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PubMed2004

Adaptive denoising of event-related functional magnetic resonance imaging data using spectral subtraction.

A new adaptive signal-preserving technique for noise suppression in event-related functional magnetic resonance imaging (fMRI) data is proposed based on spectral subtraction. The proposed technique estimates a parametric model for the power spectrum of random noise from the acquired data based on the characteristics of the Rician statistical model. This model is subsequently used to estimate a noise-suppressed power spectrum for any given pixel time course by simple subtraction of power spectra. The new technique is tested using computer simulations and real data from event-related fMRI experiments. The results show the potential of the new technique in suppressing noise while preserving the other deterministic components in the signal. Moreover, we demonstrate that further analysis using principal component analysis and independent component analysis shows a significant improvement in both convergence and clarity of results when the new technique is used. Given its simple form, the new method does not change the statistical characteristics of the signal or cause correlated noise to be present in the processed signal. This suggests the value of the new technique as a useful preprocessing step for fMRI data analysis.

Algorithms↗

PubMed2005

Personality disorders in substance abusers: validation of the DIP-Q through principal components factor analysis and canonical correlation analysis.

BACKGROUND: Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. METHODS: The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a) a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133), and (b) a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. RESULTS: It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. CONCLUSION: The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.

Adult↗

PubMedDate not supplied

[Validation of the French version of a pleasure scale for children (The Pleasure Scale for Children, PSC, Kazdin, 1989) in 214 hospitalized children in pediatrics].

UNLABELLED: The aim of this study was to determine the metrological parameters of a french version of the Pleasure Scale for Children (PSC): 214 (121 males and 93 females) with a mean age of 8.69 years (sd: 1.95) ranging from 6 years to 12 years were included in the study. The children were inpatients presenting various somatic disorders. STATISTICAL ANALYSIS: First a principal component analysis was done on the 39 items of the correlation matrix. Several guidelines were used to limit the number of factors (Kaiser criteria, Cattell scree test, Horn parallel analysis). Secondly the construct validity was studied using the alpha Cronbach coefficient and by calculing the Pearson correlation coefficient between each item and the total score. Thirdly the concurrent validity was determinated using two items of the Children Depression Rating Scale--Revised (CDRS-R) measuring pleasure (social withdrawal and enjoyment capacity). Fourthly the discriminant validity of the PSC was studied by comparing non depressive children (score lower than 30 to the CDRS-R) and depressive children (score higher than 30 to the CDRS-R). RESULTS: The principal component analysis showed a one factor solution with 33 items among the 39 having a higher than 0.3 saturation. The Cronbach alpha coefficient was 0.84. All the items correlated with the total score. The mean value was 0.37. The correlations between the total score of the scale and the CDRS-R enjoyment capacity and social withdrawal items were respectively -0.37 (p < 0.01) and -0.38 (p < 0.01). PSC score were significantly lower in depressive children (m = 86.96; sd = 8.33) than in non depressive children (m = 94.67; sd = 10) (t = 5.32; df = 212; p < 0.001).

Animals↗

PubMedDate not supplied

Design and testing of the use of a complementary and alternative therapies survey in women with breast cancer.

PURPOSE/OBJECTIVES: To design and test a reliable and valid instrument to determine the frequency of use of complementary and alternative medicine (CAM) therapies among women diagnosed with breast cancer. DESIGN: A descriptive cross-sectional survey. SETTING: Women were recruited from the southeastern area and a rural midwestern area of the United States. SAMPLE: 105 predominantly Caucasian women (mean= 59 years of age) with a diagnosis of breast cancer. METHODS: The Use of Complementary and Alternative Therapies Survey was designed with a content validity index, and reliability was determined with the coefficient alpha. Exploratory factor analysis using a principal components analysis identified primary components (factors) embedded within the survey. Frequency of CAM therapy use was calculated for 33 individual therapies listed on the survey and among three survey-defined subscales of CAM therapies (i.e., diet and nutritional supplements, stress-reducing techniques, and traditional and ethnic medicines). MAIN RESEARCH VARIABLES: Psychometric properties of an instrument to assess frequency of use of CAM among women with breast cancer. FINDINGS: The reported prevalence of use of the individual CAM therapies varied considerably. The coefficient alpha estimate for the total survey was 0.86. Estimates for the individual hypothesized subscales were 0.67 for diet and nutritional supplements, 0.79 for stress-reducing techniques, and 0.80 for traditional and ethnic medicines. The principal components analysis resulted in a two-factor solution with nine items that loaded heavily and uniquely on a factor conceptualized as stress and anxiety reduction and six items that loaded heavily and uniquely on a factor conceptualized as dietary and physical manipulation. The remaining five items (vitamins and minerals, prayer and spiritual healing, massage, reflexology, and aromatherapy) indicated moderate loadings on factors one and two and, thus, were interpreted as equivocal items. CONCLUSIONS: Preliminary data indicated that the instrument is reliable and valid. Additional work is needed to improve the range of items and to test the instrument with other populations. IMPLICATIONS FOR NURSING: Use of CAM by women with breast cancer is believed to be increasing. However, limited data exist on the frequency and predictors of its use in this patient population; therefore, reliable and valid instruments are needed to determine use. If nurses can determine which CAM therapies women are employing, nurses can educate patients with breast cancer on the safe use of these therapies.

