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Papers by Brian Lamb

Aerosol and Air Quality Research, 2020

In the beginning of 2020, the global human population encountered the pandemic of novel coronavir... more In the beginning of 2020, the global human population encountered the pandemic of novel coronavirus disease 2019 (COVID-19). Despite social and economic concerns, this epidemiologic emergency has brought unexpected positive consequences for environmental quality as human activities were reduced. In this paper, the impact of restricted human activities on urban air quality in Ecuador is investigated. This country implemented a particularly strict set of quarantine measures at the very dawn of the exponential growth of infections on March 17, 2020. As a result, significant reductions in the concentrations of NO 2 (-68%), SO 2 (-48%), CO (-38%) and PM 2.5 (-29%) were measured in the capital city of Quito during the first month of quarantine. This large drop in air pollution concentrations occurred at all the monitoring sites in Quito, serving as a valuable proof of the anthropogenic impact on urban air quality. The spatial evolution of atmospheric pollution using observed surface and satellite data, showed different results for the two major cities: Quito and Guayaquil. While the population in Quito adhered to the quarantine measures immediately, in the port city of Guayaquil, quarantine measures were slow to be adopted and, thus, the effect on air quality in Guayaquil occurred more slowly. This lag could have a considerable cost to the mortality rate in the port city, not only due to the spread of the disease but also due to the poor air quality. Overall, the air quality data demonstrate how quickly air quality can improve when emissions are reduced.

Sustainability

In the light of the 21st century, after two devastating world wars, humanity still has not learne... more In the light of the 21st century, after two devastating world wars, humanity still has not learned to solve their conflicts through peaceful negotiations and dialogue. Armed conflicts, both international and within a single state, still cause devastation, displacement, and death all over the world. Not to mention the consequences that war has on the environment. Due to a lack of published research about war impact on modern air quality, this work studies air pollution evolution during the first months of the Russian-Ukrainian conflict. Satellite images of NO2, CO, O3, SO2, and PM2.5 over Ukrainian territory and PM2.5 land monitoring data for Kyiv were analyzed. The results showed that NO2 and PM2.5 correlated the most with war activities. CO and O3 levels increased, while SO2 concentrations reduced four-fold as war intensified. Drastic increases in pollution (especially PM2.5) from bombing and structural fires, raise additional health concerns, which might have serious implications ...

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC5 Moses Lake on-farm site.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC4 Moscow Mountain on-farm... more This is the AmeriFlux version of the carbon flux data for the site US-RC4 Moscow Mountain on-farm site.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC2 Cook Agronomy Farm - Co... more This is the AmeriFlux version of the carbon flux data for the site US-RC2 Cook Agronomy Farm - Conventional Till.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC1 Cook Agronomy Farm - No... more This is the AmeriFlux version of the carbon flux data for the site US-RC1 Cook Agronomy Farm - No Till.

Air-quality modeling is an important tool for evaluating strategies for complying with the NAAQS.... more Air-quality modeling is an important tool for evaluating strategies for complying with the NAAQS. Two perennial issues of interest are the effects of long-range transport (LRT) and of stratospheric ozone intrusion (SOI) on air quality. Under the EPA Exceptional Events Policy, for example, a nominal exceedance can be excluded from design value calculation if it can be credibly ascribed to long-range transport or stratospheric ozone intrusion. Air-quality modeling is potentially an appropriate tool for attempting demonstration of LRT and SOI in making a case for Exceptional Event status for an exceedance. Also, ample evidence exists that local air pollution should sometimes be viewed in the context of a baseline pollution levels, and that these baseline levels are influenced by LRT and SOI (Wigder et al., 2013).

