Annual and weekly patterns of ozone and particulate matter in Jeddah,Saudi Arabia

Air pollution has been an increasing concern within the Kingdom of Saudi Arabia and other Middle Eastern countries. In this work the authors present an analysis of daily ozone (O₃), nitrogen oxide (NO_x), and particulate matter (<10 μm aerodynamic diameter; PM₁₀) concentrations for two years (2010 and 2011) at sites in and around the coastal city of Jeddah, as well as a remote background site for comparison. Monthly and weekly variations, along with their implications and consequences, were also examined. O₃ within Jeddah was remarkably low, and exhibited the so-called weekend effect—elevated O₃ levels on the weekends, despite reduced emissions of O₃ precursors on those days. Weekend O₃ increases averaged between 12% and 14% in the city, suggesting that NO_x/volatile organic compound (VOC) ratios within cities such as Jeddah may be exceptionally high. Sites upwind or far removed from Jeddah did not display this weekend effect. Based on these results, emission control strategies in and around Jeddah must carefully address NO_x/VOC ratios so as to reduce O₃ at downwind locations without increasing it within urban locations themselves. PM₁₀ concentrations within Jeddah were elevated compared with North American cites of similar climatology, though comparable to other large cities within the Middle East.

Implications:Daily concentrations of O₃, PM₁₀, and NO_x in and around the city of Jeddah, Saudi Arabia, are analyzed and compared with those of other reference cities. Extremely low O₃ levels, along with a significant urban weekend effect (higher weekend O₃, despite reduced NO_x concentrations), is apparent, along with high levels of PM₁₀ within the city. Urban O₃ in Jeddah was found to be lower than that of other comparable cities, but the strong weekend effect suggests that care must be taken to reduce downwind O₃ levels without increasing them within the city itself. Further research into the emissions and chemistry contributing to the reduced O₃ levels within the city is warranted.     

Chemical characterization and source apportionment of fine and coarse particulate matter in Lahore,Pakistan

Lahore, Pakistan is an emerging megacity that is heavily polluted with high levels of particle air pollution. In this study, respirable particulate matter (PM_2.5 and PM₁₀) were collected every sixth day in Lahore from 12 January 2007 to 19 January 2008. Ambient aerosol was characterized using well-established chemical methods for mass, organic carbon (OC), elemental carbon (EC), ionic species (sulfate, nitrate, chloride, ammonium, sodium, calcium, and potassium), and organic species. The annual average concentration (±one standard deviation) of PM_2.5 was 194 ± 94 μg m^?3 and PM₁₀ was 336 ± 135 μg m^?3. Coarse aerosol (PM_10?2.5) was dominated by crustal sources like dust (74 ± 16%, annual average ± one standard deviation), whereas fine particles were dominated by carbonaceous aerosol (organic matter and elemental carbon, 61 ± 17%). Organic tracer species were used to identify sources of PM_2.5 OC and chemical mass balance (CMB) modeling was used to estimate relative source contributions. On an annual basis, non-catalyzed motor vehicles accounted for more than half of primary OC (53 ± 19%). Lesser sources included biomass burning (10 ± 5%) and the combined source of diesel engines and residual fuel oil combustion (6 ± 2%). Secondary organic aerosol (SOA) was an important contributor to ambient OC, particularly during the winter when secondary processing of aerosol species during fog episodes was expected. Coal combustion alone contributed a small percentage of organic aerosol (1.9 ± 0.3%), but showed strong linear correlation with unidentified sources of OC that contributed more significantly (27 ± 16%). Brick kilns, where coal and other low quality fuels are burned together, are suggested as the most probable origins of unapportioned OC. The chemical profiling of emissions from brick kilns and other sources unique to Lahore would contribute to a better understanding of OC sources in this megacity.     

