Aerosol characterisation at the FEBUKO upwind station Goldlauter (I): Particle mass,main ionic components,OCEC, and mass closure

This contribution presents characterisation efforts of the gas phase and particle phase main components during the FEBUKO orographic cloud passage experiments in autumn 2001 and 2002 in the Thüringer Wald (Germany). Three events out of a total of 14 were chosen as the best events considering all meteorological conditions. Gas phase and size-segregated particle phase data obtained from physical (dry size distribution) and chemical (particle mass, main ions, OCEC, and water-soluble metals) measurements are presented for the upwind site. The total particulate mass concentration (PM₁₀) was found to be between 8 and 17 μg m⁻³. Particles with an aerodynamic diameter up to 1.2 μm contribute about 80% of the mass concentration. About 90% of the total ion concentration consists of nitrate, sulphate and ammonium. The OC concentration in all three events amounts to about 1.0 μg m⁻³, whereas EC concentrations were between 0.40 and 1.0 μg m⁻³. The contribution of OC and EC to stage mass ranged from 5% to 35% and from 2% to 17%, respectively. The water content of particles was estimated to be 16–18%. Physical and chemical mass closure is discussed in detail and the results are in a reasonable agreement. The complex data set obtained for each event can be used in the initialisation of models for the multiphase processes during and after the cloud passage of the characterised air mass.     

Chemical Dynamics of Clouds at Mt. Mitchell,North Carolina

The role of clouds as the primary pathway for deposition of air pollutants into ecosystems has recently acquired much attention. Moreover, the acidity of clouds is highly variable over short periods of time. Cloud water collections were made at Mt. Mitchell State Park, North Carolina, using a real-time cloud and rain acidity/ conductivity (CRAC) analyzer during May to September 1987, 1988 and 1989 in an effort to explore extremes of chemical exposure. On the average, the mountain peak was exposed to cloud episodes about 70 percent of experimental days. The lowest pH of cloud water in nearly real-time (～10 min.) samples was 2.4, while that in hourly integrated samples was 2.6. The cloud pH during short cloud events (mean pH 3.1), whjch results from the orographic lifting mechanism, was lower than that during long cloud events (mean pH 3.5), which are associated with mesoscale or synoptic atmospheric disturbances. On the average, the pH values in nonprecipitating cloud events were about 0.4 pH unit lower than those in precipitating cloud events. Sulfate, nitrate, ammonium and hydrogen ions were found to be the major constituents of cloud water, and these accounted for -90 percent of the ionic concentration. Total ionic concentrations were found to be much higher in non-precipitating clouds (670-3,010 μeq/L) than those in precipitating clouds (220-370 μeq/L). At low acidity, ionic balance is sometimes not obtained. It is suggested that organic acids may provide this balance.

The profile of cloud water ionic concentration versus time was frequently observed to show decrease at the beginning and rising toward the end during short cloud events. Before the dissipation of clouds, a decrease in cloud water pH and an increase in ionic concentration were found. At the same time, temperature and solar radiation increased, and relative humidity and microphysical parameters (liquid water content, average droplet size, and droplet concentration) decreased. These observations suggest that evaporative dissipation of cloud droplets leads to acidification of cloud water. Mean pH of cloud water was 3.4 when the prevailing wind was from the northwest direction, and it was 3.9 when the wind was from the west direction. The effects of variations in cloud liquid water content have been separated from variations in pre-cloud pollutant concentrations to determine the relationship between source intensity and cloud water concentrations.     

Directional biases in back trajectories caused by model and input data

Back trajectory analyses are often used for source attribution estimates in visibility and other air quality studies. Several models and gridded meteorological datasets are readily available for generation of trajectories. The Big Bend Regional Aerosol and Visibility Observational (BRAVO) tracer study of July to October 1999 provided an opportunity to evaluate trajectory methods and input data against tracer concentrations, particulate data, and other source attribution techniques. Results showed evidence of systematic biases between the results of different back trajectory model and meteorological input data combinations at Big Bend National Park during the BRAVO. Most of the differences were because of the choice of meteorological data used as input to the trajectory models. Different back trajectories also resulted from the choice of trajectory model, primarily because of the different mechanisms used for vertical placement of the trajectories. No single model or single meteorological data set was found to be superior to the others, although rawinsonde data alone are too sparse in this region to be used as the only input data, and some combinations of model and input data could not be used to reproduce known attributions of tracers and simulated sulfate.     

