scholarly journals Relationship between Biomass Burning Emissions and Deforestation in Amazonia over the Last Two Decades

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1217
Author(s):  
Guilherme A. V. Mataveli ◽  
Gabriel de Oliveira ◽  
Hugo T. Seixas ◽  
Gabriel Pereira ◽  
Scott C. Stark ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Anthropogenic Activities ◽  
Human Health Risk ◽  
Agricultural Practices ◽  
Remote Sensing Data ◽  
Emission Model ◽  
Early 21St Century ◽  
Deforestation Rates ◽  
Radiative Power ◽  
Forested Areas

With deforestation and associated fires ongoing at high rates, and amidst urgent need to preserve Amazonia, improving the understanding of biomass burning emissions drivers is essential. The use of orbital remote sensing data enables the estimate of both biomass burning emissions and deforestation. In this study, we have estimated emissions of particulate matter with diameter less than 2.5 µm (PM2.5) associated with biomass burning, a primary human health risk, using the Brazilian Biomass Burning emission model with Fire Radiative Power (3BEM_FRP), and estimated deforestation based on the MapBiomas dataset. Using these estimates, we have assessed for the first time how deforestation drove biomass burning emissions in Amazonia over the last two decades at three scales of analysis: Amazonia-wide, country/state and pixel. Amazonia accounted for 48% of PM2.5 emitted from biomass burning in South America and current deforestation rates have reached values on par with those of the early 21st Century. Emissions and deforestation were concentrated in the Eastern and Central-Southern portions of Amazonia. Amazonia-wide deforestation and emissions were linked through time (R = 0.65). Countries/states with the widest spread agriculture were less likely to be correlated at this scale, likely because of the importance of biomass burning in agricultural practices. Concentrated in regions of ongoing deforestation, in 18% of Amazonia grid cells PM2.5 emissions associated with biomass burning and deforestation were significantly positively correlated. Deforestation is an important driver of emissions in Amazonia but does not explain biomass burning alone. Therefore, future work must link climate and other non-deforestation drivers to completely understand biomass burning emissions in Amazonia. The advance of anthropogenic activities over forested areas, which ultimately leads to more fires and deforestation, is expected to continue, worsening a crisis of dangerous emissions.

scholarly journals Rapid Recent Deforestation Incursion in a Vulnerable Indigenous Land in the Brazilian Amazon and Fire-Driven Emissions of Fine Particulate Aerosol Pollutants

Forests ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 829
Author(s):  
Gabriel de Oliveira ◽  
Jing M. Chen ◽  
Guilherme A. V. Mataveli ◽  
Michel E. D. Chaves ◽  
Hugo T. Seixas ◽  
...  
Keyword(s):  
Respiratory Health ◽  
Human Health Risk ◽  
Agricultural Practices ◽  
Brazilian Amazon ◽  
Forest Degradation ◽  
Climate Feedback ◽  
Emission Model ◽  
Annual Average ◽  
Fire Emissions ◽  
Indigenous Land

Deforestation in the Brazilian Amazon is related to the use of fire to remove natural vegetation and install crop cultures or pastures. In this study, we evaluated the relation between deforestation, land-use and land-cover (LULC) drivers and fire emissions in the Apyterewa Indigenous Land, Eastern Brazilian Amazon. In addition to the official Brazilian deforestation data, we used a geographic object-based image analysis (GEOBIA) approach to perform the LULC mapping in the Apyterewa Indigenous Land, and the Brazilian biomass burning emission model with fire radiative power (3BEM_FRP) to estimate emitted particulate matter with a diameter less than 2.5 µm (PM2.5), a primary human health risk. The GEOBIA approach showed a remarkable advancement of deforestation, agreeing with the official deforestation data, and, consequently, the conversion of primary forests to agriculture within the Apyterewa Indigenous Land in the past three years (200 km2), which is clearly associated with an increase in the PM2.5 emissions from fire. Between 2004 and 2016 the annual average emission of PM2.5 was estimated to be 3594 ton year−1, while the most recent interval of 2017–2019 had an average of 6258 ton year−1. This represented an increase of 58% in the annual average of PM2.5 associated with fires for the study period, contributing to respiratory health risks and the air quality crisis in Brazil in late 2019. These results expose an ongoing critical situation of intensifying forest degradation and potential forest collapse, including those due to a savannization forest-climate feedback, within “protected areas” in the Brazilian Amazon. To reverse this scenario, the implementation of sustainable agricultural practices and development of conservation policies to promote forest regrowth in degraded preserves are essential.

