Use of stationary and mobile measurements to study power plant emissions

This paper presents a technique to study air pollution by combining high spatial resolution data obtained by a mobile platform and those measured by conventional stationary stations. Conventional stations provide time-series point data but cannot yield information that is distant from the sites. This can be complemented or supplemented by mobile measurements in the vicinity of the conventional sites. Together, the combined dataset yields a clearer and more precise picture of the dispersion and the transformation of pollutants in the atmosphere in a fixed time frame. Several experiments were conducted in the years 2002-2003 to track the impact of power plant plumes on ground receptors in the immediate vicinity (within a radius of 30 km) of the plants, using a combined mobile and stationary dataset. The mobile data allowed the identification of emissions from coal-fired and gas-fired power plants. Coal-fired power plants were the major source of sulfur dioxide (SO2), whereas nitrogen oxides (NOx) emitted from the gas-fired power plant played an important role in the formation of ozone (O3) at ground level. The mobile data showed that two particle size distribution regimes were detected: one had a dominant accumulation mode at 0.40-0.65 microm and the other at 0.65-1 microm. The existence of particles characterized by their mode at 0.65-1 microm and formed by in-cloud processes suggests that vehicular emissions were not the important source. Other local sources, such as power plants (elevated emission), were the likely sources, because Hong Kong does not have much manufacturing industry.     

Validation of a test method for the measurement of methanol emissions from stationary sources

Title III of the 1990 Clean Air Act Amendments designated methanol as a pollutant to be regulated. The U.S. Environmental Protection Agency (EPA), through a contract with Research Triangle Institute, has developed a method for measuring methanol emissions from stationary sources. The methanol sampling train (MST) consists of a glass-lined heated probe, two condensate knockout traps, and three sorbent cartridges packed with Anasorb 747. Samples are desorbed with a 1:1 mixture of carbon disulfide (CS2) and N,N-dimethylformamide (DMF). Condensate water and CS2/ DMF samples are analyzed by gas chromatography with flame ionization detection. The MST has a practical quantitation limit of approximately 3 ppm for a 20-L sample. Samples were shown to be stable for at least two weeks after collection. Field tests of the MST and the National Council of the Paper Industry for Air and Stream Improvement (NCASI) methanol sampling method were conducted at two pulp and paper mills. Sampling and analysis procedures followed EPA Method 301 requirements. The sampling location for the first field test was the inlet vent to a softwood bleach plant scrubber, where the methanol concentration was approximately 30 ppm. The mean recovery of spike was 108.3% for the MST method and 81.6% for the NCASI method. Although neither method showed significant bias at the 95% confidence level, the between-methods bias was significantly different. A second field test was conducted at a vent from a black liquor oxidation tank where the methanol concentration was approximately 350 ppm. Mean spike recoveries were 96.6 and 94.2% for the MST and NCASI methods, respectively. The biases of the two methods and the between-methods bias were not significantly different for the second field test.     

An inexpensive method to estimate CO and NOx emissions from mobile sources

CO and NO_x measurements from mobile sources at two urban locations in Córdoba City, Argentina, were used to develop a very simple method to estimate emission from these sources. This development was possible because primary urban air pollution in Córdoba comes mostly from mobile sources and because a field measurement campaign was conducted by the city government during 1995–1996 that has allowed us to have a complete and valuable data bank. Air concentrations of CO, NO_x as well as physical, and meteorological variables were measured at two urban sites with two monitoring stations. We compared the measured CO and NO_x air concentration data with the predictions of a method that uses regression analysis to estimate the emission factor from the mobile sources. The agreement is good, considering the simplicity of the approach.     

Dilution-based emissions sampling from stationary sources: Part 1--Compact sampler methodology and performance

This paper presents the design and performance of a compact dilution sampler (CDS) for characterizing fine particle emissions from stationary sources. The sampler is described, along with the methodology adopted for its use. Dilution sampling has a number of advantages, including source emissions that are measured under conditions simulating stack gas entry and mixing in the ambient atmosphere. This is particularly important for characterizing the semivolatile species in effluents as a part of particulate emissions. The CDS characteristics and performance are given, along with sampling methodology. The CDS was compared with a reference dilution sampler. The results indicate that the two designs are comparable for tests on gas-fired units and a diesel electrical generator. The performance data indicate that lower detection limits can be achieved relative to current regulatory methods for particulate emissions. Test data for the fine particulate matter (PM2.5) emissions are provided for comparison with U.S. Environment Protection Agency (EPA) Conditional Test Method 040 for filterable particulate matter (FPM) and the EPA Method 202 for condensable particulate matter. This comparison showed important differences between methods, depending on whether a comparison is done between in situ FPM determinations or the sum of such values with condensable PM from liquid filled impingers chilled in an ice bath. These differences are interpretable in the light of semivolatile material present in the stack effluent and, in some cases, differences in detection and quantification limits. Determination of emissions from combustors using liquid fuels can be readily achieved using 1-hr sampling with the CDS. Emissions from gasfired combustors are very low, requiring careful attention to sample volumes. Sampling volumes corresponding with 6-hr operation were used for the combined mass and broad chemical speciation. Particular attention to dilution sampler operation with clean dilution air also is essential for gas-fired sources.     