The effects of global changes upon regional ozone pollution in the United States J. Chen, J. Avis... more The effects of global changes upon regional ozone pollution in the United States J. Chen, J. Avise, B. Lamb, E. Salathé, C. Mass, A. Guenther, C. Wiedinmyer, J.-F. Lamarque, S. O’Neill, D. McKenzie, and N. Larkin Washington State University, Pullman, WA, USA University of Washington, Seattle, WA, USA National Center for Atmospheric Research, Boulder, CO, USA United States Department of Agriculture, Natural Resources Conservation Service, Portland, OR, USA United States Department of Agriculture, Forest Service, Seattle, WA, USA now at: National Research Council Canada, Ottawa, ON, Canada now at: California Air Resources Board, Sacramento, CA, USA

Chemical transport models (CTM) are widely used for air quality modeling, but these models miss f... more Chemical transport models (CTM) are widely used for air quality modeling, but these models miss forecasting some air pollution events, and require a lot of computational power. In Kennewick, WA, elevated O3 episodes can occur during the summer and early fall, but the CTM-based operational forecasting system (AIRPACT) struggles to capture them. This research used the 2015 – 2018 historical archives from the Weather Research and Forecasting (WRF) meteorological model forecasts produced daily by the University of Washington, and O3 observation data at Kennewick to train two machine learning modeling frameworks, ML1 and ML2 for a reliable forecasting system. ML1 used the random forest (RF) classifier and multiple linear regression (MLR) models, and ML2 used a two-phase RF regression model with best-fit weighting factors. Since April 2019, the ML modeling frameworks have been used to produce daily 72-hour O3 forecasts and have provided the forecasts via the web for the agency and public ...

Journal of Sensor and Actuator Networks, 2017

In the coming decades, as we experience global population growth and global aging issues, there w... more In the coming decades, as we experience global population growth and global aging issues, there will be corresponding concerns about the quality of the air we experience inside and outside buildings. Because we can anticipate that there will be behavioral changes that accompany population growth and aging, we examine the relationship between home occupant behavior and indoor air quality. To do this, we collect both sensor-based behavior data and chemical indoor air quality measurements in smart home environments. We introduce a novel machine learning-based approach to quantify the correlation between smart home features and chemical measurements of air quality, and evaluate the approach using two smart homes. The findings may help us understand the types of behavior that measurably impact indoor air quality. This information could help us plan for the future by developing an automated building system that would be used as part of a smart city.

Atmospheric Chemistry and Physics Discussions, 2014

A number of numerical wind flow models have been developed for simulating wind flow at relatively... more A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ∼100 m); however, there are very limited observational data available for evaluating these high resolution models. This study presents high-resolution surface wind datasets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically-driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds collected on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. Wind speed did not have a simple, consistent trend with position on the slope during the downslope regime on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest me...

Tellus B, 2007

These measurements were used to calculate total ozone flux and partitioning between stomatal and ... more These measurements were used to calculate total ozone flux and partitioning between stomatal and non-stomatal sinks. Total ozone flux varied diurnally with maximum values reaching 100 µmol m −2 h −1 at midday and minimums at or near zero at night. Mean daytime canopy conductance was 0.5 mol m −2 s −1. During daytime, non-stomatal ozone conductance accounted for as much as 66% of canopy conductance, with the non-stomatal sink representing 63% of the ozone flux. Stomatal conductance showed expected patterns of behaviour with respect to photosynthetic photon flux density (PPFD) and vapour pressure defecit (VPD). Non-stomatal conductance for ozone increased monotonically with increasing PPFD, increased with temperature (T) before falling off again at high T, and behaved similarly for VPD. Daytime non-stomatal ozone sinks are large and vary with time and environmental drivers, particularly PPFD and T. This information is crucial to deriving mechanistic models that can simulate ozone uptake by different vegetation types.

Journal of the Air & Waste Management Association, 2012

The impact of climate change on surface-level ozone is examined through a multiscale modeling eff... more The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF E), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects of future anthropogenic emissions, biogenic emissions, and climate on the RRF E. For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF C or CAF CB when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF EC was calculated (RRF EC ¼ RRF E Â CAF C). In general, RRF EC > RRF E , which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF E than does future climate change itself. The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO X ¼ NO þ NO 2). Regions that are generally NO X limited show a decrease in ozone and RRF EC , while VOC-limited regions show an increase in ozone and RRF EC. Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF CB. Implications: We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO X emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO X emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Journal of Geophysical Research, 2006

Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is... more Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is subject to errors involving the column retrieval and the assumed relationship between HCHO columns and isoprene emissions, taken here from the GEOS-CHEM chemical transport model. Here we use a 6-year (1996-2001) HCHO column data set from the Global Ozone Monitoring Experiment (GOME) satellite instrument to (1) quantify these errors, (2) evaluate GOME-derived isoprene emissions with in situ flux measurements and a process-based emission inventory (Model of Emissions of Gases and Aerosols from Nature, MEGAN), and (3) investigate the factors driving the seasonal and interannual variability of North American isoprene emissions. The error in the GOME HCHO column retrieval is estimated to be 40%. We use the Master Chemical Mechanism (MCM) to quantify the time-dependent HCHO production from isoprene, aand b-pinenes, and methylbutenol and show that only emissions of isoprene are detectable by GOME. The time-dependent HCHO yield from isoprene oxidation calculated by MCM is 20-30% larger than in GEOS-CHEM. GOME-derived isoprene fluxes track the observed seasonal variation of in situ measurements at a Michigan forest site with a À30% bias. The seasonal variation of North American isoprene emissions during 2001 inferred from GOME is similar to MEGAN, with GOME emissions typically 25% higher (lower) at the beginning (end) of the growing season. GOME and MEGAN both show a maximum over the southeastern United States, but they differ in the precise location. The observed interannual variability of this maximum is 20-30%, depending on month. The MEGAN isoprene emission dependence on surface air temperature explains 75% of the month-to-month variability in GOME-derived isoprene emissions over the

International Journal of Mass Spectrometry, 2006

A proton transfer reaction mass spectrometer (PTR-MS) was redesigned and deployed to monitor sele... more A proton transfer reaction mass spectrometer (PTR-MS) was redesigned and deployed to monitor selected hydrocarbon emissions from in-use vehicles as part of the Mexico City Metropolitan Area (MCMA) 2003 field campaign. This modified PTR-MS instrument provides the necessary time response (<2 s total cycle time) and sensitivity to monitor the rapidly changing hydrocarbon concentrations, within intercepted dilute exhaust emission plumes. Selected hydrocarbons including methanol, acetaldehyde, acetone, methyl tertiary butyl ether (MTBE), benzene and toluene were among the vehicle exhaust emission components monitored. A comparison with samples collected in canisters and analyzed by gas chromatography provides validation to the interpretation of the ion assignments and the concentrations derived using the PTR-MS. The simultaneous detection of multiple hydrocarbons in dilute vehicle exhaust plumes provides a valuable tool to study the impact of driving behavior on the exhaust gas emissions.

Ecosystems, 2004

This report summarizes our current knowledge of leaf-level physiological processes that regulate ... more This report summarizes our current knowledge of leaf-level physiological processes that regulate carbon gain and water loss of the dominant tree species in an old-growth forest at the Wind River Canopy Crane Research Facility. Analysis includes measurements of photosynthesis, respiration, stomatal conductance, water potential, stable carbon isotope values, and biogenic hydrocarbon emissions from Douglas-fir 1 (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla), and western red cedar (Thuja plicata). Leaf-level information is used to scale fluxes up to the canopy to estimate gross primary production using a physiologybased process model. Both light-saturated and in situ photosynthesis exhibit pronounced vertical gradients through the canopy, but are consistently highest in Douglas-fir, intermediate in western hemlock, and lowest in western red cedar. Net photosynthesis and stomatal conductance are strongly dependent on vapor-pressure deficit in Douglas-fir, and decline through the course of a seasonal drought. Foliar respiration is similar for Douglas-fir and western hemlock, and lowest for western red cedar. Water-use efficiency varied with species and tree height, as indexed using stable carbon isotopes values for foliage. Leaf water potential is most negative for Douglas-fir and similar for western hemlock and western red cedar. Terpene fluxes from foliage equal approximately 1% of the net carbon loss from the forest. Modeled estimates based on physiological measurements show gross primary productivity (GPP) to be about 22 Mg C m)2 y)1. Physiological studies will be necessary to further refine estimates of stand-level carbon balance and to make long-term predictions of changes in carbon balance due to changes in forest structure, species composition, and climate.

Atmospheric Environment, 2009

A regional modeling system was applied with inputs from global climate and chemistry models to qu... more 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 þ8 ppbv and þ10 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 À5 ppbv to þ5 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.

