The influence of tropical cyclone Melor on PM10 concentrations during an aerosol episode over the Pearl River Delta region of China: Numerical modeling versus observational analysis

In this article, numerical simulations and observational analyses have been made for the aerosol episode that occurred over the Pearl River Delta (PRD) region in China during 1–3 November 2003. An air quality modeling system that consisted of the mesoscale model MM5, chemical transport model MODELS-3/CMAQ, and air pollutant emission model SMOKE, was employed. Studies have shown that this particulate matter (PM) pollution episode was apparently associated with the activity of tropical cyclone (TC) Melor. Model simulations revealed that Melor spawned this PM episode through dynamic and thermodynamic processes. The strong compensating subsidence induced by Melor's peripheral circulations created favorable meteorological conditions that enhanced local aerosol pollution. This strong downward motion produced significant adiabatic warming (2–4 °C daily) and dramatic drying in the low-level troposphere over the PRD. As a result, the PRD region was blanketed with a dry and warm air layer that strengthened the static stability of the lower troposphere. The descending motion also tended to dramatically lower the heights of the planetary boundary layer (PBL) through its dynamic effect. The fair weather created by this synoptic pattern further intensified the nocturnal temperature inversions through enhanced radiative cooling. All of these factors promoted a stagnant local atmosphere with very light winds near the surface. The horizontal and vertical dispersions of locally emitted aerosol particles were largely suppressed, leading to the accumulation of large amounts of PMs near local emission sources in the PRD region. As Melor drew near, changes in surface winds strengthened the horizontal transport of aerosol particles from inland sources to the area of Hong Kong downstream. This horizontal advection greatly contributed to the high PM₁₀ (particulate matters less than 10 μm in diameters) concentrations in Hong Kong.     

A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems

A harmonized comparative performance evaluation of A Unified Regional Air-quality Modelling System (AURAMS) v1.3.1b and Community Multiscale Air Quality (CMAQ) v4.6 air-quality modelling systems was conducted on the same North American grid for July 2002 using the same emission inventories, emissions processor, and input meteorology.Comparison of AURAMS- and CMAQ-predicted O₃ concentrations against hourly surface measurement data showed a lower normalized mean bias (NMB) of 20.7% for AURAMS versus 46.4% for CMAQ. However, AURAMS and CMAQ had more similar normalized mean errors (NMEs) of 46.9% and 54.2%, respectively. Both models did similarly well in predicting daily 1-h O₃ maximums; however, AURAMS performed better in calculating daily minimums. CMAQ's poorer performance for O₃ is partly due to its inability to correctly predict nighttime lows.Total PM_2.5 hourly surface concentration was under-predicted by both AURAMS and CMAQ with NMBs of ?10.4% and ?65.2%, respectively. However, as with O₃, both models had similar NMEs of 68.0% and 70.6%, respectively. In general, AURAMS performance was better than CMAQ for all major PM_2.5 species except nitrate and elemental carbon. Both models significantly under-predicted total organic aerosols (TOAs), although the mean AURAMS concentration was over four times larger than CMAQ's. The under-prediction of TOA was partly due to the exclusion of forest-fire emissions. Sea-salt aerosol made up approximately 50.2% of the AURAMS total PM_2.5 surface concentration versus only 6.2% in CMAQ when averaged over all grid cells. When averaged over land cells only, sea-salt still contributed 13.9% to the total PM_2.5 mass in AURAMS versus 2.0% in CMAQ.     

Lagrangian sampling of 3-D air quality model results for regional transport contributions to sulfate aerosol concentrations at Baltimore,MD, in summer 2004

We use ensemble-mean Lagrangian sampling of a 3-D Eulerian air quality model, CMAQ, together with ground-based ambient monitors data from several air monitoring networks and satellite (MODIS) observations to provide source apportionment and regional transport vs. local contributions to sulfate aerosol and PM_2.5 concentrations at Baltimore, MD, for summer 2004. The Lagrangian method provides estimates of the chemical and physical evolution of air arriving in the daytime boundary layer at Baltimore. Study results indicate a dominant role for regional transport contributions on those days when sulfate air pollution is highest in Baltimore, with a principal transport pathway from the Ohio River Valley (ORV) through southern Pennsylvania and Maryland, consistent with earlier studies. Thus, reductions in sulfur emissions from the ORV under the EPA's Clean Air Interstate Rule may be expected to improve particulate air quality in Baltimore during summer. The Lagrangian sampling of CMAQ offers an inexpensive and complimentary approach to traditional methods of source apportionment based on multivariate observational data analysis, and air quality model emissions separation. This study serves as a prototype for the method applied to Baltimore. EPA is establishing a system to allow air quality planners to readily produce and access equivalent results for locations of their choice.     

