Computer Simulations of Particle Deposition in the Developing Human Lung

ABSTRACT

An age-dependent theoretical model has been developed to predict PM dosimetry in children's lungs. Computer codes have been written that describe the dimensions of individual airways and the geometry of branching airway networks within developing lungs. Breathing parameters have also been formulated as functions of subject age. Our computer simulations suggest that particle size, age, and activity level markedly affect deposition patterns of inhaled air pollutants. For example, the predicted lung deposition fraction is 38% in an adult but is nearly twice as high (73%) in a 7-month-old for 2-um particles inhaled during heavy breathing. Tracheobronchial (TB) and pulmonary (or alveolated airways, P) deposition patterns may also be calculated using the model. Due to different clearance processes in the TB and P airways (i.e., mucociliary transport and macrophage action, respectively), the determination of compartmental dose is important for PM risk assessment analyses. Furthermore, the results of such simulations may aid in the setting of regulatory standards for air pollutants, as the data provide a scientific basis for estimating dose delivered to a designated sensitive subpopulation (children).     

Designing Optimal Strategies to Attain the New U.S. Particulate Matter Standards: Some Initial Concepts

ABSTRACT

This paper proposes that a fundamental principle for designing optimal strategies to attain new U.S. particulate matter (PM) standards be minimization of community and susceptible group exposure to, and inhaled dosage of, ambient PM. Properly done, such minimization maximizes human health risk reduction. To illustrate implementation of such a principle, an initial prototype model, PM Exposure (PMEX), is described that calculates PM exposure and inhaled dosage as figures-of-merit for control strategy optimization. The model accounts for age-occupation and susceptible group activity patterns, indoor-outdoor concentration differences, and geographical location. Modeling results are presented for a hypothetical example, apportioning inhaled dosage among different classes of sources, under alternative assumptions about the relative potency of different PM species categories. The results, while preliminary, demonstrate that conclusions about source class contribution based on inhaled dosage can be appreciably different than those based on ambient air measurements or emission inventories.     

Estimating the resuspension rate and residence time of indoor particles

Resuspension experiments were performed in a single-family residence. Resuspension by human activity was found to elevate the mass concentration of indoor particulate matter with an aerodynamic diameter less than 10 microm (PM10) an average of 2.5 times as high as the background level. As summarized from 14 experiments, the average estimated PM10 resuspension rate by a person walking on a carpeted floor was (1.4 +/- 0.6) x 10(-4) hr(-1). The estimated residence time for PM in the indoor air following resuspension was less than 2 hr for PM10 and less than 3 hr for 2-microm tracer particles. However, experimental results show that the 2-microm tracer particles stayed in the combined indoor air and surface compartments much longer (>19 days). Using a two-compartment model to simulate a regular deposition and resuspension cycle by normal human activity (e.g., walking and sitting on furniture), we estimated residence time for 2-microm conservative particulate pollutants to be more than 7 decades without vacuum cleaning, and months if vacuum cleaning was done once per week. This finding supports the observed long residence time of persistent organic pollutants in indoor environments. This study introduces a method to evaluate the particle resuspension rate from semicontinuous concentration data of particulate matter (PM). It reveals that resuspension and subsequent exfiltration does not strongly affect the overall residence time of PM pollutants when compared with surface cleaning. However, resuspension substantially increases PM concentration, and thus increases short-term inhalation exposure to indoor PM pollutants.     

Comparison of computer simulations of total lung deposition to human subject data in healthy test subjects

A mathematical model was used to predict the deposition fractions (DF) of PM within human lungs. Simulations using this computer model were previously validated with human subject data and were used as a control case. Human intersubject variation was accounted for by scaling the base lung morphology dimensions based on measured functional residual capacity (FRC) values. Simulations were performed for both controlled breathing (tidal volumes [VT] of 500 and 1000 mL, respiratory times [T] from 2 to 8 sec) and spontaneous breathing conditions. Particle sizes ranged from 1 to 5 microns. The deposition predicted from the computer model compared favorably with the experimental data. For example, when VT = 1000 mL and T = 2 sec, the error was 1.5%. The errors were slightly higher for smaller tidal volumes. Because the computer model is deterministic (i.e., derived from first principles of physics), the model can be used to predict deposition fractions for a range of situations (i.e., for different ventilatory parameters and particle sizes) for which data are not available. Now that the model has been validated, it may be applied to risk assessment efforts to estimate the inhalation hazards of airborne pollutants.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

