A New Method for Determining the Contribution of a Refinery to Local SO2 Levels in an Industrial Region

A new method was developed for determining the contribution of one pollutant source to the air quality in an industrialized region. Although the method is general, it is presented in reference to a 130,000 bbl/day petroleum refinery and its effect on ambient SO₂ concentrations in Sarnia, Ontario. The plumes from SO₂ emitters located upwind of the refinery were represented by a single hypothetical plume which influences monitoring stations located upwind as well as downwind from the refinery. However, the refinery emissions affect only the downwind stations. A simple equation was derived by means of which the concentration at the downwind station could be calculated from the concentration at the upwind station and the refinery emission. This equation contains two coefficients A and B which were evaluated such that the difference between the cumulative frequency distributions of the measured and calculated SO₂ concentrations at the downwind station was minimized. For the meteorological conditions and monitoring stations considered, it was found that the refinery contributed less than 4.5 pphm to ambient SO₂ concentrations over 1 hr periods. This result and the validity of the method are discussed.     

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.     

Factors Influencing the Variability of SO2 Concentrations in Istanbul

ABSTRACT

The correlation between sulfur dioxide (SO₂) concentrations measured at the European and Asian sides of Istanbul and meteorological parameters is investigated using principal component analysis (PCA) and multiple regression analysis techniques. Several meteorological parameters are selected to represent the atmospheric conditions during two winter periods: 1993–1994 and 1994–1995. Six principal components are found to explain the majority of the observed meteorological variability. Surface pressure, 850-mb temperature, and surface zonal (east-west) and meridional (north-south) winds show high loadings on separate factors identified by PCA. We seek dominant meteorological parameters that control the SO₂ levels at each monitoring station. Several multiple regression analysis models are fitted to the data from each monitoring station using six principal components and previous day SO₂ concentrations as independent variables.

Results suggest that the most important parameters, highly correlated with SO₂ concentrations in the Istanbul metropolitan area, are atmospheric pressure and surface zonal and meridional winds. These components have more influence on the determination of the air pollution levels at the Asian side than at the European side.     

Transport of SO2 and aerosol over the Yellow sea

Aircraft measurements of air pollutants were made to investigate the characteristic features of long-range transport of sulfur compounds over the Yellow Sea for the periods of 26–27 April and 7–10 November in 1998, and 9–11 April and 19 June in 1999, together with aerosol measurements at the Taean background station in Korea. The overall mean concentrations of SO₂, O₃ and aerosol number in the boundary layer for the observation period ranged 0.1–7.4 ppb 32.1–64.1 ppb and 1.0–143.6 cm⁻³, respectively. It was found that the air mass over the Yellow Sea had a character of both the polluted continental air and clean background air, and the sulfur transport was mainly confined in the atmospheric boundary layer. The median of SO₂ concentration within the boundary layer was about 0.1–2.2 ppb. However, on 8 November, 1998, the mean concentrations of SO₂ and aerosol number increased up to 7.4 ppb and 109.5 cm⁻³, respectively, in the boundary layer, whereas O₃ concentration decreased remarkably. This enhanced SO₂ concentration occurred in low level westerly air stream from China to Korea. Aerosol analyses at the downstream site of Taean in Korea showed 2–3 times higher sulfate concentration than that of other sampling days, indicating a significant amount of SO₂ conversion to non sea-salt sulfate during the long-range transport.     

Behavior of particulate matter during high concentration episodes in Seoul

The behavior of particulate matter (PM) during high-concentration episodes was investigated using monitoring data from Guui station, a comprehensive air monitoring station in Seoul, Korea, from January 2008 to March 2010. Five non-Asian dust (ND) episodes and two Asian dust (AD) episodes of high PM concentrations were selected for the study. During the ND episode, primary air pollutants accumulated due to low wind speeds, and PM_2.5 increased along with most other air pollutants. Particles larger than PM_2.5 were also high since these particles were generated by vehicular traffic rather than wind erosion. During strong AD episodes, PM_10–2.5 primarily increased and gaseous primary air pollutants decreased under high wind speeds. However, even during the AD episode, PM_2.5 and gaseous primary air pollutants increased when the effects of AD were weak and wind speeds were low. This study corroborates that accumulation of air pollutants due to a drop in surface wind speed plays an important role in short-term high-concentration occurrences. However, low wind speeds could not be directly linked to local emissions because a significant portion of accumulated air pollutants resulted from long-range transport.     