Chemical characteristics of long-range transport aerosol at background sites in Korea

In this study, background concentration sites of Deokjeok and Gosan, which were deemed suitable for monitoring the impact of long-range transported air pollutants, were selected. An investigation of the source types of pollutants, their locations, and relative quantitative contributions to the particulate concentrations at both sites using appropriate methodologies to make initial estimations was conducted. Episodic measurements of PM_2.5, PM₁₀, and size distribution, along with its ion and carbon components were performed from 2005 to 2007, and a comprehensive analysis of the results was conducted utilizing back trajectory analysis. As for frequency of wind direction, it was quite apparent that the two sites are heavily influenced by air masses originating from the eastern and northern regions of China. For PM_2.5 and PM₁₀, the mass concentrations from north and east China were higher than other cases, originating from the ocean. In the northerly-wind case, meteorological properties for Deokjeok and Gosan and the influence of carbon emissions from northwest Korea resulted in a changing of air mass properties during transport. As was the case with mass concentration, the highest contribution for ionic and carbon components of PM_2.5 and PM₁₀ for both sites appeared for the westerly wind case. A specially high relative contribution, greater than 1.4 times, was apparent in the secondary aerosol case because of a large influence of long-range transported pollutants from east China. Carbon components exhibited different behaviors for the northerly and westerly wind cases compared with secondary aerosol. The major reason for this discrepancy appears to be the carbon emissions from northwest Korea.     

Application of Satellite Remote-Sensing Data for Source Analysis of Fine Particulate Matter Transport Events

Abstract

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative imagery and quantitative data, such as aerosol optical depth. Yet there has been limited application of these new datasets in the study of air pollutant sources relevant to public policy. One promising approach to more directly link satellite sensor data to air quality policy is to integrate satellite sensor data with air quality parameters and models. This paper presents a visualization technique to integrate satellite sensor data, ground-based data, and back trajectory analysis relevant to a new rule concerning the transport of particulate matter across state boundaries. Overlaying satellite aerosol optical depth data and back trajectories in the days leading up to a known fine particulate matter with an aerodynamic diameter of <2.5 μm (PM_2.5) event may indicate whether transport or local sources appear to be most responsible for high PM_2.5 levels in a certain location at a certain time. Events in five cities in the United States are presented as case studies. This type of analysis can be used to help understand the source locations of pollutants during specific events and to support regulatory compliance decisions in cases of long distance transport.     

Implementation and application of sub-grid-scale plume treatment in the latest version of EPA’s third-generation air quality model,CMAQ 5.01

The Community Multiscale Air Quality (CMAQ) modeling system Version 5.0 (CMAQv5.0) was released by the U.S. Environmental Protection Agency (EPA) in February 2012, with an interim release (v5.01) in July 2012. Because CMAQ is a community model, the EPA encourages the development of proven alternative science treatments by external scientists and developers that can be incorporated as part of an official CMAQ release. This paper describes the implementation, evaluation, and testing of a plume-in-grid (PinG) module in CMAQ 5.01. The PinG module, also referred to as Advanced Plume Treatment (APT), provides the capability of resolving sub-grid-scale processes, such as the transport and chemistry of point-source plumes, in a grid model. The new PinG module in CMAQ 5.01 is applied and evaluated for two 15-day summer and winter periods in 2005 to the eastern United States, and the results are compared with those from the base CMAQ 5.01. Eighteen large point sources of NOx in the eastern United States were selected for explicit plume treatment with APT in the PinG simulation. The results show that overall model performance is negligibly affected when PinG treatment is included. However, the PinG model predicts significantly different contributions of the 18 sources to pollutant concentrations and deposition downwind of the point sources compared to the base model.

Implications: This study describes the incorporation of a plume-in-grid (PinG) capability within the latest version of the EPA grid model, CMAQ. The capability addresses the inherent limitation of the grid model to resolve processes, such as the evolution of point-source plumes, which occur at scales much smaller than the grid resolution. The base grid model and the PinG version predict different source contributions to ozone and PM_2.5 concentrations that need to be considered when source attribution studies are conducted to determine the impacts of large point sources on downwind concentrations and deposition of primary and secondary pollutants.     

