Atmospheric Environment (v.37, #36)

Application of receptor modeling to atmospheric constituents at Potsdam and Stockton, NY by Wei Liu; Philip K. Hopke; Young-ji Han; Seung-Muk Yi; Thomas M. Holsen; Scott Cybart; Kimberly Kozlowski; Michael Milligan (4997-5007).
A measurement program in this study has been undertaken to measure the concentrations of particles and Hg0 in rural areas of New York State during the summer of 2000 and 2001. Sampling was performed at sites in southwestern (Stockton, NY) and northern New York (Potsdam, NY) where these materials may be transported into the New York from the central United States and from Canada. The data from these measurements were used in paired receptor models to assess the origins of the measured concentrations. Factor analysis in the form of positive matrix factorization (PMF) was used to obtain information about possible sources of the aerosol. Six and seven sources were resolved from Stockton and Potsdam sites, respectively. Six of the sources are common to the two sites in these two summers. They are secondary sulfate, secondary nitrate, soil, wood smoke, zinc smelter and copper smelter. A nickel smelter source is also resolved at Potsdam. Potential source contribution function (PSCF) analysis which combines the aerosol data with the air parcel backward trajectories was applied to identify possible source areas and pathways from these sources at the two sites. The combination of the two receptor modeling methods, PMF and PSCF, provides an effective way in identifying atmospheric aerosol sources and their likely locations. Emissions from different anthropogenic activities as well as secondary aerosol production are the main source measured in Potsdam and Stockton.
Keywords: PM2.5; PAHs; Vapor phase mercury; PMF; Potsdam; Stockton; PSCF; Trace elements; Particulate matter;

Incorporation of parametric factors into multilinear receptor model studies of Atlanta aerosol by Eugene Kim; Philip K. Hopke; Pentti Paatero; Eric S. Edgerton (5009-5021).
In prior work with simulated data, ancillary variables including time resolved wind data were utilized in a multilinear model to successfully reduce rotational ambiguity and increase the number of resolved sources. In this study, time resolved wind and other data were incorporated into a model for the analysis of real measurement data. Twenty-four hour integrated PM2.5 (particulate matter ⩽2.5 μm in aerodynamic diameter) compositional data were measured in Atlanta, GA between August 1998 and August 2000 (662 samples). A two-stage model that utilized 22 elemental species, two wind variables, and three time variables was used for this analysis. The model identified nine sources: sulfate-rich secondary aerosol I (54%), gasoline exhaust (15%), diesel exhaust (11%), nitrate-rich secondary aerosol (9%), metal processing (3%), wood smoke (3%), airborne soil (2%), sulfate-rich secondary aerosol II (2%), and the mixture of a cement kiln with a carbon-rich source (0.9%). The results of this study indicate that utilizing time resolved wind measurements aids to separate diesel exhaust from gasoline vehicle exhaust. For most of the sources, well-defined directional profiles, seasonal trends, and weekend effects were obtained.
Keywords: Source apportionment; Receptor modeling; Positive matrix factorization; Multilinear engine; PM2.5;

Concentrations and co-occurrence correlations of 88 volatile organic compounds (VOCs) in the ambient air of 13 semi-rural to urban locations in the United States by James F Pankow; Wentai Luo; David A Bender; Lorne M Isabelle; Jay S Hollingsworth; Cai Chen; William E Asher; John S Zogorski (5023-5046).
The ambient air concentrations of 88 volatile organic compounds were determined in samples taken at 13 semi-rural to urban locations in Maine, Massachusetts, New Jersey, Pennsylvania, Ohio, Illinois, Louisiana, and California. The sampling periods ranged from 7 to 29 months, yielding a large data set with a total of 23,191 individual air concentration values, some of which were designated “ND” (not detected). For each compound at each sampling site, the air concentrations (c a, ppbV) are reported in terms of means, medians, and means of the detected values. The analytical method utilized adsorption/thermal desorption with air-sampling cartridges. The analytes included numerous halogenated alkanes, halogenated alkenes, ethers, alcohols, nitriles, esters, ketones, aromatics, a disulfide, and a furan. At some sites, the air concentrations of the gasoline-related aromatic compounds and the gasoline additive methyl tert-butyl ether were seasonally dependent, with concentrations that maximized in the winter. For each site studied here, the concentrations of some compounds were highly correlated one with another (e.g., the BTEX group (benzene, toluene, ethylbenzene, and the xylenes). Other aromatic compounds were also all generally correlated with one another, while the concentrations of other compound pairs were not correlated (e.g., benzene was not correlated with CFC-12). The concentrations found for the BTEX group were generally lower than the values that have been previously reported for urbanized and industrialized areas of other nations.
Keywords: Volatile organic compounds (VOCs); Benzene, toluene, ethylbenzene, xylenes, BTX (BTEX); Aromatic hydrocarbons; Alkyl benzenes; Alkylated aromatics; MTBE; ETBE; TAME; Chlorinated hydrocarbons; Solvents; Chlorofluorocarbons, CFC (CFCs); Urban air; Air quality; Adsorption/thermal desorption (ATD);

