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Article ; Online: Kriging-Based Land-Use Regression Models That Use Machine Learning Algorithms to Estimate the Monthly BTEX Concentration

Chin-Yu Hsu / Yu-Ting Zeng / Yu-Cheng Chen / Mu-Jean Chen / Shih-Chun Candice Lung / Chih-Da Wu

International Journal of Environmental Research and Public Health, Vol 17, Iss 6956, p

2020 Volume 6956

Abstract: This paper uses machine learning to refine a Land-use Regression (LUR) model and to estimate the spatial–temporal variation in BTEX concentrations in Kaohsiung, Taiwan. Using the Taiwanese Environmental Protection Agency (EPA) data of BTEX (benzene, ... ...

Abstract	This paper uses machine learning to refine a Land-use Regression (LUR) model and to estimate the spatial–temporal variation in BTEX concentrations in Kaohsiung, Taiwan. Using the Taiwanese Environmental Protection Agency (EPA) data of BTEX (benzene, toluene, ethylbenzene, and xylenes) concentrations from 2015 to 2018, which includes local emission sources as a result of Asian cultural characteristics, a new LUR model is developed. The 2019 data was then used as external data to verify the reliability of the model. We used hybrid Kriging-land-use regression (Hybrid Kriging-LUR) models, geographically weighted regression (GWR), and two machine learning algorithms—random forest (RF) and extreme gradient boosting (XGBoost)—for model development. Initially, the proposed Hybrid Kriging-LUR models explained each variation in BTEX from 37% to 52%. Using machine learning algorithms (XGBoost) increased the explanatory power of the models for each BTEX, between 61% and 79%. This study compared each combination of the Hybrid Kriging-LUR model and (i) GWR, (ii) RF, and (iii) XGBoost algorithm to estimate the spatiotemporal variation in BTEX concentration. It is shown that a combination of Hybrid Kriging-LUR and the XGBoost algorithm gives better performance than other integrated methods.
Keywords	nitrogen dioxide (NO 2 ) ; hybrid Kriging-LUR model ; culture-specific sources ; spatiotemporal variations ; Medicine ; R
Subject code	006
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Simple scoring algorithm to identify community-dwelling older adults with limited health literacy

Chung-Yi Li / Der-Sheng Han / Ding-Cheng Chan / Wen-Hsuan Hou / Ken N Kuo / Hsiu-Nien Shen / Yao-Mao Chang / Chien-Tien Su / Mu-Jean Chen / Han-Wei Tsai

BMJ Open, Vol 11, Iss

a cross-sectional study in Taiwan

2021 Volume 11

Keywords	Medicine ; R
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Pollen of Broussonetia papyrifera: An emerging aeroallergen associated with allergic illness in Taiwan

Wu, Pei-Chih / Huey-Jen Su / Mu-Jean Chen / Shih-Chun Candice Lung / Wei-Ping Lin

Science of the total environment. 2019 Mar. 20, v. 657

2019

Abstract: Pollen has long been recognized as a major allergen, having diverse patterns of allergenicity caused by differences in climate, geography, and vegetation. Our research aimed to explore the role of a regionally dominant pollen in Taiwan, Broussonetia ... ...

Abstract	Pollen has long been recognized as a major allergen, having diverse patterns of allergenicity caused by differences in climate, geography, and vegetation. Our research aimed to explore the role of a regionally dominant pollen in Taiwan, Broussonetia papyrifera, on clinical sensitization and daily 5collected and extracted for a skin prick test on 30 volunteers recruited from a medical college. Daily atmospheric pollen levels were measured using a Burkard 7-day volumetric trap. The association between daily atmospheric pollen levels and clinic visits for allergic illness was examined using a generalized additive model with a normal assumption. After excluding four participants with a positive response to a negative control, 10 participants (38.4%) were determined to be sensitive to B. papyrifera pollen extract. The three-day lagged concentration of B. papyrifera pollen exhibited the highest risk of daily asthma visits (relative risk [RR] = 1.166, 95% confidence interval [CI]: 1.014–1.341) and allergic rhinitis visits (RR = 1.119, 95% CI: 0.916–1.367) when the pollen increased equally in magnitude to its mean. Our study is the first to provide evidence indicating that the most dominant airborne pollen in Taiwan, B. papyrifera, plays a major role in sensitization and clinic visits for asthma and allergic rhinitis, thus highlighting the need to integrate aeroallergen monitoring with clinical diagnosis.
Keywords	allergenicity ; allergens ; asthma ; Broussonetia papyrifera ; climate ; confidence interval ; geography ; models ; monitoring ; pollen ; relative risk ; rhinitis ; skin prick tests ; vegetation ; Taiwan
Language	English
Dates of publication	2019-0320
Size	p. 804-810.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2018.11.324
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Developing Land-Use Regression Models to Estimate PM 2.5 -Bound Compound Concentrations

