Determination of PM10 emission rates from street sweepers

The use of street sweepers to clean paved roads, particularly after high-wind events, has been proposed as a PM10 control method. Using an artificial tunnel, the emission rates for several street sweepers were quantified under actual operating conditions. The tunnel was a tent enclosure, 6.1 x 4.3 x 73 m, open on both ends. PM10 concentrations were measured at the inlet and outlet while a sweeper removed sand deposited along the length. Measurements were made using a specialized low-volume filter sampler and an integrating nephelometer. The volume of air passing through the tunnel was measured by releasing an inert tracer, sulfur hexafluoride, at the inlet and measuring its concentration at the outlet. A large difference in emission rates between vacuum-type sweepers was observed, with rates varying from 5 to 100 mg m-1 swept. For the cleanest sweepers, the background rates (collected by sweeping clean pavement) were about half of the total PM10 emission rate. These background emission rates likely were from diesel exhaust; background rates for the single gasoline-powered sweeper were below detection. Particle light scattering data confirmed the filter collection results. The artificial tunnel approach would be useful in measuring total emissions from other mobile and stationary sources.     

Identification of the sources of PM10 in a subway tunnel using positive matrix factorization

The level of particulate matter of less than 10 μm diameter (PM₁₀) at subway platforms can be significantly reduced by installing a platform screen-door system. However, both workers and passengers might be exposed to higher PM₁₀ levels while the cars are within the tunnel because it is a more confined environment. This study determined the PM₁₀ levels in a subway tunnel, and identified the sources of PM₁₀ using elemental analysis and receptor modeling. Forty-four PM₁₀ samples were collected in the tunnel between the Gireum and Mia stations on Line 4 in metropolitan Seoul and analyzed using inductively coupled plasma–atomic emission spectrometry and ion chromatography. The major PM₁₀ sources were identified using positive matrix factorization (PMF). The average PM₁₀ concentration in the tunnels was 200.8 ± 22.0 μg/m³. Elemental analysis indicated that the PM₁₀ consisted of 40.4% inorganic species, 9.1% anions, 4.9% cations, and 45.6% other materials. Iron was the most abundant element, with an average concentration of 72.5 ± 10.4 μg/m³. The PM₁₀ sources characterized by PMF included rail, wheel, and brake wear (59.6%), soil combustion (17.0%), secondary aerosols (10.0%), electric cable wear (8.1%), and soil and road dust (5.4%). Internal sources comprising rail, wheel, brake, and electric cable wear made the greatest contribution to the PM₁₀ (67.7%) in tunnel air.

ImplicationsWith installation of a platform screen door, PM₁₀ levels in subway tunnels were higher than those on platforms. Tunnel PM₁₀ levels exceeded 150 μg/m³ of the Korean standard for subway platform. Elemental analysis of PM₁₀ in a tunnel showed that Fe was the most abundant element. Five PM₁₀ sources in tunnel were identified by positive matrix factorization. Railroad-related sources contributed 68% of PM₁₀ in the subway tunnel.     

Aerosol Measurement: The Use of Optical Light Scattering for the Determination of Particulate Size Distribution,and Particulate Mass,Including the Semi-Volatile Fraction

Abstract

The GRIMM model 1.107 monitor is designed to measure particle size distribution and particulate mass based on a light scattering measurement of individual particles in the sampled air. The design and operation of the instrument are described. Protocols used to convert the measured size number distribution to a mass concentration consistent with U.S. Environmental Protection Agency protocols for measuring particulate matter (PM) less than 10 μm (PM₁₀) and less than 2.5 μm (PM_2.5) in aerodynamic diameter are described. The performance of the resulting continuous monitor has been evaluated by comparing GRIMM monitor PM_2.5 measurements with results obtained by the Rupprecht and Patashnick Co. (R&P) filter dynamic measurement system (FDMS). Data were obtained during month-long studies in Rubidoux, CA, in July 2003 and in Fresno, CA, in December 2003. The results indicate that the GRIMM monitor does respond to total PM_2.5 mass, including the semi-volatile components, giving results comparable to the FDMS. The data also indicate that the monitor can be used to estimate water content of the fine particles. However, if the inlet to the monitor is heated, then the instrument measures only the nonvolatile material, more comparable to results obtained with a conventional heated filter tapered element oscillating microbalance (TEOM) monitor. A recent modification of the model 180, with a Nafion dryer at the inlet, measures total PM_2.5 including the nonvolatile and semi-volatile components, but excluding fine particulate water. Model 180 was in agreement with FDMS data obtained in Lindon, UT, during January through February 2007     

