Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Analysis of Short-Term and Episodic Variations in PM2.5 Concentrations Using Hourly Air Monitoring Data

Abstract

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter <2.5 μm (PM_2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen oxide (NO_x), and ozone (O₃)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM_2.5 concentrations measured during this period were ≤17 μg/m³, concentrations >65 μg/m³ were observed 76 times. On average, PM_2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO_x. This pattern was highly variable; however, PM_2.5 concentrations >65 μg/m³ were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM_2.5 concentration during these episodes was 76.6 μg/m³. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 μg/m³), and many exhibited strong covariation between PM_2.5 and CO, NO_x, or SO₂. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM_2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM_2.5 should carefully consider exposure issues related to the intraday timing of PM_2.5 episodes, as well as the potential for toxicological interactions among PM_2.5 and primary gaseous pollutants.     

Analysis of a Summertime PM2.5 and Haze Episode in the Mid-Atlantic Region

Abstract

Observations of the mass and chemical composition of particles less than 2.5 μm in aerodynamic diameter (PM_2.5), light extinction, and meteorology in the urban Baltimore-Washington corridor during July 1999 and July 2000 are presented and analyzed to study summertime haze formation in the mid-Atlantic region. The mass fraction of ammoniated sulfate (SO₄ ^2-) and carbonaceous material in PM_2.5 were each ～50% for cleaner air (PM_2.5 < 10 μg/m³) but changed to ～60% and ～20%, respectively, for more polluted air (PM_2.5 > 30 μg/m³). This signifies the role of SO₄ ^2- in haze formation. Comparisons of data from this study with the Interagency Monitoring of Protected Visual Environments network suggest that SO₄ ^2? is more regional than carbonaceous material and originates in part from upwind source regions. The light extinction coefficient is well correlated to PM_2.5 mass plus water associated with inorganic salt, leading to a mass extinction efficiency of 7.6 ± 1.7 m²/g for hydrated aerosol. The most serious haze episode occurring between July 15 and 19, 1999, was characterized by westerly transport and recirculation slowing removal of pollutants. At the peak of this episode, 1-hr PM_2.5 concentration reached ～45 μg/m³, visual range dropped to ～5 km, and aerosol water likely contributed to ～40% of the light extinction coefficient.     

Recent spatial gradients and time trends in Dhaka,Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM_2.5 (<2.5 µm in aerodynamic diameter), PM₁₀ (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO₂, NO₂, CO, and O₃) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM_2.5 and PM₁₀ being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM_2.5 and PM₁₀) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM_2.5 (72% of total study days), followed by PM₁₀ (40% of total study days), O₃ (1.7% of total study days), SO₂ (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO₂ (5.6 ppb yr^?1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr^?1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM_2.5 (?4.6 µg/m³ yr^?1, 95% CI: ?12.7, 3.6) and PM₁₀ (?2.7 µg/m³ yr^?1, 95% CI: ?7.9, 2.5) were observed during this study period, the PM_2.5 concentration is still too high (~ 82.0 µg/m³) and can cause severe impact on human health.

Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.     

Defining the Photochemical Contribution to Particulate Matter in Urban Areas Using Time-Series Analysis

Abstract

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 μm 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 μg/m³ (3.03%) in Chicago to 3.9 μg/m³ (7.65%) in Phoenix.     

Source Identification and Trends in Concentrations of Gaseous and Fine Particulate Principal Species in Seoul,South Korea

Abstract

Ambient measurements were made using two sets of annular denuder system during the four seasons (April 2001 to February 2002) and were then compared with the results during the period of 1996–1997 to estimate the trends and seasonal variations in concentrations of gaseous and fine particulate matter (PM_2.5) principal species. Annual averages of gaseous HNO₃ and NH₃ increased by 11% and 6%, respectively, compared with those of the previous study, whereas HONO and SO₂ decreased by 11% and 136%, respectively. The PM_2.5 concentration decreased by ～17%, 35% for SO₄ ^2?, and 29% for NH₄ ⁺, whereas NO₃ ^? increased by 21%. Organic carbon (OC) and elemental carbon (EC) were 12.8 and 5.98 μg/m^-3, accounting for ～26 and 12% of PM_2.5 concentration, respectively. The species studied accounted for 84% of PM_2.5 concentration, ranging from 76% in winter to 97% in summer.

