Estimating the emission source reduction of PM10 in central Taiwan

Three theoretical parent frequency distributions; lognormal, Weibull and gamma were used to fit the complete set of PM10 data in central Taiwan. The gamma distribution is the best one to represent the performance of high PM10 concentrations. However, the parent distribution sometimes diverges in predicting the high PM10 concentrations. Therefore, two predicting methods, Method I: two-parameter exponential distribution and Method II: asymptotic distribution of extreme value, were used to fit the high PM10 concentration distributions more correctly. The results fitted by the two-parameter exponential distribution are better matched with the actual high PM10 data than that by the parent distributions. Both of the predicting methods can successfully predict the return period and exceedances over a critical concentration in the future year. Moreover, the estimated emission source reductions of PM10 required to meet the air quality standard by Method I and Method II are very close. The estimated emission source reductions of PM10 range from 34% to 48% in central Taiwan.     

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

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.     

Particle size distribution and anion content at a traffic site in Sha-Lu, Taiwan.

Ambient air particle concentrations were sampled by two total suspended particle (TSP) samplers, PM10/PM2.5 specific sampler and micro-orifice uniform deposit impactor (MOUDI) during July-October 2000 at a traffic sampling site in central Taiwan. The average TSP concentration (194 microg/m3) was about a factor of two higher than that of the fraction <2.5 microm (93.2 microg/m3). The mean level of the fraction <10 microm collected by MOUDI (93.2 microg/m3) was about 1 1/2 times higher than that of the size class <2.5 microm (43.8 microg/m3). Furthermore, this fraction showed a certain correlation with the TSP concentration. The particle size distribution was bimodal in the ambient air at the traffic site. The major peaks appear at particle diameters between 0.56-1.0 and 3.2-5.6 microm. The percentages of anions contained in TSP were 0.24% F-, 13.7% Cl, 0.52% Br, 12.0% NO-, 18.9% NO2-, and 54.6% SO2-. The Cl-, NO2-, and NO3- size distributions were all unimodal and the major peaks appeared at 3.2-5.6 microm. The SO2 size distribution was bimodal, with major peaks at 0.32-0.56 and 3.2-5.6.     

Frequency distribution of dust concentration in Barbados as a function of averaging time

Two sets of daily-averaged dust concentration data from Barbados, West Indies, have been analyzed to determine the affect of averaging time, ranging from 1 to 7 days, on the dust concentration frequency distribution. On each of the time scales examined, the frequency distribution is characterized as a bimodal lognormal distribution. The major effects of increasing the averaging are a major reduction in the percentage of the samples represented by the lower of the two modes and a significant increase in the geometric mean concentration of that mode. Consequently, predictions of the distributions on a shorter time scale are likely to substantially underestimate the frequency of low concentration samples.     

Statistical characterization of atmospheric PM10 and PM2.5 concentrations at a non-impacted suburban site of Istanbul, Turkey

Inhalable particulate matter (PM10) has been monitored at several stations by Istanbul Municipality. On the other hand, information about fine fraction aerosols (PM2.5) in Istanbul atmosphere was not reported. In this study, 86 daily aerosol samples were collected between July 2002 and July 2003. The PM10 annual arithmetic mean value of 47.1 microg m(-3), was lower than the Turkish air quality standard of 60 microg m(-3). On the other hand, this value was found higher than the annual European Union air quality PM(10) standard of 40 microg m(-3). Furthermore, the annual mean concentration of PM2.5 20.8 microg m(-3) was found higher than The United States EPA standard of 15 microg m(-3). The statistics and relationships of fine, coarse, and inhalable particles were studied. Cyclic behavior of the monthly average concentrations of PM10 and PM2.5 data were investigated. Several frequency distribution functions were used to fit the measured data. According to Chi-squared and Kolmogorov-Smirnov tests, the frequency distributions of PM2.5 and PM10 data were found to fit Log-logistic functions.     

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.     