Chin-Yu Hsu / Chih-Da Wu / Ya-Ping Hsiao / Yu-Cheng Chen / Mu-Jean Chen / Shih-Chun Candice Lung

Remote Sensing, Vol 10, Iss 12, p

2018 Volume 1971

Abstract: Epidemiology estimates how exposure to pollutants may impact human health. It often needs detailed determination of ambient concentrations to avoid exposure misclassification. However, it is unrealistic to collect pollutant data from each and every ... ...

Abstract	Epidemiology estimates how exposure to pollutants may impact human health. It often needs detailed determination of ambient concentrations to avoid exposure misclassification. However, it is unrealistic to collect pollutant data from each and every subject. Land-use regression (LUR) models have thus been used frequently to estimate individual levels of exposures to ambient air pollution. This paper used remote sensing and geographical information system (GIS) tools to develop ten regression models for PM 2.5 -bound compound concentration based on measurements of a six-year period including <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>NH</mi> </mrow> <mn>4</mn> <mo>+</mo> </msubsup> <mo>,</mo> <msubsup> <mrow> <mrow> <mo></mo> <mi>SO</mi> </mrow> </mrow> <mn>4</mn> <mrow> <mn>2</mn> <mo>−</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mrow> <mrow> <mo></mo> <mi>NO</mi> </mrow> </mrow> <mn>3</mn> <mo>−</mo> </msubsup> </mrow> </semantics> </math> , OC, EC, Ba, Mn, Cu, Zn, and Sb. The explained variance (R 2 ) of these LUR models ranging from 0.60 to 0.92 confirms that this study successfully estimated the fine spatial variability of PM 2.5 -bound compound concentrations in Taiwan where the distribution of traffic, industrial area, greenness, and culture-specific PM 2.5 sources like temples collected from GIS and remote sensing data were main variables. In particular, while they were much less used, this study showcased the necessity of remote sensing data of greenness in future LUR studies for reducing the exposure bias. In terms of local residents’ health outcome or health effect indicators, this study further offers much-needed support for future air epidemiological studies. The results ...
Keywords	fine particulate matter (PM 2.5 ) ; land-use regression (LUR) ; compounds ; culture-specific PM 2.5 sources ; temples ; Science ; Q
Subject code	333
Language	English
Publishing date	2018-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration

Chin-Yu Hsu / Jhao-Yi Wu / Yu-Cheng Chen / Nai-Tzu Chen / Mu-Jean Chen / Wen-Chi Pan / Shih-Chun Candice Lung / Yue Leon Guo / Chih-Da Wu

International Journal of Environmental Research and Public Health, Vol 16, Iss 7, p

2019 Volume 1300

Abstract: This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O 3 concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency’s ( ...

