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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Characterization of distribution of pesticide residues in crop units

The characteristic features of distribution of pesticide residues in crop units and single sample increments were studied based on more than 19,000 residue concentrations measured in root vegetables, leafy vegetables, small-, medium- and large-size fruits representing 20 different crops and 46 pesticides. Log-normal, gamma and Weibull distributions were found to provide the best fit for the relative frequency distributions of individual residue data sets. The overall best fit was provided by lognormal distribution. The relative standard deviation of residues (CV) in various crops ranged from 15–170%. The 100–120 residue values being in one data set was too small to identify potential effects of various factors such as the chemical and physical properties of pesticides and the nature of crops. Therefore, the average of CV values, obtained from individual data sets, were calculated and considered to be the best estimate for the likely variability of unit crop residues for treated field (CV = 0.8) and market samples (CV = 1.1), respectively. The larger variation of residues in market samples was attributed to the potential mixing of lots and varying proportion of non-detects. The expectable average variability of residues in composited samples can be calculated from the typical values taking into account the sample size.     

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.     

Use of two different acidic aerosol samplers to measure acidic aerosols in Hsinchu, Taiwan

Acidic aerosol concentrations measured by an annular denuder system (ADS) and a honeycomb denuder system (HDS) in Hsinchu, Taiwan, were compared. Aerosols were also sampled by a MOUDI (micro-orifice uniform deposit impactor) and analyzed by an ion chromatograph to determine the size distributions of different species. Using the measured aerosol size distribution, theoretical analysis showed that positive HNO3 artifact due to volatilization of NH4NO3 is generally negligible for both samplers. Comparing two different denuder samplers, the average concentration of HNO3 measured by the ADS was found to be lower than that measured by the HDS, while the difference between the two samplers for the average concentration of other species was found to be within +/- 15%. A possible cause of the difference in HNO3 concentrations is due to a greater loss of HNO3 in the cyclone used by the ADS than in the impactor used by the HDS. The study also showed incomplete absorption of the evaporated HCl and HNO3 from the particles on the Teflon filter by the first nylon filter in the filter pack of the ADS. Collection efficiency and capacity of HCl and HNO3 by the nylon filters need further investigation.     

Characteristics of springtime profiles and sources of ozone in the low troposphere over northern Taiwan

To quantify the possible sources of the high ambient ozone concentration in the low troposphere over Taiwan, ozone sounding data from a two-year intensive field measurement program conducted in April and early May of 2004 and 2005 in northern Taiwan has been examined. We found that the vertical ozone distributions and occurrence of enhanced ozone in the lower troposphere (below 6 km) mainly resulted from (1)Type NE: the long-range transport of ozone controlled by the prevailing northeasterly winds below 2 km, (2)Type LO: the local photochemical ozone production process, and (3)Type SW: the strong southwest/westerly winds aloft (2–6 km). In the boundary layer (BL), where Asian continental outflow prevails, the average profile for type NE is characterized by a peak ozone concentration of nearly 65 ppb at about 1500 m altitude. For type LO, high ozone concentration with an average ozone concentration greater than 80 ppb was also found in the BL in the case of stagnant atmospheric and sunny weather conditions dominated. For type SW, significant ozone enhancement with average ozone concentration of 70–85 ppb was found at around 4 km altitude. It is about 10 ppb greater than that of the types NE and LO at the same troposphere layer owing to the contribution of the biomass burning over Indochina. Due to Taiwan's unique geographic location, the complex interaction of these ozone features in the BL and aloft, especially features associated with northeasterly and south/southwesterly winds, have resulted in complex characteristics of ozone distributions in the lower troposphere over northern Taiwan.     

