Emission factors of fine particulate matter, organic and elemental carbon, carbon monoxide, and carbon dioxide for four solid fuels commonly used in residential heating by the U.S. Navajo Nation

To assist interpretation of a study in rural Pakistan on the use of biomass for cooking and the risk of coronary heart disease, we continuously monitored airborne concentrations of fine particulate matter (PM2.5) and carbon monoxide (CO) for up to 48 h in the kitchens of households randomly selected from the parent study. Satisfactory data on PM2.5 and CO respectively were obtained for 16 and 17 households using biomass, and 19 and 17 using natural gas. Linear regression analysis indicated that in comparison with kitchens using natural gas, daily average PM2.5 concentrations were substantially higher in kitchens that used biomass in either a chimney stove (mean difference 611, 95% CI: 359, 863 µg/m3) or traditional three-stone stove (mean difference 389, 95% CI: 231, 548 µg/m3). Daily average concentrations of CO were significantly increased when biomass was used in a traditional stove (mean difference from natural gas 3.7, 95% CI: 0.8, 6.7 ppm), but not when it was used in a chimney stove (mean difference −0.8, 95% CI: −4.8, 3.2 ppm). Any impact of smoking by household members was smaller than that of using biomass, and not clearly discernible. In the population studied, cooking with biomass as compared with natural gas should serve as a good proxy for higher personal exposure to PM2.5.

Download Full-text

Associations between personal exposures and fixed-site ambient measurements of fine particulate matter, nitrogen dioxide, and carbon monoxide in Toronto, Canada

Journal of Exposure Science & Environmental Epidemiology ◽

10.1038/sj.jea.7500446 ◽

2005 ◽

Vol 16 (2) ◽

pp. 172-183 ◽

Cited By ~ 45

Author(s):

David Kim ◽

Andrea Sass-Kortsak ◽

James T Purdham ◽

Robert E Dales ◽

Jeffrey R Brook

Keyword(s):

Carbon Monoxide ◽

Particulate Matter ◽

Nitrogen Dioxide ◽

Fine Particulate Matter ◽

Fine Particulate ◽

Personal Exposures ◽

Ambient Measurements

Download Full-text

Use of a process analysis tool for diagnostic study on fine particulate matter predictions in the U.S. – Part I: Model evaluation

Atmospheric Pollution Research ◽

10.5094/apr.2011.007 ◽

2011 ◽

Vol 2 (1) ◽

pp. 49-60 ◽

Cited By ~ 6

Author(s):

Ping Liu ◽

Yang Zhang

Keyword(s):

Particulate Matter ◽

Model Evaluation ◽

Process Analysis ◽

Fine Particulate Matter ◽

Diagnostic Study ◽

Analysis Tool ◽

Fine Particulate ◽

The U.S

Download Full-text

Fine Particulate Matter Pollution Characteristics and Source Apportionment of Changchun Atmosphere

10.21203/rs.3.rs-431378/v1 ◽

2021 ◽

Author(s):

Jie Tang ◽

Zhuo Yang ◽

Yue Tui ◽

Ju Wang

Keyword(s):

Particulate Matter ◽

Mass Concentration ◽

Elemental Carbon ◽

Motor Vehicle ◽

Fine Particulate Matter ◽

Water Soluble ◽

Chemical Components ◽

Sample Collection ◽

Pollution Characteristics ◽

Fine Particulate

Abstract In order to study the pollution characteristics and main sources of fine particulate matter in the atmosphere of the city of Changchun, PM2.5 samples were collected during the four seasons in 2014, and representative months for each season are January, April, July, and October. Sample collection was carried out on 10 auto-monitoring stations in Changchun, and PM2.5 mass concentration, and its chemical components (including inorganic elements, organic carbon, elemental carbon, and water-soluble ions) were measured. The results show that the annual average mass concentration of PM2.5 in Changchun in 2014 was about 66.77 µg/m3. Organic matter was the highest component in PM2.5, followed by secondary inorganic ions (SNA), mineral dust (MIN), elemental carbon (EC), and trace elements (TE). Positive Matrix Factorization (PMF) results gave seven factors, namely, industrial, biomass- and coal-burning, industrial and soil dust, motor-vehicle, soil and secondary-ion, light-industrial, and hybrid-automotive and -industrial sources in PM2.5, with contributing values of 18.9%, 24.2%, 5.7%, 23.0%, 11.5%, 13.0%, and 3.6%, respectively.

Download Full-text