Air Pollution Transport Model Research Articles

Development of a source-specific biomass burning emissions inventory for Washington, Oregon, and California

While wildfires are the dominant source of biomass burning emissions across the U.S., prescribed and agricultural burns also contribute to emissions and ambient air quality. Understanding the differential impacts that these different sources of biomass burning have on air quality and public health is important in the development of effective exposure reduction strategies. We leverage the high-resolution Fire INventory from NCAR (FINN) to develop a source-specific biomass burning emission inventory that distinguishes between wildfire, prescribed burn, and agricultural burn sources across Washington, Oregon, and California. We describe the methodology for reclassifying FINN using multiple national and state-level fire and fuel treatment inventories and present the results of the emissions reclassification process for these three states from 2012 to 2020. We matched 72%, 78% and 81% of FINN emissions event locations to fire locations from the fire type input datasets in Washington, Oregon, and California, respectively. When compared to county-level fire type-specific PM2.5 emissions estimates from the 2014, 2017, and 2020 EPA National Emissions Inventory, we found greater agreement among wildfire-specific estimates across years and states (R2 range: 0.59–0.98), relative to prescribed (R2 range: 0.12–0.73) and agricultural burns (R2 range: 0.43–0.95). This fire type-specific biomass burning emissions inventory can be used in air pollution transport models to better understand the impacts of each of these sources on air quality across the region along with downstream public health impacts.

Anthropogenic aerosols in precipitation over the Indo-Gangetic basin.

This study investigated the concentration of heavy metals in rainwater (RW) at a semi-arid region of the Indo-Gangetic basin to understand the influence of local, regional, or long-range transport of air pollutants during the monsoon and non-monsoonal rain. The concentration of heavy metals in RW was determined using Atomic Absorption Spectrophotometer with Graphite Furnace, the scavenging ratio was estimated, and source interpretation was carried out using Principle Component Analysis (PCA) and HYSPLIT model. Ca was the highest contributor in RW followed by Na, Fe, Mg, and Al whereas Ba, Cr, Cu, Mn, Ni, Pb, and Zn were found in trace quantity. During the non-monsoon period, the crustal component (Ca) was the highest; however, during the monsoon, sea salt components (Na and Fe) were found higher. The scavenging ratio for metals was estimated and was found many times higher than those reported over European sites. The moderate concentration of heavy metal in RW was found with higher wind from South (S), South-West (SW), and North-West (NW) directions. Air mass back trajectory shows a significant contribution of metals from the Arabian Sea (South-Westerly wind) during active monsoon, whereas, in the non-monsoon season, the air masses mainly originated from the north-west indicating a contribution from wind-blown dust. The correlation analysis has shown the positive correlations between Ca and Mg, Mg and Na, Na and Cu, Al and Zn, Zn and Ba, Ba and Cr, and Cr and Zn. Principal Component Analysis (PCA) indicated loading of Ca, Na, Mg, Cu, Mn, and Ni in the first factor suggesting their crustal origin, whereas the second factor showed high loading of Al, Ba, Zn, Cr, and Ni indicating vehicular exhaust and industrial emission as their major sources, and loading for Ba and Mg in the third factor indicates the mixed contribution from both natural and anthropogenic sources in rainwater during the monsoon and non-monsoon periods. The data of this study can be used in the air pollution transport model. This study will help in source interpretation over the Indo-Gangetic basin and will help in planning for National Clean Air Program (NCAP) and deriving critical load.

Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation

Data assimilation (DA) combines incomplete background values obtained via chemical transport model predictions with observational information. Several 3-Dimensional variational (3DVAR) and sequential methods (e.g., ensemble Kalman filter (EnKF)) are used to define model errors and build a background error covariance (BEC) and are important factors affecting the prediction performance of DA. The BEC determines the spatial range, where observation concentration is reflected in the model when DA is applied to an air pollution transport model. However, studies investigating the characteristics of BEC using air quality models remain lacking. In this study, horizontal length scale (HLS) and vertical length scale (VLS) analyses of a BEC were applied to EnKF and ensemble square root filter (EnSRF), respectively, and two ensemble-based DA methods were performed; the characteristics were compared with those of a BEC applied to 3DVAR. The results of 6 h PM2.5 predictions performed for 42 days were evaluated for a control run without DA (CTR), 3DVAR, EnKF, and EnSRF. HLS and VLS respectively exhibited a high correlation with the ground wind speed and with the planetary boundary layer height for diurnal and daily variations; EnKF and EnSRF exhibited superior performances among all the methods. The root mean square errors were 11.9 μg m−3 and 11.7 μg m−3 for EnKF and EnSRF, respectively, while those for 3DVAR and CTR were 12.6 μg m−3 and 18.3 μg m−3, respectively. Thus, we proposed a simple method to find a Gaussian function that best described the error correlation of the BEC based on the physical distance.

