Light-absorbing organic aerosols, known as brown carbon (BrC), counteract the overall cooling effect of aerosols on Earth’s climate. The spatial and temporal dynamics of their light-absorbing properties are poorly constrained and unaccounted for in climate models, because of limited ambient observations. We combine carbon isotope forensics (δ¹³C) with measurements of light absorption in a conceptual aging model to constrain the loss of light absorptivity (i.e., bleaching) of water-soluble BrC (WS-BrC) aerosols in one of the world’s largest BrC emission regions—South Asia. On this regional scale, we find that atmospheric photochemical oxidation reduces the light absorption of WS-BrC by ~84% during transport over 6000 km in the Indo-Gangetic Plain, with an ambient first-order bleaching rate of 0.20 ± 0.05 day⁻¹ during over-ocean transit across Bay of Bengal to an Indian Ocean receptor site. This study facilitates dynamic parameterization of WS-BrC absorption properties, thereby constraining BrC climate impact over South Asia.

The Surface PARTiculate mAtter Network (SPARTAN) 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. SPARTAN 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 (r² = 0.76, slope = 1.12), daily sulfate (r² = 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 hourly PM_2.5 estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r² = 0.67 (n = 3167), compared to r² = 0.62 when κ_v was not considered. SPARTAN continues to provide an open-access database of PM_2.5 compositional filter information and hourly mass collected from a global federation of instruments.

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-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level 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 PM₁₀, 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, water-soluble 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.

Black carbon (BC) aerosols perturb climate and impoverish air quality/human health—affecting ~1.5 billion people in South Asia. However, a lack of source-diagnostic observations of BC is hindering evaluation of uncertain bottom-up emission inventories (EIs), and thereby also models/policies. Here, we present dual-isotope-based (Δ¹⁴C/δ¹³C) fingerprinting of wintertime BC at two receptor sites of the continental outflow. Our results show a remarkable similarity in contributions of biomass and fossil combustion, both from the site capturing the highly-populated highly-polluted Indo-Gangetic Plain footprint (IGP; Δ¹⁴C-f_biomass=50±3%) and the second site in the N. Indian Ocean representing a wider South Asian footprint (52±6%). Yet, both sites reflect distinct δ¹³C-fingerprints, indicating a distinguishable contribution of C₄-biomass burning from peninsular India (PI). Tailored-model-predicted season-averaged BC concentrations (700±440 ng m^-3) match observations (740±250 ng m^-3), however, unveiling a systematically increasing model-observation bias (+19% to -53%) through winter. Inclusion of BC from open burning alone does not reconcile predictions (f_biomass=44±8%) with observations. Direct source-segregated comparison reveals regional offsets in anthropogenic emission fluxes in EIs, overestimated fossil-BC in the IGP and underestimated biomass-BC in PI, which contributes to the model-observation bias. This ground-truthing pinpoints uncertainties in BC emission sources, which benefit both climate/air-quality modeling and mitigation policies in South Asia.