Edith Gégo

Observation-Based Assessment of the Impact of Nitrogen Oxides Emissions Reductions on Ozone Air Quality over the Eastern United States

Abstract Ozone is produced by chemical interactions involving nitrogen oxides (NOx) and volatile organic compounds in the presence of sunlight. At high concentrations, ground-level ozone has been shown to be harmful to human health and to the environment. It has been recognized that ozone is a regional-scale problem and that regionwide control strategies would be needed to improve ozone air quality in the eastern United States. To mitigate interstate transport of ozone and its precursors, the U.S. Environmental Protection Agency issued a regional rule in 1998 known as the “NOx State Implementation Plan (SIP) Call,” requiring 21 states in the eastern United States to reduce their summertime NOx emissions by 30 May 2004. In this paper, the effectiveness of the new emission control measures mandated by the NOx SIP Call is assessed by quantifying the changes that occurred in the daily maximum 8-h ozone concentrations measured at nearly 50 locations, most of which are rural (33 sites of the Clean Air Status an...

Has the Performance of Regional-Scale Photochemical Modelling Systems Changed over the Past Decade?

This study analyzes summertime ozone concentrations that have been simulated by various regional-scale photochemical modelling systems over the Eastern U.S. as part of more than ten independent studies. Results indicate that there has been a reduction of root mean square errors (RMSE) and an improvement in the ability to capture ozone fluctuations stemming from synoptic-scale meteorological forcings between the earliest seasonal modelling simulations and more recent studies. However, even the more recent model simulations exhibit RMSE values of about 15 ppb and there is no evidence that differences in RMSE between these recent simulations are attributable to systematic improvements in modelling capability. Moreover, it was determined that certain aspects of model performance have not changed over the past decade. One such aspect is that the RMSE of simulated time series can be reduced by applying temporal averaging kernels of up to seven days while the benefit of longer averaging windows appears to vary from year to year. In addition, it is found that spatial patterns simulated by these modelling systems typically have lower correlations and higher centered RMSE than temporal patterns. Analogous to the errors in the simulated time series, these errors in the spatial patterns can be reduced through the application of spatial averaging kernels.

Characterizing the Exposure of Regional-Scale Air Quality in the Northeastern United States

The Clean Air Act (CAA) requires that the United States (U.S.) Environmental Protection Agency (EPA) set National Ambient Air Quality Standards (NAAQS) for pollutants considered harmful to human health and the environment. Previous research has shown that high ambient ozone levels are harmful to human health (e.g., Bell ML, Dominici F, Samet JM, Epidemiology, 16(4):436–445, 2005; Ito K, De Leon SF, Lippmann M, Epidemiology, 16(4):446–457, 2005, [4]). While ozone is not directly emitted, the formation of ozone is driven by chemical interactions in the presence of sunlight involving nitrogen oxides (NOx) and volatile organic compounds. Prevailing weather conditions in the Northeastern U.S. transport the relatively long-lived NOx (NO and NO2) and the secondarily-formed ozone downwind, contributing to pollutant levels at locations much farther from the emission source regions. In this study, we investigate associations between polluted air parcels transported from the Ohio River Valley (ORV) in the Midwestern U.S. and respiratory-related hospital admissions in New York State (NYS). We also examine whether better characterization of exposure in an epidemiology model would improve the discernment of this health signal.

Chapter 2.10 Modeling assessment of the impact of nitrogen oxides emission reductions on ozone air quality in the Eastern United States: Offsetting increases in energy use

Abstract A photochemical air quality model was used to evaluate the impact of a series of NOx control rules on ozone air quality in the eastern U.S. Thanks to the acid rain program and the NOx SIP Call, emission rates of NOx (mass NOx/energy content of fuel used) from industrial point sources have declined dramatically since 1997. Model simulations were performed with three emission scenarios: 2002 emissions, 2004 emissions, and a ‘no control’ scenario. The latter simulates conditions that would have existed in 2002 had new NOx emission controls not been imposed. All scenarios used 2002 meteorology. Controls lead to reductions of NOx emissions in 2002 and 2004 to roughly two thirds and one third of their 1997 levels, respectively. In response to these emission changes, the model predicted that maximun 8-h average ozone concentrations would have decreased from 3% to 8% between 2002 and 2004 given 2002 meteorolgy. The absence of control would have led to considerably higher ozone levels in most of the eastern U.S., with exceptions occurring in the vicinity of point sources, regions that would have experienced lower ozone levels thanks to a more intense titration process.

