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

Abstract

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

Objectives and Design of Central California's 1995 Integrated Monitoring Study of the California Regional PM10/PM2.5 Air Quality Study

ABSTRACT

The 1995 Integrated Monitoring Study (IMS95) is part of the Phase 1 planning efforts for the California Regional PM_10/PM_2.5 Air Quality Study. Thus, the overall objectives of IMS95 are to (1) fill information gaps needed for planning an effective field program later this decade; (2) develop an improved conceptual model for pollution buildup (PM10, PM2.5, and aerosol precursors) in the San Joaquin Valley; (3) develop a uniform air quality, meteorological, and emissions database that can be used to perform initial evaluations of aerosol and fog air quality models; and (4) provide early products that can be used to help with the development of State Implementation Plans for PM_10. Consideration of the new particulate matter standards were also included in the planning and design of IMS95, although they were proposed standards when IMS95 was in the planning process.     

Using continuous PM2.5 monitoring data to report an air quality index

As stated in 40 CFR 58, Appendix G (2000), statistical linear regression models can be applied to relate PM2.5 continuous monitoring (CM) measurements with federal reference method (FRM) measurements, collocated or otherwise, for the purpose of reporting the air quality index (AQI). The CM measurements can then be transformed via the model to remove any bias relative to FRM measurements. The resulting FRM-like modeled measurements may be used to provide more timely reporting of a metropolitan statistical area's (MSA's) AQI. Of considerable importance is the quality of the model used to relate the CM and FRM measurements. The use of a poor model could result in misleading AQI reporting in the form of incorrectly claiming either good or bad air quality. This paper describes a measure of adequacy for deciding whether a statistical linear regression model that relates FRM and continuous PM2.5 measurements is sufficient for use in AQI reporting. The approach is the U.S. Environmental Protection Agency's (EPA's) data quality objectives (DQO) process, a seven-step strategic planning approach to determine the most appropriate data type, quality, quantity, and synthesis for a given activity. The chosen measure of model adequacy is r2, the square of the correlation coefficient between FRM measurements and their modeled counterparts. The paper concludes by developing regression models that meet this desired level of adequacy for the MSAs of Greensboro/Winston-Salem/High Point, NC; and Davenport/Moline/Rock Island, IA/IL. In both cases, a log transformation of the data appeared most appropriate. For the data from the Greensboro/Winston-Salem/High Point MSA, a simple linear regression model of the FRM and CM measurements had an r2 of 0.96, based on 227 paired observations. For the data from the Davenport/Moline/Rock Island MSA, due to seasonal differences between CM and FRM measurements, the simple linear regression model had to be expanded to include a temperature dependency, resulting in an r2 of 0.86, based on 214 paired observations.     

Using CALINE dispersion to assess vehicular PM2.5 emissions

This paper explores the range of CALINE4's PM_2.5 modeling capabilities by comparing previously collected PM_2.5 data with CALINE4 predicted values. Two sampling sites, a suburban site located at an intersection in Sacramento, CA, and an urban site located in London, were used. Predicted concentrations are graphed against observed concentrations and evaluated against the criterion that 75% of the points fall within the factor-of-two prediction envelope. For the suburban site, data estimated by CALINE4 produced results that fell within the acceptable factor-of-two percentage envelope. A reverse dispersion test was also conducted for the suburban site using observed and calculated emission factors, and although it showed correlations between the observed values and CALINE4 predicted values, it could not conclusively prove that the model is accurate at predicting PM_2.5 concentrations. Although the results suggest that CALINE4 PM_2.5 predictions may be reasonably close to observed values, the number of observations used to verify the model was small and consequently, findings from the suburban site should be considered exploratory. For the urban site, a much larger data set was evaluated; however, the CALINE4 results for this site did not fall 75% within the factor-of-two envelope. Several factors, including street canyon effects, likely contributed to an inaccuracy of the emission factors used in CALINE4, and therefore, to the overall CALINE4 predictions. In summary, CALINE4 does not appear to perform well in densely populated areas and differences in topography may be a decisive factor in determining when CALINE4 may be applicable to modeling PM_2.5. For critical transportation projects requiring PM_2.5 analysis, use of CALINE4 may not be optimal because of its inability to produce reasonable estimates for highly trafficked areas. Additional data sets for CALINE4 analysis, particularly in urban environments, are required to fully understand CALINE4's PM_2.5 modeling capabilities.     