Comparison of Computer Simulations of Total Lung Deposition to Human Subject Data in Healthy Test Subjects

ABSTRACT

A mathematical model was used to predict the deposition fractions (DF) of PM within human lungs. Simulations using this computer model were previously validated with human subject data and were used as a control case. Human intersubject variation was accounted for by scaling the base lung morphology dimensions based on measured functional residual capacity (FRC) values. Simulations were performed for both controlled breathing (tidal volumes [V_T] of 500 and 1000 mL, respiratory times [T] from 2 to 8 sec) and spontaneous breathing conditions. Particle sizes ranged from 1 to 5 um. The deposition predicted from the computer model compared favorably with the experimental data. For example, when V_T = 1000 mL and T = 2 sec, the error was 1.5%. The errors were slightly higher for smaller tidal volumes. Because the computer model is deterministic (i.e., derived from first principles of physics), the model can be used to predict deposition fractions for a range of situations (i.e., for different ventilatory parameters and particle sizes) for which data are not available. Now that the model has been validated, it may be applied to risk assessment efforts to estimate the inhalation hazards of airborne pollutants.     

Review of Singapore's air quality and greenhouse gas emissions: current situation and opportunities

Singapore has many environmental accomplishments to its credit. Accessible data on air quality indicates that all criteria pollutants satisfy both U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality standards and guidelines, respectively. The exception is PM2.5 (particles with an aerodynamic diameter < or = 2.5 microm), which is not currently considered a criteria pollutant in Singapore but may potentially be the major local air pollution problem and cause for health concern. Levels of other airborne pollutants as well as their physical and chemical processes associated with local formation, transformation, dispersion, and deposition are not known. According to available emission inventories, Singapore contribution to the total atmospheric pollution and carbon budget at the regional and global scales is small. Emissions per unit gross domestic product (GDP) are low compared with other countries, although Singapore's per-capita GDP and per-capita emissions are among the highest in the world. Some information is available on health effects, but the impacts on the ecosystem and the complex interactions of air pollution and climate change at a regional level are also unknown. This article reviews existing available information on atmospheric pollution and greenhouse gas emissions and proposes a multipollutant approach to greenhouse gas mitigation and local air quality. Singapore, by reducing its per-capita emissions, increasing the availability of information (e.g., through regularly publishing hourly and/or daily PM2.5 concentrations) and developing a research agenda in this area, would likely be seen to be a model of a high-density, livable, and sustainable city in Southeast Asia and other tropical regions worldwide.     

湍流环形通道热泳脱除可吸入颗粒物技术研究

湍流中PM 2.5粒子的热泳沉积是国际上研究热门课题.但目前单纯热泳沉积效率也不过20%左右.依据热泳基本原理,设计了一种新型湍流方环形双壁冷却式通道.计算表明,该类型通道比一般单管通道有着较高的可吸入颗粒物脱除效率.同时,利用湍流的沉积效率,加上热泳沉积效率,可以达到较高的总泳沉积效率.通过结构设计,可以提高可吸入颗粒物的脱除效率,是值得进一步探索的新路子.     

Characterization of spatially homogeneous regions based on temporal patterns of fine particulate matter in the continental United States

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.     

