Grantee Research Project Results
2019 Progress Report: Planning for an Unknown Future: Incorporating Meteorological Uncertainty into Predictions of the Impact of Fires and Dust on US Particulate Matter
EPA Grant Number: R835884Title: Planning for an Unknown Future: Incorporating Meteorological Uncertainty into Predictions of the Impact of Fires and Dust on US Particulate Matter
Investigators: Fischer, Emily , Pierce, Jeffrey , Barnes, Elizabeth
Institution: Colorado State University
EPA Project Officer: Chung, Serena
Project Period: January 1, 2016 through December 31, 2018 (Extended to December 31, 2020)
Project Period Covered by this Report: January 1, 2019 through December 31,2019
Project Amount: $349,969
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text | Recipients Lists
Research Category: Air , Climate Change , Early Career Awards
Objective:
The objective of this research is to determine how model uncertainty in future meteorology translates into uncertainty in the contributions of smoke and dust to future particulate matter (PM) episodes.
Progress Summary:
We have developed two manuscripts. The first manuscript focuses on wildfires and employs an objective method for choosing environmental variables that best explain historical wildfire variability. This allows us to build on the relationships observed by previous studies while putting forth a new method for identifying key variables. We use Lasso regression to objectively identify the antecedent season for a set of environmental conditions that best explain observed variance in interannual summertime (June, July, August) large wildfire (> 1000 acres) burn area for western U.S. ecoregions. We focus on these months as they have the greatest burn area in recent decades. This is done individually for ecoregions, to allow for varying relationships between burn area and environmental conditions. We use CMIP5 model output to quantify the mean change and future spread in the environmental variables that best explain historical variance for each fire-prone ecoregion. We contrast the trends and spread between models made for each candidate variable and discuss what the changes may imply for future burn area. This work shows that the predicted change in burn area is extremely sensitive to what environmental predictors are chosen to drive burn area.
We have also prepared and submitted a second manuscript to the Journal of Geophysical Research. This manuscript examines how environmental conditions that drive fine dust emissions and concentrations in the southwestern U.S. change in the future and what these changes imply for future dust concentrations based on historical relationships. We examined environmental conditions identified by previous studies to influence dust emissions including temperature, vapor pressure deficit, relative humidity, precipitation, soil moisutre, wind speed and leaf area index. The manuscript quantifies fine dust concentrations in the U.S. southwest dust season (March through July) using fine iron as a dust proxy, quantified with measurements from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network between 1995 and 2015. We show that the largest contribution to the spread in future dust concentration estimates come from the choice of variable used to explain observed variability in dust concentrations. The spread between variable estimates is larger than the spread between climate scenarios, or intermodel spread. The majority of models in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) that simulate leaf area index (LAI, a quantity anticorrelated with dust emissions and concentrations) show increasing leaf area index in the southwest U.S. throughout the 21st century. Based on our linear estimates of dust dependence on LAI, this LAI incresae would result in reduced dust concentrations in the future. However, when we objectively select environmental predictors of dust concentrations using Lasso regression, LAI is not selected in favor of other variables. When using a linear combination of the objectively selected environmental variables, we estimate that the southwest U.S. future mean dust concentrations will increast by 0.24 ug m-3 (12%) by the end of the 21st century for RCP 8.5. This estimated increase in fine dust concentration is driven by decreases in relative humidity, preciptation, soil moisture, and buffered by decreased wind speeds.
Future Activities:
Our goals for the no-cost extension year is to shepherd two manuscripts through the review process at Earth’s Future and the Journal of Geophsical Research.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
| Other project views: | All 18 publications | 9 publications in selected types | All 9 journal articles |
|---|
| Type | Citation | ||
|---|---|---|---|
|
|
Pratt JR, Gan RW, Ford B, Brey S, Pierce JR, Fischer EV, Magzamen S. A national burden assessment of estimated pediatric asthma emergency department visits that may be attributed to elevated ozone levels associated with the presence of smoke. Environmental Monitoring and assessment 2019;191(2):269. |
R835884 (2019) R835884 (Final) |
Exit Exit |
|
|
Lipner EM, O'Dell K, Brey SJ, Ford B, Pierce JR, Fischer EV, Crooks JL. The associations between clinical respiratory outcomes and ambient wildfire smoke exposure among pediatric asthma patients at National Jewish Health. GeoHealth 2019;3(6):146-59. |
R835884 (2019) R835884 (Final) |
Exit Exit |
Supplemental Keywords:
particulate matter, fires, dust, climate, synoptic meteorologyProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.