Land use forecasting in regional air quality modeling
Abstract
When estimating the impacts of air pollutant control measures on future air
quality, it is typically presumed that land covers remain constant. However, changes in
land cover can have an impact on air pollutant concentrations. This work develops and
applies modeling methodologies for land cover and regional air quality interactions, using
regions in and around central and eastern Texas as case studies. Changes in land cover
considered in this work are driven by urban development and inter-annual variability in
climate. Urbanization, associated with changes in biogenic emissions and air pollutant
dry deposition, leads to changes in daily maximum ozone concentration, that range from -
0.94 to 0.12 ppb for the Austin area. In comparison, the effects of the same urban
development led to changes in anthropogenic emissions that led to changes ranging from
-7.0 to -1.3 ppb in ozone concentrations for the Austin area. Inter-annual variation in
climate led much larger changes in daily maximum ozone concentrations than changes
due to urbanization. Changes in daily maximum ozone concentrations, due to inter-
annual variation in biogenic emissions associated with inter-annual variability in climate,
ranged from -5.9 to 9.7 ppb for the Austin area and 0.0 to 18 ppb for the Houston area.
Description
text
Subject
Air quality--Texas--Austin--Forecasting--Mathematical models
Air quality--Texas--Houston--Forecasting--Mathematical models
Ozone--Air content--Texas--Measurement--Forecasting
Air--Pollution--Texas--Forecasting
Greenhouse gases--Texas
Urbanization--Environmental aspects--Texas
Climatic changes--Texas
Air quality--Texas--Houston--Forecasting--Mathematical models
Ozone--Air content--Texas--Measurement--Forecasting
Air--Pollution--Texas--Forecasting
Greenhouse gases--Texas
Urbanization--Environmental aspects--Texas
Climatic changes--Texas
Collections
Related items
Showing items related by title, author, creator and subject.
-
An analysis of the petroleum industry’s inability to deliver on early production forecasts : shortcomings in probabilistic modeling
Petutschnig, David (2019-12)Previous studies have confirmed that production forecasts in the oil and gas industry are exposed to a variety of biases. This thesis extends those previous findings by investigating the quality of production forecasts for ... -
Temporal geoprocessing for hydroperiod analysis of the Kissimmee River
Sorenson, Jennifer Kay; Maidment, David R. (Center for Research in Water Resources, University of Texas at Austin, 2004-05) -
Quantification of production recovery using probabilistic approach and semi-analytical model for unconventional oil reservoirs
Choi, Bong Joon (2015-12)Decline curve analysis is widely applied for production forecasting in oil & gas industry. However, many models do not work for super-tight, unconventional wells with dominant fracture flows. Some novel decline models have ...