Windblown Dust Contributes to High PM25 Concentrations

ABSTRACT

The revised National Ambient Air Quality Standards for PM include fine particulate standards based upon mass measurements of PM₂₅. It is possible in arid and semi-arid regions to observe significant coarse mode intrusion in the PM_2.5 measurement. In this work, continuous PM₁₀, PM_2.5, and PM_1.0 were measured during several windblown dust events in Spokane, WA. PM_{2 5} constituted ~30% of the PM₁₀ during the dust event days, compared with ~48% on the non-dusty days preceding the dust events. Both PM₁₀ and PM_2.5 were enhanced during the dust events. However, PM_1.0 was not enhanced during dust storms that originated within the state of Washington. During a dust storm that originated in Asia and impacted Spokane, PM_1.0 was also enhanced, although the Asian dust reached Washington during a period of stagnation and poor dispersion, so that local sources were also contributing to high particulate levels. The “intermodal” region of PM, defined as particles ranging in aerodynamic size from 1.0 to 2.5 um, was found to represent a significant fraction of PM₂₅ (~51%) during windblown dust events, compared with 28% during the non-dusty days before the dust events.     

Spatial and temporal variations in PM10 and PM2.5 source contributions and comparison to emissions during the 1995 integrated monitoring study

The ambient PM₁₀ and PM_2.5 data collected during the fall and winter portions of the 1995 Integrated Monitoring Study (IMS95) were used to conduct Chemical Mass Balance (CMB) Modeling to determine source contribution estimates. Data from the core and saturation monitoring sites provided an extensive database for evaluating the spatial and temporal variations of contributing sources. Geological sources dominated fall samples, while secondary ammonium nitrate and carbonaceous sources were the largest contributors for winter samples. Secondary ammonium nitrate concentrations were uniform across all sites during both the fall and winter. Site-to-site variability was primarily due to differences in geological contributions in the fall, and carbonaceous source contributions in the winter. During the winter, diurnal profiles of particulate matter (PM) were driven by variations in carbonaceous sources at urban sites, and by variations in secondary ammonium nitrate at rural sites. Although records of day-specific PM activities were recorded during the study, no correlation was observed between 24-h CMB results and specific activities. The ambient data collected during IMS95 was also used to evaluate the adequacy of the emissions inventory. Comparison of ambient and emissions based ratios of NMHC/NO_x, PM/NO_x, CO/NO_x, and SO_x/NO_x suggested that emissions of NMHC and CO in some locations may be underestimated, while emissions for PM and SO_x may be overestimated. Comparison of fractional primary CMB source contribution estimates to corresponding fractional emissions estimates indicated that geological sources were overemphasized in the inventory, while carbonaceous sources were underrepresented.     

Development of a PM2 5 Emissions Inventory for the South Coast Air Basin

ABSTRACT

With the promulgation of a national PM_2.5 ambient air quality standard, it is important that PM_2.5 emissions inventories be developed as a tool for understanding the magnitude of potential PM2.5 violations. Current PM₁₀ inventories include only emissions of primary particulate matter (1 ^ï PM), whereas, based on ambient measurements, both PM₁₀ and PM2.5 emissions inventories will need to include sources of both 1^ï PM and secondary particulate matter (2^ï PM). Furthermore, the U. S. Environmental Protection Agency’s (EPA) current edition of AP-42 includes size distribution data for 1o PM that overestimate the PM_2.5 fraction of fugitive dust sources by at least a factor of 2 based on recent studies.

This paper presents a PM_2.5 emissions inventory developed for the South Coast Air Basin (SCAB) that for the first time includes both 1^ï PM and 2^ï PM. The former is calculated by multiplying PM₁₀ emissions estimates by the PM_2.5/PM₁₀ ratios for different sources. The latter is calculated from estimated emission rates of gas-phase aerosol precursor and gas to aerosol conversion rates consistent with the measured chemical composition of ambient PM_2.5 concentrations observed in the SCAB. The major finding of this PM_2.5 emissions inventory is that the ^2ï aerosol component is more than twice the ^1ï aerosol component, which may result in widely different control strategies being required for fine PM and coarse PM.     

Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside

The 24-h average coarse (PM₁₀) and fine (PM_2.5) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM₁₀ and PM_2.5 concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM₁₀ concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM_2.5 concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM₁₀ and PM_2.5 masses showed a high concentration in winter followed by monsoon and summer seasons.The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM₁₀ and PM_2.5 concentrations at the study area. Results indicated that marine aerosol (40.4% in PM₁₀ and 21.5% in PM_2.5) and secondary PM (22.9% in PM₁₀ and 42.1% in PM_2.5) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM₁₀ and 6% in PM_2.5), biomass burning (0.7% in PM₁₀ and 14% in PM_2.5), tire and brake wear (4.1% in PM₁₀ and 5.4% in PM_2.5), soil (3.4% in PM₁₀ and 4.3% in PM_2.5) and other sources (12.7% in PM₁₀ and 6.8% in PM_2.5).     

