A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast

Abstract

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998–2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x), sulfur dioxide (SO₂), coarse particulate matter (PM₁₀), fine particulate matter (PM_2.5)_, and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO₂, PM₁₀ and NO_x. Larger errors, up to 50%, are expected for NO, SO₂, PM_2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Meta-analysis of time-series studies of air pollution and mortality: effects of gases and particles and the influence of cause of death,age, and season

A comprehensive, systematic synthesis was conducted of daily time-series studies of air pollution and mortality from around the world. Estimates of effect sizes were extracted from 109 studies, from single- and multipollutant models, and by cause of death, age, and season. Random effects pooled estimates of excess all-cause mortality (single-pollutant models) associated with a change in pollutant concentration equal to the mean value among a representative group of cities were 2.0% (95% CI 1.5-2.4%) per 31.3 microg/m3 particulate matter (PM) of median diameter < or = 10 microm (PM10); 1.7% (1.2-2.2%) per 1.1 ppm CO; 2.8% (2.1-3.5%) per 24.0 ppb NO2; 1.6% (1.1-2.0%) per 31.2 ppb O3; and 0.9% (0.7-1.2%) per 9.4 ppb SO2 (daily maximum concentration for O3, daily average for others). Effect sizes were generally reduced in multipollutant models, but remained significantly different from zero for PM10 and SO2. Larger effect sizes were observed for respiratory mortality for all pollutants except O3. Heterogeneity among studies was partially accounted for by differences in variability of pollutant concentrations, and results were robust to alternative approaches to selecting estimates from the pool of available candidates. This synthesis leaves little doubt that acute air pollution exposure is a significant contributor to mortality.     

Effects of SO2 and NOx emission reductions on PM2.5 mass concentrations in the southeastern United States

Measurements from sites of the Southeastern Aerosol Research and Characterization (SEARCH) program, made from 1998 to 2001, are used with a thermodynamic equilibrium model, Simulating Composition of Atmospheric Particles at Equilbrium (SCAPE2), to extend an earlier investigation of the responses of fine particulate nitrate (NO3-) and fine particulate matter (PM2.5) mass concentrations to changes in concentrations of nitric acid (HNO3) and sulfate (SO42-). The responses were determined for a projected range of variations of SO42- and HNO3 concentrations resulting from adopted and proposed regulatory initiatives. The predicted PM2.5 mass concentration decreases averaged 1.8-3.9 microg/m3 for SO42- decreases of 46-63% from current concentrations. Combining the S042- decrease with a 40% HNO3 decrease from current concentrations (approximating expected mobile-source oxides of nitrogen [NOx] reductions by 2020) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0.2 microg/m3 for three nonurban sites and 0.8-1 microg/m3 for one nonurban and two urban sites. Increasing the HNO3 reduction to 55% (an estimate of adding Clear Skies Phase II NOx reductions) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0-0.4 microg/m3. Because of the well-documented losses of particulate NO3- from Federal Reference Method (FRM) filters, only a fraction of these incremental changes would be observed.     

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eski?ehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.     

Effects of instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, Georgia

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO2, CO, NOx, and O3) and fine particulate matter ([PM2.5] PM2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7-40% of the temporal variation in the daily pollutant measures and was largest for the PM2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO2, CO, NOx, and EC). Population-weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O3 to 70% of the temporal variation for SO2 and EC. Wind     

Air pollution and health studies in China--policy implications

During the rapid economic development in China, ambient air pollutants in major cities, including PM10 (particulate matter with aerodynamic diameter < or =10 microm) and SO2 have been reduced due to various measures taken to reduce or control sources of emissions, whereas NO2 is stable or slightly increased. However, air pollution levels in China are still at the higher end of the world level. Less information is available regarding changes in national levels of other pollutants such as PM2.5 and ozone. The Chinese Ministry of Environmental Protection (MOEP) set an index for "controlling/reducing total SO2 emissions" to evaluate the efficacy of air pollution control strategy in the country. Total SO2 emissions declined for the first time in 2007. Chinese epidemiologic studies evidenced adverse health effects of ambient air pollution similar to those reported from developed countries, though risk estimates on mortality/morbidity per unit increase of air pollutant are somewhat smaller than those reported in developed countries. Disease burden on health attributable to air pollution is relatively greater in China because of higher pollution levels. Improving ambient air quality has substantial and measurable public health benefits in China. It is recommended that the current Chinese air quality standards be updated/revised and the target for "controlling/reducing total SO2 emissions" be maintained and another target for "reducing total NO2 emissions" be added in view of rapid increase in motor vehicles. Continuous and persistent efforts should be taken to improve ambient air quality.     

