The Australian Air Quality Forecasting System: the use of green scenarios of motor vehicle usage as an educational tool

The Australian Air Quality Forecasting System (AAQFS) is one of several newly emerging, high-resolution, numerical air quality forecasting systems. The system is briefly described. A public education application of the air quality impact of motor vehicle usage is explored by computing the concentration and dosage of particulate matter less than 10 microm in aerodynamic diameter (PM10) for a commuter traveling to work between Geelong and Melbourne, Victoria, Australia, under "business-as-usual" and "green" scenarios. This application could be routinely incorporated into systems like AAQFS. Two methodologies for calculating the dosage are described: one for operational use and one for more detailed applications. The Clean Air Research Programme-Personal Exposure Study in Melbourne provides support for this operational methodology. The more detailed methodology is illustrated using a system for predicting concentrations due to near-road emissions of PM10 and applied in Sydney.     

Determination of air quality zones in Turkey

In this study, the particulate matter (with an aerodynamic diameter <10 μm; PM₁₀) profile of Turkey with data from the air quality monitoring stations located throughout the country was used. The number of stations (119) was reduced to 55 after a missing data treatment for statistical analyses. First, a classification method was developed based on ongoing national and international (European Commission directives) legislations to categorize air zones into six groups, from a “Very Clear Air Zone” to a “Polluted Air Zone.” Then, a Geographic Information System (GIS)-based interpolation technique and statistical analyses (correlation analysis and factor analysis) were used to generate PM₁₀ pollution profiles of the annual heating time and nonheating time periods. Finally, the coherent air pollution management zones of Turkey, based on air quality criteria and measured data using a GIS-based model supported by statistical analyses, were suggested. Based on the analysis, four hot spots were identified: (i) the eastern part of the Black Sea region; (ii) the northeastern part of inland Anatolia; (iii) the western part of Northeastern Anatolia; and (vi) the eastern part of Turkey. The possible reasons for the elevated PM₁₀ levels are discussed using topographic, climatologic, land use, and energy utilization parameters. Finally, the suggested air zones were compared with the administrative air zones, which were newly developed by the Turkish Ministry of Environment and Forestry, to evaluate the level of agreement between the two.

Implications: The evaluation of air quality profiles of specific regions is important in the development and/or application of an effective air quality management strategy. Factor analysis (FA), together with correlation analysis (CA), provides useful information to classify air pollution management areas over regional networks that have historical time-series air quality data. In this study, which relied on a FA- and CA-based methodology, the coherent air pollution management zones of Turkey after using a GIS-based model were suggested. Policy makers and scientist can use these suggested zones to construct better air quality management strategies.     

Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing

This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM_2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new “Deep Blue” retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM_2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented.

Implications: Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM_2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise result in more serious air quality episodes or more deleterious health effects.     

Evaluation of Human Exposure to Ambient PM10 in the Metropolitan Area of Mexico City Using a GIS-Based Methodology

ABSTRACT

The main goal of this study was to evaluate the magnitude of outdoor exposure to fine particulate matter (PM₁₀) potentially experienced by the population of metropolitan Mexico City. With the use of a geographic information system (GIS), spatially resolved PM₁₀ distributions were generated and linked to the local population. The PM₁₀ concentration exceeded the 24-hr air quality standard of 150 μg/m³ on 16% of the days, and the annual air quality standard of 50 μg/m³ was exceeded by almost twice its value in some places. The basic methodology described in this paper integrates spatial demographic and air quality databases, allowing the evaluation of various air pollution reduction scenarios. Achieving the annual air quality standard would represent a reduction in the annual arithmetic average concentration of 14 μg/m³ for the typical inhabitant. Human exposure to particulate matter (PM) has been associated with mortality and morbidity in Mexico City; reducing the concentration levels of this pollutant would represent a reduction in mortality and morbidity and the associated cost of such impacts. This methodology is critical to assessing the potential benefits of the current initiative to improve air quality implemented by the Environmental Metropolitan Commission of Mexico City.     

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.     

