Abstract. In the US wildfires and prescribed burning present significant challenges to air regulatory agencies attempting to achieve and maintain compliance with National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. Wildland fire emission inventories (EI) provide critical inputs for atmospheric chemical transport models used by air regulatory agencies to understand and to predict the impact of fires on air quality. Fire emission factors (EF), which quantify the amount of pollutants released per mass of biomass burned, are essential input for the emission models used to develop EI. Over the past decade substantial progress has been realized in characterizing the composition of fresh biomass burning (BB) smoke and in quantifying BB EF. However, most BB studies of temperate ecosystems have focused on emissions from prescribed burning. Little information is available on EF for wildfires in the temperate forests of the conterminous US. Current emission estimates for US wildfires rely largely on EF measurements from prescribed burns and it is unknown if these fires are a reasonable proxy for wildfires. Over 8 days in August of 2011 we deployed airborne chemistry instruments and sampled emissions from 3 wildfires and a prescribed fire that occurred in mixed conifer forests of the northern Rocky Mountains. We measured the combustion efficiency, quantified as the modified combustion efficiency (MCE), and EF for CO2, CO, and CH4. Our study average values for MCE, EFCO2, EFCO, and EFCH4 were 0.883, 1596 g kg−1, 135 g kg−1, 7.30 g kg−1, respectively. Compared with previous field studies of prescribed fires in similar forest types, the fires sampled in our study had significantly lower MCE and EFCO2 and significantly higher EFCO and EFCH4. An examination of our study and 47 temperate forest prescribed fires from previously published studies shows a clear trend in MCE across US region/fire type: southeast (MCE = 0.933) > southwest (MCE = 0.922) > northwest (MCE = 0.900) > northwest wildfires (MCE = 0.883). The fires sampled in this work burned in areas reported to have moderate to heavy components of standing dead trees and dead down wood due to insect activity and previous fire, but fuel consumption data was not available for any of the fires. However, fuel consumption data was available for 18 prescribed fires reported in the literature. For these 18 fires we found a significant negative correlation (r =-0.83, p-value = 1.7e-5) between MCE and the ratio of heavy fuel (large diameter dead wood and duff) consumption to total fuel consumption. This observation suggests the relatively low MCE measured for the fires in our study resulted from the availability of heavy fuels and conditions that facilitated combustion of these fuels. More generally, our measurements and the comparison with previous studies indicate that fuel composition is an important driver of variability in MCE and EF. This study only measured EF for CO2, CO, and CH4; however, we used our study average MCE to estimate wildfire EF for PM2.5 and 13 other species using EF–MCE linear relationships reported in the literature. The EF we derived for several non-methane organic compounds (NMOC) were substantially larger (by a factor of 1.5 to 4) than the published prescribed fire EF. Wildfire EFPM2.5 estimated in our analysis is approximately twice that reported for temperate forests in a two widely used reviews of BB emission studies. Likewise, western US wildfire PM2.5 emissions reported in a recent national emission inventory are based on an effective EFPM2.5 that is only 40% of that estimated in our study. If the MCE of the fires sampled in this work are representative of the combustion characteristics of wildfires across western US forests then the use of EF based on prescribed fires may result in a significant underestimate of wildfire PM2.5 and NMOC emissions. Given the magnitude of biomass consumed by western US wildfires, the failure to use wildfire appropriate EFPM2.5 has significant implications for the forecasting and management of regional air quality. The contribution of wildfires to NAAQS PM2.5 and Regional Haze may be underestimated by air regulatory agencies.
Complex statistical data analysis of electric power consumption, consumption of energy resources and production volumes