The Steubenville comprehensive air monitoring program (SCAMP): associations among fine particulate matter, co-pollutants, and meteorological conditions

We determined 24-hr average ambient concentrations of PM2.5 and its ionic and carbonaceous components in Steubenville, OH, between May 2000 and May 2002. We also determined daily average gaseous co-pollutant concentrations, meteorological conditions, and pollen and mold spore counts. Data were analyzed graphically and by linear regression and time series models. Multiple-day episodes of elevated fine particulate matter (PM2.5) concentrations often occurred during periods of locally high temperature (especially during summer), high pressure, or low wind speed (especially during winter) and generally ended with the passage of a frontal system. After removing autocorrelation, we observed statistically significant positive associations between concentrations of PM2.5 and concentrations of CO, NOx, and SO2. Associations with NOx and CO exhibited significant seasonal dependencies, with the strongest correlations during fall and winter. NOx, CO, SO2, O3, temperature, relative humidity, and wind speed were all significant predictors of PM2.5 concentration in a time-series model with external regressors, which successfully accounted for 79% of the variance in log-transformed daily PM2.5 concentrations. Coefficient estimates for NOx and temperature varied significantly by season. The results provide insight that may be useful in the development of future PM2.5 reduction strategies for Steubenville. Additionally, they demonstrate the need for PM epidemiology studies in Steubenville (and elsewhere) to carefully consider the potential confounding effects of gaseous co-pollutants, such as CO and NOx, and their seasonally dependent associations with PM2.5.     

Characterization of major chemical components of fine particulate matter in North Carolina

This paper presents measurements of daily sampling of fine particulate matter (PM2.5) and its major chemical components at three urban and one rural locations in North Carolina during 2002. At both urban and rural sites, the major insoluble component of PM2.5 is organic matter, and the major soluble components are sulfate (SO4(2-)), ammonium (NH4(+)), and nitrate (NO3(-)). NH4(+) is neutralized mainly by SO4(2-) rather than by NO3(-), except in winter when SO4(2-) concentration is relatively low, whereas NO3(-) concentration is high. The equivalent ratio of NH4(+) to the sum of SO4(2-) and NO3(-) is < 1, suggesting that SO4(2-) and NO3(-) are not completely neutralized by NH4(+). At both rural and urban sites, SO4(2-) concentration displays a maximum in summer and a minimum in winter, whereas NO3(-) displays an opposite seasonal trend. Mass ratio of NO3(-) to SO4(2-) is consistently < 1 at all sites, suggesting that stationary source emissions may play an important role in PM2.5 formation in those areas. Organic carbon and elemental carbon are well correlated at three urban sites although they are poorly correlated at the agriculture site. Other than the daily samples, hourly samples were measured at one urban site. PM2.5 mass concentrations display a peak in early morning, and a second peak in late afternoon. Back trajectory analysis shows that air masses with lower PM2.5 mass content mainly originate from the marine environment or from a continental environment but with a strong subsidence from the upper troposphere. Air masses with high PM2.5 mass concentrations are largely from continental sources. Our study of fine particulate matter and its chemical composition in North Carolina provides crucial information that may be used to determine the efficacy of the new National Ambient Air Quality Standard (NAAQS) for PM fine. Moreover, the gas-to-particle conversion processes provide improved prediction of long-range transport of pollutants and air quality.     

