scholarly journals An analysis of long-term regional-scale ozone simulations over the Northeastern United States: variability and trends

2010 ◽  
Vol 10 (10) ◽  
pp. 23045-23090 ◽  
Author(s):  
C. Hogrefe ◽  
W. Hao ◽  
E. E. Zalewsky ◽  
J.-Y. Ku ◽  
B. Lynn ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Interannual Variability ◽  
Ground Level ◽  
Lateral Boundary ◽  
Ground Level Ozone ◽  
Lateral Boundary Conditions ◽  
Ozone Precursor ◽  
Time Invariant

Abstract. This study presents the results from two sets of 18-year air quality simulations over the Northeastern US performed with a regional photochemical modeling system. These two simulations utilize different sets of lateral boundary conditions, one corresponding to a time-invariant climatological vertical profile and the other derived from monthly mean concentrations extracted from archived ECHAM5-MOZART global simulations. The objective is to provide illustrative examples of how model performance in several key aspects – trends, intra- and interannual variability of ground-level ozone, and ozone/precursor relationships – can be evaluated against available observations, and to identify key inputs and processes that need to be considered when performing and improving such long-term simulations. To this end, several methods for comparing observed and simulated trends and variability of ground level ozone concentrations, ozone precursors and ozone/precursor relationships are introduced. The application of these methods to the simulation using time-invariant boundary conditions reveals that the observed downward trend in the upper percentiles of summertime ozone concentrations is captured by the model in both directionality and magnitude. However, for lower percentiles there is a marked disagreement between observed and simulated trends. In terms of variability, the simulations using the time-invariant boundary conditions simulations underestimate observed inter-annual variability by 30–50% depending on the percentiles of the distribution. In contrast, the use of boundary conditions from the ECHAM5-MOZART simulations improves the representation of interannual variability. However, biases in the global simulations have the potential to significantly affect ozone simulations throughout the modeling domain, both at the surface and aloft. The comparison of both simulations highlights the significant impact lateral boundary conditions can have on a regional air quality model's ability to simulate long-term ozone variability and trends, especially for the lower percentiles of the ozone distribution.

scholarly journals An analysis of long-term regional-scale ozone simulations over the Northeastern United States: variability and trends

2011 ◽  
Vol 11 (2) ◽  
pp. 567-582 ◽  
Author(s):  
C. Hogrefe ◽  
W. Hao ◽  
E. E. Zalewsky ◽  
J.-Y. Ku ◽  
B. Lynn ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Interannual Variability ◽  
Ground Level ◽  
Lateral Boundary ◽  
Ground Level Ozone ◽  
Lateral Boundary Conditions ◽  
Ozone Precursor ◽  
Time Invariant

Abstract. This study presents the results from two sets of 18-year air quality simulations over the Northeastern US performed with a regional photochemical modeling system. These two simulations utilize different sets of lateral boundary conditions, one corresponding to a time-invariant climatological vertical profile and the other derived from monthly mean concentrations extracted from archived ECHAM5-MOZART global simulations. The objective is to provide illustrative examples of how model performance in several key aspects – trends, intra- and interannual variability of ground-level ozone, and ozone/precursor relationships – can be evaluated against available observations, and to identify key inputs and processes that need to be considered when performing and improving such long-term simulations. To this end, several methods for comparing observed and simulated trends and variability of ground level ozone concentrations, ozone precursors and ozone/precursor relationships are introduced. The application of these methods to the simulation using time-invariant boundary conditions reveals that the observed downward trend in the upper percentiles of summertime ozone concentrations is captured by the model in both directionality and magnitude. However, for lower percentiles there is a marked disagreement between observed and simulated trends. In terms of variability, the simulations using the time-invariant boundary conditions underestimate observed inter-annual variability by 30%–50% depending on the percentiles of the distribution. The use of boundary conditions from the ECHAM5-MOZART simulations improves the representation of interannual variability but has an adverse impact on the simulated ozone trends. Moreover, biases in the global simulations have the potential to significantly affect ozone simulations throughout the modeling domain, both at the surface and aloft. The comparison of both simulations highlights the significant impact lateral boundary conditions can have on a regional air quality model's ability to simulate long-term ozone variability and trends, especially for the lower percentiles of the ozone distribution.