Aerosol and Air Quality Research, 2020

In the beginning of 2020, the global human population encountered the pandemic of novel coronavir... more In the beginning of 2020, the global human population encountered the pandemic of novel coronavirus disease 2019 (COVID-19). Despite social and economic concerns, this epidemiologic emergency has brought unexpected positive consequences for environmental quality as human activities were reduced. In this paper, the impact of restricted human activities on urban air quality in Ecuador is investigated. This country implemented a particularly strict set of quarantine measures at the very dawn of the exponential growth of infections on March 17, 2020. As a result, significant reductions in the concentrations of NO 2 (-68%), SO 2 (-48%), CO (-38%) and PM 2.5 (-29%) were measured in the capital city of Quito during the first month of quarantine. This large drop in air pollution concentrations occurred at all the monitoring sites in Quito, serving as a valuable proof of the anthropogenic impact on urban air quality. The spatial evolution of atmospheric pollution using observed surface and satellite data, showed different results for the two major cities: Quito and Guayaquil. While the population in Quito adhered to the quarantine measures immediately, in the port city of Guayaquil, quarantine measures were slow to be adopted and, thus, the effect on air quality in Guayaquil occurred more slowly. This lag could have a considerable cost to the mortality rate in the port city, not only due to the spread of the disease but also due to the poor air quality. Overall, the air quality data demonstrate how quickly air quality can improve when emissions are reduced.

Sustainability

In the light of the 21st century, after two devastating world wars, humanity still has not learne... more In the light of the 21st century, after two devastating world wars, humanity still has not learned to solve their conflicts through peaceful negotiations and dialogue. Armed conflicts, both international and within a single state, still cause devastation, displacement, and death all over the world. Not to mention the consequences that war has on the environment. Due to a lack of published research about war impact on modern air quality, this work studies air pollution evolution during the first months of the Russian-Ukrainian conflict. Satellite images of NO2, CO, O3, SO2, and PM2.5 over Ukrainian territory and PM2.5 land monitoring data for Kyiv were analyzed. The results showed that NO2 and PM2.5 correlated the most with war activities. CO and O3 levels increased, while SO2 concentrations reduced four-fold as war intensified. Drastic increases in pollution (especially PM2.5) from bombing and structural fires, raise additional health concerns, which might have serious implications ...

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC5 Moses Lake on-farm site.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC4 Moscow Mountain on-farm... more This is the AmeriFlux version of the carbon flux data for the site US-RC4 Moscow Mountain on-farm site.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC2 Cook Agronomy Farm - Co... more This is the AmeriFlux version of the carbon flux data for the site US-RC2 Cook Agronomy Farm - Conventional Till.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2019

This is the AmeriFlux version of the carbon flux data for the site US-RC1 Cook Agronomy Farm - No... more This is the AmeriFlux version of the carbon flux data for the site US-RC1 Cook Agronomy Farm - No Till.

Air-quality modeling is an important tool for evaluating strategies for complying with the NAAQS.... more Air-quality modeling is an important tool for evaluating strategies for complying with the NAAQS. Two perennial issues of interest are the effects of long-range transport (LRT) and of stratospheric ozone intrusion (SOI) on air quality. Under the EPA Exceptional Events Policy, for example, a nominal exceedance can be excluded from design value calculation if it can be credibly ascribed to long-range transport or stratospheric ozone intrusion. Air-quality modeling is potentially an appropriate tool for attempting demonstration of LRT and SOI in making a case for Exceptional Event status for an exceedance. Also, ample evidence exists that local air pollution should sometimes be viewed in the context of a baseline pollution levels, and that these baseline levels are influenced by LRT and SOI (Wigder et al., 2013).