Source extraction information from air quality data monitored in an Argentinean steel mill

A statistical analysis of a series of ambient air concentrations of suspended particulate matter (SPM) and NO2 is presented. Measurements were taken at four sites that belong to an Argentinean steel mill and in another site located in its vicinity. The air pollutants were measured during a three-week exploratory sampling. The monitoring sites were selected on the basis of relevant characteristics of the emission sources and the corresponding climatological statistics of the last decade. Suspended particulate matter with aerodynamic diameter of less than 10 microm (PM10) and NO2 were continuously measured at only one site, while 1-hr samples of NO2 and 24-hr samples of total SPM and SO2 were collected at the other sites. The registered concentrations show that SPM was the pollutant of major concern. A first estimate about the nature of the contribution of the different sources of particles and NO2 present in the area was obtained through the statistical analysis of measured concentration data coupled with prevalent meteorological variables.     

Current status of air quality models for particulate matter.

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO4(2-), while NO3-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

Impact of biogenic emission uncertainties on the simulated response of ozone and fine particulate matter to anthropogenic emission reductions

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1-0.25 microg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM2.5 NAAQS of 15 microg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions.     

Atmospheric particulate matter and polycyclic aromatic hydrocarbons for PM10 and size-segregated samples in Bangkok

Air samples of particulate matter (PM) with an aerodynamic diameter less than 10 microm (PM10) were collected from six sites in Bangkok, Thailand, using high-volume air samplers. Daily samples were taken at intervals of 12 days from November 1999 to November 2000. Size-selected sampling using a multislit Andersen size-fractionated cascade impactor was undertaken at one site in central Bangkok to identify particulate size distribution. The annual average PM10 concentration at all six sites exceeded the Thailand National Ambient Air Quality Standard (NAAQS) of 50 microg/m3. The daily PM10 concentrations at heavy traffic roadside areas ranged between 30 and 160 microg/m3. The highest PM10 level occurred during the winter period (November-February), which is the dry season. From our results, which are based on a 1-yr survey, it can be observed that the particulate concentrations are associated with traffic volumes and seasonal factors (temperature and rainfall). The relative importance of size fractions in contributing to PM load is presented and discussed. Twenty polycyclic aromatic hydrocarbons (PAHs) associated with PM have been identified and quantified. The summed PAHs based on the 20 species had an average concentration of 60 ng/m3. Benzo(e)pyrene, indeno(123cd)pyrene, and benzo(ghi)perylene were the major compounds with average concentrations of 8, 10, and 13 ng/m3, respectively. Results indicate that more than 97% of PAHs were found in the small particulate size range of <0.95 microm.     

Particulate composition characteristics under different ambient air quality conditions

Particulate compositions including elemental carbon (EC), organic carbon (OC), water-soluble ionic species, and elemental compositions were investigated during the period from 2004 to 2006 in southern Taiwan. The correlation between the pollutant standard index (PSI) of ambient air quality and the various particle compositions was also addressed in this study. PSI revealed a correlation with fine (r = 0.74) and coarse (r = 0.80) particulate matter (PM). PSI manifested a significant correlation with the amount of analyzed ionic species (r approximately 0.80) in coarse and fine particles and a moderate correlation with carbon content (r = 0.63) in fine particles; however, it showed no correlation with elemental content. Although the ambient air quality ranged from good to moderate, the ionic species including chloride (Cl-), nitrate (NO3-), sulfate (SO4(2-)), sodium (Na+), ammonium (NH4+), magnesium (Mg2+), and calcium (Ca2+) increased significantly (1.5-3.7 times for Daliao and 1.8-6.9 times for Tzouying) in coarse PM. For fine particles, NO3-, SO4(2-), NH4+, and potassium (K+) also increased significantly (1.3-2.4 times for Daliao and 2.8-9.6 times for Tzouying) when the air quality went from good to moderate. For meteorological parameters, temperature evidenced a slightly negative correlation with PM concentration and PSI value, which implied a high PM concentration in the low-temperature condition. This reflects the high frequency of PM episodes in winter and spring in southern Taiwan. In addition, the mixing height increase from 980 to 1450 m corresponds to the air quality condition changing from unhealthy to good.     

Estimation of ambient PM2.5 concentrations in Maryland and verification by measured values

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 microm in aerodynamic diameter (PM23), but did have annual ambient data for PM smaller than 10 microm (PM10) at 24 sites. The PM10 data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM2.5 concentrations at the 24 PM10 monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM2.5 NAAQS of 15 microg/m3, but Maryland's air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM2.5 across central Maryland.     

The relationship between atmospheric pollutant emissions and fuel qualities of inland vessels in Jiangsu Province,China

Air pollution caused by ship exhaust emission is receiving more and more attention. The physical and chemical properties of fuels, such as sulfur content and PAHs content, potentially had a significant influence on air pollutant emissions from inland vessels. In order to investigate the effects of fuel qualities on atmospheric pollutant emissions systematically, a series of experiments was conducted based on the method of actual ship testing. As a result, SO2, PM and NOx emission rates all increased with the increase of main engine rotating speed under cruise mode, while PM and NOx emission factors were inversely proportional to the main engine rotating speed. Moreover, SO2 emission factor changed little with the increase of the main engine rotating speed. In summary, the fuel-dependent specific emission of SO2 was a direct reflection of the sulfur content in fuel. The PM emission increased with the increase of sulfur content and PAHs content in fuel. However, fuel qualities impacted little on NOx emissions from inland vessels because of NOx formation mechanisms and conditions.

Implications: Ship activity is considered to be the third largest source of air pollution in China. In particular, air pollutants emitted from ships in river ports and waterways have a direct impact on regional air quality and pose threat on the health of local residents owing to high pollutants concentration and poor air diffusion. The study on the relationship between air pollutant emissions and fuel quality of inland vessels can provide foundational data for local authority to formulate reasonable and appropriate policies for reducing atmospheric pollution due to inland vessels.     

Emission strength validation using four-dimensional data assimilation: application to primary aerosol and precursors to ozone and secondary aerosol.

Three-dimensional air quality models (AQMs) represent the most powerful tool to follow the dynamics of air pollutants at urban and regional scales. Current AQMs can account for the complex interactions between gas-phase chemistry, aerosol growth, cloud and scavenging processes, and transport. However, errors in model applications still exist due in part to limitations in the models themselves and in part to uncertainties in model inputs. Four-dimensional data assimilation (FDDA) can be used as a top-down tool to validate several of the model inputs, including emissions inventories, based on ambient measurements. Previously, this FDDA technique was used to estimate adjustments in the strength and composition of emissions of gas-phase primary species and O3 precursors. In this paper, we present an extension to the FDDA technique to incorporate the analysis of particulate matter (PM) and its precursors. The FDDA approach consists of an iterative optimization procedure in which an AQM is coupled to an inverse model, and adjusting the emissions minimizes the difference between ambient measurements and model-derived concentrations. Here, the FDDA technique was applied to two episodes, with the modeling domain covering the eastern United States, to derive emission adjustments of domainwide sources of NO., volatile organic compounds (VOCs), CO, SO2, NH3, and fine organic aerosol emissions. Ambient measurements used include gas-phase inorganic and organic species and speciated fine PM. Results for the base-case inventories used here indicate that emissions of SO2 and CO appear to be estimated reasonably well (requiring minor revisions), while emissions of NOx, VOC, NH3, and organic PM with aerodynamic diameter less than 2.5 microm (PM2.5) require more significant revision.     

Semicontinuous PM2.5 sulfate and nitrate measurements at an urban and a rural location in New York: PMTACS-NY summer 2001 and 2002 campaigns

Several collocated semicontinuous instruments measuring particulate matter with particle sizes < or =2.5 microm (PM2.5) sulfate (SO4(2-)) and nitrate (NO3-) were intercompared during two intensive field campaigns as part of the PM2.5 Technology Assessment and Characterization Study. The summer 2001 urban campaign in Queens, NY, and the summer 2002 rural campaign in upstate New York (Whiteface Mountain) hosted an operation of an Aerosol Mass Spectrometer, Ambient Particulate Sulfate and Nitrate Monitors, a Continuous Ambient Sulfate Monitor, and a Particle-Into-Liquid Sampler with Ion Chromatographs (PILS-IC). These instruments provided near real-time particulate SO4(2-) and NO3- mass concentration data, allowing the study of particulate SO4(2-)/NO3- diurnal patterns and detection of short-term events. Typical particulate SO4(2-) concentrations were comparable at both sites (ranging from 0 to 20 microg/m3), while ambient urban particulate NO3- concentrations ranged from 0 to 11 microg/m3 and rural NO3- concentration was typically less than 1 microg/m3. Results of the intercomparisons of the semicontinuous measurements are presented, as are results of the comparisons between the semicontinuous and time-integrated filter-based measurements. The comparisons at both sites, in most cases, indicated similar performance characteristics. In addition, charge balance calculations, based on major soluble ionic components of atmospheric aerosol from the PILS-IC and the filter measurements, indicated slightly acidic aerosol at both locations.     

Screening and Scenarios of Traffic Emissions at Trier,Germany

SCOPE AND BACKGROUND: In the course of the European Council Directive on permissible air pollutant limit values, valid starting from 2005 there is an urgent call for action, particularly for fine dust (PM10). Current investigations (Junk & Helbig 2003, Reuter & Baumüller 2003) show that the limit values in certain places in congested areas are exceeded. Only if it is possible to locate these Hot Spots purposeful measures to reduce the ambient air pollution can be conducted. For an efficient identification of these Hot Spots numerical computer models or establishing special measurements networks are too expensive. Using the statistical model STREET 5.0 (KTT 2003) a cost-effective screening of the air pollution situation caused by the traffic can be done. METHODS: STREET is based on the 3-dimensional micro-scale non-hydrostatic flow- and dispersion model MISCAM (Eichhorn 1989). The results of over 100.000 different calculations with MISCAM are stored in a Database and used to calculate the emissions with STREET. In collaboration with the city council of Trier more than 150 streets were investigated, mapped, and calculated. A special urban climate measuring network supplies the necessary meteorological input data about the wind field and precipitation events in the valley of the Moselle. Information about road width and road orientation as well as building density was derived from aerial photographs. Traffic censuses and mobile air pollutants measurements supplied the remaining input data. We calculated the mean annual air pollutant concentrations for NO2, CO, SO2, O3, benzene as well as PM10. RESULTS: A comparison of the model results with the values obtained from the stations of the central emission measuring network of Rhineland-Palatinate (ZIMEN, annual report 2002) shows very good agreements. The model was not only used to calculate the annual air pollutant but also for urban planning and management. The absolute level of the air pollutant is mainly dependent on the amount of traffic in the street canyons. Therefore four different case-scenarios with varying quantity of traffic were calculated and interpreted for each street. The results of the calculation show that on the basis of the mean values for both NO2 and benzene, it is not to be expected that the limits PERSPECTIVES: Furthermore the model can be used to find the maximum tolerable numbers of cars for a street without exceeding the air pollutant thresholds.     

On the local and regional influence on ground-level ozone concentrations in Hong Kong

Hong Kong is a densely populated city situated in the fast developing Pearl River Delta of southern China. In this study, the recent data on ozone (O3) and related air pollutants obtained at three sites in Hong Kong are analyzed to show the variations of O3 in urban, sub-urban and rural areas and the possible regional influences. Highest monthly averaged O3 was found at a northeastern rural site and lowest O3 level was observed at an urban site. The levels of NOx, CO, SO2 and PM10 showed a different spatial pattern with the highest level in the urban site and lowest at the rural site. Analysis of chemical species ratios such as SO2/NOx and CO/NOx indicated that the sites were under the influences of local and regional emissions to varying extents reflecting the characteristics of emission sources surround the respective sites. Seasonal pattern of O3 is examined. Low O3 level was found in summer and elevated levels occurred in autumn and spring. The latter appears different from the previous result obtained in 1996 indicating a single maximum occurring in autumn. Principal component analysis was used to further elucidate the relationships of air pollutants at each site. As expected, the O3 variation in the northeastern rural area was largely determined by regional chemical and transport processes, while the O3 variability at the southwestern suburban and urban sites were more influenced by local emissions. Despite the large difference in O3 levels across the sites, total potential ozone (O3+NO2) showed little variability. Cases of high O3 episodes were presented and elevated O3 levels were formed under the influence of tropical cyclone bringing in conditions of intense sunlight, high temperature and light winds. Elevated O3 levels were also found to correlate with enhanced ratio of SO2 to NOx, suggesting influence of regional emissions from the adjacent Pearl River Delta region.