On the potential of regional-scale emissions zoning as an air quality management tool for the grand canyon

Air arriving at the Grand Canyon of the Colorado River during 1988-1989 is attributed to one of four geographic quadrants--NE, SE, SW, NW--on the basis of routinely calculated back-trajectories. Most of the haze observed at the Canyon is attributed to the SW quadrant, which contains the populous and industrialized areas of southern California. Air from either northern quadrant tends to be significantly clearer than air from either southern quadrant. Clear northern air is most common during the winter, and is rarely observed during the summer tourist season, when steady flow from the southwest is the norm. Various possible interpretations of these empirical results are discussed, with varying implications for emissions management policy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31947/1/0000900.pd

Development of Techniques to Calibrate and Derive Basic and Advanced Visibility Metrics from Digital Imagery

Images captured with consumer grade digital cameras can be used to estimate visual air quality metrics directly from image pixel data. These indices can be classified as basic and advanced. Basic metrics are calculated using digital image data collected, manipulated, and output by the camera and include sky conditions and target perceptibility. Advanced metrics use the raw or minimally processed camera sensor data to determine characteristics of the scene without artificial “enhancements ” added by camera firmware to make the image appear “better ” to the end user. Though all consumer grade digital cameras produce images pleasing to the end user and may be usable for basic air quality metrics; most do not make raw image data available. In addition, the algorithms used to convert raw sensor data to final image data are proprietary and not made available by manufacturers. This means advanced image metrics cannot be accurately determined from typical consumer grade digital cameras. Two digital camera models are used to demonstrate how digital cameras acquire and then process the raw image data into a typical “pleasing ” image for consumer use. The Olympus 5060 digital camera represents a camera typically used to acquire images. Because it also makes raw data available, it is used to show that this processing (the camera “black box”) is based on nonlinear algorithms. In contrast, the Olympus C-730 camera’s algorithms are available and can be used for advanced image metrics