scholarly journals Assessment of Impacts of Hurricane Katrina on Net Primary Productivity in Mississippi

2010 ◽  
Vol 14 (14) ◽  
pp. 1-12 ◽  
Author(s):  
Shrinidhi Ambinakudige ◽  
Sami Khanal
Keyword(s):  
Natural Disasters ◽  
Hurricane Katrina ◽  
Primary Productivity ◽  
Atmospheric Carbon Dioxide ◽  
Net Primary Productivity ◽  
Gulf Coast ◽  
Carbon Sink ◽  
Anthropogenic Activities ◽  
Remote Sensing Data ◽  
The United States

Abstract Southern forests contribute significantly to the carbon sink for the atmospheric carbon dioxide (CO2) associated with the anthropogenic activities in the United States. Natural disasters like hurricanes are constantly threatening these forests. Hurricane winds can have a destructive impact on natural vegetation and can adversely impact net primary productivity (NPP). Hurricane Katrina (23–30 August 2005), one of the most destructive natural disasters in history, has affected the ecological balance of the Gulf Coast. This study analyzed the impacts of different categories of sustained winds of Hurricane Katrina on NPP in Mississippi. The study used the Carnegie–Ames–Stanford Approach (CASA) model to estimate NPP by using remote sensing data. The results indicated that NPP decreased by 14% in the areas hard hit by category 3 winds and by 1% in the areas hit by category 2 winds. However, there was an overall increase in NPP, from 2005 to 2006 by 0.60 Tg of carbon, in Mississippi. The authors found that Pearl River, Stone, Hancock, Jackson, and Harrison counties in Mississippi faced significant depletion of NPP because of Hurricane Katrina.

scholarly journals Combining fire radiative power observations with the fire weather index improves the estimation of fire emissions

2017 ◽  
Author(s):  
Francesca Di Giuseppe ◽  
Samuel Rémy ◽  
Florian Pappenberger ◽  
Fredrik Wetterhall
Keyword(s):  
Biomass Burning ◽  
Atmospheric Composition ◽  
Composition Analysis ◽  
Fire Weather ◽  
Atmospheric Conditions ◽  
Weather Index ◽  
Fire Weather Index ◽  
Fire Emissions ◽  
Radiative Power ◽  
Fire Radiative Power

Abstract. The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass burning fire emission estimates from the Global Fire Assimilation System (GFAS). GFAS converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence where observed FRP from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an overestimation of fire duration, which in turn translates into an overestimation of emissions from fires. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

scholarly journals Remote Sensing Data for Calibrated Assessment of Wildfire Emissions in Siberian Forests

Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 348
Author(s):  
Evgenii Ponomarev ◽  
Eugene Shvetsov ◽  
Kirill Litvintsev ◽  
Irina Bezkorovaynaya ◽  
Tatiana Ponomareva ◽  
...  
Keyword(s):  
Standard Procedure ◽  
Remote Sensing Data ◽  
Fire Danger ◽  
Variable Intensity ◽  
Burned Areas ◽  
Radiative Power ◽  
Terra Modis ◽  
Siberian Forests

This study was carried out for Siberia using Terra/Modis satellite data (2002–2016), data of ground surveys on burned areas of different ages, long-term meteorological information, and numerical simulation results. On the basis of meteorological and wildfire databases, we evaluated the probability (~18%) of an extreme fire danger scenario that was found to occur every 8 ± 3 years in different parts of the region. Next, we used Fire Radiative Power (FRP) measurements to classify the varieties of burning conditions for each wildfire in the database. The classification of the annually burned forest area was obtained in accordance with the assessments of burning intensity ranges categorized by FRP. Depending on the fire danger scenario in Siberia, 47.04 ± 13.6% of the total wildfire areas were classified as low-intensity burning, 42.46 ± 10.50% as medium-intensity fire areas, and 10.50 ± 6.90% as high-intensity. Next, we calculated the amount of combusted biomass and the direct emissions for each wildfire, taking into account the variable intensity of burning within the fire polygons. The total annual emissions were also calculated for Siberia for the last 15 years, from 2002 to 2016. The average estimate of direct carbon emission was 83 ± 21 Tg/year, which is lower than the result (112 ± 25 Tg/year) we obtained using the standard procedure.