Systematic Biases in Measured PM10 Values with U.S. Environmental Protection Agency-Approved Samplers at Owens Lake,California

ABSTRACT

From 1993 through 1998, Wedding or Graseby high-volume PM₁₀ samplers were collocated with tapered element oscillating microbalance (TEOM) samplers at three sites at Owens Lake, CA. The study area is heavily impacted by windblown dust from the dry Owens Lake bed, which was exposed as a result of water diversions to the city of Los Angeles. A dichotomous (dichot) sampler and three collocated Partisol samplers were added in 1995 and 1999, respectively. U.S. Environmental Protection Agency (EPA) operating procedures were followed for all samplers, except for a Wedding sampler that was not cleaned for the purpose of this study. On average, the TEOM and Partisol samplers agreed to within 6%, and the dichot, Graseby, and Wedding samplers measured lower PM₁₀ concentrations by about 10, 25, and 35%, respectively. Surprisingly, the “clean” Wedding sampler consistently measured the same concentration as the “dirty” Wedding sampler through 85 runs without cleaning. The finding that the Graseby and Wedding high-volume PM₁₀ samplers read consistently lower than the TEOM, Partisol, and dichot samplers at Owens Lake is consistent with PM₁₀ sampler comparisons done in other fugitive dust areas, and with wind tunnel tests showing that sampler cut points can be significantly lower than 10 um under certain conditions. However, these results are opposite of the bias found for TEOM samplers in areas that have significant amounts of volatile particles, where the TEOM reads low due to the vaporization of particles on the TEOM's heated filter. Coarse particles like fugitive dust are relatively unaffected by the filter temperature. This study shows that in the absence of volatile particles and in the presence of fugitive dust, a different systematic bias of up to 35% exists between samplers using dichot inlets and high-volume samplers, which may cause the Graseby and Wedding PM₁₀ samplers to undermeasure PM₁₀ by up to 35% when the PM₁₀ is predominantly from coarse particulate sources.     

Estimation of Organic Compound Emissions from Waste Lagoons

Abstract

With the recent focus on fine particle matter (PM_2.5),new, self-consistent data are needed to characterize emissions from combustion sources. Such data are necessary for health assessment and air quality modeling. To address this need, emissions data for gas-fired combustors are presented here, using dilution sampling as the reference.The dilution method allows for collection of emitted particles under conditions simulating cooling and dilution during entry from the stack into the air. The sampling and analysis of the collected particles in the presence of precursor gases, SO₂, nitrogen oxide, volatile organic compound, and NH₃ is discussed; the results include data from eight gas fired units, including a dual-fuel institutional boiler and a diesel engine powered electricity generator. These data are compared with results in the literature for heavy-duty diesel vehicles and stationary sources using coal or wood as fuels. The results show that the gas-fired combustors have very low PM_2.5 mass emission rates in the range of ～10_-4 lb/million Btu (MMBTU) compared with the diesel backup generator with particle filter, with ～5 × 10_-3 lb/MMBTU. Even higher mass emission rates are found in coal-fired systems, with rates of ～0.07 lb/MMBTU for a bag-filter-controlled pilot unit burning eastern bituminous coal. The characterization of PM_2.5 chemical composition from the gas-fired units indicates that much of the measured primary particle mass in PM_2.5 samples is organic or elemental carbon and, to a much less extent, sulfate. Metal emissions are quite low compared with the diesel engines and the coal- or woodfueled combustors. The metals found in the gas-fired combustor particles are low in concentration, similar in concentration to ambient particles. The interpretation of the particulate carbon emissions is complicated by the fact that an approximately equal amount of particulate carbon (mainly organic carbon) is found on the particle collector and a backup filter. It is likely that measurement artifacts, mostly adsorption of volatile organic compounds on quartz filters, are positively biasing “true” particulate carbon emission results.     