Determination of PM2.5 sources using time-resolved integrated source and receptor models

Multivariate statistical techniques are applied to particulate matter (PM) and meteorological data to identify the sources responsible for evening PM spikes at Sunland Park, NM (USA). The statistical techniques applied are principal components analysis (PCA), redundancy analysis (RDA), and absolute principal components scores analysis (APCSA), and the data evaluated are 3-h average (6–9 p.m.) PM_2.5 mass and chemical composition and 1-h average PM_2.5 and PM₁₀ mass and environmental data collected in the winter of 2002. Although the interpretation of the data was complicated by the presence of sources which are likely changing in time (e.g. brick kilns), the multivariate analyses indicate that the evening high PM_2.5 is associated with burning-activities occurring to the south of Sunland Park, and these emissions are characterized by elevated Sb, Cl⁻, and elemental carbon; ∼68% of the PM_2.5 mass can be attributed to this source. The PM₁₀ evening peaks, on the other hand, are mainly caused by resuspended dust generated by vehicular movements south of the site and transported by the local terrain-induced drainage flow.     

PM Emissions Emanating from Limited-Access Highways

ABSTRACT

Motor vehicle contributions to primary particulate matter (PM) emissions include exhaust, tire wear, brake and clutch wear, and resuspended road dust. Relatively few field studies have been conducted to quantify fleetaverage exhaust emissions for actual on-road conditions. Therefore, direct measurements of motor vehicle-related PM emissions are warranted. In this study, PM₁₀ and PM_2.5 mass concentrations were measured near two major highways in the St. Louis area over the period from February–April 1997. Samplers were deployed both upwind and downwind of the roadways to capture the transport and dispersion of PM with distance from the roadway. The observed microscale concentration fields were compared to estimates using the PART5 emission factor model together with the CALINE4 highway dispersion model. Traffic- induced PM mass concentrations observed downwind of the roadway were always less than PART5/CALINE4 predictions; average percent differences for observed traffic-induced mass concentrations compared to predicted values were ?34% for PM_2.5 and -70% for PM₁₀. In most cases, the observed PM concentration decay with increasing distance from the roadway was steeper than predicted by dispersion modeling. Motor vehicle-induced emission factors were reconstructed by fitting CALINE4 to the observed concentration data with the emission factor as the sole adjustable parameter. Reconstructed fleet-average motor vehicle emission factors for the urban interstate highway were 0.03–0.04 g/VMT for both PM_2.5 and PM₁₀, while the fleet-average emission factors for the rural interstate highway were 0.2 and 0.3 g/VMT for PM_2.5 and PM₁₀, respectively.     

PM composition and source reconciliation in Mexico City

PM_2.5 and PM₁₀ were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM_2.5 concentrations ranged from 32 to 70 μg m⁻³ while that of PM10 did so from 51 to 132 μg m⁻³. The most abundant chemical species for both PM fractions were: OC, EC, SO₄²⁻, NO₃⁻, NH₄⁺, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM_2.5 than for PM₁₀, and did not display significant differences during the sampling period. The PM_2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O₃S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.     

Air quality at Santiago,Chile: a box modeling approach II. PM2.5, coarse and PM10 particulate matter fractions

Ambient monitored data at Santiago, Chile, are analyzed using box models with the goal of assessing contributions of different economic activities to air pollution levels. The box modeling approach was applied to PM₁₀, PM_2.5 and coarse (PM₁₀–PM_2.5) particulate matter (PM) fractions; the period analyzed is 1989–1999. A linear model for each PM fraction was obtained, having as independent variables CO and SO₂ concentrations, plus a term proportional to (wind speed)⁻¹ that lumps together non-combustion emissions and secondary generation terms; wet scavenging is included as another independent variable. Model identification results show good agreement for the different parameters across monitoring stations. The washout ratios and scavenging coefficients agree with data published in the literature, being higher for the coarse PM fraction. The CO and SO₂ coefficients fitted for 1989–1995 agree with a priori estimates for the same period. Background estimates for the PM fractions are in agreement with measurement campaigns in upwind sites. Results show that transportation sources have become the dominant contributors to ambient PM levels, while stationary sources have decreased their contributions in the last years. The relative importance of mobile sources to PM_2.5 ambient concentrations has doubled in the last 10 years, whereas stationary sources have reduced their relative contributions to half the value in the early 1990s. Model estimates of regional background of PM_2.5 and PM₁₀ have decreased 50% and 22% in the last decade, respectively; coarse background has shown no significant change. The final conclusion is that there is room and need for a more intensive emission reduction strategy for Santiago, focusing on mobile sources. The approach pursued in this work is feasible for cities or regions where comprehensive, transport and chemistry models are not available yet, but estimates of air quality contributions are needed for policy purposes. The methodology requires data on ambient air quality measurements and surface meteorology.     

