Jia-Yeong Ku

Space and Time Scales in Ambient Ozone Data

Abstract This paper describes the characteristic space and time scales in time series of ambient ozone data. The authors discuss the need and a methodology for cleanly separating the various scales of motion embedded in ozone time series data, namely, short-term (weather related) variations, seasonal (solar induced) variations, and long-term (climate–policy related) trends, in order to provide a better understanding of the underlying physical processes that affect ambient ozone levels. Spatial and temporal information in ozone time series data, obscure prior to separation, is clearly displayed by simple laws afterward. In addition, process changes due to policy or climate changes may be very small and invisible unless they are separated from weather and seasonality. Successful analysis of the ozone problem, therefore, requires a careful separation of seasonal and synoptic components. The authors show that baseline ozone retains global information on the scale of more than 2 months in time and about 300 km...

Assessing Ozone-Related Health Impacts under a Changing Climate

Climate change may increase the frequency and intensity of ozone episodes in future summers in the United States. However, only recently have models become available that can assess the impact of climate change on O3 concentrations and health effects at regional and local scales that are relevant to adaptive planning. We developed and applied an integrated modeling framework to assess potential O3-related health impacts in future decades under a changing climate. The National Aeronautics and Space Administration–Goddard Institute for Space Studies global climate model at 4° × 5° resolution was linked to the Penn State/National Center for Atmospheric Research Mesoscale Model 5 and the Community Multiscale Air Quality atmospheric chemistry model at 36 km horizontal grid resolution to simulate hourly regional meteorology and O3 in five summers of the 2050s decade across the 31-county New York metropolitan region. We assessed changes in O3-related impacts on summer mortality resulting from climate change alone and with climate change superimposed on changes in O3 precursor emissions and population growth. Considering climate change alone, there was a median 4.5% increase in O3-related acute mortality across the 31 counties. Incorporating O3 precursor emission increases along with climate change yielded similar results. When population growth was factored into the projections, absolute impacts increased substantially. Counties with the highest percent increases in projected O3 mortality spread beyond the urban core into less densely populated suburban counties. This modeling framework provides a potentially useful new tool for assessing the health risks of climate change.

Effects of uncertainties in meteorological inputs on urban airshed model predictions and ozone control strategies

Abstract Although well-recognized within the photochemical modeling community, the effect of uncertainties in meteorological input on the urban airshed model (UAM) output has not been systematically evaluated. In this study, the UAM has been applied to investigate the sensitivity of ozone predictions to the choices in wind fields and mixing height profiles for the data-sparse New York metropolitan area. A set of three wind fields, in combination with spatially varying and spatially invariant mixing heights, is investigated for the July 1988 ozone episode. In general, model-predicted ozone levels were higher under the spatially varying mixing height (SVM) option than under the spatially invariant mixing height (SIM) option. SVM based UAM simulations provided better agreement between the predicted and measured ozone concentrations than SIM-based UAM simulations. However, from the regulatory standpoint, predicted ozone concentrations based on either of these mixing height options are within the range considered as acceptable. UAM simulations with emission reductions of 75% NOx and 25% VOCs (NOx-focused) reveal that the improvement in peak ozone levels under the SIM option is larger than that under the SVM option, whereas the emission reduction scenario of 25% NOx and 75% VOCs (VOC-focused) yields greater improvement in peak ozone under the SVM option than with the SIM option. Given the strong influence of mixing heights and wind fields on UAM model predictions in data-sparse areas, it is imperative that uncertainties in development of ozone abatement plans be quantified.

An Operational Evaluation of Two Regional-Scale Ozone Air Quality Modeling Systems over the Eastern United States

In this paper, the performance of two commonly used regional-scale Eulerian photochemical modeling systems, namely, RAMS/UAM-V and MM5/SAQM, from the regulatory or operational perspective, is examined. While the Urban Airshed Model with Variable Grid (UAM-V) is driven with the meteorological fields derived from the Regional Atmospheric Model System (RAMS), the San Joaquin Valley Air Quality Model (SAQM) used the meteorological fields derived from the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model Version 5 (MM5). The models performance in reproducing the observed ozone air quality over the eastern United States is evaluated for three typical high-ozone episodic events that occurred during 16–20 June, 12–16 July, and 30 July–2 August of 1995. The prevailing meteorological conditions associated with these three episodes are characterized by a slow eastward-moving high pressure system, westerly and southwesterly low-level jets, stable boundary layers, and the Appalach...

Numerical Investigation of Boundary-Layer Evolution and Nocturnal Low-Level Jets: Local versus Non-Local PBL Schemes

Numerical simulations of the evolution of the planetary boundary layer (PBL) and nocturnal low-level jets (LLJ) have been carried out using MM5 (version 3.3) with four-dimensional data assimilation (FDDA) for a high pollution episode in the northeastern United States during July 15–20, 1999. In this paper, we assess the impact of different parameterizations on the PBL evolution with two schemes: the Blackadar PBL, a hybrid local (stable regime) and non-local (convective regime) mixing scheme; and the Gayno–Seaman PBL, a turbulent kinetic energy (TKE)-based eddy diffusion scheme. No FDDA was applied within the PBL to evaluate the ability of the two schemes to reproduce the PBL structure and its temporal variation. The restriction of the application of FDDA to the atmosphere above the PBL or the lowest 8 model levels, whichever is higher, has significantly improved the predicted strength and timing of the LLJ during the night. A systematic analysis of the PBL evolution has been performed for the primary meteorological fields (temperature, specific humidity, horizontal winds) and for the derived parameters such as the PBL height, virtual potential temperature, relative humidity, and cloud cover fraction. There are substantial differences between the PBL structures and evolutions simulated by these two different schemes. The model results were compared with independent observations (that were not used in FDDA) measured by aircraft, RASS and wind profiler, lidar, and tethered balloon platforms during the summer of 1999 as part of the NorthEast Oxidant and Particle Study (NE-OPS). The observations tend to support the non-local mixing mechanism better than the layer-to-layer eddy diffusion in the convective PBL.