Toward verifying fossil fuel CO2 emissions with the CMAQ model: Motivation,model description and initial simulation

Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO₂ spatiotemporal variability and verify CO₂ fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO₂. This paper presents methods, input data, and initial results for CO₂ simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere–atmosphere exchange, and meteorology in regulating the spatial distribution of CO₂ near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO₂ concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver, CO, the CMAQ model using hourly varying, high-resolution CO₂ fossil-fuel emissions from the Vulcan inventory and CarbonTracker optimized NEE reproduced the observed diurnal profile of CO₂ reasonably well but with a low bias in the early morning. The spatial distribution of CO₂ was found to correlate with NOx, SO₂, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO₂ observations and understand CO₂ variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO₂ source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO₂ spatiotemporal variability and various uncertainties in the future.

Implications: Atmospheric CO₂ has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO₂ variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO₂ emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO₂ as an air pollutant.     

Characterization of organic aerosol in Big Bend National Park,Texas

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study was conducted in Big Bend National Park, Texas, July through October 1999. Daily PM_2.5 organic aerosol samples were collected on pre-fired quartz fiber filters. Daily concentrations were too low for detailed organic analysis by gas chromatography-mass spectrometry (GC-MS) and were grouped based on their air mass trajectories. A total of 12 composites, each containing 3–10 daily samples, were analyzed. Alkane carbon preference indices suggest primary biogenic emissions were small contributors to primary PM_2.5 organic matter (OM) during the first 3 months, while in October air masses advecting from the north and south were more strongly influenced by biogenic sources. A series of trace organic compounds previously shown to serve as particle phase tracers for various carbonaceous aerosol source types were examined. Molecular tracer species were generally at or below detection limits, except for the wood smoke tracer levoglucosan in one composite, so maximum possible source influences were calculated using the detection limit as an upper bound to the tracer concentration. Wood smoke was found not to contribute significantly to PM_2.5 OM, with contributions for most samples at <1% of the total organic particulate matter. Vehicular exhaust also appeared to make only minor contributions, with maximum possible influences calculated to be 1–4% of PM_2.5 OM. Several factors indicate that secondary organic aerosol formation was important throughout the study, and may have significantly altered the molecular composition of the aerosol during transport.     

Temporal Variations of PM2.5, PM10, and Gaseous Precursors during the 1995 Integrated Monitoring Study in Central California

ABSTRACT

The spatial and temporal distributions of particle mass and its chemical constituents are essential for understanding the source-receptor relationships as well as the chemical, physical, and meteorological processes that result in elevated particulate concentrations in California’s San Joaquin Valley (SJV). Fine particulate matter ₍PM_2.5), coarse particulate matter (PM₁₀), and aerosol precursor gases were sampled on a 3-hr time base at two urban (Bakersfield and Fresno) and two non-urban (Kern Wildlife Refuge and Chowchilla) core sites in the SJV during the winter of 1995–1996.

Day-to-day variations of PM_2.5 and PM₁₀ and their chemical constituents were influenced by the synoptic-scale meteorology and were coherent among the four core sites. Under non-rainy conditions, similar diurnal variations of PM_2.5 and coarse aerosol were found at the two urban sites, with concentrations peaking during the nighttime hours. Conversely, PM_2.5 and coarse aerosol peaked during the morning and afternoon hours at the two non-urban sites. Under rainy and foggy conditions, these diurnal patterns were absent or greatly suppressed.

In the urban areas, elevated concentrations of primary pollutants (e.g., organic and elemental carbons) during the late afternoon and nighttime hours reflected the impact from residential wood combustion and motor vehicle exhaust. During the daytime, these concentrations decreased as the mixed layer deepened. Increases of secondary nitrate and sulfate concentrations were found during the daylight hours as a result of photochemical reactions. At the non-urban sites, the same increases in secondary aerosol concentrations occurred during the daylight hours but with a discernable lag time. Concentrations of the primary pollutants also increased at the non-urban sites during the daytime. These observations are attributed to mixing aloft of primary aerosols and secondary precursor gases in urban areas followed by rapid transport aloft to non-urban areas coupled with photochemical conversion.     