Potential source contribution function (PSCF) analysis was used to identify possible source areas affecting air pollution levels at a receptor site in Seoul. High possible source areas in concentrations of PM_2.5, NO₃ ^?, SO₄ ^2?, NH₄ ⁺, and K⁺ were coastal cities of Liaoning province (possibly emissions from oil-fired boilers on ocean liners and fishing vessels and industrial emissions), inland areas of Heibei/Shandong provinces (the highest density areas of agricultural production and population) in China, and typical port cities (Mokpo, Yeosu, and Busan) of South Korea. In the PSCF map for OC, high possible source areas were also coastal cities of Liaoning province and inland areas of Heibei/Shandong provinces in China. In contrast, high possible source areas of EC were highlighted in the south of the Yellow Sea, indicating possible emissions from oil-fired boilers on large ships between South Korea and Southeast Asia. In summary, the PSCF results may suggest that air pollution levels in Seoul are affected considerably by long-range transport from external areas, such as the coastal zone in China and other cities in South Korea, as well as Seoul itself.     

Roadside Particulate Air Pollution in Bangkok

Abstract

Airborne fine particles of PM_2.5-10 and PM_2.5 in Bangkok, Nonthaburi, and Ayutthaya were measured from December 22, 1998, to March 26, 1999, and from November 30, 1999, to December 2, 1999. Almost all the PM₁₀ values in the high-polluted (H) area exceeded the Thailand National Ambient Air Quality Standards (NAAQS) of 120 μg/m³. The low-polluted (L) area showed low PM₁₀ (34–74 μg/m³ in the daytime and 54–89 μg/m³ at night). PM_2.5 in the H area varied between 82 and 143 μg/m³ in the daytime and between 45 and 146 μg/m³ at night. In the L area, PM_2.5 was quite low both day and night and varied between 24 and 54 μg/m³, lower than the U.S. Environmental Protection Agency (EPA) standard (65 μg/m³). The personal exposure results showed a significantly higher proportion of PM_2.5 to PM₁₀ in the H area than in the L area (H = 0.80 ± 0.08 and L = 0.65 ± 0.04).

Roadside PM₁₀ was measured simultaneously with the Thailand Pollution Control Department (PCD) monitoring station at the same site and at the intersections where police work. The result from dual simultaneous measurements of PM₁₀ showed a good correlation (correlation coefficient: r = 0.93); however, PM levels near the roadside at the intersections were higher than the concentrations at the monitoring station. The relationship between ambient PM level and actual personal exposures was examined. Correlation coefficients between the general ambient outdoors and personal exposure levels were 0.92 for both PM_2.5 and PM₁₀.

Bangkok air quality data for 1997–2000, including 24-hr average PM₁₀, NO₂, SO₂, and O₃ from eight PCD monitoring stations, were analyzed and validated. The annual arithmetic mean PM₁₀ of the PCD data at the roadside monitoring stations for the last 3 years decreased from 130 to 73 μg/m³, whereas the corresponding levels at the general monitoring stations decreased from 90 to 49 μg/m³. The proportion of days when the level of the 24-hr average PM₁₀ exceeded the NAAQS was between 13 and 26% at roadside stations. PCD data showed PM₁₀ was well correlated with NO₂ but not with SO₂, suggesting that automobile exhaust is the main source of the particulate air pollution. The results obtained from the simultaneous measurement of PM_2.5 and PM₁₀ indicate the potential environmental health hazard of fine particles. In conclusion, Bangkok traffic police were exposed to high levels of automobile-derived particulate air pollution.     