Dilution-based emissions sampling from stationary sources: Part 2--Gas-fired combustors compared with other fuel-fired systems

With the recent focus on fine particle matter (PM2.5), new, self-consistent data are needed to characterize emissions from combustion sources. Such data are necessary for health assessment and air quality modeling. To address this need, emissions data for gas-fired combustors are presented here, using dilution sampling as the reference. The dilution method allows for collection of emitted particles under conditions simulating cooling and dilution during entry from the stack into the air. The sampling and analysis of the collected particles in the presence of precursor gases, SO2 nitrogen oxide, volatile organic compound, and NH3 is discussed; the results include data from eight gas fired units, including a dual-fuel institutional boiler and a diesel engine powered electricity generator. These data are compared with results in the literature for heavy-duty diesel vehicles and stationary sources using coal or wood as fuels. The results show that the gas-fired combustors have very low PM2.5 mass emission rates in the range of approximately 10(-4) lb/million Btu (MMBTU) compared with the diesel backup generator with particle filter, with approximately 5 x 10(-3) lb/MMBTU. Even higher mass emission rates are found in coal-fired systems, with rates of approximately 0.07 lb/MMBTU for a bag-filter-controlled pilot unit burning eastern bituminous coal. The characterization of PM2.5 chemical composition from the gas-fired units indicates that much of the measured primary particle mass in PM2.5 samples is organic or elemental carbon and, to a much less extent, sulfate. Metal emissions are quite low compared with the diesel engines and the coal- or wood-fueled combustors. The metals found in the gas-fired combustor particles are low in concentration, similar in concentration to ambient particles. The interpretation of the particulate carbon emissions is complicated by the fact that an approximately equal amount of particulate carbon (mainly organic carbon) is found on the particle collector and a backup filter. It is likely that measurement artifacts, mostly adsorption of volatile organic compounds on quartz filters, are positively biasing "true" particulate carbon emission results.     

Correlating emissions with time and temperature to predict worst-case emissions from open liquid area sources

The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry's law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H2S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H2S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85-90 degrees F), the constant emission rate underestimated odor impact significantly (by 73%).     

Atmospheric emissions of mercury from Australian point sources

The UN Global Mercury Assessment (GMA) estimates that atmospheric emissions of mercury from Australian stationary combustion sources were 97.0 tonnes for the year of 1995. This is more than 90% of the estimated emissions from stationary combustion for the whole of North America, and seems abnormally high for a country with a population of around 20 million, in spite of the fact that most of Australia's stationary energy supply is provided by coal. It is also significantly larger than previous estimates of mercury emissions from Australian sources. New estimates of Australian mercury emissions from stationary energy sources, based on both a top down and bottom up approach, are presented. These estimates can be reconciled for black coal fired power stations, but suggest that the bottom up approach (the Australian National Pollutant Inventory) significantly under-estimates emissions from brown coal fired plant, if mercury capture efficiencies in these plants are low, as observed for lignite-fired plant. The major uncertainties in these estimates are the coal mercury content in coals burnt in Australian power stations, and the mercury capture efficiency in particulate control devices used at these stations. Based on these estimates, Australian emissions of mercury from stationary energy are currently 2–8 tonnes/year, significantly lower than the GMA estimate.     

固定源氮氧化物排放及控制技术应用

固定源是氮氧化物排放的一个主要来源。通过对主要固定源氮氧化物生成机理及现有的排放控制技术进行论述，分析我国固定源氮氧化物排放的实际情况，提出我国固定源氮氧化物排放控制还处于起步阶段，氮氧化物排放标准相对宽松，氮氧化物排放控制技术有待进一步普及，并提出固定源氮氧化物排放治理的一些建议。     

固定源氮氧化物排放及控制技术应用

固定源是氮氧化物排放的一个主要来源.通过对主要固定源氮氧化物生成机理及现有的排放控制技术进行论述,分析我国固定源氮氧化物排放的实际情况,提出我国固定源氮氧化物排放控制还处于起步阶段,氮氧化物排放标准相对宽松,氮氧化物排放控制技术有待进一步普及,并提出固定源氮氧化物排放治理的一些建议.     