Estimations of primary and secondary organic carbon formation in PM2.5 aerosols of Santiago City,Chile

High concentration of fine airborne particulates is considered one of the major environmental pollutants in Santiago, the Chilean Capital city, which in 1997 was declared a PM₁₀ saturated zone. To date there is no control of the amounts of fine and coarse aerosols concentrations and the source and chemical characterizations of the PM_2.5 particulates in the carbonaceous fractions are not well known even though this fraction could be represented almost the 50% in mass of the PM_2.5.In this work, we present for the first time determinations of primary organic aerosol (POA) and secondary organic aerosol composition (SOA) fractions of the total mass of PM_2.5 particulates collected in the urban atmosphere of Santiago City. Our purpose is to know the anthropogenic contributions to the formation of SOA. To accomplish this we used the elemental carbon (EC) and organic carbon (OC) determinations developed by automatic monitoring stations installed in the city during the period 2002–2005, with a particular analysis of the summer time occurred in February 2004. Based on the EC tracer method, we have estimated the POA and SOA fraction and our data permit us to estimate the SOA reaching up to 20% of total organic aerosol matter, in good agreement to other measurements observed in large cities of Europe and U.S.A.     

Evaluation of the community multiscale air quality (CMAQ) model version 4.5: Sensitivities impacting model performance; Part II—particulate matter

This paper is Part II in a pair of papers that examines the results of the Community Multiscale Air Quality (CMAQ) model version 4.5 (v4.5) and discusses the potential explanations for the model performance characteristics seen. The focus of this paper is on fine particulate matter (PM_2.5) and its chemical composition. Improvements made to the dry deposition velocity and cloud treatment in CMAQ v4.5 addressing compensating errors in 36-km simulations improved particulate sulfate (SO₄²⁻) predictions. Large overpredictions of particulate nitrate (NO₃⁻) and ammonium (NH₄⁺) in the fall are likely due to a gross overestimation of seasonal ammonia (NH₃) emissions. Carbonaceous aerosol concentrations are substantially underpredicted during the late spring and summer months, most likely due, in part, to a lack of some secondary organic aerosol (SOA) formation pathways in the model. Comparisons of CMAQ PM_2.5 predictions with observed PM_2.5 mass show mixed seasonal performance. Spring and summer show the best overall performance, while performance in the winter and fall is relatively poor, with significant overpredictions of total PM_2.5 mass in those seasons. The model biases in PM_2.5 mass cannot be explained by summing the model biases for the major inorganic ions plus carbon. Errors in the prediction of other unspeciated PM_2.5 (PM_Other) are largely to blame for the errors in total PM_2.5 mass predictions, and efforts are underway to identify the cause of these errors.     

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

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

Chemical speciation,transport and contribution of biomass burning smoke to ambient aerosol in Guangzhou,a mega city of China

Intensive measurements of aerosol (PM₁₀) and associated water-soluble ionic and carbonaceous species were conducted in Guangzhou, a mega city of China, during summer 2006. Elevated levels of most chemical species were observed especially at nighttime during two episodes, characterized by dramatic build-up of the biomass burning tracers levoglucosan and non-sea-salt potassium, when the prevailing wind direction had changed due to two approaching tropical cyclones. High-resolution air mass back trajectories based on the MM5 model revealed that air masses with high concentrations of levoglucosan (43–473 ng m^?3) and non-sea-salt potassium (0.83–3.2 μg m^?3) had passed over rural regions of the Pearl River Delta and Guangdong Province, where agricultural activities and field burning of crop residues are common practices. The relative contributions of biomass burning smoke to organic carbon in PM₁₀ were estimated from levoglucosan data to be on average 7.0 and 14% at daytime and nighttime, respectively, with maxima of 9.7 and 32% during the episodic transport events, indicating that biomass and biofuel burning activities in the rural parts of the Pearl River Delta and neighboring regions could have a significant impact on ambient urban aerosol levels.     

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.     

Understanding of regional air pollution over China using CMAQ,part I performance evaluation and seasonal variation

The U.S. EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system with the process analysis tool is applied to China to study the seasonal variations and formation mechanisms of major air pollutants. Simulations show distinct seasonal variations, with higher surface concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM₁₀), column mass of carbon monoxide (CO) and NO₂, and aerosol optical depth (AOD) in winter and fall than other seasons, and higher 1-h O₃ and troposphere ozone residual (TOR) in spring and summer than other seasons. Higher concentrations of most species occur over the eastern China, where the air pollutant emissions are the highest in China. Compared with surface observations, the simulated SO₂, NO₂, and PM₁₀ concentrations are underpredicted throughout the year with NMBs of up to ?51.8%, ?32.0%, and ?54.2%, respectively. Such large discrepancies can be attributed to the uncertainties in emissions, simulated meteorology, and deviation of observations based on air pollution index. Max. 1-h O₃ concentrations in Jan. and Jul. at 36-km are overpredicted with NMBs of 12.0% and 19.3% and agree well in Apr. and Oct. Simulated column variables can capture the high concentrations over the eastern China and low values in the central and western China. Underpredictions occur over the northeastern China for column CO in Apr., TOR in Jul., and AODs in both Apr. and Jul.; and overpredictions occur over the eastern China for column CO in Oct., NO₂ in Jan. and Oct., and AODs in Jan. and Oct. The simulations at 12-km show a finer structure in simulated concentrations than that at 36-km over higher polluted areas, but do not always give better performance than 36-km. Surface concentrations are more sensitive to grid resolution than column variables except for column NO₂, with higher sensitivity over mountain and coastal areas than other regions.     