西安采暖期PM2.5及其水溶性无机离子的时段分布特征

为了探讨西安市采暖期大气颗粒物PM2.5及其水溶性无机成分的污染水平,于2010年1月4日—2月1日按一天8个时段(每个时段3 h)连续采集PM2.5样品四周,每周更换一次滤膜。结果显示,西安市采暖期PM2.5的质量浓度时段差异较大,呈现明显的双峰分布特征:21:00—24:00时段(147.516μg/m3)和09:00—12:00时段(141.678μg/m3)。4种被测水溶性无机组分总浓度为39.801μg/m3,占PM2.5总浓度的30.5%。SO24-和NO3-是最主要组分,占到4种无机组分的86.2%。各离子间相关分析显示,Cl-只与NO3-有较强的相关性,表明机动车尾气对Cl-有较大的贡献。SO24-和NO3-时段分布规律较为相似,与PM2.5浓度的时段分布特征相反:在PM2.5污染最轻的15:00—18:00时段,SO24-和NO3-的相对含量达到一天中的最高浓度时段,而在PM2.5双峰时段,它们的含量有所降低。     

A study on variations of concentrations of particulate matter with different sizes in Lanzhou,China

Lanzhou is one of the most air-polluted cities in China and in the world, and its primary air pollutant is particulate matter (PM). Different size particulate matter (TSP, PM₁₀, PM_2.5 and PM_1.0) have different sources and affect the environment and human health differently, so it is very important to study the pollutant characteristics of different particles in order to deeply understand the pollution situation of Lanzhou city and establish reasonable preventive countermeasures. TSP, PM₁₀, PM_2.5 and PM_1.0 concentrations were simultaneously measured in Lanzhou to detect the annual and diurnal variations of concentrations of PM with different sizes and possible causes. The main results are as follows: (1) The annual distribution of monthly average concentrations for coarse particles (TSP and PM₁₀) is bimodal with the highest peak in April, which is different from the situation in other cities not affected by sand-dust events. However, the annual distribution for fine particles (PM_2.5 and PM_1.0) is unimodal with the peak in December. This difference between coarse and fine particles indicates that sand-dust events in spring carry much more coarse than fine particles to Lanzhou. This result is supported by the correlation between springtime wind speed and concentrations of PM with different sizes. (2) Under normal conditions (without dust intrusions), the diurnal distribution of coarse particle concentration in Lanzhou is bimodal. However, the distribution is trimodal during dust intrusions in April, with an extra peak in the afternoon. (3) In general, the highest concentration peaks of the diurnal variations for TSP, PM₁₀, PM_2.5 and PM_1.0 occur at about the same time. However, there are obvious differences in the occurrence time of the minimum concentrations among different kinds of PM. The differences in the occurrence time of minima between coarse and fine particles are due to their different diffusion behaviors in the atmospheric boundary layer.     

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.     

On the Evaluation of Predictions from a Gaussian Plume Model

The performance of a CRSTER equivalent Gaussian plume model (CEQM) is examined using data from the EPRI Plume Model Validation study at the Klncaid, Illinois site. Four-way comparisons are made on the ordered statistics or the cumulative frequency distribution (CFD) of maximum hourly observed and predicted concentrations. Using the uniform random distribution and the lognormal random distribution as simple predictive schemes without any physical context, it Is found that the CEQM predicts a concentration CFD which matches the observed CFD significantly closer than the CFD predicted by the uniform random distribution. The two-parameter lognormal random distribution predicts the concentration CFD better than the CEQM over all concentration ranges; however, the CEQM fits the upper range of the concentration distribution better than the lognormal random distribution,, despite the fact that the predictions are generated using dispersion conditions entirely different from those of the observations. The nature of this ergodicity of distribution is probed by exercising CEQM using randomized input based on the observed frequency distributions of the Input parameters instead of feeding the hour-by-hour model input matched by time into CEQM as is customarily done. The exercise of the model by uncoupling the time linkage in model Input has no systematic effect on the predicted cumulative frequency distribution of concentrations. Only at the highest concentration range (99.5% or higher) do the two sets of predictions begin to diverge.     