The Southeastern Aerosol Research and Characterization Study: Part II. Filter-Based Measurements of Fine and Coarse Particulate Matter Mass and Composition

Abstract

The Southeastern Aerosol Research and Characterization Study (SEARCH) was implemented in 1998–1999 to provide data and analyses for the investigation of the sources, chemical speciation, and long-term trends of fine particulate matter (PM_2.5) and coarse particulate matter (PM_10–2.5) in the Southeastern United States. This work is an initial analysis of 5 years (1999–2003) of filter-based PM_2.5 and PM_10–2.5 data from SEARCH. We find that annual PM_2.5 design values were consistently above the National Ambient Air Quality Standards (NAAQS) 15 µg/m³ annual standard only at monitoring sites in the two largest urban areas (Atlanta, GA, and North Birmingham, AL). Other sites in the network had annual design values below the standard, and no site had daily design values above the NAAQS 65 µg/m³ daily standard. Using a particle composition monitor designed specifically for SEARCH, we found that volatilization losses of nitrate, ammonium, and organic carbon must be accounted for to accurately characterize atmospheric particulate matter. In particular, the federal reference method for PM_2.5 underestimates mass by 3–7% as a result of these volatilization losses. Organic matter (OM) and sulfate account for ≥60% of PM_2.5 mass at SEARCH sites, whereas major metal oxides (MMO) and unidentified components (“other”) account for ≥80% of PM_10–2.5 mass. Limited data suggest that much of the unidentified mass in PM_10–2.5 may be OM. For paired comparisons of urban-rural sites, differences in PM_2.5 mass are explained, in large part, by higher OM and black carbon at the urban site. For PM₁₀, higher urban concentrations are explained by higher MMO and “other.” Annual means for PM_2.5 and PM_10–2.5 mass and major components demonstrate substantial declines at all of the SEARCH sites over the 1999–2003 period (10–20% in the case of PM_2.5, dominated by 14–20% declines in sulfate and 11–26% declines in OM, and 14–25% in the case of PM_10–2.5, dominated by 17–30% declines in MMO and 14–31% declines in “ other”). Although declining national emissions of sulfur dioxide and anthropogenic carbon may account for a portion of the observed declines, additional investigation will be necessary to establish a quantitative assessment, especially regarding trends in local and regional emissions, primary carbon emissions, and meteorology.     

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.     

Codependencies of Reactive Air Toxic and Criteria Pollutants on Emission Reductions

Abstract

It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM_2.5), and hazardous air pollutants (HAPs) simultaneously, to evaluate the full range of health, ecosystem, and economic effects. Until recently, the capability to simultaneously evaluate interrelated atmospheric pollutants (“one atmosphere” analysis) was unavailable to air quality managers. In this work, we use an air quality model to examine the potential effect of three emission reductions on concentrations of ozone, PM_2.5, and four important HAPs (formaldehyde, acetaldehyde, acrolein, and benzene) over a domain centered on Philadelphia for 12-day episodes in July and January 2001. Although NO_x controls are predicted to benefit PM_2.5 concentrations and sometimes benefit ozone, they have only a small effect on formaldehyde, slightly increase acetaldehyde and acrolein, and have no effect on benzene in the July episode. Concentrations of all pollutants except benzene increase slightly with NO_x controls in the January simulation. Volatile organic compound controls alone are found to have a small effect on ozone and PM_2.5, a less than linear effect on decreasing aldehydes, and an approximately linear effect on acrolein and benzene in summer, but a slightly larger than linear effect on aldehydes and acrolein in winter. These simulations indicate the difficulty in assessing how toxic air pollutants might respond to emission reductions aimed at decreasing criteria pollutants such as ozone and PM_2.5.     

Particulate Emission Rates for Unpaved Shoulders along a Paved Road

ABSTRACT

This paper reports the first empirical estimate of particle emissions from unpaved shoulders along paved roads.¹ Its objectives are to develop and demonstrate an emission rate measurement methodology that can be applied in different areas; identify the mechanisms that suspend dust from unpaved shoulders and the observables related to this suspension process; and quantify PM₁₀ mass emissions in the form of an emission rate. To achieve these objectives, fast-response observations from nephelometers and a sonic anemometer were used to characterize shortlived dust plumes generated by passing vehicles. In addition, detailed soil surface measurements determined the mechanical properties of the shoulder surfaces.

