Kenneth L. Schere

Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System

This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-ofthe-science capabilities for modeling multiple air quality issues, including tropospheric ozone, fine particles, acid deposition, and visibility degradation. CMAQ was also designed to have multiscale capabilities so that separate models were not needed for urban and regional scale air quality modeling. By making CMAQ a modeling system that addresses multiple pollutants and different spatial scales, it has a “one-atmosphere” perspective that combines the efforts of the scientific community. To implement multiscale capabilities in CMAQ, several issues (such as scalable atmospheric dynamics and generalized coordinates), which depend on the desired model resolution, are addressed. A set of governing equations for compressible nonhydrostatic atmospheres is available to better resolve atmospheric dynamics at smaller scales. Because CMAQ is designed to handle scale-dependent meteorological formulations and a large amount of flexibility, its governing equations are expressed in a generalized coordinate system. This approach ensures consistency between CMAQ and the meteorological modeling system. The generalized coordinate system determines the necessary grid and coordinate transformations, and it can accommodate various vertical coordinates and map projections. The CMAQ modeling system simulates various chemical and physical processes that are thought to be important for understanding atmospheric trace gas transformations and distributions. The modeling system contains three types of modeling components (Models-3): a meteorological modeling system for the description of atmospheric states and motions, emission models for man-made and natural emissions that are injected into the atmosphere, and a chemistry-transport modeling system for simulation of the chemical transformation and fate. The chemical transport model includes the following process modules: horizontal advection, vertical advection, mass conservation adjustments for advection processes, horizontal diffusion, vertical diffusion, gas-phase chemical reactions and solvers, photolytic rate computation, aqueous-phase reactions and cloud mixing, aerosol dynamics, size distributions and chemistry, plume chemistry effects, and gas and aerosol deposition velocity estimation. This paper describes the Models-3 CMAQ system, its governing equations, important science algorithms, and a few application examples. This review article cites 114 references. DOI: 10.1115/1.2128636

Linking the Eta Model with the Community Multiscale Air Quality (CMAQ) Modeling System to Build a National Air Quality Forecasting System

Abstract NOAA and the U.S. Environmental Protection Agency (EPA) have developed a national air quality forecasting (AQF) system that is based on numerical models for meteorology, emissions, and chemistry. The AQF system generates gridded model forecasts of ground-level ozone (O3) that can help air quality forecasters to predict and alert the public of the onset, severity, and duration of poor air quality conditions. Although AQF efforts have existed in metropolitan centers for many years, this AQF system provides a national numerical guidance product and the first-ever air quality forecasts for many (predominantly rural) areas of the United States. The AQF system is currently based on NCEP’s Eta Model and the EPA’s Community Multiscale Air Quality (CMAQ) modeling system. The AQF system, which was implemented into operations at the National Weather Service in September of 2004, currently generates twice-daily forecasts of O3 for the northeastern United States at 12-km horizontal grid spacing. Preoperationa...

The sensitivity of regional ozone modeling to biogenic hydrocarbons

The sensitivity of regional ozone concentrations to biogenic hydrocarbons in the northeastern United States has been examined using an Eulerian grid photochemical model having a horizontal resolution of 18 km. A 6-day period during which observed ozone concentrations exceeded 200 ppb was simulated. Detailed estimates of biogenic nonmethane hydrocarbon (NMHC) emissions were included in the model simulations. Overall, biogenic emissions were of the same order of magnitude as anthropogenic emissions. Approximately 33% of the biogenic inventory was in the form of isoprene, with the remainder of the NMHC in the form of monoterpenes and unidentified NMHC. Three model sensitivity runs were analyzed in which biogenic emissions, and then anthropogenic hydrocarbon emissions, were selectively removed from the emissions data set. Episode maximum predicted ozone concentrations were compared for each simulation, and a detailed chemical analysis was performed on two trajectories within the modeling domain. The analysis showed that the relative impact of biogenic compared to anthropogenic hydrocarbons on ozone generation varied spatially over the model domain. The biogenic influence on ozone was greatest in western and southern sections of the domain, particularly in the Ohio Valley, while the anthropogenic influence was greatest in the urbanized Northeast Corridor and industrial Great Lakes area.

Modeled response of photochemical oxidants to systematic reductions in anthropogenic volatile organic compound and NO x emissions

As an exercise in model sensitivity, the Environmental Protection Agencys regional oxidant model (ROM) was run for several simulations to study the impact of across-the-board reductions in anthropogenic volatile organic compound (VOC) and NOx emissions on the photochemical environment of the eastern United States. The ROM, which simulates most of the physical and chemical processes responsible for the formation of O3 on regional scales, was used to simulate a widespread high O3 episode in the eastern United States. Separate simulations were performed over the period July 2–10, 1988, for each of the sensitivity runs. An operational evaluation and several model diagnostics were performed on the base case simulation. The sensitivity runs reduced anthropogenic NOx and VOC emissions separately and in combination in increments of 25% of full scale emissions. Biogenic emissions were held constant across all sensitivity tests. Seventeen of the potential 25 nodes of the NOx, VOC emissions reduction matrix were simulated. In the analysis the modeled domain (the eastern half of the United States) is subdivided into several chemically coherent regions. Several chemical species, including afternoon average concentrations of O3, PAN, HNO3, OH, and HO2 + RO2, are examined to gain an understanding of how the reduction in emissions affected the overall chemical system for each sensitivity test. Results are presented as a series of statistical and graphical displays illustrating the response of the system within the selected subdomains to the emission reductions.

