Characterization of Spatially Homogeneous Regions Based on Temporal Patterns of Fine Particulate Matter in the Continental United States

Kim, Seoung Bum; Temiyasathit, Chivalai; Chen, Victoria C. P.; Park, Sun Kyoung; Sattler, Melanie L.; Russell, Armistead G.

doi:10.3155/1047-3289.58.7.965

Cited by 24 publications

(15 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This cluster technique is used to split observations (stations) into k different groups, yielding a solution that minimizes the distance between the observations and maximizes the between-cluster variance (Kim et al, 2008). To perform this grouping, the methodology to select the centroids (cluster centre) in the initialization stage of the k-means method was to choose the first N (number of clusters) observations as the initial cluster centres.…”

Section: Stationsmentioning

confidence: 99%

Identification of airborne radioactive spatial patterns in Europe – Feasibility study using Beryllium-7

Hernández-Ceballos

Cinelli

Tollefsen

et al. 2016

Journal of Environmental Radioactivity

View full text Add to dashboard Cite

The present study proposes a methodology to identify spatial patterns in airborne radioactive particles in Europe. The methodology is based on transforming the activity concentrations in the set of stations for each month (monthly index), due to the tightly spaced sampling intervals (daily to monthly), in combination with hierarchical and non-hierarchical clustering approaches, due to the lack of a priori knowledge of the number of clusters to be created. Three different hierarchical cluster methodologies are explored to set the optimal number of clusters necessary to initialize the non-hierarchical one (k-means). To evaluate this methodology, cosmogenic beryllium-7 ((7)Be) data, collected between 2007 and 2010 at 19 sampling stations in European Union (EU) countries and stored in the Radioactivity Environmental Monitoring (REM) database, are used. This methodology yields a solution with three distinguishable clusters (south, central and north), each with a different evolution of the (7)Be monthly index. Clear differences between monthly indices are shown in both intensity and time trends, following a latitudinal distribution of the sampling stations. This cluster result is evaluated performing ANOVA analysis, considering the original (7)Be activity concentrations grouped in each cluster. The statistical results (among clusters and sampling stations within clusters) confirm the spatial distribution of (7)Be in Europe, and, hence, reinforce the use of this methodology. Finally, the impact of tropopause height on this grouping is successfully tested, suggesting its influence on the spatial distribution of (7)Be in Europe. For airborne radioactive particles the analysis gave valuable results that improve knowledge of these atmospheric compounds in Europe. Hence, this work addresses a methodology to a grouping of airborne sampling stations, 1) allowing a better understanding of the distribution of (7)Be activity concentrations in the EU, and 2) serving as a basis for further investigation of the heterogeneity of airborne radioactivity concentrations in Europe.

show abstract

Section: Stationsmentioning

confidence: 99%

Identification of airborne radioactive spatial patterns in Europe – Feasibility study using Beryllium-7

Hernández-Ceballos

Cinelli

Tollefsen

et al. 2016

Journal of Environmental Radioactivity

View full text Add to dashboard Cite

show abstract

“…17,18 Compared with short-term effects of air pollution, there is little information on the relation between chronic exposure to air pollution and prevalent hypertension. Inconsistent results have also been reported on the association between incident hypertension and air pollution.…”

mentioning

confidence: 99%

“…The results showed that the odds ratio for hypertension increased by pollution on BP in different parts of the world are unclear but may result from spatial and temporal variability in pollution sources and composition. 17,18 Compared with short-term effects of air pollution, there is little information on the relation between chronic exposure to air pollution and prevalent hypertension. Inconsistent results have also been reported on the association between incident hypertension and air pollution.…”

mentioning

confidence: 99%

Association Between Long-Term Air Pollution and Increased Blood Pressure and Hypertension in China