Breast Neoplasms↗

PubMed2004

Sperm subpopulations in Iberian red deer epididymal sperm and their changes through the cryopreservation process.

We have applied a statistical protocol based on principal component analysis, clustering methods, and discriminant analysis for the identification of sperm subpopulations in computer-assisted sperm analysis (CASA) data. Samples were obtained from the cauda epididymis of 11 Iberian red deer and cryopreserved following a standard protocol. Motility by CASA was analyzed just after sperm recovery, just before freezing, and after thawing, and eight motility descriptors for each individual spermatozoon were recorded. Sperm viability and acrosomal status were also assessed. Subpopulation analysis was performed in four sequential steps: principal component analysis using the eight motility descriptors; nonhierarchical clustering analysis (k-means) using the first two principal components; hierarchical clustering analysis (UPGMA); and selection of the final number of clusters. Three clusters were obtained for each motility analysis: slow and nonlinear; rapid and linear; and rapid, high ALH, nonlinear. We detected variations in the clusters between treatments (initial, prefreezing and postthawed). Indeed, motility increased and linearity decreased in the prefreezing analysis. A discriminant analysis isolated three descriptors that were used again in the same statistical analysis, giving four clusters that resembled the pattern found in the first classification. We also performed a clustering analysis of the males according to prefreezing/postthawed variation of total motility, viability, and acrosomal status. The proportion of the linear subpopulations in the prefreezing treatment, in both clustering analyses, correlated positively with postthawed viability recovery. Our results show that clustering analysis of CASA data gives useful and practical information that is not obtained by conventional sperm analysis.

Acrosome↗

PubMed2005

Correlation of KIT and platelet-derived growth factor receptor alpha mutations with gene activation and expression profiles in gastrointestinal stromal tumors.

Activating mutations of KIT and platelet-derived growth factor receptor alpha (PDGFRA) are known to be alternative and mutually exclusive genetic events in the development of gastrointestinal stromal tumors (GISTs). We examined the effect of the mutations of these two genes on the gene expression profile of 22 GISTs using the oligonucleotide microarray. Mutations of KIT and PDGFRA were found in 17 cases and three cases, respectively. The remaining two cases had no detectable mutations in either gene. The mutation status of KIT and PDGFRA was directly related to the expression levels of activated KIT and PDGFRA, and was also related to the different expression levels of activated proteins that play key roles in the downstream of the receptor tyrosine kinase III family. To evaluate the impact of mutation status and the importance of the type of mutation in gene expression and clinical features, microarray-derived data from 22 GISTs were interpreted using a principal component analysis (PCA). Three relevant principal component representing mutation of KIT, PDGFRA and chromosome 14q deletion were identified from the interpretation of the oligonucleotide microarray data with PCA. After supervised analysis, there was at least a two fold difference in expression between GISTs with KIT and PDGFRA mutation in 70 genes. Our findings demonstrate that mutations of KIT and PDGFRA affect differential activation and expression of some genes, and can be used for the molecular classification of GISTs.

Adult↗

PubMed2003

Predicting risk of coronary artery disease from DNA microarray-based genotyping using neural networks and other statistical analysis tool.

This paper presents a novel approach for complex disease prediction that we have developed, exemplified by a study on risk of coronary artery disease (CAD). This multi-disciplinary approach straddles fields of microarray technology and genetics, neural networks (NN), data mining and machine learning, as well as traditional statistical analysis techniques, namely principal components analysis (PCA) and factor analysis (FA). A description of the biological background of the study is given, followed by a detailed description of how the problem has been modeled for analyses by neural networks and FA. A committee learning approach for NN has been used to improve generalization rates. We show that our NN approach is able to yield promising prediction results despite using only the most fundamental network structures. More interestingly, through the statistical analysis process, genes of similar biological functions have been clustered. In addition, a gene marker involved in breaking down lipids has been found to be the most correlated to CAD.

