Ammonia emissions from biomass burning in the continental United States. (August 2018)
- Record Type:
- Journal Article
- Title:
- Ammonia emissions from biomass burning in the continental United States. (August 2018)
- Main Title:
- Ammonia emissions from biomass burning in the continental United States
- Authors:
- Bray, Casey D.
Battye, William
Aneja, Viney P.
Tong, Daniel Q.
Lee, Pius
Tang, Youhua - Abstract:
- Abstract: This study quantifies ammonia (NH3 ) emissions from biomass burning from 2005 to 2015 across the continental US (CONUS) and compares emissions from biomass burning with the US Environmental Protection Agency (EPA) National Emissions Inventory (NEI), the Fire Inventory from the National Center for Atmospheric Research (FINN) and the Global Fire Emissions Database (GFED). A statistical regression model was developed in order to predict NH3 emissions from biomass burning using a combination of fire properties and meteorological data. Satellite data were used to evaluate the annual fire strength and frequency as well as to calculate the total NH3 emissions across the CONUS. The results of this study showed the total fire number has decreased, while the total yearly burn area and the average fire radiative power has increased. The average annual NH3 emissions from biomass burning from this study, on a national scale, were approximately 5.4e8 ± 3.3e8 kg year −1 . When comparing the results of this study with other emission inventories, it was found that ammonia emissions estimated by the NEI were approximately a factor of 1.3 lower than what was calculated in this study and a factor of 1.1 lower than what was modeled using the statistical regression model for 2010–2014. The calculated NH3 emissions from biomass burning were a factor of 5.9 and a factor of 13.1 higher than the emissions from FINN and the GFED, respectively. The modeled NH3 emissions from biomass burningAbstract: This study quantifies ammonia (NH3 ) emissions from biomass burning from 2005 to 2015 across the continental US (CONUS) and compares emissions from biomass burning with the US Environmental Protection Agency (EPA) National Emissions Inventory (NEI), the Fire Inventory from the National Center for Atmospheric Research (FINN) and the Global Fire Emissions Database (GFED). A statistical regression model was developed in order to predict NH3 emissions from biomass burning using a combination of fire properties and meteorological data. Satellite data were used to evaluate the annual fire strength and frequency as well as to calculate the total NH3 emissions across the CONUS. The results of this study showed the total fire number has decreased, while the total yearly burn area and the average fire radiative power has increased. The average annual NH3 emissions from biomass burning from this study, on a national scale, were approximately 5.4e8 ± 3.3e8 kg year −1 . When comparing the results of this study with other emission inventories, it was found that ammonia emissions estimated by the NEI were approximately a factor of 1.3 lower than what was calculated in this study and a factor of 1.1 lower than what was modeled using the statistical regression model for 2010–2014. The calculated NH3 emissions from biomass burning were a factor of 5.9 and a factor of 13.1 higher than the emissions from FINN and the GFED, respectively. The modeled NH3 emissions from biomass burning were a factor of 5.0 and a factor of 11.1 higher than the emissions from FINN and the GFED, respectively. As the climate continues to change, the pattern (frequency, intensity and magnitude) of fires across the US will also change, leading to changes in NH3 emissions. The statistical regression model developed in this study will allow prediction of NH3 emissions associated with climate change. Highlights: ~5.4e8 ± 3.3e8 kg of ammonia/year were emitted per year from biomass burning from 2005 to 2015 across the CONUS. An overall increase in ammonia emissions from biomass burning were observed over the study period. Emissions of ammonia from biomass burning from this study are higher than other inventories. A statistical regression model was developed (r 2 = 0.92, n = 48) to project future emissions.. … (more)
- Is Part Of:
- Atmospheric environment. Volume 187(2018)
- Journal:
- Atmospheric environment
- Issue:
- Volume 187(2018)
- Issue Display:
- Volume 187, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 187
- Issue:
- 2018
- Issue Sort Value:
- 2018-0187-2018-0000
- Page Start:
- 50
- Page End:
- 61
- Publication Date:
- 2018-08
- Subjects:
- Ammonia -- Wildfires -- Biomass burning -- National emissions inventory -- Fire emissions
Air -- Pollution -- Periodicals
Air -- Pollution -- Meteorological aspects -- Periodicals
551.51 - Journal URLs:
- http://www.sciencedirect.com/web-editions/journal/13522310 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.atmosenv.2018.05.052 ↗
- Languages:
- English
- ISSNs:
- 1352-2310
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1767.120000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20903.xml