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM_1–10) sources in a village, B?ezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM_1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM₁₀ and PM_1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM_1–10 data across the multiple sites. PMF resolved seven sources of PM_1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM_1–10. The conditional probability function (CPF) helped to identified local sources of PM_1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM_1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region.

Supplemental Materials:?Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM_1–10; (3) factors contribution to PM_1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.     

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.     

Response

ABSTRACT

The Las Vegas Valley PM₁₀ Study was conducted during 1995 to determine the contributions to PM₁₀ aerosol from fugitive dust, motor vehicle exhaust, residential wood combustion, and secondary aerosol sources. Twenty-four-hr PM₁₀ samples were collected at two neighborhood-scale sites every sixth day for 13 months. Five week-long intensive studies were conducted over a middle-scale sub-region at 29 locations that contained many construction projects emitting fugitive dust. The study found that the zone of influence around individual emitters was less than 1 km. Most of the sampling sites in residential and commercial areas yielded equivalent PM₁₀ concentrations in the neighborhood region, even though they were more distant from each other than they were from the nearby construction sources. Based on chemical mass balance (CMB) receptor modeling, fugitive dust accounted for 80–90% of the PM₁₀, and motor vehicle exhaust accounted for 3–9% of the PM₁₀ in the Las Vegas Valley.     

Chemical Composition and Source Apportionment of PM25 Particles in the Sihwa Area,Korea

ABSTRACT

To investigate the chemical characteristics of fine particles in the Sihwa area, Korea, atmospheric aerosol samples were collected using a dichotomous PM₁₀ sampler and two URG PM_2.5 cyclone samplers during five intensive sampling periods between February 1998 and February 1999. The Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS), ion chromatograph (IC), and thermal manganese dioxide oxidation (TMO) methods were used to analyze the trace elements, ionic species, and carbonaceous species, respectively. Backward trajectory analysis, factor analysis, and a chemical mass balance (CMB) model were used to estimate quantitatively source contributions to PM_{2 5} particles collected in the Sihwa area.

The results of PM_2.5 source apportionment using the CMB7 receptor model showed that (NH₄)₂SO₄ was, on average, the major contributor to PM_2.5 particles, followed by nontraffic organic carbon (OC) emission, NH₄NO₃, agricultural waste burning, motor vehicle emission, road dust, waste incineration, marine aerosol, and others. Here, the nontraffic OC sources include primary anthropogenic OC emitted from the industrial complex zone, secondary OC, and organic species from distant sources. The source impact of waste incineration emission became significant when the dominant wind directions were from southwest and west sectors during the sampling periods. It was found that PM_2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.     

A study on variations of concentrations of particulate matter with different sizes in Lanzhou,China

Lanzhou is one of the most air-polluted cities in China and in the world, and its primary air pollutant is particulate matter (PM). Different size particulate matter (TSP, PM₁₀, PM_2.5 and PM_1.0) have different sources and affect the environment and human health differently, so it is very important to study the pollutant characteristics of different particles in order to deeply understand the pollution situation of Lanzhou city and establish reasonable preventive countermeasures. TSP, PM₁₀, PM_2.5 and PM_1.0 concentrations were simultaneously measured in Lanzhou to detect the annual and diurnal variations of concentrations of PM with different sizes and possible causes. The main results are as follows: (1) The annual distribution of monthly average concentrations for coarse particles (TSP and PM₁₀) is bimodal with the highest peak in April, which is different from the situation in other cities not affected by sand-dust events. However, the annual distribution for fine particles (PM_2.5 and PM_1.0) is unimodal with the peak in December. This difference between coarse and fine particles indicates that sand-dust events in spring carry much more coarse than fine particles to Lanzhou. This result is supported by the correlation between springtime wind speed and concentrations of PM with different sizes. (2) Under normal conditions (without dust intrusions), the diurnal distribution of coarse particle concentration in Lanzhou is bimodal. However, the distribution is trimodal during dust intrusions in April, with an extra peak in the afternoon. (3) In general, the highest concentration peaks of the diurnal variations for TSP, PM₁₀, PM_2.5 and PM_1.0 occur at about the same time. However, there are obvious differences in the occurrence time of the minimum concentrations among different kinds of PM. The differences in the occurrence time of minima between coarse and fine particles are due to their different diffusion behaviors in the atmospheric boundary layer.     