Solar radiometer sensing of multi-year aerosol features over a tropical urban station: direct-Sun and inversion products

Abstract. The AErosol RObotic NETwork (AERONET) is the most developed ground-based network for aerosol remote sensing and has been playing a significant role not only in monitoring air quality for protecting human health but also in assessing the radiative budget of our planet Earth. In this paper, we report the direct-Sun and inversion products, comprising of spectral variation of aerosol optical depth (AOD), associated Ångström exponent (AE), fine- and coarse-mode aerosol fractions, aerosol size distribution (ASD), refractive index (RI), asymmetry parameter (AP), single scattering albedo (SSA), aerosol radiative forcing (ARF) and columnar concentration of gas constituents such as water vapor (H2O), obtained from a Cimel Sun–sky radiometer, functioning in Pune, India, under the AERONET program since October 2004. These long-term measurements carried out from 2005 to 2015 could serve as an urban aerosol optical long-term average or climatology. The AOD long-term variations at all wavelengths, considered in the study, exhibited an increasing trend, implying year-to-year enhancement in aerosol loading. The mean seasonal variations in AOD from cloud-free days indicated greater values during the monsoon season, revealing dominance of hygroscopic aerosol particles over the station. Contribution by different aerosol types to AOD has also been deduced and discussed, and dominance of a mixed type of aerosols (44.85 %) found, followed by combination of biomass burning and urban industrial aerosols (22.57 %) compared to other types of aerosols during the study period. The long-term datasets, derived aerosol and trace gas products play a significant role in understanding aerosol climate forcing, trends and evaluation of regional air pollution and validation of aerosol transport models over the study region.

Short‐Term Impacts of the Megaurbanizations of New Delhi and Los Angeles Between 2000 and 2009

AbstractUrban areas are expanding worldwide due to increasing population, standard of living, and migration from rural areas. This study uses satellite and road data to quantify the urbanization of two megacities, New Delhi and Los Angeles, between 2000 and 2009. It then estimates, with a three‐dimensional nested global‐through‐urban climate, weather, and air pollution model, Gas, Aerosol, Transport, Radiation, General Circulation, Mesoscale, and Ocean Model, the short‐term atmospheric impacts of such urbanization alone. The simulations account for changes in meteorologically driven natural emissions, but not anthropogenic emissions, between 2000 and 2009. New Delhi's urban extent, defined based on the physical existence of its built structures and the transitional gradient from buildings to rural areas rather than on abrupt administrative borders, increased by ~80% and Los Angeles's by ~22.5% between 2000 and 2009. New Delhi experienced a larger increase in its urban extent relative to its population during this period than did Los Angeles. In both megacities, urbanization increased surface roughness, increasing shearing stress and vertical turbulent kinetic energy, decreasing near‐surface and boundary layer wind speed, contributing to higher column pollution levels. Urbanization may also have increased downward solar plus thermal infrared radiation fluxes to the ground and consequently upward latent and sensible heat fluxes from the ground to the air, increasing near‐surface air temperatures. As such, urbanization alone may have had notable impacts on both meteorology and air quality.