scholarly journals High-Resolution Biomass Burning Aerosol Transport Simulations in the Tropics

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 91
Author(s):  
Nurzahziani ◽  
Chinnawat Surussavadee ◽  
Thanchanok Noosook
Keyword(s):  
High Resolution ◽  
Biomass Burning ◽  
Mean Squared Error ◽  
Dry Mass ◽  
Northern Region ◽  
Emission Model ◽  
Aerosol Transport ◽  
Monthly Average ◽  
Biomass Burning Aerosol ◽  
The Tropics

This study evaluates the performance of the Weather Research and Forecasting Model with Chemistry (WRF-Chem) for simulating biomass burning aerosol transport at high resolution in the tropics using two different biomass burning emission inventories. Hourly, daily, and monthly average PM10 dry mass concentrations at 5 km resolution—simulated separately using the Brazilian Biomass Burning Emission Model (WRF-3BEM) and the Fire Inventory from NCAR (WRF-FINN) and their averages (WRF-AVG) for 3 months from February to April—are evaluated, using measurements from ground stations distributed in northern Thailand for 2014 and 2015. Results show that WRF-3BEM agrees well with observations and performs much better than WRF-FINN and WRF-AVG. WRF-3BEM simulations are almost unbiased, while those of WRF-FINN and WRF-AVG are significantly overestimated due to significant overestimates of FINN emissions. WRF-3BEM and the measured monthly average PM10 concentrations for all stations and both years are 89.22 and 87.20 μg m−3, respectively. The root mean squared error of WRF-3BEM simulated monthly average PM10 concentrations is 72.00 and 47.01% less than those of WRF-FINN and WRF-AVG, respectively. The correlation coefficient of WRF-3BEM simulated monthly PM10 concentrations and measurements is 0.89. WRF-3BEM can provide useful biomass burning aerosol transport simulations for the northern region of Thailand.

scholarly journals An improved glyoxal retrieval from OMI measurements

2014 ◽  
Vol 7 (12) ◽  
pp. 4133-4150 ◽  
Author(s):  
L. M. A. Alvarado ◽  
A. Richter ◽  
M. Vrekoussis ◽  
F. Wittrock ◽  
A. Hilboll ◽  
...  
Keyword(s):  
Cross Sections ◽  
Anthropogenic Activities ◽  
Absorption Cross ◽  
Fire Event ◽  
Data Set ◽  
Polynomial Degree ◽  
Temperature Boundary ◽  
Sensitivity Tests ◽  
Radiative Power ◽  
The Impact

Abstract. Satellite observations from the SCIAMACHY, GOME-2 and OMI spectrometers have been used to retrieve atmospheric columns of glyoxal (CHOCHO) with the DOAS method. High CHOCHO levels were found over regions with large biogenic and pyrogenic emissions, and hot-spots have been identified over areas of anthropogenic activities. This study focuses on the development of an improved retrieval for CHOCHO from measurements by the OMI instrument. From sensitivity tests, a fitting window and a polynomial degree are determined. Two different approaches to reduce the interference of liquid water absorption over oceanic regions are evaluated, achieving significant reduction of the number of negative columns over clear water regions. The impact of using different absorption cross-sections for water vapour is evaluated and only small differences are found. Finally, a high-temperature (boundary layer ambient: 294 K) absorption cross-section of nitrogen dioxide (NO2) is introduced in the DOAS retrieval to account for potential interferences of NO2 over regions with large anthropogenic emissions, leading to improved fit quality over these areas. A comparison with vertical CHOCHO columns retrieved from GOME-2 and SCIAMACHY measurements over continental regions is performed, showing overall good consistency. However, SCIAMACHY CHOCHO columns are systematically higher than those obtained from the other instruments. Using the new OMI CHOCHO data set, the link between fires and glyoxal columns is investigated for two selected regions in Africa. In addition, mapped averages are computed for a fire event in Russia between mid-July and mid-August 2010. In both cases, enhanced CHOCHO levels are found in close spatial and temporal proximity to elevated levels of MODIS fire radiative power, demonstrating that pyrogenic emissions can be clearly identified in the new OMI CHOCHO product.

