An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 3. Vegetation Injury

Acute leaf injury data are analyzed for 19 plant species exposed to ozone or sulfur dioxide. The data can be depicted by a new leaf injury mathematical model with two characteristics: (1) a constant percentage of leaf surface is injured by an air pollutant concentration that is inversely proportional to exposure duration raised to an exponent; (2) for a given exposure duration, the percent leaf injury as a function of pollutant concentration tends to fit a lognormal frequency distribution. Leaf injury as a function of laboratory exposure duration is modeled and compared with ambient air pollutant concentration measurements for various averaging times to determine which exposure durations are probably most important for setting ambient air quality standards to prevent or reduce visible leaf injury. The 8 hour average appears to be most important for most of the plants investigated for most sites, 1 hr concentrations are important for most plants at a few sites, and 3 hr S0₂ concentrations are important for some plants, especially those exposed to isolated point sources of the pollutant. The 1, 3, and 8 hr threshold injury concentrations are listed for each of the 19 plant species studied. To prevent or reduce acute leaf injury, fixed, nonoverlapping ambient air quality measurements and standards are recommended for averaging times of 1, 3, and 8hr.     

A methodology to urban air quality assessment during large time periods of winter using computational fluid dynamic models

The representativeness of point measurements in urban areas is limited due to the strong heterogeneity of the atmospheric flows in cities. To get information on air quality in the gaps between measurement points, and have a 3D field of pollutant concentration, Computational Fluid Dynamic (CFD) models can be used. However, unsteady simulations during time periods of the order of months, often required for regulatory purposes, are not possible for computational reasons. The main objective of this study is to develop a methodology to evaluate the air quality in a real urban area during large time periods by means of steady CFD simulations. One steady simulation for each inlet wind direction was performed and factors like the number of cars inside each street, the length of streets and the wind speed and direction were taken into account to compute the pollutant concentration. This approach is only valid in winter time when the pollutant concentrations are less affected by atmospheric chemistry. A model based on the steady-state Reynolds-Averaged Navier–Stokes equations (RANS) and standard k-? turbulence model was used to simulate a set of 16 different inlet wind directions over a real urban area (downtown Pamplona, Spain). The temporal series of NO_x and PM₁₀ and the spatial differences in pollutant concentration of NO₂ and BTEX obtained were in agreement with experimental data. Inside urban canopy, an important influence of urban boundary layer dynamics on the pollutant concentration patterns was observed. Large concentration differences between different zones of the same square were found. This showed that concentration levels measured by an automatic monitoring station depend on its location in the street or square, and a modelling methodology like this is useful to complement the experimental information. On the other hand, this methodology can also be applied to evaluate abatement strategies by redistributing traffic emissions.     

Estimating the emission source reduction of PM10 in central Taiwan

Three theoretical parent frequency distributions; lognormal, Weibull and gamma were used to fit the complete set of PM10 data in central Taiwan. The gamma distribution is the best one to represent the performance of high PM10 concentrations. However, the parent distribution sometimes diverges in predicting the high PM10 concentrations. Therefore, two predicting methods, Method I: two-parameter exponential distribution and Method II: asymptotic distribution of extreme value, were used to fit the high PM10 concentration distributions more correctly. The results fitted by the two-parameter exponential distribution are better matched with the actual high PM10 data than that by the parent distributions. Both of the predicting methods can successfully predict the return period and exceedances over a critical concentration in the future year. Moreover, the estimated emission source reductions of PM10 required to meet the air quality standard by Method I and Method II are very close. The estimated emission source reductions of PM10 range from 34% to 48% in central Taiwan.     