Evaluation of weather conditions for methyl bromide ambient air monitoring in Monterey, Santa Cruz, and Kern Counties in the year 2000

Weather condition is one of the most important factors affecting spatial and temporal distributions of air pollutants, especially for short-term air dispersion. Abnormal weather conditions might lead to higher or lower ambient air concentrations than they would be under normal weather conditions. Therefore, testing for normality of weather conditions during the air monitoring period is an essential step for evaluating ambient air monitoring results. In this paper, a distance method was used to select a most representative weather station from the available candidates. An array of meteorological elements were identified that affect air dispersion and transportation. A statistical method was used to determine whether the weather conditions during the air monitoring period were significantly different from that of previous years. Using methyl bromide ambient air monitoring as a case study, this paper documents the methods, procedures, and results of weather analysis for Monterey, Santa Cruz, and Kern Counties during ambient air monitoring periods for methyl bromide in the year 2000. With a few exceptions, the meteorological elements and atmospheric stability factors, such as wind speeds, wind directions, and stability classes, during the monitoring period were in the normal range. Although there were higher frequencies of stable atmospheric conditions in Monterey/Santa Cruz Counties than in Kern County, weather conditions during the monitoring period were not significantly different from normal local weather conditions of previous years. Consequently, the subchronic air concentrations observed during the ambient air monitoring periods for methyl bromide in the year 2000 was taken under typical weather conditions of those areas at that time of the year.     

The effect of improved nowcasting of precipitation on air quality modeling

The predictive potential of air quality models and thus their value in emergency management and public health support are critically dependent on the quality of their meteorological inputs. The atmospheric flow is the primary cause of the dispersion of airborne substances. The scavenging of pollutants by cloud particles and precipitation is an important sink of atmospheric pollution and subsequently determines the spatial distribution of the deposition of pollutants. The long-standing problem of the spin-up of clouds and precipitation in numerical weather prediction models limits the accuracy of the prediction of short-range dispersion and deposition from local sources. The resulting errors in the atmospheric concentration of pollutants also affect the initial conditions for the calculation of the long-range transport of these pollutants. Customary the spin-up problem is avoided by only using NWP (Numerical Weather Prediction) forecasts with a lead time greater than the spin-up time of the model. Due to the increase of uncertainty with forecast range this reduces the quality of the associated forecasts of the atmospheric flow.In this article recent improvements through diabatic initialization in the spin-up of large-scale precipitation in the Hirlam NWP model are discussed. In a synthetic example using a puff dispersion model the effect is demonstrated of these improvements on the deposition and dispersion of pollutants with a high scavenging coefficient, such as sulphur, and a low scavenging coefficient, such as cesium-137. The analysis presented in this article leads to the conclusion that, at least for situations where large-scale precipitation dominates, the improved model has a limited spin-up so that its full forecast range can be used. The implication for dispersion modeling is that the improved model is particularly useful for short-range forecasts and the calculation of local deposition. The sensitivity of the hydrological processes to proper initialization implies that the spin-up problem may reoccur with changes in the model and increased model resolution. Spin-up should be an ongoing concern for atmospheric modelers.     

Chemical climatology of high elevation spruce-fir forests in the southern Appalachian mountains