scholarly journals AIR QUALITY MONITORING AND DATA MANAGEMENT IN GERMANY – STATUS QUO AND SUGGESTIONS FOR IMPROVEMENT

2020 ◽  
Vol XLIV-4/W2-2020 ◽  
pp. 37-43
Author(s):  
L. Petry ◽  
H. Herold ◽  
G. Meinel ◽  
T. Meiers ◽  
I. Müller ◽  
...  
Keyword(s):  
Decision Making ◽  
Air Quality ◽  
Management Practices ◽  
System Development ◽  
Ground Level ◽  
Ground Level Ozone ◽  
Novel Approach ◽  
Depth Analysis ◽  
New Generation

Abstract. This paper proposes a novel approach to facilitate air quality aware decision making and to support planning actors to take effective measures for improving the air quality in cities and regions. Despite many improvements over the past decades, air pollutants such as particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3) pose still one of the major risks to human health and the environment. Based on both a general analysis of the air quality situation and regulations in the EU and Germany as well as an in-depth analysis of local management practices requirements for better decision making are identified. The requirements are used to outline a system architecture following a co-design approach, i.e., besides scientific and industry partners, local experts and administrative actors are actively involved in the system development. Additionally, the outlined system incorporates two novel methodological strands: (1) it employs a deep neural network (DNN) based data analytics approach and (2) makes use of a new generation of satellite data, namely Sentinel-5 Precursor (Sentinel-5P). Hence, the system allows for providing areal and high-resolution (e.g., street-level) real-time and forecast (up to 48 hours) data to inform decision makers for taking appropriate short-term measures, and secondly, to simulate air quality under different planning options and long-term actions such as modified traffic flows and various urban layouts.

scholarly journals Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

2013 ◽  
Vol 13 (5) ◽  
pp. 13967-14035 ◽  
Author(s):  
A. Robichaud ◽  
R. Ménard
Keyword(s):  
Air Quality ◽  
North America ◽  
Warm Season ◽  
Ground Level ◽  
Objective Analysis ◽  
Error Statistics ◽  
Ground Level Ozone ◽  
Air Quality Forecast ◽  
Background Check

Abstract. We present multi-year objective analyses (OA) on a high spatio-temporal resolution (15 or 21 km, every hour) for the warm season period (1 May–31 October) for ground-level ozone (2002–2012) and for fine particulate matter (diameter less than 2.5 microns (PM2.5)) (2004–2012). The OA used here combines the Canadian Air Quality forecast suite with US and Canadian surface air quality monitoring sites. The analysis is based on an optimal interpolation with capabilities for adaptive error statistics for ozone and PM2.5 and an explicit bias correction scheme for the PM2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth–Lönnberg's (H–L) method. Various quality controls (gross error check, sudden jump test and background check) have been applied to the observations to remove outliers. An additional quality control is applied to check the consistency of the error statistics estimation model at each observing station and for each hour. The error statistics are further tuned "on the fly" using a χ2 (chi-square) diagnostic, a procedure which verifies significantly better than without tuning. Successful cross-validation experiments were performed with an OA set-up using 90% of observations to build the objective analysis and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM2.5 satellite surface derived measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 μg m−3 (micrograms per cubic meter) for ozone and PM2.5 respectively and a random error generally less than 9 ppbv for ozone and under 12 μg m−3 for PM2.5. In this paper, we focus on two applications: (1) presenting long term averages of objective analysis and analysis increments as a form of summer climatology and (2) analyzing long term (decadal) trends and inter-annual fluctuations using OA outputs. Our results show that high percentiles of ozone and PM2.5 are both following a decreasing trend overall in North America with the eastern part of United States (US) presenting the highest decrease likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM2.5 such as the northwestern part of North America (northwest US and Alberta). The low percentiles are generally rising for ozone which may be linked to increasing emissions from emerging countries and the resulting pollution brought by the intercontinental transport. After removing the decadal trend, we demonstrate that the inter-annual fluctuations of the high percentiles are significantly correlated with temperature fluctuations for ozone and precipitation fluctuations for PM2.5. We also show that there was a moderately significant correlation between the inter-annual fluctuations of the high percentiles of ozone and PM2.5 with economic indices such as the Industrial Dow Jones and/or the US gross domestic product growth rate.

