Combustion sources of particles: 2. Emission factors and measurement methods

Zhang, Junfeng Jim; Morawska, Lidia

doi:10.1016/s0045-6535(02)00240-0

Cited by 57 publications

(27 citation statements)

References 54 publications

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“…Biomass smoke contains a wide spectrum of potentially health damaging pollutants that include coarse, fine, and ultrafine particles, carbon monoxide (CO), oxide of nitrogen and sulfur, transition metals, polycyclic aromatic hydrocarbons, volatile organic compounds and bio-aerosols http://dx.doi.org/10.1016/j.ijsbe.2014.11.002 2212-6090/Ó 2014 The Gulf Organisation for Research and Development. Production and hosting by Elsevier B.V. Morawska, 2002;Smith et al, 2000). Recent studies (Mondal et al, 2013;Dasgupta et al, 2006) in rural households had shown that indoor air pollution is due to combustion of biomass fuels.…”

Section: Introductionmentioning

confidence: 99%

Indoor pollution from solid biomass fuel and rural health damage: A micro-environmental study in rural area of Burdwan, West Bengal

Chakraborty

Mondal

Datta

2014

International Journal of Sustainable Built Environment

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Emissions from biomass combustion are a major source of indoor and outdoor air pollution, and are estimated to cause millions of premature deaths worldwide annually. In this study, we assessed the effect of exposure to biomass smoke on various health status including blood pressure, gaseous component and ventilation pattern of kitchen and living room. For this investigation, a number of measurements were done to obtain indoor air quality (IAQ) data (indoor humidity, temperature, CO, CO 2 and O 3 concentration). Blood pressure was measured at baseline and one hour post-exposure. Results highlighted that a higher concentration of CO 2 was released during burning of dry leaf, straw, cow dung compared to that from straw and LPG gas. Moreover, correlation study showed a strong negative relationship between CO and humidity (r = À0.609, p < 0.000). Symptoms like eye irritation, shortness of breath, cough and dizziness were highly prevalent among biomass users. Both systolic and diastolic blood pressure showed a strong positive (p < 0.05) relationship with age of biomass users. However, wood users suffer from high systolic pressure (p < 0.037). On the other hand, a very poor ventilation pattern was recorded in the studied population.

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Section: Introductionmentioning

confidence: 99%

Indoor pollution from solid biomass fuel and rural health damage: A micro-environmental study in rural area of Burdwan, West Bengal

Chakraborty

Mondal

Datta

2014

International Journal of Sustainable Built Environment

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“…The quantification of particulate emissions from combustion sources is important for multiple reasons including generation of emission inventories for the development of air management and control strategies, examination of specific sources on compliance with standards, and assessment of personal and environmental exposures (Zhang and Morawska, 2002). Because many of the health and climate effects associated with atmospheric particles are influenced by size, particle emission factors should also be size resolved.…”

Section: Introductionmentioning

confidence: 99%

Size-resolved aerosol emission factors and new particle formation/growth activity occurring in Mexico City during the MILAGRO 2006 Campaign

et al. 2011

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Abstract. Measurements of the aerosol size distribution from 11 nm to 2.5 microns were made in Mexico City in March 2006, during the MILAGRO (Megacity Initiative: Local and Global Research Observations) field campaign. Observations at the urban supersite, referred to as T0, could often be characterized by morning conditions with high particle mass concentrations, low mixing heights, and highly correlated particle number and CO 2 concentrations, indicative that particle number is controlled by primary emissions. Average size-resolved and total number-and volume-based emission factors for combustion sources impacting T0 have been determined using a comparison of peak sizes in particle number and CO 2 concentration. Peaks are determined by subtracting the measured concentration from a calculated baseline concentration time series. The number emission and volume emission factors for particles from 11 nm to 494 nm are 1.56×10 15 particles, and 9.48×10 11 cubic microns per kg of carbon, respectively. The uncertainty of the number emission factor is approximately plus or minus 50 %. The mode of the number emission factor was between 25 and 32 nm, while the mode of the volume factor was between 0.25 and 0.32 microns. These emission factors are reported as log normal model parameters and are compared with multiple emission factors from the literature. In Mexico City in the afternoon, the CO 2 concentration drops during ventilation of the polCorrespondence to: C. O. Stanier (charles-stanier@uiowa.edu) luted layer, and the coupling between CO 2 and particle number breaks down, especially during new particle formation events when particle number is no longer controlled by primary emissions. Using measurements of particle number and CO 2 taken aboard the NASA DC-8, the determined primary emission factor was applied to the Mexico City Metropolitan Area (MCMA) plume to quantify the degree of secondary particle formation in the plume; the primary emission factor accounts for less than 50 % of the total particle number and the surplus particle count is not correlated with photochemical age. Primary particle volume and number in the size range 0.1-2 µm are similarly too low to explain the observed volume distribution. Contrary to the case for number, the apparent secondary volume increases with photochemical age. The size distribution of the apparent increase, with a mode at ∼250 nm, is reported.

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“…The main sources contributing to outdoor air pollution are combustion sources, including vehicle emissions, industrial combustion, biomass burning, and others (Zang and Morawska, 2002). In terms of particle mass concentration, combustion sources predominantly emit material in the PM 2.5 size range, while in terms of particle numbers, most of the emissions are submicrometer and ultrafine particles (Ristovski et al, 1998;CONCAWE, 1998;Morawska et al, 1999).…”

Section: Sourcesmentioning

confidence: 99%

Modeling of Indoor Particle Concentration

Jamriska

2003

Indoor Environment

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Applications and Case Studies320 Fig. 3.8-1 Schematic diagram of the main factors affecting indoor particle concentration · ·Macromodels are based on the material (mass, number) balance equation and the assumption of perfect air mixing. The indoor space is divided into one or several compartments, in which uniformity of a considered parameter (e.g. concentration or particle emission rate) is assumed over the time of interest. The macromodels are characterized in the form of ordinary differential equations, and provide information about the temporal variation of particle concentration levels indoors. No spatial variation data are available, as only the average values are provided for each compartment or zone. Depending on the type, range, and the number of parameters involved (e.g. sinks, sources), the macromodels can differ significantly in their complexity and capabilities.Micromodels are based on the full form of Navier-Stokes equations containing the spatial and time dependency of all indoor environment variables, such as air velocity vectors, temperature, and species concentration. Micromodels may have one, two, or three dimensions depending on the flow problem and application. Advanced numerical methods, such as finite volume and finite element methods, are needed to solve the equations. The micromodels are more complex and require more computational power compared to macromodeling; however, the predictive capability of the model is enhanced.Both modeling approaches are important, and the choice of approach to be followed depends on the application, the information required, issues to be addressed, understanding of the problem, input data, and the computational power availability. A key to choosing the best model for an application is understanding how it addresses various parameters relevant to that application.

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Combustion sources of particles: 2. Emission factors and measurement methods

Cited by 57 publications

References 54 publications

Indoor pollution from solid biomass fuel and rural health damage: A micro-environmental study in rural area of Burdwan, West Bengal

Indoor pollution from solid biomass fuel and rural health damage: A micro-environmental study in rural area of Burdwan, West Bengal

Size-resolved aerosol emission factors and new particle formation/growth activity occurring in Mexico City during the MILAGRO 2006 Campaign

Modeling of Indoor Particle Concentration

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