Simulating the fine and coarse inorganic particulate matter concentrations in a polluted megacity

A three dimensional chemical transport model (PMCAMx) is applied to the Mexico City Metropolitan Area (MCMA) in order to simulate the chemical composition and mass of the major PM₁ (fine) and PM_1–10 (coarse) inorganic components and determine the effect of mineral dust on their formation. The aerosol thermodynamic model ISORROPIA-II is used to explicitly simulate the effect of Ca, Mg, and K from dust on semi-volatile partitioning and water uptake. The hybrid approach is applied to simulate the inorganic components, assuming that the smallest particles are in thermodynamic equilibrium, while describing the mass transfer to and from the larger ones. The official MCMA 2004 emissions inventory with improved dust and NaCl emissions is used. The comparison between the model predictions and measurements during a week of April of 2003 at Centro Nacional de Investigacion y Capacitacion Ambiental (CENICA) “Supersite” shows that the model reproduces reasonably well the fine mode composition and its diurnal variation. Sulfate predicted levels are relatively uniform in the area (approximately 3 μg m^?3), while ammonium nitrate peaks in Mexico City (approximately 7 μg m^?3) and its concentration rapidly decreases due to dilution and evaporation away from the urban area. In areas of high dust concentrations, the associated alkalinity is predicted to increase the concentration of nitrate, chloride and ammonium in the coarse mode by up to 2 μg m^?3 (a factor of 10), 0.4 μg m^?3, and 0.6 μg m^?3 (75%), respectively. The predicted ammonium nitrate levels inside Mexico City for this period are sensitive to the physical state (solid versus liquid) of the particles during periods with RH less than 50%.     

Effects of wind direction on coarse and fine particulate matter concentrations in southeast Kansas

Field data for coarse particulate matter ([PM] PM10) and fine particulate matter (PM2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM10 but not for PM2.5. PM10 concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM10 or PM2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM10 and PM2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from "other" directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.     

湖北省大气颗粒物浓度时空变化特征

了解大气颗粒物浓度的时空变化格局对于大气污染防治、预警预报等具有重要理论和实践意义。根据2015年1月至2015年12月湖北省13个主要城市53个监测站点每小时发布的PM10和PM2.5浓度数据,研究了湖北省大气颗粒物浓度时空变化特征。结果表明,PM10和PM2.5浓度在空间上均呈现出鄂西部最低、中部最高、东部居中、南北向的均质性;时间上各城市均呈现颗粒物浓度随着月份变化先降低后升高,1月份最高,8月份最低,且呈现夏季浓度<秋季浓度<春季浓度<冬季浓度的变化规律。分析表明,湖北省大气颗粒物浓度时空变化特征与降水量、气温等气象因子呈现出显著负相关关系,与风速关系不显著;与其来源中建筑施工面积、机动车保有量、货运量和客运量、人均GDP和人均第二产值关系紧密。     

Identification and source apportionment of polycyclic aromatic hydrocarbons in ambient air particulate matter of Riyadh, Saudi Arabia

In an effort to assess the occurrence and sources of polycyclic aromatic hydrocarbons (PAHs) in the ambient air of Riyadh, Saudi Arabia, PM₁₀ samples were collected during December 2010. Diagnostic PAH concentration ratios were used as a tool to identify and characterize the PAH sources. The results reflect high PM₁₀ and PAH concentrations (particulate matter (PM)?=?270–1,270 μg/m³). The corresponding average PAH concentrations were in the range of 18?±?8 to 1,003?±?597 ng/m³ and the total concentrations (total PAHs (TPAHs) of 17 compounds) varied from 1,383 to 13,470 ng/m³ with an average of 5,871?±?2,830 ng/m³. The detection and quantification limits were 1–3 and 1–10 ng/ml, respectively, with a recovery range of 42–80 %. The ratio of the sum of the concentrations of the nine major non-alkylated compounds to the total (CPAHs/TPAHs) was 0.87?±?0.10, and other ratios were determined to apportion the PM sources. The PAHs found are characteristic for emissions from traffic with diesel being a predominant source.     

