Citation:

Olson, D., T. Riedel, R. Long, J. Offenberg, M. Lewandowski, AND T. Kleindienst. Time series analysis of wintertime O3 and NOx formation using vector autoregressions. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 218:116988, (2019). https://doi.org/10.1016/j.atmosenv.2019.116988

Impact/Purpose:

Product uses vector autoregressions to better understand O3 and NOx formation during wintertime conditions based on field study measurements collected in Utah.

Description:

Concentrations of 11 species are reported from continuous measurements taken during a wintertime field study in Utah. Time series data for measured species generally displayed strong diurnal patterns. Six species show a diurnal pattern of daytime maximums (NO, NOy, O3, H2O2, CH2O2, and Cl2), while five species show a diurnal pattern of night time maximums (NO2, HONO, ClNO2, HNO3, and N2O5). Vector autoregression analyses were completed to better understand important species influencing the formation of O3 and NOx. For the species studied, r2 values of predicted versus measured concentrations ranged from 0.82 to 0.99. Fitting parameters for the autoregressive matrix, Π, indicated the importance of species precursors. In addition, values of fitting parameters for Π were relatively insensitive to data size, with variations generally <10%. Variable causation was quantified using the Granger causation method. Assuming O3 and NOx behave as chemical products, reactants (in order of importance) are as follows: H2O2, N2O5, HONO, and ClNO2.

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