Special Issue "Air Pollution Modeling: Reviews of Science Process Algorithms"

Guest Editor
Dr. Daewon Byun
Air Quality Modeling Group, Air Resources Laboratory, National Oceanic & Atmospheric Administration, SSMC3, Rm 3316 (R/ARL), 1315 East West Highway, Silver Spring, MD 20910, USA
Website: http://www.geosc.uh.edu/people/faculty/daewon-byun/index.php
E-Mail: daewon.byun@noaa.gov

Guest Editor
Dr. William R. Stockwell
Department of Chemistry, Room 120, Howard University, 525 College Street, NW, Washington, DC 20059, USA
Website: http://www.coas.howard.edu/chem/wstockwell/
E-Mail: william.r.stockwell@gmail.com

Guest Editor
Dr. Mehmet Talat Odman
School of Civil and Environmental Engineering, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332, USA
Website: http://people.ce.gatech.edu/~odman/
E-Mail: odman@gatech.edu
Phone: +1 404-894-2783

Dear Colleagues,

Air quality simulation models are important tools for regulatory, policy, and environmental decision making and science studies. Pollutants in the atmosphere are subject to myriad transport processes and transformation pathways that control their composition and concentration levels. The residence times of pollutants in the atmosphere can extend to multiple days to months and the corresponding spatial scales are commensurately large, ranging from local to continental scales. On these temporal and spatial scales, emissions from chemical manufacturing and other industrial activities, power generation, transportation, and waste treatment activities, as well as the natural sources, contribute to a variety of air pollution issues including visibility, ozone, particulate matter (PM), acid rain, and nutrient and toxic deposition.

This special issue is devoted to papers which provide in-depth reviews of physical and chemical process algorithms represented in the modern air quality models. This issue in Atmosphere will serve as the compendium of the state-of-science information on how these different atmospheric processes are treated in air quality models. Studies with critical reviews of pros and cons of process algorithms concerning atmospheric transport, turbulent mixing, atmospheric deposition, cloud processes, homogeneous and heterogeneous transformation of atmospheric gaseous and PM species, as well as anthropogenic and natural emission representations are welcome.

Dr. Daewon Byun
A/Prof. William R. Stockwell
Mehmet Talat Odman
Guest Editors

Submission

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• atmospheric transport
• turbulent mixing
• atmospheric deposition
• cloud processes
• homogeneous and heterogeneous reactions
• particulate matter
• anthropogenic emissions
• natural emissions

Type of Paper: Article
Title: Atmospheric Response Modeling for Decision Support
Authors: Daniel S. Cohan and Sergey L. Napelenok
Affiliation: Department of Civil and Environmental Engineering, Rice University, MS-519, Houston, TX 77005, USA; E-Mail: cohan@rice.edu (D.S.C.)
Abstract: Air quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants like ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results.

Type of Paper: Article
Title: Cloud Processing of Gases and Aerosols in Air Quality Modeling
Authors: Wanmin Gong *, Craig Stroud and Leiming Zhang
Affiliation: Air Quality Research Division, Science and Technology Branch, Environment Canada, 4905 Dufferin Street, Toronto, Ontario, M3H 5T4, Canada; E-Mails: wanmin.gong@ec.gc.ca (W.G.); craig.stroud@ec.gc.ca (C.S.); leiming.zhang@ec.gc.ca (L.Z.)
Abstract: Clouds play an active role in the processing and cycling of chemicals in the atmosphere. In particular, it has been long recognized that a large portion of the atmospheric particulate sulfate, which contributes to a significant fraction of the total PM mass, is produced in cloud via aqueous-phase oxidation. Recently there is increasing evidence that reactions involving organic compounds in the aqueous phase may be an important pathway in the formation of secondary organic aerosols in the atmosphere. On the other hand, clouds also act as an effective sink for gases and aerosols. This paper discusses the algorithms employed in current air quality models representing cloud processing of gases and aerosols, particularly with respect to scavenging of gases and aerosols by hydrometeors, aqueous-phase chemistry, and wet removal of atmospheric tracers. The sensitivity and uncertainty in model representations of these processes are assessed, and new challenges are discussed.
Keywords: cloud processes; aqueous-phase chemistry; sulfate; secondary organic aerosol; cloud-aerosol interaction; wet deposition