Estimating the frequency distributions of particulate matter and their metal elements in a temple

Air quality inside Asian temples is typically poor because of the burning of incense. This study measured and analyzed concentrations of fine (PM2.5) and coarse (PM2.5-10) particulate matter and their metal elements inside a temple in central Taiwan. Experimental results showed that the concentrations of metals Cd, Ni, Pb, and Cr inside the temple were higher than those at rural, suburban, urban, and industrial areas in other studies. Three theoretical parent distributions (lognormal, Weibull, and gamma) were used to fit the measured data. The lognormal distribution was the most appropriate distribution for representing frequency distributions of PM10, PM2.5, and their metal elements. Furthermore, the central limit theorem, H-statistic-based scheme, and parametric and nonparametric bootstrap methods were used to estimate confidence intervals for mean pollutant concentrations. The estimated upper confidence limits (UCLs) of means between different methods were very consistent, because the sample coefficient of variation (CV) was < 1. When the sample CV was > 1, the UCL based on H-statistical method tended to overestimate the UCLs when compared with other methods. Confidence intervals for pollutant concentrations at different percentiles were evaluated using parametric and nonparametric bootstrap methods. The probabilities of pollutants exceeding a critical concentration were also calculated.     

On the Evaluation of Predictions from a Gaussian Plume Model

The performance of a CRSTER equivalent Gaussian plume model (CEQM) is examined using data from the EPRI Plume Model Validation study at the Klncaid, Illinois site. Four-way comparisons are made on the ordered statistics or the cumulative frequency distribution (CFD) of maximum hourly observed and predicted concentrations. Using the uniform random distribution and the lognormal random distribution as simple predictive schemes without any physical context, it Is found that the CEQM predicts a concentration CFD which matches the observed CFD significantly closer than the CFD predicted by the uniform random distribution. The two-parameter lognormal random distribution predicts the concentration CFD better than the CEQM over all concentration ranges; however, the CEQM fits the upper range of the concentration distribution better than the lognormal random distribution,, despite the fact that the predictions are generated using dispersion conditions entirely different from those of the observations. The nature of this ergodicity of distribution is probed by exercising CEQM using randomized input based on the observed frequency distributions of the Input parameters instead of feeding the hour-by-hour model input matched by time into CEQM as is customarily done. The exercise of the model by uncoupling the time linkage in model Input has no systematic effect on the predicted cumulative frequency distribution of concentrations. Only at the highest concentration range (99.5% or higher) do the two sets of predictions begin to diverge.     

The co-occurrence of potentially phytotoxic concentrations of various gaseous air pollutants

Studies on impacts of air pollutants on vegetation have focused primarily on individual pollutants: ozone, sulfur dioxide and nitrogen dioxide. The impacts of pollutant combinations have not been extensively studied and there has been no concerted effort to ensure that experimental regimes for combined pollutant exposures are representative of ambient pollutant concentration, frequency, duration and time intervals between events. Most studies concerning the impact of pollutant combinations on vegetation have used concentrations of 0.05 ppm and greater. Therefore, co-occurrence was defined as the simultaneous occurrence of hourly averaged concentrations of 0.05 ppm or greater for pollutant pairs (SO₂/NO₂, O₃/SO₂, or O₃/NO₂). Air quality information from three data bases (EPA-SAROAD, EPRI-SURE and TVA) was analyzed to determine the frequency of co-occurrence for pollutant pairs. Ambient air quality data representing a diverse range of monitoring sites (e.g. rural, remote, city center, urban, near urban, etc.) were used in the analysis. Results showed that at most sites (1) the co-occurrence of two-pollutant mixtures lasted only a few hours per episode, (2) the time interval between episodes was generally large (weeks, sometimes months) and (3) most studies have used more intense exposure regimes than occurred at most monitored sites. When designing vegetation experiments for assessing pollutant mixture effects, it may be desirable to give greater emphasis to sequential patterns of exposure. It is suggested that future work is required before a reliable estimate can be made of the environmental significance of pollutant mixtures on vegetation.     

The effects of roadside structures on the transport and dispersion of ultrafine particles from highways