Estimates of community exposure and health risk to sulfur dioxide from power plant emissions using short-term mobile and stationary ambient air monitoring

To estimate plausible health effects associated with peak sulfur dioxide (SO₂) levels from three coal-fired power plants in the Baltimore, Maryland, area, air monitoring was conducted between June and September 2013. Historically, the summer months are periods when emissions are highest. Monitoring included a 5-day mobile and a subsequent 61-day stationary monitoring study. In the stationary monitoring study, equipment was set up at four sites where models predicted and mobile monitoring data measured the highest average concentrations of SO₂. Continuous monitors recorded ambient concentrations each minute. The 1-min data were used to calculate 5-min and 1-hr moving averages for comparison with concentrations from clinical studies that elicited lung function decrement and respiratory symptoms among asthmatics. Maximum daily 5-min moving average concentrations from the mobile monitoring study ranged from 70 to 84 ppb (183–220 µg/m³), and maximum daily 1-hr moving average concentrations from the mobile monitoring study ranged from 15 to 24 ppb (39–63 µg/m³). Maximum 5-min moving average concentrations from stationary monitoring ranged from 39 to 229 ppb (102–600 µg/m³), and maximum daily 1-hr average concentrations ranged from 15 to 134 ppb (40–351 µg/m³). Estimated exposure concentrations measured in the vicinity of monitors were below the lowest levels that have demonstrated respiratory symptoms in human clinical studies for healthy exercising asthmatics. Based on 5-min and 1-hr monitoring, the exposure levels of SO₂ in the vicinity of the C.P. Crane, Brandon Shores, and H.A. Wagner power plants were not likely to elicit respiratory symptoms in healthy asthmatics.

Implications: Mobile and stationary air monitoring for SO₂ were conducted to quantify short-term exposure risk, to the surrounding community, from peak emissions of three coal-fired power plants in the Baltimore area. Concentrations were typically low, with only a few 5-min averages higher than levels indicated during clinical trials to induce changes in lung capacity for healthy asthmatics engaged in exercise outdoors.     

Assessment of ambient air quality in the port of Naples

Two experimental monitoring campaigns were carried out in 2012 to investigate the air quality in the port of Naples, the most important in southern Italy for traffic of passengers and one of the most important for goods. Therefore, it represents an important air pollution source located close to the city of Naples. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and BTEX (benzene, toluene, ethylbenzene, and xylenes) in the air were measured at 15 points inside the Naples port area through the use of passive samplers. In addition, a mobile laboratory was positioned in a fixed point inside the port area to measure continuous concentration of pollutants together with particulate matter, ambient parameters, and wind direction and intensity. The pollution levels monitored were compared with those observed in the urban area of Naples and in other Mediterranean ports. Even though the observation time was limited, measured concentrations were also compared with limit values established by European legislation. All the measured pollutants were below the limits with the exception of nitrogen dioxide: its average concentration during the exposition time exceeded the yearly limit value. A spatial analysis of data, according to the measured wind direction and intensity, provided information about the effects that ship emissions have on ambient air quality in the port area. The main evidence indicates that ship emissions influence sulfur dioxide concentration more than any other pollutants analyzed.

Implications: Two monitoring campaigns were carried out to measure BTEX, SO₂, NO₂, and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) air concentrations in the port of Naples. NO₂ hourly average and PM₁₀ daily average comply with European legislative standards. Spatial variation of pollutants long the axis corresponding to the prevailing wind direction seems to indicate a certain influence of ship emissions for SO₂. For NO₂ and PM₁₀, a correlation between concentrations in the harbor and those measured by the air quality monitoring stations sited in the urban area of Naples was observed, indicating a possible contribution of the near road traffic to the air pollution in the port of Naples.     