A radiative transfer model based on the Delta-Eddington approximation is coupled into the framework of a three-dimensional air quality model that represents airborne particles as a source-oriented external mixture. Model simulations performed for Southern California on 25 September 1996 show that ultra-violet (UV) irradiance calculated by the model is in good agreement with measured ground level UV at central Los Angeles. Ozone performance statistics show that the use of the fully coupled radiative transfer calculation within the air quality models leads to more realistic predictions in regions with significant concentration gradients of airborne particulate matter and absorbing gases. The new air quality model with fully coupled radiative transfer calculations predicts lower ozone concentrations (10–22% reduction) and lower PM2.5 concentrations (2.3–8.5% reduction) relative to air quality models that use decoupled radiative transfer calculations or surface UV observations from sparse measurement networks. The greatest ozone reduction predicted by the fully coupled model occurs in polluted regions where photolysis rates are greatly reduced. The feedback effect on ozone concentrations decreased when VOC emissions increased but was insensitive to temperature. The greatest PM2.5 reduction occurs in regions with high gas-phase ammonia and particle-phase ammonium nitrate concentrations. The representation of airborne particulate matter as an internal mixture vs. source-oriented external mixture and homogenous particle vs. core-and-shell configuration did not have a significant effect on the relationship between UV feedback and secondary pollutant concentrations.
Keywords: UV extinction; Secondary particulate matter; Source-oriented air quality model;

A baseline urban dispersion model evaluated with Salt Lake City and Los Angeles tracer data by Steven R. Hanna; Rex Britter; Pasquale Franzese (5069-5082).
A simple baseline urban dispersion model is suggested for use in simulating near-surface releases of tracer chemicals in the urban canopy layer. The model is based on the Gaussian plume or puff model, accounting for low wind speeds, nearly neutral stabilities, large turbulence intensities, and large initial mixing in urban areas. The performance characteristics of this baseline model can be easily determined and used for comparisons with more complex models. Two urban tracer data sets are used to demonstrate the baseline model's performance—the Salt Lake City (SLC) Urban 2000 data set, and the Los Angeles (LA) 2001 data set. The focus of the comparisons is on the maximum concentration, C max, on a given monitoring arc, normalized by the emission rate, Q. The C max/Q observations follow some straightforward similarity relations, such as a decrease with downwind distance, x, raised to the power −1.5 to −2.0, and a lack of dependence on wind speed during nighttime light wind scenarios when wind speeds are less than about 1.5 m/s. The predictions of the simple baseline model are shown to agree with the observations from the 30 experimental trials in SLC and LA within a factor of about two to three.
Keywords: Urban dispersion; Urban meteorology; Turbulence and dispersion; Air pollution modeling;

The analysis of comprehensive chemical reactions mechanisms, parameter estimation techniques, and variational chemical data assimilation applications require the development of efficient sensitivity methods for chemical kinetics systems. The new release (KPP-1.2) of the kinetic preprocessor (KPP) contains software tools that facilitate direct and adjoint sensitivity analysis. The direct-decoupled method, built using BDF formulas, has been the method of choice for direct sensitivity studies. In this work, we extend the direct-decoupled approach to Rosenbrock stiff integration methods. The need for Jacobian derivatives prevented Rosenbrock methods to be used extensively in direct sensitivity calculations; however, the new automatic and symbolic differentiation technologies make the computation of these derivatives feasible. The direct-decoupled method is known to be efficient for computing the sensitivities of a large number of output parameters with respect to a small number of input parameters. The adjoint modeling is presented as an efficient tool to evaluate the sensitivity of a scalar response function with respect to the initial conditions and model parameters. In addition, sensitivity with respect to time-dependent model parameters may be obtained through a single backward integration of the adjoint model. KPP software may be used to completely generate the continuous and discrete adjoint models taking full advantage of the sparsity of the chemical mechanism. Flexible direct-decoupled and adjoint sensitivity code implementations are achieved with minimal user intervention. In a companion paper, we present an extensive set of numerical experiments that validate the KPP software tools for several direct/adjoint sensitivity applications, and demonstrate the efficiency of KPP-generated sensitivity code implementations.
Keywords: Chemical kinetics; Sensitivity analysis; Direct-decoupled method; Adjoint model;