An inverse Gaussian plume approach for estimating atmospheric pollutant emissions from multiple point sources

A method is developed for estimating the emission rates of contaminants into the atmosphere from multiple point sources using measurements of particulate material deposited at ground level. The approach is based on a Gaussian plume type solution for the advection–diffusion equation with ground-level deposition and given emission sources. This solution to the forward problem is incorporated into an inverse algorithm for estimating the emission rates by means of a linear least squares approach. The results are validated using measured deposition and meteorological data from a large lead–zinc smelting operation in Trail, British Columbia. The algorithm is demonstrated to be robust and capable of generating reasonably accurate estimates of total contaminant emissions over the relatively short distances of interest in this study.     

Identification of stationary sources of air pollutants by concentration statistical analysis

The atmospheric concentrations of benzene, toluene, ethylbenzene and isomeric xylenes (BTEX) in a medium-sized town (S. Maria Capua Vetere, about 32000 inhabitants, Southern Italy) have been determined during working days and weekends in 2006. The procedure used was 24h passive adsorption by samplers distributed throughout the town followed by GC/MS analysis. On a yearly base, the arithmetic mean benzene concentrations were above the limit required by the 2000/69/CE European Directive. The Pearson correlation coefficients of the 24h geometric mean BTEX concentrations were indicative of stationary sources of toluene located in a well circumscribed area of the urban territory, active only during the working days and not officially recognized. The results highlight the effectiveness of the statistical approach used in this study for the identification of pollutant sources.     

An inventory of nitrous oxide emissions from agriculture in the UK using the IPCC methodology: emission estimate,uncertainty and sensitivity analysis

Nitrous oxide emission from UK agriculture was estimated, using the IPCC default values of all emission factors and parameters, to be 87 Gg N₂O–N in both 1990 and 1995. This estimate was shown, however, to have an overall uncertainty of 62%. The largest component of the emission (54%) was from the direct (soil) sector. Two of the three emission factors applied within the soil sector, EF1 (direct emission from soil) and EF3_PRP (emission from pasture range and paddock) were amongst the most influential on the total estimate, producing a ±31 and +11% to −17% change in emissions, respectively, when varied through the IPCC range from the default value. The indirect sector (from leached N and deposited ammonia) contributed 29% of the total emission, and had the largest uncertainty (126%). The factors determining the fraction of N leached (Frac_LEACH) and emissions from it (EF5), were the two most influential. These parameters are poorly specified and there is great potential to improve the emission estimate for this component. Use of mathematical models (NCYCLE and SUNDIAL) to predict Frac_LEACH suggested that the IPCC default value for this parameter may be too high for most situations in the UK.Comparison with other UK-derived inventories suggests that the IPCC methodology may overestimate emission. Although the IPCC approach includes additional components to the other inventories (most notably emission from indirect sources), estimates for the common components (i.e. fertiliser and animals), and emission factors used, are higher than those of other inventories. Whilst it is recognised that the IPCC approach is generalised in order to allow widespread applicability, sufficient data are available to specify at least two of the most influential parameters, i.e. EF1 and Frac_LEACH, more accurately, and so provide an improved estimate of nitrous oxide emissions from UK agriculture.     

Estimating receptor sensitivity to spatial proximity of emissions sources

Spatial proximity of emissions sources to receptors may affect sensitivity to potential adverse human health effects. This research investigates whether receptor sensitivity to the location of emission sources can be utilized efficiently to minimize health risk in selecting sites for industrial enterprises, thermal electric stations, etc. A sensitivity function that is independent of the location of pre-existing emission sources is derived and applied to Minsk, Belarus. The function estimates exposures based on weather and climatic conditions as well as the distribution of population density at a given locality. Arraying prospective sites based on their sensitivity function magnitude provides a technique for minimizing health risk based on receptor sensitivity to the spatial proximity of atmospheric emissions sources.     