Evaluating urban PM10 pollution benefit induced by street cleaning activities

Despite their burden in urban particulate air pollution, road traffic non-exhaust emissions are often uncontrolled and information about the effectiveness of mitigation measures on paved roads is still scarce. The present study is aimed to evaluate the effectiveness of mechanical sweeping/water flushing treatments in mitigating urban road dust resuspension and to quantify the real benefit in terms of ambient PM₁₀ concentrations. To this aim a specific campaign was carried out in a heavily trafficked central road of Barcelona (Spain), a Mediterranean city suffering from a traffic-related pollution, both for a high car density and a frequent lack of precipitation. Several street washings were performed by means of mechanical sweepers and pressure water during night in all traffic lanes and sidewalks. PM₁₀ levels were simultaneously compared with four reference urban background air quality stations to interpret any meteorological variability. At the downwind measurement site, PM₁₀ concentrations registered a mean daily decrease of 8.8 μg m^?3 during the 24 h after street washing treatments. However 3.7–4.9 μg m^?3 of such decrease were due to the meteorological variability detected at the upwind site, as well as at two of the reference sites. This reveals that an effective decrease of 4–5 μg m^?3 (7–10%) can be related to street washing efficiency. Mitigation of road dust resuspension was confirmed by investigating the chemical composition of airborne-PM₁₀ filters. Concentrations of Cu, Sb, Fe and mineral matter decrease significantly with respect to concentrations of elemental carbon, used as tracer for exhaust diesel emissions. High efficiency of street washing in reducing road dust loads was found by performing periodic samplings both on the treated and the untreated areas.     

A Federal Tax on Energy

Abstract

In this investigation, the collection efficiency of particulate emission control devices (PECDs), particulate matter (PM) emissions, and PM size distribution were determined experimentally at the inlet and outlet of PECDs at five coal-fired power plants. Different boilers, coals, and PECDs are used in these power plants. Measurement in situ was performed by an electrical low-pressure impactor with a sampling system, which consisted of an isokinetic sampler probe, precut cyclone, and two-stage dilution system with a sample line to the instruments. The size distribution was measured over a range from 0.03 to 10 µm. Before and after all of the PECDs, the particle number size distributions display a bimodal distribution. The PM_2.5 fraction emitted to atmosphere includes a significant amount of the mass from the coarse particle mode. The controlled and uncontrolled emission factors of total PM, inhalable PM (PM₁₀), and fine PM P(M_2.5) were obtained. Electrostatic precipitator (ESP) and baghouse total collection efficiencies are 96.38–99.89% and 99.94%, respectively. The minimum collection efficiency of the ESP and the baghouse both appear in the particle size range of 0.1–1 µm. In this size range, ESP and baghouse collection efficiencies are 85.79–98.6% and 99.54%. Real-time measurement shows that the mass and number concentration of PM₁₀ will be greatly affected by the operating conditions of the PECDs. The number of emitted particles increases with increasing boiler load level because of higher combustion temperature. During test run periods, the data reproducibility is satisfactory.     

Estimating fugitive dust emission rates using an environmental boundary layer wind tunnel

Emissions from fugitive dust due to erosion of “natural” wind-blown surfaces are an increasingly important part of PM₁₀ (particulate matter with sizes of 10 μm aerodynamic diameter) emission inventories. These inventories are particularly important to State Implementation Plans (SIP), the plan required for each state to file with the Federal government indicating how they will comply with the Federal Clean Air Act (FCAA). However, techniques for determining the fugitive dust contribution to over all PM₁₀ emissions are still in their developmental stages. In the past, the methods have included field monitoring stations, specialized field studies and field wind-tunnel studies. The measurements made in this paper allow for systematic determination of PM₁₀ emission rates through the use of an environmental boundary layer wind tunnel in the laboratory. Near surface steady-state concentration profiles and velocity profiles are obtained in order to use a control volume approach to estimate emission rates. This methodology is applied to soils retrieved from the nation's single largest PM₁₀ source, Owens (dry) Lake in California, to estimate emission rates during active storm periods. The estimated emission rates are comparable to those obtained from field studies and lend to the validity of this method for determining fugitive dust emission rates.     

