Real-time bias-adjusted O3 and PM2.5 air quality index forecasts and their performance evaluations over the continental United States

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA’s North American Mesoscale (NAM) meteorological model with EPA’s Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2.5) forecasts over the continental United States (CONUS) during 2008. This paper describes the implementation of a real-time Kalman Filter (KF) bias-adjustment technique to improve the accuracy of O₃ and PM_2.5 forecasts at discrete monitoring locations. The operational surface-level O₃ and PM_2.5 forecasts from the NAQFC system were post-processed by the KF bias-adjusted technique using near real-time hourly O₃ and PM_2.5 observations obtained from EPA’s AIRNow measurement network. The KF bias-adjusted forecasts were created daily, providing 24-h hourly bias-adjusted forecasts for O₃ and PM_2.5 at all AIRNow monitoring sites within the CONUS domain. The bias-adjustment post-processing implemented in this study requires minimal computational cost; requiring less than 10 min of CPU on a single processor Linux machine to generate 24-h hourly bias-adjusted forecasts over the entire CONUS domain.The results show that the real-time KF bias-adjusted forecasts for both O₃ and PM_2.5 have performed as well as or even better than the previous studies when the same technique was applied to the historical O₃ and PM_2.5 time series from archived AQF in earlier years. Compared to the raw forecasts, the KF forecasts displayed significant improvement in the daily maximum 8-h O₃ and daily mean PM_2.5 forecasts in terms of both discrete (i.e., reduced errors, increased correlation coefficients, and index of agreement) and categorical (increased hit rate and decreased false alarm ratio) evaluation metrics at almost all locations during the study period in 2008.     

Results from a pilot-scale air quality study in Addis Ababa, Ethiopia

Twenty-one samples were collected during the dry season (26 January–28 February 2004) at 12 sites in and around Addis Ababa, Ethiopia and analyzed for particulate matter with aerodynamic diameter <10 μm (PM₁₀) mass and composition. Teflon-membrane filters were analyzed for PM₁₀ mass and concentrations of 40 elements. Quartz-fiber filters were analyzed for chloride, sulfate, nitrate, and ammonium ions as well as elemental carbon (EC) and organic carbon (OC) content. Measured 24-h PM₁₀ mass concentrations were <100 and 40 μg m⁻³ at urban and suburban sites, respectively. PM₁₀ lead concentrations were <0.1 μg m⁻³ for all samples collected, an important finding because the government of Ethiopia had stopped the distribution of leaded gasoline a few months prior to this study. Mass concentrations reconstructed from chemical composition indicated that 34–66% of the PM₁₀ mass was due to geologically derived material, probably owing to the widespread presence of unpaved roads and road shoulders. At urban sites, EC and OC compounds contributed between 31% and 60% of the measured PM₁₀ while at suburban sites carbon compounds contributed between 24% and 26%. Secondary sulfate aerosols were responsible for <10% of the reconstructed mass in urban areas but as much as 15% in suburban sites, where PM₁₀ mass concentrations were lower. Non-volatile particulate nitrate, a lower limit for atmospheric nitrate, constituted <5% and 7% of PM₁₀ at the urban and suburban sites, respectively. At seven of the 12 sites, real-time PM₁₀ mass, real-time carbon monoxide (CO), and instantaneous ozone (O₃) concentrations were measured with portable nephelometers, electrochemical analyzers, and indicator test sticks, respectively. Both PM₁₀ and CO concentrations exhibited daily maxima around 7:00 and secondary peaks in the late afternoon and evening, suggesting that those pollutants were emitted during periods associated with motor-vehicle traffic, food preparation, and heating of homes. The morning concentration maxima were likely accentuated by stable atmospheric conditions associated with overnight surface temperature inversions. Ozone concentrations were measured near mid-day on filter sample collection days and were in all cases <45 parts per billion.     