Numerical study of the effect of ventilation pattern on coarse, fine, and very fine particulate matter removal in partitioned indoor environment

An indoor size-dependent particulate matter (PM) transport approach is developed to investigate coarse PM (PM10), fine PM (PM2.5), and very fine PM (PM1) removal behaviors in a ventilated partitioned indoor environment. The approach adopts the Eulerian large eddy simulation of turbulent flow and the Lagrangian particle trajectory tracking to solve the continuous airflow phase and the discrete particle phase, respectively. Model verification, including sensitivity tests of grid resolution and particle numbers, is conducted by comparison with the full-size experiments conducted previously. Good agreement with the measured mass concentrations is found. Numerical scenario simulations of the effect of ventilation patterns on PM removal are performed by using three common ventilation patterns (piston displacement, mixing, and cross-flow displacement ventilation) with a measured indoor PM10 profile in the Taipei metropolis as the initial condition. The temporal variations of suspended PM10, PM2.5, and PM1 mass concentrations and particle removal mechanisms are discussed. The simulated results show that for all the of the three ventilation patterns, PM2.5 and PM1 are much more difficult to remove than PM10. From the purpose of health protection for indoor occupants, it is not enough to only use the PM10 level as the indoor PM index. Indoor PM2.5 and PM1 levels should be also considered. Cross-flow displacement ventilation is more effective to remove all PM10, PM2.5, and PM1 than the other ventilation patterns. Displacement ventilation would result in more escaped particles and less deposited particles than mixing ventilation.     

Effect of meteorological parameters on fine and coarse particulate matter mass concentration in a coal-mining area in Zonguldak, Turkey

In this work, the effect of meteorological parameters and local topography on mass concentrations of fine (PM2.5) and coarse (PM2.5-10) particles and their seasonal behavior was investigated. A total of 236 pairs of samplers were collected using an Anderson Dichotomous sampler between December 2004 and October 2005. The average mass concentrations of PM2.5, PM2.5-10, and particulate matter less than 10 microm in aerodynamic diameter (PM10) were found to be 29.38, 23.85, and 53.23 microg/m3, respectively. The concentrations of PM2.5 and PM10 were found to be higher in heating seasons (December to May) than in summer. The increase of relative humidity, cloudiness, and lower temperature was found to be highly related to the increase of particulate matter (PM) episodic events. During non-rainy days, the episodic events for PM2.5 and PM10 were increased by 30 and 10.7%, respectively. This is a result of the extensive use of fuel during winter for heating purposes and also because of stagnant air masses formed because of low temperature and low wind speed over the study area.     

Identification of haze-creating sources from fine particulate matter in Dhaka aerosol using carbon fractions

Fine particulate matter (PM_2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 μg/m³ and 6.0 μg/m³ of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter.

Implications: Fine particle concentrations in Dhaka, Bangladesh, are very high and cause significant degradation of urban visibility. This work shows that using carbon fraction data from the IMPROVE OC/EC protocol provides improved source apportionment. Soil dust, brick kiln, diesel, gasoline, and the Pb sources contribute strongly to haze, particularly in the winter.     

Sources of fine urban particulate matter in Detroit, MI

Data from the speciation trends network (STN) was used to evaluate the amount and temporal patterns of particulate matter originating from local industrial sources and long-range transport at two sites in Detroit, MI: Allen Park, MI, southwest of both Detroit and the areas of heavy industrial activity; Dearborn, MI, located on the south side of Detroit near the most heavily industrialized region. Using positive matrix factorization (PMF) and comparing source contributions at Allen Park to those in Dearborn, contributions made by local industrial sources (power plants, coke refineries, iron smelting, waste incineration), local area sources (automobile and diesel truck) and long range sources of PM(2.5) can be distinguished in greater Detroit. Overall, the mean mass concentration measured at Dearborn was 19% higher than that measured at Allen Park. The mass at Allen Park was apportioned as: secondary sulfate 31%, secondary nitrate 28%, soil 8%, mixed aged sea and road salts 4%, gasoline 15%, diesel 4%, and biomass burning 3%. At Dearborn the mass was apportioned as: secondary sulfate 25%, secondary nitrate 20%, soil 12%, mixed aged sea and road salts 4%, gasoline 20%, diesel 8%, iron and steel, 5%, and mixed industrial 7%. The impact of the iron and steel, soil, and mixed aged sea and road salt was much higher at the Dearborn site than at the Allen Park site, suggesting that close proximity to a local industrial complex has a direct negative impact on local air quality.     

