Effects of land use data on dry deposition in a regional photochemical model for eastern Texas

Land use data are among the inputs used to determine dry deposition velocities for photochemical grid models such as the Comprehensive Air Quality Model with extensions (CAMx) that is currently used for attainment demonstrations and air quality planning by the state of Texas. The sensitivity of dry deposition and O3 mixing ratios to land use classification was investigated by comparing predictions based on default U.S. Geological Survey (USGS) land use data to predictions based on recently compiled land use data that were collected to improve biogenic emissions estimates. Dry deposition of O3 decreased throughout much of eastern Texas, especially in urban areas, with the new land use data. Predicted 1-hr averaged O3 mixing ratios with the new land use data were as much as 11 ppbv greater and 6 ppbv less than predictions based on USGS land use data during the late afternoon. In addition, the area with peak O3 mixing ratios in excess of 100 ppbv increased significantly in urban areas when deposition velocities were calculated based on the new land use data. Finally, more detailed data on land use within urban areas resulted in peak changes in O3 mixing ratios of approximately 2 ppbv. These results indicate the importance of establishing accurate, internally consistent land use data for photochemical modeling in urban areas in Texas. They also indicate the need for field validation of deposition rates in areas experiencing changing land use patterns, such as during urban reforestation programs or residential and commercial development.     

Sensitivity of biogenic secondary organic aerosols to future climate change at regional scales: An online coupled simulation

Biogenic emissions and secondary organic aerosols (SOA) are strongly dependent on climatic conditions. To understand the SOA levels and their sensitivity to future climate change in the United States (U.S.), we present a modeling work with the consideration of SOA formation from the oxidation of biogenic emissions with atmospheric oxidants (e.g., OH, O₃, and NO₃). The model simulation for the present-day climate is evaluated against satellite and ground-based aerosol measurements. Although the model underestimates aerosol concentrations over the northwestern U.S. due to the lack of fire emissions in the model simulations, overall, the SOA results agree well with previous studies. Comparing with the available measurements of organic carbon (OC) concentrations, we found that the amount of SOA in OC is significant, with the ratio ranging from 0.1 to 0.5/0.6. The enhanced modeling system driven by global climate model output was also applied for two three-year one-month simulations (July, 2001–2003 and 2051–2053) to examine the sensitivity of SOA to future climate change. Under the future two emissions scenarios (A1B and A2), future temperature changes are predicted to increase everywhere in the U.S., but with different degrees of increase in different regions. As a result of climate change in the future, biogenic emissions are predicted to increase everywhere, with the largest increase (～20%) found in the southeastern and northwestern U.S. under the A1B scenario. Changes in SOA are not identical with those in biogenic emissions. Under the A1B scenario, the biggest increase in SOA is found over Texas, with isoprene emissions being the major contributor to SOA formation. The range of change varies from 5% over the southeast region to 26% over Texas. The changes in either biogenic emissions or SOA under the two climate scenarios are different due to the differences in climatic conditions. Our results also suggest that future SOA concentrations are also influenced by several other factors such as the partitioning coefficients, the atmospheric oxidative capability, primary organic carbon aerosols and anthropogenic emissions.     

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 leaf biomass densities associated with these land use classifications ranged from 0 to 556 g/m², with the highest assigned total and oak leaf biomass densities located in central and eastern Texas. The land cover data were used as input to a biogenic emissions model, GLOBEIS2. Estimates of biogenic emissions of isoprene 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 of Texas.     

Effects of Land Use Data on Dry Deposition in a Regional Photochemical Model for Eastern Texas

ABSTRACT

Land use data are among the inputs used to determine dry deposition velocities for photochemical grid models such as the Comprehensive Air Quality Model with extensions (CAMx) that is currently used for attainment demonstrations and air quality planning by the state of Texas. The sensitivity of dry deposition and O₃ mixing ratios to land use classification was investigated by comparing predictions based on default U.S. Geological Survey (USGS) land use data to predictions based on recently compiled land use data that were collected to improve biogenic emissions estimates. Dry deposition of O₃ decreased throughout much of eastern Texas, especially in urban areas, with the new land use data. Predicted 1-hr averaged O₃ mixing ratios with the new land use data were as much as 11 ppbv greater and 6 ppbv less than predictions based on USGS land use data during the late afternoon. In addition, the area with peak O₃ mixing ratios in excess of 100 ppbv increased significantly in urban areas when deposition velocities were calculated based on the new land use data. Finally, more detailed data on land use within urban areas resulted in peak changes in O₃ mixing ratios of ~2 ppbv. These results indicate the importance of establishing accurate, internally consistent land use data for photochemical modeling in urban areas in Texas. They also indicate the need for field validation of deposition rates in areas experiencing changing land use patterns, such as during urban reforestation programs or residential and commercial development.     

