Climate change scenarios are increasingly being used to model future air quality. Typically this involves a sequence of models, with global climate model output scenarios, projections of future emissions inventories based on assumptions of population and technology changes (e.g. cleaner car emissions), feeding an air quality model. While intrinsically uncertain, due to the long time lags involved, air quality projections are increasingly driving policy and management decisions. In some cases, such as the regional haze rule, these projections are needed for federal, state, and tribal implementation plans to show compliance and/or mitigation with an air quality regulation (e.g. the EPA regional haze rule).

Wildland fire has been shown to be a large, and in many cases, the single largest contributor to air quality concerns such as particular matter (PM) to ozone to regional haze is wildland fire (e.g., Ames and Malm, 2001). Wildland fire refers to both naturally occurring fire, and prescribed fire, both of which are likely to increase for the next several decades as land areas come into balance after a history of fire suppression. Because of it’s significant role in air quality, air quality projections must be able to include fire emissions in their emissions inventories. To date this has been accomplished mainly in ways that do not ensure self-consistency between future meteorology projections and fire location and timing [e.g., WRAP, 2002.]

We are developing a nationwide Fire Scenario Builder (FSB) that creates self-consistent, spatially explicit U.S. prescribed and wildland fire scenarios for use in modeling both current and projected fire effects, including fire emissions. The FSB creates stochastic fire location and size scenarios that are consistent with known weather, vegetation, and land management controls on fire ignition and spread. At its core, the FSB is based on a coarse-scale classification and quantification of fire regimes and tunable land management strategies. Fire regime attributes are created from reconstructed fire history, historical fire records, and potential natural vegetation. The FSB also utilizes weather and climate information from global climate model output. The climate projections used in this effort are those from the NCAR Climate Systems Model (CSM) at T42 resolution atmospheric resolution, but the FSB methodology is not limited to a particular model or resolution. The FSB utilizes in parallel known statistical relationships between climate, vegetation, and fire to create fire-ignition probabilities and a probability distribution of estimated fire sizes. The FSB is still under development, but we present initial results from forecasts for 1996-2000 and 2046-2050 based on initial vegetation, lightning, and relative humidity relationships.

References

Ames, R.B. and W.C. Malm. 2001. Chemical species’ contributions to the upper extremes of aerosol fine mass. Atmospheric Environment, 35, 5193 – 5204.

WRAP, 2002: Integrated assessment update and 2018 emissions inventory for prescribed fire, wildfire, and agricultural burning. Prepared by Air Sciences, Inc. , Lakewood, CO.