Type of Paper: Article
Title: Adaptive Grid Use in Air Quality Modeling
Authors: Fernando Garcia-Menendez and Mehmet Talat Odman
Affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; E-Mail: odman@gatech.edu (M.T.O.)
Abstract: The predictions from air quality models are subject to many sources of uncertainty; among them grid resolution has been viewed as one that is limited by the availability of computational resources. A large grid size could lead to unacceptable errors for many pollutants that are formed via non-linear chemical reactions. Further, using large grid resolution limits the ability to perform accurate exposure assessment. To address this issue in parallel to increasing computational power, modeling techniques have been developed that use finer grids in areas of interest and coarser grids elsewhere. Techniques using multiple grid sizes are called nested grid or multi-scale modeling techniques. These types of approaches are limited by the uncertainty in the placement of finer grids since pertinent locations may not be known a-priori, loss in solution accuracy due to grid boundary interface problems, and inability to adjust to dynamic changes in grid resolution requirements. Another approach to achieving local resolution involves using dynamic adaptive grids. Various adaptive mesh refinement techniques using structured grids as well as mesh enrichment techniques with unstructured grids have been tried in atmospheric modeling. Recently, some of these techniques have been applied in full blown air quality models. In this paper, adaptive grid methods used in weather forecasting and air quality modeling are reviewed and categorized. Recent advances made in air quality simulations owing to the use of adaptive grids are summarized. The advantages and disadvantages of each adaptive grid method and the potential of adaptive grid use in meteorological, air quality, and climate modeling are discussed.

Type of Paper: Article
Title: Dynamics and Physical Process Considerations for On-Line/Off-line Coupled Meteorology and Air Quality Modeling
Authors: Daewon W. Byun and coauthor (TBD)
Affiliation: Air Resoruces Laboratory, NOAA, US, SSMC3 1315 East West High way, Silver Spring, MD 20910, USA; E-Mail: daewon.byun@noaa.gov (D.W.B.)
Abstract: A reliable air quality simulation requires both a well-verified comprehensive air quality model and accurate model inputs such as meteorological data from a weather prediction model, initial and boundary conditions of modeled chemical species and high quality emissions data. There are many different levels of providing meteorology data for air quality modeling depending on the temporal and physical scales of air quality problems that need to be addressed. In the early days of Eulerian air quality modeling, diagnostic wind field modeling and objective analysis approaches have been widely used to provide meteorological input parameters. Since the early 1980s, prognostic meteorological models are applied for air quality simulations, usually in an off-line mode, where the meteorological simulation is performed firsts and necessary meteorological fields are supplied to air quality model at a predetermined time interval. Recently, there have been active developments to include atmospheric chemistry code directly in a meteorological model (in-line mode) or linking an independent air quality model to communicate with the dynamic core of meteorological model concurrently computing dynamics and chemistry (on-line mode). The direction of communication can be one way from meteorological model to air quality only, or two-ways where air quality influence meteorology as well. Both off-line and on-line coupling methods are needed for different operational applications and science investigation activities. In this paper we will review critical issues of coupling dynamics, physics and chemical modules with respect to the scales of atmospheric motions and chemical phenomena. We will review limitations imposed by the governing equations, grid and coordinate structures, physics modules, and numerical techniques available in a few mesoscale meteorological models and their impacts on simulating air quality such as long-range transport, regional and local ozone and particulate matter nonattainment issues. Also, we will review needs for the key model inputs for meteorology and air quality and discuss how to harmonize the different requirements. This review intends to contribute to advancing integration approaches between the dynamic and atmospheric components for building fully coupled system with on-line and off-line capabilities.

