Estimating the frequency distributions of particulate matter and their metal elements in a temple

Air quality inside Asian temples is typically poor because of the burning of incense. This study measured and analyzed concentrations of fine (PM2.5) and coarse (PM2.5-10) particulate matter and their metal elements inside a temple in central Taiwan. Experimental results showed that the concentrations of metals Cd, Ni, Pb, and Cr inside the temple were higher than those at rural, suburban, urban, and industrial areas in other studies. Three theoretical parent distributions (lognormal, Weibull, and gamma) were used to fit the measured data. The lognormal distribution was the most appropriate distribution for representing frequency distributions of PM10, PM2.5, and their metal elements. Furthermore, the central limit theorem, H-statistic-based scheme, and parametric and nonparametric bootstrap methods were used to estimate confidence intervals for mean pollutant concentrations. The estimated upper confidence limits (UCLs) of means between different methods were very consistent, because the sample coefficient of variation (CV) was < 1. When the sample CV was > 1, the UCL based on H-statistical method tended to overestimate the UCLs when compared with other methods. Confidence intervals for pollutant concentrations at different percentiles were evaluated using parametric and nonparametric bootstrap methods. The probabilities of pollutants exceeding a critical concentration were also calculated.     

Atmospheric lead concentration distribution in Northern Taiwan

Atmospheric lead concentrations were measured randomly, approximately once per week, at five traffic sites in northern Taiwan from September 1994 to May 1995. Three types of theoretical distributions, lognormal, Weibull and gamma were selected to fit the frequency distribution of the measured lead concentration. Four goodness-of-fit criteria were used to judge which theoretical distribution is the most appropriate to represent the frequency distributions of atmospheric lead.The results show that atmospheric lead concentrations in total suspended particulates fit the lognormal distribution reasonably well in northern Taiwan. The intervals of fitted theoretical cumulative frequency distributions (CFDs) can successfully contain the measured data when the population mean is estimated with a 95% confidence interval. In addition, atmospheric lead concentration exceeding a critical concentration is also predicted from the fitted theoretical CFDs.     

Estimating the Frequency Distributions of Particulate Matter and Their Metal Elements in a Temple

Abstract

Air quality inside Asian temples is typically poor because of the burning of incense. This study measured and analyzed concentrations of fine (PM_2.5) and coarse (PM_2.5–10) particulate matter and their metal elements inside a temple in central Taiwan. Experimental results showed that the concentrations of metals Cd, Ni, Pb, and Cr inside the temple were higher than those at rural, suburban, urban, and industrial areas in other studies. Three theoretical parent distributions (lognormal, Weibull, and gamma) were used to fit the measured data. The lognormal distribution was the most appropriate distribution for representing frequency distributions of PM₁₀, PM_2.5, and their metal elements.

Furthermore, the central limit theorem, H-statistic-based scheme, and parametric and nonparametric bootstrap methods were used to estimate confidence intervals for mean pollutant concentrations. The estimated upper confidence limits (UCLs) of means between different methods were very consistent, because the sample coefficient of variation (CV) was <1. When the sample CV was >1, the UCL based on H-statistical method tended to overestimate the UCLs when compared with other methods. Confidence intervals for pollutant concentrations at different percentiles were evaluated using parametric and nonparametric bootstrap methods. The probabilities of pollutants exceeding a critical concentration were also calculated.     

Comparisons of statistical characteristic of air pollutants in Taiwan by frequency distribution

The lognormal, Weibull, and type V Pearson distributions were selected to fit the concentration frequency distributions of particulate matter with an aerodynamic diameter of < or = 10 microm (PM10) and SO2 in the Taiwan area. Air quality data from three stations, Hsin-Chu, Shalu, and Gain-Jin, were fitted with three distributions and compared with the measured data. The parameters of unimodal and bimodal fitted distributions were obtained by the methods of maximum likelihood and nonlinear least squares, respectively. Moreover, the root mean square error (RMSE), index of agreement (d), and Kolmogorov-Smirnov (K-S) test were used as criteria to judge the goodness-of-fit of these three distributions. These results show that the frequency distributions of PM10 concentration at the Hsin-Chu and Shalu stations are unimodal, but the distribution at Gain-Jin is bimodal. The distribution type of PM10 concentration varied greatly in different areas and could be influenced by local meteorological conditions. For SO2 concentration distribution, the distributions were all unimodal. The results also show that the lognormal distribution is the more appropriate to represent the PM10 distribution, while the Weibull and lognormal distributions are more suitable to represent the SO2 distribution. Moreover, the days exceeding the air quality standard (AQS) (PM10 > 125 microg/ m3) for the Hsin-Chu, Shalu, and Gain-Jin stations in the coming year are successfully predicted by the theoretic distributions.     