Sensitivity of ozone to summertime climate in the eastern USA: A modeling case study

The goal of this modeling study is to determine how concentrations of ozone respond to changes in climate over the eastern USA. The sensitivities of average ozone concentrations to temperature, wind speed, absolute humidity, mixing height, cloud liquid water content and optical depth, cloudy area, precipitation rate, and precipitating area extent are investigated individually. The simulation period consists of July 12–21, 2001, during which an ozone episode occurred over the Southeast. The ozone metrics used include daily maximum 8 h average O₃ concentration and number of grid cells exceeding the US EPA ambient air-quality standard. The meteorological factor that had the largest impact on both ozone metrics was temperature, which increased daily maximum 8 h average O₃ by 0.34 ppb K⁻¹ on average over the simulation domain. Absolute humidity had a smaller but appreciable effect on daily maximum 8 h average O₃ (−0.025 ppb for each percent increase in absolute humidity). While domain-average responses to changes in wind speed, mixing height, cloud liquid water content, and optical depth were rather small, these factors did have appreciable local effects in many areas. Temperature also had the largest effect on air-quality standard exceedances; a 2.5 K temperature increase led to a 30% increase in the area exceeding the EPA standard. Wind speed and mixing height also had appreciable effects on ozone air-quality standard exceedances.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.     

Source apportionment of emissions from light-duty gasoline vehicles and other sources in the United States for ozone and particulate matter

Federal Tier 3 motor vehicle emission and fuel sulfur standards have been promulgated in the United States to help attain air quality standards for ozone and PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm). The authors modeled a standard similar to Tier 3 (a hypothetical nationwide implementation of the California Low Emission Vehicle [LEV] III standards) and prior Tier 2 standards for on-road gasoline-fueled light-duty vehicles (gLDVs) to assess incremental air quality benefits in the United States (U.S.) and the relative contributions of gLDVs and other major source categories to ozone and PM_2.5 in 2030. Strengthening Tier 2 to a Tier 3-like (LEV III) standard reduces the summertime monthly mean of daily maximum 8-hr average (MDA8) ozone in the eastern U.S. by up to 1.5 ppb (or 2%) and the maximum MDA8 ozone by up to 3.4 ppb (or 3%). Reducing gasoline sulfur content from 30 to 10 ppm is responsible for up to 0.3 ppb of the improvement in the monthly mean ozone and up to 0.8 ppb of the improvement in maximum ozone. Across four major urban areas—Atlanta, Detroit, Philadelphia, and St. Louis—gLDV contributions range from 5% to 9% and 3% to 6% of the summertime mean MDA8 ozone under Tier 2 and Tier 3, respectively, and from 7% to 11% and 3% to 7% of the maximum MDA8 ozone under Tier 2 and Tier 3, respectively. Monthly mean 24-hr PM_2.5 decreases by up to 0.5 μg/m³ (or 3%) in the eastern U.S. from Tier 2 to Tier 3, with about 0.1 μg/m³ of the reduction due to the lower gasoline sulfur content. At the four urban areas under the Tier 3 program, gLDV emissions contribute 3.4–5.0% and 1.7–2.4% of the winter and summer mean 24-hr PM_2.5, respectively, and 3.8–4.6% and 1.5–2.0% of the mean 24-hr PM_2.5 on days with elevated PM_2.5 in winter and summer, respectively.

Implications: Following U.S. Tier 3 emissions and fuel sulfur standards for gasoline-fueled passenger cars and light trucks, these vehicles are expected to contribute less than 6% of the summertime mean daily maximum 8-hr ozone and less than 7% and 4% of the winter and summer mean 24-hr PM_2.5 in the eastern U.S. in 2030. On days with elevated ozone or PM_2.5 at four major urban areas, these vehicles contribute less than 7% of ozone and less than 5% of PM_2.5, with sources outside North America and U.S. area source emissions constituting some of the main contributors to ozone and PM_2.5, respectively.     