The Kinetic PreProcessor KPP was extended to generate the building blocks needed for the direct and adjoint sensitivity analysis of chemical kinetic systems. An overview of the theoretical aspects of sensitivity calculations and a discussion of the KPP software tools is presented in the companion paper.In this work the correctness and efficiency of the KPP generated code for direct and adjoint sensitivity studies are analyzed through an extensive set of numerical experiments. Direct-decoupled Rosenbrock methods are shown to be cost-effective for providing sensitivities at low and medium accuracies. A validation of the discrete–adjoint evaluated gradients is performed against the finite difference estimates. The accuracy of the adjoint gradients is measured using a reference gradient value obtained with a standard direct-decoupled method. The accuracy is studied for both constant step size and variable step size integration of the forward/adjoint model and the consistency between the discrete and continuous adjoint models is analyzed.Applications of the KPP-1.2 software package to direct and adjoint sensitivity studies, variational data assimilation, and parameter identification are considered for the comprehensive chemical mechanism SAPRC-99.
Keywords: Sensitivity analysis; Data assimilation; Parameter identification; Optimization;

Mercury is a highly volatile, bioaccumulating toxic trace metal with a long (∼1 yr) atmospheric residence time. Hg is strongly enriched in volcanic emanations, and volcanoes are the only natural sources of direct Hg emission to the free troposphere and stratosphere. However, there is considerable uncertainty over the annual emission rate of mercury from volcanoes. Previous estimates, based on limited measurements from volcanic plumes, span three orders of magnitude (∼100–103  Mg Hg/yr), or from <1% to ∼50% of total natural Hg emissions.Here we critically evaluate published data from volcanic plumes, and combine this with information from natural archives to show unequivocally the significance of volcanoes for the global biogeochemical mercury cycle. ‘Low’ global volcanic flux estimates (<∼50 Mg/yr) are based on the inappropriate extrapolation of data from low-temperature fumarolic degassing at non-erupting volcanoes to the high-temperature emissions from active volcanoes. Based on data from active volcanoes, we estimate that the time-averaged volcanic Hg emission is ∼700 Mg/yr, or 20–40% of total natural emissions. Continuous degassing accounts for only ∼10% of this flux, while 75% of volcanic Hg is released during ‘smaller’ sporadic eruptions (<10–102  Mg/event). Rare, large (>103  Mg) explosive eruptions overwhelm the total atmospheric burden several times per century, and account for ∼15% of total volcanic Hg emissions.
Keywords: Mercury; Degassing; Volcanic; Pollution; Heavy metal; Emissions inventories;

In recent years magnetic measurements were increasingly used as a proxy for the heavy metal content in soils and sediments influenced by industrial emissions. But sometimes it is difficult to judge if the measured distribution really reflects the present situation or if it is a product of past industrial activities. Therefore, we tested in how far magnetic measurements of tree leaf samples can give information on the current spread of magnetic dusts. We sampled maple leaves at 102 locations in and around the industrial city of Leoben in Austria and determined magnetic susceptibility, isothermal remanent magnetization (IRM) at 1 Telsa(T), the S-ratio (IRM−100mT/IRM1T) and the ratio of IRM to susceptibility (IRM/κ). The distributions of S-ratio and IRM/κ showed that one soft ferrimagnetic phase is dominant over the whole investigated area. This finding was corroborated by scanning electron microscopy (SEM) analysis of the leaves. A comparison with a map of soil magnetic susceptibility revealed that the location of the main source has been the same over a long-time span. The correspondence of the soil map and the leaf map is a convincing proof of the suitability of the method to monitor ongoing emissions.
Keywords: Heavy metals; Biomonitoring; Magnetic mapping;