Association between Levels of Fine Particulate and Emergency Visits for Pneumonia and other Respiratory Illnesses among Children in Santiago,Chile

ABSTRACT

Recent evidence has implicated the fine fraction of particulate as the major contributor to the increase in mortality and morbidity related to particulate ambient levels. We therefore evaluated the impact of daily variation of ambient PM_2.5 and other pollutants on the number of daily respiratory-related emergency visits (REVs) to a large pediatric hospital of Santiago, Chile. The study was conducted from February 1995 to August 1996. Four monitoring stations from the network of Santiago provided air pollution data. The PM2.5 24-hr average ranged from 10 to 111 μg/m³ during September to April (warm months) and from 10 to 156 μg/m³ during May to August (cold months). Other contaminants (ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂)) were, in general, low during the study period. The increase in REVs was significantly related to PM₁₀ and PM_2.5 ambient levels, with the relationship between PM_2.5 levels and the number of REVs the stronger. During the cold months, an increase of 45 ìg/m³ in the PM_2.5 24-hr average was related to a 2.7% increase in the number of REVs (95% CI, 1.1–4.4%) with a two-day lag, and to an increase of 6.7% (95% CI, 1.7–12.0%) in the number of visits for pneumonia with a three-day lag. SO₂ and NO₂ were also related to REVs. We conclude that urban air pollutant mixture, particularly fine particulates, adversely affect the respiratory health of children residing in Santiago.     

Ionic composition of TSP and PM2.5 during dust storms and air pollution episodes at Xi'an,China

TSP and PM_2.5 samples were collected at Xi'an, China during dust storms (DSs) and several types of pollution events, including haze, biomass burning, and firework displays. Aerosol mass concentrations were up to 2 times higher during the particulate matter (PM) events than on normal days (NDs), and all types of PM led to decreased visibility. Water-soluble ions (Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺, F^?, Cl^?, NO₃^?, and SO₄^2?). were major aerosol components during the pollution episodes, but their concentrations were lower during DSs. NH₄⁺, K⁺, F^?, Cl^?, NO₃^?, and SO₄^2? were more abundant in PM_2.5 than TSP but the opposite was true for Mg²⁺ and Ca²⁺. PM collected on hazy days was enriched with secondary species (NH₄⁺, NO₃^?, and SO₄²) while PM from straw combustion showed high K⁺ and Cl^?. Firework displays caused increases in K⁺ and also enrichments of NO₃^? relative to SO₄^2?. During DSs, the concentrations of secondary aerosol components were low, but Ca²⁺ was abundant. Ion balance calculations indicate that PM from haze and straw combustion was acidic while the DSs samples were alkaline and the fireworks' PM was close to neutral. Ion ratios (SO₄^2?/K⁺, NO₃^?/SO₄^2?, and Cl^?/K⁺) proved effective as indicators for different pollution episodes.     

Characterization of major pollution events (dust, haze, and two festival events) at Agra, India

Total suspended particulate (TSP) samples were collected during dust, haze, and two festival events (Holi and Diwali) from February 2009 to June 2010. Pollutant gases (NO₂, SO₂, and O₃) along with the meteorological parameters were also measured during the four pollution events at Agra. The concentration of pollutant gases decreases during dust events (DEs), but the levels of the gases increase during other pollution events indicating the impact of anthropogenic emissions. The mass concentrations were about two times higher during pollution events than normal days (NDs). High TSP concentrations during Holi and Diwali events may be attributed to anthropogenic activities while increased combustion sources in addition to stagnant meteorological conditions contributed to high TSP mass during haze events. On the other hand, long-range transport of atmospheric particles plays a major role during DEs. In the dust samples, Ca²⁺, Cl^?, NO₃ ^?, and SO₄ ^2? were the most abundant ions and Ca²⁺ alone accounted for 22 % of the total ionic mass, while during haze event, the concentrations of secondary aerosols species, viz., NO₃ ^?, SO₄ ^2?, and NH₄ ⁺, were 3.6, 3.3, and 5.1 times higher than the normal days. During Diwali, SO₄ ^2? concentration (17.8 μg?m^?3) was highest followed by NO₃ ^?, K⁺, and Cl^? while the Holi samples were strongly enriched with Cl^? and K⁺ which together made up 32.7 % of the total water-soluble ions. The ion balances indicate that the haze samples were acidic. On the other hand, Holi, Diwali, and DE samples were enriched with cations. The carbonaceous aerosol shows strong variation with the highest concentration during Holi followed by haze, Diwali, DEs, and NDs. However, the secondary organic carbon concentration follows the order haze > DEs > Diwali > Holi > NDs. The scanning electron microscope/EDX results indicate that KCl and carbon-rich particles were more dominant during Holi and haze events while DE samples were enriched with particles of crustal origin.     