Type of Paper: Article
Title: A Review of Tropospheric Atmospheric Chemistry and Gas-Phase Chemical Mechanisms for Air Quality Modeling
Authors: Willam R. Stockwell
Affiliation: Department of Chemistry, Howard University, 525 College Street, NW, Washington, DC 20059, USA; E-Mail: wstockwell@Howard.edu
Abstract: Gas-phase chemical mechanisms are vital components of prognostic air quality models. The mechanisms are incorporated into modules that are used to calculate the chemical sources and sinks of ozone and the precursors of particulates. Fifty years ago essential atmospheric chemical processes, such as the importance of the hydroxyl radical, were unknown and crude air quality models incorporated only a few parameterized reactions obtained from fitting observations. Chemical mechanisms improved as more experimental data became available and more powerful computers that could support more detailed models became available. However it will not be possible to incorporate a detailed treatment of the chemistry for all known chemical constituents because there are thousands of organic compounds emitted into the atmosphere. Some simplified method of treating atmospheric organic chemistry is required to make air quality modeling computationally possible. Most of the most significant differences between air quality mechanisms are due to the differing methods of treating this organic chemistry. The purpose of this review is to present an overview of atmospheric chemistry that is incorporated into air quality mechanisms and the history and differences between some of the more widely used mechanisms.

Type of Paper: Article
Title: Surface Flux Modeling for Air Quality Applications
Authors: Jonathan Pleim and Limei Ran
Affiliation: Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, USEPA, RTP, NC 27711, USA;
E-Mail: pleim.jon@epa.gov (P.J.)
Abstract: Surface fluxes of chemical constituents are key sources and sinks for atmospheric chemistry and air quality modeling. The ultimate fate of all mass emitted into the atmosphere is to return to the Earth’s surface via wet and dry deposition. Many important chemical species are also emitted to the atmosphere through surface flux from the land, biosphere, and ocean. These chemicals are best modeled using bi-directional algorithms where the sign of the concentration gradient across the surface-atmosphere interface determines evasion or deposition. Other chemical species that are either produced chemically in the atmosphere (e.g. ozone) or are emitted primarily by anthropogenic sources (e.g. CO) can be treated by one-way surface flux, or dry deposition, models. A third category includes chemicals that are primarily emitted from biogenic sources (e.g. isoprene) that can be modeled as one-way surface emission fluxes. All three of these types of air-surface exchange processes are partially analogous to surface fluxes of heat and moisture that are simulated by meteorology models. Thus, consistent representation of surface parameterizations and turbulent flux parameters between the meteorology and air quality models is highly desirable. However, the wide variety of characteristics of gases and aerosols in the atmosphere require consideration of multiple pathways for air-surface exchange. For example many species exhibit strong stomatal uptake and/or emissions and therefore may be modeled analogously to vegetative evapotranspiration and CO2 assimilation. Absorption into leaf cuticle, dissolution in canopy water or soil moisture, and reaction with surfaces are also important deposition pathways. Deposition of aerosols depends primarily on size where larger particles are affected by gravitational settling and ultrafine particles by Brownian diffusion. This review will describe the current state of chemical dry deposition modeling, recent progress in bi-directional flux modeling, synergistic model development research with field measurements, and coupling with meteorological land surface models.
Keywords: dry deposition; bi-directional fluxes

Type of Paper: Article
Title: Chemical Mechanism Solvers in Air Quality Models
Authors: Hong Zhang, John C. Linford and Adrian Sandu
Affiliation: Computational Science Laboratory, Department of Computer Science, Virginia Polytechnic Institute and State University, Blaskcburg, VA 24061, USA; E-Mails: zhang@vt.edu (H.Z.); jlinford@vt.edu (J.C.L.); sandu@cs.vt.edu (A.S.)
Abstract: The numerical solution of large numbers of coupled partial differential equations describing the chemical mechanism in air quality models requires intensive computational effort, and computational costs increase rapidly as the number of chemical species increases. As a result, highly efficient chemical mechanism solvers have been developed for use in air quality models. High performance techniques have also been applied to these solvers for solving large scale problems. In this paper we reviews several stiff integration methods which have been widely used in chemical mechanism solvers and acceleration of these solvers on multi-core platforms. This review is biased toward work done over the last 10 years with emphasis on current state-of-the-art software KPP.

