Some aspects of air pollution in Buenos Aires city

This paper presents three aspects of air pollution in the city of Buenos Aires (Argentina). First, we describe the main features of air pollution climatology in the city: the characteristics of wind flow, atmospheric stability and mixing heights. Then, we present the results of the application of DAUMOD and ISCST3 atmospheric dispersion models to calculate spatial and temporal distributions of carbon monoxide and nitrogen oxides background concentrations. Finally, we present the main features of carbon monoxide concentrations observed in a narrow street canyon located downtown.     

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.     

Assessing the impact of weather events at mid-latitudes on the atmospheric transport of chemical pollutants using a 2-dimensional multimedia meteorological model

We investigate the long-range transport potential (LRTP) of five different classes of hypothetical chemical pollutants (volatile, multimedia, semivolatile, particle-associated and hydrophilic) during a low pressure weather event using a novel 2 (x- and z-axis)-Dimensional Multi-Media Meteorological Model (2D4M). The atmosphere (z-axis) is described by three atmospheric layers, where two layers constitute the boundary layer and the third layer the free troposphere. The 2D4M can describe distinct weather events on a regional scale and calculate the LRTP of chemicals as a function of time during these events. Four weather factors are used to model weather events and their influence on the atmospheric transport of chemicals: (1) temperature, (2) wind speed and mixing dynamics of the troposphere, (3) hydroxyl radical concentrations and (4) precipitation. We have modeled the impact of variability in each of these factors on LRTP of pollutants during a front event associated with a low pressure period that interrupts a dominant high pressure system. The physico-chemical properties of the pollutant determine which specific weather factors contribute most to variability in transport potential during the event. Volatile and multimedia chemicals are mainly affected by changing atmospheric mixing conditions, wind speeds and OH radical concentrations, while semivolatile substances are also affected by temperature. Low-vapor-pressure pollutants that are particle-associated, and water-soluble pollutants are most strongly affected by precipitation. Some chemical pollutants are efficiently transported from the boundary layer into the upper troposphere during the modeled low pressure event and are transported by much higher wind speeds than in the boundary layer. Our model experiments show that the transport potential of volatile, multimedia and semivolatile compounds is significantly increased during a front event as a result of efficient tropospheric mixing and fast wind speeds in the upper troposphere, whereas low-volatility and hydrophilic chemicals are largely scavenged from the atmosphere. In future LRTP assessment of chemical contaminants as required by the Stockholm Convention and the convention on long-range transboundary air pollution, it is therefore advised to prioritize volatile, multimedia and semivolatile chemicals that are identified in initial screening.     

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.     

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.     

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.     

The use of wind fields in a land use regression model to predict air pollution concentrations for health exposure studies

A methodology is developed to include wind flow effects in land use regression (LUR) models for predicting nitrogen dioxide (NO₂) concentrations for health exposure studies. NO₂ is widely used in health studies as an indicator of traffic-generated air pollution in urban areas. Incorporation of high-resolution interpolated observed wind direction from a network of 38 weather stations in a LUR model improved NO₂ concentration estimates in densely populated, high traffic and industrial/business areas in Toronto-Hamilton urban airshed (THUA) of Ontario, Canada. These small-area variations in air pollution concentrations that are probably more important for health exposure studies may not be detected by sparse continuous air pollution monitoring network or conventional interpolation methods. Observed wind fields were also compared with wind fields generated by Global Environmental Multiscale-High resolution Model Application Project (GEM-HiMAP) to explore the feasibility of using regional weather forecasting model simulated wind fields in LUR models when observed data are either sparse or not available. While GEM-HiMAP predicted wind fields well at large scales, it was unable to resolve wind flow patterns at smaller scales. These results suggest caution and careful evaluation of regional weather forecasting model simulated wind fields before incorporating into human exposure models for health studies. This study has demonstrated that wind fields may be integrated into the land use regression framework. Such integration has a discernable influence on both the overall model prediction and perhaps more importantly for health effects assessment on the relative spatial distribution of traffic pollution throughout the THUA. Methodology developed in this study may be applied in other large urban areas across the world.     

Air pollution dispersion within urban street canyons

A semi-empirical mathematical model, Urban Street Model (USM), is proposed to efficiently estimate the dispersion of vehicular air pollution in cities. This model describes urban building arrangements by combining building density, building heights and the permeability of building arrangements relative to wind flow. To estimate the level of air pollution in the city of Krasnoyarsk (in Eastern Siberia), the spatial distribution of pollutant concentrations off roadways is calculated using Markov's processes in USM. The USM-predicted numerical results were compared with field measurements and with results obtained from other frequently used models, CALINE-4 and OSPM. USM consistently yielded the best results. OSPM usually overestimated pollutant concentration values. CALINE-4 consistently underestimated these values. For OSPM, the maximum differences were 160% and for CALINE-4 about 400%. Permeability and building density are necessary parameters for accurately modeling urban air pollution and influencing regulatory requirements for building planning.     

