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Abstract. The atmosphere over the equatorial Indian Ocean is a unique environment in which to study the chemical and radiative effects of an intense source of anthropogenic emissions from the northern hemisphere directly coupled to the relatively pristine background conditions present in the southern hemisphere. As an initial investigation into the role of the intertropical convergence zone (ITCZ) on interhemispheric transport of pollutants, a number of trace atmospheric species were measured aboard the National Oceanic and Atmospheric Administration (NOAA) R/V Malcolm Baldrige between Durban, South Africa, and Colombo, Sri Lanka, from March 12 to April 22, 1995. Sharp increases in the concentrations of carbon monoxide (CO), carbon dioxide (CO2), and aerosols were associated with four distinct meteorological regimes transected by the cruise track from 33øS to 9øN. Across the ITCZ, aerosol concentrations, including non-sea-salt sulfate, nitrate and ammonium, increased by a factor of 4. Surface ozone measurements showed a latitudinal gradient with a minimum near the equator and a strong diurnal variation in the equatorial regions. The latitudinal profile of gas-phase reactive nitrogen paralleled ozone and was higher in the remote southern hemisphere than in the remote northern hemisphere. Evidence of direct anthropogenic impact on the region was observed more than 1500 km from the southern tip of India. Back trajectories, calculated with NOAA's medium range forecast data using the Hybrid SingleParticle Lagrangian Integrated Trajectory (HY-SPLIT) program, identified the origin of the air mass regimes characterized by the trace gas and aerosol data. Continental emissions in the northern hemisphere were shown to have a major impact on the radiative properties and oxidizing capacity of the marine atmosphere.

During the Particulate Matter Technology Assessment and Characterization Study–New York (PMTACS‐NY) in January/February 2004 a variety of modern aerosol measurement instruments were deployed at a field site on the campus of Queens College in Queens, New York. These instruments included the Aerodyne Aerosol Mass Spectrometer (Q‐AMS), R&P Particulate Ambient Sulfate and Nitrate monitors (8400S&N), a Particle‐into‐liquid Sampler equipped with ion chromatographs (PILS‐IC), an R&P FDMS TEOM, and several other techniques to measure physical aerosol properties. The PMTACS‐NY 2004 winter campaign was designed to replicate measurements performed at this site during the PMTACS‐NY 2001 summer campaign. The field campaign experienced significant meteorological variability and extreme weather conditions, which together with local and regional aerosol and precursor emissions generated a wide range of PM concentrations at the site, with significant changes in physical aerosol properties as well as aerosol composition as a function of particle size. Q‐AMS quantification procedures and intercomparison studies of nonrefractory species mass concentrations measured with the Q‐AMS and other colocated instruments (PILS‐IC, R&P 8400 S/N, FDMS TEOM, and Sunset Labs OC Analyzer) are presented. The size‐resolved aerosol composition over the measurement period and its variation with time of the day, regional meteorology and local source impacts are discussed. Results obtained during this field campaign are compared to data from the PMTACS‐NY 2001 summer campaign, where aerosol composition was observed to have higher sulfate, significantly lower nitrate content and overall mean aerosol mass size distributions with larger mode diameters.

Single-particle mass spectrometers are now commonly used to analyze atmospheric particles and generate tens of thousands of spectra from typical measurement campaigns. The ART-2a spectrum algorithm has been used to classify these spectra. In this work, we generate a range of particles that are models of those that are common in the atmosphere. A single-particle mass spectrometer is used to analyze these known particles, and the spectra are classified using ART-2a. The optimum vigilance parameter is approximately 0.5 while the optimum learning rate is approximately 0.05. The classifications elucidate limitations in generation of test particles, their analysis by single-particle techniques, and their classification by ART-2a.