Response of Inorganic PM to Precursor Concentrations

Ansari, Asif S.; Pandis, Spyros Ν.

doi:10.1021/es971130j

Cited by 244 publications

(239 citation statements)

References 13 publications

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“…Adams et al, 1999). Formation of ammonium sulphate and nitrate depends strongly on ambient conditions and availability of ammonia, which is determined by the physical processes like emission rate but also by the degree of sulphate neutralisation (Ansari and Pandis, 1998;Adams et al, 1999). Detailed sensitivity studies concerning these factors have been presented in the literature (e.g.…”

Section: Nh 4 -No 3 -So 4 Equilibriummentioning

confidence: 99%

“…Detailed sensitivity studies concerning these factors have been presented in the literature (e.g. Ansari and Pandis, 1998 and references therein). Here we present the nitrate partitioning, calculated with the Isorropia module (Nenes et al, 1998), as function of the sulphate concentration and ambient conditions.…”

Section: Nh 4 -No 3 -So 4 Equilibriummentioning

confidence: 99%

“…We could not identify a buffering effect of NH 4 on NO 3 , due to a lack of representative and reliable long-term data. However, box model studies on the nitrate partitioning, using measured data as input, do indicate that the SIA levels are sensitive to NO 3 buffering, when the SO 4 levels are decreased (Ansari and Pandis, 1998). We made a first attempt to include feedback mechanisms on the lifetimes of the involved species by using a 3D long-range transport model.…”

Section: Synthesismentioning

confidence: 99%

See 2 more Smart Citations

The need for ammonia abatement with respect to secondary PM reductions in Europe

Erisman

Schaap

2004

Environmental Pollution

212

121

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Section: Nh 4 -No 3 -So 4 Equilibriummentioning

confidence: 99%

Section: Nh 4 -No 3 -So 4 Equilibriummentioning

confidence: 99%

Section: Synthesismentioning

confidence: 99%

See 1 more Smart Citation

The need for ammonia abatement with respect to secondary PM reductions in Europe

Erisman

Schaap

2004

Environmental Pollution

212

121

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“…Airborne PM consists of a mix of organic and inorganic substances, such as sulfates, nitrates, water, trace elements, oxidants and organic compounds with a variety of functional groups and spanning a wide range of vapor pressures and polarities (Ansari and Pandis, 1998;Seinfeld and Pandis, 1998;Turpin et al, 2000). Particles emitted from different sources have different compositions, and their toxicities as well are expected to be distinct.…”

Section: Introductionmentioning

confidence: 99%

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: Analyses of RIOPA data

Meng

Turpin

Korn

et al. 2004

J Expo Sci Environ Epidemiol

247

170

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The Relationship of Indoor, Outdoor and Personal Air (RIOPA) study was designed to investigate residential indoor, outdoor and personal exposures to several classes of air pollutants, including volatile organic compounds, carbonyls and fine particles (PM 2.5 ). Samples were collected from summer, 1999 to spring, 2001 in Houston (TX), Los Angeles (CA) and Elizabeth (NJ). Indoor, outdoor and personal PM 2.5 samples were collected at 212 nonsmoking residences, 162 of which were sampled twice. Some homes were chosen due to close proximity to ambient sources of one or more target analytes, while others were farther from sources. Median indoor, outdoor and personal PM 2.5 mass concentrations for these three sites were 14.4, 15.5 and 31.4 mg/m 3 , respectively. The contributions of ambient (outdoor) and nonambient sources to indoor and personal concentrations were quantified using a single compartment box model with measured air exchange rate and a random component superposition (RCS) statistical model. The median contribution of ambient sources to indoor PM 2.5 concentrations using the mass balance approach was estimated to be 56% for all study homes (63%, 52% and 33% for California, New Jersey and Texas study homes, respectively). Reasonable variations in model assumptions alter median ambient contributions by less than 20%. The mean of the distribution of ambient contributions across study homes agreed well for the mass balance and RCS models, but the distribution was somewhat broader when calculated using the mass balance model with measured air exchange rates.

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“…37 This might be attributed to the colder temperature in winter that enhances the formation of particulate nitrate. 38,39 The soil and dust particles were re-entrained by the ground wind field. The dust contribution in winter was higher than in summer.…”

Section: Cmb Summer 1992mentioning

confidence: 99%

Seasonal Source-Receptor Relationships in a Petrochemical Industrial District over Northern Taiwan

Chiang

Chang

et al. 2005

Journal of the Air & Waste Management Association

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This study investigated the relationships between meteorological data, pollution sources, and receptors over northern Taiwan. During the intensive sampling period in summer 1992, the weather was controlled predominantly by a Pacific subtropical high and by Typhoon Mark. During the other intensive sampling period in winter 1993, while a cold frontal system approached Taiwan, the northeasterly winds prevailed most of the time. The local circulation such as land-sea breeze only developed under weak synoptic environment. Particle concentrations and element composition in winter were higher than in summer. This can be attributed to the high convection of air mass, which leads to the vertical dispersion of pollutants in summer. In addition to the subtropical high pressure, typhoons are frequently accompanied with high-wind speeds and unstable weather conditions that also dilute and eliminate the pollutants. In winter, the prevailing northeasterlies might carry pollutants from Midland China. Furthermore, the anticyclone system develops a stagnant condition that easily leads to pollutant accumulation. In this case, the wind direction affected the source contribution of the receptor and the PM 10 displays a higher correlation with coarse and fine particulate than meteorological parameters in summer. In addition, the mixing height shows a high correlation with PM 10 in winter. INTRODUCTIONCorrelations between air pollution data and meteorological records can provide very useful information for ambient air quality management. Two approaches, that is, dispersion and receptor models, have been used to estimate source contributions to atmospheric aerosols. Dispersion models include the concentration of pollutants from emission rates, meteorological data, physical and chemical transformations, and removal mechanisms. This type of model can be investigated by comparing the predicted spatial and temporal distribution of pollutant concentrations. 1,2 Alternatively, receptor modeling is a best-fit linear combination of emission sources from chemical composition profiles, which can reconstruct the aerosol measured at a receptor location. [3][4][5] Receptor modeling has been used to determine aerosol sources affecting local 6 and regional sites. 7 Source contribution determination from ambient monitoring data, obtained with receptor modeling techniques, relies on the ability to characterize and distinguish differences in the chemical composition of different

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Response of Inorganic PM to Precursor Concentrations

Cited by 244 publications

References 13 publications

The need for ammonia abatement with respect to secondary PM reductions in Europe

The need for ammonia abatement with respect to secondary PM reductions in Europe

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: Analyses of RIOPA data

Seasonal Source-Receptor Relationships in a Petrochemical Industrial District over Northern Taiwan

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