Non-exhaust emission measurement system of the mobile laboratory SNIFFER

In this paper we describe and quality assure the sampling system of a mobile research laboratory SNIFFER which was shown to be a useful tool for studying emission levels of respirable dust from street surfaces. The dust plume had bimodal structure; another mode rising to higher altitudes whereas the other mode remained at lower altitudes. The system was tested on a route in Helsinki, Finland, during spring 2005 and 2006. The PM_2.5 and PM₁₀ were positively correlated and the PM levels increased with the vehicle speed. SNIFFER was able to identify the characteristic emission levels on different streets. A clear downward trend in the concentrations was observed in all street locations between April and June. The composition of the street dust collected by SNIFFER was compared with springtime PM₁₀ aerosol samples from the air quality monitoring stations in Helsinki. The results showed similarities in the abundance and composition of the mineral fraction but contained significantly more salt particles.     

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.     

The Relationship between Cross-Sectional and Time Series Studies

Abstract

There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM₁₀ and PM_2.5) emissions from artillery backblast testing on improved gun positions, was characterized at the Yuma Proving Ground near Yuma, AZ, in October 2005. Fugitive emissions are created by the shockwave from artillery pieces, which ejects dust from the surface on which the artillery is resting. Other contributions of PM can be attributed to the combustion of the propellants. For a 155–mm howitzer firing a range of propellant charges or zones, amounts of emitted PM₁₀ ranged from ～19 g of PM₁₀ per firing event for a zone 1 charge to 92 g of PM₁₀ per firing event for a zone 5. The corresponding rates for PM_2.5 were ～9 g of PM_2.5 and 49 g of PM_2.5 per firing. The average measured emission rates for PM₁₀ and PM_2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM₁₀ (52.2 t) and PM_2.5 (28.5 t) from artillery backblast are insignificant in the context of the 2002 U.S. Environment Protection Agency (EPA) PM emission inventory. Using national–level activity data for artillery fire, the most conservative estimate is that backblast would contribute the equivalent of 5 x 10^–4% and 1.6 x 10^–3% of the annual total PM₁₀ and PM_2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data.     

High Intensity lonization Applied to Venturi Scrubbing

The relationship between a standard for the class of particulate matter smaller than 10 μm (PM₁₀) and thoracic particle sampling has been explored over a wide range of ambient aerosol distributions characteristic of both the European and U.S. situations. As a general trend, the PM₁₀ sampling performance does meet the proposed U.S. EPA compliance criterion of ±10 percent. The major parameters determining compliance are the 50 percent cutpoint of the PM₁₀ inlet and the mass median diameter of the coarse particle mode.

Also an assessment has been made of a possible relationship between high volume sampling based air quality data and those based upon thoracic particle sampling. For average European situations the following indicative relation does hold: HVS ≈ 1.3 × TP ± 30 percent, and HVS ≈ 1.25 × PM₁₀. For the more arid U.S. situations: HVS ≈ 1.7 × TP and HVS ≈ 1.65 × PM₁₀, in realistic agreement with the experimentally observed U.S. findings of HVS ≈ 2.0 × PM₁₀. Under extreme situations with high winds both the compliance PM₁₀-TP and the relation HVS-TP drastically deteriorate.     

Application of a Combined Measurement and Modeling Method to Quantify Windblown Dust Emissions from the Exposed Playa at Mono Lake,California

ABSTRACT

Particulate matter ≤10 μm (PM₁₀) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM₁₀ monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km² area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM₁₀ concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM₁₀ concentrations to back-calculate the ratio of vertical PM₁₀ flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K _f) were found to change seasonally, ranging from 1.3 × 10^?5 to 5.1 × 10^?5 for sand flux measured at 15 cm above the surface (q ₁₅). Hourly PM₁₀ emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F?=?K _f ×?q ₁₅). The maximum hourly PM10 emission rate from the study area was 76 g/m²·hr (10-m wind speed?=?23.5 m/sec). Maximum daily PM₁₀ emissions were estimated at 450 g/m²·day, and annual emissions at 1095 g/m²·yr. Hourly PM₁₀ emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM₁₀ ranging from 16 to over 60,000 μg/m³ (slope?=?0.89, R ²?=?0.77).