Qian²,

et al. 2013

View full text Add to dashboard Cite

http://hyper.ahajournals.org/ Downloaded from Dong et al Effects of Air Pollution on Blood Pressure 579pollution on BP in different parts of the world are unclear but may result from spatial and temporal variability in pollution sources and composition. 17,18 Compared with short-term effects of air pollution, there is little information on the relation between chronic exposure to air pollution and prevalent hypertension. Inconsistent results have also been reported on the association between incident hypertension and air pollution. For instance, Coogan et al 19 showed in a 10-year follow-up for incident hypertension and diabetes mellitus of black women from Los Angeles that NO X (but less PM 2.5 ) borderline increased the risk of becoming hypertensive. However, Sørensen et al 20 reported that longterm exposure (1 and 5 years) to NO X was not associated with incident self-reported hypertension in a Danish cohort. We hypothesized that at the population level, long-term exposure to ambient air pollution is associated with higher BP and higher prevalence of hypertension among humans. In this study, we tested this hypothesis in the 11 Districts Chinese Study, a cross-sectional study of air pollution and adult health in a large, well-characterized population-based sample, residing in northeast China, where there are wide differences in inter-and intracity gradients and ambient pollutant levels, offering a valuable opportunity to assess the associations between exposure and response. Methods Study Cities Selection and Subject RecruitmentMore than 20 million people reside in 14 cities in Liaoning province in northeast China. To maximize the inter-and intracity gradients of the pollutants of interest and minimize the correlation between district-specific ambient pollutants, in April 2009, we selected 3 cities (Shenyang, Anshan, and Jinzhou) based on the results of air pollution measurements between 2006 and 2008. There are 5, well-identified geographic districts in Shenyang, and 3 districts in Anshan and Jinzhou, respectively. Three communities within 1 km of air-monitoring sites were randomly chosen from these districts resulting in 33 locales, and from each of these, 700 to 1000 households were randomly identified. One participant, aged 18 to 74 years, was selected from each household without replacement. Our entry criterion was that the subject should have lived at that place for at least 5 years. The design and conduct of this investigation was reviewed and approved by Human Studies Committee of China Medical University. Before data collection, a written informed consent form was obtained from each participant. Ambient Air PollutionIn each of the selected study districts, there was only 1 municipal air pollution monitoring station, which was located 1 mile from the participants' homes. Measurements of PM 10 , SO 2 , NO 2 , and O 3 concentrations from 2006 to 2008 were obtained at the stations. The measurements were subject to uniform criteria for monitoring, siting, instrumentation, and quality assurance. Thes...

show abstract

“…By considering a functional representation, Bengtsson and Cavanaugh [54] modeled the observed time series in a state space setup and classified the sites via hierarchical clustering methods relying on disparity measures based on Kullback information. Kim et al [55] employed k-means clustering for classifying sites based on the temporal fluctuation of PM2.5. In order to identify city areas with similar air pollution behavior and to locate emission sources, Pires et al [56,57] applied Principal Components Analysis and Cluster Analysis i.e., the Euclidean-based average linkage method, to the mass concentrations of SO 2 and PM10 [56] and CO, NO 2 and O 3 [57] collected in the air quality monitoring network of Oporto Metropolitan Area.…”

Section: Literature Of Time Series Clustering/classification In Envirmentioning

confidence: 99%

Time series clustering by a robust autoregressive metric with application to air pollution

D’Urso

Giovanni

Massari

2015

Chemometrics and Intelligent Laboratory Systems

View full text Add to dashboard Cite

In this paper, following a fuzzy approach and adopting an autoregressive parameterization, we propose a robust clustering model for classifying time series. In particular, by adopting a fuzzy\ud partitioning around medoids approach, the suggested clustering model is able to define the so-called medoid time series, which is a representative time series of each cluster, and the membership degrees of each time series to the different clusters. The robustness of the proposed clustering model is guaranteed by the adoption of a suitable robust metric for time series, i.e. the so-called exponential distance measure. In this way, the clustering model is able to tolerate the presence of outlier time series in the clustering process. In particular, it is capable of neutralizing and smoothing the disruptive effect of outlier time series, preserving the original clustering structure of the dataset, by assigning to outlier time series approximately the same membership degrees across clusters. To illustrate the usefulness and effectiveness of the suggested time series clustering model, a simulation study and an application to air pollution time series are carried out. Comparison with some existing clustering procedures suggested in the literature shows several advantages of the proposed model

show abstract

Characterization of Spatially Homogeneous Regions Based on Temporal Patterns of Fine Particulate Matter in the Continental United States

Cited by 24 publications

References 24 publications

Identification of airborne radioactive spatial patterns in Europe – Feasibility study using Beryllium-7

Identification of airborne radioactive spatial patterns in Europe – Feasibility study using Beryllium-7

Association Between Long-Term Air Pollution and Increased Blood Pressure and Hypertension in China

Time series clustering by a robust autoregressive metric with application to air pollution

Contact Info

Product

Resources

About