The physical and chemical climatology of high elevation (> 1500 m) spruce-fir forests in the southern Appalachian mountains was studied by establishing a weather and atmospheric chemical observatory at Mt Mitchell State Park in North Carolina (35 degrees 44' 05" N, 82 degrees 17' 15"W). Data collected during the summer and autumn (May-October) of 1986, 1987, and 1988 are reported. All measurements were made on or near a 16.5 m walk-up tower extending 10 m above the forest canopy on Mt Gibbes (2006 m msl), which is located approximately 2 km SW of Mt Mitchell. The tower was equipped with standard meteorological instrumentation, a passive cloud water collector, and gas pollutant sensors for O3, SO2, NOx. The tower and nearby forest canopy were immersed in clouds 25 to 40% of the time. Non-precipitating clouds were very acidic (pH 2.5-4.5). Precipitating clouds were less acidic (pH 3.5-5.5). The dominant wind directions were WNW and ESE. Clouds from the most common wind direction (WNW) were more acidic (mean pH 3.5) than those from the next most common wind direction (ESE, mean pH 5.5). Cloud water acidity was related to the concentration of SO4(2-), and NO3- ions. Mean concentration of H+, NH4+, SO4(2-), and NO3- ions in the cloud water varied from 330-340, 150-200, 190-200 and 120-140 micromol litre(-1) respectively. The average and range of O3 were 50 (25-100) ppbv (109) in 1986, 51 (26-102) ppbv in 1987, and 66 (30-140) during the 1988 field seasons, respectively. The daily maximum, 1-h average, and 24-h average concentrations were all greatest during June through mid-August, suggesting a correlation with the seasonal temperature and solar intensity. Throughfall collectors near the tower were used to obtain a useful estimate of deposition to the forest canopy. Between 50-60% of the total deposition of SO4(2-) was due to cloud impact.     

Seasonal source-receptor relationships in a petrochemical industrial district over northern Taiwan

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 PM10 displays a higher correlation with coarse and fine particulate than meteorological parameters in summer. In addition, the mixing height shows a high correlation with PM10 in winter.     

Arctic haze and clouds observed by lidar during four winter seasons of 1993–1997, at Eureka,Canada

A Mie-scattering-polarized Haze Lidar was installed at Eureka, Canada (80°N, 86°W), in February 1993 and has been used to observe the arctic haze during winter seasons from 1993–94 to 1996–97. Although it is difficult to distinguish between the arctic haze and other scattering objects (mainly clouds) under the specific conditions, two methods were used to classify those objects into two groups. First the vertical profiles of the arctic haze and clouds were compared with meteorological data observed by a radiosonde, and the relations between the scattering and depolarization ratios and the meteorological data were investigated. Then, since the arctic haze had very stable layers, the time dependency of the correlation coefficient between the different vertical profiles for the arctic haze and clouds was investigated. After the scattering objects were classified into two groups (the arctic haze and the clouds), the scattering ratio, the depolarization ratio, and the occurrence probabilities of them were investigated statistically. The statistical results, from the observations over the last four winter seasons, indicate that the average values of the scattering and depolarization ratios of the arctic haze were respectively 1.27 and 1.34%. The average humidity over ice of the layer containing the arctic haze was 42±19% (cloud: 92±13%). The arctic haze was observed at altitudes less than 3 km frequently and at altitudes of 3–5 km occasionally.     

Assessing the meteorological conditions of a deep Italian Alpine valley system by means of a measuring campaign and simulations with two models during a summer smog episode

The typical features of a summer smog episode in the highly complex terrain of the Province of Bolzano (Northern Italy) were investigated by numerical modelling with two non-hydrostatic models, ground-based monitoring stations, and vertical profiling with two sodars and an ultra-light aircraft. High ozone concentrations are most likely to appear in situations where the local circulation in the valleys is decoupled from the synoptic flow above during anticyclonic weather regimes. Both models (MM5 and TVM) produced similar results and were able to simulate the local winds in the valleys. A comparison of the measured data to the model simulation results made an evaluation of the performance of the two models in such complex terrain possible. Both models proved to be suitable for the simulation of the meteorological conditions during such summer smog episodes in complex terrain.     

Vertical distributions of aerosols under different weather conditions: Analysis of in-situ aircraft measurements in Beijing,China