IMPLICATIONS Under a U.S. Environmental Protection Agency (EPA)-approved plan, the method described in this paper has been used since 2000 at Owens Lake, CA, to identify and successfully mitigate dust from over 100 km² of the dry lakebed. It continues to be used to monitor dust control compliance at Owens Lake. Scaled-down versions of the Owens Lake network can be implemented in other areas in a manner similar to the Mono Lake study. Once K-factors are established, low-cost CSC samplers (about $35 U.S.) may be used for periodic monitoring (e.g., daily, weekly, or monthly) to estimate PM₁₀ emissions or to evaluate dust control compliance.     

An Analysis of Visual Range in the Eastern United States Under Different Meteorological Regimes

ABSTRACT

The issue of fine particle (PM₂₅) exposures and their potential health effects is a focus of scientific research because of the recently promulgated National Ambient Air Quality Standard for PM_{2 5}. Before final implementation, the health and exposure basis for the standard will be reviewed by the U.S. Environmental Protection Agency within the next five years. As part of this process, it is necessary to understand total particle exposure issues and to determine the relative importance of the origin of PM_{2 5} exposure in various micro-environments. The results presented in this study examine emissions of fine particles from a previously uncharacterized indoor source: the residential vacuum cleaner. Eleven standard vacuum cleaners were tested for the emission rate of fine particles by their individual motors and for their efficiency in collecting laboratory-generated fine particles. An aerosol generator was used to introduce fine potassium chloride (KC1) particles into the vacuum cleaner inlet for the collection efficiency tests. Measurements of the motor emissions, which include carbon, and the KCl aerosol were made using a continuous HIAC/Royco 5130A light-scattering particle detector. All tests were conducted in a metal chamber specifically designed to completely contain the vacuum cleaner and operate it in a stationary position. For the tested vacuum cleaners, fine particle motor emissions ranged from 9.6 x 10⁴ to 3.34 x 10⁸ particles/min, which were estimated to be 0.028 to 176 mg/min for mass emissions, respectively. The vast majority of particles released were in the range of 0.3-0.5 mm in diameter. The lowest particle emission rate was obtained for a vacuum cleaner that had a high efficiency (HEPA) filter placed after the vacuum cleaner bag and the motor within a sealed exhaust system. This vacuum cleaner removed the KC1particles that escaped the vacuum cleaner bag and the particles emitted by the motor. Results obtained for the KC1 collection efficiency tests show >99% of the fine particles were captured by the two vacuum cleaners that used a HEPA filter. A series of tests conducted on two vacuum cleaners found that the motors also emitted ultra-fine particles above 0.01 mm in diameter at rates of greater than 10⁸ ultra-fine particles/CF of air. The model that had the best collection efficiency for fine particles also reduced the ultra-fine particle emissions by a factor of 1 x 10³.     

Installation of platform screen doors and their impact on indoor air quality: Seoul subway trains

In this study, variations of particulate matter (PM) concentrations in subway trains following installation of platform screen doors (PSDs) in the Seoul subway system were investigated. PM samples were collected in the trains on subway lines 1–8 before and after installation of PSDs. It was found that the mean PM₁₀ concentration in the trains after PSDs installation increased significantly by 29.9% compared to that before installation. In particular, the increase of PM₁₀ in line 6 was the highest at 103%. When the relationship between PM₁₀ and PM_2.5 was compared, coefficients of determination (r²) before and after PSDs installations were 0.696 and 0.169, respectively. This suggests that air mixing between the platform and the tunnel after PSDs installation was extremely restricted. In addition, the indoor/outdoor PM₁₀ ratio following PSDs installation increased from 1.32 to 2.97 relative to the period with no installed PSDs. Furthermore, this study revealed that PM levels in subway trains increased significantly after all underground PSDs were put in use. Several potential factors were examined that could result in this PM increase, such as train ventilation systems, operational conditions, passenger volume, subway depth, and the length of underground segments.

