An evaluation of Terra-MODIS sampling for monthly and annual particulate matter air quality assessment over the Southeastern United States

Although satellites provide reliable and repeated measurements on a global basis, particulate matter air quality information can be derived from satellites only when clouds are absent and when surface conditions are favorable. However, ground measurements provide particulate matter information irrespective of cloud cover and surface conditions. Therefore there could be a sampling bias when using satellite data for air quality research. To examine this issue, we calculate particulate matter (PM2.5) mass concentration from daily ground-based measurements (ALLPM) on monthly to yearly time scales and compare these against the same ground measurements for only those days when satellite data is available (SATPM). To accomplish this, we use six years of PM2.5 mass concentration data from 38 stations along with Terra-MODIS satellite data over the Southeastern United States. Our results indicate that satellite data are generally available less than 50% of the time over these locations, although the interregional variability of data availability is between 32% and 57%. However, the mean differences between the ALLPM and SATPM, over monthly to yearly time scales over the Southeastern United States, is less than 2 μgm−3 indicating that low sampling from satellites due to cloud cover and other reasons is not a major problem for studies that require long term PM2.5 data sets. These results have important implications for satellite studies especially over areas where ground-based measurements are not available.