家居环境PM2.5控制用空气滤料

针对目前家居环境净化PM2.5的要求,在现有空气过滤材料的基础上,探讨一种适合于家居环境移动式空气净化装置用低阻、高效和长寿命的过滤材料。采用实验研究的方法对常用玻纤滤纸以及驻极体空气过滤材料进行了过滤特性、电镜、孔径测试的对比实验研究。结果表明,当过滤风速为5 cm/s时,3种驻极体滤料对粒径≤4.5 μm的颗粒物的分级过滤效率要高于玻纤滤纸且都在90%以上,其过滤阻力在4.9~6.4 Pa之间,而高效滤纸的过滤阻力在57.8~78.6 Pa之间;在实验风速条件下,驻极体滤料对PM2.5的过滤效率和过滤阻力分别高于和低于高效玻纤滤纸;对驻极体滤料进行蒸馏水洗涤后,其对颗粒物的过滤效率下降,驻极体滤料静电效应具有不稳定特性;电镜测试发现,玻纤滤纸纤维层排布致密,纤维存在断裂现象,而驻极体滤料较为蓬松,无纤维断裂现象;孔径实验表明,驻极体滤料的平均孔径为玻纤滤纸的11.9~14.7倍,驻极体滤料具有良好的透气和容尘特性。     

Monitoring of PM10 and PM2.5 around primary particulate anthropogenic emission sources

Investigations on the monitoring of ambient air levels of atmospheric particulates were developed around a large source of primary anthropogenic particulate emissions: the industrial ceramic area in the province of Castelló (Eastern Spain). Although these primary particulate emissions have a coarse grain-size distribution, the atmospheric transport dominated by the breeze circulation accounts for a grain-size segregation, which results in ambient air particles occurring mainly in the 2.5–10 μm range. The chemical composition of the ceramic particulate emissions is very similar to the crustal end-member but the use of high Al, Ti and Fe as tracer elements as well as a peculiar grain-size distribution in the insoluble major phases allow us to identify the ceramic input in the bulk particulate matter. PM2.5 instead of PM10 monitoring may avoid the interference of crustal particles without a major reduction in the secondary anthropogenic load, with the exception of nitrate. However, a methodology based in PM2.5 measurement alone is not adequate for monitoring the impact of primary particulate emissions (such as ceramic emissions) on air quality, since the major ambient air particles derived from these emissions are mainly in the range of 2.5–10 μm. Consequently, in areas characterised by major secondary particulate emissions, PM2.5 monitoring should detect anthropogenic particulate pollutants without crustal particulate interference, whereas PM10 measurements should be used in areas with major primary anthropogenic particulate emissions.     

Monitoring study of the near-road PM2.5 concentrations in Maryland

The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site.

Implications: PM_2.5 monitoring at 150 m (approximately 500 feet) from a major highway in Maryland near Washington, DC, demonstrated that roadway traffic contributes to the total PM_2.5 concentration near the roadway, but the contribution at such distance is small, in the order of 12–17% of the total.     

A Quantitative Approach to the Traffic Air Quality Problem: The Traffic Air Quality Index

Abstract

The Traffic Air Quality (TAQ) model is a simple tool to estimate traffic fine particulate emissions on roadways (g/km) and can be used for both real-time analysis and for localized conformity analysis (“hot-spot” analysis for nonattainment areas) as defined by 40 CFR 93.123. This paper is a follow-up to a study published earlier regarding the development of the TAQ model. This paper shows how local air quality levels can be a factor in traffic management in nonattainment areas. Similar to the industrial source quotas measured in tons per year, it is proposed that road segments are to be assigned emission quotas (or TAQ indices) measured in pollutant mass emitted per road length (g/km) above which traffic-measures have to be taken to reduce the fine-particulates emissions on such road links. The TAQ model as well as traffic-rerouting measures along with the Intelligent Transportation System (ITS) protocols can be used to have a real-time control of the traffic conditions along expressways to maintain the fine-particulates emissions below the quota assigned per road link and consequently improving the over all local air quality in nonattainment areas.     