Large traffic-induced turbulence events that led to significant dust entrainment were almost exclusively caused by “large” vehicles such as trucks, semis, and vehicles pulling trailers, all traveling 50-65 mph. PM₁₀ emission rates for these large, fast-traveling vehicles were determined to be 8 ± 4 grams per vehicle kilometer traveled under dry conditions. Emissions due to smaller vehicles such as cars, vans, and sport utility vehicles were negligible for normal on-road driving. These results indicate that the majority of PM₁₀ emissions from unpaved shoulders is caused by relatively few vehicles.     

A combined model–observation approach to estimate historic gridded fields of PM2.5 mass and species concentrations

This paper introduces a methodology for estimating gridded fields of total and speciated fine particulate matter (PM_2.5) concentrations for time periods and regions not covered by observational data. The methodology is based on performing long-term regional scale meteorological and air quality simulations and then integrating these simulations with available observational data. To illustrate this methodology, we present an application in which year-round simulations with a meteorological model (the National Center for Atmospheric Research/Penn State Mesoscale Model, hereafter referred to as MM5) and a photochemical air quality model (the Community Multiscale Air Quality Model, hereafter referred to as CMAQ) have been performed over the northeastern United States for 1988–2005. Model evaluation results for total PM_2.5 mass and individual species for the time period from 2000 to 2005 show that model performance varies by species, season, and location. Therefore, an approach is developed to adjust CMAQ output with factors based on these three variables. The adjusted model values for total PM_2.5 mass for 2000–2005 are compared against independent measurements not utilized for the adjustment approach. This comparison reveals that the adjusted model values have a lower root mean square error (RMSE) and higher correlation coefficients than the original model values. Furthermore, the PM_2.5 estimates from these adjusted model values are compared against an alternate method for estimating historic PM_2.5 values that is based on PM_2.5/PM₁₀ ratios calculated at co-located monitors. Results reveal that both methods yield estimates of historic PM_2.5 mass that are broadly consistent; however, the adjusted CMAQ values provide greater spatial coverage and information for PM_2.5 species in addition to total PM_2.5 mass. Finally, strengths and limitations of the proposed approach are discussed in the context of potential uses of this method.     

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi,Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th–March 31st) and during the partial lockdown (April 1st–April 22nd) with “current” data obtained in 2020 and “historical” data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

     

Estimation of Ambient PM2.5 Concentrations in Maryland and Verification by Measured Values

Abstract

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5), but did have annual ambient data for PM smaller than 10 μm (PM₁₀) at 24 sites. The PM₁₀ data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM_2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM_2.5 concentrations at the 24 PM₁₀ monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM_2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM_2.5 NAAQS of 15 ug/m³, but Maryland’s air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM_2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM_2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM_2.5 across central Maryland.     

Characterization of Particulate Matter for Three Sites in Kuwait

Abstract

Many studies have shown strong associations between particulate matter (PM) levels and a variety of health outcomes, leading to changes in air quality standards in many regions, especially the United States and Europe. Kuwait, a desert country located on the Persian Gulf, has a large petroleum industry with associated industrial and urban land uses. It was marked by environmental destruction from the 1990 Iraqi invasion and subsequent oil fires. A detailed particle characterization study was conducted over 12 months in 2004–2005 at three sites simultaneously with an additional 6 months at one of the sites. Two sites were in urban areas (central and southern) and one in a remote desert location (northern). This paper reports the concentrations of particles less than 10 µm in diameter (PM₁₀) and fine PM (PM_2.5), as well as fine particle nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and elements measured at the three sites. Mean annual concentrations for PM₁₀ ranged from 66 to 93 µg/m³ across the three sites, exceeding the World Health Organization (WHO) air quality guidelines for PM₁₀ of 20 µg/m³. The arithmetic mean PM_2.5 concentrations varied from 38 and 37 µg/m³ at the central and southern sites, respectively, to 31 µg/m³ at the northern site. All sites had mean PM_2.5 concentrations more than double the U.S. National Ambient Air Quality Standard (NAAQS) for PM_2.5. Coarse particles comprised 50–60% of PM₁₀. The high levels of PM₁₀ and large fraction of coarse particles comprising PM₁₀ are partially explained by the resuspension of dust and soil from the desert crust. However, EC, OC, and most of the elements were significantly higher at the urbanized sites, compared with the more remote northern site, indicating significant pollutant contributions from local mobile and stationary sources. The particulate levels in this study are high enough to generate substantial health impacts and present opportunities for improving public health by reducing airborne PM.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Overview and Statistical Considerations