Particulate Matter in California: Part 2—Spatial,Temporal, and Compositional Patterns of PM2.5, PM10–2.5, and PM10

Abstract

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM_2.5 and PM₁₀ concentrations range from 3 to 10 [H9262]g/m³ and from 5 to 18 µg/m³, respectively. In the urban areas of California, annual-averages for PM_2.5 range from 7 to 30 [H9262]g/m³, with observed 24-hr peaks reaching levels as high as 160 [H9262]g/m³. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM_2.5 concentrations that are more prolonged and regional in nature. PM_2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM_2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO₄ ^2?) and nitrate (NO₃ ^?) components of PM_2.5 and PM₁₀ and correlate with reductions in ambient levels of oxides of sulfur (SO_x) and oxides of nitrogen (NO_x). Annual averages for PM_10–2.5 and PM₁₀ exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

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.     

The characterization of water-soluble inorganic ions in PM2.5 during a winter period in Xi'an,China

The characteristics of water-soluble inorganic ions (WSIIs) during a winter period in a suburb of Xi'an, China, were investigated. Our results show that the total mass concentration of the dominant WSIIs (8) was 91.27 µg m^–3, accounting for 50.1% of the total mass concentration of PM_2.5 (particulates with a size of 2.5 µm or less). Secondary inorganic aerosols (SO₄^2?, NO₃^? and NH₄⁺) were the most abundant ions, accounting for up to 95.12% of the total ions. By using the anion and cation equivalence ratio method, PM_2.5 was shown to have weak alkalinity, and the chemical forms of WSIIs were mainly (NH₄)₂SO₄ and NH₄NO₃. The sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) suggested that larger proportions of SO₄^2? and NO₃^? were formed by gas-phase SO₂ and NO₂ in the sampling site. Ratio analysis also indicated that anthropogenic sources significantly contributed to WSII pollution. Among the anthropogenic sources, fixed pollution sources were found to be dominant over mobile sources.     

Chemical characteristics of fine particulate matters measured during severe winter haze events in Ulaanbaatar,Mongolia

In order to investigate the chemical characteristics of atmospheric aerosol measured during a severe winter haze event, 12-hr PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) samples were collected at an urban site in Ulaanbaatar, Mongolia, from January 9 to February 17, 2008. On average, 12-hr PM_2.5 mass concentration was 105.1 ± 34.9 μg/m³. Low PM_2.5 mass concentrations were measured when low pressure developed over central Mongolia. The 12-hr average organic mass by carbon (OMC) varied from 6.4 to 132.3 μg/m³, with a mean of 54.9 ± 25.4 μg/m³, whereas elemental carbon (EC) concentration ranged from 0.1 to 3.6 μgC/m³, with a mean of 1.5 ± 0.8 μgC/m³. Ammonium sulfate was found to be the most abundant water-soluble ionic component in Ulaanbaatar during the sampling period, with an average concentration of 11.3 ± 5.0 μg/m³. In order to characterize the effect of air mass pathway on fine particulate matter characteristics, 5-day back-trajectory analysis was conducted, using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The haze level was classified into three categories, based on the 5-day air mass back trajectories, as Stagnant (ST), Continental (CT), and Low Pressure (LP) cases. PM_2.5 mass concentration during the Stagnant condition was approximately 2.5 times higher than that during the Low Pressure condition, mainly due to increased pollutant concentration of OMC and secondary ammonium sulfate.