Design of a Cost-Effective Weighing Facility for PM2.5 Quality Assurance

Abstract

The U.S. Environmental Protection Agency (EPA) Quality Assurance (QA) Guidance Document 2.12: Monitoring PM_2.5 in Ambient Air Using Designated Reference or Class I Equivalent Methods¹ (Document 2.12) requires conditioning of PM_2.5 filters at 20-23 °C and 30-40% relative humidity (RH) for 24 hr prior to gravimetric analysis. Variability of temperature and humidity may not exceed ±2 °C and ±5% RH during the conditioning period. The quality assurance team at EPA Region 2’s regional laboratory designed a PM_2.5 weighing facility that operates well within these strict performance requirements.

The traditional approach to meeting the performance requirements of Document 2.12 for PM_2.5 filter analysis is to build a walk-in room, with costs typically exceeding $100,000. The initial one-time capital cost for the laboratory at EPA’s Edison, NJ, facility was approximately $24,000. Annual costs [e.g., National Institute of Standards and Technology (NIST) recertifications and nitrogen replacement cylinders used for humidity control] are approximately $500. The average 24-hr variabilities in temperature and RH in the Region 2 weighing chamber are small, ±0.2 °C and ±0.8% RH, respectively. The mass detection limit for the PM_2.5 weighing system of 47-mm stretched Teflon (lab blank) filters is 6.3 μg. This facility demonstrates an effective and economical example for states and other organizations planning PM_2.5 weighing facilities.     

Using geographically temporally weighted regression to assess the contribution of corruption governance to global PM2.5

Environmental Science and Pollution Research - In the face of the global haze crisis, exploring the driving force of political factors for controlling minute atmospheric particles has become...     

Windblown dust contributes to high PM2.5 concentrations

The revised National Ambient Air Quality Standards for PM include fine particulate standards based upon mass measurements of PM2.5. It is possible in arid and semi-arid regions to observe significant coarse mode intrusion in the PM2.5 measurement. In this work, continuous PM10, PM2.5, and PM1.0 were measured during several windblown dust events in Spokane, WA. PM2.5 constituted approximately 30% of the PM10 during the dust event days, compared with approximately 48% on the non-dusty days preceding the dust events. Both PM10 and PM2.5 were enhanced during the dust events. However, PM1.0 was not enhanced during dust storms that originated within the state of Washington. During a dust storm that originated in Asia and impacted Spokane, PM1.0 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 microns, was found to represent a significant fraction of PM2.5 (approximately 51%) during windblown dust events, compared with 28% during the non-dusty days before the dust events.     

A Microprocessor-Based Air Quality Monitoring System

Portable air quality monitoring systems may be required to supplement fixed installations or to provide for quick response to a transient situation, possibly at a remote location. A microprocessor-based monitoring unit has been developed for use with existing sensors. The unit is portable and its operational sequence can be programmed to adapt it to any unique requirements existing at the deployment site. Selectable on-site calculations are performed on raw data, and a hard copy or tape record of results can be produced.     

An Index and Model of Human Response to Air Quality

This study undertook an empirical Investigation of human response to air quality. Home interviews of 475 respondents living in 22 neighborhoods of Los Angeles County had elicited information on respondent socioeconomic characteristics, behavioral patterns, and measures of human response to air quality. This data base was then augmented with nine measures of actual air quality for six time frames for each neighborhood.

An observer-based air quality index (OBAQI) was constructed based upon which combination of air quality variables correlated best with the percentage of neighborhood respondents who perceived “smoggy air.” The best combination (OBAQI 3) consisted of prevailing visibility, O₃, and SO₂, each measured as the annual number of days that a selected standard had been equalled or exceeded. Subsequently, multiple regression models were constructed using this index as a predictor of aggregated perception of air quality. In addition to a general model for all neighborhoods, separate models were constructed for clusters of neighborhoods of similar micrometeorology as approximated by uniform elevations and/or coastal distances. Zones of homogeneous air quality and micrometeorology were then defined. Within these zones variation in four measures of human response to air quality was associated with respondent socioeconomic characteristics and behavioral patterns. Both the index and model could prove useful in gauging public response to proposed actions of air quality management districts.     