scholarly journals Utilization of Ostracods (Crustacea) as Bioindicator for Environmental Pollutants

2020 ◽  
pp. 73-93
Author(s):  
E. Parameswari ◽  
V. Davamani ◽  
R. Kalaiarasi ◽  
T. Ilakiya ◽  
S. Arulmani
Keyword(s):  
Industrial Development ◽  
Oil Spills ◽  
Human Impacts ◽  
Anthropogenic Activities ◽  
Environmental Pollutants ◽  
Chemical Properties ◽  
Agricultural Practices ◽  
Human Beings ◽  
Magnesium Calcite ◽  
Marine Areas

Ecosystem undergoes drastic changes due to the anthropogenic activities. As a consequence of industrial development, increasing population growth and modernized agricultural practices water resources like limnetic zone and marine areas have undergone eutrophication. This resulted in the decline in population of phytoplankton and zooplankton. Hence, it is an urgent need to monitor the quality of the environment. Several organisms are used as biomonitors. Among them, Ostracodes (Seed Shrimps) which belong to Crustacean group are very sensitive to those changes in the environment and useful in predicting the paleo environmental conditions. Ostracodes are bivalve arthropods which are enclosed in a carapace made of low magnesium calcite. These species are occurring for about 450 million years dates back to ordovician which are known for their easier fossilization. The development of Ostracodes is influenced by the physic - chemical properties of waters such as Salinity, temperature, pH, Dissolved oxygen, bottom grain sizes and sedimentation rates.  In addition to diversity and abundance of population, morphological and geochemical changes can also be detected in the Ostracod carapace (shell) which serves as a tracer of the water quality. These details are basis for utilizing Ostracods as paleoenvironmental (paleoclimatic, paleosalinity, paleooceanographic) reconstruction, ecotoxicity monitoring, biostratigraphic indicator. Moreover, these microcrustaceans showed similar or higher sensitivity to herbicides, pesticides, oil spills or heavy metals pollution other than traditional groups like copepods, protozoan, rotifers, cladocerans which are used to test the human impacts on ecosystem. These meiofaunas are highly adaptable to waters containing organic and inorganic contaminants generated by catastrophic activities by human beings in the surroundings.

scholarly journals Analysis of Pattern and Extent of Deforestation in Akure Forest Reserve, Ondo State, Nigeria

2019 ◽  
Vol 12 (1-2) ◽  
pp. 1-11
Author(s):  
Isaac Adelakun Gbiri ◽  
Nathaniel Olugbade Adeoye
Keyword(s):  
Anthropogenic Activities ◽  
Remote Sensing Data ◽  
Satellite System ◽  
Optical Remote Sensing ◽  
Human Beings ◽  
Southwestern Nigeria ◽  
Forest Reserve ◽  
Forest Depletion ◽  
Undisturbed Forest ◽  
The Government

Abstract Forest Reserves in Southwestern Nigeria have been threatened by urbanization and anthropogenic activities and the rate of deforestation is not known. This study examined the vegetation characteristics of Akure Forest Reserve using optical remote sensing data. It also assessed the changing pattern in the forest reserve between 1986 and 2017. Global Navigation Satellite System (GNSS) receiver was used to capture the location of the prominent settlements that surrounded the Forest Reserve in order to evaluate their effects on the forest. Landsat TM 1986, Landsat ETM+ 2002 and Landsat OLI_TIRS 2017 with 30m resolution were classified to assess the spatio-temporal changing pattern of the forest reserve. The results showed different composition of vegetation, which include undisturbed forest, secondary regrowth and farmlands. The study further revealed that in 1986, 2002 and 2017, undisturbed forest constituted 63.3%, 32.4% and 32.1% of the entire land area respectively, while secondary regrowth occupied 8.3% in 1986, 9.5% in 2002 and 15.6% in 2017. The farmlands had erratic growth between 1986 and 2017. It was 16.9% in 1986, 22.1% in 2002 and 17.5% in 2017. The bare ground exhibited inconsistency in the coverage. In 1986 the areal extent was 11.5%, when it increased to 36% in 2002 and decreased to 31.9% in 2017. In conclusion, the study revealed the extent of forest depletion at Akure Forest Reserve and it is therefore important that the residents, the government and the researchers show major concern about some of the critical factors to human beings that are responsible for forest depletion.

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