Abstract. To improve dust storm identification over the western United States, historical dust events measured by air quality and satellite observations are analyzed based on their characteristics in data sets of regular meteorology, satellitebased aerosol optical depth (AOD), and air quality measurements. Based on the prevailing weather conditions associated with dust emission, dust storm events are classified into the following four typical types:(1) The key feature of cold front-induced dust storms is their rapid process with strong dust emissions.(2) Events caused by meso-to small-scale weather systems have the highest levels of emissions.(3) Dust storms caused by tropical disturbances show a stronger air concentration of dust and last longer than those in (1) and (2).(4) Dust storms triggered by cyclogenesis last the longest.In this paper, sample events of each type are selected and examined to explore characteristics observed from in situ and remote-sensing measurements. These characteristics include the lasting period, surface wind speeds, areas affected, average loading on ground-based optical and/or air quality measurements, peak loading on ground-based optical and/or air quality measurements, and loading on satellite-based aerosol optical depth. Based on these analyses, we compare the characteristics of the same dust events captured in different data sets in order to define the dust identification criteria. The analyses show that the variability in mass concentrations captured by in situ measurements is consistent with the variability in AOD from stationary and satellite observations. Our analyses also find that different data sets are capable of identifying certain common characteristics, while each data set also provides specific information about a dust storm event.For example, the meteorological data are good at identifying the lasting period and area impacted by a dust event; the ground-based air quality and optical measurements can capture the peak strength well; aerosol optical depth (AOD) from satellite data sets allows us to better identify dust-stormaffected areas and the spatial extent of dust. The current study also indicates that the combination of in situ and satellite observations is a better method to fill gaps in dust storm recordings.

Abstract. As precursors to tropospheric ozone and nitrate, nitrogen oxide (NO x ) in the present atmosphere and its transformation in response to emission and climate perturbations are studied by using the CAM-Chem model and air quality measurements from the National Emissions Inventory (NEI), Clean Air Status and Trends Network (CASTNET), and Environmental Protection Agency Air Quality System (EPA AQS). It is found that NO x transformations in present atmospheric conditions show different sensitivities over industrial and non-industrial regions. As a result, the surface ozone and nitrate formations can be divided into several regimes associated with the dominant emission types and relative levels of NO x and volatile organic compounds (VOC). Ozone production in industrial regions (the main NO x emission source areas) increases in warmer conditions and slightly decreases following an increase in NO x emissions due to NO x titration, which is opposite to the response in non-industrial regions. The ozone decrease following a temperature increase in non-industrial regions indicates that ozone production in regions that lack NO x emission sources may be sensitive to NO x transformation in remote source regions. The increase in NO 2 from NO x titration over industrial regions results in an increase rate of total nitrate that remains higher than the increase rate of NO x emissions. The presented findings indicate that a change in the ozone concentration is more directly affected by changes in climate and precursor emissions, while a change in the nitrate concentration is affected by local ozone production types and their seasonal transfer. The sensitivity to temperature perturbations shows that a warmer climate accelerates the decomposition of odd nitrogen (NO y ) during the night. As a result, the transformation rate of NO x to nitrate decreases. Examinations of the historical emissions and air quality records of a typical NO xlimited area, such as Atlanta and a VOC-limited area, such as Los Angeles further confirm the conclusions drawn from the modeling experiments.