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.     

Evaluation of the effect of long-range transport of air pollutants on coastal atmospheric monitoring sites in and around Taiwan

Long-range transport of pollution outflow from Asian mainland has been noticed and expected to play a significant role in Pacific background. Since 1993 the Taiwanese Environmental Protection Administration (TEPA) is conducting ground-based observations of various particulate and gaseous pollutants at 74 monitoring stations in Taiwan. One of these stations, Heng-Chun at the south coast of Taiwan can be considered as a background station with only negligible amounts of local pollution, and another one, Wan-Li at the north coast, predominantly receives air that has not passed over Taiwan, so that background air can be analysed by means of sectorisation. In this work, the sectorised 13-year time series of measurements of CO, SO₂, O₃, NO_x and PM₁₀, from the Wan-Li station are presen and compared to data from the Heng-Chun station and another TEPA background station off the coast of mainland China, Ma-Zu. The CO and O₃ measurements are also compared to data from the Yonaguni station, a Pacific island site, part of the Global Atmospheric Watch (GAW) network.The similarity of the sectorised data from the Wan-Li station with the data of the other station indicates that atmospheric measurements from the Wan-Li site can be used to make inferences about trends in western Pacific background air pollution and the effect of long-range transport of pollutants. The measurement time series from 1993 to 2006 do not indicate a significant trend in the monthly mean O₃ concentrations in accordance with other research about ozone in tropical latitudes. An increasing trend in CO concentrations of 2.8% per annum is observed between 1999 and 2006 for long-range transport to northern Taiwan, and a doubling of the SO₂ and NO_x concentrations observed at the Wan-Li and Heng-Chun sites within the period 2001–2006. SO₂ concentrations are found to quadruple at Ma-Zu within the same period. The data suggest that pollution from the Asian mainland enhances significantly the background air pollution over the Pacific.     

Effect of wind speed on the atmospheric levels of particles produced by traditional and non traditional sources on the island of curacao

The TSP, SO₄⁼ and Pb levels observed downwind of a large refinery and in the city of Willemstad in Curaçao are presented. The results show that wiht increasing wind speed TSP and SO₄⁼ levels increase while Pb levels decrease. On the other hand, at relatively constant wind speeds a good correlation between TSP and Pb was observed.The correlation observed between TSP, SO₄⁼ and Pb and the wind speed, the effect of rain on the atmospheric levels observed during the sampling period, the lack of secondary pollutants (e.g. ozone, NO₃^?) and the composition of the island background air, allow us to conclude that the SO₄⁼ measured at the monitoring sites is mainly produced as a primary pollutant in the refinery, the high atmospheric TSP levels are due to refinery emissions (traditional source) and the recirculation of street dust particles (non traditional source) produced by traffic and the predominantly high wind velocity.The implication on air quality and control measures are discussed.     

Air Pollution Control and Waste Management in a New World

Abstract

A research site for atmospheric chemistry and air pollution measurements was established at Pinnacle State Park in Addison, NY, in 1995. This paper presents an overview of the site characteristics and measurement program, as well as monthly average concentrations for many of the trace gas and aerosol pollutants over the full measurement period. Monthly averaged ozone concentrations range from values as low as 15 parts per billion (ppb) during cold-season months, to values approaching 50 ppb during some spring and summer months. Sulfur dioxide (SO₂), oxides of nitrogen (NO_x), and reactive odd nitrogen (NO_y) all show distinct seasonal variation, with summertime monthly averages as low as 1–3 ppb, and wintertime monthly averages from 6–12 ppb. The variation in carbon monoxide (CO) is much smaller, with minimums of approximately 150 ppb and maximums only rarely exceeding 250 ppb. Data for three hydrocarbon species propane, benzene, and isoprene—are presented. Propane and benzene show higher monthly averaged concentrations in the winter and lower values in the summer, with values ranging over a factor of 4–5. Isoprene, on the other hand has much higher values during the summer season, sometimes a factor of 10 or more greater than concentrations measured in the winter. Monthly averaged plots for fine particulate matter (PM_2.5) beginning in 1999 show a robust summer maximum and winter minimum, and roughly a factor of two difference between the two. An empirical measure of ozone production using the correlation of hour-averaged ozone and NO_y data illustrates relatively robust ozone production during some, but not all, summertime months over the time period. Also, an analysis of the frequency distribution of the hours of maximum ozone concentration shows a strong mid-afternoon peak, as expected, but also a prominent secondary maximum centered around midnight. The secondary peak is interpreted as ozone transported from ozone-producing areas to the west, including Buffalo, Cleveland, Pittsburgh, and the Ohio Valley. Finally, SO₂ concentrations as a function of wind direction clearly indicate maximum impacts when the winds are out of the south (Pittsburgh and Philadelphia), with a secondary peak when the winds are from the north-northeast, consistent with the locations of major SO₂ emission sources in the region.     

