title: A New Combined Stepwise-Based High-Order Decoupled Direct and Reduced-Form Method To Improve Uncertainty Analysis in PM2.5Simulations.
abstract: The traditional reduced-form model (RFM) based on the high-order decoupled direct method (HDDM), is an efficient uncertainty analysis approach for air quality models, but it has large biases in uncertainty propagation due to the limitation of the HDDM in predicting nonlinear responses to large perturbations of model inputs. To overcome the limitation, a new stepwise-based RFM method that combines several sets of local sensitive coefficients under different conditions is proposed. Evaluations reveal that the new RFM improves the prediction of nonlinear responses. The new method is applied to quantify uncertainties in simulated PM2.5concentrations in the Pearl River Delta (PRD) region of China as a case study. Results show that the average uncertainty range of hourly PM2.5concentrations is -28% to 57%, which can cover approximately 70% of the observed PM2.5concentrations, while the traditional RFM underestimates the upper bound of the uncertainty range by 1-6%. Using a variance-based method, the PM2.5boundary conditions and primary PM2.5emissions are found to be the two major uncertainty sources in PM2.5simulations. The new RFM better quantifies the uncertainty range in model simulations and can be applied to improve applications that rely on uncertainty information.
authors.affiliation: College of Environment and Energy, South China University of Technology , Guangzhou, PR China.
authors.forename: Zhijiong
authors.initials: Z
authors.lastname: Huang
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332-0355, United States.
authors.forename: Yongtao
authors.initials: Y
authors.lastname: Hu
authors.affiliation: College of Environment and Energy, South China University of Technology , Guangzhou, PR China.
authors.forename: Junyu
authors.identifier: 0000-0002-8267-7255
authors.initials: J
authors.lastname: Zheng
authors.affiliation: College of Environment and Energy, South China University of Technology , Guangzhou, PR China.
authors.forename: Zibing
authors.initials: Z
authors.lastname: Yuan
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332-0355, United States.
authors.forename: Armistead G
authors.initials: AG
authors.lastname: Russell
authors.affiliation: College of Environment and Energy, South China University of Technology , Guangzhou, PR China.
authors.forename: Jiamin
authors.initials: J
authors.lastname: Ou
authors.affiliation: College of Environment and Energy, South China University of Technology , Guangzhou, PR China.
authors.forename: Zhuangmin
authors.initials: Z
authors.lastname: Zhong
mesh_terms: D000393:Air Pollutants; D004784:Environmental Monitoring; D008962:Models, Theoretical; D052638:Particulate Matter; D035501:Uncertainty
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter