Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta,Georgia

Abstract

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, NO_x, and O₃) and fine particulate matter ([PM_2.5] PM_2.5 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 PM_2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO₂, CO, NO_x, 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 rose plots, corrected for diurnal and seasonal pattern effects, are used to demonstrate the impacts of local sources on monitoring station data. The results presented are being used to quantify the impacts of instrument precision and spatial variability on the assessment of health effects of ambient air pollution in Atlanta and are relevant to the interpretation of results from time series health studies that use data from fixed monitors.     

Short-term temporal variation in PM2.5 mass and chemical composition during the Atlanta Supersite Experiment, 1999

Measurements in urban Atlanta of transient aerosol events in which PM2.5 mass concentrations rapidly rise and fall over a period of 3-6 hr are reported. The data are based on new measurement techniques demonstrated at the U.S. Environmental Protection Agency (EPA) Atlanta Supersite Experiment in August 1999. These independent instruments for aerosol chemical speciation of NO3-, SO4(2-), NH4+, and organic and elemental carbon (OC and EC), reconstructed the observed hourly dry PM2.5 mass to within 20% or better. Data from the experiment indicated that transient PM2.5 events were ubiquitous in Atlanta and were typically characterized by a sudden increase of EC (soot) and OC in the early morning or SO4(2-) in the late afternoon. The frequent temporal decoupling of these events provides insights into their origins, suggesting mobile sources in metro Atlanta as the main contributor to early morning PM2.5 and more regionally located point SO2 sources for afternoon PM2.5 events. The transient events may also have health implications. New data suggest that short-term PM2.5 exposures may lead to adverse health effects. Standard integrated filter-based techniques used in PM2.5 compliance monitoring networks and in most past PM2.5 epidemiologic studies collect samples over 24-hr periods and thus are unable to capture these transient events. Moreover, health-effects studies that focus on daily PM2.5 mass alone cannot evaluate the health implications of the unique and variable chemical properties of these episodes.     

A statistical assessment of saturation and mobile sampling strategies to estimate long-term average concentrations across urban areas

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 (NOx), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), 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 NOx. Larger errors, up to 50%, are expected for NO, SO2, PM2.5, 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.     

The Aerosol Research and Inhalation Epidemiology Study (ARIES): PM2.5 mass and aerosol component concentrations and sampler intercomparisons

The Aerosol Research and Inhalation Epidemiology Study (ARIES) was designed to provide high-quality measurements of PM2.5, its components, and co-varying pollutants for an air pollution epidemiology study in Atlanta, GA. Air pollution epidemiology studies have typically relied on available data on particle mass often collected using filter-based methods. Filter-based PM2.5 sampling is susceptible to both positive and negative errors in the measurement of aerosol mass and particle-phase component concentrations in the undisturbed atmosphere. These biases are introduced by collection of gas-phase aerosol components on the filter media or by volatilization of particle phase components from collected particles. As part of the ARIES, we collected daily 24-hr PM2.5 mass and speciation samples and continuous PM2.5 data at a mixed residential-light industrial site in Atlanta. These data facilitate analysis of the effects of a wide variety of factors on sampler performance. We assess the relative importance of PM2.5 components and consider associations and potential mechanistic linkages of PM2.5 mass concentrations with several PM2.5 components. For the 12 months of validated data collected to date (August 1, 1998-July 31, 1999), the monthly average Federal Reference Method (FRM) PM2.5 mass always exceeded the proposed annual average standard (12-month average = 20.3 +/- 9.5 micrograms/m3). The particulate SO4(2-) fraction (as (NH4)2SO4) was largest in the summer and exceeded 50% of the FRM mass. The contribution of (NH4)2SO4 to FRM PM2.5 mass dropped to less than 30% in winter. Particulate NO3- collected on a denuded nylon filter averaged 1.1 +/- 0.9 micrograms/m3. Particle-phase organic compounds (as organic carbon x 1.4) measured on a denuded quartz filter sampler averaged 6.4 +/- 3.1 micrograms/m3 (32% of FRM PM2.5 mass) with less seasonal variability than SO4(2-).     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

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.     

Effectiveness of emission control technologies for auxiliary engines on ocean-going vessels

Large auxiliary engines operated on ocean-going vessels in transit and at berth impact the air quality of populated areas near ports. This paper presents new information on the comparison of emission ranges from three similar engines and the effectiveness of three control technologies: switching to cleaner burning fuels, operating in the low oxides of nitrogen (NOx) mode, and selective catalytic reduction (SCR). In-use measurements of gaseous (NOx, carbon monoxide [CO], carbon dioxide [CO2]) and fine particulate matter (PM2.5; total and speciated) emissions were made on three auxiliary engines on post-PanaMax class container vessels following the International Organization for Standardization-8178-1 protocol. The in-use NOx emissions for the MAN B&W 7L32/40 engine family vary from 15 to 21.1 g/kW-hr for heavy fuel oil and 8.9 to 19.6 g/kW-hr for marine distillate oil. Use of cleaner burning fuels resulted in NOx reductions ranging from 7 to 41% across different engines and a PM2.5 reduction of up to 83%. The NOx reductions are a consequence of fuel nitrogen content and engine operation; the PM2.5 reduction is attributed to the large reductions in the hydrated sulfate and organic carbon (OC) fractions. As expected, operating in the low-NOx mode reduced NOx emissions by approximately 32% and nearly doubled elemental carbon (EC) emissions. However, PM2.5 emission factors were nearly unchanged because the EC emission factor is only approximately 5% of the total PM2.5 mass. SCR reduced the NOx emission factor to less than 2.4 g/kW-hr, but it increased the PM2.5 emissions by a factor of 1.5-3.8. This increase was a direct consequence of the conversion of sulfur dioxide to sulfate emissions on the SCR catalyst. The EC and OC fractions of PM2.5 reduced across the SCR unit.     

Temporal and Spatial Distributions of Ozone in Atlanta: Regulatory and Epidemiologic Implications

ABSTRACT

Relationships between ambient levels of selected air pollutants and pediatric asthma exacerbation in Atlanta were studied retrospectively. As a part of this study, temporal and spatial distributions of ambient ozone concentrations in the 20-county Atlanta metropolitan area during the summers of 1993, 1994, and 1995 were assessed. A universal kriging procedure was used for spatial interpolation of aerometric monitoring station data. In this paper, the temporal and spatial distributions of ozone are described, and regulatory and epidemiologic implications are discussed. For the study period, the Atlanta ozone nonattainment area based on the 1-h, exceedance-based standard of 0.12 ppm is estimated to expand—from 56% of the Atlanta MSA by area and 71% by population to 88% by area and 96% by population—under the new 8-h, concentration-based standard of 0.08 ppm. Regarding asthma exacerbation, a 4% increase in pediatric asthma rate per 20-ppb increase in ambient ozone concentration was observed (p-value = 0.001), with ambient ozone level representing a general indicator of air quality due to its correlations with other pollutants. The use of spatial ozone estimates in the epidemiologic analysis demonstrates the need for control of demographic covariates in spatiotem poral assessments of associations of ambient air pollutant concentrations with health outcome.     

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.     

Spatial/temporal variations of elemental carbon, organic carbon, and trace elements in PM10 and the impact of land-use patterns on community air pollution in Paterson, NJ

An urban community PM10 (particulate matter < or = 10 microm in aerodynamic diameter) air pollution study was conducted in Paterson, NJ, a mixed land-use community that is interspersed with industrial, commercial, mobile, and residential land-use types. This paper examines (1) the spatial/temporal variation of PM10, elemental carbon (EC), organic carbon (OC), and nine elements; and (2) the impact of land-use type on those variations. Air samples were collected from three community-oriented locations in Paterson that attempted to capture industrial, commercial, and mobile source-dominated emissions. Sampling was conducted for 24 hr every 6 days from November 2005 through December 2006. Samples were concurrently collected at the New Jersey Department of Environmental Protection-designated air toxics background site in Chester, NJ. PM10 mass, EC, OC, and nine elements (Ca, Cu, Fe, Pb, Mn, Ni, S, Ti, and Zn) that had more than 50% of samples above detection and known sources or are toxic were selected for spatial/temporal analysis in this study. The concentrations of PM10, EC, OC, and eight elements (except S) were significantly higher in Paterson than in Chester (P < 0.05). The concentrations of these elements measured in Paterson were also found to be higher during winter than the other three seasons (except S), and higher on weekdays than on weekends (except Pb). The concentrations of EC, Cu, Fe, and Zn at the commercial site in Paterson were significantly higher than the industrial and mobile sites; however, the other eight species were not significantly different within the city (P > 0.05). These results indicated that anthropogenic sources of air pollution were present in Paterson. The source apportionment confirmed the impact of vehicular and industrial emissions on the PM10 ambient air pollution in Paterson. The multiple linear regression analysis showed that categorical land-use type was a significant predictor for all air pollution levels, explaining up to 42% of the variability in concentration by land-use type only.     