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM_2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM_2.5 concentration (13.2 ± 13.7 µg/m³) was similar to the average measured Grimm 11-R PM_2.5 concentration (11.3 ± 15.1 µg/m³). The overall correlation (r²) for PM_2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m³) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m³) with an r² of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.

Implications: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM_2.5 and coarse PM (PM_10-2.5) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.     

Effect of the fine fraction of particulate matter versus the coarse mass and other pollutants on daily mortality in Santiago, Chile

Daily counts of non-accidental deaths in Santiago, Chile, from 1988 to 1996 were regressed on six air pollutants--fine particles (PM2.5), coarse particles (PM10-2.5), CO, SO2, NO2, and O3. Controlling for seasonal and meteorological conditions was done using three different models--a generalized linear model, a generalized additive model, and a generalized additive model on previously filtered data. Single- and two-pollutant models were tested for lags of 1-5 days and the average of the previous 2-5 days. The increase in mortality associated with the mean levels of air pollution varied from 4 to 11%, depending on the pollutants and the way season of the year was considered. The results were not sensitive to the modeling approaches, but different effects for warmer and colder months were found. Fine particles were more important than coarse particles in the whole year and in winter, but not in summer. NO2 and CO were also significantly associated with daily mortality, as was O3 in the warmer months. No consistent effect was observed for SO2. Given particle composition in Santiago, these results suggest that combustion-generated pollutants, especially from motor vehicles, may be associated with increased mortality. Temperature was closely associated with mortality. High temperatures led to deaths on the same day, while low temperatures lead to deaths from 1 to 4 days later.     

Determination of levoglucosan in atmospheric fine particulate matter

A microanalytical method suitable for the quantitative determination of the sugar anhydride levoglucosan in low-volume samples of atmospheric fine particulate matter (PM) has been developed and validated. The method incorporates two sugar anhydrides as quality control standards. The recovery standard sedoheptulosan (2,7-anhydro-beta-D-altro-heptulopyranose) in 20 microL solvent is added onto samples of the atmospheric fine PM and aged for 1 hr before ultrasonic extraction with ethylacetate/ triethylamine. The extract is reduced in volume, an internal standard is added (1,5-anhydro-D-mannitol), and a portion of the extract is derivatized with 10% by volume N-trimethylsilylimidazole. The derivatized extract is analyzed by gas chromatography/mass spectrometry (GC/MS). The recovery of levoglucosan using this procedure was 69 +/- 6% from five filters amended with 2 microg levoglucosan, and the reproducibility of the assay is 9%. The limit of detection is approximately 0.1 microg/mL, which is equivalent to approximately 3.5 ng/m3 for a 10 L/min sampler or approximately 8.7 ng/m3 for a 4 L/min personal sampler (assuming 24-hr integrated samples). We demonstrated that levoglucosan concentrations in collocated samples (expressed as ng/m3) were identical irrespective of whether samples were collected by PM with aerodynamic diameter < or = 2.5 microm or PM with aerodynamic diameter < or = 10 microm impactors. It was also demonstrated that X-ray fluorescence analysis of samples of atmospheric PM, before levoglucosan determinations, did not alter the levels of levoglucosan.     