Comparison of the Space-Time Signatures of Air Quality Data From Different Monitoring Networks

Ambient air quality in the United States is measured by several regional air quality monitoring networks. Yet, differences in sampling protocol between the networks may not allow joint use of the data reported by different networks. In this study, we compare the space-time signatures of sulfate and nitrate fine particle mass concentrations reported by the Clean Air Status and Trend Network (CASTNet) and the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE). First, a spectral decomposition technique was used to separate the low and high frequency variations in time series of pollutant concentrations at collocated IMPROVE and CASTNet sites. Through Principal Component Analysis (PCA) and Varimax orthogonal rotation, we determined the number of significant sulfate and nitrate modes of variation identifiable with both networks, and identify the mode of variation characterizing each monitoring site. In the case of sulfate, both networks allow identification of seven distinct modes of variation, each of which corresponds to a well-defined geographic area. PCA also suggests the existence of seven modes of variation for nitrate but, in contrast to sulfate, these modes of variations could not be linked to any unified geographic area. A combination of spectral decomposition and PCA reveals that the long-term fluctuations in sulfate at both networks are virtually identical — when they are averaged in homogeneous regions defined by PCA — between both networks.

Metamodels for Ozone: Comparison of Three Estimation Techniques

A metamodel for ozone is a mathematical relationship between the inputs and outputs of an air quality modeling experiment, permitting calculation of outputs for scenarios of interest without having to run the model again. In this study we compare three metamodel estimation techniques applied to an 18 year long CMAQ simulation covering the Northeastern US (NEUS). The estimation methods considered here include projection onto latent structures, stochastic kriging and a combination of principal components and stochastic kriging.

Integrating PM25 Observations, Model Estimates and Satellite Signals for the Eastern United States by Projection onto Latent Structures

Detailed, time-varying spatial fields of air contaminant concentrations are valuable to public health professionals seeking to identify relationships between human health and ambient air quality, and policy makers interested in assessing compliance with air quality regulations. In this paper PM25 fields are created from a linear model that predicts PM25 at unmonitored grid points from observed PM25 concentrations, CMAQ model outputs, and satellite estimates of aerosol optical density. The dimensionality of the input data set is first reduced using projection onto latent structures. Parameters of the linear model are mapped to the CMAQ model domain, permitting estimation of PM25 at unmonitored sites.

Fusing Observations and Model Results for Creation of Enhanced Ozone Spatial Fields: Comparison of Three Techniques

This paper presents three simple techniques for fusing observations and numerical model predictions. The techniques rely on model/observation bias being considered either as error free, or containing some uncertainty, the latter mitigated with a Kalman filter approach or a spatial smoothing method. The fusion techniques are applied to the daily maximum 8-hour average ozone concentrations observed in the New York state area during summer 2001. Classical evaluation metrics (mean absolute bias, mean squared error, correlation, etc.) show that fused predictions are not better than a simple interpolation of observations. However, fused maps better reproduce the spatial texture of the model predictions.

Temporal Signatures of Observations and Model Outputs: Do Time Series Decomposition Methods Capture Relevant Time Scales?

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereby helping to untangle complex processes. Mode-to-mode comparison of observed and modeled data provides a mechanism for model evaluation. The decomposition methods included empirical orthogonal functions (EOF), empirical mode decomposition (EMD), and wavelet filters (WF). EOF, a linear method designed for stationary time series, is principal component analysis (PCA) applied to time-lagged copies of a given time series. EMD is a relatively new nonlinear method that operates locally in time and is suitable for nonstationary and nonlinear processes; it is not, in theory, band-width limited, and the number of modes is automatically determined. Wavelet filters are band-width guided with the number of modes set by the analyst. The purpose of this paper is to compare the performance of decomposition techniques in characterizing time scales in meteorological and air quality variables. The time series for this study, modeled and observed temperature and PM2.5, were chosen because they represent relatively easy and difficult tests,

Poster 19 Relationships between nitrogen oxide emissions from electrical generating units in the U.S. and meteorology

Abstract The correlation between nitrogen oxide (NO X ) emissions and heat input (HI) from electrical generating units as well as meteorology was investigated. HI is the energy content of fuel used to generate electricity. Here, we examine time scales common to both HI and meteorology with the goal of improving the performance of air quality modeling and forecasting.