Understanding local-scale transport and dispersion of pollutants emitted from traffic sources is important for urban planning and air quality assessments. Predicting pollutant concentration patterns in complex environments depends on accurate representations of local features (e.g., noise barriers, trees, buildings) affecting near-field air flows. This study examined the effects of roadside barriers on the flow patterns and dispersion of pollutants from a high-traffic highway in Raleigh, North Carolina, USA. The effects of the structures were analyzed using the Quick Urban & Industrial Complex (QUIC) model, an empirically based diagnostic tool which simulates fine-scale wind field and dispersion patterns around obstacles. Model simulations were compared with the spatial distributions of ultrafine particles (UFP) from vehicular emissions measured using a passenger van equipped with a Differential Mobility Analyzer/Condensation Particle Counter. The field site allowed for an evaluation of pollutant concentrations in open terrain, with a noise barrier present near the road, and with a noise barrier and vegetation present near the road.Results indicated that air pollutant concentrations near the road were generally higher in open terrain situations with no barriers present; however, concentrations for this case decreased faster with distance than when roadside barriers were present. The presence of a noise barrier and vegetation resulted in the lowest downwind pollutant concentrations, indicating that the plume under this condition was relatively uniform and vertically well-mixed. Comparison of the QUIC model with the mobile UFP measurements indicated that QUIC reasonably represented pollutant transport and dispersion for each of the study configurations.     

Estimating the Frequency Distributions of Particulate Matter and Their Metal Elements in a Temple

Abstract

Air quality inside Asian temples is typically poor because of the burning of incense. This study measured and analyzed concentrations of fine (PM_2.5) and coarse (PM_2.5–10) particulate matter and their metal elements inside a temple in central Taiwan. Experimental results showed that the concentrations of metals Cd, Ni, Pb, and Cr inside the temple were higher than those at rural, suburban, urban, and industrial areas in other studies. Three theoretical parent distributions (lognormal, Weibull, and gamma) were used to fit the measured data. The lognormal distribution was the most appropriate distribution for representing frequency distributions of PM₁₀, PM_2.5, and their metal elements.

Furthermore, the central limit theorem, H-statistic-based scheme, and parametric and nonparametric bootstrap methods were used to estimate confidence intervals for mean pollutant concentrations. The estimated upper confidence limits (UCLs) of means between different methods were very consistent, because the sample coefficient of variation (CV) was <1. When the sample CV was >1, the UCL based on H-statistical method tended to overestimate the UCLs when compared with other methods. Confidence intervals for pollutant concentrations at different percentiles were evaluated using parametric and nonparametric bootstrap methods. The probabilities of pollutants exceeding a critical concentration were also calculated.     

Calculating Air Quality and Its Control

Air quality is shown as a function of averaging times of five minutes to one year for carbon monoxide, hydrocarbons, nitric oxide, nitrogen dioxide, nitrogen oxides, oxidant, and sulfur dioxide in Chicago, Cincinnati, Los Angeles, New Orleans, Philadelphia, San Francisco, and Washington, D. C. Concentrations are approximately lognormally distributed for all pollutants in all cities for all averaging times. Maximum concentration is inversely proportional to averaging time to an exponent. The exponent is a function of the standard geometric deviation. General air quality and control parameters are derived and shown for one example, nitrogen oxides in Washington, D. C. These values are compared to one air quality standard.     

A model for the maximum credible hourly impact on any ground receptor from point sources with thermal plume rise

A pollutant dispersion model is developed, allowing fast evaluation of the maximum credible 1-h average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with buoyant plumes in urban or rural areas. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height. The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings, respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the buoyant plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights. The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. It is also suited for regulatory purposes, as it can be used to define the minimum stack size requirements for a given source as a function of the exit gas volume and temperature, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

Surface Air Pollutant Concentration Frequency Distributions: Implications for Urban Modeling

With the development of ambient air quality standards (AAQS), the need arises to describe the characteristics of regional surface air-pollutant concentration frequency distributions. In the evaluation of land use plans, numerous agencies will be concerned with evaluating the effectiveness of emission zoning and/or control actions. On a regional basis, one means of performing this assessment lies in determining the changes in the pollutant frequency distributions resulting from control actions.

This study presents new data concerning the surface air-pollutant concentration frequency distributions observed for area sources and continuous point sources, and compares these distributions with those of the pertinent meteorological variables describing the transport and diffusion of the pollutant. The observed surface air pollutant frequency distributions are compared to those corresponding to simple modeling concepts from either an urban area source or a continuous point source. For an urban source and a relatively inert pollutant like CO, we found that the observed frequency distribution for CO surface air concentration parallels the approximately log-normal frequency distribution of the reciprocal of the wind speed. We show that the constant relating these two well-correlated frequency distributions can be determined either experimentally or with a numerical simulation model of air pollution. The usefulness of numerical models in air pollution is discussed.     