An integrated MM5–CMAQ modeling approach for assessing trans-boundary PM10 contribution to the host city of 2008 Olympic summer games—Beijing,China

In this paper, an integrated MM5–CMAQ modeling approach was employed to investigate the PM₁₀ air pollution issue in Beijing, China, with a focus on assessing pollution contributions from surrounding provinces. A 2-level-nested grid domain with spatial resolutions of 36 and 12 km was designed for the study region. Seven monitoring stations across Beijing municipality were selected to provide hourly PM₁₀ measurement data. The months of January, April, July and October in 2002 were taken as target periods for model performance evaluation. Five emission scenarios were designed and run in order to quantitatively assess the trans-boundary PM₁₀ contributions. The results show that, while Beijing needs to take positive steps to reduce its own pollution emissions, much effort should also be placed on demanding more pollution reduction and better environmental performance from surrounding provinces.     

Extensive aerosol optical properties and aerosol mass related measurements during TRAMP/TexAQS 2006 – Implications for PM compliance and planning

Extensive aerosol optical properties, particle size distributions, and Aerodyne quadrupole aerosol mass spectrometer measurements collected during TRAMP/TexAQS 2006 were examined in light of collocated meteorological and chemical measurements. Much of the evident variability in the observed aerosol-related air quality is due to changing synoptic meteorological situations that direct emissions from various sources to the TRAMP site near the center of the Houston-Galveston-Brazoria (HGB) metropolitan area. In this study, five distinct long-term periods have been identified. During each of these periods, observed aerosol properties have implications that are of interest to environmental quality management agencies. During three of the periods, long range transport (LRT), both intra-continental and intercontinental, appears to have played an important role in producing the observed aerosol. During late August 2006, southerly winds brought super-micron Saharan dust and sea salt to the HGB area, adding mass to fine particulate matter (PM_2.5) measurements, but apparently not affecting secondary particle growth or gas-phase air pollution. A second type of LRT was associated with northerly winds in early September 2006 and with increased ozone and sub-micron particulate matter in the HGB area. Later in the study, LRT of emissions from wildfires appeared to increase the abundance of absorbing aerosols (and carbon monoxide and other chemical tracers) in the HGB area. However, the greatest impacts on Houston PM_2.5 air quality are caused by periods with low-wind-speed sea breeze circulation or winds that directly transport pollutants from major industrial areas, i.e., the Houston Ship Channel, into the city center.     

African dust contributions to mean ambient PM10 mass-levels across the Mediterranean Basin

Data on mass-levels of PM₁₀ measured at regional background sites across the Mediterranean Basin, available from Airbase (European Environmental Agency) and from a few aerosol research sites, are compiled. PM₁₀ levels increase from north to south and west to east of the Basin. These variations are roughly coincident with the PM₁₀ African mineral dust load. However, when subtracting the African dust from mean PM₁₀ levels using a consistent methodology, the PM₁₀ background levels are still 5–10 μg m^?3 higher in the Eastern Basin (EMB) when compared with those in the Western (WMB), mainly due to the higher anthropogenic and sea spray loads.As regards for the seasonal trends, these are largely driven by the occurrence of African dust events, resulting in a spring-early summer maximum over the EMB, and a clear summer maximum in the WMB, although in this later region the recirculations of aged air masses play an important role. Furthermore, a marked seasonal trend is still evident when subtracting the African dust load. This is characterised by a high summer maximum (driven by low precipitation, high insolation) and a winter minimum (intense synoptic winds).Important inter-annual variations in the dust contribution are detected, more evident in the southern sites. These differences are generally associated with the occurrence of extreme dust events. Generally, the years with higher dust contributions over the EMB correspond with lower contributions over the WMB, and vice versa.The characterization of individual particles, collected in both basins during African dust events, by scanning electron microscopy reveals only slight differences between them. This fact probably reflects the high degree of mixture of mineral dust from different sources before the transport towards the receptor sites.     

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.     

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

ABSTRACT

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

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