In this study, aerosol vertical distributions of 17 in-situ aircraft measurements during 2005 and 2006 springs are analyzed. The 17 flights are carefully selected to exclude dust events, and the analyses are focused on the vertical distributions of aerosol particles associated with anthropogenic activities. The results show that the vertical distributions of aerosol particles are strongly affected by weather and meteorological conditions, and 3 different types of aerosol vertical distributions corresponding to different weather systems are defined in this study. The measurement with a flat vertical gradient and low surface aerosol concentrations is defined as type-1; a gradual decrease of aerosols with altitudes and modest surface aerosol concentrations is defined as type-2; a sharp vertical gradient (aerosols being strongly depressed in the PBL) with high surface aerosol concentrations is defined as type-3. The weather conditions corresponding to the 3 different aerosol types are high pressure, between two high pressures, and low pressure systems (frontal inversions), respectively. The vertical mixing and horizontal transport for the 3 different vertical distributions are analyzed. Under the type-1 condition, the vertical mixing and horizontal transport were rapid, leading to strong dilution of aerosols in both vertical and horizontal directions. As a result, the aerosol concentrations in PBL (planetary boundary layer) were very low, and the vertical distribution was flat. Under the type-2 condition, the vertical mixing was strong and there was no strong barrier at the PBL height. The horizontal transport (wind flux) was modest. As a result, the aerosol concentrations were gradually reduced with altitude, with modest surface aerosol concentrations. Under the type-3 condition, there was a cold front near the region. As a result, a frontal inversion associated with weak vertical mixing appeared at the top of the inversion layer, forming a very strong barrier to prevent aerosol particles being exchanged from the PBL height to the free troposphere. As a result, the aerosol particles were strongly depressed in the PBL height, producing high surface aerosol concentrations. The measured vertical aerosol distributions have important implications for studying the effects of aerosols on photochemistry. The J[O₃] values are reduced by 11%, 48%, and 50%, under the type-1, type-2, and type-3 conditions, respectively. This result reveals that atmospheric oxidant capacity (OH concentrations) is modestly reduced under the type-1 condition, but is significantly reduced under the type-2 and type-3 conditions. This result also suggests that the effect of aerosol particles on surface solar flux is an integrated column effect, and detailed vertical distributions of aerosol particles are very important for assessing the impacts of aerosol on photochemistry.     

A model of sulphate production in a cap cloud and subsequent turbulent deposition onto the hill surface

A model has been constructed of the dynamics and microphysics of a hill cap cloud. This has been used to investigate the aqueous phase oxidation of SO₂ in the cloud droplets and the subsequent turbulent deposition of chemical species onto the hill surface. It is suggested that the dominant oxidant is H₂O₂ in these clouds and that therefore the process is likely to be oxidant limited. The amount of sulphate produced is comparable to that found in cloud condensation nuclei typically found over the U.K. and elsewhere away from strong local sources of sulphate aerosol. Ammonia concentrations are very important as they alter the cloud water pH and hence the solubility of SO₂.Turbulent or ‘occult’ deposition is very sensitive to wind speed, the stability profile of the atmosphere and to the surface roughness. In a supercritical flow regime the occult deposition is a maximum just on the lee of the hill.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

The Transport of Suspended Particulates as a Function of Wind Direction and Atmospheric Conditions

Linear regression of high volume air sampler data and various meteorological parameters was used to determine a suspended particulate air pollution climatology for Albany, NY. A new method for exhibiting associations between wind direction and pollutant levels using correlation coefficients is presented. Correlations between wind direction distribution frequency and other meteorological parameters is employed to help explain differences in correlations for direction with suspended particulate levels. Results show that high particulate concentrations correlate well with southerly wind flow throughout the study area, regardless of relative location of receptor to local sources. This suggests that ambient background concentrations inherent in different air masses more consistently affected suspended particulate levels than did the diffusion from local sources during the study period. Maximum particulate advection occurs under conditions of good mixing of the boundary layer and moderate wind speeds and is enhanced further in the absence of removal processes such as rainout and washout. Trajectory analysis of selected days indicates a definite relationship between path and origin of the wind flow and regional average particulate concentration.     

Dynamics of cyanobacterial bloom formation during short-term hydrodynamic fluctuation in a large shallow, eutrophic, and wind-exposed Lake Taihu, China