An air quality data analysis system for interrelating effects, standards, and needed source reductions: Part 13--Applying the EPA Proposed Guidelines for Carcinogen Risk Assessment to a set of asbestos lung cancer mortality data

The Clean Air Act Amendments of 1990 (CAAA-90) list 189 hazardous air pollutants (HAPs) for which "safe" ambient concentrations are to be determined. The primary purpose of this paper is to develop two mathematical models, lognormal and logarithmic, that effectively express excess lung cancer mortality as a function of asbestos concentration for an example set of data and also to suggest using these two models for additional HAPs. The secondary purpose of this paper is to calculate a "safe" asbestos concentration by first assuming a default linear extrapolation (to one excess death per million people, as specified for carcinogenic HAPs). The resulting "safe" concentration is an impossible-to-achieve 1/1000 of present background asbestos concentrations. A letter to the editor and a response in this Journal issue use additional asbestos data that suggest that the "safe" concentration should be about 730 times higher than first calculated here and that a default nonlinear extrapolation should be used instead, with the "safe" concentration proportional to the desired mortality level raised to the 0.39 power. These results suggest that the most important problem in setting a "safe" concentration for each carcinogenic HAP is to determine the correct nonlinear extrapolation to use for each HAP.     

A note on average vertical profiles of vehicular pollutant concentrations in urban street canyons

Recent observations of air pollutant concentrations measured within and above street canyons were used to study the average vertical profiles of vehicular pollutant concentrations in the urban environment. The idea of an exponential vertical concentration distribution, exp( −Bz^q), resulted from a near ground-level source diffusing over flat terrain, was tentatively extended to the urban street canyons, where the empirical parameters B and q are generally dependent on the atmospheric stability and the aerodynamic characteristics of the canyon.     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

Analysis of an anomalous case of high air pollution concentration in Turin after a foehn event

A case of unusually high concentrations of some urban air pollutants (CO, NO, SO₂) in Turin (Northwestern Italy) is presented. This episode occurred during the late afternoon of 7 November 1995. This day was characterised by a strong northern foehn event in the morning, which followed the passage of a cold front. The analysis has been carried out by means of data derived from the urban and suburban air quality monitoring networks, of meteorological data (wind velocity, temperature and relative humidity) from the same network and from other networks in the region, and of the output of the numerical model LAMBO (operatively used by the Regional Meteorological Service of Emilia Romagna). The analysis of meteorological data appears to be in good correlation with the distribution of the air pollutant concentrations; in particular, the high concentrations observed in the late afternoon are due to a strong thin inversion layer near the ground, developing immediately after the sudden end of the foehn episode.     

Flow and dispersion in street intersections

Street intersections play an important role in determining pollutant concentrations in the urban canopy – vehicle emissions often increase in the vicinity of road intersections, and the complex flow patterns that occur within the intersection determine the pollutant fluxes into adjoining streets and into the atmosphere. Operational models for urban air quality therefore need to take account of the particular characteristics of street intersections. We have performed an experimental and numerical investigation of flow and dispersion mechanisms within an urban intersection, and on the basis of our observations and results, we have developed a new operational model for pollutant exchanges in the intersection, which takes account of the non-uniformity of the pollutant fluxes entering and leaving the intersection. The intersection is created by two streets of square cross-section, crossing orthogonally; concentrations were measured by releasing a neutrally buoyant tracer gas from a line source located in one of the streets. As a general result, the numerical simulations agree well with the measurements made in the wind tunnel experiments, except for the case of ground-level concentrations, where the computed concentrations far from the axis of the line source are significantly lower than the measured values. In the first part of the study we investigate the influence of an intersection on the velocity and concentration fields in the adjoining streets; we show that the immediate influence of the intersection extends within the adjoining streets, to a distance of the order of the characteristic size of the streets. A large recirculating vortex is formed at the entrance to the cross-wind streets, and this determines the exchange of pollutants between the streets and the intersection. For some wind directions the average velocity in the street segment between intersections is the same as that which occurs in an infinitely long street with the same wind, but for other angles the average velocity in the finite-length street is significantly lower. The average concentration along a finite-length street is significantly different from that observed in an infinitely long street. In the second part of the study we investigate how the pollutant fluxes in the incoming streets are redistributed amongst the outgoing streets. An analysis of the mean streamlines shows that the flows remain relatively planar, with little variation over the vertical, and we have exploited this result to develop a simple operational model for the redistribution of pollutant fluxes within the intersection. This model has been further adapted to take account of the influence of fluctuations in wind direction over typical averaging periods. The resulting model is used in the street network model SIRANE.     