A study of polycyclic aromatic hydrocarbons concentrations and source identifications by methods of diagnostic ratio and principal component analysis at Taichung chemical Harbor near Taiwan Strait

Fine (PM(2.5)) and Coarse (PM(2.5-10)) particulates concentrations of ambient air particle-bound polycyclic aromatic hydrocarbons (PAHs) were measured simultaneously from February 2004 to January 2005 at the Taichung Harbor (TH) sampling site near Taiwan of central Taiwan. Particle-bound polycyclic aromatic hydrocarbons (PAHs) were collected on quartz filters, the collected sample used soxhlet analytical method extracted with a dichloromethane (DCM)/n-hexane mixture (50/50, v/v) for 24h, and then the extracts were subjected to gas chromatography-mass spectrometric (GC-MS) analysis. The results indicated that vehicle emissions, coal combustion, incomplete combustion and pyrolysis of fuel and oil burning were the main source of PAHs near Taiwan Strait of central Taiwan. Diagnostic ratio and principal component analysis (PCA) were also used to characterize and identify PAHs emission source in this study.     

Mass-size distributions of particulate sulfate, nitrate, and ammonium in a particulate matter nonattainment region in southern Taiwan

Concentrations and distributions of three major water-soluble ion species (sulfate, nitrate, and ammonium) contained in ambient particles were measured at three sampling sites in the Kao-ping ambient air quality basin, Taiwan. Ambient particulate matter (PM) samples were collected in a Micro-orifice Uniform Deposit Impactor from February to July 2003 and were analyzed for water-soluble ion species with an ion chromatograph. The PM1/ PM2.5 and PM1/PM10 concentration ratios at the emission source site were 0.73 and 0.53 and were higher than those (0.68 and 0.48) at the background site because there are more combustion sources (i.e., industrial boilers and traffic) around the emission source site. Mass-size distributions of PM NO3- were found in both the fine and coarse modes. SO4(2-)and NH4+ were found in the fine particle mode (PM2.5), with significant fractions of submicron particles (PM1). The source site had higher PM1/PM10(79, 42, and 90%) and PM1/PM2.5 concentration ratios (90, 58, and 93%) for the three major inorganic secondary aerosol components (SO4(2-), NO3-, and NH4+) than the receptor site (65, 27, and 65% for PM1/PM10, 69, 51, and 70% for PM1/PM2.5. Results obtained in this study indicate that the PM1 (submicron aerosol particles) fraction plays an important role in the ambient atmosphere at both emission source and receptor sites. Further studies regarding the origin and formation of ambient secondary aerosols are planned.     

Road dust resuspension in the vicinity of limestone quarries in Jordan

Many areas in Jordan suffer from elevated levels of coarse particulate matter (PM10). One potentially significant source of the observed PM is the resuspension of road dust in the vicinity of limestone quarries. To obtain data to assess the impact from this source, PM10 road dust resuspension factors near Abusiiah, a town to the north east of Amman surrounded by many quarries and brick factories, were measured. Measurements included PM10 mass, particle size distributions, wind speed, and wind direction. The results showed that PM10 concentrations could be as high as 600 microg/m3, and most of the airborne PM is in the coarse fraction. Loading trucks play a major role in resuspending road dust, with an observed PM10 emission rate of >6000 mg/km.     

Estimation of ambient PM2.5 concentrations in Maryland and verification by measured values

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 microm in aerodynamic diameter (PM23), but did have annual ambient data for PM smaller than 10 microm (PM10) at 24 sites. The PM10 data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM2.5 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 PM2.5 concentrations at the 24 PM10 monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM2.5 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 PM2.5 NAAQS of 15 microg/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 PM2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM2.5 across central Maryland.     