Characterization and Identification of Trends in Average Ambient Ozone and Fine Particulate Matter Levels through Trajectory Cluster Analysis in Eastern Canada

Abstract

In many locations in Eastern Canada, ambient levels of fine particulate matter (PM_2.5) and surface ozone (O₃) depend on airflow direction and synoptic scale meteorological conditions. In this study, a cluster analysis was performed on 10 yr (1994 –2003) of back-trajectory data for 11 locations in Eastern Canada, resulting in the identification of 10 unique back-trajectory clusters (or airflows) for each location. The airflows were then used to characterize and identify spatial and temporal trends in the daily maximum 8-hr average O₃ (dmax 8-hr O₃) and the daily average PM_2.5 levels. Results showed that airflows from the southwest passing over Michigan and Southern Ontario were associated, on average, with the highest O₃ levels at most locations in Eastern Canada.For PM_2.5, the highest levels occurred with airflows from the Eastern Ohio River Valley. At major urban locations in Ontario and Quebec, the warm season mean (May to September) dmax 8-hr O₃ and the annual mean PM_2.5 were, on average, 12 parts per billion and 7.6 μg/m³ higher, respectively, than airflows from the north. Elevated levels of O₃ and PM_2.5 also occurred under light airflows, and, on average, the levels under light airflows were higher than their nonlight counterparts. At several locations in Canada, including Toronto, Montreal, Quebec City, and Kejimkujik, the annual warm season mean dmax 8-hr O₃ experienced a statistically significant (95% confidence) increasing trend over the 10-yr period. When airflow direction was considered, a number of locations experienced statistically significant upward trends in O₃ for airflow from the north and northwest. Several locations also showed significant upward trends associated with airflow from the southwest passing over Michigan and Southwestern Ontario. Although there are no statistically significant downward trends, airflows from the southwest have shown a reduction in O₃ levels in Southwestern Ontario in more recent years.     

Codependencies of Reactive Air Toxic and Criteria Pollutants on Emission Reductions

Abstract

It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM_2.5), and hazardous air pollutants (HAPs) simultaneously, to evaluate the full range of health, ecosystem, and economic effects. Until recently, the capability to simultaneously evaluate interrelated atmospheric pollutants (“one atmosphere” analysis) was unavailable to air quality managers. In this work, we use an air quality model to examine the potential effect of three emission reductions on concentrations of ozone, PM_2.5, and four important HAPs (formaldehyde, acetaldehyde, acrolein, and benzene) over a domain centered on Philadelphia for 12-day episodes in July and January 2001. Although NO_x controls are predicted to benefit PM_2.5 concentrations and sometimes benefit ozone, they have only a small effect on formaldehyde, slightly increase acetaldehyde and acrolein, and have no effect on benzene in the July episode. Concentrations of all pollutants except benzene increase slightly with NO_x controls in the January simulation. Volatile organic compound controls alone are found to have a small effect on ozone and PM_2.5, a less than linear effect on decreasing aldehydes, and an approximately linear effect on acrolein and benzene in summer, but a slightly larger than linear effect on aldehydes and acrolein in winter. These simulations indicate the difficulty in assessing how toxic air pollutants might respond to emission reductions aimed at decreasing criteria pollutants such as ozone and PM_2.5.     

Comparisons of ambient air particulates concentrations (TSP,PM2.5) and dry depositions during smog and non-smog periods at Luliao,Shalu District sampling site

The concentrations of ambient total suspended particulates (TSP) and PM_2.5, and the dry depositions at a sample site at Luliao Junior High School (Luliao) in central Taiwan were measured during smog and non-smog days between December 2017 and July 2018. The results are compared to those obtained during non-smog periods in the years 2015–2017. The mean TSP and PM_2.5 concentrations and dry deposition flux were 72.41?±?26.40, 41.88?±?23.51?μg/m³, and 797.57?±?731.46?μg/m² min, respectively, on the smog days. The mean TSP and PM_2.5 concentrations and dry deposition flux on the non-smog days were 56.39?±?18.08, 34.81?±?12.59?μg/m³ and 468.93?±?600.57?μg/m² min, respectively. The mean TSP concentration in the smog period was 28% greater than that in the non-smog period, and the mean PM_2.5 concentration was 20% higher. The mean dry deposition flux in the smog period was 70% higher than that in the non-smog period at Luliao. The PM_2.5 concentrations exceeded the standards set by the Taiwan EPA (35?μg/m³ daily, and 15?μg/m³ annually). Therefore, the TSP and PM_2.5 concentrations and dry deposition must be reduced in central Taiwan on smog days. In addition, atmospheric TSP and PM_2.5 concentrations at various sampling sites were compared, and those herein were not higher than those measured in other countries. Finally, apart from the local traffic emissions, during smog periods, the other pollution source originated from the transportation process of traffic pollutants emitted in the northwest side of Taiwan.     