Abstract	This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O 3 concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency’s (EPA) data of O 3 concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R 2 of 0.74 and a 10-fold cross-validated R 2 of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O 3 concentration variation in Asian areas.
Keywords	land use regression (LUR) ; ozone ; Asian culturally specific source ; temple ; spatial-temporal variability ; Medicine ; R
Subject code	333
Language	English
Publishing date	2019-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Elemental characterization and source apportionment of PM10 and PM2.5 in the western coastal area of central Taiwan

Hsu, Chin-Yu / Hung-Che Chiang / Mu-Jean Chen / Sheng-Lun Lin / Tzu-Yu Lin / Yu-Cheng Chen

Science of the total environment. 2016 Jan. 15, v. 541

2016

Abstract: This study investigated seasonal variations in PM10 and PM2.5 mass and associated trace metal concentrations in a residential area in proximity to the crude oil refinery plants and industrial parks of central Taiwan. Particle measurements were conducted ... ...

Abstract	This study investigated seasonal variations in PM10 and PM2.5 mass and associated trace metal concentrations in a residential area in proximity to the crude oil refinery plants and industrial parks of central Taiwan. Particle measurements were conducted during winter, spring and summer in 2013 and 2014. Twenty-six trace metals in PM10 and PM2.5 were analyzed using ICP-MS. Multiple approaches of the backward trajectory model, enrichment factor (EF), Lanthanum enrichment and positive matrix fraction (PMF) were used to identify potential sources of particulate metals. Mean concentrations of PM10 in winter, spring and summer were 76.4Â±22.6, 33.2Â±9.9 and 37.4Â±17.0Î¼gmâ3, respectively, while mean levels of PM2.5 in winter, spring and summer were 47.8Â±20.0, 23.9Â±11.2 and 16.3Â±8.2Î¼gmâ3, respectively. The concentrations of carcinogenic metals (Ni, As and adjusted Cr(VI)) in PM10 and PM2.5 exceeded the guideline limits published by WHO. The result of EF analysis confirmed that Mo, Sb, Cd, Zn, Mg, Cr, As, Pb, Cu, Ni and V were attributable to anthropogenic emission. PMF analysis demonstrated that trace metals in PM10 and PM2.5 were from the similar sources, such as coal combustion, oil combustion and traffic-related emission, except for soil dust and crustal element emissions only observed in PM10 and secondary aluminum smelter only observed in PM2.5. Considering health-related particulate metals, the traffic-related emission and coal combustion for PM10 and PM2.5, respectively, are important to control for reducing potential carcinogenic risk. The results could aid efforts to clarify the impact of source-specific origins on human health.
Keywords	aluminum ; antimony ; arsenic ; cadmium ; chromium ; coal ; coasts ; combustion ; copper ; dust ; emissions ; guidelines ; human health ; lanthanum ; lead ; magnesium ; models ; molybdenum ; nickel ; oils ; particulates ; petroleum ; residential areas ; risk ; seasonal variation ; soil ; spring ; summer ; vanadium ; winter ; World Health Organization ; zinc ; Taiwan
Language	English
Dates of publication	2016-0115
Size	p. 1139-1150.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2015.09.122
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Cologne/Königswinter

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Article: Land-use regression with long-term satellite-based greenness index and culture-specific sources to model PM2.5 spatial-temporal variability

Wu, Chih-Da / Mu-Jean Chen / Shih-Chun Candice Lung / Wen-Chi Pan / Yu-Cheng Chen / Yue Leon Guo / Yu-Ting Zeng

Environmental pollution. 2017 May, v. 224

2017

Abstract: This study utilized a long-term satellite-based vegetation index, and considered culture-specific emission sources (temples and Chinese restaurants) with Land-use Regression (LUR) modelling to estimate the spatial-temporal variability of PM2.5 using data ...