Assessment of influential range and characteristics of fugitive dust in limestone extraction processes

Fugitive dust emission from limestone extraction areas is a significant pollution source. The cracking operation in limestone extraction areas easily causes high total suspended particulate (TSP) concentrations in the atmosphere, occasionally exceeding the 1-hr national emission standard of Taiwan (500 microg/m3). The concentration and size distribution were measured at different distances (0.05-15 km) in the extraction areas. The highest hourly concentrations of TSP, PM10 (suspended particulate matter [PM] smaller than 10 microm), and PM2.5 (suspended PM smaller than 2.5 microm) are 1111, 825, and 236 microg/m3, respectively, during the cracking process. Measurement results obtained from the Micro-Orifice Uniform Deposit Impactor indicated that the mass median aerodynamic diameter is approximately 0.7 microm, with the geometric standard deviation exceeding 7. In addition, the emission factors are 0.143 and 0.211 kg/t for both vertical well and stair extraction operations, respectively. Experimental results demonstrate that the corresponding TSP control efficiencies for spraying water, planting grass, setting short walls, paving gravel roads, and establishing vertical well transportation are approximately 55, 50, 44, 22, and 30%, respectively. Furthermore, the PM10 control efficiencies are approximately 45, 41, 54, 35, and 30%, respectively, whereas the PM2.5 control efficiencies are roughly 23, 31, 15, 11, and 10%, individually.     

Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Identification and chemical characterization of industrial particulate matter sources in southwest Spain

A detailed physical and chemical characterization of coarse particulate matter (PM10) and fine particulate matter (PM2.5) in the city of Huelva (in Southwestern Spain) was carried out during 2001 and 2002. To identify the major emission sources with a significant influence on PM10 and PM2.5, a methodology was developed based on the combination of: (1) real-time measurements of levels of PM10, PM2.5, and very fine particulate matter (PM1); (2) chemical characterization and source apportionment analysis of PM10 and PM2.5; and (3) intensive measurements in field campaigns to characterize the emission plumes of several point sources. Annual means of 37, 19, and 16 microg/m3 were obtained for the study period for PM10, PM2.5, and PM1, respectively. High PM episodes, characterized by a very fine grain size distribution, are frequently detected in Huelva mainly in the winter as the result of the impact of the industrial emission plumes on the city. Chemical analysis showed that PM at Huelva is characterized by high PO4(3-) and As levels, as expected from the industrial activities. Source apportionment analyses identified a crustal source (36% of PM10 and 31% of PM2.5); a traffic-related source (33% of PM10 and 29% of PM2.5), and a marine aerosol contribution (only in PM10, 4%). In addition, two industrial emission sources were identified in PM10 and PM2.5: (1) a petrochemical source, 13% in PM10 and 8% in PM2.5; and (2) a mixed metallurgical-phosphate source, which accounts for 11-12% of PM10 and PM2.5. In PM2.5 a secondary source has been also identified, which contributed to 17% of the mass. A complete characterization of industrial emission plumes during their impact on the ground allowed for the identification of tracer species for specific point sources, such as petrochemical, metallurgic, and fertilizer and phosphate production industries.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 4. A Three-Parameter Averaging-Time Model

Urban air pollutant concentration data often tend to fit a two-parameter averaging-time model having three characteristics: (1) pollutant concentrations are (two-parameter) lognormally distributed for all averaging times; (2) median concentrations are proportional to averaging time raised to an exponent; and (3) maximum concentrations are approximately inversely proportional to averaging time raised to an exponent. Concentration data obtained near many isolated point sources and in some urban areas often do not fit a two-parameter lognormal distribution. An increment (either positive or negative) can be added to each such concentration in order to fit the data instead to a three-parameter lognormal distribution. This increment has been incorporated as the third parameter in a new three-parameter averaging-time model that can be used in both point-source and urban settings. Examples show how this new model can be used to analyze SO₂ concentration data obtained near a point source to determine the degree of emission reduction needed to achieve the national ambient air quality standards.     

Modeling the benefits of power plant emission controls in Massachusetts

Older fossil-fueled power plants provide a significant portion of emissions of criteria air pollutants in the United States, in part because these facilities are not required to meet the same emission standards as new sources under the Clean Air Act. Pending regulations for older power plants need information about any potential public health benefits of emission reductions, which can be estimated by combining emissions information, dispersion modeling, and epidemiologic evidence. In this article, we develop an analytical modeling framework that can evaluate health benefits of emission controls, and we apply our model to two power plants in Massachusetts. Using the CALPUFF atmospheric dispersion model, we estimate that use of Best Available Control Technology (BACT) for NOx and SO2 would lead to maximum annual average secondary particulate matter (PM) concentration reductions of 0.2 microg/m3. When we combine concentration reductions with current health evidence, our central estimate is that the secondary PM reductions from these two power plants would avert 70 deaths per year in a population of 33 million individuals. Although benefit estimates could differ substantially with different interpretations of the health literature, parametric perturbations within CALPUFF and other simple model changes have relatively small impacts from an aggregate risk perspective. While further analysis would be required to reduce uncertainties and expand on our analytical model, our framework can help decision-makers evaluate the magnitude and distribution of benefits under different control scenarios.     