Algorithms↗

PubMed2006

Coordination of thumb joints during opposition.

Thumb opposition plays a vital role in hand function. Kinematically, thumb opposition results from composite movements from multiple joints moving in multiple directions. The purpose of this study was to examine the coordination of thumb joints during opposition tasks. A total of 15 female subjects with asymptomatic hands were studied. Three-dimensional angular kinematics of the carpometacarpal (CMC), metacarpophalangeal (MCP) and interphalangeal (IP) joints were obtained by a marker-based motion analysis system. Thumb opposition revealed coordination among joints in a specific direction (inter-joint coordination) and among different directions within a joint (intra-joint coordination). In particular, linear couplings existed between the flexion and pronation at the CMC joint, and between the flexion of the CMC joint and flexion of the MCP joint. Principal component analysis showed that only two principal components adequately represented the thumb opposition data of seven movement directions. A term functional degrees of freedom by virtue of principal component analysis was proposed to uncover the extent of movement coordination in functional tasks.

Biomechanical Phenomena↗

PubMed1983

Principal components for allometric analysis.

Logarithmic bivariate regression slopes and logarithmic principal component coefficient ratios are two methods for estimating allometry coefficients corresponding to a in the classic power formula Y = BXa. Both techniques depend on high correlation between variables. Interpretation is logically limited to the variables included in analysis. Principal components analysis depends also on relatively uniform intercorrelations; given this, it serves satisfactorily as a method for summarizing many bivariate combinations. Unmodified major principal component coefficients cannot represent scaling to body weight; rather, they represent scaling to a composite size vector which usually is highly correlated with body size or weight but has an unspecified allometry. Thus, the concepts of proportionality and of isometry must be kept distinct.

Animals↗

PubMed2003

[Quality of life and well-being of elderly people: an exploratory study in the Portuguese population].

OBJECTIVES: To characterize elderly people's perception of quality of life and well-being. METHODS: A sample of 1,665 elderly aged 75 years or more living in 13 districts in Portugal were studied. Of them, 311 subjects were excluded because they were not able to convey their opinions. The EASYcare (Elderly Assessment System) was used to collect data from 1,354 (81.3%) of 1,665 subjects. Statistical analysis was based on principal components analysis and cluster analysis. RESULTS: EASYcare's showed to have good psychometric proprieties (Cronbach a =0.92). The principal component analysis identified 4 factors: mobility, communication competencies, well-being and daily living activities. Cluster analysis showed 4 groups of elderly people: autonomous (62.8%), almost autonomous (8.5%), almost dependent (4.3%) and dependent (3.2%). CONCLUSIONS: Quality of life for most of the elderly is quite positive, and only a small group presents problems related to severe cognitive impairment or some degree of dependence.

Activities of Daily Living↗

PubMed2000

Three-dimensional Bolton-Brush Growth Study landmark data: ontogeny and sexual dimorphism of the Bolton standards cohort.

OBJECTIVE: The treatment of craniofacial reconstructive surgery patients may benefit from comparison to average referent three-dimensional landmark data. These data may be useful for diagnosis, treatment planning, prosthetic design, or outcomes assessment. With regard to subadult patients, we hypothesize that the pattern of ontogenetic shape change of same sex, same ethnicity, referent populations will show gross uniformity. We present a preliminary shape analysis of 50 three-dimensional landmarks derived from 317 Bolton-Brush Growth Study biorthogonal image pairs. We determine which landmarks can be collected from scanned radiographs reliably by four operators for the precisely locatable points, ontogenetic trends in landmark configuration shape change, and patterns of sexual dimorphism. PARTICIPANTS: Participants were Bolton standards individuals (16 male and 16 female) who contributed biplane cephalograms seven or more times with annual or greater spacing between ages 3 and 18 years. DESIGN: After removing outliers, we searched for ontogenetic heterogeneity, including sexual dimorphism and within sex-specific Procrustes coordinate shape spaces. RESULTS: A cut-off of 4.3-mm interoperator error left 32 landmarks in our analysis. Three different approaches (principal component analysis, age-trend analysis, and principal components of age residuals) all found no patterns of individual variation around sex-specific average trends of shape change. Male shape change peaks at age 15, a correlate of the growth spurt. CONCLUSIONS: Simultaneous frontal and lateral anatomic landmark identification improves three-dimensional localization reliability. Three-dimensional craniodental shape change from ages 8 to 18 within the Bolton standards presents little heterogeneity. Considerations of ethnicity aside, these may be initial grounds for use of these data as a normative referent.

