Implementation of a Markov Chain Monte Carlo method to inorganic aerosol modeling of observations from the MCMA-2003 campaign – Part I: Modeldescription and application to the La Merced site

[摘要] The equilibrium inorganic aerosol model ISORROPIA was embedded in a MarkovChain Monte Carlo algorithm to develop a powerful tool to analyze aerosoldata and predict gas phase concentrations where these are unavailable. Themethod directly incorporates measurement uncertainty, prior knowledge, andprovides a formal framework to combine measurements of different quality.The method was applied to particle- and gas-phase precursor observationstaken at La Merced during the Mexico City Metropolitan Area (MCMA) 2003Field Campaign and served to discriminate between diverging gas-phaseobservations of ammonia and predict gas-phase concentrations of hydrochloricacid. The model reproduced observations of particle-phase ammonium, nitrate,and sulfate well. The most likely concentrations of ammonia were found tovary between 4 and 26 ppbv, while the range for nitric acid was 0.1 to 55 ppbv.During periods where the aerosol chloride observations wereconsistently above the detection limit, the model was able to reproduce theaerosol chloride observations well and predicted the most likely gas-phasehydrochloric acid concentration varied between 0.4 and 5 ppbv. Despite thehigh ammonia concentrations observed and predicted by the model, when theaerosols were assumed to be in the efflorescence branch they are predictedto be acidic (pH~3).

[学科分类] 大气科学