Statistical distributions of particulate matter and the error associated with sampling frequency

The distribution of particulate matter (PM) concentrations has an impact on human health effects and the setting of PM regulations. Since PM is commonly sampled on less than daily schedules, the magnitude of sampling errors needs to be determined. Daily PM data from Spokane, Washington were resampled to simulate common sampling schedules and the sampling error was computed for regulatory and distribution statistics. Probability density functions (pdf's) were fit to the annual daily data to determine the shape of the PM_2.5 and PM₈ concentration distributions and they were also fit to the less than daily sampling to determine if pdf's could be used to predict the daily high-concentration percentiles. There is an error when using a less than daily sampling schedule for all statistics. The error expressed as a percentage difference from the everyday sampling for the PM_2.5 mean was as large as 1.7, 3.4 and 7.7% and the 98th percentile error was as great as 8.8, 18 and 67% for 1-in-2 day, 1-in-3 day and 1-in-6 day sampling, respectively. For PM₈ the error in the mean was 2.5, 4.7 and 8.6% for and the error in the 99th percentile was 27, 18 and 46% for 1-in-2 day, 1-in-3 day, and 1-in-6 day sampling, respectively. The PM_2.5 and PM₈ concentration data were best fit by a three-parameter lognormal distribution and a generalized extreme value distribution, respectively. For PM_2.5 and PM₈, as the annual mean increased the mode concentration increased, but for PM₈ the shape of the distribution also flattened. Predicting the daily high percentiles from pdf's that were fit to the less than daily sampled data produced mixed results. For PM₈, the pdf's predicted high concentrations were closer to the daily percentiles than the actual less-than-daily sampling percentile while for PM_2.5 they were not.     

Spatial distribution and vertical variation of arsenic in Guangdong soil profiles, China

Total of 260 soil profiles were reported to investigate the arsenic spatial distribution and vertical variation in Guangdong province. The arsenic concentration followed an approximately lognormal distribution. The arsenic geometric mean concentration of 10.4 mg/kg is higher than that of China. An upper baseline concentration of 23.4 mg/kg was estimated for surface soils. The influence of soil properties on arsenic concentration was not important. Arsenic spatial distributions presented similar patterns that high arsenic concentration mainly located in limestone, and sandshale areas, indicating that soil arsenic distribution was dependent on bedrock properties than anthropogenic inputs. Moreover, from A- to C-horizon arsenic geometric mean concentrations had an increasing tendency of 10.4, 10.7 to 11.3 mg/kg. This vertical variation may be related to the lower soil organic matter and soil degradation and erosion. Consequently, the soil arsenic export into surface and groundwaters would reach 1040 t year-1 in the study area.     

Historical trends of PCDD/Fs and dioxin-like PCBs in sediments buried in a reservoir in Northern Taiwan

Polychlorinated dibenzo-p-dioxin (PCDD), polychlorinated dibenzofuran (PCDF) and polychlorinated biphenyl (PCB) concentrations were analyzed at 1-2cm intervals in a sediment core collected from a reservoir in Northern Taiwan to evaluate the organic pollution history. The highest PCDD/F (14.4ng TEQ/kg d.w.) and PCB (0.261ng TEQ(WHO)/kg d.w.) concentrations were determined at 13-15cm (estimated year: 1992). The ages of the levels of sediment core were estimated from the sedimentation rate. Analysis results demonstrate that the PCDD/F concentration of the sediment core measured in the reservoir reached their peak when the municipal waste incinerators (MWIs) in the area started to operate. Furthermore, the decrease in sediment core PCDD/F concentration is related to the time of enforcement of the PCDD/F emission limit set by the Environmental Protection Administration (EPA) in Taiwan. Significant distribution of OCDD in homologue profiles was noted in archived soil samples in Taiwan in which the major input of PCDD/Fs was thought to be atmospheric. Major PCB congeners found in the sediment core were the major components of the commercial PCB products. Input fluxes of PCDD/Fs (5.75-158ng-I-TEQ/m(2)-yr) and PCBs (0.248-3.71ng TEQ(WHO)/m(2)yr) into the reservoir of interest are also calculated from the concentration and sedimentation rate of the sediment. The results reveal that considerable amounts of PCDD/Fs and PCBs were carried into the reservoir of interest in the flood stage but not during normal stage.     