Long-term trends in airborne SO2 in an air quality monitoring station in Seoul,Korea, from 1987 to 2013

Atmospheric concentration of sulfur dioxide (SO₂) was intermittently measured at an air quality monitoring (AQM) station in the Yong-san district of Seoul, Korea, between 1987 and 2013. The SO₂ level was compared with other important pollutants concurrently measured, including methane (CH₄), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), ozone (O₃), and particulate matter (PM₁₀). If split into three different periods (period 1, 1987–1988, period 2, 1999–2000, and period 3, 2004–2013), the respective mean [SO₂] values (6.57 ± 4.29, 6.30 ± 2.44, and 5.29 ± 0.63 ppb) showed a slight reduction across the entire study period. The concentrations of SO₂ are found to be strongly correlated with other pollutants such as CO (r = 0.614, p = 0.02), which tracked reductions in reported emissions due to tighter emissions standards enacted by the South Korean government. There was also a clear seasonal trend in the SO₂ level, especially in periods 2 and 3, reflecting the combined effects of domestic heating by coal briquettes and meteorological conditions. Although only a 16% concentration reduction was achieved during the 27-year study duration, this is significant if one considers rapid urbanization, an 83.2% increase in population, and rapid industrialization that took place during that period.

Implications: Since 1970, a network of air quality monitoring (AQM) stations has been operated by the Korean Ministry of Environment (KMOE) for routine nationwide monitoring of air pollutant concentrations in urban/suburban areas. To date, the information obtained from these stations has provided a platform for analyzing long-term trends of major pollutant species. In this study, we examined the long-term trends of SO₂ levels and relevant environmental parameters monitored continuously in the Yong-san district of Seoul between 1987 and 2013. The data were analyzed over various time scales (i.e., monthly, seasonal, and annual intervals). The results obtained from this study will allow us to assess the effectiveness of abatement strategy and to predict future concentrations trends in association with future abatement strategies and technologies.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Assessment of yield losses in tropical wheat using open top chambers

The present study deals with the evaluation of effects of ambient gaseous air pollution on wheat (Triticum aestivum L. var. HUW-234) growing in a suburban area situated in eastern Gangetic plain of India, using open top chambers. Eight hourly air monitoring was conducted for ambient concentrations of SO₂, NO₂ and O₃ in filtered chambers (FCs), non-filtered chambers (NFCs) and open plots (OPs). Various morphological, physiological and biochemical parameters were assessed during different developmental stages and finally yield parameters were quantified at the time of harvest.Mean concentrations of SO₂, NO₂ and O₃ were 8.4, 39.9 and 40.1 ppb, respectively during the experiment in NFCs. Concentrations of SO₂, NO₂ and O₃ reduced by 74.6%, 84.7% and 90.4%, respectively in FCs as compared to NFCs. Plants grown in FCs showed higher photosynthetic rate, stomatal conductance, chlorophyll content and Fv/Fm ratio as compared to the plants in NFCs and OPs. Lipid peroxidation, proline, total phenol and ascorbic acid contents and peroxidase activity were higher in plants grown in NFCs. There were improvements in morphological parameters of plants growing in FCs as compared to those in NFCs and OPs. Yield of plants also increased significantly in FCs as compared to those ventilated with ambient air (NFCs) or grown in OPs. During the vegetative phase, NO₂ concentrations were higher than O₃, but O₃ became dominant pollutant during the time of grain setting and filling. The study concludes that O₃ and NO₂ are the main air pollutants in the sub-urban areas causing significant yield reductions in tropical wheat plants.     