Type of Paper: Article
Title: Sub-Grid Scale Plume Modeling
Authors: Prakash Karamchandani, Krish Vijayaraghavan and Shu-Yun Chen
Affiliation: ENVIRON International, 773 San Marin Drive, Suite 2115, Novato, CA 94998, USA; E-Mail: prakash@environcorp.com (P.K.)
Abstract: Multi-pollutant chemical transport grid models, such as CMAQ and CAMx, are being routinely used to predict the impacts of emission controls on the concentrations and depositions of pollutants such as ozone (O₃), fine particulate matter (PM_2.5), mercury (Hg), and air toxics. While these models have a fairly comprehensive treatment of the governing atmospheric processes, they are unable to correctly represent the near-source transport and chemistry of sub-grid scale emissions, such as those from elevated point sources, because of their relatively coarse horizontal resolution. Several different approaches have been used to address this limitation, such as using fine grids, adaptive grids, or an embedded sub-grid scale plume model (plume-in-grid). Of these various approaches, Plume-in-Grid (PinG) modeling has been more commonly used in previous and current operational models. In this paper, we provide a history and review of plume-in-grid modeling from its initial applications for ozone modeling in the Urban Airshed Model (UAM) in the early 1980s using a relatively simple plume model, to more sophisticated and state-of-the-science plume models, that include a full treatment of gas-phase, aerosol, and cloud chemistry, embedded in contemporary models such as CMAQ, CAMx, and WRF-Chem. We present some results from PinG applications using CMAQ for ozone, PM_2.5, and mercury impacts from elevated point sources.

Type of Paper: Article
Title: Representation of Regional Lightning NO_x Source in Regional Air Quality Models
Authors: Ken Pickering
Affiliation: NASA/GFSC; E-Mail: kenneth.e.pickering@nasa.gov
Abstract: The parameterization of lightning-generated NO_x (LNO_x) in regional air quality models will be reviewed. The LNO_x source plays a very important role in photochemical ozone production in the upper troposphere in the tropics year-round and in the summer over the midlatitude continental regions. The influence on boundary layer air quality is much less than in the upper troposphere, but needs to be included in the regional models. Three components are required for specifying the LNO_x source: a method of predicting lightning flash rates, an average NO_x production rate per flash, and a method of distributing the LNO_x emissions in the vertical. In order to best simulate the photochemistry of convective outflow conditions, LNO_x needs to be injected into the model at the same times and locations where convective transport of other ozone precursor gases occur. Therefore, flash rates should be predicted based on variables produced by the convective parameterization in the meteorological driving model. We review the variables that have been used for this purpose. Globally, the best current estimate of the lightning NO_x source is 5 TgN/year, which combined with the satellite-based climatological annual flash rate yields approximately 250 moles NO_x per flash. However, cloud-resolved modeling of LNO_x for midlatitude and subtropical thunderstorms constrained with anvil NO_x observations and observed flash rates has indicated an average value of ~500 moles/flash is more appropriate for these regions. Average vertical profiles of flash channel segment length from Lightning Mapping Arrays (LMA), along with a pressure dependence, are typically used to specify the vertical distribution of LNO_x emissions in the models. The methods by which these model components are handled in CMAQ, WRF-Chem, REAM, and other models are discussed. The impacts of LNO_x on boundary layer air quality are also reviewed.