Abstract. The Surface PARTiculate mAtter Network (SPAR-TAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM 2.5 ). Our methods infer the spatial and temporal variability of PM 2.5 in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM 2.5 , with a collocated nephelometer sampling air continuously. SPAR-TAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM 2.5 and columnar aerosol optical depth (AOD).We have examined the chemical composition of PM 2.5 at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2-26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM 2.5 constituents across all sites (relative contribution ± SD) are ammoniated sulfate (20 % ± 11 %), crustal material (13.4 % ± 9.9 %), equivalent black carbon (11.9 % ± 8.4 %), ammonium nitrate (4.7 % ± 3.0 %), sea salt (2.3 % ± 1.6 %), trace element oxides (1.0 % ± 1.1 %), water (7.2 % ± 3.3 %) at 35 % RH, and residual matter (40 % ± 24 %).Analysis of filter samples reveals that several PM 2.5 chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 µg m −3 (Buenos Aires, Argentina) to 17 µg m −3 (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 µg m −3 (Mammoth Cave, in summer) to 6.8 µg m −3 (Kanpur, dry season). Equivalent black carbon ranged from 0.7 µg m −3 (Mammoth Cave) to over 8 µg m −3 (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM 2.5 (r 2 = 0.76, slope = 1.12), daily sulfate (r 2 = 0.86, slope = 1.03), and mean fractions of all major PM 2.5 components (within 6 %). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 % for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn : Al ratios.The expected water contribution to aerosols is calculated via the hygroscopicity parameter κ v for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 ± 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM 2.5 at 35 % relative humidity by merging with nephelometer measurements. These hour...

Exposure to ambient fine particulate matter (PM) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM to interpret globally dispersed PM mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m), mineral dust (1.9-14.7 μg/m), residual/organic matter (2.1-40.2 μg/m), and black carbon (1.0-7.3 μg/m). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m), industry (6.5 μg/m), and power generation (5.6 μg/m) are leading sources of outdoor global population-weighted PM concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM provides insight into sources and processes that influence the global spatial variation in PM composition.

Abstract. Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM 2.5 ) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short-and long-term exposure to PM 2.5 at local-toglobal scales, but there are limitations and outstanding questions about the accuracy and precision with which groundlevel aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM 2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM 2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM 2.5 and PM 10 , are highly autonomous. Hourly PM 2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, watersoluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM 2.5 estimates used for assessing the health effects of aerosols. Mean PM 2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM 2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.

The energy spectra and the corresponding two-component spinor wavefunctions of the Dirac equation for the Rosen-Morse potential with spin and pseudospin symmetry are obtained. The s−wave (κ = 0 state) solutions for this problem are obtained by using the basic concept of the supersymmetric quantum mechanics approach and function analysis (standard approach) in the calculations. Under the spin symmetry and pseudospin symmetry, the energy equation and the corresponding twocomponent spinor wavefunctions for this potential and other special types of this potential are obtained. Extension of this result to κ = 0 state is suggested.

By employing the Pekeris-type (or a new improved approximation) to deal with the (pseudo or) centrifugal term, we solve the Klein–Gordon and Dirac equations with equally mixed scalar and vector Deng–Fan molecular potentials for all values of l (orbital the angular momentum quantum number) and κ (spin–orbit coupling quantum number), respectively. Using the formalism of the Nikiforov–Uvarov method, the approximate analytical bound state energy equations and the associated two-component spinors corresponding to the two relativistic equations are obtained. Also, special cases including the non-relativistic limits of the relativistic equation are obtained.