Spatial and Temporal Variation in the Mixing Depth over the Northeastern United States during the Summer of 1995

Abstract A study of the temporal and spatial variations of mixing layer height over the Ozone Transport Region of the northeastern United States for the summer of 1995 is presented using meteorological data obtained from the North American Research Strategy for Tropospheric Ozone-Northeast (NARSTO-NE) 1995 field program. Rawinsonde balloon soundings made every 4 h during 13 ozone episode days during NARSTO-NE provided the principal source of upper-air data, supplemented by virtual temperature profiles from five radio acoustic sounder system sites. Forty-four weather stations provided surface data. Daytime mixing depths were estimated using a profile-intersection technique. The height of the surface inversion was used as a measure of the depth of the turbulent boundary layer at night. For the 13 ozone episode days, the average maximum mixing depth ranged from less than 500 m offshore to greater than 2000 m inland, with most of the increase occurring within the first 100 km of the coastline. The coefficient...

Uncertainties in estimating the mixing depth-comparing three mixing-depth models with profiler measurements

Abstract Determining the temporal evolution of the mixing depth is a complex problem in air pollution modeling. In this paper, mixing depths derived from three algorithms, RAMMET-X, MIXEMUP, and CALMET, are compared with estimates derived from a 915-MHZ radar profiler and Radio Acoustic Sounding System (RASS) located at Schenectady, NY, for nine clear summer days. Besides wind and temperature soundings, the profiler system also provided estimates of the mixing depth based on refractive index structure parameter ( C n 2 ) measurements. For the nine test days studied, mixing depths ranged from 1.6 km in midafternoon to 150–250 m at night, based on C n 2 . Mixing depths obtained from CALMET and MIXEMUP were in good agreement with C n 2 estimates throughout the day, but especially in the afternoon when they agreed to within 100 m. In contrast, estimates from RAMMET-X displayed considerably less diurnal variation, with afternoon mixing depths 300–400 m lower than profiler estimates, and nighttime values similarly too high. A separate “analytical method” based on an analysis of the profiler systems wind and temperature profiles, is offered as an alternate way for estimating the mixing depth. Mixing depths derived from the analytical method agreed well with C n 2 estimates at the times of the maximum and minimum, but displayed a much faster growth rate during the morning and a slightly slower decay rate in the evening. It is well known that ozone concentrations predicted by photochemical models are very sensitive to the mixing depth. The impact of the uncertainties inherent in the estimation of the mixing-depth profile on the ozone concentrations is examined through Ozone Isopleth Research Model (OZIPR) simulations. The results reveal that the variability in the OZIPR-predicted ozone concentration due to the uncertainties in the specification of the evolution of the mixing height is comparable or greater than that of different chemical mechanisms in the OZIPR model.

Impact of Biogenic Emission Uncertainties on the Simulated Response of Ozone and Fine Particulate Matter to Anthropogenic Emission Reductions

ABSTRACT The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1–0.25 μg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1–2% of the value of the annual PM2.5 NAAQS of 15 μg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions. IMPLICATIONS The findings presented in this study demonstrate that uncertainties in biogenic emission estimates due to different emission models can have a significant effect on the model estimates of ozone and PM2.5 concentrations; specifically, the changes in these concentrations due to reductions in anthropogenic emissions considered in regulatory modeling scenarios. These results point to the need for further research aimed at improving biogenic emission estimates as well as better characterizing their dependency on environmental factors and the fate of these emissions once released into the atmosphere.

Daily Simulation of Ozone and Fine Particulates over New York State: Findings and Challenges

Abstract This study investigates the potential utility of the application of a photochemical modeling system in providing simultaneous forecasts of ozone (O3) and fine particulate matter (PM2.5) over New York State. To this end, daily simulations from the Community Multiscale Air Quality (CMAQ) model for three extended time periods during 2004 and 2005 have been performed, and predictions were compared with observations of ozone and total and speciated PM2.5. Model performance for 8-h daily maximum O3 was found to be similar to other forecasting systems and to be better than that for the 24-h-averaged total PM2.5. Both pollutants exhibited no seasonal differences in model performance. CMAQ simulations successfully captured the urban–rural and seasonal differences evident in observed total and speciated PM2.5 concentrations. However, total PM2.5 mass was strongly overestimated in the New York City metropolitan area, and further analysis of speciated observations and model predictions showed that most of th...

Numerical simulation of air pollution in urban areas: Model development

Abstract A three-dimensional, grid-based numerical air pollution model for the estimation of air pollutant concentrations in an urban area is developed. Based on the continuity equation, the modeling system incorporates the combined influences of advective transport, turbulent diffusion, chemical transformation, source emissions and surface removal of air contaminants. Recent developments in plume rise and plume penetration processes, objective wind field analysis procedures and numerical solution techniques incorporated into the model are described.