RESUMEN
A study of a Powder River Basin (PRB) coal pile found that fugitive emissions from natural and human activity each produced similar levels of downwind fine + coarse (i.e., smaller than 10 µm, or PM10) particle mass concentrations. Natural impacts were statistically removed from downwind measurements to estimate emission factor Ev for bulldozers working on the pile. The Ev determined here was similar in magnitude to emission factors (EFs) computed using a U.S. Environmental Protection Agency (EPA) formulation for unpaved surfaces at industrial sites, even though the latter was not based on data for coal piles. EF formulations from this study and those in the EPA guidance yield values of similar magnitude but differ in the variables used to compute Ev variations. EPA studies included effects of surface silt fraction and vehicle weight, while the present study captured the influence of coal moisture. Our data indicate that the relationship between PRB coal fugitive dust Ev (expressed as mass of PM10 emitted per minute of bulldozer operation) and coal moisture content Mc (in percent) at the study site is best expressed as Ev =10(f(Mc())) where f(Mc) is a function of moisture. This function was determined by statistical regression between log10(Ev) and Mc where both Ev and Mc are expressed as daily averages of observations based on 289 hours sampled during 44 days from late June through mid-November of 2012. A methodology is described that estimates Mc based on available meteorological data (precipitation amount and solar radiation flux). An example is given of computed variations in daily Ev for an entire year. This illustrates the sensitivity of the daily average particulate EF to meteorological variability at one location. Finally, a method is suggested for combining the moisture-sensitive formulation for Ev with the EPA formulation to accommodate a larger number of independent variables that influence fugitive emissions.
Asunto(s)
Polvo/análisis , Emisiones de Vehículos/análisis , Carbón Mineral , Minas de Carbón , Modelos Teóricos , Tiempo (Meteorología)RESUMEN
UNLABELLED: Dry fly ash disposal involves dropping ash from a truck and the movement of a heavy grader or similar vehicle across the ash surface. These operations are known to produce fugitive particulate emissions that are not readily quantifiable using standard emission measurement techniques. However there are numerous situations--such as applying for a source air permit--that require these emissions be quantified. Engineers traditionally use emission factors (EFs) derived from measurements of related processes to estimate fly ash disposal emissions. This study near a dry fly ash disposal site using state-of-the-art particulate monitoring equipment examines for the first time fugitive emissions specific to fly ash handling at an active disposal site. The study measured hourly airborne mass concentrations for particles smaller than 2.5 microm (PM2.5) and 10 microm (PM10) along with meteorological conditions and atmospheric turbidity at high temporal resolution to characterize and quantify fugitive fly ash emissions. Fugitive fly ash transport and dispersion were computed using the on-site meteorological data and a regulatory air pollutant dispersion model (AERMOD). Model outputs coupled with ambient measurements yielded fugitive fly ash EFs that averaged 96 g Mg(-1) (of ash processed) for the PM(c) fraction (= PM10 - PM2.5) and 18 g Mg(-1) for PM2.5. Median EFs were much lower due to the strongly skewed shape of the derived EF distributions. Fugitive EFs from nearby unpaved roads were also characterized. Our primary finding is that EFs for dry fly ash disposal are considerably less than EFs derived using US Environmental Protection Agency AP-42 Emissions Handbook formulations for generic aggregate materials. This appears to be due to a large difference (a factor of 10+) between fugitive vehicular EFs estimated using the AP-42 formulation for vehicles driving on industrial roads (in this case, heavy slow-moving grading equipment) and EFs derived by the current study. IMPLICATIONS: Fugitive fly ash emission factors (EFs) derived by this study contribute to the small existing knowledge base for a type of pollutant that will become increasingly important as ambient particulate standards become tighter. In areas that are not in attainment with standards, realistic EFs can be used for compliance modeling and can help identify which classes of sources are best targeted to achieve desired air quality levels. In addition, understanding the natural variability in fugitive fly ash emissions can suggest methods that are most likely to be successful in controlling fugitive emissions related to dry fly ash storage.
Asunto(s)
Contaminantes Atmosféricos/análisis , Ceniza del Carbón/análisis , Monitoreo del Ambiente/métodos , Incineración , Material Particulado/análisis , Contaminación del Aire/prevención & control , Alabama , Monitoreo del Ambiente/normas , Modelos Teóricos , Tamaño de la Partícula , Factores de Tiempo , VientoRESUMEN
The relative roles of natural and anthropogenic sources in determining ozone and fine particle concentrations over the continental United States (U.S.) are investigated using an expanded emissions inventory of natural sources and an updated version of the Community Multiscale Air Quality (CMAQ) model. Various 12-month CMAQ simulations for the year 2002 using different sets of input emissions data are combined to delineate the contributions of background pollutants (i.e., model boundary conditions), natural emissions, anthropogenic emissions, as well as the specific impacts of lightning and wildfires. Results are compared with observations and previous air quality model simulations. Wildfires and lightning are both identified as contributing significantly to ozone levels with lightning NO(x) adding as much as 25-30 ppbV (or up to about 50%) to surface 8-h average natural O(3) mixing ratios in the southeastern U.S. Simulated wildfire emissions added more than 50 ppbV (in some cases >90%) to 8-h natural O(3) at several locations in the west. Modeling also indicates that natural emissions (including biogenic, oceanic, geogenic and fires) contributed ≤ 40% to the annual average of total simulated fine particle mass over the eastern two-thirds of the U.S. and >40% across most of the western U.S. Biogenic emissions are the dominant source of particulate mass over the entire U.S. and wildfire emissions are secondary. Averaged over the entire modeling domain, background and natural ozone are dominant with anthropogenically derived ozone contributing up to a third of the total only during summer. Background contributions to fine particle levels are relatively insignificant in comparison. Model results are also contrasted with the U.S. Environmental Protection Agency (EPA) default values for natural light scattering particle concentrations to be used for regional haze regulatory decision-making. Regional differences in EPA guidance are not supported by the modeling and EPA uncertainty estimates for default values are far smaller than the modeled variability in natural particle concentrations.