Airborne observations of vegetation and implications for biogenic emission characterization

Measuring hydrocarbons from aircraft represents one way to infer biogenic emissions at the surface. The focus of this paper is to show that complementary remote sensing information can be provided by optical measurements of a vegetation index, which is readily measured with high temporal coverage using reflectance data. We examine the similarities between the vegetation index and in situ measurements of the chemicals isoprene, methacrolein, and alpha-pinene to estimate whether the temporal behavior of the in situ measurements of these chemicals could be better understood by the addition of the vegetation index. Data were compared for flights conducted around Houston in August and September 2000. The three independent sets of chemical measurements examined correspond reasonably well with the vegetation index curves for the majority of flight days. While low values of the vegetation index always correspond to low values of the in situ chemical measurements, high values of the index correspond to both high and low values of the chemical measurements. In this sense it represents an upper limit when compared with in situ data (assuming the calibration constant is adequately chosen). This result suggests that while the vegetation index cannot represent a purely predictive quantity for the in situ measurements, it represents a complementary measurement that can be useful in understanding comparisons of various in situ observations, particularly when these observations occur with relatively low temporal frequency. In situ isoprene measurements and the vegetation index were also compared to an isoprene emission inventory to provide additional insight on broad issues relating to the use of vegetation indices in emission database development.     

Changing weather and climate in Northern Ghana: comparison of local perceptions with meteorological and land cover data

Regional Environmental Change - Local perspectives on changing weather and climate and analyses of meteorological data represent two different but potentially complementary ways of knowing about...     

Future land use and land cover influences on regional biogenic emissions and air quality in the United States

A regional modeling system was applied with inputs from global climate and chemistry models to quantify the effects of global change on future biogenic emissions and their impacts on ozone and biogenic secondary organic aerosols (BSOA) in the US. Biogenic emissions in the future are influenced by projected changes in global and regional climates and by variations in future land use and land cover (LULC). The modeling system was applied for five summer months for the present-day case (1990–1999, Case 1) and three future cases covering 2045–2054. Individual future cases were: present-day LULC (Case 2); projected-future LULC (Case 3); and future LULC with designated regions of tree planting for carbon sequestration (Case 4). Results showed changing future meteorology with present-day LULC (Case 2) increased average isoprene and monoterpene emission rates by 26% and 20% due to higher temperature and solar insolation. However when LULC was changed together with climate (Case 3), predicted isoprene and monoterpene emissions decreased by 52% and 31%, respectively, due primarily to projected cropland expansion. The reduction was less, at 31% and 14% respectively, when future LULC changes were accompanied by regions of tree planting (Case 4). Despite the large decrease in biogenic emission, future average daily maximum 8-h (DM8H) ozone was found to increase between +8 ppbv and +10 ppbv due to high future anthropogenic emissions and global chemistry conditions. Among the future cases, changing LULC resulted in spatially varying future ozone differences of ?5 ppbv to +5 ppbv when compared with present-day case. Future BSOA changed directly with the estimated monoterpene emissions. BSOA increased by 8% with current LULC (Case 2) but decreased by 45%–28% due to future LULC changes. Overall, the results demonstrated that on a regional basis, changes in LULC can offset temperature driven increases in biogenic emissions, and, thus, LULC projection is an important factor to consider in the study of future regional air quality.     

The contribution of biological particles to observed particulate organic carbon at a remote high altitude site

Although a significant fraction of atmospheric particulate mass is organic carbon, the sources of particulate organic carbon (POC) are not always apparent. One potential source of atmospheric POC is biological particles, such as bacteria, pollen, and fungal spores. Measurements of POC and biological particles, including bacteria, fungal spores, and pollen, were made as part of the Storm Peak Aerosol and Cloud Characterization Study in Steamboat Springs, CO in March–April 2008. Biological particles were identified and characterized using several methods. The results suggest that biological particles could account for an average of 40% of the organic carbon mass in particles with aerodynamic diameters less than 10 μm. These estimates of POC mass from biological particles are highly uncertain; however, the results suggest that biological particles could be a significant source of organic aerosol in the background continental atmosphere and further observations are needed to better constrain these estimates.