Look for complete geospatial metadata in this layer's associated xml document available from the download link * Metric Name: Potential Avoided Smoke Production Index * Tier: 1 * Data Vintage: 2022. Includes disturbances through the end of 2022. * Unit Of Measure: 0 - 1, **** a unitless number serving an an index; on a per 30-m pixel basis * Metric Definition and Relevance: This is an index of how much _less_ smoke (as defined by PM2.5 emissions) would be produced from a given pixel by burning under moderate fire weather conditions rather than the extreme conditions that lead to high-severity smoke production. This serves as a proxy for efforts to minimize smoke emissions by allowing a given area to burn under more desirable conditions (e.g., prescribed burning conditions) vs. how it would burn under extreme conditions. Since identical fuelbeds are used as inputs in the high-severity and low-severity model runs, the index does _not_ represent the effects of fuel treatments on subsequent wildfire. Rather, this metric represents the maximum potential difference between emissions under high vs. moderate fire weather conditions. Summing these reductions over large areas would be unrealistic because wildland fire burns with a mix of intensities and severities over landscapes, and does not burn everywhere in California, every year. Wildland fire is often self-limiting in extent. In other words, wildfires may stop spreading when they reach the boundary of a recent burn. Since prescribed fire and managed wildfire can be selected to burn under moderate fire weather conditions, proactive fire use can shift high-severity-type fire emissions to low-severity-type fire emissions. This metric provides a rough index of the potential fire emissions benefits if a fire is allowed to burn under moderate weather conditions rather than in a wildfire under extreme weather. By showing the spatial variation in this potential benefit, this index is intended to help identify where fire management may have the greatest emissions benefit. It may be useful for regional scale planning and/or prioritization. It is important to note that not all managed fire will produce an emissions benefit, because wildfire may not have otherwise burned in that location within the lifespan of the managed fire’s effects, and the managed fire’s footprint may not prevent a subsequent wildfire from burning in the same location. Furthermore, actual weather conditions vary from those used in model inputs. Therefore, the map does not represent actual avoided smoke production (PM2.5 emissions) during an actual fire event that may occur in the future. For data users interested in near-term smoke forecasts that reflect the environmental drivers of emissions, project-specific modeling tools are recommended. For example, the BlueSky Playground (https://tools.airfire.org/playground) can tailor model inputs based on the fuel and moisture conditions observed or planned for in the project area of interest. Potential smoke emissions do not consider the probability of a fire or the transport of smoke to more distant locations; they only reflect what would happen locally if a pixel were to burn. * Creation Method: This index a unitless number (ranging between 0 and 1) on a per 30-meter pixel basis, which is calculated using the following equation: Potential Avoided Smoke Production Index = ( Di for a given pixel ) / ( the maximum Di statewide) where Di = the difference in modeled PM2.5 emissions between high severity and low severity scenarios for pixel i = (high severity PM2.5 emissions scenario for pixel i) – (low severity PM2.5 emissions scenario for pixel i) “High severity PM2.5 emissions” were calculated as described for the “POTENTIAL TOTAL SMOKE PRODUCTION INDEX” metric. Calculated with SpatialFOFEM (First Order Fire Effects Model), embedded in FlamMap 6.2. Fuels are LCP and FCCS 2022 from LANDFIRE (LCP_LF2022_FBFM40_220_CONUS and LF2022_FCCS_220_CONUS). Conditions for Low severity PM 2.5 emissions were calculated for the following settings (FOFEM parameters used for this application): Seasonality: Spring Canopy consumption - 5% Duff moisture - 75% 1 hour fuel moisture - 14% 10-hour fuel moisture - 16% 100-hour fuel moisture - 18% 1000-hour fuel moisture - 25% * Credits: LANDFIRE FCCS ([LANDFIRE Program: Data Products - Fuel - Fuel Characteristic Classification System Fuelbeds](https://www.landfire.gov/fccs.php)) 2022 Rocky Mountain Research Station https://www.firelab.org/project/fofem-fire- effects-model