Characteristics of inhalable particulate matter concentration and size distribution from power plants in China

In this investigation, the collection efficiency of particulate emission control devices (PECDs), particulate matter (PM) emissions, and PM size distribution were determined experimentally at the inlet and outlet of PECDs at five coal-fired power plants. Different boilers, coals, and PECDs are used in these power plants. Measurement in situ was performed by an electrical low-pressure impactor with a sampling system, which consisted of an isokinetic sampler probe, precut cyclone, and two-stage dilution system with a sample line to the instruments. The size distribution was measured over a range from 0.03 to 10 microm. Before and after all of the PECDs, the particle number size distributions display a bimodal distribution. The PM2.5 fraction emitted to atmosphere includes a significant amount of the mass from the coarse particle mode. The controlled and uncontrolled emission factors of total PM, inhalable PM (PM10), and fine PM P(M2.5) were obtained. Electrostatic precipitator (ESP) and baghouse total collection efficiencies are 96.38-99.89% and 99.94%, respectively. The minimum collection efficiency of the ESP and the baghouse both appear in the particle size range of 0.1-1 microm. In this size range, ESP and baghouse collection efficiencies are 85.79-98.6% and 99.54%. Real-time measurement shows that the mass and number concentration of PM10 will be greatly affected by the operating conditions of the PECDs. The number of emitted particles increases with increasing boiler load level because of higher combustion temperature. During test run periods, the data reproducibility is satisfactory.     

A quantitative description of vehicle exhaust particle size distributions in a highway tunnel

During the period May 18-May 22, 1999, a comprehensive study was conducted in the Tuscarora Mountain Tunnel on the Pennsylvania Turnpike to measure real-world motor-vehicle emissions. As part of this study, size distributions of particle emissions were determined using a scanning mobility particle sizer. Each measured size distribution consisted of two modes: a nucleation mode with midpoint diameter less than 20 nm and an accumulation mode with midpoint diameter less than 100 nm. The nucleation and accumulation components in some distributions also exhibited second maxima, which implies that such particle size distributions are superpositions of two particle size distributions. This hypothesis was utilized in fitting the particle size distributions that exhibited second maxima with four lognormal distributions, two for the nucleation mode and two for the accumulation mode. The fitting assumed that the observed particle size distribution was a combination of two bimodal log-normal distributions, one attributed to the heavy-duty diesel (HDD) vehicles and another attributed either to a different class of HDD vehicles or to the light-duty spark ignition vehicles. Based on this method, estimated particle production rates were 1.8 x 10(13) and 2.8 x 10(14) particles/vehicle-km for light-duty spark ignition and HDD vehicles, respectively, which agreed with independently obtained estimates.     

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eski?ehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.     

Characterization of atmospheric PM10 and related chemical species in southern Taiwan during the episode days

The concentrations of atmospheric PM10 on days with episodes of pollution were examined at four different sampling sites (CC, DL, LY, and HK) in southern Taiwan. The related to particulates water-soluble ionic species (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO4(2-)), carbonaceous species (EC and OC) and metallic species (Zn, Ni, Pb, Fe, Mn, Al, Si, V) were also analyzed. On the episode days of this study, the PM10 mass concentration ranged from 155 to 210 microgm(-3), from 150 to 208 microgm(-3), from 182 to 249 microgm(-3), and from 166 to 228 microgm(-3) at CC, DL, LY, and HK, respectively. The results indicate that the dominant water-soluble species were SO4(2-), NO3-, NH4+, and Cl- at the four sampling sites on these days. Moreover, the high sulfate and nitrate conversion values (SOR and NOR) presented herein suggest that secondary formations from SO2 to SO4(2-) and from NO2 to NO3- are present in significant quantities in the atmosphere of southern Taiwan on episode days. In particular, high SOR and NOR verified that both SO4(2-) and NO3- dominated the increase of atmospheric PM10 concentration in southern Taiwan on episode days.     

A physical explanation of the lognormality of pollutant concentrations

Investigators in different environmental fields have reported that the concentrations of various measured substances have frequency distributions that are lognormal, or nearly so. That is, when the logarithms of the observed concentrations are plotted as a frequency distribution, the resulting distribution is approximately normal, or Gaussian, over much of the observed range. Examples include radionuclides in soil, pollutants in ambient air, indoor air quality, trace metals in streams, metals in biological tissue, calcium in human remains. The ubiquity of the lognormal distribution in environmental processes is surprising and has not been adequately explained, since common processes in nature (for example, computation of the mean and the analysis of error) usually give rise to distributions that are normal rather than lognormal. This paper takes the first step toward explaining why lognormal distributions can arise naturally from certain physical processes that are analogous to those found in the environment. In this paper, these processes are treated mathematically, and the results are illustrated in a laboratory beaker experiment that is simulated on the computer.     

