2ngm^-3 in air, between 186 and 8810ngm^-2day^-1 in atmospheric deposition, and between 0.05 and 65.9ngL^-1 in surface water. Air concentrations were strongly correlated with human population density. In the Middle and Lower Reaches of the Ganges River, atmospheric PAHs were mainly attributed to fossil fuel combustion sources. In the Himalayan Reach the influence of forest fire or biomass combustion was evident during the dry pre-monsoon season. Seasonality in concentrations of PAHs in river water was evident in the Himalayan Reach of the river, as a probable consequence of climate-modulated secondary source intensity (i.e. releases from glacier melting). Seasonality faded in the Middle and Lower Reaches of the Ganges where water contamination is expected to mainly reflect anthropogenic primary sources. Ambient air concentrations were used to calculate the probabilistic incremental lifetime cancer risk (ILCR). It was expectedly found to be higher in the Middle and Lower Reaches compared to the Himalayan Reach. The strong correlation between population density and air concentrations suggests population density may be used as a surrogate variable to assess human health risk in data-sparse regions such as the Ganges River basin.