Spatial, temporal, and interspecies patterns in fine particulate matter in Texas

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) field study was conducted from July to October 1999 and was followed by several years of modeling and data analyses to examine the causes of haze at Big Bend National Park TX (BBNP). During BRAVO, daily speciated fine (diameter <2.5 microm) particulate concentrations were measured at 37 sites throughout Texas. At the primary receptor site, K-Bar Ranch, there were many additional measurements including a "high-sensitivity" version of the 24-hr fine particulate elemental data. The spatial, temporal, and interspecies patterns in these data are examined here to qualitatively investigate source regions and source types influencing the fine particulate concentrations in Texas with an emphasis on sources of sulfates, the largest contributor to fine mass and light extinction. Peak values of particulate sulfur (S) varied spatially and seasonally. Maximum S was in Northeast Texas during the summer, whereas peak S at BBNP was in the fall. Sulfate acidity at BBNP also varied by month. Sources of Se were evident in Northeast Texas and from the Carbón I and II plants. High S episodes at BBNP during BRAVO had several different trace element characteristics. Carbon concentrations at BBNP during BRAVO were probably mostly urban-related, with arrival from the Houston area likely. The Houston artificial tracer released during the second half of BRAVO was highly correlated with some carbon fractions. There was evidence of the influence of African dust at sites throughout Texas during the summer. Patterns in several trace elements were also examined. Vanadium was associated with air masses from Mexico. Lead concentrations in southern Texas have dropped dramatically over the past several years.     

Molecular composition of organic fine particulate matter in Houston,TX

Organic fine particulate matter collected in Houston, TX between March 1997 and March 1998 was analyzed to determine the concentration of individual organic compounds. Samples from four sites were analyzed including two industrial locations (Houston Regional Monitoring Corporation (HRM-3) site in Channelview and Clinton Drive site near the Ship Channel Turning Basin), one suburban location (Bingle Drive site in Northwest Houston) and one background site (Galveston Island). At the three urban locations, samples were divided into three seasonal sample aggregates (spring, summer and winter), while at the background site a single annual average sample pool was used. Between 10 and 16 individual samples were pooled to get aggregate samples with enough organic carbon mass for analysis. Overall, 82 individual organic compounds were quantified. These include molecular markers which are compounds unique to specific fine particle sources and can be used to track the relative contribution of source emissions to ambient fine particle levels. The differences both spatially and temporally in these tracers can be used to evaluate the variability in emission source strengths.     

Nonlinear analysis and prediction of coarse particulate matter concentration in ambient air

This study attempts to characterize and predict coarse particulate matter (PM10) concentration in ambient air using the concepts of nonlinear dynamical theory. PM10 data observed daily from 1999 to 2002 at a site in Mumbai, India, was used to study the applicability of the chaos theory. First, the autocorrelation function and Fourier power spectrum were used to analyze the behavior of the time-series. The dynamics of the time-series was additionally studied through correlation integral analysis and phase space reconstruction. The nonlinear predictions were then obtained using local polynomial approximation based on the reconstructed phase space. The results were then compared with the autoregressive model. The results of nonlinear analysis indicated the presence of chaotic character in the PM10 time-series. It was also observed that the nonlinear local approximation outperforms the autoregressive model, because the observed relative error of prediction for the autoregressive model was greater than the local approximation model. The invariant measures of nonlinear dynamics computed for the predicted time-series using the two models also supported the same findings.     

Measurement, analysis, and modeling of fine particulate matter in eastern North Carolina

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.     

Spatial and temporal variability in urban fine particulate matter concentrations

Identification of hot spots for urban fine particulate matter (PM(2.5)) concentrations is complicated by the significant contributions from regional atmospheric transport and the dependence of spatial and temporal variability on averaging time. We focus on PM(2.5) patterns in New York City, which includes significant local sources, street canyons, and upwind contributions to concentrations. A literature synthesis demonstrates that long-term (e.g., one-year) average PM(2.5) concentrations at a small number of widely-distributed monitoring sites would not show substantial variability, whereas short-term (e.g., 1-h) average measurements with high spatial density would show significant variability. Statistical analyses of ambient monitoring data as a function of wind speed and direction reinforce the significance of regional transport but show evidence of local contributions. We conclude that current monitor siting may not adequately capture PM(2.5) variability in an urban area, especially in a mega-city, reinforcing the necessity of dispersion modeling and methods for analyzing high-resolution monitoring observations.