Abstract

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5) in Steubenville, OH, have decreased by more than 10 μg/m³ since the landmark Harvard Six Cities Study¹ associated the city’s elevated PM_2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM_2.5 in 1997, a current assessment of PM_2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM_2.5 data analyses. The average PM_2.5 concentration measured in Steubenville during SCAMP (18.4 μg/m³) was 3.4g/m³ above the annual PM_2.5 NAAQS. On average, sulfate and organic material accounted for ～31% and 25%, respectively, of the total PM_2.5 mass. Local sources contributed an estimated 4.6 μg/m³ to Steubenville’s mean PM_2.5 concentration. PM_2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM_2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM_2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.     

Nitrate Artifacts during PM25 Sampling in the South Coast Air Basin of California

ABSTRACT

In February 1993, the South Coast Air Basin (SCAB) was redesignated as a “serious” nonattainment area for PM10. To improve the understanding and characterization of fine particulate matter in the SCAB, the South Coast Air Quality Management District (SCAQMD) initiated a comprehensive PM₁₀ Technical Enhancement Program (PTEP). Using enhanced PTEP monitors (specially designed multichannel/multifilter samplers), a one-year fine particulate matter (PM) monitoring program was initiated in January 1995. As part of the special monitoring program, nitric acid, ammonia, and speciated PM₁₀ and PM_2.5 concentrations were measured at five locations in the SCAB (downtown Los Angeles, Anaheim, Diamond Bar, Fontana, and Rubidoux) and at one background station (San Nicolas Island). The PM2.5 data are the first spatially resolved speciated data collected in the SCAB on an annual basis. Within the SCAB, where nitrate is a major component of PM_2.5, nitrate losses have been documented. The spatial and temporal variations of the nitrate losses during PM_2.5 sampling and the uncertainties of the nitrate losses are discussed. Significant losses occur at a low mass range, between 10 and 50 ìg/m³. Significant gains occur at an even lower mass range of less than 30 ìg/m³. On an annual average basis, nitrate losses vary between 1.25 and 2.32 ìg/m³ and the SCAB-wide average value of nitrate loss is 1.8 ìg/m³ based on five PTEP stations in the SCAB. The maximum nitrate losses for each station vary from 6.4 ìg/m³ to 22.5 ìg/m ³. Theoretical prediction of the sampling efficiency of the nitrate during PM_2.5 sam - pling was compared with the PTEP data. In general, theoretical prediction was in good agreement with measured values.     

Air Quality Impacts of Distributed Energy Resources Implemented in the Northeastern United States

Abstract

Emissions from the potential installation of distributed energy resources (DER) in the place of current utility-scale power generators have been introduced into an emissions inventory of the northeastern United States. A methodology for predicting future market penetration of DER that considers economics and emission factors was used to estimate the most likely implementation of DER. The methodology results in spatially and temporally resolved emission profiles of criteria pollutants that are subsequently introduced into a detailed atmospheric chemistry and transport model of the region. The DER technology determined by the methodology includes 62% reciprocating engines, 34% gas turbines, and 4% fuel cells and other emerging technologies. The introduction of DER leads to retirement of 2625 MW of existing power plants for which emissions are removed from the inventory. The air quality model predicts maximum differences in air pollutant concentrations that are located downwind from the central power plants that were removed from the domain. Maximum decreases in hourly peak ozone concentrations due to DER use are 10 ppb and are located over the state of New Jersey. Maximum decreases in 24-hr average fine particulate matter (PM_2.5) concentrations reach 3 μg/m3 and are located off the coast of New Jersey and New York. The main contribution to decreased PM_2.5 is the reduction of sulfate levels due to significant reductions in direct emissions of sulfur oxides (SO_x) from the DER compared with the central power plants removed. The scenario presented here represents an accelerated DER penetration case with aggressive emission reductions due to removal of highly emitting power plants. Such scenario provides an upper bound for air quality benefits of DER implementation scenarios.     