Determination of Microgram Quantities of Inorganic Sulfate in Atmospheric Particulates

Abstract

Before a community-wide woodstove changeout program, a chemical mass balance (CMB) source apportionment study was conducted in Libby, MT, during the winter of 2003–2004 to identify the sources of fine particulate matter (PM_2.5) within the valley. Results from this study showed that residential woodstoves were the major source, contributing approximately 80% of the ambient PM_2.5 throughout the winter months. In an effort to lower the ambient PM_2.5, a large woodstove changeout program was conducted in Libby from 2005 to 2007 in which nearly 1200 old woodstoves were changed out with cleaner burning models. During the winter of 2007–2008, a follow-up CMB source apportionment study was conducted to evaluate the effectiveness of the changeout. Results from this study showed that average winter PM_2.5 mass was reduced by 20%, and woodsmoke-related PM_2.5 (as identified by the CMB model) was reduced by 28% when compared with the pre-changeout winter of 2003– 2004. These results suggest that a woodstove changeout can be an effective tool in reducing ambient levels of PM_2.5 in woodstove-impacted communities.     

Comparison and Evaluation of Chemically Speciated Mobile Source PM2.5 Particulate Matter Profiles

ABSTRACT

Mobile sources are significant contributors to ambient PM_{2 5}, accounting for 50% or more of the total observed levels in some locations. One of the important methods for resolving the mobile source contribution is through chemical mass balance (CMB) receptor modeling. CMB requires chemically speciated source profiles with known uncertainty to ensure accurate source contribution estimates. Mobile source PM profiles are available from various sources and are generally in the form of weight fraction by chemical species. The weight fraction format is commonly used, since it is required for input into the CMB receptor model. This paper examines the similarities and differences in mobile source PM_2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources.

Notable characteristics of the mass fraction data include variability (relative contributions of elements and ions) among supposedly similar sources and a wide range of average EC:OC ratios (0.60 ± 0.53 to 1.42 ± 2.99) for light-duty gasoline vehicles (LDGVs), indicating significant EC emissions from LDGVs in some cases. For diesel vehicles, average EC:OC ratios range from 1.09 ± 2.66 to 3.54 ± 3.07. That different populations of the same class of emitters can show considerable variability suggests caution should be exercised when selecting and using profiles in source apportionment studies.     

Analysis of PM2.5and PM10 in the Atmosphere of Mexico City during 2000-2002

Abstract

During the last 10 years, high atmospheric concentrations of airborne particles recorded in the Mexico City metropolitan area have caused concern because of their potential harmful effects on human health. Four monitoring campaigns have been carried out in the Mexico City metropolitan area during 2000-2002 at three sites: (1) Xalos-toc, located in an industrial region; (2) La Merced, located in a commercial area; and (3) Pedregal, located in a residential area. Results of gravimetric and chemical analyses of 330 samples of particulate matter (PM) with an aerodynamic diameter less than 2.5 μm (PM_2.5) and PM with an aerodynamic diameter less than 10 μm (PM₁₀) indicate that (1) PM_2.5/PM₁₀ average ratios were 0.42, 0.46, and 0.52 for Xalostoc, La Merced, and Pedregal, respectively; (2) the highest PM_2.5 and PM₁₀ concentrations were found at the industrial site; (3) PM_2.5 and PM₁₀ concentrations were lower at nighttime; (4) PM_2.5 and PM₁₀ spatial averages concentrations were 35 and 76 μg/m³, respectively; and (5) when the PM_2.5 standard was exceeded, nitrate, sulfate, ammonium, organic carbon, and elemental carbon concentrations were high. Twenty-four hour averaged PM_2.5 concentrations in Mexico City and Sao Paulo were similar to those recorded in the 1980s in Los Angeles. PM₁₀ concentrations were comparable in Sao Paulo and Mexico City but 3-fold lower than those found in Santiago.     