ImplicationsPM₁₀ concentrations inside the subway trains increased after PSDs installation. This indicates that air quality in trains was very seriously impacted by PSDs. PM₁₀ levels were also influenced by the tunnel depth and length of the underground segments. To prevent the adverse effect on human health by PM₁₀ emitted from the tunnel, an applicable ventilation system to reduce PM₁₀ is required inside trains and tunnels.     

Particulate matter emissions from on-road vehicles in a freeway tunnel study

Particulate matter, including coarse particles (PM_2.5–10, aerodynamic diameter of particle between 2.5 and 10 μm) and fine particles (PM_2.5, aerodynamic diameter of particle lower than 2.5 μm) and their compositions, including elemental carbon, organic carbon, and 11 water-soluble ionic species, and elements, were measured in a tunnel study. A comparison of the six-hour average of light-duty vehicle (LDV) flow of the two sampling periods showed that the peak hours over the weekend were higher than those on weekdays. However, the flow of heavy-duty vehicles (HDVs) on the weekdays was significant higher than that during the weekend in this study. EC and OC content were 49% for PM_2.5–10 and 47% for PM_2.5 in the tunnel center. EC content was higher than OC content in PM_2.5–10, but EC was about 2.3 times OC for PM_2.5. Sulfate, nitrate, ammonium were the main species for PM_2.5–10 and PM_2.5. The element contents of Na, Al, Ca, Fe and K were over 0.8 μg m^?3 in PM_2.5–10 and PM_2.5. In addition, the concentrations of S, Ba, Pb, and Zn were higher than 0.1 μg m^?3 for PM_2.5–10 and PM_2.5. The emission factors of PM_2.5–10 and PM_2.5 were 18 ± 6.5 and 39 ± 11 mg km^?1-vehicle, respectively. The emission factors of EC/OC were 3.6/2.7 mg km^?1-vehicle for PM_2.5–10 and 15/4.7 mg km^?1-vehicle for PM_2.5 Furthermore, the emission factors of water-soluble ions were 0.028(Mg²⁺)–0.81(SO₄^2?) and 0.027(NO₂^?)–0.97(SO₄^2?) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively. Elemental emission factors were 0.003(V)–1.6(Fe) and 0.001(Cd)–1.05(Na) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively.     

PM10 concentration levels at an urban and background site in Cyprus: The impact of urban sources and dust storms

Air quality in Cyprus is influenced by both local and transported pollution, including desert dust storms. We examined PM₁₀ concentration data collected in Nicosia (urban representative) from April 1, 1993, through December 11, 2008, and in Ayia Marina (rural background representative) from January 1, 1999, through December 31, 2008. Measurements were conducted using a Tapered Element Oscillating Micro-balance (TEOM). PM₁₀ concentrations, meteorological records, and satellite data were used to identify dust storm days. We investigated long-term trends using a Generalized Additive Model (GAM) after controlling for day of week, month, temperature, wind speed, and relative humidity. In Nicosia, annual PM₁₀ concentrations ranged from 50.4 to 63.8 μg/m³ and exceeded the EU annual standard limit enacted in 2005 of 40 μg/m³ every year. A large, statistically significant impact of urban sources (defined as the difference between urban and background levels) was seen in Nicosia over the period 2000–2008, and was highest during traffic hours, weekdays, cold months, and low wind conditions. Our estimate of the mean (standard error) contribution of urban sources to the daily ambient PM₁₀ was 24.0 (0.4) μg/m³. The study of yearly trends showed that PM₁₀ levels in Nicosia decreased from 59.4 μg/m³ in 1993 to 49.0 μg/m³ in 2008, probably in part as a result of traffic emission control policies in Cyprus. In Ayia Marina, annual concentrations ranged from 27.3 to 35.6 μg/m³, and no obvious time trends were observed. The levels measured at the Cyprus background site are comparable to background concentrations reported in other Eastern Mediterranean countries. Average daily PM₁₀ concentrations during desert dust storms were around 100 μg/m³ since 2000 and much higher in earlier years. Despite the large impact of dust storms and their increasing frequency over time, dust storms were responsible for a small fraction of the exceedances of the daily PM₁₀ limit.

