Biomass Burning in Africa: An Investigation of Fire Radiative Power Missed by MODIS Using the 375 m VIIRS Active Fire Product

Spatial variations in vegetation fires and emissions in South and Southeast Asia during COVID-19 and pre-pandemic

Vegetation fires are common in South/Southeast Asian (SA/SEA) countries. However, very few studies focused on vegetation fires and the changes during the COVID as compared to pre-pandemic. This study fills an information gap and reports total fire incidences, total burnt area, type of vegetation burnt, and total particulate matter emission variations in SA/SEA during COVID-2020 and pre-pandemic (2012-2019). Results from the short-term 2020-COVID versus 2019-non-COVID year showed a decline in fire counts varying from - 2.88 to 79.43% in S/SEA. The exceptions in South Asia include Afghanistan and Sri Lanka, with a 152% and 4.9% increase, and Cambodia and Myanmar in Southeast Asia, with an 11.1% and 8.5% increase in fire counts in the 2020-COVID year. The burnt area decline for 2020 compared to 2019 varied from - 0.8% to 92% for South/Southeast Asian countries, with most burning in agricultural landscapes than forests. Several patches in S/SEA showed a decrease in fires for the 2020 pandemic year compared to long term 2012-2020 pre-pandemic record, with Z scores greater or less than two denoting statistical significance. However, on a country scale, the results were not statistically significant in both S/SEA, with Z scores ranging from - 0.24 to - 1, although most countries experienced a decrease in fire counts. The associated mean TPM emissions declined from ~ 2.31 Tg (0.73stdev) during 2012-2019 to 2.0 (0.65stdev)Tg in 2020 in South Asia and 6.83 (0.70stdev)Tg during 2012-2019 to 5.71 (0.69 stdev)Tg in 2020 for South East Asian countries. The study highlights variations in fires and emissions useful for fire management and mitigation.

The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment

Wildfires significantly influence ecosystem patterns and processes on a global scale. In many cases, they pose a threat to human lives and property. Through greenhouse gas emissions, wildfires also directly contribute to climate change. The monitoring of such events and the analysis of acquired data is crucial for understanding wildfire and ecosystem interactions. The FireBIRD small satellite mission, operated by the German Aerospace Center (DLR), was specifically designed for the detection of wildfires. It features a higher spatial resolution than available with other Earth-observation systems. In addition to the detection of active fire locations, the system also allows the derivation of fire intensity by means of the Fire Radiative Power (FRP). This indicator can be used as a basis to derive the amount of emitted pollutant, which makes it valuable for climate studies. With the FireBIRD mission facing its end of life in 2021, this study retrospectively evaluates the performance of the system through an inter-comparison with data from two satellite missions of the National Aeronautics and Space Administration (NASA) and discusses the potential of such a system. The comparison is performed regarding both geometrical and radiometric aspects, the latter focusing on the FRP. This study uses and compares two different methods to derive the FRP from FireBIRD data. The data are analyzed regarding six major fire incidents in different regions of the world. The FireBIRD results are in accordance with the reference data, showing a geometrical overlapping rate of 83% and 84% regarding MODIS (Moderate-resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) overpasses in close temporal proximity. Furthermore, the results show a positive bias in FRP of about 11% compared to MODIS.

Three-dimensional spatiotemporal evolution of wildfire-induced smoke aerosols: A case study from Liangshan, Southwest China

Carbonaceous aerosols and gaseous pollutants emitted from wildfires play a crucial role in both the global climate system and regional air quality. Here, using multisource satellite and ground-based observations combined with reanalysis data, we investigate the three-dimensional evolution of biomass-burning emissions from a forest wildfire event in Liangshan, Southwest China, which occurred from 29 March to 1 April 2020. The meteorological field analysis showed that the negative anomaly of relative humidity and precipitation, as well as the positive anomaly of near-surface wind speed, created favourable conditions for the occurrence and spread of this wildfire event. During the fire, satellite observations suggested a maximum fire radiation power of over 100 MW. In addition, there were significant short-term effects of fire activity on regional air quality, with downwind surface PM_2.5 concentrations at the Xichang site reaching a maximum of approximately 470 μg·m ^-3 on March 31. Driven by a southwesterly airflow, large amounts of smoke aerosols were transported rapidly to downstream areas, significantly deteriorating air quality, with the maximum value of the aerosol optical depth (AOD) exceeding 2. Moreover, the quantitative evaluation based on Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis showed that the instantaneous maximum values of the column mass concentration of black carbon (BC) and organic carbon (OC) reached 9.8 g·m^-2 and 1.8 g·m^-2 during the fire respectively. Further analysis suggested that the interaction between the lower and upper atmosphere constrained the smoke aerosols to altitudes below approximately 5 km, which was also supported by the vertical distribution of elevated smoke aerosols observed by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP).

A high-resolution emission inventory of air pollutants from primary crop residue burning over Northern India based on VIIRS thermal anomalies

Emissions from the crop residue burning adversely affect the regional and global air quality including public health. In this study, a district-wise comprehensive emission inventory of key pollutants (PM_2.5, PM₁₀, CO, CO₂, SO₂, NOx, N₂O, NH₃, CH₄, NMVOC, EC, OC, PAH) emitted during primary crop residue burning was developed using activity data for the major agrarian states of north India for the agricultural year 2017-18. The emissions were scaled to the spatial resolution of 1 km grid to study the spatial distribution of crop residue burning activities using VIIRS Thermal anomalies datasets. An estimated 20.3 Mt and 9.6 Mt of crop residue were burned in Punjab and Haryana, resulting in an emission of 137.2 Gg and 56.9 Gg of PM_2.5 and 163.7 Gg and 72.1 of PM₁₀ Gg for respective states. The emissions of EC, OC, and PAHs were 8.6 Gg, 45.7 Gg, and 0.08 Gg in Punjab, whereas in Haryana emissions were 3.7 Gg, 17.7 Gg, and 0.03 Gg, respectively. The results show that rice and wheat crops were major contributor to residue burnt at the field (>90%) leading to the high load of atmospheric emissions in the IGP region. Further, CO₂ equivalent greenhouse gas emissions were 34.8 Tg and 17.3 Tg for Punjab and Haryana, respectively. Around 30000 and 8500 active fires were detected by VIIRS over the agricultural area of Punjab and Haryana during the studied year. The GIS-based bottom-up approach using gridded emission inventory shows pollutant distribution dominates over the south-western part of Punjab and north-western region of Haryana. The proximity of these regions to Delhi and transboundary movement of emissions towards Indo-Gangetic plains causes high air pollution episodes. The high-resolution inventory of various pollutants will be useful for regional air quality models to better predict and manage the hotspot of air pollution.