Exposure to particulate matter in traffic: A comparison of cyclists and car passengers

Emerging evidence suggests that short episodes of high exposure to air pollution occur while commuting. These events can result in potentially adverse health effects. We present a quantification of the exposure of car passengers and cyclists to particulate matter (PM). We have simultaneously measured concentrations (PNC, PM2.5 and PM10) and ventilatory parameters (minute ventilation (VE), breathing frequency and tidal volume) in three Belgian locations (Brussels, Louvain-la-Neuve and Mol) for 55 persons (38 male and 17 female). Subjects were first driven by car and then cycled along identical routes in a pairwise design. Concentrations and lung deposition of PNC and PM mass were compared between biking trips and car trips.Mean bicycle/car ratios for PNC and PM are close to 1 and rarely significant. The size and magnitude of the differences in concentrations depend on the location which confirms similar inconsistencies reported in literature. On the other hand, the results from this study demonstrate that bicycle/car differences for inhaled quantities and lung deposited dose are large and consistent across locations. These differences are caused by increased VE in cyclists which significantly increases their exposure to traffic exhaust. The VE while riding a bicycle is 4.3 times higher compared to car passengers. This aspect has been ignored or severely underestimated in previous studies. Integrated health risk evaluations of transport modes or cycling policies should therefore use exposure estimates rather than concentrations.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Codependencies of reactive air toxic and criteria pollutants on emission reductions

It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM2.5), 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, PM2.5, 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 PM2.5 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 PM2.5, 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 PM2.5.     

Air quality modeling for effective environmental management in the mining region

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM₁₀, PM_2.5, TSP, NO₂, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM_2.5, from 0.71 to 0.82 for PM₁₀, and from 0.71 to 0.89 for NO₂. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM_2.5, PM₁₀, TSP, and NO₂) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.     

Particulate matter in the cultivation area may contaminate leafy vegetables with heavy metals above safe levels in Korea

Environmental Science and Pollution Research - Among air pollutants, particulate matter (PM) has been identified as a major cause of environmental pollutants due to the advancement of industrial...     

湍流环形通道热泳脱除可吸入颗粒物技术研究

湍流中PM2．5粒子的热泳沉积是国际上研究热门课题。但目前单纯热泳沉积效率也不过20％左右。依据热泳基本原理，设计了一种新型湍流方环形双壁冷却式通道。计算表明，该类型通道比一般单管通道有着较高的可吸入颗粒物脱除效率。同时，利用湍流的沉积效率，加上热泳沉积效率。可以达到较高的总泳沉积效率。通过结构设计，可以提高可吸入颗粒物的脱除效率，是值得进一步探索的新路子。     

Monitoring and modelling of biosphere/atmosphere exchange of gases and aerosols in Europe

Monitoring and modelling of deposition of air pollutants is essential to develop and evaluate policies to abate the effects related to air pollution and to determine the losses of pollutants from the atmosphere. Techniques for monitoring wet deposition fluxes are widely applied. A recent intercomparison experiment, however, showed that the uncertainty in wet deposition is relatively high, up to 40%, apart from the fact that most samplers are biased because of a dry deposition contribution. Wet deposition amounts to about 80% of the total deposition in Europe with a range of 10-90% and uncertainty should therefore be decreased. During recent years the monitoring of dry deposition has become possible. Three sites have been operational for 5 years. The data are useful for model development, but also for model evaluation and monitoring of progress in policy. Data show a decline in SO(2) dry deposition, whereas nitrogen deposition remained constant. Furthermore, surface affinities for pollutants changed leading to changes in deposition. Deposition models have been further developed and tested with dry deposition measurements and total deposition measurements on forests as derived from throughfall data. The comparison is reasonable given the measurement uncertainties. Progress in ozone surface exchange modelling and monitoring shows that stomatal uptake can be quantified with reasonable accuracy, but external surface uptake yields highest uncertainty.     