ImplicationsThis paper examines PM₁₀ concentrations in Nicosia, Cyprus, from 1993 to 2008. The decrease in PM₁₀ levels in Nicosia suggests that the implementation of traffic emission control policies in Cyprus has been effective. However, particle levels still exceeded the European Union annual standard, and dust storms were responsible for a small fraction of the daily PM₁₀ limit exceedances. Other natural particles that are not assessed in this study, such as resuspended soil and sea salt, may be responsible in part for the high particle levels.     

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.     

Whole House Particle Removal and Clean Air Delivery Rates for In-Duct and Portable Ventilation Systems

Abstract

A novel method for determining whole house particle removal and clean air delivery rates attributable to central and portable ventilation/air cleaning systems is described. The method is used to characterize total and air-cleaner-specific particle removal rates during operation of four in-duct air cleaners and two portable air-cleaning devices in a fully instrumented test home. Operation of in-duct and portable air cleaners typically increased particle removal rates over the baseline rates determined in the absence of operating a central fan or an indoor air cleaner. Removal rates of 0.3- to 0.5-μm particles ranged from 1.5 hr^?1 during operation of an in-duct, 5-in. pleated media filter to 7.2 hr^?1 for an in-duct electrostatic air cleaner in comparison to a baseline rate of 0 hr^?1 when the air handler was operating without a filter. Removal rates for total particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5) mass concentrations were 0.5 hr^?1 under baseline conditions, 0.5 hr^?1 during operation of three portable ionic air cleaners, 1 hr^?1 for an in-duct 1-in. media filter, 2.4 hr^?1 for a single high-efficiency particle arrestance (HEPA) portable air cleaner, 4.6 hr^?1 for an in-duct 5-in. media filter, 4.7 hr^?1 during operation of five portable HEPA filters, 6.1 hr^?1 for a conventional in-duct electronic air cleaner, and 7.5 hr^?1 for a high efficiency in-duct electrostatic air cleaner. Corresponding whole house clean air delivery rates for PM_2.5 attributable to the air cleaner independent of losses within the central ventilation system ranged from 2 m³/min for the conventional media filter to 32 m³/min for the high efficiency in-duct electrostatic device. Except for the portable ionic air cleaner, the devices considered here increased particle removal indoors over baseline deposition rates.     

Evaluation of PM10 forecasting based on the artificial neural network model and intake fraction in an urban area: A case study in Taiyuan City,China

Primary fine particulate matters with a diameter of less than 10 µm (PM₁₀) are important air emissions causing human health damage. PM₁₀ concentration forecast is important and necessary to perform in order to assess the impact of air on the health of living beings. To better understand the PM₁₀ pollution health risk in Taiyuan City, China, this paper forecasted the temporal and spatial distribution of PM₁₀ yearly average concentration, using Back Propagation Artificial Neural Network (BPANN) model with various air quality parameters. The predicted results of the models were consistent with the observations with a correlation coefficient of 0.72. The PM₁₀ yearly average concentrations combined with the population data from 2002 to 2008 were given into the Intake Fraction (IF) model to calculate the IFs, which are defined as the integrated incremental intake of a pollutant released from a source category or a region over all exposed individuals. The results in this study are only for main stationary sources of the research area, and the traffic sources have not been included. The computed IFs results are therefore under-estimations. The IFs of PM₁₀ from Taiyuan with a mean of 8.5 per million were relatively high compared with other IFs of the United States, Northern Europe and other cities in China. The results of this study indicate that the artificial neural network is an effective method for PM₁₀ pollution modeling, and the Intake Fraction model provides a rapid population risk estimate for pollutant emission reduction strategies and policies.

Implications The PM₁₀ (particulate matter with an aerodynamic diameter ≤10 μm) yearly average concentration of Taiyuan, with a mean of 0.176 mg/m³, was higher than the 65 μg/m³ recommended by the U.S. Environmental Protection Agency (EPA). The spatial distribution of PM₁₀ yearly average concentrations showed that wind direction and wind speed played an important role, whereas temperature and humidity had a lower effect than expected. Intake fraction estimates of Taiyuan were relatively high compared with those observed in other cities. Population density was the major factor influencing PM₁₀ spatial distribution. The results indicated that the artificial neural network was an effective method for PM₁₀ pollution modeling.