Modeled response of ozone to electricity generation emissions in the northeastern United States using three sensitivity techniques

Electrical generation units (EGUs) are important sources of nitrogen oxides (NO_x) that contribute to ozone air pollution. A dynamic management system can anticipate high ozone and dispatch EGU generation on a daily basis to attempt to avoid violations, temporarily scaling back or shutting down EGUs that most influence the high ozone while compensating for that generation elsewhere. Here we investigate the contributions of NO_x from individual EGUs to high daily ozone, with the goal of informing the design of a dynamic management system. In particular, we illustrate the use of three sensitivity techniques in air quality models—brute force, decoupled direct method (DDM), and higher-order DDM—to quantify the sensitivity of high ozone to NO_x emissions from 80 individual EGUs. We model two episodes with high ozone in the region around Pittsburgh, PA, on August 4 and 13, 2005, showing that the contribution of 80 EGUs to 8-hr daily maximum ozone ranges from 1 to >5 ppb at particular locations. At these locations and on the two high ozone days, shutting down power plants roughly 1.5 days before the 8-hr ozone violation causes greater ozone reductions than 1 full day before; however, the benefits of shutting down roughly 2 days before the high ozone are modest compared with 1.5 days. Using DDM, we find that six EGUs are responsible for >65% of the total EGU ozone contribution at locations of interest; in some locations, a single EGU is responsible for most of the contribution. Considering ozone sensitivities for all 80 EGUs, DDM performs well compared with a brute-force simulation with a small normalized mean bias (–0.20), while this bias is reduced when using the higher-order DDM (–0.10).

Implications: Dynamic management of electrical generation has the potential to meet daily ozone air quality standards at low cost. We show that dynamic management can be effective at reducing ozone, as EGU contributions are important and as the number of EGUs that contribute to high ozone in a given location is small (<6). For two high ozone days and seven geographic regions, EGUs would best be shut down or their production scaled back roughly 1.5 days before the forecasted exceedance. Including online sensitivity techniques in an air quality forecasting model can provide timely and useful information on which EGUs would be most beneficial to shut down or scale back temporarily.     

The impacts of different kinds of dust events on PM10 pollution in northern China

In this study the frequencies of PM₁₀ (as key urban pollutant) in 14 key environmental protection cities in northern China were analyzed. It follows that the PM₁₀ concentration in the high-frequency period is higher with an extent 0.009–0.066 mg m⁻³ than in the low-frequency period of 2001–2002. Further the impacts of three kinds of dust events on the PM₁₀ concentration in four cities (Beijing, Hohhot, Xi’an and Lanzhou) were explored. The results showed that different kinds of dust events have different influences on variation of PM₁₀ concentration in these four cities. In Lanzhou and Hohhot, which are near the source areas of dust events, the contribution degree of these three dust events to the PM₁₀ is: floating dust>dust storm>blowing dust. Whereas, in Beijing and Xi’an situated in dust event passing areas, the mean value of PM₁₀ concentration is higher in blowing dust than in floating dust (no dust storm). In addition, the influences of dust events on PM₁₀ concentration are different in the cities on different dust event paths. In Beijing and Hohhot (on the northern path), the high PM₁₀ concentration is usually caused by blowing dust. But in both Lanzhou and Xi’an (on the western/northwestern path) the high PM₁₀ pollution concentration is usually caused by floating dust.     