Outdoor and indoor factors influencing particulate matter and carbon dioxide levels in naturally ventilated urban homes

ABSTRACT

The present study investigated indoor and outdoor concentrations of two particulate matter size fractions (PM₁₀ and PM_2.5) and CO₂ in 20 urban homes ventilated naturally and located in one congested residential and commercial area in the city of Alexandria, Egypt. The results indicate that the daily mean PM_2.5 concentrations measured in the ambient air, living rooms, and kitchens of all sampling sites exceeded the WHO guideline by 100%, 65%, and 95%, respectively. The daily mean outdoor and indoor PM₁₀ levels in all sampling sites were found to exceed the WHO guideline by 100% and 80%, respectively. The indoor PM₁₀ and PM_2.5 concentrations were significantly correlated with their corresponding outdoor levels, as natural ventilation through opening doors and windows allowed direct transfer of outdoor airborne particles into the indoor air. Most of the kitchens investigated had higher indoor concentrations of PM_2.5 and CO₂ than in living rooms. The elevated levels of PM_2.5 and CO₂ in domestic kitchens were probably related to inadequate ventilation. The current study attempted to understand the sources and the various indoor and outdoor factors that affect indoor PM₁₀, PM_2.5 and CO₂ concentrations. Several domestic activities, such as smoking, cooking, and cleaning, were found to constitute important sources of indoor air pollution. The indoor pollution caused by PM_2.5 was also found to be more serious in the domestic kitchens than in the living rooms and the results suggest that exposure to PM_2.5 is high and highlights the need for more effective control measures.

Implications: Indoor air pollution is a complex problem that involves many determinant factors. Understanding the relationships and the influence of various indoor and outdoor factors on indoor air quality is very important to prioritize control measures and mitigation action plans. There is currently a lack of research studies in Egypt to investigate determinant factors controlling indoor air quality for urban homes. The present study characterizes the indoor and outdoor concentrations of PM₁₀, PM_2.5, and CO₂ in residential buildings in Alexandria city. The study also determines the indoor and outdoor factors which influence the indoor PM and CO₂ concentrations as well as it evaluates the potential indoor sources in the selected homes. This research will help in the development of future indoor air quality standards for Egypt.     

Simulating industrial emissions using Atmospheric Dispersion Modeling System: Model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NO_X), carbon monoxide (CO), fine particulate matter (PM₁₀) and sulfur dioxide (SO₂)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement d values reaching 0.58, fractional bias “FB” and geometric mean bias “MG” values approaching 0 and 1, respectively, and normalized mean square error “NMSE” values as low as 2.17. However, median ratios of predicted to observed concentrations “Cp/Co” at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NO_X, CO, PM₁₀ and SO₂, respectively, and the fraction of predictions within a factor of two of observations “FAC2” values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.

Implications In the absence of site-specific source emission factors, the use of internationally reported emission factors without testing their validity may generate significant errors. Instead, recorded field measurements and meteorological data may be combined with atmospheric transport and dispersion models to better estimate source emissions, particularly in regulatory compliance studies. In this context, lower model performance is expected at higher wind speeds for most indicators such as CO, PM₁₀, and SO₂.     

Patterns and Concentrations of PM10 in a Mountainous Basin Region

ABSTRACT

In this study, continuous data of PM₁₀ (particles with aerodynamic diameter <10 u,m) concentration measurements for a 4-yr period were analyzed. These measurements have been carried out in the Eordea Basin, an industrial area in the northwestern mountainous region of Greece. The annual, monthly, and diurnal patterns are presented and investigated regarding the prevailing meteorological conditions and atmospheric processes that affect the ambient concentrations of PM₁₀. The effect of wind on controlling PM₁₀ concentration is also discussed. Based on the data analysis, an attempt is made to provide useful information about air quality levels, taking into account U.S. Environmental Protection Agency air quality standards.