A study of the relationship between photochemical ozone and its precursor emissions of nitrogen oxides and hydrocarbons in Tokyo and surrounding areas

Abstract The relationship between emission intensity of (nitrogen oxides) (NO x ), NC non-methane hydrocarbons (NMHC) and O 3 concentration covering the Kanto area (Tokyo and surrounding prefectures) were investigated based on data analysis and model simulation. The observed trend in NO x concentration increased and the NMHC/NO x ratio and NMHC concentration decreased from 1978 to 1990. These emission changes will act to change the place where the maximum ozone is observed in the Kanto area. The fact is that the location of the daily maximum oxidant concentration has moved further from the emission areas. To clarify the temporal and areal distribution of photochemical air pollution in the Kanto area, the Urban Airshed Model (UAM) was applied. Assuming 25% decrease in NMHC and 50% increase in NO x emission intensities, simulation result showed almost the same maximum O 3 value compared with the base-case simulation for 1981. On the other hand, the time when the maximum value appeared changed from 1400JST to 1600JST. Higher concentrations of oxidants were usually observed near the shore in the morning, and moved inland following sea breeze penetration. Under these meteorological conditions, the time shift obtained by the UAM simulation corresponds to the observed areal shift of the daily maximum O 3 concentration.

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...

Performance and Diagnostic Evaluation of Ozone Predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study

Abstract A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within [H11006]20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites.The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64 –77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

Dependencies and sensitivity of tropospheric oxidants to precursor concentrations over the northeast United States: A model study

Atmospheric distribution of photochemical oxidants has been a subject of interest and concern not only because of their deleterious effects on human health and vegetation but also because of their crucial role in determining the chemical composition of the atmosphere. Several important issues related to the distribution and production of photochemical species are examined through an analysis of results obtained from applications of a comprehensive three-dimensional regional scale photochemical model over the Northeast United States. The Regional Oxidant Model (ROM) is used to simulate the response of various photochemical species to specific anthropogenic emission strategies involving NOx, and hydrocarbon reductions for an episodic period during July 1988. Domain and temporal averages of predicted concentrations are examined for various species. Their relative influence on oxidant chemistry over the modeled domain is investigated. Further, spatial distributions of O3 with respect to those of NOx, NOy, and hydrocarbons over the modeled domain are examined and the variations in O3 levels for different chemical regimes classified by characteristic NOx/reactive organic gases and NOx/NOy ratios are investigated. Temporal trends in domain-averaged concentrations indicate that the model replicates the expected diurnal trends in species concentrations. The relative benefits of reductions in NOx and hydrocarbon emissions on predicted O3 levels are also examined. In general, for this modeled domain, reductions in NOx emissions with or without reductions in hydrocarbon emissions have more impact on reducing predicted O3 levels compared to reductions only in hydrocarbon emissions.

An evaluation of several numerical advection schemes

Abstract Three categories of numerical advection techniques are tested: SHASTA, a flux-corrected onedimensional algorithm; FCT, a multi-dimensional flux-corrected technique; and the BIQUINTIC method, a polynomial approximation algorithm. The tests include the transport of a finite amount of material through a 25 × 25 cell grid driven by three different flow fields: one-dimensional linear flow, two-dimensional linear flow, and rotational flow. For each of these tests, two initial distributions of material are used: a rectangular blockshape and an ellipse-shape. In addition, a test with a non-divergent flow field with a homogeneous material field was performed to check for inherent divergence in a particular method. Results show that the FCT and BIQUINTIC methods maintain the integrity of an initial distribution of material better than SHASTA through a simulation. While SHASTA is the fastest of the methods tested computationally it also produces the greatest amount of spurious numerical diffusion. The FCT method has a tendency to flatten the top of a peaked distribution, and the BIQUINTIC method tends to produce a peak in a top-hat distribution during numerical transport. The BIQUINTIC scheme requires more computer time to execute than the other methods tested.

Use of a process analysis tool for diagnostic study on fine particulate matter predictions in the U.S.–Part II: Analyses and sensitivity simulations

Abstract Following the Part I paper that describes an application of the U.S. EPA Models–3/Community Multiscale Air Quality (CMAQ) modeling system to the 1999 Southern Oxidants Study episode, this paper presents results from process analysis (PA) using the PA tool embedded in CMAQ and subsequent sensitivity simulations to estimate the impacts of major model uncertainties identified through PA. Aerosol processes and emissions are the most important production processes for PM 2.5 and its secondary components, while horizontal and vertical transport and dry deposition contribute to their removal. Cloud processes can contribute the production of PM 2.5 and SO 4 2– and the removal of NO 3 – and NH 4 + . The model biases between observed and simulated concentrations of PM 2.5 and its secondary inorganic components are found to correlate with aerosol processes and dry deposition at all sites from all networks and sometimes with emissions and cloud processes at some sites. Guided with PA results, specific uncertainties examined include the dry deposition of PM 2.5 species and its precursors, the emissions of PM 2.5 precursors, the cloud processes of SO 4 2– , and the gas–phase oxidation of SO 2 . Adjusting the most influential processes/factors (i.e., emissions of NH 3 and SO 2 , dry deposition velocity of HNO 3 , and gas–phase oxidation of SO 2 by OH) is found to improve the model overall performance in terms of SO 4 2– , NO 3 – , and NH 4 + predictions.