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi,Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th–March 31st) and during the partial lockdown (April 1st–April 22nd) with “current” data obtained in 2020 and “historical” data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

     

A prediction-based approach to modelling temporal and spatial variability of traffic-related air pollution in Montreal, Canada

Concentrations of traffic-related air pollution can be highly variable at the local scale and can have substantial seasonal variability. This study was designed to provide estimates of intra-urban concentrations of ambient nitrogen dioxide (NO₂) in Montreal, Canada, that would be used subsequently in health studies of chronic diseases and long-term exposures to traffic-related air pollution. We measured concentrations of NO₂ at 133 locations in Montreal with passive diffusion samplers in three seasons during 2005 and 2006. We then used land use regression, a proven statistical prediction method for describing spatial patterns of air pollution, to develop separate estimates of spatial variability across the city by regressing NO₂ against available land-use variables in each of these three periods. We also developed a “pooled” model across these sampling periods to provide an estimate of an annual average. Our modelling strategy was to develop a predictive model that maximized the model R². This strategy is different from other strategies whose goal is to identify causal relationships between predictors and concentrations of NO₂.Observed concentrations of NO₂ ranged from 2.6 ppb to 31.5 ppb, with mean values of 12.6 ppb in December 2005, 14.0 ppb in May 2006, and 8.9 ppb in August 2006. The greatest variability was observed during May. Concentrations of NO₂ were highest downtown and near major highways, and they were lowest in the western part of the city. Our pooled model explained approximately 80% of the variability in concentrations of NO₂. Although there were differences in concentrations of NO₂ between the three sampling periods, we found that the spatial variability did not vary significantly across the three sampling periods and that the pooled model was representative of mean annual spatial patterns.     

Urban and rural ozone concentrations in Alberta,Canada

Ozone concentrations in Alberta cities typically exhibit a maximum in May (up to 35 ppb) and a minimum in November (as low as 4 ppb). This behaviour is similar to that of rural Alberta O₃ concentrations. Annual O₃ concentrations at six urban monitoring stations vary from 11 ppb to 22 ppb and are about one-half the values at rural stations. In winter, urban O₃ concentrations are always smaller than rural concentrations and the cities act as sinks for O₃. Although urban stations do not exceed Canada's maximum acceptable levels of daily (25 ppb) and annual (15 ppb) O₃ concentrations as often as rural stations, the frequency is still quite large. Canada's hourly maximum desirable level (50 ppb) is exceeded 11 times more often at the remote (rural) station than at the downtown (urban) stations.     

Predicting ozone levels

This paper presents a statistical model that is capable of predicting ozone levels from precursor concentrations and meteorological conditions during daylight hours in the Shuaiba Industrial Area (SIA) of Kuwait. The model has been developed from ambient air quality data that was recorded for one year starting from December 1994 using an air pollution mobile monitoring station. The functional relationship between ozone level and the various independent variables has been determined by using a stepwise multiple regression modelling procedure. The model contains two terms that describe the dependence of ozone on nitrogen oxides (NOx) and nonmethane hydrocarbon precursor concentrations, and other terms that relate to wind direction, wind speed, sulphur dioxide (SO₂) and solar energy. In the model, the levels of the precursors are inversely related to ozone concentration, whereas SO₂ concentration, wind speed and solar radiation are positively correlated. Typically, 63 % of the variation in ozone levels can be explained by the levels of NOx. The model is shown to be statistically significant and model predictions and experimental observations are shown to be consistent. A detailed analysis of the ozone-temperature relationship is also presented; at temperatures less than 27 °C there is a positive correlation between temperature and ozone concentration whereas at temperatures greater than 27 °C a negative correlation is seen. This is the first time a non-monotonic relationship between ozone levels and temperature has been reported and discussed.     