Implications: Mongolia is experiencing rapid rates of urbanization similar to other Asian countries, resulting in air pollution problems by the growing number of automobiles and industrialization. Ulaanbaatar, capital of Mongolia, is inherently vulnerable to air pollution because of its emission sources, topography, and meteorological characteristics. Very limited measurements on chemical characteristics of particulate matter have been carried out in Ulaanbaatar, Mongolia.     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

PAH air pollution at a Portuguese urban area: carcinogenic risks and sources identification

This study aimed to characterize air pollution and the associated carcinogenic risks of polycyclic aromatic hydrocarbon (PAHs) at an urban site, to identify possible emission sources of PAHs using several statistical methodologies, and to analyze the influence of other air pollutants and meteorological variables on PAH concentrations.The air quality and meteorological data were collected in Oporto, the second largest city of Portugal. Eighteen PAHs (the 16 PAHs considered by United States Environment Protection Agency (USEPA) as priority pollutants, dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were collected daily for 24 h in air (gas phase and in particles) during 40 consecutive days in November and December 2008 by constant low-flow samplers and using polytetrafluoroethylene (PTFE) membrane filters for particulate (PM₁₀ and PM_2.5 bound) PAHs and pre-cleaned polyurethane foam plugs for gaseous compounds. The other monitored air pollutants were SO₂, PM₁₀, NO₂, CO, and O₃; the meteorological variables were temperature, relative humidity, wind speed, total precipitation, and solar radiation. Benzo[a]pyrene reached a mean concentration of 2.02 ng?m^?3, surpassing the EU annual limit value. The target carcinogenic risks were equal than the health-based guideline level set by USEPA (10^?6) at the studied site, with the cancer risks of eight PAHs reaching senior levels of 9.98?×?10^?7 in PM₁₀ and 1.06?×?10^?6 in air. The applied statistical methods, correlation matrix, cluster analysis, and principal component analysis, were in agreement in the grouping of the PAHs. The groups were formed according to their chemical structure (number of rings), phase distribution, and emission sources. PAH diagnostic ratios were also calculated to evaluate the main emission sources. Diesel vehicular emissions were the major source of PAHs at the studied site. Besides that source, emissions from residential heating and oil refinery were identified to contribute to PAH levels at the respective area. Additionally, principal component regression indicated that SO₂, NO₂, PM₁₀, CO, and solar radiation had positive correlation with PAHs concentrations, while O₃, temperature, relative humidity, and wind speed were negatively correlated.     

Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore,MD

ABSTRACT

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM₂₅, PM₁₀, SO₄ ^2-, O₃, NO₂, SO₂, and exhaust-related VOCs.

Results of this study showed that longitudinal associations between ambient PM_2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM_2.5 exposures and resulting personal-ambient associations. Associations between personal PM₂₅ exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM_{2 5} sources. Evidence for this was provided by SO₄ ^2-measurements, which can be thought of as a tracer for ambient PM₂₅. For SO₄ ^2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM_2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM_2.5 sources to personal PM_2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments.

Results also indicate that the potential for confounding by PM_2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM_2.5 exposures were not significantly correlated with personal exposures to PM_2.5-10, PM_2.5 of non-ambient origin, O₃, NO₂, and SO₂. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM_2.5 epidemiologic studies are unlikely to be due to confounding by the PM_2.5 co-pollutants measured in this study.     