Simulation of the daily average PM10 concentrations at Ta-Liao with Box–Jenkins time series models and multivariate analysis

Southern Taiwan has experienced severe PM₁₀ problems for over a decade. The present paper describes the establishment of a simulation model for the daily average PM₁₀ concentrations at Ta-Liao, southern Taiwan. The study used a regression with time series error models (RTSE models) (multivariate ARIMA time series model), including an explanatory variable resulting from principal component analyses to complete the PM₁₀ simulation. Factor 1 estimated from the factor analyses explained the variance of 44–49%, which indicated the important contribution from the neighbor-city PM₁₀ at Mei-Nung, Lin-Yuang, Zuoying, Chao-Chou, local ozone and NOx. Factor 1 can be interpreted with regional PM₁₀ plus photochemical reactions. To improve the predictability of extremely high PM₁₀, different results from the principal component analysis were introduced to the RTSE models. We constructed four kinds of RTSE models: RTSE model without PC, with PC4S (PM₁₀ at Mei-Nung, Lin-Yuang, Zuoying, and Chao-Chou), with PCTL (meteorological variables and co-pollutants at Ta-Liao), and with PCTL4S (the combination of the above two) and evaluated the statistics model performance. Ozone, dew point temperature, NOx, wind speed, wind directions, and the PC trigger were the significant variables in the RTSE models most of time. When the neighbor-city PM₁₀ was included in the PC trigger, the predictability was apparently improved. The closeness of fit with the inclusion of PC4S and PCTL4S was improved by reducing SEE from 0.117 to 0.092. Using the RTSE models with PC4S or PCTL4S, POD was improved by an increase of 33%, FAR was reduced 30%, and CSI was increased 39%, when simulating the daily average PM₁₀ > 150 μg m^?3. Evidently we need to survey source impacts prior to establishing a simulation model. Factor analysis is a useful method to investigate sources that contributed PM₁₀ to a target site prior to establishing a simulation model.     

An enhanced ozone forecasting model using air mass trajectory analysis

An enhanced ozone forecasting model using nonlinear regression and an air mass trajectory parameter has been developed and field tested. The model performed significantly better in predicting daily maximum 1-h ozone concentrations during a five-year model calibration period (1993–1997) than did a previously reported regression model. This was particularly true on the 28 “high ozone” days ([O₃]>120 ppb) during the period, for which the mean absolute error (MAE) improved from 21.7 to 12.1 ppb. On the 77 days meteorologically conducive to high ozone, the MAE improved from 12.2 to 9.1 ppb, and for all 580 calibration days the MAE improved from 9.5 to 8.35 ppb. The model was field-tested during the 1998 ozone season, and performed about as expected. Using actual meteorological data as input for the ozone predictions, the MAE for the season was 11.0 ppb. For the daily ozone forecasts, which used meteorological forecast data as input, the MAE was 13.4 ppb. The high ozone days were all anticipated by the ozone forecasters when the model was used for next day forecasts.     

Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period

In order to investigate the air quality and the abatement of traffic-related pollution during the 2008 Olympic Games, we select 12 avenues in the urban area of Beijing to calculate the concentrations of PM₁₀, CO, NO₂ and O₃ before and during the Olympic traffic controlling days, with the OSPM model.Through comparing the modeled results with the measurement results on a representative street, the OSPM model is validated as sufficient to predict the average concentrations of these pollutants at street level, and also reflects their daily variations well, i.e. CO presents the similar double peaks as the traffic flow, PM₁₀ concentration is influenced by other sources. Meanwhile, the model predicts O₃ to stay less during the daytime and ascend in the night, just opposite to NO₂, which reveals the impact of photochemical reactions. In addition, the predicted concentrations on the windward side often exceed the leeward side, indicating the impact of the special street shape, as well as the wind.The comparison between the predicted street concentrations before and during the Olympic traffic control period shows that the overall on-road air quality was improved effectively, due to the 32.3% traffic flow reduction. The concentrations of PM₁₀, CO and NO₂ have reduced from 142.6 μg m⁻³, 3.02 mg m⁻³ and 118.7 μg m⁻³ to 102.0 μg m⁻³, 2.43 mg m⁻³ and 104.1 μg m⁻³. However, the different pollutants show diverse changes after the traffic control. PM₁₀ decreases most, and the reduction effect focusing on the first half-day even clears the morning peak, whereas CO and NO₂ have even reductions to minify the daily fluctuations on the whole. Opposite to the other pollutants, ozone shows an increase of concentration. The average reduction rate of PM₁₀, CO, NO₂ and O₃ are respectively 28%, 19.3%, 12.3% and −25.2%. Furthermore, the streets in east, west, south and north areas present different air quality improvements, probably induced by the varied background pollution in different regions around Beijing, along with the impact of wind force. This finding suggests the pollution control in the surrounding regions, not only in the urban area.     