Toxic emissions from mobile sources: a total fuel-cycle analysis for conventional and alternative fuel vehicles

Mobile sources are among the largest contributors of four hazardous air pollutants--benzene, 1,3-butadiene, acetaldehyde, and formaldehyde--in urban areas. At the same time, federal and state governments are promoting the use of alternative fuel vehicles as a means to curb local air pollution. As yet, the impact of this movement toward alternative fuels with respect to toxic emissions has not been well studied. The purpose of this paper is to compare toxic emissions from vehicles operating on a variety of fuels, including reformulated gasoline (RFG), natural gas, ethanol, methanol, liquid petroleum gas (LPG), and electricity. This study uses a version of Argonne National Laboratory's Greenhouse Gas, Regulated Emissions, and Energy Use in Transportation (GREET) model, appropriately modified to estimate toxic emissions. The GREET model conducts a total fuel-cycle analysis that calculates emissions from both downstream (e.g., operation of the vehicle) and upstream (e.g., fuel production and distribution) stages of the fuel cycle. We find that almost all of the fuels studied reduce 1,3-butadiene emissions compared with conventional gasoline (CG). However, the use of ethanol in E85 (fuel made with 85% ethanol) or RFG leads to increased acetaldehyde emissions, and the use of methanol, ethanol, and compressed natural gas (CNG) may result in increased formaldehyde emissions. When the modeling results for the four air toxics are considered together with their cancer risk factors, all the fuels and vehicle technologies show air toxic emission reduction benefits.     

Bottom-up uncertainty estimates of global ammonia emissions from global agricultural production systems

Here we present an uncertainty analysis of NH₃ emissions from agricultural production systems based on a global NH₃ emission inventory with a 5×5 min resolution. Of all results the mean is given with a range (10% and 90% percentile). The uncertainty range for the global NH₃ emission from agricultural systems is 27–38 (with a mean of 32) Tg NH₃-N yr⁻¹, N fertilizer use contributing 10–12 (11) Tg yr⁻¹ and livestock production 16–27 (21) Tg yr⁻¹. Most of the emissions from livestock production come from animal houses and storage systems (31–55%); smaller contributions come from the spreading of animal manure (23–38%) and grazing animals (17–37%). This uncertainty analysis allows for identifying and improving those input parameters with a major influence on the results. The most important determinants of the uncertainty related to the global agricultural NH₃ emission comprise four parameters (N excretion rates, NH₃ emission rates for manure in animal houses and storage, the fraction of the time that ruminants graze and the fraction of non-agricultural use of manure) specific to mixed and landless systems, and total animal stocks. Nitrogen excretion rates and NH₃ emission rates from animal houses and storage systems are shown consistently to be the most important parameters in most parts of the world. Input parameters for pastoral systems are less relevant. However, there are clear differences between world regions and individual countries, reflecting the differences in livestock production systems.     

Current and future emissions of selected heavy metals to the atmosphere from anthropogenic sources in Europe

Current atmospheric emissions of As, Cd, Cr, Ni, and Pb (reference year 2000) from major anthropogenic sources in Europe are presented in this paper. Combustion of fuels in stationary sources was the main emission source for As, Cd, Cr, and Ni (more than a half of the total anthropogenic emissions), while combustion of gasoline was the main source of for lead. There is a continuous reduction of heavy metal emissions in Europe during the last 40 years. Better knowledge of heavy metal sources, emissions, pathways, and fate in the environment, and progress in developing efficient emission control equipment has resulted in more efficient regulatory efforts to curb heavy metal emissions from anthropogenic sources very substantially. There is a potential for further reduction of these emissions until the year 2010 up to about 40% for As, Cd, Cr, and Ni and about 57% for Pb, as estimated within various emission scenarios presented in the paper.     

Hazardous air pollutant emissions from gas-fired combustion sources: emissions and the effects of design and fuel type

Air emissions from gas-fired combustion devices such as boilers, process heaters, gas turbines and stationary reciprocating engines contain hazardous air pollutants (HAPs) subjected to consideration under the federal clean air act (CAA). This work presents a recently completed major research project to develop an understanding of HAP emissions from gas-fired boilers and process heaters and new HAP emission factors based on field emission tests of gas-fired external combustion devices used in the petroleum industry. The effect of combustion system design and operating parameters on HAP emissions determined by both field and research tests are discussed. Data from field tests of gas-fired petroleum industry boilers and heaters generally show very low emission levels of organic HAPs. A comparison of the emission data for boilers and process heaters, including units with and without various forms of NOx emission controls, showed no significant difference in organic HAP emission characteristics due to process or burner design. This conclusion is also supported by the results of research tests with different burner designs. Based on field tests of units fired with natural gas and various petroleum industry process gases and research tests in which gas composition was intentionally varied, organic HAP emissions were not determined to be significantly affected by the gas composition. Research data indicate that elevated organic HAP emission levels are found only under extreme operating conditions (starved air or high excess air combustion) associated with poor combustion.