Exposure to hazardous air pollutants along Oba Akran road, Lagos-Nigeria

We measured toxic air pollutants along Oba Akran road in Lagos to evaluate pedestrian exposure. PM₁₀, CO, O₃, NO₂, SO₂, CH₄, noise, wind velocity and temperature were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM₁₀ (with an average of 274.6 μg m⁻³ for all samples) and CO (with an average of 19.27 ppm for all samples) was relatively high. CO is a traffic-related pollutant, so the influence of the local traffic emissions on CO levels is strong. The high concentration of the PM₁₀ measured at the three environments also suggests that the traffic is a major source of ultrafine particles. The overall average concentrations for the 72-day experimental period for SO₂, NO₂ and O₃ are 101.2, 62.5 and 0.32 ppb respectively, all of which are below the US national ambient air quality standards. Strong traffic impacts can be observed from the concentrations of some of these pollutants measured in these three environments. Most clear is a reflection of diesel truck traffic activity rich in black carbon concentrations. The diurnal variation of O₃ and NO₂ also showed that NO₂ was depleted by photochemically formed O₃ during the day and replenished at night as O₃ was destroyed. A multivariate statistical analysis (Principal Component Analysis, Factor Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone interactions.     

Gaseous and particulate air pollution in the san gabriel mountains of southern california

In order to assess concentrations and daily patterns of air pollutants at a mountainous site in the South Coast Air Basin, a study was undertaken in the San Dimas Experimental Forest of the San Gabriel Mountains between April 1985 and October 1985. Continuous monitoring of O₃, NO, NO₂, SO₂, total S compounds and light scattering coefficient was conducted. Particulate aerosols were collected twice a week and concentrations of nitrate, ammonium and sulfate in fine (< 2.5 μm diameter) and coarse (> 2.5 μm diameter) modes were determined.For the June–August period, when the levels of photochemical smog were the highest, monthly 24-h average concentrations of the pollutants were: O₃, about 200 μg m⁻³; NO₂, 40–75 μg m⁻³; NO, 1–5 μg m ⁻³; and SO₂, 0.5–5 μgm⁻³. The concentrations of O₃ were about two times higher than in the neighboring stations of the South Coast Air Basin. O₃, SO₂ and total S concentrations peaked in the early afternoon, generally between 1500 and 1600 PST. Peak concentrations of NO occurred in the morning, generally between 1000 and 1100 PST. NO₂ concentrations typically peaked in the late afternoon between 1500 and 1800 PST, but occasionally (in 9 % of days) maximum NO₂ occurred in the morning, concurrently with the NO peaks. Daytime concentrations of the nitrate in fine aerosol fraction were generally between 100 and 600 nEq m ⁻³, those of ammonium between 50 and 300 nEq m ⁻³, and concentrations of sulfate between 60 and 250 nEq m⁻³. A 3-day denuder study showed that HNO₃can make up to 73 % of the total amount of total nitrate in the air. NO₂ was the most abundant N compound at Tan bark Flat (69–86% of the total amount of the monitored N compounds). Nitrate amounted to 9–15 %, HNO₃ to 4–11 %, ammonium to 3–9%, and NO to 1–2% of the total amount of the measured nitrogen compounds.     

Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode

Abstract

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29–July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O₃), particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM₁₀) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O₃ and PM than CMAQ. Both models tend to predict O₃ values that are higher than those observed. For observed O₃ values above 60 ppb, O₃ performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O₃ values above 40 ppb.

Both models predict similar amounts of sulfate (SO₄ ^2?) and organic matter, and both predict SO₄ ^2? to be the largest contributor to PM_2.5. PMCAMx generally predicts higher amounts of ammonium (NH₄ ⁺), nitrate (NO₃ ^?), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO₃ ^?,NH₄ ⁺, and BC than observed, which degrades its performance. For PM₁₀ and PM_2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37–43% and –33–4% for CMAQ and 50–59% and 7–30% for PMCAMx. Both models predict the largest MNGEs for NO₃ ^? (98–104% for CMAQ, 138–338% for PMCAMx). The inaccurate NO₃ ^? predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.