Multi-criteria analysis for PM10 planning

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source–receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source–receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.     

Continuous monitoring of particle emissions during showering

Particle formation from showering may be attributed to dissolved mineral aerosols remaining after evaporation of micron-sized satellite droplets produced by the showerhead or from splashing of larger shower water droplets on surfaces. Duplicate continuous particle monitors measured particle size distributions in a ventilated residential bathroom under various showering conditions, using a full-size mannequin in the shower to simulate splashing effects during showering. Particle mass concentrations were estimated from measured shower particle number densities and used to develop emission factors for inhalable particles. Emission source strengths of 2.7-41.3 microg/ m3/min were estimated under the various test conditions using residential tap water in Columbus, OH. Calculated fine particulate matter (PM2.5) concentrations in the bathroom reached several hundred micrograms per cubic meter; calculated coarse particulate matter (PM10) levels approached 1000 microg/m3. Rates of particle formation tended to be highest for coarse shower spray settings with direct impact on the mannequin. No consistent effects of water temperature, water pressure, or spray setting on overall emission rates were apparent, although water temperature and spray setting did have an effect when varied within a single shower sampling run. Salt solutions were injected into the source water during some tests to assess the effects of total dissolved solids on particle emission rates. Injection of salts was shown to increase the PM2.5 particle formation rate by approximately one third, on average, for a doubling in tap water-dissolved solids content; PM10 source strengths approximately doubled under these conditions, because very few particles >10 microm were formed.     

Air quality impacts of distributed energy resources implemented in the northeastern United States

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 (PM2.5) concentrations reach 3 microg/m3 and are located off the coast of New Jersey and New York. The main contribution to decreased PM2.5 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.     

The sensitivity of PM2.5 source-receptor relationships to atmospheric chemistry and transport in a three-dimensional air quality model

Air quality model simulations constitute an effective approach to developing source-receptor relationships (so-called transfer coefficients in the risk analysis framework) because a significant fraction of particulate matter (particularly PM2.5) is secondary (i.e., formed in the atmosphere) and, therefore, depends on the atmospheric chemistry of the airshed. In this study, we have used a comprehensive three-dimensional air quality model for PM2.5 (SAQM-AERO) to compare three approaches to generating episodic transfer coefficients for several source regions in the Los Angeles Basin. First, transfer coefficients were developed by conducting PM2.5 SAQM-AERO simulations with reduced emissions of one of four precursors (i.e., primary PM, sulfur dioxide (SO2), oxides of nitrogen (NOx), and volatile organic compounds) from each source region. Next, we calculated transfer coefficients using two other methods: (1) a simplified chemistry for PM2.5 formation, and (2) simplifying assumptions on transport using information limited to basin-wide emission reductions. Transfer coefficients obtained with the simplified chemistry were similar to those obtained with the comprehensive model for VOC emission changes but differed for NOx and SOz emission changes. The differences were due to the parameterization of the rates of secondary PM formation in the simplified chemistry. In 90% of the cases, transfer coefficients estimated using only basin-wide information were within a factor of two of those obtained with the explicit source-receptor simulations conducted with the comprehensive model. The best agreement was obtained for VOC emission changes; poor agreement was obtained for primary PM2.5.     