The effects of global changes upon regional ozone pollution in the United States J. Chen, J. Avis... more The effects of global changes upon regional ozone pollution in the United States J. Chen, J. Avise, B. Lamb, E. Salathé, C. Mass, A. Guenther, C. Wiedinmyer, J.-F. Lamarque, S. O’Neill, D. McKenzie, and N. Larkin Washington State University, Pullman, WA, USA University of Washington, Seattle, WA, USA National Center for Atmospheric Research, Boulder, CO, USA United States Department of Agriculture, Natural Resources Conservation Service, Portland, OR, USA United States Department of Agriculture, Forest Service, Seattle, WA, USA now at: National Research Council Canada, Ottawa, ON, Canada now at: California Air Resources Board, Sacramento, CA, USA

Chemical transport models (CTM) are widely used for air quality modeling, but these models miss f... more Chemical transport models (CTM) are widely used for air quality modeling, but these models miss forecasting some air pollution events, and require a lot of computational power. In Kennewick, WA, elevated O3 episodes can occur during the summer and early fall, but the CTM-based operational forecasting system (AIRPACT) struggles to capture them. This research used the 2015 – 2018 historical archives from the Weather Research and Forecasting (WRF) meteorological model forecasts produced daily by the University of Washington, and O3 observation data at Kennewick to train two machine learning modeling frameworks, ML1 and ML2 for a reliable forecasting system. ML1 used the random forest (RF) classifier and multiple linear regression (MLR) models, and ML2 used a two-phase RF regression model with best-fit weighting factors. Since April 2019, the ML modeling frameworks have been used to produce daily 72-hour O3 forecasts and have provided the forecasts via the web for the agency and public ...

Journal of Sensor and Actuator Networks, 2017

In the coming decades, as we experience global population growth and global aging issues, there w... more In the coming decades, as we experience global population growth and global aging issues, there will be corresponding concerns about the quality of the air we experience inside and outside buildings. Because we can anticipate that there will be behavioral changes that accompany population growth and aging, we examine the relationship between home occupant behavior and indoor air quality. To do this, we collect both sensor-based behavior data and chemical indoor air quality measurements in smart home environments. We introduce a novel machine learning-based approach to quantify the correlation between smart home features and chemical measurements of air quality, and evaluate the approach using two smart homes. The findings may help us understand the types of behavior that measurably impact indoor air quality. This information could help us plan for the future by developing an automated building system that would be used as part of a smart city.

Atmospheric Chemistry and Physics Discussions, 2014

A number of numerical wind flow models have been developed for simulating wind flow at relatively... more A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ∼100 m); however, there are very limited observational data available for evaluating these high resolution models. This study presents high-resolution surface wind datasets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically-driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds collected on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. Wind speed did not have a simple, consistent trend with position on the slope during the downslope regime on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest me...

Tellus B, 2007

These measurements were used to calculate total ozone flux and partitioning between stomatal and ... more These measurements were used to calculate total ozone flux and partitioning between stomatal and non-stomatal sinks. Total ozone flux varied diurnally with maximum values reaching 100 µmol m −2 h −1 at midday and minimums at or near zero at night. Mean daytime canopy conductance was 0.5 mol m −2 s −1. During daytime, non-stomatal ozone conductance accounted for as much as 66% of canopy conductance, with the non-stomatal sink representing 63% of the ozone flux. Stomatal conductance showed expected patterns of behaviour with respect to photosynthetic photon flux density (PPFD) and vapour pressure defecit (VPD). Non-stomatal conductance for ozone increased monotonically with increasing PPFD, increased with temperature (T) before falling off again at high T, and behaved similarly for VPD. Daytime non-stomatal ozone sinks are large and vary with time and environmental drivers, particularly PPFD and T. This information is crucial to deriving mechanistic models that can simulate ozone uptake by different vegetation types.

Journal of the Air & Waste Management Association, 2012

The impact of climate change on surface-level ozone is examined through a multiscale modeling eff... more The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF E), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects of future anthropogenic emissions, biogenic emissions, and climate on the RRF E. For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF C or CAF CB when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF EC was calculated (RRF EC ¼ RRF E Â CAF C). In general, RRF EC > RRF E , which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF E than does future climate change itself. The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO X ¼ NO þ NO 2). Regions that are generally NO X limited show a decrease in ozone and RRF EC , while VOC-limited regions show an increase in ozone and RRF EC. Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF CB. Implications: We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO X emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO X emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Journal of Geophysical Research, 2006

Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is... more Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is subject to errors involving the column retrieval and the assumed relationship between HCHO columns and isoprene emissions, taken here from the GEOS-CHEM chemical transport model. Here we use a 6-year (1996-2001) HCHO column data set from the Global Ozone Monitoring Experiment (GOME) satellite instrument to (1) quantify these errors, (2) evaluate GOME-derived isoprene emissions with in situ flux measurements and a process-based emission inventory (Model of Emissions of Gases and Aerosols from Nature, MEGAN), and (3) investigate the factors driving the seasonal and interannual variability of North American isoprene emissions. The error in the GOME HCHO column retrieval is estimated to be 40%. We use the Master Chemical Mechanism (MCM) to quantify the time-dependent HCHO production from isoprene, aand b-pinenes, and methylbutenol and show that only emissions of isoprene are detectable by GOME. The time-dependent HCHO yield from isoprene oxidation calculated by MCM is 20-30% larger than in GEOS-CHEM. GOME-derived isoprene fluxes track the observed seasonal variation of in situ measurements at a Michigan forest site with a À30% bias. The seasonal variation of North American isoprene emissions during 2001 inferred from GOME is similar to MEGAN, with GOME emissions typically 25% higher (lower) at the beginning (end) of the growing season. GOME and MEGAN both show a maximum over the southeastern United States, but they differ in the precise location. The observed interannual variability of this maximum is 20-30%, depending on month. The MEGAN isoprene emission dependence on surface air temperature explains 75% of the month-to-month variability in GOME-derived isoprene emissions over the

International Journal of Mass Spectrometry, 2006

A proton transfer reaction mass spectrometer (PTR-MS) was redesigned and deployed to monitor sele... more A proton transfer reaction mass spectrometer (PTR-MS) was redesigned and deployed to monitor selected hydrocarbon emissions from in-use vehicles as part of the Mexico City Metropolitan Area (MCMA) 2003 field campaign. This modified PTR-MS instrument provides the necessary time response (<2 s total cycle time) and sensitivity to monitor the rapidly changing hydrocarbon concentrations, within intercepted dilute exhaust emission plumes. Selected hydrocarbons including methanol, acetaldehyde, acetone, methyl tertiary butyl ether (MTBE), benzene and toluene were among the vehicle exhaust emission components monitored. A comparison with samples collected in canisters and analyzed by gas chromatography provides validation to the interpretation of the ion assignments and the concentrations derived using the PTR-MS. The simultaneous detection of multiple hydrocarbons in dilute vehicle exhaust plumes provides a valuable tool to study the impact of driving behavior on the exhaust gas emissions.

Ecosystems, 2004

This report summarizes our current knowledge of leaf-level physiological processes that regulate ... more This report summarizes our current knowledge of leaf-level physiological processes that regulate carbon gain and water loss of the dominant tree species in an old-growth forest at the Wind River Canopy Crane Research Facility. Analysis includes measurements of photosynthesis, respiration, stomatal conductance, water potential, stable carbon isotope values, and biogenic hydrocarbon emissions from Douglas-fir 1 (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla), and western red cedar (Thuja plicata). Leaf-level information is used to scale fluxes up to the canopy to estimate gross primary production using a physiologybased process model. Both light-saturated and in situ photosynthesis exhibit pronounced vertical gradients through the canopy, but are consistently highest in Douglas-fir, intermediate in western hemlock, and lowest in western red cedar. Net photosynthesis and stomatal conductance are strongly dependent on vapor-pressure deficit in Douglas-fir, and decline through the course of a seasonal drought. Foliar respiration is similar for Douglas-fir and western hemlock, and lowest for western red cedar. Water-use efficiency varied with species and tree height, as indexed using stable carbon isotopes values for foliage. Leaf water potential is most negative for Douglas-fir and similar for western hemlock and western red cedar. Terpene fluxes from foliage equal approximately 1% of the net carbon loss from the forest. Modeled estimates based on physiological measurements show gross primary productivity (GPP) to be about 22 Mg C m)2 y)1. Physiological studies will be necessary to further refine estimates of stand-level carbon balance and to make long-term predictions of changes in carbon balance due to changes in forest structure, species composition, and climate.

Atmospheric Environment, 2009

A regional modeling system was applied with inputs from global climate and chemistry models to qu... more 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 þ8 ppbv and þ10 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 À5 ppbv to þ5 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.