Transport and dispersion during wintertime particulate matter episodes in the San Joaquin Valley, California

Data analysis and modeling were performed to characterize the spatial and temporal variability of wintertime transport and dispersion processes and the impact of these processes on particulate matter (PM) concentrations in the California San Joaquin Valley (SJV). Radar wind profiler (RWP) and radio acoustic sounding system (RASS) data collected from 18 sites throughout Central California were used to estimate hourly mixing heights for a 3-month period and to create case studies of high-resolution diagnostic wind fields, which were used for trajectory and dispersion analyses. Data analyses show that PM episodes were characterized by an upper-level ridge of high pressure that generally produced light winds through the entire depth of the atmospheric boundary layer and low mixing heights compared with nonepisode days. Peak daytime mixing heights during episodes were -400 m above ground level (agl) compared with -800 m agl during nonepisodes. These episode/nonepisode differences were observed throughout the SJV. Dispersion modeling indicates that the range of influence of primary PM emitted in major population centers within the SJV ranged from -15 to 50 km. Trajectory analyses revealed that little intrabasin pollutant transport occurred among major population centers in the SJV; however, interbasin transport from the northern SJV and Sacramento regions into the San Francisco Bay Area (SFBA) was often observed. In addition, this analysis demonstrates the usefulness of integrating RWP/RASS measurements into data analyses and modeling to improve the understanding of meteorological processes that impact pollution, such as aloft transport and boundary layer evolution.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

Air Pollution Directional Risk Assessment for Siting a Landfill

Abstract

Air pollution directional risk (APDR) is an essential factor to be assessed when selecting an appropriate landfill site. Because air pollutants generated from a landfill are diffused and transported by wind in different directions and speeds, areas surrounding the landfill will be subject to different associated risks, depending on their relative position from the landfill. This study assesses potential APDRs imposed from a candidate landfill site on its adjacent areas on the basis of the pollutant distribution simulated by a dispersion model, wind directions and speeds from meteorological monitoring data, and population density. A pollutant distribution map layer was created using a geographic information system and layered onto a population density map to obtain an APDR map layer. The risk map layer was then used in this study to evaluate the suitability of a candidate site for placing a landfill. The efficacy of the proposed procedure was demonstrated for a siting problem in central Taiwan, Republic of China.     

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.     

Assessment of traffic-related air pollution in two street canyons in Paris: implications for exposure studies

The small-scale spatial variability of air pollution observed in urban areas has created concern about the representativeness of measurements used in exposure studies. It is suspected that limit values for traffic-related pollutants may be exceeded near busy streets, although respected at urban background sites. In order to assess spatial concentration gradients and identify weather conditions that might induce air pollution episodes in urban areas, different sampling and modelling techniques were studied.Two intensive monitoring campaigns were carried out in typical street canyons in Paris during winter and summer. Steep cross-road and vertical concentration gradients were observed within the canyons, in addition to large differences between roadside and background levels. Low winds and winds parallel to the street axis were identified as the worst dispersion conditions. The correlation between the measured compounds gave an insight into their sources and fate. An empirical relationship between CO and benzene was established. Two relatively simple mathematical models and an algorithm describing vertical pollutant dispersion were used. The combination of monitoring and modelling techniques proposed in this study can be seen as a reliable and cost-effective method for assessing air quality in urban micro-environments. These findings may have important implications in designing monitoring studies to support investigation on the health effects of traffic-related air pollution.     

An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

An Air Pollution Incident Due to a Stationary Front

In January 1971, the New York City area experienced a period of high pollution in which concentrations exceeded the present criteria for Stage I of the New York City Alert-Warning System. The incident was unusual because the high concentrations were associated with a weak frontal system which moved back and forth over the area and not with a stagnating anticyclone. Concentrations of pollutants were found to be closely related to the movement of the frontal system as well as to changes in wind speed and stability. Climatological criteria for identifying-periods of potential high air pollution and the criteria for mixing heights, transport wind speed and ventilation factors necessary for the issuance of an official advisory from the National Meteorological Center were not met during this incident. Therefore, some re-evaluation and redefinition of these criteria are recommended.     