Partition and tempospatial variation of gaseous and particulate mercury at a unique mercury-contaminated remediation site

This study investigated the seasonal variation and spatial distribution of gaseous and particulate mercury at a unique mercury-contaminated remediation site located at the near-coastal region of Tainan City, Taiwan. Gaseous elemental mercury (GEM), particulate mercury (PTM), and dustfall mercury (DFM) were measured at six nearby sites from November 2009 to September 2010. A newly issued Method for Sampling and Analyzing Mercury in Air (National Institute of Environmental Analysis [NIEA] Method A304.10C) translated from U.S. Environmental Protection Agency (EPA) Method 10-5, was applied for the measurement of atmospheric mercury in this particular study. One-year field measurements showed that the seasonal averaged concentrations of GEM and PTM were in the range of 5.56-12.60 and 0.06-0.22 ng/m3, respectively, whereas the seasonal averaged deposition fluxes of DFM were in the range of 27.0-56.8 g/km2-month. The maximum concentrations of GEM and PTM were 38.95 and 0.58 ng/m3, respectively. The atmospheric mercury apportioned as 97.42-99.87% GEM and 0.13-2.58% PTM. As a whole, the concentrations of mercury species were higher in the springtime and summertime than those in the wintertime and fall. The southern winds generally brought higher mercury concentrations, whereas the northern winds brought relatively lower mercury concentrations, to the nearby fishing villages. This study revealed that the mercury-contaminated remediation site, an abandoned chlor-alkali manufacturing plant, was the major mercury emission source that caused severe atmospheric mercury contamination over the investigation region. The hot spot of mercury emissions was allocated at the southern tip of the abandoned chlor-alkali manufacturing plant. On-site continuous monitoring of GEM at the mercury-contaminated remediation site observed that GEM concentrations during the open excavation period were 2-3 times higher than those during the nonexcavation period.     

Comparisons of aerosol properties measured by impactors and light scattering from individual particles: refractive index,number and volume concentrations,and size distributions

The southeastern aerosol and visibility study (SEAVS) was conducted in Great Smoky Mountains National Park in summer 1995 to investigate variations in ambient aerosol size distributions and their effect on visibility. In this paper, we compare dry aerosol size distribution parameters from a MOUDI impactor and two different optical particle counters (OPCs). Size distributions from the various instruments are expressed in a common measure of size, specifically, optical and aerodynamic diameters are converted to a dry, geometric diameter basis. Comparisons of the real part of particle refractive index obtained directly from light scattering measurements and inferred from aerosol composition measurements are also shown. Real refractive indices from direct measurements and those computed from measured fine aerosol chemical composition were generally within ±0.02. Maximum differences in estimated accumulation mode integrated volume concentrations from all instruments were within ∼22%. Accumulation mode integrated number concentrations and geometric standard deviations from the two OPCs agreed within ∼30% and ∼3%, respectively. Differences between MOUDI- and OPC-derived accumulation mode number concentrations and geometric standard deviations were ∼20% and ∼8%, respectively. The average geometric volume mean diameters derived from the three instruments agreed within 15% or less. The volume median diameters obtained by fitting the CSU number concentration data to a lognormal function were typically the smallest. We show that these discrepancies can be related to the differences and biases in the measurement and data analysis techniques.     

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.     

Functional models for colloid retention in porous media at the triple line

Spectral confocal microscope visualizations of microsphere movement in unsaturated porous media showed that attachment at the Air Water Solid (AWS) interface was an important retention mechanism. These visualizations can aid in resolving the functional form of retention rates of colloids at the AWS interface. In this study, soil adsorption isotherm equations were adapted by replacing the chemical concentration in the water as independent variable by the cumulative colloids passing by. In order of increasing number of fitted parameters, the functions tested were the Langmuir adsorption isotherm, the Logistic distribution, and the Weibull distribution. The functions were fitted against colloid concentrations obtained from time series of images acquired with a spectral confocal microscope for three experiments performed where either plain or carboxylated polystyrene latex microspheres were pulsed in a small flow chamber filled with cleaned quartz sand. Both moving and retained colloids were quantified over time. In fitting the models to the data, the agreement improved with increasing number of model parameters. The Weibull distribution gave overall the best fit. The logistic distribution did not fit the initial retention of microspheres well but otherwise the fit was good. The Langmuir isotherm only fitted the longest time series well. The results can be explained that initially when colloids are first introduced the rate of retention is low. Once colloids are at the AWS interface they act as anchor point for other colloids to attach and thereby increasing the retention rate as clusters form. Once the available attachment sites diminish, the retention rate decreases.