Short-term hydrodynamic fluctuations caused by extreme weather events are expected to increase worldwide because of global climate change, and such fluctuations can strongly influence cyanobacterial blooms. In this study, the cyanobacterial bloom disappearance and reappearance in Lake Taihu, China, in response to short-term hydrodynamic fluctuations, was investigated by field sampling, long-term ecological records, high-frequency sensors and MODIS satellite images. The horizontal drift caused by the dominant easterly wind during the phytoplankton growth season was mainly responsible for cyanobacterial biomass accumulation in the western and northern regions of the lake and subsequent bloom formation over relatively long time scales. The cyanobacterial bloom changed slowly under calm or gentle wind conditions. In contrast, the short-term bloom events within a day were mainly caused by entrainment and disentrainment of cyanobacterial colonies by wind-induced hydrodynamics. Observation of a westerly event in Lake Taihu revealed that when the 30 min mean wind speed (flow speed) exceeded the threshold value of 6 m/s (5.7 cm/s), cyanobacteria in colonies were entrained by the wind-induced hydrodynamics. Subsequently, the vertical migration of cyanobacterial colonies was controlled by hydrodynamics, resulting in thorough mixing of algal biomass throughout the water depth and the eventual disappearance of surface blooms. Moreover, the intense mixing can also increase the chance for forming larger and more cyanobacterial colonies, namely, aggregation. Subsequently, when the hydrodynamics became weak, the cyanobacterial colonies continuously float upward without effective buoyancy regulation, and cause cyanobacterial bloom explosive expansion after the westerly. Furthermore, the results of this study indicate that the strong wind happening frequently during April and October can be an important cause of the formation and expansion of cyanobacterial blooms in Lake Taihu.     

A model of wet deposition to complex terrain

A two dimensional model of the seeder-feeder mechanism of orographic rainfall enhancement has been developed. The model has been extended to include the deposition of aerosol material incorporated into the orographic feeder cloud by nucleation scavenging. Parameterizations of any changes in the concentration of SO₄²⁻ in the cloud due to chemical reactions have also been included. The model is used to predict the rainfall enhancement and SO₄²⁻ deposition over terrain consisting of two parallel ridges oriented perpendicular to the wind. A wide range of spatial scales has been used of up to 150 km. It is found that the patterns of rainfall enhancement and deposition are strongly dependent on the spatial scales, the atmospheric structure and the cloud chemistry.     

Evaluation of the Meteo-France response in ETEX release 1

During ETEX Meteo-France applied part of its emergency response system for critical events developped in the framework of the World Meteorological Organization environmental emergency response program. The atmospheric transport model used to forecast the evolution of a passive tracer is an eulerian model called MEDIA. In real time this model is driven by meteorological data from ARPEGE, the operational numerical weather prediction model available at the Meteo-France operation center. The overall evaluation of the results show that the model can reproduce the cloud displacement, but there exists a stretching in the transport direction. In the ATMES-II phase, the results are closer to the observations when meteorological data from the European Center for Medium range Weather Forecast are used. A simulation using analyzed meteorological data from ARPEGE every 6 h slightly improve the results comparing with the real-time experiment. All the simulations we performed reveal that the quality of the atmospheric transport model is strongly dependent on the quality of the driving numerical weather prediction model.     

A model study of smoke-haze influence on clouds and warm precipitation formation in Indonesia 1997/1998

In the last few decades, fire and smoke-haze occurrence increased in Indonesia by intentionally set land clearing fires and higher fire susceptibility of disturbed forests. Particularly, during El Niño years with prolonged droughts in Indonesia, land clearing fires become uncontrolled wildfires and produce large amounts of gaseous and particulate emissions. This paper investigates the influence of smoke-haze aerosols from such fires on clouds and precipitation over Indonesia during the El Niño event 1997/1998 by numerical modelling. Warm precipitation formation in both layered and convective clouds is calculated dependent on the atmospheric aerosol concentration. In the smoke-haze affected regions of Indonesia, aerosol–cloud interactions induce events with both precipitation suppression and increase compared to a reference simulation without aerosol–cloud interactions. The effect of precipitation suppression is found to dominate with about 2/3 of all precipitation modification events pointing to a prolongation of smoke-haze episodes. The corresponding convective cloud top height of shallow clouds is increased whereas distinct lower deep convective cloud top heights are found. The remaining about 1/3 events are characterised by increased precipitation and cloud liquid water content, accompanied by lower convective cloud top heights of shallow clouds and higher deep convective clouds.     

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

Abstract

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 PM₁₀ displays a higher correlation with coarse and fine particulate than meteorological parameters in summer. In addition, the mixing height shows a high correlation with PM₁₀ in winter.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.