Characterization of major chemical components of fine particulate matter in North Carolina

This paper presents measurements of daily sampling of fine particulate matter (PM2.5) and its major chemical components at three urban and one rural locations in North Carolina during 2002. At both urban and rural sites, the major insoluble component of PM2.5 is organic matter, and the major soluble components are sulfate (SO4(2-)), ammonium (NH4(+)), and nitrate (NO3(-)). NH4(+) is neutralized mainly by SO4(2-) rather than by NO3(-), except in winter when SO4(2-) concentration is relatively low, whereas NO3(-) concentration is high. The equivalent ratio of NH4(+) to the sum of SO4(2-) and NO3(-) is < 1, suggesting that SO4(2-) and NO3(-) are not completely neutralized by NH4(+). At both rural and urban sites, SO4(2-) concentration displays a maximum in summer and a minimum in winter, whereas NO3(-) displays an opposite seasonal trend. Mass ratio of NO3(-) to SO4(2-) is consistently < 1 at all sites, suggesting that stationary source emissions may play an important role in PM2.5 formation in those areas. Organic carbon and elemental carbon are well correlated at three urban sites although they are poorly correlated at the agriculture site. Other than the daily samples, hourly samples were measured at one urban site. PM2.5 mass concentrations display a peak in early morning, and a second peak in late afternoon. Back trajectory analysis shows that air masses with lower PM2.5 mass content mainly originate from the marine environment or from a continental environment but with a strong subsidence from the upper troposphere. Air masses with high PM2.5 mass concentrations are largely from continental sources. Our study of fine particulate matter and its chemical composition in North Carolina provides crucial information that may be used to determine the efficacy of the new National Ambient Air Quality Standard (NAAQS) for PM fine. Moreover, the gas-to-particle conversion processes provide improved prediction of long-range transport of pollutants and air quality.     

Simplified Methods for Statistical Interpretation of Monitoring Data

Statistical techniques are useful for interpretation of monitoring data for pollutants, process variables, etc. Simplified nomographical methods are presented for relating numbers of samples to confidence intervals for their mean values, and for determining the proportion of the population exceeding a specified concentration and confidence intervals for the proportion. A chart also is given for design of a sampling program for quality control. Illustrative frequency distribution data are given for hourly-averaged methane concentrations in air over three-week periods. They show trimodal lognormal distributions. These charts are applicable to lognormal distributions, as well as to normal distributions. They are convenient for many common problems.     

A Physical Explanation of the Lognormality of Pollutant Concentrations

Investigators In different environmental fields have reported that the concentrations of various measured substances have frequency distributions that are lognormal, or nearly so. That is, when the logarithms of the observed concentrations are plotted as a frequency distribution, the resulting distribution is approximately normal, or Gaussian, over much of the observed range. Examples include radionuclides in soil, pollutants in ambient air, Indoor air quality, trace metals In streams, metals in biological tissue, calcium In human remains. The ubiquity of the lognormal distribution in environmental processes is surprising and has not been adequately explained, since common processes in nature (for example, computation of the mean and the analysis of error) usually give rise to distributions that are normal rather than lognormal. This paper takes the first step toward explaining why lognormal distributions can arise naturally from certain physical processes that are analogous to those found in the environment. In this paper, these processes are treated mathematically, and the results are illustrated in a laboratory beaker experiment that Is simulated on the computer.     

Ions species size distribution in particulate matter associated with VOCs and meteorological conditions over an urban region

Airborne particulate matter (PM10, PM2.5, PM1) and volatile organic compounds (benzene, toluene, m,p-xylene, o-xylene) samples were collected during winter and summer seasons of 2005 at two sites, representing an urban and a suburban region of the Greater Athens Area. Urban site traffic emissions were the major contributor to the concentration of PM2.5, PM10, toluene, and xylenes, while benzene and PM1 concentrations were presented in significant spatial variations. K+, Na+, Mg2+, Ca2+, NO3-, Cl- and SO42- ions were analyzed for the chemical characterization of the collected PM samples. The results showed that Na+ cations and SO42- anions were the dominant species, during winter and summer, respectively, in both sites. The analysis of the synoptic scale and mesoscale atmospheric circulation during the experimental periods demonstrated that the meteorological conditions play a key role, not only in the variation but also in the distribution of the ionic concentrations at the three fractions of particulates and the dominant character (alkaline/acidic/neutral) of the particulates at the two sampling sites.