Secondary formation of organic aerosol in the Los Angeles basin: A descriptive analysis of organic and elemental carbon concentrations

Turpin, B. J.; Huntzicker, James J.

doi:10.1016/0960-1686(91)90291-e

Cited by 333 publications

(205 citation statements)

References 25 publications

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“…The above results are consistent with the theory that aerosol yield in a given ozone/terpene system is not constant but varies with the existing particle surface area/unit volume. The greater the existing surface area of airborne particles, the greater the yield (48).…”

Section: Resultsmentioning

confidence: 99%

Ozone and limonene in indoor air: a source of submicron particle exposure.

Wainman

Zhang

Weschler

et al. 2000

Environ Health Perspect

229

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Little information currently exists regarding the occurrence of secondary organic aerosol formation in indoor air. Smog chamber studies have demonstrated that high aerosol yields result from the reaction of ozone with terpenes, both of which commonly occur in indoor air. However, smog chambers are typically static systems, whereas indoor environments are dynamic. We conducted a series of experiments to investigate the potential for secondary aerosol in indoor air as a result of the reaction of ozone with d-limonene, a compound commonly used in air fresheners. A dynamic chamber design was used in which a smaller chamber was nested inside a larger one, with air exchange occurring between the two. The inner chamber was used to represent a model indoor environment and was operated at an air exchange rate below 1 exchange/hr, while the outer chamber was operated at a high air exchange rate of approximately 45 exchanges/hr. Limonene was introduced into the inner chamber either by the evaporation of reagent-grade d-limonene or by inserting a lemon-scented, solid air freshener. A series of ozone injections were made into the inner chamber during the course of each experiment, and an optical particle counter was used to measure the particle concentration. Measurable particle formation and growth occurred almost exclusively in the 0.1-0.2 microm and 0.2-0.3 microm size fractions in all of the experiments. Particle formation in the 0.1-0.2 microm size range occurred as soon as ozone was introduced, but the formation of particles in the 0.2-0.3 microm size range did not occur until at least the second ozone injection occurred. The results of this study show a clear potential for significant particle concentrations to be produced in indoor environments as a result of secondary particle formation via the ozone-limonene reaction. Because people spend the majority of their time indoors, secondary particles formed in indoor environments may make a significant contribution to overall particle exposure. This study provides data for assessing the impact of outdoor ozone on indoor particles. This is important to determine the efficacy of the mass-based particulate matter standards in protecting public health because the indoor secondary particles can vary coincidently with the variations of outdoor fine particles in summer.

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Section: Resultsmentioning

confidence: 99%

Ozone and limonene in indoor air: a source of submicron particle exposure.

Wainman

Zhang

Weschler

et al. 2000

Environ Health Perspect

229

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“…106 In some studies, (OC/EC) pri was determined from the regression slope of the lowest 5-10% of OC and EC concentrations. 107,108 This approach may be appropriate for large datasets in which SOA concentrations are nearly zero in some of the samples. Russell and Allen 106 used independent criteria to select samples to derive a representative (OC/EC) pri ratio for the Houston area.…”

Section: Quantification Of Soamentioning

confidence: 99%

Source Apportionment: Findings from the U.S. Supersites Program

Watson

Chen

Chow

et al. 2008

Journal of the Air & Waste Management Association

220

132

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Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software. In their more general form, the CMB equations allow spatial, temporal, transport, and particle size profiles to be combined with chemical source profiles for improved source resolution. Although UNMIX and PMF do not use source profiles explicitly as input data, they still require measured profiles to justify their derived source factors. The U.S. Supersites Program provided advanced datasets to apply these CMB solutions in different urban areas. Still lacking are better characterization of source emissions, new methods to estimate profile changes between source and receptor, and systematic sensitivity tests of deviations from receptor model assumptions. INTRODUCTIONReceptor-oriented source apportionment models infer source contributions and atmospheric processes from air quality measurements. Receptor models complement, rather than replace, source-oriented dispersion and chemical transformation models that begin with source emission rates to estimate ambient concentrations. 1,2 Source and receptor models are mathematical representations of reality, requiring simplifying assumptions that create uncertainty. Applying both types of models to the same situation allows them to be improved when their results diverge and lends confidence to their results when they agree. 3

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“…Good OC and EC correlations were observed for all four seasons (r N 0.84), suggesting that OC and EC might have similar sources and their relationship could be used for the estimation of secondary organic formation. As EC is resistant to chemical reactions, it is a good indicator of primary anthropogenic pollutants and it has often been used as a tracer of primary OC (Turpin and Huntzicker, 1991). OC/EC ratios exceeding 2.0 have been used to identify secondary organic aerosol formation .…”

Section: Soc Estimation and Correlation Of Wsoc And Socmentioning

confidence: 99%