Abstract	This study utilized a long-term satellite-based vegetation index, and considered culture-specific emission sources (temples and Chinese restaurants) with Land-use Regression (LUR) modelling to estimate the spatial-temporal variability of PM2.5 using data from Taipei metropolis, which exhibits typical Asian city characteristics. Annual average PM2.5 concentrations from 2006 to 2012 of 17 air quality monitoring stations established by Environmental Protection Administration of Taiwan were used for model development. PM2.5 measurements from 2013 were used for external data verification. Monthly Normalized Difference Vegetation Index (NDVI) images coupled with buffer analysis were used to assess the spatial-temporal variations of greenness surrounding the monitoring sites. The distribution of temples and Chinese restaurants were included to represent the emission contributions from incense and joss money burning, and gas cooking, respectively. Spearman correlation coefficient and stepwise regression were used for LUR model development, and 10-fold cross-validation and external data verification were applied to verify the model reliability. The results showed a strongly negative correlation (r: −0.71 to −0.77) between NDVI and PM2.5 while temples (r: 0.52 to 0.66) and Chinese restaurants (r: 0.31 to 0.44) were positively correlated to PM2.5 concentrations. With the adjusted model R2 of 0.89, a cross-validated adj-R2 of 0.90, and external validated R2 of 0.83, the high explanatory power of the resultant model was confirmed. Moreover, the averaged NDVI within a 1750 m circular buffer (p < 0.01), the number of Chinese restaurants within a 1750 m buffer (p < 0.01), and the number of temples within a 750 m buffer (p = 0.06) were selected as important predictors during the stepwise selection procedures. According to the partial R2, NDVI explained 66% of PM2.5 variation and was the dominant variable in the developed model. We suggest future studies consider these three factors when establishing LUR models for estimating PM2.5 in other Asian cities.
Keywords	air quality ; burning ; cities ; cooking ; correlation ; environmental protection ; land use ; models ; monitoring ; normalized difference vegetation index ; particulates ; restaurants ; satellites ; Taiwan
Language	English
Dates of publication	2017-05
Size	p. 148-157.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	280652-6
ISSN	1873-6424 ; 0013-9327 ; 0269-7491
ISSN (online)	1873-6424
ISSN	0013-9327 ; 0269-7491
DOI	10.1016/j.envpol.2017.01.074
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Precipitation increases the occurrence of sporadic legionnaires' disease in Taiwan.

Nai-Tzu Chen / Mu-Jean Chen / Chao-Yu Guo / Kow-Tong Chen / Huey-Jen Su

PLoS ONE, Vol 9, Iss 12, p e

2014 Volume 114337

Abstract: Legionnaires' disease (LD) is an acute form of pneumonia, and changing weather is considered a plausible risk factor. Yet, the relationship between weather and LD has rarely been investigated, especially using long-term daily data. In this study, daily ... ...

Abstract	Legionnaires' disease (LD) is an acute form of pneumonia, and changing weather is considered a plausible risk factor. Yet, the relationship between weather and LD has rarely been investigated, especially using long-term daily data. In this study, daily data was used to evaluate the impacts of precipitation, temperature, and relative humidity on LD occurrence in Taiwan from 1995-2011. A time-stratified 2:1 matched-period case-crossover design was used to compare each case with self-controlled data using a conditional logistic regression analysis, and odds ratios (ORs) for LD occurrence was estimated. The city, gender and age were defined as a stratum for each matched set to modify the effects. For lag day- 0 to 15, the precipitation at lag day-11 significantly affected LD occurrence (p<0.05), and a 2.5% (95% CIs = 0.3-4.7%) increased risk of LD occurrence was associated with every 5-mm increase in precipitation. In addition, stratified analyses further showed that positive associations of precipitation with LD incidence were only significant in male and elderly groups and during the warm season ORs = 1.023-1.029). However, such an effect was not completely linear. Only precipitations at 21-40 (OR = 1.643 (95% CIs = 1.074-2.513)) and 61-80 mm (OR = 2.572 (1.106-5.978)) significantly increased the risk of LD occurrence. Moreover, a negative correlation between mean temperature at an 11-day lag and LD occurrence was also found (OR = 0.975 (0.953-0.996)). No significant association between relative humidity and LD occurrence was identified (p>0.05). In conclusion, in warm, humid regions, an increase of daily precipitation is likely to be a critical weather factor triggering LD occurrence where the risk is found particularly significant at an 11-day lag. Additionally, precipitation at 21-40 and 61-80 mm might make LD occurrence more likely.
Keywords	Medicine ; R ; Science ; Q
Subject code	910
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: When are we most vulnerable to temperature variations in a day?

