Development and evaluation of processes affecting simulation of diel fine particulate matter variation in the GEOS-Chem model

Abstract

The capability of chemical transport models to represent fine particulate matter (PM2.5) over the course of a day is of vital importance for air quality simulation and assessment. In this work, we used the nested GEOS-Chem model at 0.25∘×0.3125∘ resolution to simulate the diel (24 h) variation in PM2.5 mass concentrations over the contiguous United States (US) in 2016. We evaluate the simulations with in situ measurements from a national monitoring network. Our base case simulation broadly reproduces the observed morning peak, afternoon dip, and evening peak of PM2.5, matching the timings of these features within 1–3 h. However, the simulated PM2.5 diel amplitude in our base case was 106 % biased high, relative to observations. We find that temporal resolution of emissions, subgrid vertical gradient between surface model-level center and observations, and biases in boundary layer mixing and aerosol nitrate are the major causes for this inconsistency. We applied an hourly anthropogenic emission inventory, converted the PM2.5 mass concentrations from the model-level center to the height of surface measurements by correcting for aerodynamic resistance, adjusted the boundary layer heights in the driving meteorological fields using aircraft observations, and constrained nitrate concentrations using in situ measurements. The bias in the PM2.5 diel amplitude was reduced to −12 % in the improved simulation. Gridded hourly emissions rather than diel scaling factors applied to monthly emissions reduced biases in simulated PM2.5 overnight. Resolving the subgrid vertical gradient in the surface model level aided the capturing of the timings of the PM2.5 morning peak and afternoon minimum. Based on the improved model, we find that the mean observed diel variation in PM2.5 for the contiguous US is driven by (1) building up of PM2.5 by 10 % in early morning (04:00–08:00 local time, LT), due to increasing anthropogenic emissions into a shallow mixed layer; (2) decreasing PM2.5 by 22 % from mid-morning (08:00 LT) through afternoon (15:00 LT), associated with mixed-layer growth; (3) increasing PM2.5 by 30 % from mid-afternoon (15:00 LT) though evening (22:00 LT) as emissions persist into a collapsing mixed layer; and (4) decreasing PM2.5 by 10 % overnight (22:00–04:00 LT) as emissions diminish.