Indicator
Regional Visibility 90th Percentile ("Worst Visibility Days")
2019 Evaluation
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This indicator measures regional visibility on the "worst" days of the year at non-urban areas in the Tahoe Basin. Visibility measures the distance at which an object or light can be clearly discerned by the human eye. Sources of locally generated haze pollutants include entrained/suspended roadway particles, vehicle emissions, residential wood burning, campfires, prescribed fires, and wildfires. Some particles responsible for the degradation of regional visibility in the Tahoe Basin include dust and other pollutants transported into the Basin from areas as far as Asia, and record-setting catastrophic wildfires throughout California and the western states in the last five years. Regional programs such as decreasing the number of polluting wood stoves and work to improve forest health aim to increase regional visibility. Regional visibility is monitored at DL Bliss State Park as part of the national IMPROVE monitoring network. 

Regional Visibility 90Th Percentile (Worst Visibility Days) Bliss State Park - Copy.jpg
Status

Regional visibility conditions monitored at the DL Bliss IMPROVE monitoring station.

2019 Evaluation
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Status
At or Somewhat Better Than Target
Trend
Little or No Change
Confidence
High
Applicable Standard
AQ6: Achieve an extinction coefficient of 34 Mm-1 at least 90 percent of the time as calculated from aerosol species concentrations measured at the Bliss State Park monitoring site (visual range of 115 km, 71 miles).
Key Points
  • Visibility on the worst visibility days at DL Bliss State Park site has not changed significantly since monitoring began in the early 1990’s.
  • Decreases in visibility on the worst days are largely attributed to smoke from severe wildfires.
Evaluation Map
Description

Regional visibility monitoring station at DL Bliss State Park.

About the Threshold
This indicator measures regional visibility and the distance that the human eye can see. It is measured by using a reconstructed light extinction (bext) value, which is derived from an equation that combines measured concentrations of several gasses and particles. The equation is corrected for humidity and natural “background” light scattering. Bext is summarized by “average visibility days” (50th percentile values) and “worst visibility days” (90th percentile values) for each year, followed by calculating the 3-year running average. This threshold standard has been adopted to protect regional visibility and air quality.
Particulate matter in the atmosphere is the primary driver of visibility impairment because of the optical properties and long retention times in the air (Green et al. 2011, 201). The main sources of particulate matter in the basin are residential and wildfire smoke, and entrained roadway dust (DRI 2011a). Effective motor vehicle tail pipe emission controls, residential wood combustion controls, appropriately managed prescribed burning, and road dust emission control aid in improving regional visibility conditions (Chen, Watson, and Wang 2011). There is uncertainty related to visibility condition in the future due to predicted increases in frequency and intensity of wildfires in the western U.S.
Delivering and Measuring Success

EIP Indicators

Example EIP Projects

Monitoring Programs

  • Regional Visibility Monitoring

    Visibility monitoring data are collected, analyzed, and reported by the IMPROVE (national Interagency Monitoring of Protected Environments) network using nationally accepted protocols.

Rationale Details
The current status was determined based on the 90th percentile "worst day" measurement at the DL Bliss monitoring station during the most recent year monitoring data is available, 2018. The reading in 2018 was an extinction coefficient of 33.8 compared to a maximum allowable level of 34, which is 99% of the maximum value. Therefore, the status is considered at or somewhat better than target.
Trend was determined by all year readings of 90th percentile "worst days" at the DL Bliss monitoring station from 1993-2018 using the Theil-Sen robust regression method. There was not a significant trend during this time frame, with various ups and downs through the years.
Confidence Details
High. Monitoring was conducted using strict protocols.
High. Monitoring was conducted using strict protocols and there is a long data set to analyze trend.
High.
Additional Figures and Resources

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