Adolescent↗

PubMedDate not supplied

Determination of the number and waveshapes of event related potential components using comparative factor analysis.

This paper applies new factor analysis methods to determine empirically the number and waveshapes of ERP components. It addresses several well-known problems in previous applications of factor analysis or principal components analysis (PCA) to ERP data, such as the assumption of simple structure by varimax rotation, low noise levels required by PCA, response latency variation, and background EEG (correlated noise). ERPs are modeled as consisting of nonstationary (response) components, stationary (random-phased EEG) processes, and independent noise. The analysis indicated that there was one main response component for the datasets analyzed, and that the EEG processes accounted for a major portion of the variance. Response components corresponded to the first and second derivatives of the dataset mean. This finding is due to response latency variation. Once the number and waveshapes of ERP components have been determined, source localization methods can be applied with much greater accuracy.

Adult↗

PubMed2006

Metabolomic analysis of methyl jasmonate treated Brassica rapa leaves by 2-dimensional NMR spectroscopy.

The metabolomic analysis of Brassica rapa leaves treated with methyl jasmonate was performed using 2-dimensional J-resolved NMR spectroscopy combined with multivariate data analysis. The principal component analysis of the J-resolved NMR spectra showed discrimination between control and methyl jasmonate treated plants by principal components 1 and 2. While the level of glucose, sucrose and amino acids showed a decrease after methyl jasmonate treatment, hydroxycinnamates and glucosinolate were highly increased. Methyl jasmonate treatment resulted in a long-term accumulation of indole glucosinolate and indole-3-acetic acid, lasting up to 14 days after treatment. Malate conjugated hydroxycinnamates also exhibited an increase until 14 days after methyl jasmonate treatment, these compounds might play an important role in plant defence responses mediated by methyl jasmonate.

Acetates↗

PubMed1999

Statistical analysis of array expression data as applied to the problem of tamoxifen resistance.

BACKGROUND: Although the emerging complementary DNA (cDNA) array technology holds great promise to discern complex patterns of gene expression, its novelty means that there are no well-established standards to guide analysis and interpretation of the data that it produces. We have used preliminary data generated with the CLONTECH Atlas human cDNA array to develop a practical approach to the statistical analysis of these data by studying changes in gene expression during the development of acquired tamoxifen resistance in breast cancer. METHODS: For hybridization to the array, we prepared RNA from MCF-7 human breast cell tumors, isolated from our athymic nude mouse xenograft model of acquired tamoxifen resistance during estrogen-stimulated, tamoxifen-sensitive, and tamoxifen-resistant growth. Principal components analysis was used to identify genes with altered expression. RESULTS AND CONCLUSIONS: Principal components analysis yielded three principal components that are interpreted as 1) the average level of gene expression, 2) the difference between estrogen-stimulated gene expression and the average of tamoxifen-sensitive and tamoxifen-resistant gene expression, and 3) the difference between tamoxifen-sensitive and tamoxifen-resistant gene expression. A bivariate (second and third principal components) 99% prediction region was used to identify outlier genes that exhibit altered expression. Two representative outlier genes, erk-2 and HSF-1 (heat shock transcription factor-1), were chosen for confirmatory study, and their predicted relative expression levels were confirmed in western blot analysis, suggesting that semiquantitative estimates are possible with array technology. IMPLICATIONS: Principal components analysis provides a useful and practical method to analyze gene expression data from a cDNA array. The method can identify broad patterns of expression alteration and, based on a small simulation study, will likely provide reasonable power to detect moderate-sized alterations in clinically relevant genes.

Animals↗

PubMed2001

Diversity in the rhizobia associated with Phaseolus vulgaris L. in Ecuador, and comparisons with Mexican bean rhizobia.

