Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China

Journal Article · Mon Dec 01 00:00:00 EST 2014 · Atmospheric Environment, 98:105-110

DOI:https://doi.org/10.1016/j.atmosenv.2014.08.023· OSTI ID:1166868

Situ, S.; Wang, Xuemei; Guenther, Alex B.; Zhang, Yanli; Wang, Xinming; Huang, Minjuan; Fan, Qi; Xiong, Zhe

Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as high as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1166868
• Report Number(s): PNNL-SA-104214
• Journal Information: Atmospheric Environment, 98:105-110, Journal Name: Atmospheric Environment, 98:105-110
• Country of Publication: United States
• Language: English