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.     

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.     

Estimating uncertainties and uncertainty contributors of CMB PM2.5 source apportionment results

The chemical mass balance (CMB) model was applied for source apportionment of PM_2.5 in Atlanta in order to explore levels and causes of uncertainties in source contributions. Monte Carlo analysis with Latin hypercube sampling (MC-LHS) was performed to evaluate the source impact uncertainties and quantify how uncertainties in ambient measurement and source profile data affect results. In general, uncertainties in the source profile data contribute more to the final uncertainties in source apportionment results than do those in ambient measurement data. Uncertainty contribution estimates suggest that non-linear interactions among source profiles also affect the final uncertainties although their influence is typically less than uncertainties in source profile data.     

Assessment of natural components of PM10 at UK urban and rural sites

Proposals from the European Commission have raised the possibility that Member States may be able to subtract the concentrations of natural components of airborne particulate matter from measured concentrations when evaluating compliance with EU Limit Values. By applying the pragmatic mass closure model [Harrison et al., 2003. A pragmatic mass closure model for airborne particulate matter at urban background and roadside sites. Atmospheric Environment 37, 4927–4933] to chemical composition data for PM₁₀, it has been possible to estimate the concentrations of natural sea salt, strongly bound water and secondary organic carbon (which is assumed wholly biogenic) to the measured mass of PM₁₀. Because of the difficulty in distinguishing between natural and anthropogenic crustal dusts, the contribution of natural windblown dust and soil has not been accounted for. When the natural components are estimated for two urban and one rural site in the UK, the long-term mean PM₁₀ concentration is reduced by between 5.2 and 7.3 μg m⁻³. The number of exceedences of the 50 μg m⁻³ 24-h limit value falls dramatically from 54 to 21 (from a total of 291 days) at an urban street canyon site, 7 to 3 (n=292 days) at an urban background site and from 8 to 0 (n=241 days) at a rural site when using gravimetric PM₁₀ concentrations. The calculations have also been performed using PM₁₀ concentrations measured by TEOM increased by a factor of 1.3 as recommended by the European Commission as an interim means of estimating gravimetric equivalency, and the number of exceedences of the 24-h limit value fell from 92 to 47 (from a total of 291 days) at the urban street canyon site, from 11 to 3 (n=292 days) at the urban background site and from 6 to 3 (n=241) at the rural site. Clearly, therefore, application of this proposed measure would make a very major difference to the likelihood of compliance or otherwise with the 24-h limit value for PM₁₀.     

The impact of wood smoke on ambient PM2.5 in northern Rocky Mountain valley communities

During the winters of 2006/2007 and 2007/2008, PM_2.5 source apportionment programs were carried out within five western Montana valley communities. Filter samples were analyzed for mass and chemical composition. Information was utilized in a Chemical Mass Balance (CMB) computer model to apportion the sources of PM_2.5. Results showed that wood smoke (likely residential woodstoves) was the major source of PM_2.5 in each of the communities, contributing from 56% to 77% of the measured wintertime PM_2.5. Results of ¹⁴C analyses showed that between 44% and 76% of the measured PM_2.5 came from a new carbon (wood smoke) source, confirming the results of the CMB modeling. In summary, the CMB model results, coupled with the ¹⁴C results, support that wood smoke is the major contributor to the overall PM_2.5 mass in these rural, northern Rocky Mountain airsheds throughout the winter months.     

Long-term variation of PM2.5 levels and composition at rural, urban, and roadside sites in Hong Kong: Increasing impact of regional air pollution

Long-term study of air pollution plays a decisive role in formulating and refining pollution control strategies. In this study, two 12-month measurements of PM_2.5 mass and speciation were conducted in 00/01 and 04/05 to determine long-term trend and spatial variations of PM_2.5 mass and chemical composition in Hong Kong. This study covered three sites with different land-use characteristics, namely roadside, urban, and rural environments. The highest annual average PM_2.5 concentration was observed at the roadside site (58.0±2.0 μg m⁻³ (average±2σ) in 00/01 and 53.0±2.7 μg m⁻³ in 04/05), followed by the urban site (33.9±2.5 μg m⁻³ in 00/01 and 39.0±2.0 μg m⁻³ in 04/05), and the rural site (23.7±1.9 μg m⁻³ in 00/01 and 28.4±2.4 μg m⁻³ in 04/05). The lowest PM_2.5 level measured at the rural site was still higher than the United States’ annual average National Ambient Air Quality Standard of 15 μg m⁻³. As expected, seasonal variations of PM_2.5 mass concentration at the three sites were similar: higher in autumn/winter and lower in summer. Comparing PM_2.5 data in 04/05 with those collected in 00/01, a reduction in PM_2.5 mass concentration at the roadside (8.7%) but an increase at the urban (15%) and rural (20%) sites were observed. The reduction of PM_2.5 at the roadside was attributed to the decrease of carbonaceous aerosols (organic carbon and elemental carbon) (>30%), indicating the effective control of motor vehicle emissions over the period. On the other hand, the sulfate concentration at the three sites was consistent regardless of different land-use characteristics in both studies. The lack of spatial variation of sulfate concentrations in PM_2.5 implied its origin of regional contribution. Moreover, over 36% growth in sulfate concentration was found from 00/01 to 04/05, suggesting a significant increase in regional sulfate pollution over the years. More quantitative techniques such as receptor models and chemical transport models are required to assess the temporal variations of source contributions to ambient PM_2.5 mass and chemical speciation in Hong Kong.     

PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

The measurement of roadway PM10 emission rates using atmospheric tracer ratio techniques

In this work, stationary and mobile point source tracer release techniques have been used to determine PM₁₀ emission rates from four-lane commercial/residential paved roads under sanded and unsanded conditions, and from unpaved roads relative to site-specific vehicular and ambient parameters. Measured street (4 + lanes; ? 10,000 vehicles per day) emission factors for unsanded and sanded roads were 40 and 20% lower, respectively, than the EPA approved reference value. The sanded road emission factor was approximately 40% higher than that for the unsanded road. These results indicate a consistent relationship between PM₁₀ and relative humidity under unsanded conditions. There is some evidence to suggest that street sweeping has a measurable effect on PM,, emission reduction during periods of low relative humidity (i.e. ? 30%). Within the constraints imposed by the variable experimental conditions, the emission factors determined for unpaved roads agreed reasonably well with the unpaved road empirical formula. Limited correlations were observed with ambient meteorological parameters. The capability of the “upwind-dowiawind” concentration modeling method to predict accurate emission was tested using a Gaussian dispersion model (SIMFLUX). Predictions agreed well with the experimentally determined emission factors.     

Regression modelling of hourly NOx and NO2 concentrations in urban air in London

Based on hourly measurements of NO_x NO₂ and O₃ and meteorological data, an ordinary least squares (OLS) model and a first-order autocorrelation (AR) model were developed to analyse the regression and prediction of NO_x and NO₂ concentrations in London. Primary emissions and wind speed are the most important factors influencing NO_x concentrations; in addition to these two, reaction of NO with O₃ is also a major factor influencing NO₂ concentrations. The AR model resulted in high correlation coefficients (R > 0.95) for the NO_x and NO₂ regression based on a whole year's data, and is capable of predicting NO₂ (R = 0.83) and NO_x (R = 0.65) concentrations when the explanatory variables were available. The analysis of the structure of regression models by Principal Component Analysis (PCA) indicates that the regression models are stable. The results of the OLS model indicate that there was an exceptional NO₂ source, other than primary emission and reaction of NO with O₃, in the air pollution episode in London in December 1991.     

Trees as bioindicator of heavy metal pollution in three European cities

Concentrations of four heavy metals were determined in tree leaves and bark collected from polluted and non-polluted areas of three European cities (Salzburg, Belgrade and Thessaloniki) for a comparative study. Platanus orientalis L. and Pinus nigra Arn., widespread in urban northern and southern Europe, were tested for their suitability for air quality biomonitoring. Leaves and barks were collected uniformly of an initial quantity of about 30 g of each sample. Analysis was accomplished by electrothermal atomic absorption spectrometry after total digestion. Site-dependent variations were found with the highest concentration level measured in Belgrade, followed by Thessaloniki and Salzburg. A higher accumulation of heavy metals was found in bark compared to leaves. Pine tree bark, accumulating higher concentrations of trace metals compared to plane tree bark, shows a higher efficiency as bioindicator for urban pollution. Both indicator species are suitable for comparative studies on bioindication of urban air pollution.     

Assessment of population exposure to particulate matter pollution in Chongqing, China

To determine the population exposure to PM(10) in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM(10) concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM(10) were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 microg/m(3), respectively, in winter, summer and as the annual average. Indoor PM(10) level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM(10) exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas.     