Long-Term Aerosol Climate Data Record Derived from Operational AVHRR Satellite Observations

Aerosol optical thickness (AOT) was retrieved using the Advanced Very High Resolution Radiometer (AVHRR) PATMOS-x Level-2b gridded radiances and the two-channel algorithm of the National Climatic Data Center (NCDC). The primary retrieval product is AOT at 0.63 μm channel. AOT is also retrieved at 0.83 μm or 1.61 μm channel for consistent check. The retrieval was made during day time, under clear sky and snow-free conditions, and over the global oceans. The spatial resolution is 0.1×0.1 degree grid and the temporal resolution is both daily and monthly. The resultant AVHRR AOT climate data record (CDR) spans from August 1981 to December 2009 and provides the longest aerosol CDR currently available from operational satellites. This dataset is useful in studying aerosol climate forcing, monitoring long-term aerosol trends, and evaluating global air pollution and aerosol transport models over the global ocean.

SO-MUM: A Coupled Atmospheric Transport and Multimedia Model Used to Predict Intraurban-Scale PCB and PBDE Emissions and Fate

A spatially resolved, dynamic version of the Multimedia Urban Model (MUM) and the boundary layer forecast and air pollution transport model BLFMAPS were coupled to build Spatially Oriented MUM (SO-MUM), to estimate emissions and fate of POPs in an urban area on a 5 × 5 km(2) cell resolution. SO-MUM was used to back-calculate emissions from spatially resolved measured air concentrations of PCBs and PBDEs in Toronto, Canada. Estimated emissions of Σ(88)PCBs were 230 (40-480) kg y(-1), 280 (50-580) g y(-1) km(-2), or 90 (16-190) mg y(-1) capita(-1), and Σ(26)PBDEs were 28 (6-63) kg y(-1), 34 (7-77) g y(-1) km(-2), or 11 (2-25) mg y(-1) capita(-1). A mass inventory of penta- and octa-BDEs in Toronto was estimated to be 200 tonnes (90-1000 tonnes) or 80 (40-400) g capita(-1). Using this estimate and that of 440 (280-800) tonnes of PCBs, estimated emissions of Σ(88)PCBs and Σ(26)PBDEs per mass of chemical inventory in Toronto were 0.5 (0.05-1.6) and 0.1 (0.01-0.7) g y(-1) kg(-1), respectively. The results suggest annual emission rates of 0.04% and 0.01% from the mass inventories with downtown accounting for 30% and 16% of Toronto's chemical inventory and emissions of PCBs and PBDEs, respectively. Since total PBDE emissions are a function of mass inventory, which is proportional to building volume, we conclude that building volume can be used as a proxy to predict emissions. Per mass inventory emission rates were negatively related to vapor pressure within a compound class, but not consistently when considering all compound congeners.

On the sign-stability of numerical solutions of one-dimensional parabolic problems

The preservation of the qualitative properties of physical phenomena in numerical models of these phenomena is an important requirement in scientific computations. In this paper, the numerical solutions of a one-dimensional linear parabolic problem are analysed. The problem can be considered as a altitudinal part of a split air pollution transport model or a heat conduction equation with a linear source term. The paper is focussed on the so-called sign-stability property, which reflects the fact that the number of the spatial sign changes of the solution does not grow in time. We give sufficient conditions that guarantee the sign-stability both for the finite difference and the finite element methods.

Analysis of a transport model applying operator splitting and semi-Lagrangian method

In the present paper, a simple 2D air pollution transport model is investigated applying the sequential and the Strang Marchuk operator splitting procedures. A comparison is done between the cases when the upwind scheme and the semi-Lagrangian scheme are used for solving the advection sub-problem.

Operational air pollution forecast modelling using the THOR system

An operational air pollution forecast system, THOR, is under development. The aim of the system is to produce 2–3 days air pollution forecasts, twice every day, from European scale to local (street) scale, for the most important harmful air pollution species. Currently, the system consists of a numerical weather forecast model and a long range air pollution transport model. The single models, the coupling of the models and their real time performance on fast workstations with parallel architecture will be described. Some preliminary model results will be shown.

A High-Resolution Air Pollution Model Suitable for Dispersion Studies in Complex Terrain

Abstract The development of an air pollution transport model that uses an expanding terrain-following coordinate with high resolution in analytic form near the surface and a high-order accurate transport algorithm is described. The model is designed to be internally consistent in the application of numerical methods, computationally efficient, and suitable for pollutant dispersion studies in complex terrain. The application of the time-splitting Warming–Kutler–Lomax advection scheme is examined in both rotational and deformational flows for its conservation and stability properties. It is found that the combination of this scheme with a short-wave filter makes the integration mass conserving and dispersion free. The model is applied to some hypothetical cases that represent the typical phenomena occurring over mountains. The model proves to be capable of simulating realistic planetary boundary layer structure and stability variation, hydrostatic mountain waves, thermally induced mountain–valley winds, and...

