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.

Comprehensive study of aerosols properties over various terrain types

Aerosols are a crucial part of the climate system. Numerous factors, including aerosols, govern Earth's radiation balance. Different aerosols have distinct radiational effects on the earth system, and thus the slight change in their composition may lead to a drastic change in their radiative effects. Aerosols' chemical and physical properties also depend on generation processes, generation source, and geographical location. Significant spatio-temporal inconsistency is noticed in the distribution of aerosols. It makes it much difficult task to assess their radiative properties. We attempted to explore aerosol's optical properties and wavelength dependence over different locations. We have used AERONET (Aerosol Robotic Network) data over various stations (Kanpur, Jaipur, Gandhi College, Pune) with varying terrain properties in the Indian continent. We have studied the variation of different optical parameters: aerosol optical depth (AOD), single scattering albedo (SSA), and Angstrom exponent (α), and their wavelength dependence. This study indicated that Jaipur is the cleanest site, with dust aerosols as a primary aerosol. Though over Pune also aerosol concentration was relatively low but the anthropogenic aerosols contributed primarily over this site. Over the Indo-Gangetic Plain (IGP) sites, dust aerosols dominated the pre-monsoon season, while anthropogenic aerosols dominated the post-monsoon and winter seasons. The scatter plot of AOD with α gives the details of different aerosols (desert dust, continental aerosols, mixed aerosol, biomass burning aerosols, and sulfate aerosols) in the different seasons and places. This study provides an overview of aerosol properties, dominant aerosols in the aerosol system, and their seasonal and spectral variation.

Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading

Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (fAOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying fAOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.

Analysis of a Haze Event over Nanjing, China Based on Multi-Source Data

We analyzed a June 2018 Nanjing, China haze event using ground-based and spaceborne sensors, combined with sounding and HYSPLIT backward trajectory data, with the ground-based and spaceborne sensor data exhibiting good consistency. Water vapor content showed significant positive correlation with AOD (aerosol optical depth), and AOD measured in urban and industrial areas was much higher compared to other similar zones. The afternoon convection caused the aerosol uplift during the haze event. Higher aerosol concentration was detected below 2 km. Due to the summer afternoon convective movement, pollutants at high altitude were dominated by small particles, while the overall pollutant mix was dominated by mixed aerosols. During a stable period over June 11–18, a single, near-surface inversion layer, and occasional two inversion layers, stopped pollutant dispersal, with only very stable ocean air mass transport in the southeast direction available. The Air Quality Index drop which took place during June 28–30 was caused by two inversion layers, combined with the immigration of pollutants from inland air masses.

Impact of dust and smoke mixing on column-integrated aerosol properties from observations during a severe wildfire episode over Valencia (Spain)

The most destructive wildfire experienced in Spain since 2004 occurred close to Valencia in summer 2012. A total of 48.500ha were affected by two wildfires, which were mostly active during 29-30 June. The fresh smoke plume was detected at the Burjassot measurement station simultaneously to a severe dust episode. We propose an empirical method to evaluate the dust and smoke mixing and its impact on the microphysical and optical properties. For this, we combine direct-sun measurements with a Cimel CE-318 sun-photometer with an inversion methodology, and the Mie theory to derive the column-integrated size distribution, single scattering albedo (SSA) and asymmetry parameter (g). The mixing of dust and smoke greatly increased the aerosol load and modified the background aerosol properties. Mineral dust increased the aerosol optical depth (AOD) up to 1, while the smoke plume caused an extreme AOD peak of 8. The size distribution of the mixture was bimodal, with a fine and coarse modes dominated by the smoke particles and mineral dust, respectively. The SSA and g for the dust-smoke mixture show a marked sensitivity on the smoke mixing-ratio, mainly at longer wavelengths. Mineral dust and smoke share a similar SSA at 440nm (~0.90), but with opposite spectral dependency. A small dust contribution to the total AOD substantially affects the SSA of the mixture, and also SSA at 1020nm increases from 0.87 to 0.95. This leads to a different spectral behaviour of SSA that changes from positive (smoke plume) to negative (dust), depending on the dust and smoke mixing-ratio.

Direct In Situ Mass Specific Absorption Spectra of Biomass Burning Particles Generated from Smoldering Hard and Softwoods

Particles from smoldering biomass burning (BB) represent a major source of carbonaceous aerosol in the terrestrial atmosphere. In this study, mass specific absorption spectra of laboratory-generated smoldering wood particles (SWP) from 3 hardwood and 3 softwood species were measured in situ. Absorption data spanning from λ = 500 to 840 nm were collected using a photoacoustic spectrometer coupled to a supercontinuum laser with a tunable wavelength and bandwidth filter. SWP were size- (electrical mobility) and mass-selected prior to optical characterization allowing data to be reported as mass-specific absorption cross sections (MAC). The median measured MAC at λ = 660 nm for smoldering oak particles was 1.1 (0.57/1.8) × 10^-2 m² g^-1 spanning from 83 femtograms (fg) to 517 fg (500 nm ≤ mobility diameter ≤950 nm), MAC values in parentheses are the 16^th and 84^th percentiles of the measured data (i.e., 1σ). The collection of all six wood species (Oak, Hickory, Mesquite, Western redcedar, Baldcypress, and Blue spruce) had median MAC values ranging from 1.4 × 10^-2 m² g^-1 to 7.9 × 10^-2 m² g^-1 at λ = 550 nm with absorption Ångström exponents (AAE) between 3.5 and 6.2. Oak, Western redcedar, and Blue spruce possessed statistically similar (p > 0.05) spectra while the spectra of Hickory, Mesquite, and Baldcypress were distinct (p < 0.01) as calculated from a point-by-point analysis using the Wilcox rank-sum test.

Forest fire smoke layers observed in the free troposphere over Portugal with a multiwavelength Raman lidar: optical and microphysical properties

Vertically resolved optical and microphysical properties of biomass burning aerosols, measured in 2011 with a multiwavelength Raman lidar, are presented. The transportation time, within 1-2 days (or less), pointed towards the presence of relatively fresh smoke particles over the site. Some strong layers aloft were observed with particle backscatter and extinction coefficients (at 355 nm) greater than 5 Mm⁻¹ sr⁻¹ and close to 300 Mm⁻¹, respectively. The particle intensive optical properties showed features different from the ones reported for aged smoke, but rather consistent with fresh smoke. The Ångström exponents were generally high, mainly above 1.4, indicating a dominating accumulation mode. Weak depolarization values, as shown by the small depolarization ratio of 5% or lower, were measured. Furthermore, the lidar ratio presented no clear wavelength dependency. The inversion of the lidar signals provided a set of microphysical properties including particle effective radius below 0.2 μm, which is less than values previously observed for aged smoke particles. Real and imaginary parts of refractive index of about 1.5-1.6 and 0.02i, respectively, were derived. The single scattering albedo was in the range between 0.85 and 0.93; these last two quantities indicate the nonnegligible absorbing characteristics of the observed particles.