Flow and dispersion in an urban cubical cavity

Flow and dispersion in an urban cubical cavity are numerically investigated using a Reynolds-averaged Navier–Stokes equations (RANS) model with the renormalization group (RNG) k–? turbulence closure model. The urban cubical cavity is surrounded by flank walls that are parallel to the streamwise direction, called end-walls, as well as upstream and downstream walls. A primary vortex and secondary vortices including end-wall vortices are formed in the cavity. Because of the end-wall drag effect, the averaged mean-flow kinetic energy in the cavity is smaller than that in an urban street canyon that is open in the along-canyon direction. A trajectory analysis shows that the end-wall vortices cause fluid particles to move in the spanwise direction, indicating that flow in the cavity is essentially three-dimensional. The iso-surfaces of the Okubo–Weiss criterion capture cavity vortices well. The pollutant concentration is high near the bottom of the upstream side in the case of continuous pollutant emission, whereas it is high near the center of the primary vortex in the case of instantaneous pollutant emission. To get some insight into the degree of pollutant escape from the cavity according to various meteorological factors, extensive numerical experiments with different ambient wind speeds and directions, inflow turbulence intensities, and cavity-bottom heating intensities are performed. For each experiment, we calculate the time constant, which is defined as the time taken for the pollutant concentration to decrease to e^?1 of its initial value. The time constant decreases substantially with increasing ambient wind speed, and tends to decrease with increasing inflow turbulence intensity and cavity-bottom heating intensity. The time constant increases as the ambient wind direction becomes oblique. High ambient wind speed is found to be the most crucial factor for ventilating the cavity, thus improving air quality in an urban cubical cavity.     

A hybrid modeling approach to resolve pollutant concentrations in an urban area

A modeling tool that can resolve contributions from individual sources to the urban environment is critical for air-toxics exposure assessments. Air toxics are often chemically reactive and may have background concentrations originated from distant sources. Grid models are the best-suited tools to handle the regional features of these chemicals. However, these models are not designed to resolve pollutant concentrations on local scales. Moreover, for many species of interest, having reaction time scales that are longer than the travel time across an urban area, chemical reactions can be ignored in describing local dispersion from strong individual sources making Lagrangian and plume-dispersion models practical. In this study, we test the feasibility of developing an urban hybrid simulation system. In this combination, the Community Multi-scale Air Quality model (CMAQ) provides the regional background concentrations and urban-scale photochemistry, and local models such as Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) and AMS/EPA Regulatory Model (AERMOD) provide the more spatially resolved concentrations due to local emission sources. In the initial application, the HYSPLIT, AERMOD, and CMAQ models are used in combination to calculate high-resolution benzene concentrations in the Houston area. The study period is from 18 August to 4 September of 2000. The Mesoscale Model 5 (MM5) is used to create meteorological fields with a horizontal resolution of 1×1 km². In another variation to this approach, multiple HYSPLIT simulations are used to create a concentration ensemble to estimate the contribution to the concentration variability from point sources. HYSPLIT simulations are used to model two sources of concentration variability; one due to variability created by different particle trajectory pathways in the turbulent atmosphere and the other due to different flow regimes that might be introduced when using gridded data to represent meteorological data fields. The ensemble mean concentrations determined by HYSPLIT plus the concentrations estimated by AERMOD are added to the CMAQ calculated background to estimate the total mean benzene concentration. These estimated hourly mean concentrations are also compared with available field measurements.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.