A study of the association between daily mortality and ambient air pollutant concentrations in Pittsburgh, Pennsylvania

We have studied the possible association of daily mortality with ambient pollutant concentrations (PM10, CO, O3, SO2, NO2, and fine [PM2.5] and coarse PM) and weather variables (temperature and dew point) in the Pittsburgh, PA, area for two age groups--less than 75, and 75 and over--for the 3-year period of 1989-1991. Correlation functions among pollutant concentrations show important seasonal dependence, and this fact necessitates the use of seasonal models to better identify the link between ambient pollutant concentrations and daily mortality. An analysis of the seasonal model results for the younger-age group reveals significant multicollinearity problems among the highly correlated concentrations of PM10, CO, and NO2 (and O3 in spring and summer), and calls into question the rather consistent results of the single- and multi-pollutant non-seasonal models that show a significant positive association between PM10 and daily mortality. For the older-age group, dew point consistently shows a significant association with daily mortality in all models. Collinearity problems appear in the multi-pollutant seasonal and non-seasonal models such that a significant, positive PM10 coefficient is accompanied by a significant, negative coefficient of another ambient pollutant, and the identity of this other pollutant changes with season. The PM2.5 data set is half that of PM10. Identical-model runs for both data sets reveal instability in the pollutant coefficients, especially for the younger age group. The concern for the instability of the pollutant coefficients due to a small signal-to-noise ratio makes it impossible to ascertain credibly the relative associations of the fine- and coarse-particle modes with daily mortality. In this connection, we call for caution in the interpretation of model results for causal inference when the models use fully or partially estimated PM values to fill large data gaps.     

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.     

Fine and coarse particulate matter chemical characterization in a heavily industrialized city in central Mexico during Winter 2003

This paper presents the results of the first reported study on fine particulate matter (PM) chemical composition at Salamanca, a highly industrialized urban area of Central Mexico. Samples were collected at six sites within the urban area during February and March 2003. Several trace elements, organic carbon (OC), elemental carbon (EC), and six ions were analyzed to characterize aerosols. Average concentrations of PM with aerodynamic diameter of less than 10 microm (PM10) and fine PM with aerodynamic diameter of less than 2.5 microm (PM2.5) ranged from 32.2 to 76.6 [g m(-3) and 11.1 to 23.7 microg m(-3), respectively. OC (34%), SO4= (25.1%), EC (12.9%), and geological material (12.5%) were the major components of PM2.5. For PM10 geological material (57.9%), OC (17.3%), and SO4= (9.7%) were the major components. Coarse fraction (PM,, -PM2.5), geological material (81.7%), and OC (8.6%) were the dominant species, which amounted to 90.4%. Correlation analysis showed that sulfate in PM2.5 was present as ammonium sulfate. Sulfate showed a significant spatial variation with higher concentrations to the north resulting from predominantly southwesterly winds above the surface layer and by major SO2 sources that include a power plant and refinery. At the urban site of Cruz Roja it was observed that PM2.5 mass concentrations were similar to the submicron fraction concentrations. Furthermore, the correlation between EC in PM2.5 and EC measured from an aethalometer was r(2) = 0.710. Temporal variations of SO2 and nitrogen oxide were observed during a day when the maximum concentration of PM2.5 was measured, which was associated with emissions from the nearby refinery and power plant. From cascade impactor measurements, the three measured modes of airborne particles corresponded with diameters of 0.32, 1.8, and 5.6 microm.     

Spatial and temporal variability of ambient air toxics data

This paper summarizes information on the spatial and temporal variability of selected air toxics pollutants collected on a national basis primarily for a period encompassing 1990-2003. Spatial information on pollutant concentrations is characterized in terms of within-city and between-city variability. Temporal information is summarized as diurnal and seasonal variability and in multiyear trends. The information on variability is presented in the framework of a larger need for systematic documentation of information on air toxics pollutants to assess progress in air pollution control programs.     

Daily mortality and air pollution in The Netherlands

We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models. Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM10 concentration by 100 micrograms/m3 was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM10, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO2 and NO2. Aerosol SO4(-2), NO3-, and BS were more consistently associated with total mortality than was PM10. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM10 was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas.     

Defining the photochemical contribution to particulate matter in urban areas using time-series analysis

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O3 (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM10 (PM with less than 10 microm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O3, NO or NO2, CO, and SO2. Approximately 3 years of daily average PM10, daily maximum 8-hr average O3 and CO, daily 24-hr average SO2 and NO2, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O3, PM10, NO, NO2, CO, and SO2 series. Cross correlations between PM10 (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM10 and that O3 is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM10 is defined for an urban location, the effect of an O3-control strategy on PM concentrations is estimated by calculating daily PM10 concentrations with reduced O3 concentrations. Forecasted summertime PM10 reductions resulting from a 5 percent decrease in ambient O3 range from 1.2 microg/m3 (3.03%) in Chicago to 3.9 microg/m3 (7.65%) in Phoenix.     

Furnace Sorbent Injection

Abstract

This paper summarizes information on the spatial and temporal variability of selected air toxics pollutants collected on a national basis primarily for a period encompassing 1990–2003. Spatial information on pollutant concentrations is characterized in terms of within-city and between-city variability. Temporal information is summarized as diurnal and seasonal variability and in multiyear trends. The information on variability is presented in the framework of a larger need for systematic documentation of information on air toxics pollutants to assess progress in air pollution control programs.     

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.