Mark Estes

A land use database and examples of biogenic isoprene emission estimates for the state of Texas, USA

Using data from a variety of sources, land use and vegetation in Texas were mapped with a spatial resolution of approximately 1 km. Over 600 classifications were used to characterize the land use and land cover throughout the state and field surveys were performed to assign leaf biomass densities, by species, to the land cover classifications. The total leafbiomass densities associated with these land use classifications ranged from 0 to 556 g/m 2 , with the highest assigned total and oak leafbiomass densities located in central and eastern Texas. The land cover data were used as input to a biogenic emissions model, GLOBEIS2. Estimates ofbiogenic emissions ofisoprene based on GLOBEIS2 and the new land cover data showed significant differences when compared to biogenic isoprene emissions estimated using previous land cover data and emission estimation procedures. For example, for one typical domain in eastern Texas, total daily isoprene emissions increased by 38% with the new modeling tools. These results may ultimately affect the way in which ozone and other photochemical pollutants are modeled and evaluated in the state ofTexas. r 2001 Elsevier Science Ltd. All rights reserved.

Biogenic hydrocarbon emission estimates for North Central Texas

Abstract Biogenic hydrocarbon emissions were estimated for a 37 county region in North Central Texas. The estimates were based on several sources of land use/land cover data that were combined using geographical information systems. Field studies were performed to collect species and tree diameter distribution data. These data were used to estimate biomass densities and species distributions for each of the land use/land cover classifications. VOC emissions estimates for the domain were produced using the new land use/land cover data and a biogenic emissions model. These emissions were more spatially resolved and a factor of 2 greater in magnitude than those calculated based on the biogenic emissions landuse database (BELD) commonly used in biogenic emissions models.

Formaldehyde Column Density Measurements as a Suitable Pathway to Estimate Near-Surface Ozone Tendencies from Space

In support of future satellite missions that aim to address the current shortcomings in measuring air quality from space, NASAs Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign was designed to enable exploration of relationships between column measurements of trace species relevant to air quality at high spatial and temporal resolution. In the DISCOVER-AQ data set, a modest correlation (r 2 = 0.45) between ozone (O3) and formaldehyde (CH2O) column densities was observed. Further analysis revealed regional variability in the O3-CH2O relationship, with Maryland having a strong relationship when data were viewed temporally and Houston having a strong relationship when data were viewed spatially. These differences in regional behavior are attributed to differences in volatile organic compound (VOC) emissions. In Maryland, biogenic VOCs were responsible for ~28% of CH2O formation within the boundary layer column, causing CH2O to, in general, increase monotonically throughout the day. In Houston, persistent anthropogenic emissions dominated the local hydrocarbon environment, and no discernable diurnal trend in CH2O was observed. Box model simulations suggested that ambient CH2O mixing ratios have a weak diurnal trend (±20% throughout the day) due to photochemical effects, and that larger diurnal trends are associated with changes in hydrocarbon precursors. Finally, mathematical relationships were developed from first principles and were able to replicate the different behaviors seen in Maryland and Houston. While studies would be necessary to validate these results and determine the regional applicability of the O3-CH2O relationship, the results presented here provide compelling insight into the ability of future satellite missions to aid in monitoring near-surface air quality.