Chao-Yu Guo / Wen-Chi Pan / Mu-Jean Chen / Chen-Wei Tsai / Nai-Tzu Chen / Huey-Jen Su

PLoS ONE, Vol 9, Iss 12, p e

2014 Volume 113195

Abstract: Daily temperature measures are commonly used when examining the association between temperature and mortality. In fact, temperature measures are available 24 hours a day and more detailed records may provide a better prediction of mortality compared to ... ...

Abstract	Daily temperature measures are commonly used when examining the association between temperature and mortality. In fact, temperature measures are available 24 hours a day and more detailed records may provide a better prediction of mortality compared to daily statistics. In this article, monthly stratified analysis modeling for mortality is conducted for the total population as well as the stratified elderly and younger subgroups. We identified the most significant time during the day that is associated with daily mortality. Surprisingly, the estimates of relative risk and magnitude of associations derived from the hourly temperature measures are similar or even stronger compared to those modeled by the daily statistics. This phenomenon remains true for lagged hourly temperature measures and the changing patterns of associations from January through December are revealed. In summary, people are the most vulnerable to temperature variations in the early morning around 5 am and the night time around 8 pm.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Ambient PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) in Changhua County, central Taiwan: Seasonal variation, source apportionment and cancer risk assessment

Chen, Yu-Cheng / Chin-Yu Hsu / Hung-Che Chiang / Mu-Jean Chen / Nai-Tzu Chen / Tzu-Ting Yang / Tzu-Yu Lin / Yuh-Shen Wu

Environmental pollution. 2016 Nov., v. 218

2016

Abstract: This study investigates PM2.5-bound PAHs for rural sites (Dacheng and Fangyuan) positioned close to heavy air-polluting industries in Changhua County, central Taiwan. A total of 113 PM2.5 samples with 22 PAHs collected from 2014 to 2015 were analyzed, ... ...

Abstract	This study investigates PM2.5-bound PAHs for rural sites (Dacheng and Fangyuan) positioned close to heavy air-polluting industries in Changhua County, central Taiwan. A total of 113 PM2.5 samples with 22 PAHs collected from 2014 to 2015 were analyzed, and Positive Matrix Factorization (PMF) and diagnostic ratios of PAHs were applied to quantify potential PAH sources. The influences of local and regional sources were also explored using the conditional probability function (CPF) and potential source contribution function (PSCF) with PMF-modeled results, respectively. Annual mean concentrations of total PAHs were 2.91Â Â±Â 1.34 and 3.04Â Â±Â 1.40Â ng/m3 for Dacheng and Fangyuan, respectively, and their corresponding BaPeq were measured at 0.534Â Â±Â 0.255 and 0.563Â Â±Â 0.273Â ng/m3 in concentration. Seasonal variations with higher PAHs found for the winter than for the spring and summer were observed for both sites. The lifetime excess cancer risk (ECR) from inhalation exposure to PAHs was recorded as 4.7Â ÃÂ 10â5 overall. Potential sources of PM2.5-bound PAHs include unburned petroleum and traffic emissions (42%), steel industry and coal combustion (31%), and petroleum and oil burning (27%), and unburned petroleum and traffic emission could contribute the highest ECR (2.4Â ÃÂ 10â5). The CPF results show that directional apportionment patterns were consistent with the actual locations of local PAH sources. The PSCF results indicate that mainly northeastern regions of China have contributed elevated PM2.5-bound PAHs from long-range transports.
Keywords	burning ; combustion ; emissions ; inhalation exposure ; neoplasms ; oils ; particulates ; petroleum ; polycyclic aromatic hydrocarbons ; risk ; risk assessment ; seasonal variation ; spring ; steel ; summer ; traffic ; winter ; China ; Taiwan
Language	English
Dates of publication	2016-11
Size	p. 372-382.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	280652-6
ISSN	1873-6424 ; 0013-9327 ; 0269-7491
ISSN (online)	1873-6424
ISSN	0013-9327 ; 0269-7491
DOI	10.1016/j.envpol.2016.07.016
Database	NAL-Catalogue (AGRICOLA)

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