The study of TSP, PM(2.5-10) and PM2.5 during Taiwan Chi-Chi Earthquake in the traffic site of central Taiwan, Taichung

Ambient particle concentration was taken on the traffic sampling site over the Chung-Chi Road over bridge (CCROB) in front of Hungkuang Institute of Technology (HKIT). The sampling time was from August 1999 to December 1999. During the sampling period, Taiwan's biggest earthquake in more than a century registered 7.3 on the Richter scale (Taiwan Chi-Chi Earthquake). Besides, there were more than 20,000 aftershocks that followed the Taiwan Chi-Chi Earthquake within three months. Thus, the PM2.5, PM(2.5-10) particle concentrations were also collected then and compared with total suspended particle (TSP) in this study. The average PM(2.5-10), PM2.5 and TSP concentrations are 24.6, 58.0 and 106 microg/m3, respectively, after the Taiwan Chi-Chi Earthquake. The average TSP concentrations before and after Taiwan Chi-Chi Earthquake were 70 and 127 microg/m3, respectively. It is clearly shown that the average concentration of TSP after Taiwan Chi-Chi Earthquake was about 1.8 times as that of TSP concentration before Taiwan Chi-Chi Earthquake in the traffic site of central Taiwan. And the ratios of PM2.5/PM(2.5-10), PM2.5/PM10 and PM2.5/TSP are 2.2%, 67.2%, 38.9%, respectively. The results also indicated about Chi-Chi fine particle concentration (PM25) and the TSP increases in the traffic site of central Taiwan after Taiwan Chi-Chi Earthquake.     

Fugitive dust emission source profiles and assessment of selected control strategies for particulate matter at gravel processing sites in Taiwan

Particles emitted from gravel processing sites are one contributor to worsening air quality in Taiwan. Major pollution sources at gravel processing sites include gravel and sand piles, unpaved roads, material crushers, and bare ground. This study analyzed fugitive dust emission characteristics at each pollution source using several types of particle samplers, including total suspended particulates (TSP), suspended particulate (PM10), fine suspended particulate (PM2.5), particulate sizer, and dust-fall collectors. Furthermore, silt content and moisture in the gravel were measured to develop particulate emission factors. The results showed that TSP (< 100 microm) concentrations at the boundary of gravel sites ranged from 280 to 1290 microg/m3, which clearly exceeds the Taiwan hourly air quality standard of 500 microg/m3. Moreover, PM10 concentrations, ranging from 135 to 550 microg/m3, were also above the daily air quality standard of 125 microg/m3 and approximately 1.2 and 1.5 times the PM2.5 concentrations, ranging from 105 to 470 microg/m3. The size distribution analysis reveals that mass mean diameter and geometric standard deviation ranged from 3.2 to 5.7 microm and from 2.82 to 5.51, respectively. In this study, spraying surfactant was the most effective control strategy to abate windblown dust from unpaved roads, having a control efficiency of approximately 93%, which is significantly higher than using paved road strategies with a control efficiency of approximately 45%. For paved roads, wet suppression provided the best dust control efficiencies ranging from 50 to 83%. Re-vegetation of disturbed ground had dust control efficiencies ranging from 48 to 64%.     

Influence of sea-land breezes on the tempospatial distribution of atmospheric aerosols over coastal region

The influence of sea-land breezes (SLBs) on the spatial distribution and temporal variation of particulate matter (PM) in the atmosphere was investigated over coastal Taiwan. PM was simultaneously sampled at inland and offshore locations during three intensive sampling periods. The intensive PM sampling protocol was continuously conducted over a 48-hr period. During this time, PM2.5 and PM(2.5-10) (PM with aerodynamic diameters < 2.5 microm and between 2.5 and 10 microm, respectively) were simultaneously measured with dichotomous samplers at four sites (two inland and two offshore sites) and PM10 (PM with aerodynamic diameters < or =10 microm) was measured with beta-ray monitors at these same 4 sites and at 10 sites of the Taiwan Air Quality Monitoring Network. PM sampling on a mobile air quality monitoring boat was further conducted along the coastline to collect offshore PM using a beta-ray monitor and a dichotomous sampler. Data obtained from the inland sites (n=12) and offshore sites (n=2) were applied to plot the PM10 concentration contour using Surfer software. This study also used a three-dimensional meteorological model (Pennsylvania State University/National Center for Atmospheric Research Meteorological Model 5) and the Comprehensive Air Quality Model with Extensions to simulate surface wind fields and spatial distribution of PM10 over the coastal region during the intensive sampling periods. Spatial distribution of PM10 concentration was further used in investigating the influence of SLBs on the transport of PM10 over the coastal region. Field measurement and model simulation results showed that PM10 was transported back and forth across the coastline. In particular, a high PM10 concentration was observed at the inland sites during the day because of sea breezes, whereas a high PM10 concentration was detected offshore at night because of land breezes. This study revealed that the accumulation of PM in the near-ocean region because of SLBs influenced the tempospatial distribution of PM10 over the coastal region.