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Mexico City aerosol analysis during MILAGRO using high resolution aerosol mass spectrometry at the urban supersite (T0) – Part 1: Fine particle composition and organic source apportionment

TLDR
In this article, an analysis of high resolution OA spectra was performed at the T0 urban supersite in Mexico City with a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and complementary instrumentation.
Abstract
. Submicron aerosol was analyzed during the MILAGRO field campaign in March 2006 at the T0 urban supersite in Mexico City with a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and complementary instrumentation. Mass concentrations, diurnal cycles, and size distributions of inorganic and organic species are similar to results from the CENICA supersite in April 2003 with organic aerosol (OA) comprising about half of the fine PM mass. Positive Matrix Factorization (PMF) analysis of the high resolution OA spectra identified three major components: chemically-reduced urban primary emissions (hydrocarbon-like OA, HOA), oxygenated OA (OOA, mostly secondary OA or SOA), and biomass burning OA (BBOA) that correlates with levoglucosan and acetonitrile. BBOA includes several very large plumes from regional fires and likely also some refuse burning. A fourth OA component is a small local nitrogen-containing reduced OA component (LOA) which accounts for 9% of the OA mass but one third of the organic nitrogen, likely as amines. OOA accounts for almost half of the OA on average, consistent with previous observations. OA apportionment results from PMF-AMS are compared to the PM2.5 chemical mass balance of organic molecular markers (CMB-OMM, from GC/MS analysis of filters). Results from both methods are overall consistent. Both assign the major components of OA to primary urban, biomass burning/woodsmoke, and secondary sources at similar magnitudes. The 2006 Mexico City emissions inventory underestimates the urban primary PM2.5 emissions by a factor of ~4, and it is ~16 times lower than afternoon concentrations when secondary species are included. Additionally, the forest fire contribution is at least an order-of-magnitude larger than in the inventory.

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Journal ArticleDOI

Elucidating severe urban haze formation in China

TL;DR: A periodic cycle of PM episodes in Beijing is demonstrated that is governed by meteorological conditions and characterized by two distinct aerosol formation processes of nucleation and growth, but with a small contribution from primary emissions and regional transport of particles.
Journal ArticleDOI

Interpretation of organic components from Positive Matrix Factorization of aerosol mass spectrometric data

TL;DR: In this paper, positive matrix factorization (PMF) was used to identify and interpret the organic aerosol (OA) data from an Aerodyne Aerosol Mass Spectrometer (Q-AMS) collected at the Pittsburgh Air Quality Study (PAQS) in September 2002.

Secondary Organic Aerosol Formation from Anthropogenic Air Pollution: Rapid and Higher than Expected

TL;DR: This paper showed that reactive anthropogenic VOCs (AVOCs) produce much larger amounts of SOA than these models predict, even shortly after sunrise, and a significant fraction of the excess SOA is formed from first-generation AVOC oxidation products.
Journal ArticleDOI

Formation of Urban Fine Particulate Matter

TL;DR: Air pollutants consist of a complex combination of gases and particulate matter, which is emitted directly into the atmosphere or formed in the atmosphere through gas-to-particle conversion (secondary) (Figure 1).
References
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Climate change 2007: the physical science basis

TL;DR: The first volume of the IPCC's Fourth Assessment Report as mentioned in this paper was published in 2007 and covers several topics including the extensive range of observations now available for the atmosphere and surface, changes in sea level, assesses the paleoclimatic perspective, climate change causes both natural and anthropogenic, and climate models for projections of global climate.
Journal ArticleDOI

Health effects of fine particulate air pollution: lines that connect

TL;DR: A comprehensive evaluation of the research findings provides persuasive evidence that exposure to fine particulate air pollution has adverse effects on cardiopulmonary health.
Journal ArticleDOI

Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values†

TL;DR: In this paper, a new variant of Factor Analysis (PMF) is described, where the problem is solved in the weighted least squares sense: G and F are determined so that the Frobenius norm of E divided (element-by-element) by σ is minimized.
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