scholarly journals Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

2014 ◽  
Vol 14 (4) ◽  
pp. 1769-1800 ◽  
Author(s):  
A. Robichaud ◽  
R. Ménard
Keyword(s):  
Air Quality ◽  
North America ◽  
Warm Season ◽  
Ground Level ◽  
The United States ◽  
Error Statistics ◽  
Spatiotemporal Resolution ◽  
Ground Level Ozone ◽  
Air Quality Forecast

Abstract. Multi-year objective analyses (OA) on a high spatiotemporal resolution for the warm season period (1 May to 31 October) for ground-level ozone and for fine particulate matter (diameter less than 2.5 microns (PM2.5)) are presented. The OA used in this study combines model outputs from the Canadian air quality forecast suite with US and Canadian observations from various air quality surface monitoring networks. The analyses are based on an optimal interpolation (OI) with capabilities for adaptive error statistics for ozone and PM2.5 and an explicit bias correction scheme for the PM2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth–Lönnberg (H–L) method. The error statistics are "tuned" using a χ2 (chi-square) diagnostic, a semi-empirical procedure that provides significantly better verification than without tuning. Successful cross-validation experiments were performed with an OA setup using 90% of data observations to build the objective analyses and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM2.5 satellite surface-derived or ground-based measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 μg m−3 (micrograms per cubic meter) for ozone and PM2.5, respectively, and a random error generally less than 9 ppbv for ozone and under 12 μg m−3 for PM2.5. This paper focuses on two applications: (1) presenting long-term averages of OA and analysis increments as a form of summer climatology; and (2) analyzing long-term (decadal) trends and inter-annual fluctuations using OA outputs. The results show that high percentiles of ozone and PM2.5 were both following a general decreasing trend in North America, with the eastern part of the United States showing the most widespread decrease, likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM2.5, such as the northwestern part of North America (northwest US and Alberta). Conversely, the low percentiles are generally rising for ozone, which may be linked to the intercontinental transport of increased emissions from emerging countries. After removing the decadal trend, the inter-annual fluctuations of the high percentiles are largely explained by the temperature fluctuations for ozone and to a lesser extent by precipitation fluctuations for PM2.5. More interesting is the economic short-term change (as expressed by the variation of the US gross domestic product growth rate), which explains 37% of the total variance of inter-annual fluctuations of PM2.5 and 15% in the case of ozone.

scholarly journals Comparison of chemical lateral boundary conditions for air quality predictions over the contiguous United States during pollutant intrusion events

2021 ◽  
Vol 21 (4) ◽  
pp. 2527-2550
Author(s):  
Youhua Tang ◽  
Huisheng Bian ◽  
Zhining Tao ◽  
Luke D. Oman ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Model Performance ◽  
Chemical Species ◽  
Saharan Dust ◽  
Atmospheric Composition ◽  
Lateral Boundary ◽  
Model Framework ◽  
Air Quality Forecast ◽  
Lateral Boundary Conditions

Abstract. The National Air Quality Forecast Capability (NAQFC) operated in the US National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) over the contiguous 48 US states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions (CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to CMAQ's CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015. The simulated PM2.5 was improved from 0.18 to 0.37, and the mean bias was reduced from −6.74 to −2.96 µg m−3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the CLBCs of global models, such as GEOS CLBCs, are not available.

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