An assessment of the relationship between functional groups of weather elements and atmospheric pollution in Calgary,Canada

Nine regularly observed meteorological elements were classified into four functional groups—ventilation, energy, wet deposition and Chinook—and the contribution of each group to the air pollution process in Calgary, Canada, assessed by multiple correlation. While ventilation was the dominant process in most situations, the energy terms were the most significant during a smog. Heavy air pollution often occurred during a Chinook if the wind was weaker than 3 m s⁻¹. A linear combination of weather elements successfully separated clean from polluted air except on weekends and in very cold weather.     

Air pollution in the Krusne Hory region,Czech Republic during the 1990s

Emissions from the Black Triangle Region were considered to be the major source of air pollution problems in Europe during the 1990s. This discussion reviews the changes in emissions and pollution concentrations in the Krusne Hory Region (Czech Republic) in the winter half of the year during most of the past decade, and describes the relationships with meteorology. Sulfur dioxide (SO₂) is used as the example pollutant. The results show a decrease in pollution concentrations since 1996, as air pollution control and management strategies for important point sources take effect. The winter of 1995–1996 was especially harsh in the number of pollution episodes. Correlations between SO₂ and meteorological parameters are inconsistent. Wind direction provides the best relationship at monitoring stations along the Krusne Hory Plateau, with wind speed and temperature more variable depending on month and location. For the valley stations, higher SO₂ concentrations are strongly related to colder temperatures, higher relative humidities, and lower wind speeds. A case study during the winter of 1995–1996 (November 9–15) illustrated the importance of synoptic high pressure and a low-level inversion in minimizing plume dispersion from point sources. Specific sources of SO₂ affecting each station could thus be identified.     

Intercomparison of nocturnal mixing height estimate methods for urban air pollution modelling

One of the most important meteorological input parameters for three-dimensional photochemical air pollution models is the mixing height h, which has a strong influence on the shape and intensity of the vertical diffusivity K_z and, as a consequence, on ground-level air concentrations of primary and secondary pollutants. A number of indirect algorithms for the estimate of h in nocturnal, stable conditions, when the mixing is dominated by mechanical turbulence, are reviewed and compared with mixing heights derived from wind (SODAR) and temperature (RASS) profiles measured in the Milan urban area during spring and summer 1996. Mixing heights derived from temperature soundings correlate positively with those derived from wind soundings only when a stable layer is superimposed to a quasi-adiabatic layer, while the correlation is very weak in the presence of a ground-based inversion. In general, indirect algorithms perform very poorly if compared with RASS-based estimates, and reasonably well if compared with SODAR-based estimates. Among the others, Benkley and Schulman (1979, Journal of Applied Meteorology 18, 772–780) method, which makes use of wind speed observed at 10 m height, and Nieuwstadt (1984, Boundary-Layer Meteorology 30, 31–55), which makes use of friction velocity and Monin–Obukhov length, give the best results.     

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.     

Statistical and diagnostic evaluation of a new-generation urban dispersion modelling system against an extensive dataset in the Helsinki area

We have developed a modelling system for predicting the traffic volumes, emissions from stationary and vehicular sources, and atmospheric dispersion of pollution in an urban area. This paper describes a comparison of the NO_x and NO₂ concentrations predicted using this modelling system with the results of an urban air quality monitoring network. We performed a statistical analysis to determine the agreement between predicted and measured hourly time series of concentrations at four permanently located and three mobile monitoring stations in the Helsinki Metropolitan Area in 1996–1997 (at a total of ten urban and suburban measurement locations). At the stations considered, the so-called index of agreement values of the predicted and measured time series of the NO₂ concentrations vary between 0.65 and 0.82, while the fractional bias values range from −0.29 to +0.26. In comparison with corresponding results presented in the literature, the agreement between the measured and predicted datasets is good, as indicated by these statistical parameters. The seasonal variations of the NO₂ concentrations were analysed in terms of the relevant meteorological parameters. We also analysed the difference between model predictions and measured data diagnostically, in terms of meteorological parameters, including wind speed and direction (the latter separately for two wind speed classes), atmospheric stability and ambient temperature, at two monitoring stations in central Helsinki. The modelling system tends to overpredict the measured NO₂ concentrations both at the highest (u⩾6 m s⁻¹) and at the lowest wind speeds (u<2 m s⁻¹). For higher wind speeds, the modelling system overpredicts the measured NO₂ concentrations in certain wind direction intervals; specific ranges were found for both monitoring stations considered. The modelling system tends to underpredict the measured concentrations in convective atmospheric conditions, and overpredict in stable conditions. The possible physico-chemical reasons for these differences are discussed.