Extending the Kolmogorov-Zurbenko filter: application to ozone, particulate matter, and meteorological trends

Tropospheric ozone (O3) and particulate matter (PM) are pollutants of great concern to air quality managers. Federal standards for these pollutants have been promulgated in recent years because of the known adverse effects of the pollutants on human health, the environment, and visibility. Local meteorological conditions exert a strong influence over day-to-day variations in pollutant concentrations; therefore, the meteorological signal must be removed in order for air quality planners and managers to examine underlying emissions-related trends and make better air quality management decisions for the future. Although the Kolmogorov-Zurbenko (KZ) filter has been widely used for this type of trend separation in O3 studies in the eastern United States, this article aims to extend the method in three key ways. First, whereas the KZ filter is known as a useful tool for O3 analysis, this study also evaluates its effectiveness when applied to PM. Second, the method was applied to Tucson, AZ, a city in the semi-arid southwestern United States (Southwest), to evaluate the appropriateness of the method in a region with weaker synoptic weather controls on air quality than the eastern United States. Third, additional forms of output were developed and tailored to be more applicable to decision-makers' needs through a partnership between academic researchers and air quality planners and managers. Results of the study indicate that the KZ filter is a useful method for examining emissions-related PM trends, resulting in small, but potentially significant, differences after adjustment. For the Tucson situation with weaker synoptic controls, the KZ method identified mixing height as a more important variable than has been found in other cities.     

Factors affecting the concentrations of PM10 in central Taiwan

In this study, the synoptic weather types that have high probability and low probability of producing PM10 episode are referred to as HPE and LPE, respectively. Multiple linear regressions analysis showed that NO2 was the most important contributor (35.61%) to the concentrations of PM10 for HPE weather. For LPE weather, the season factor had the greatest contribution (48.11%) to the concentrations of PM10. Using the correlation coefficients between the concentrations of PM10 and SO2 or NO2 on HPE and LPE to calculate the increase of PM10 from LPE to HPE, we found that the increase of PM10 owing to the increase of SO2 and NO2 from LPE to HPE was 12.93microg/m3 which was about 51% of the total amount of PM10 increased from LPE to HPE. Results of factor analysis showed that the first component could be attributed to the result of local pollution especially for the weather patterns of types P3 and P6, while the secondary component for the weather patterns of types P1 and P4 can be attributed to the long-range transport of SO2 pollutants from China.     

Monitoring trace elements generated by automobiles: air pollutants with possible health impacts

Major transformations in the environmental composition are principally attributable to the combustion of fuels by automobiles. Motorized gasoline-powered two-stroke auto-rickshaws (TSA) and compressed natural gas (CNG)-powered four-stroke auto-rickshaws (FSA) are potential source of air pollution in south Asia and produce toxic amount of particulate matter (PM) to the environment. In this study, we attempted to characterize elemental pollutants from the PM of TSA and FSA using proton-induced X-ray emission (PIXE) analysis. The observations of the existing investigation recognized significant increase in Al (P?<?0.05), P (P?<?0.01), and Zn (P?<?0.01) from the PM samples of FSA. In addition, the concentrations of Cu, Fe, K, Mg, Na and S were also observed exceeding the recommended National Institute for Environmental Studies limits. On the contrary, increased concentration of Sr and V were observed in the PM samples from TSA. It is generally believed that FSA generates smaller amount of PM but data obtained from FSA are clearly describing that emissions from FSA comprised potentially more toxic substances than TSA. The current research is specific to metropolitan population and has evidently revealed an inconsistent burden of exposure to air pollutants engendered by FSA in urban communities, which could lead to the disruption of several biological activities and may cause severe damage to entire ecological system.     

A statistical model for FEV1 response to arbitrary dynamic ozone exposure conditions

Lung function response to inhaled ozone at ambient air pollution levels is known to be a function of ozone concentration, exposure duration, and minute ventilation. Most data-driven exposure-response models address exposures under static condition (i.e., with a constant ozone concentration and exercise pattern). Such models are simplifications, as both ambient ozone concentrations and normal human activity patterns change with time. The purpose of this study was to develop a dynamic model of response with the advantages of a statistical model (a relatively simple structure with few parameters). A previously proposed mechanistic model for changes in specific airways resistance was adapted to describe the percent change in forced expiratory volume in one second (FEV1). This model was then reduced using the fit to three existing exposure-response data sets as criterion. The resulting model consists of a single linear differential equation together with an algebraic logistic equation. Under restricted static conditions the model reduces to a logistic model presented earlier by the authors.