TY - JOUR
T1 - NEIVAv1.0
T2 - Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
AU - Shahid, Samiha Binte
AU - Lacey, Forrest G.
AU - Wiedinmyer, Christine
AU - Yokelson, Robert J.
AU - Barsanti, Kelley C.
N1 - Publisher Copyright:
© Author(s) 2024.
PY - 2024/11/4
Y1 - 2024/11/4
N2 - Accurate representation of fire emissions is critical for modeling the in-plume, near-source, and remote effects of biomass burning (BB) on atmospheric composition, air quality, and climate. In recent years application of advanced instrumentation has significantly improved knowledge of the compounds emitted from fires, which, coupled with a large number of recent laboratory and field campaigns, has facilitated the emergence of new emission factor (EF) compilations. The Next-generation Emissions InVentory expansion of Akagi (NEIVA) version 1.0 is one such compilation in which the EFs for 14 globally relevant fuel and fire types have been updated to include data from recent studies, with a focus on gaseous non-methane organic compounds (NMOC_g). The data are stored in a series of connected tables that facilitate flexible querying from the individual study level to recommended averages of all laboratory and field data by fire type. The querying features are enabled by assignment of unique identifiers to all compounds and constituents, including thousands of NMOC_g. NEIVA also includes chemical and physical property data and model surrogate assignments for three widely used chemical mechanisms for each NMOC_g. NEIVA EF datasets are compared with recent publications and other EF compilations at the individual compound level and in the context of overall volatility distributions and hydroxyl (OH) reactivity (OHR) estimates. The NMOC_g in NEIVA include ∼ 4–8 times more compounds with improved representation of intermediate volatility organic compounds, resulting in much lower overall volatility (lowest-volatility bin shifted by as much as 3 orders of magnitude) and significantly higher OHR (up to 90 %) than other compilations. These updates can strongly impact model predictions of the effects of BB on atmospheric composition and chemistry.
AB - Accurate representation of fire emissions is critical for modeling the in-plume, near-source, and remote effects of biomass burning (BB) on atmospheric composition, air quality, and climate. In recent years application of advanced instrumentation has significantly improved knowledge of the compounds emitted from fires, which, coupled with a large number of recent laboratory and field campaigns, has facilitated the emergence of new emission factor (EF) compilations. The Next-generation Emissions InVentory expansion of Akagi (NEIVA) version 1.0 is one such compilation in which the EFs for 14 globally relevant fuel and fire types have been updated to include data from recent studies, with a focus on gaseous non-methane organic compounds (NMOC_g). The data are stored in a series of connected tables that facilitate flexible querying from the individual study level to recommended averages of all laboratory and field data by fire type. The querying features are enabled by assignment of unique identifiers to all compounds and constituents, including thousands of NMOC_g. NEIVA also includes chemical and physical property data and model surrogate assignments for three widely used chemical mechanisms for each NMOC_g. NEIVA EF datasets are compared with recent publications and other EF compilations at the individual compound level and in the context of overall volatility distributions and hydroxyl (OH) reactivity (OHR) estimates. The NMOC_g in NEIVA include ∼ 4–8 times more compounds with improved representation of intermediate volatility organic compounds, resulting in much lower overall volatility (lowest-volatility bin shifted by as much as 3 orders of magnitude) and significantly higher OHR (up to 90 %) than other compilations. These updates can strongly impact model predictions of the effects of BB on atmospheric composition and chemistry.
UR - http://www.scopus.com/inward/record.url?scp=85208670626&partnerID=8YFLogxK
U2 - 10.5194/gmd-17-7679-2024
DO - 10.5194/gmd-17-7679-2024
M3 - Article
AN - SCOPUS:85208670626
SN - 1991-959X
VL - 17
SP - 7679
EP - 7711
JO - Geoscientific Model Development
JF - Geoscientific Model Development
IS - 21
ER -