Assessment of a regulatory model's performance relative to large spatial heterogeneity in observed ozone in Houston,Texas

In Houston, some of the highest measured 8-hr ozone (O₃) peaks are characterized by sudden increases in observed concentrations of at least 40 ppb in 1 hr, or 60 ppb in 2 hr. Measurements show that these large hourly changes appear at only a few monitors and span a narrow geographic area, suggesting a spatially heterogeneous field of O₃ concentrations. This study assessed whether a regulatory air quality model (AQM) can simulate this observed behavior. The AQM did not reproduce the magnitude or location of some of the highest observed hourly O₃ changes, and it also failed to capture the limited spatial extent. On days with measured large hourly changes in O₃ concentrations, the AQM predicted high O₃ over large regions of Houston, resulting in overpredictions at several monitors. This analysis shows that the model can make high O₃, but on these days the predicted spatial field suggests that the model had a different cause. Some observed large hourly changes in O₃ concentrations have been linked to random releases of industrial volatile organic compounds (VOCs). In the AQM emission inventory, there are several emission events when an industrial point source increases VOC emissions in excess of 10,000 mol/hr. One instance increased predicted downwind O₃ concentrations up to 25 ppb. These results show that the modeling system is responsive to a large VOC release, but the timing and location of the release, and meteorological conditions, are critical requirements. Attainment of the O₃ standard requires the use of observational data and AQM predictions. If the large observed hourly changes are indicative of a separate cause of high O₃, then the model may not include that cause, which might result in regulators enacting control strategies that could be ineffective.

Implications To show the attainment of the O₃ standard, the U.S. Environmental Protection Agency (EPA) requires the use of observations and model predictions under the assumption that simulations are capable of reproducing observed phenomena. The regulatory model is unable to reproduce observed behavior measured in the observational database. If the large observed hourly changes were indicative of a separate cause of high O₃, then the model would not include that cause. Inaccurate model predictions may prompt air quality regulators to enact control strategies that are effective in the modeling system, but prove ineffective in the real world.     

Particulate matter sources on an hourly timescale in a rural community during the winter

Particulate matter (PM) sources at four different monitoring sites in Alexandra, New Zealand, were investigated on an hourly timescale. Three of the sites were located on a horizontal transect, upwind, central, and downwind of the general katabatic flow pathway. The fourth monitoring site was located at the central site, but at a height of 26 m, using a knuckleboom, when wind conditions permitted. Average hourly PM₁₀ (PM with an aerodynamic diameter <10 μm) concentrations in Alexandra showed slightly different diurnal profiles depending on the sampling site location. Each location did, however, feature a large evening peak and smaller morning peak in PM₁₀ concentrations. The central site in Alexandra experienced the highest PM₁₀ concentrations as a result of PM transport along a number of katabatic flow pathways. A significant difference in PM₁₀ concentrations between the central and elevated sites indicated that a shallow inversion layer formed below the elevated site, limiting the vertical dispersion of pollutants. Four PM₁₀ sources were identified at each of the sites: biomass combustion, vehicles, crustal matter, and marine aerosol. Biomass combustion was identified as the most significant source of PM₁₀, contributing up to 91% of the measured PM₁₀. Plots of the average hourly source contributions to each site revealed that biomass combustion was responsible for both the evening and morning peaks in PM₁₀ concentrations observed at each of the sites, suggesting that Alexandra residents were relighting their fires when they rose in the morning. The identification of PM sources on an hourly timescale can have significant implications for air quality management.

Implications: Monitoring the sources of PM₁₀ on an hourly timescale at multiple sites within an airshed provides extremely useful information for air quality management. Sources responsible for observed peaks in measured diurnal PM₁₀ concentration profiles can be easily identified and targeted for reduction. Also, hourly PM₁₀ sampling can provide crucial information on the role meteorology plays in the development of elevated PM₁₀ concentrations.