Modelling wind fields in MAQS

MAQS is the Metropolitan Air Quality Study, a multi-million dollar scientific investigation of photochemical smog and fine particle pollution in the major urban and industrial area of New South Wales on the east coast of Australia. The study area included Newcastle/Hunter Valley region, the Sydney basin, and the Wollongong/Illawarra region. We have extended and applied the detailed prognostic numerical air pollution transport and dispersion model, LADM, to several simulations of local and inter-regional air pollution events for the MAQS region. The investigation highlighted (1) the large uncertainty in specifying surface synoptic meteorological data on high pollution days, (2) the ability of LADM to predict well the local winds and temperatures, even without assimilation of observational data into the model, (3) the need to incorporate observations of surface and upper air winds to give accurate air trajectories, (4) that days conducive to sea-breeze conditions are the key to the meteorology of high pollution in the MAQS region, and (5) that poor dispersion in the Sydney basin also implies inter-regional transport: from the Newcastle/Hunter Valley region to parts of Sydney, or from much of Sydney to the Illawarra.

Test of two numerical schemes for use in atmospheric transport-chemistry models

Two fast integration methods for chemical kinetics are tested. One is the Quasi-steady State Approximation (QSSA) method and the other is a new Euler Backward Iterative (EBI) method. The EBI method is based on iterative solution of the Euler backward approximation of a coupled system of nonlinear ordinary differential equations of chemical kinetics. The efficiency of the iteration process is increased by using analytical solutions for groups of species which are strongly coupled. The accuracy of both integration methods is evaluated by comparing the results with solutions obtained by a Gear method, the Livermore Solver for Ordinary Differential Equations (LSODE). The chemical scheme used is the Carbon-bond Mechanism IV (CBM-IV). The numerical methods are tested of three chemical scenarios: two scenarios without emissions and with constant reaction rates and one scenario with variable emissions and photodissociation rates. Using a short time step (50 s), both EBI and QSSA perform very well, even under extreme chemical conditions. For larger time steps the EBI method performs better than QSSA. In the case of more realistic chemical conditions, both methods perform well even with a time step of 900 s. The accuracy of QSSA depends highly on the iteration procedure. Without iterations the QSSA method performs poorly. The great advantage of the EBI method is that concentrations are computed using linear operators only. Because of this, the method is mass conserving and can be used in air pollution transport models where higher moments of concentration distributions also need to be evaluated. Both the QSSA and the EBI methods can be recommended for use in atmospheric transport-chemistry models, where accuracy as well as computational efficiency is important. In general, the new EBI method is, however, more efficient than QSSA with a constant number of iterations.

Systematic errors arising from the application of mean input data in long-term air pollution transport models

The effect of applying mean (i.e. temporally and spatially averaged) input data (removal coefficients, wind velocity, travel distance between source and receptor) in a long-term model of the transport of heavy metals (especially As) in Europe's atmosphere has been investigated by running modified versions of this model. At five receptors considered in this study, the application of mean removal coefficients in the model resulted in an underprediction of concentration values and dry deposition, being approximately 0.75 times the original values, and an overestimation of wet deposition by a factor of approximately 1.5. The assumption of straight travel of pollutants between a source and some receptor brings about an overestimation of concentration and deposition by a factor of approximately 1.2. The application of mean wind velocity changed results only slightly. All occurring effects have also been investigated theoretically, so that assertions and formulae which are independent of the special model under consideration have been obtained.

On coupling air pollution transport models of different scales

On coupling air pollution transport models of different scales

The CCMS air pollution model intercomparison study

Four air pollution transport models were tested and compared in an area of ~ 400 × 400 km 2. Three models were Eulcrian grid models, the fourth a Lagrangian trajectory model. The data base (emissions and meteorological observations) were essentially the same for all models. Differences in model output could only be a result of the different (numerical) structure of the models and of the differences in processing of the meteorological data. It turned out that the latter was the major source of differences in model results. Generally there was a satisfactory correlation between model results and observed concentrations. Mainly due to the negligence of transport of pollutants into the modelling region, predicted concentrations were considerably lower than the observed.