Source Apportionment of Ambient Total Suspended Particulates and Coarse Particulate Matter in Urban Areas of Jiaozuo,China

Abstract

Approximately 750 total suspended particulates (TSPs) and coarse particulate matter (PM₁₀) filter samples from six urban sites and a background site and >210 source samples were collected in Jiaozuo City during January 2002 to April 2003. They were analyzed for mass and abundances of 25 chemical components. Seven contributive sources were identified, and their contributions to ambient TSP/PM₁₀ levels at the seven sites in three seasons (spring, summer, and winter days) and a “whole” year were estimated by a chemical mass balance (CMB) receptor model. The spatial TSP average was high in spring and winter days at a level of approximately 530 ～g/m³ and low in summer days at 456 ～g/m³; however, the spatial PM₁₀ average exhibited little variation at a level of approximately 325 ～g/m³, and PM_10-to-TSP ratios ranged from 0.58 to 0.81, which suggested heavy particulate matter pollution existing in the urban areas. Apportionment results indicated that geological material was the largest contributor to ambient TSP/PM₁₀ concentrations, followed by dust emissions from construction activities, coal combustion, secondary aerosols, vehicle movement, and other industrial sources. In addition, paved road dust and re-entrained dust were also apportioned to the seven source types and found soil, coal combustion, and construction dust to be the major contributors.     

Human Exposure to Sulfates from Coal-Fired Power Plants

Abstract

Increased interest in the health effects of ambient par–ticulate mass (PM) has focused attention on the evaluation of existing mass measurement methodologies and the definition of PM in ambient air. The Rupprecht and Patashnick Tapered Element Oscillating MicroBalance (TEOM^®) method for PM is compared with time–integrated gravimetric (manual) PM methods in large urban areas during different seasons. Comparisons are conducted for both PM₁₀ and PM_2.5 concentrations.

In urban areas, a substantial fraction of ambient PM can be semi–volatile material. A larger fraction of this component of PM₁₀ may be lost from the TEOM–heated filter than the Federal Reference Method (FRM). The observed relationship between TEOM and FRM methods varied widely among sites and seasons. In East Coast urban areas during the summer, the methods were highly correlated with good agreement. In the winter, correlation was somewhat lower, with TEOM PM concentrations generally lower than the FRM. Rubidoux, CA, and two Mexican sites (Tlalnepantla and Merced) had the highest levels of PM₁₀ and the largest difference between TEOM and manual methods.

PM_2.5 data from collocation of 24–hour manual samples with the TEOM are also presented. As most of the semi–volatile PM is in the fine fraction, differences between these methods are larger for PM_2.5 than for PM₁₀.     

PM10, PM2.5 and PM1.0—Emissions from industrial plants—Results from measurement programmes in Germany

Emission measurement programmes were carried out at industrial plants in several regions of Germany to determine the fine dust in the waste gases; the PM₁₀, PM_2.5 and PM_1.0 fractions were sampled using a cascade impactor technique. The installations tested included plants used for: combustion (brown coal, heavy fuel oil, wood), cement production, glass production, asphalt mixing, and processing plants for natural stones and sand, ceramics, metallurgy, chemical production, spray painting, wood processing/chip drying, poultry farming and waste treatment. In addition waste gas samples were taken from small-scale combustion units, like domestic stoves, firing lignite briquettes or wood.In total 303 individual measurement results were obtained during 106 different measurement campaigns. In the study it was found that in more than 70% of the individual emission measurement results from industrial plants and domestic stoves the PM₁₀ portion amounted to more than 90% and the PM_2.5 portion between 50% and 90% of the total PM (particulate matter) emission. For thermal industrial processes the PM_1.0 portion constituted between 20% and 60% of the total PM emission.Typical particle size distributions for different processes were presented as cumulative frequency distributions and as frequency distributions. The particle size distributions determined for the different plant types show interesting similarities and differences depending on whether the processes are thermal, mechanical, chemical or mixed. Consequently, for the groups of plant investigated, a major finding of this study has been that the particle size distribution is a characteristic of the industrial process. Attempts to correlate particle size distributions of different plants to different gas cleaning technologies did not lead to usable results.     

Source apportionment of PM10 in six cities of northern China

Ambient PM₁₀ was sampled in six northern China cities (Urumqi, Yinchuan, Taiyuan, Anyang, Tianjin and Jinan) from December 1999 to July 2002, and analyzed for 16 chemical elements, two water-soluble ions, total carbon, and organic carbon. In addition, chemical source profiles consisting of the same particulate components were obtained from a number of naturally occurring geological sources (soil dust from exposed lands) and sources of atmospheric particulates resulting from human activities (resuspended dust, cement, coal combustion fly ash, vehicle exhaust, and secondary particles). Ambient and source data were used in a chemical mass balance (CMB) receptor model to determine the major source of PM₁₀ in these six cities. Results of CMB modeling showed that the major source of ambient PM₁₀ in all the cities was resuspended dust. Significant contributions from coal fly ash were also found in all six cities.