Wood Smoke Contribution to Winter Aerosol in Fresno,CA

Abstract

In an effort to better quantify wintertime particulate matter (PM) and the contribution of wood smoke to air pollution events in Fresno, CA, a field campaign was conducted in winter 2003–2004. Coarse and fine daily PM samples were collected at five locations in Fresno, including residential, urban, and industrial areas. Measurements of collected samples included gravimetric mass determination, organic and elemental carbon analysis, and trace organic compound analysis by gas chromatograph mass spectrometry (GC/MS). The wood smoke tracer levoglucosan was also measured in aqueous aerosol extracts using high-performance anion exchange chromatography coupled with pulsed amperometric detection. Sample preparation and analysis by this technique is much simpler and less expensive than derivatized levoglucosan analysis by GC/MS, permitting analysis of daily PM samples from all five of the measurement locations. Analyses revealed low spatial variability and similar temporal patterns of PM_2.5 mass, organic carbon (OC), and levoglucosan. Daily mass concentrations appear to have been strongly influenced by meteorological conditions, including precipitation, wind, and fog events. Fine PM (PM_2.5) concentrations are uncommonly low during the study period, reflecting frequent precipitation events. During the first portion of the study, levoglucosan had a strong relationship to the concentrations of PM_2.5 and OC. In the later portion of the study, there was a significant reduction in levoglucosan relative to PM_2.5 and OC. This may indicate a change in particle removal processes, perhaps because of fog events, which were more common in the latter period. Combined, the emissions from wood smoke, meat cooking, and motor vehicles appear to contribute ~65–80% to measured OC, with wood smoke, on average, accounting for ~41% of OC and ~18% of PM_2.5 mass. Two residential sites exhibit somewhat higher contributions of wood smoke to OC than other locations.     

Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.)

Hourly average concentrations of PM₁₀ and PM_2.5 have been measured simultaneously at a site within Birmingham U.K. between October 1994 and October 1995. Comparison of PM₁₀ and NO_x data with two other sites in the same city shows comparable summer and winter mean concentrations and highly significant inter-site correlations for both hourly and daily mean data. Over a four-month period samples were also collected for chemical analysis of sulphate, nitrate, chloride, ammonium and elemental and organic carbon. Analysis of the data indicates a marked difference between summer and winter periods. In the winter months PM_2.5 comprises about 80% of PM₁₀ and is strongly correlated with NO_x indicating the importance of road traffic as a source. In the summer months, coarse particles (PM₁₀−PM_2.5) account for almost 50% of PM₁₀ and the influence of resuspended surface dusts and soils and of secondary particulate matter is evident. The chemical analysis data are also consistent with three sources dominating the PM₁₀ composition: vehicle exhaust emissions, secondary ammonium salts and resuspended surface dusts. Coarse particles from resuspension showed a positive dependence on windspeed, whilst elemental carbon derived from road traffic exhibited a negative dependence.     