Common beans (Phaseolus vulgaris L.) have centers of origin in both Mesoamerica and Andean South America, and have been domesticated in each region for perhaps 5000 years. A third major gene pool may exist in Ecuador and Northern Peru. The diversity of the rhizobia associated with beans has also been studied, but to date with an emphasis on the Mesoamerican center of origin. In this study we compared bean rhizobia from Mexico and Andean South America using both phenotypic and phylogenetic approaches. When differences between the rhizobia of these two regions were shown, we then examined the influence of bean cultivar on the most probable number (MPN) count and biodiversity of rhizobia recovered from different soils. Three clusters of bean rhizobia were distinguished using phenotypic analysis and principal-component analysis of Box AIR-PCR banding patterns. They corresponded principally to isolates from Mexico, and the northern and southern Andean regions, with isolates from southern Ecuador exhibiting significant genetic diversity. Rhizobia from Dalea spp., which are infective and effective on beans, may have contributed to the apparent diversity of rhizobia recovered from the Mesoamerican region, while the rhizobia of wild Phaseolus aborigineus from Argentina showed only limited similarity to the other bean rhizobia tested. Use of P. vulgaris cultivars from the Mesoamerican and Andean Phaseolus gene pools as trap hosts did not significantly affect MPN counts of bean rhizobia from the soils of each region, but did influence the diversity of the rhizobia recovered. Such differences in compatibility of host and Rhizobium could be a factor in the poor reputation for nodulation and N2 fixation in this crop.

Colony Count, Microbial↗

PubMed2003

Biomarkers of aging in women and the rate of longitudinal changes.

The purposes of this study were (1) to estimate biological age score (BAS) in Japanese healthy women based on the 4-7 years longitudinal data for physiological, hematological and biochemical examinations and (2) to examine the rate of aging changes in adult women based on the estimated BAS. The samples consisted of cross-sectional (n=981) and longitudinal (n=110) groups. Out of 31 variables examined, five variables (forced expiratory volume in 1.0 s, systolic blood pressure, mean corpuscular hemoglobin, glucose, albumin/globulin ratio) that met the following criteria: 1) significant cross-sectional correlation with age; 2) significant longitudinal change in the same direction as the cross-sectional correlation; and (3) assessment of redundancy, were selected as candidate biomarkers of aging. This variable set was then submitted into a principal component analysis, and the first principal component obtained from this analysis was used as an equation for assessing one's BAS. Individual BAS showed a high longitudinal stability of age-related changes, suggesting high predictive validity of our newly developed aging measurement equation. However, changes in the aging rate based on the estimated BAS were not constant. The mean slopes of the regression lines of BAS for the three age groups (age<45, 45</=age<65 yrs, 65</=age) were 0.095, 0.065, 0.138, respectively. One-way analysis of variance detected a significant difference (F=5.14, p<0.01) among the three age groups. These results suggest that the rate of aging in adult women is relatively slower until 65 years of age, but after 65, the rate of aging shows a rapid increase. We concluded that the longitudinal method used for selection of variables to compute the BAS was useful and theoretically valid compared to those obtained from cross-sectional data analysis.

Adaptation, Physiological↗

PubMed2003

A transcriptional progression model for head and neck cancer.

PURPOSE: A genetic progression model for head and neck squamous cell carcinoma (HNSC) has been established and implies the presence of transcriptional dysregulation as a consequence of accumulation of genetic alterations. Although expression array data have been provided for HNSC, the timing of transcriptional dysregulation in the progression from normal mucosa to dyplastic epithelium to invasive HNSC has not been described. Here, we describe a transcriptional progression model of HNSC. EXPERIMENTAL DESIGN: Expression arrays representing >12,000 genes and expressed sequence tags were used to examine malignant lesions (M), premalignant lesions (PM), distant, histopathologically normal mucosa from patients with premalignant or malignant lesions (MN), and normal mucosa from the upper aerodigestive tract of patients with noncancer diagnoses (N). Significance analysis of microarrays, hierarchical clustering, and principal components analysis was used to identify genes with differential expression patterns. RESULTS: Using a false discovery rate of <5% for significance analysis of microarray, the M group revealed 965 up-regulated and 1106 down-regulated genes relative to the N group. The PM group demonstrated 108 up-regulated and 226 down-regulated genes relative to the N group, whereas the M group demonstrated only 5 up-regulated and 13 down-regulated genes relative to the PM group. Both hierarchical cluster analysis and principal components analysis revealed a consistent separation between the N, PM, and M groups, with a closer association between the PM and M groups. To provide independent validation of the microarray data, quantitative reverse transcription-PCR was performed for a significantly up-regulated gene, integrin alpha 6, correlating well with microarray data (linear regression analysis, P < 0.0001). CONCLUSIONS: Similarly to the genetic progression model of HNSC, this transcriptional model shows that the majority of alterations occurs before the development of malignancy and identifies key targets of transcriptional dysregulation during progression from a normal to a premalignant state and from a premalignant to a malignant state.

Carcinoma↗

PubMed2006

Spatiotemporal features of severe air pollution in northern Taiwan.

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.

Air Movements↗