Inter-Laboratory Comparison of Air Particulate Monitoring Data

ABSTRACT

This paper compares three analytical methods that are often used to analyze composition of atmospheric aerosol: Ion Chromatography (IC), Proton Induced X-ray Emission (PIXE), and X-Ray Fluorescence (XRF). Three monitoring studies are discussed: (1) a comparison of air particulate data collected by several independent sampler/ analytical technique suites run by different laboratories; (2) a study involving two identical samplers and a single suite of analytical techniques; and (3) analysis of identical aerosol samples by two different techniques (XRF vs. PIXE). While the XRF versus PIXE project shows a very good agreement for most elements, the first interlaboratory study demonstrates the “real-life” noise introduced into the final data set by various sampling complications and different collection characteristics of the samplers used. The XRF versus PIXE study also revealed an unexplained deviation in measured sulphur concentrations for very lightly loaded samples. In the five-sampler comparison, two data sets provided by IC were approximately 20% lower than the three data sets obtained by PIXE and XRF. When two identical IMPROVE-compat-ible samplers were used and samples were subjected to similar procedures and the same analytical techniques, the variability between the two air concentration data sets significantly decreased.     

Continuous Emissions Monitoring Using Spark-Induced Breakdown Spectroscopy

ABSTRACT

A new technology for monitoring airborne heavy metals on aerosols and particulates based on spark-induced breakdown spectroscopy (SIBS) was evaluated at a joint U.S. Environmental Protection Agency (EPA)/U.S. Department of Energy test at the rotary kiln incinerator simulator (RKIS) facility at EPA/Research Triangle Park, NC, in September 1997. The instrument was configured to measure lead and chromium in a simulated combustion flue gas in real time and in situ at target levels of 15 and 75 u, g/dry standard cubic meters. Actual metal concentrations were measured during the tests using EPA Reference Method (RM) 29.

The SIBS technology detected both lead and chromium at the low- and high-level concentrations. Additionally, the hardware performed without failure for more than 100 hr of operation and acquired data for 100% of the RM tests. The chromium data were well correlated with concentration increases resulting from duct operations and pressure fluctuations that are known to entrain dust.     

Trends in arsenic levels in PM10 and PM2.5 aerosol fractions in an industrialized area

Arsenic is a toxic element that affects human health and is widely distributed in the environment. In the area of study, the main Spanish and second largest European industrial ceramic cluster, the main source of arsenic aerosol is related to the impurities in some boracic minerals used in the ceramic process. Epidemiological studies on cancer occurrence in Spain points out the study region as one with the greater risk of cancer. Concentrations of particulate matter and arsenic content in PM₁₀ and PM_2.5 were measured and characterized by ICP-MS in the area of study during the years 2005–2010. Concentrations of PM₁₀ and its arsenic content range from 27 to 46 μg/m³ and from 0.7 to 6 ng/m³ in the industrial area, respectively, and from 25 to 40 μg/m³ and from 0.7 to 2.8 ng/m³ in the urban area, respectively. Concentrations of PM_2.5 and its arsenic content range from 12 to 14 μg/m³ and from 0.5 to 1.4 ng/m³ in the urban background area, respectively. Most of the arsenic content is present in the fine fraction, with ratios of PM_2.5/PM₁₀ in the range of 0.65–0.87. PM₁₀, PM_2.5, and its arsenic content show a sharp decrease in recent years associated with the economic downturn, which severely hit the production of ceramic materials in the area under study. The sharp production decrease due to the economic crisis combined with several technological improvements in recent years such as substitution of boron, which contains As impurities as raw material, have reduced the concentrations of PM₁₀, PM_2.5, and As in air to an extent that currently meets the existing European regulations.     

Determination of Source Contributions to Ambient PM2.5 in Kaohsiung,Taiwan, Using a Receptor Model

ABSTRACT

Ambient particulates of PM_2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM_2.5 collected from traffic tunnels, paved roads, fly ash of a municipal solid waste (MSW) incinerator, and seawater was obtained. All the samples were analyzed for twenty constituents, including water-soluble ions, organic carbon (OC), elemental carbon (EC), and metallic elements. In conjunction with local source profiles and the source profiles in the model library SPECIATE EPA, the receptor model based on chemical mass balance (CMB) was then applied to determine the source contributions to ambient PM_2.5.

The mean concentration of ambient PM_2.5 was 42.6953.68 μj.g/m³ for the sampling period. The abundant species in ambient PM_2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO₄ ^2- (12.8-15.1%), NO₃ ^- (8.110.3%), NH₄+ (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for ambient PM_2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO₄ ^2- and NO₃ ^-), and outdoor burning of agriculture wastes (13-17%).