Abstract. This study introduces an observation-based dust identification approach and applies it to reconstruct longterm dust climatology in the western United States. Longterm dust climatology is important for quantifying the effects of atmospheric aerosols on regional and global climate. Although many routine aerosol monitoring networks exist, it is often difficult to obtain dust records from these networks, because these monitors are either deployed far away from dust active regions (most likely collocated with dense population) or contaminated by anthropogenic sources and other natural sources, such as wildfires and vegetation detritus. Here we propose an approach to identify local dust events relying solely on aerosol mass and composition from general-purpose aerosol measurements. Through analyzing the chemical and physical characteristics of aerosol observations during satellite-detected dust episodes, we select five indicators to be used to identify local dust records: (1) high PM 10 concentrations; (2) low PM 2.5 /PM 10 ratio; (3) higher concentrations and percentage of crustal elements; (4) lower percentage of anthropogenic pollutants; and (5) low enrichment factors of anthropogenic elements. After establishing these identification criteria, we conduct hierarchical cluster analysis for all validated aerosol measurement data over 68 IMPROVE sites in the western United States. A total of 182 local dust events were identified over 30 of the 68 locations from 2000 to 2007. These locations are either close to the four US Deserts, namely the Great Basin Desert, the Mojave Desert, the Sonoran Desert, and the Chihuahuan Desert, or in the high wind power region (Colorado). During the eight-year study period, the total number of dust events displays an interesting four-year activity cycle (one in 2000- The monthly frequency of dust events shows a peak from March to July and a second peak in autumn from September to November. The large quantity of dust events occurring in summertime also suggests the prevailing impact of windblown dust across the year. This seasonal variation is consistent with previous model simulations over the United States.

Abstract. To show how remote-sensing products can be used to classify the entire CONUS domain into "geographical regions" and "chemical regimes", we analyzed the results of simulation from the Community Multiscale Air Quality (CMAQ) model version 4.7.1 over the Conterminous United States (CONUS) for August 2009. In addition, we observe how these classifications capture the weekly cycles of ground-level nitrogen oxide (NO x ) and ozone (O 3 ) at US EPA Air Quality System (AQS) sites. We use the Advanced Very High Resolution Radiometer (AVHRR) land use dominant categories and the Global Ozone Monitoring Experiment-2 (GOME-2) HCHO/NO 2 column density ratios to allocate geographical regions (i.e., "urban", "forest", and "other" regions) and chemical regimes (i.e., "NO x -saturated", "NO x -sensitive", and "mixed" regimes). We also show that CMAQ simulations using GOME-2 satellite-adjusted NO x emissions mitigate the discrepancy between the weekly cycles of NO x from AQS observations and that from CMAQ simulation results. We found geographical regions and chemical regimes do not show a one-to-one correspondence: the averaged HCHO / NO 2 ratios for AVHRR "urban" and "forest" regions are 2.1 and 4.0, which correspond to GOME-2 "mixed" and "NO xsensitive" regimes, respectively. Both AQS-observed and CMAQ-simulated weekly cycles of NO x show high concentrations on weekdays and low concentrations on weekends, but with one-or two-day shifts of weekly high peaks in the simulated results, which eventually introduces the shifts in simulated weekly-low O 3 concentration. In addition, whereas the high weekend O 3 anomaly is clearly observable at sites over the GOME-2 NO x -saturated regime in both AQS and CMAQ, the weekend effect is not captured at sites over the AVHRR urban region because of the chemical characteristics of the urban sites (≈ GOME-2 mixed regime). In addition, the weekend effect from AQS is more clearly discernible at sites above the GOME-2 NO x -saturated regime than at other sites above the CMAQ NO x -saturated regime, suggesting that the GOME-2-based chemical regime classification is more accurate than CMAQ-based chemical classification. Furthermore, the CMAQ simulations using the GOME-2-derived NO x emissions adjustment (decreasing from 462 Gg N to 426 Gg N over the US for August 2009) show large reductions of simulated NO x concentrations (particularly over the urban, or NO x -saturated, regime), and mitigates the large discrepancies between the absolute amount and the weekly pattern of NO x concentrations of the EPA AQS and those of the baseline CMAQ.

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