Heuristics in an Air Pollution Control Cost Model: The “AIRCOST” Model of the Electric Utility Industry

A number of uncertainties associated with national air pollution policy are currently being analyzed by the United States Congress, the Environmental Protection Agency (EPA), and the Department of Energy (DOE) with the aid of a large-scale model of electric utility plant emissions under the 1983 Clean Air Act Amendments called AIRCOST. The AIRCOST methodology combines a “supply side” economics approach with detailed plant by plant models that result in substantial spatial and technological resolution. In fact, the resulting emissions projections are being used as input to separate air pollution transport models for the evaluation of "acid rain" impacts. This paper documents and partially validates this methodology with which a critical segment of U.S. air pollution policy has been and is continuing to be analyzed.

A long-range air pollution transport model for eastern north America—II. Nitrogen oxides

A simple, five-species algorithm to model the chemistry of oxides of nitrogen during long-range transport has been developed and used in the Eastern North America Model of Air Pollution (ENAMAP). The algorithm models the reactions and the physical depositions of NO and NO 2 as the primary pollutants, HNO 3 and particulate nitrate as the reaction products, and peroxyacetyl nitrate (PAN). PAN is utilized as a temporary reservoir for NO x, reacting during the day to form HNO 3, nitrate, and itself, then decomposing back to NO 2 at night. The NO and NO 2 are kept at equilibrium, and the NO 2 reacts to form PAN, HNO 3, and nitrate. The reaction rates and NO: NO 2 equilibrium constant vary diurnally. The model has been run for the months of January and August 1977, and has produced NO 2 concentration patterns that have characteristics consistent with the limited existing measurements of atmospheric nitrogen compounds.

A long-range air pollution transport model for eastern north america—I. Sulfur oxides

This paper describes a Lagrangian model for simulating long-range air pollution transport over eastern North America. One version (denoted ENAMAP-2S) uses emissions inventories and standard daily weather reports to compute the airborne concentrations of SO 2 and sulfate, and their deposition on the earth's surface. A separate version of the model (ENAMAP-2N) applies to oxides of nitrogen. These versions of the ENAMAP model include the influences of smoothed terrain on the winds, and divide the atmospheric boundary layer into three parts, allowing pollutant emissions to be divided among the layers. Vertical mixing is controlled by diffusion coefficients computed from wind shear, stability, and knowledge of the mixing depth. The transformation and wet and dry deposition rates are based on recently published values. The models have been used to compute monthly average values of concentrations and depositions for January and August 1977. Typical examples are shown. The sensitivity of the output fields of ENAMAP-2S to values selected for input parameters (e.g. transformation rate of SO 2 to sulfate and deposition rates) has been studied; and based on present information, optimum values of the parameters are given. The model results include geographical patterns of pollutant concentration and deposition, and interregional exchange tables that show how much of the pollution in a certain region was emitted locally and how much originated in other specified areas. The simulated monthly airborne concentrations of SO 2 and sulfate are generally within a factor of 2 of measured values.

Applications of a Numerical Air Pollution Transport Model to Dispersion in the Atmospheric Boundary Layer

Abstract A numerical, advection-diffusion air pollution transport model is used to describe dispersion of emissions from urban area-type sources for several atmospheric stability situations, The estimation of appropriate velocity and diffusivity fields for use as meteorological input data is discussed in detail. Profiles representing the constant-flux surface layer are used in a nondimensional transport equation to obtain concentration fields over a limited horizontal and vertical scale. A wind spiral model and diffusivity profile after Blackadar is used to simulate dispersion under neutral stability conditions on an urban scale and in three dimensions for both a steady source and a single puff. Analysis of the trajectory and spread statistics for the puff suggests that, on an urban scale, the combined effects of vertical diffusion and transverse wind components result in effective cross-wind diffusion coefficients an order of magnitude greater than typical values of vertical diffusion coefficients. Super...