First assessment of the PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript> particulate level in the ambient air of belgrade city

INTENTION, GOAL, SCOPE, BACKGROUND: As the strong negative health effect of exposure to the inhalable particulate matter PM10 in the urban environment has been confirmed, the study of the mass concentrations, physico-chemical characteristics, sources, as well as spatial and temporal variation of atmospheric aerosol particles becomes very important. OBJECTIVE: This work is a pilot study to assess the concentration level of ambient suspended particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade central urban area. Average daily concentrations of PM10 and PM2.5 have been measured at three representative points in the city between June 2002 and December 2002. The influence of meteorological parameters on PM10 and PM2.5 concentrations was analyzed, and possible pollution sources were identified. METHODS: Suspended particles were collected on Pure Teflon filters by using a Mini-Vol low-volume air sampler (Airmetrics Co., Inc.; 5 l min(-1) flow rate). Particle mass was determined gravimetrically after 48 h of conditioning in a desiccator, in a Class 100 clean room at the temperature T = 20 degrees C and at about 50% constant relative humidity (RH). RESULTS AND DISCUSSION: Analysis of the PM10 data indicated a marked difference between season without heating--(summer; mean value 56 microg m(-3)) and heating season--(winter; mean value 96 microg m3); 62% of samples exceeded the level of 50 microg m(-3). The impact of meteorological factors on PM concentrations was not immediately apparent, but there was a significant negative correlation with the wind speed. CONCLUSIONS: The PM10 and PM2.5 mass concentrations in the Belgrade urban area had high average values (77 microg m(-3) and 61 microg m(-3)) in comparison with other European cities. The main sources of particulate matter were traffic emission, road dust resuspension, and individual heating emissions. When the air masses are coming from the SW direction, the contribution from the Obrenovac power plants is evident. During days of exceptionally severe pollution, in both summer and winter periods, high production of secondary aerosols occurred, as can be seen from an increase in PM2.5 in respect to PM10 mass concentration. RECOMMENDATION AND OUTLOOK: The results obtained gave us the first impression of the concentration level of particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade ambient air. Due to measured high PM mass concentrations, it is obvious that it would be very difficult to meet the EU standards (EEC 1999) by 2010. It is necessary to continue with PM10 and PM2.5 sampling; and after comprehensive analysis which includes the results of chemical and physical characterization of particles, we will be able to recommend effective control measures in order to improve air quality in Belgrade.     

Impact of the 1998 Central American fires on PM2.5 mass and composition in the southeastern United States

The impact of the Central American fires on PM_2.5 mass concentration and composition in the Tennessee Valley region during portions of May, 1998, has been quantified. Elevated concentrations of smoke aerosol tracers—fine potassium, (and to a lesser extent, calcium and silicon) and, where available, organic and elemental carbon—were observed in the region during times in which satellite imagery (TOMS and GOES-8) showed regional transport of hazy, smoky airmasses from southern Mexico and adjacent areas of Central America. Back-trajectories from network sites in the Tennessee Valley network were consistent with this regional transport. The extent of transport of extra-regional fine particle mass during May, 1998, is discussed relative to the new US fine particle mass-based standards for fine particulate matter.     

The short-term effects of air pollution on adolescent lung function in Taiwan

A mass screening of lung function associated with air pollutants for children is limited. This study assessed the association between air pollutants exposure and the lung function of junior high school students in a mass screening program in Taipei city, Taiwan. Among 10,396 students with completed asthma screening questionnaires and anthropometric measures, 2919 students aged 12-16 received the spirometry test. Forced vital capacity (FVC) and forced expiratory flow in 1 s (FEV₁) in association with daily ambient concentrations of particulate matter with diameter of 10 μm or less (PM₁₀), sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), and ozone (O₃) were assessed by regression models controlling for the age, gender, height, weight, student living districts, rainfall and temperature. FVC, had a significant negative association with short-term exposure to O₃ and PM₁₀ measured on the day of spirometry testing. FVC values also were reversely associated with means of SO₂, O₃, NO₂, PM₁₀ and CO exposed 1 d earlier. An increase of 1-ppm CO was associated with the reduction in FVC for 69.8 mL (95% CI: −115, −24.4 mL) or in FEV₁ for 73.7 mL (95% CI: −118, −29.7 mL). An increase in SO₂ for 1 ppb was associated with the reductions in FVC and FEV₁ for 12.9 mL (95% CI: −20.7, −5.09 mL) and 11.7 mL (95% CI: −19.3, −4.16 mL), respectively. In conclusion, the short-term exposure to O₃ and PM₁₀ was associated with reducing FVC and FEV₁. CO and SO₂ exposure had a strong 1-d lag effect on FVC and FEV₁.     

Impacts of Meteorological Factors on PM10: Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) Approaches

In this study, prediction capacities of multi-linear regression (MLR) and artificial neural networks (ANN) onto coarse particulate matter (PM₁₀) concentrations were investigated. Different meteorological factors on particulate pollution were chosen for operating variables in the model analyses. Two different regions (urban and industrial) were identified in the region of Kocaeli, Turkey. All data sets were obtained from air quality monitoring network of the Ministry of Environment and Urban Planning, and 120 data sets were used in the MLR and ANN models. Regression equations explained the effects of the meteorological factors in MLR analyses. In the ANN model, backpropagation network with two hidden layers has achieved the best prediction efficiency. Determination coefficients and error values were examined for each model. ANN models displayed more accurate results compared to MLR.