Composition and secondary formation of fine particulate matter in the Salt Lake Valley: Winter 2009

Under the National Ambient Air Quality Standards (NAAQS), put in place as a result of the Clean Air Amendments of 1990, three regions in the state of Utah are in violation of the NAAQS for PM₁₀ and PM_2.5 (Salt Lake County, Ogden City, and Utah County). These regions are susceptible to strong inversions that can persist for days to weeks. This meteorology, coupled with the metropolitan nature of these regions, contributes to its violation of the NAAQS for PM during the winter. During January–February 2009, 1-hr averaged concentrations of PM_10-2.5, PM_2.5, NO_x, NO₂, NO, O₃, CO, and NH₃ were measured. Particulate-phase nitrate, nitrite, and sulfate and gas-phase HONO, HNO₃, and SO₂ were also measured on a 1-hr average basis. The results indicate that ammonium nitrate averages 40% of the total PM_2.5 mass in the absence of inversions and up to 69% during strong inversions. Also, the formation of ammonium nitrate is nitric acid limited. Overall, the lower boundary layer in the Salt Lake Valley appears to be oxidant and volatile organic carbon (VOC) limited with respect to ozone formation. The most effective way to reduce ammonium nitrate secondary particle formation during the inversions period is to reduce NO_x emissions. However, a decrease in NO_x will increase ozone concentrations. A better definition of the complete ozone isopleths would better inform this decision.

Implications: Monitoring of air pollution constituents in Salt Lake City, UT, during periods in which PM_2.5 concentrations exceeded the NAAQS, reveals that secondary aerosol formation for this region is NO_x limited. Therefore, NO_x emissions should be targeted in order to reduce secondary particle formation and PM_2.5. Data also indicate that the highest concentrations of sulfur dioxide are associated with winds from the north-northwest, the location of several small refineries.     

Mesoscale modeling of wintertime particulate matter episodes in eastern Washington, USA

The Spokane, Washington area is classified as a non-attainment area for the 24-h PM₁₀ standard due to a history of high particulate matter concentrations. A Eulerian regional air quality model (CALMET/CALGRID) has been used to characterize the emission, transport and dispersion of PM₁₀ and PM_2.5 in Spokane. Observations from a residential site (Rockwood, RW) and an industrial site (Crown Zellerbach, CZ), spanning July 1994–August 1996 were used to evaluate the current emission inventory. Two major tasks were devised to conduct the objectives of this investigation. First, a simple and efficient urban dispersion model (WYNDValley) was used to simulate important episodes characterized by the highest PM₁₀ and PM_2.5 concentrations. The selected episodes included four days with wet conditions for which no roads would have been emitting and seven days with dry conditions for which roads would emit. In the second step, a single road-emitting event was selected from the previous predicted results for further analysis using the Eulerian regional air quality model to examine the emission inventory. The urban and regional models predicted the observed concentration distributions reasonably well for the source emissions inventoried in Spokane. The mass concentrations of PM₁₀ were well predicted for the roads emitting case examined by both models indicating that the emission inventory based primarily upon area sources including roads is reasonably well characterized, at least at the RW site. The area sources around CZ are less well characterized, so that the PM₁₀ concentrations are underpredicted at CZ. The models appear unable to reach an equilibrium mass balance status at the beginning of the simulation, and the urban model seems unable to properly resolve the nocturnal boundary layer.     

Metallic Element Composition of Particulate Matter During Day and Night Sampling at a Traffic Site

Day and night period sampling programs were carried out using a versatile air pollutant system to collect fine particulate matter (PM_2.5) and coarse particulate matter (PM_2.5–10) simultaneously at a traffic junction that is only 60 m from HungKuang University located in Central Taiwan. Therefore, HungKuang University is regarded as the traffic sampling site in this study. Similar measurements were carried out in a previous 2013 study by Fang and colleagues during October 2012 to November 2012. Determination of metallic element composition of fine and coarse particulates collected during the day and the night was accomplished with inductively coupled plasma atomic emission spectrometry (ICP-AES). The results indicated that there were no significant differences in composition of metallic elements Zn, Cu, Cr, Mn, Fe, Pb, and Cd in either coarse or fine particles for both day and night sampling periods. The statistical results indicated no significant differences for metallic elements in the PM_2.5–10 particulates for day and night sampling periods. Also, no significant differences were noted for metallic elements in the PM_2.5 particulates for day and night sampling periods at this traffic sampling site. The proposed reason is the limited sampling period employed in this study. Another potential reason is the presence of traffic that runs heavily both day and night being a major contributor to the ambient air metallic pollutants in this region.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.