Proximity to petrochemical industry and risk of childhood asthma occurrence.

Adverse effects on the respiratory system were associated with intensive petroleum-related industrial activities. The study aimed to assess the impact of petrochemical exposure on childhood asthma using various surrogate indices. A singleton birth cohort from 2004 to 2017 was conducted, leveraging two linked nationwide databases in Taiwan.

Quantifying source contributions to ambient NH using Geo-AI with time lag and parcel tracking functions.

Ambient ammonia (NH) plays an important compound in forming particulate matters (PMs), and therefore, it is crucial to comprehend NH's properties in order to better reduce PMs. However, it is not easy to achieve this goal due to the limited range/real-time NH data monitored by the air quality stations. While there were other studies to predict NH and its source apportionment, this manuscript provides a novel method (i.

A machine learning-based ensemble model for estimating diurnal variations of nitrogen oxide concentrations in Taiwan.

Air pollution is inextricable from human activity patterns. This is especially true for nitrogen oxide (NO), a pollutant that exists naturally and also as a result of anthropogenic factors. Assessing exposure by considering diurnal variation is a challenge that has not been widely studied.

Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.

Background: The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is essential.

Objective: This paper is the first of its kind to propose land-use based spatial machine learning (LBSM) models for predicting highly spatial-temporal variations of wet-bulb globe temperature (WBGT), which is a heat stress indicator used to assess thermal comfort in indoor and outdoor environments, specifically for the main island of Taiwan.

Estimating morning and evening commute period O concentration in Taiwan using a fine spatial-temporal resolution ensemble mixed spatial model with Geo-AI technology.

Elevated levels of ground-level ozone (O) can have harmful effects on health. While previous studies have focused mainly on daily averages and daytime patterns, it's crucial to consider the effects of air pollution during daily commutes, as this can significantly contribute to overall exposure. This study is also the first to employ an ensemble mixed spatial model (EMSM) that integrates multiple machine learning algorithms and predictor variables selected using Shapley Additive exExplanations (SHAP) values to predict spatial-temporal fluctuations in O concentrations across the entire island of Taiwan.

Characterization of the sources and health risks of polycyclic aromatic hydrocarbons in PM and their relationship with black carbon: A case study in northern Taiwan.

Polycyclic aromatic hydrocarbons (PAHs) and black carbon (BC) often coexist in PM because both form during the incomplete combustion of organic matter. These compounds are regarded as hazardous air pollutants with potential health effects, including respiratory and cardiovascular effects. In this study, to evaluate the health risks of PAHs and BC at an urban site in northern Taiwan, 16 priority PAHs and BC, identified by the United States Environmental Protection Agency, were analyzed and quantified in PM to determine their concentrations, their relationship with each other, and their likely sources.

Spatial distributions of PM-bound metal elements in the central part of western Taiwan and their potential emission sources and the carcinogenic health risks.

This study aimed to investigate the spatial distribution of metal elements in PM and their potential sources and associated health risks over a period of two years in eight locations in the central part of western Taiwan. The study revealed that the mass concentration of PM and the total mass concentration of 20 metal elements in PM were 39.0 μg m and 4.

Estimating the daily average concentration variations of PCDD/Fs in Taiwan using a novel Geo-AI based ensemble mixed spatial model.

It is generally established that PCDD/Fs is harmful to human health and therefore extensive field research is necessary. This study is the first to use a novel geospatial-artificial intelligence (Geo-AI) based ensemble mixed spatial model (EMSM) that integrates multiple machine learning algorithms and geographic predictor variables selected using SHapley Additive exPlanations (SHAP) values to predict spatial-temporal fluctuations in PCDD/Fs concentrations across the entire island of Taiwan. Daily PCDD/F I-TEQ levels from 2006 to 2016 were used for model construction, while external data was used for validating model dependability.

Structured Cluster Detection from Local Feature Learning for Text Region Extraction.

The detection of regions of interest is commonly considered as an early stage of information extraction from images. It is used to provide the contents meaningful to human perception for machine vision applications. In this work, a new technique for structured region detection based on the distillation of local image features with clustering analysis is proposed.

Using cluster algorithms with a machine learning technique and PMF models to quantify local-specific origins of PM and associated metals in Taiwan.

The influence of long-range transport (LRT) of air pollutants on neighboring regions and countries has been documented. The magnitude of LRT aerosols and related constituents can misdirect control strategies for local air quality management. In this study, we aimed to quantify PM (diameter less than 2.

How a winding-down oil refinery park impacts air quality nearby?

It is always difficult to compare, let alone estimate, the difference of air pollutant concentrations before and after closure of a major source because the pollutants cannot be traced or predicted after entering the ambient. Indeed, we are not aware of any studies specifically related to the air pollutants impacted by a winding-down source. In this work, we applied nine years (2010-2018) online measurement of air pollutants (including PM, PM, NO, SO, O and VOCs) to investigate (i) the temporal behavior of air pollutants before and after closure of an oil refinery park by using pair-wise statistics and correlations between wind speed and direction, and (ii) the source impacts on O concentrations using PMF coupled with multiple linear regression (MLR) analysis (PMF-MLR).

Living proximity to petrochemical industries and the risk of attention-deficit/hyperactivity disorder in children.

Evidence regarding the negative neurodevelopmental effects of compound exposure to petrochemicals remains limited. We aimed to evaluate the association between exposure to petrochemical facilities and generated emissions during early life and the risk of attention-deficit/hyperactivity disorder (ADHD) development in children. We conducted a population-based birth cohort study using the 2004 to 2014 Taiwanese Birth Certificate Database and verified diagnoses of ADHD using the National Health Insurance Database.

An integrated strategy by using long-term monitoring data to identify volatile organic compounds of high concern near petrochemical industrial parks.

Exposure to ambient volatile organic compounds (VOCs) is associated with a risk of cancer in the residents living near petrochemical facilities. However, research on the contribution of different VOCs to the lifetime cancer risk remains inconclusive. The variability in source emissions, geographical locations, seasons, and meteorological conditions can be assessed through long-term measurement of ambient VOCs with a wide spatial distribution, thus reducing the uncertainty of health risk assessment from source emissions.

A hybrid methodology to quantitatively identify inorganic aerosol of PM source contribution.

It is difficult to identify inorganic aerosol (IA) (primary and secondary), the main component of PM, without the significant tracers for sources. We are not aware of any studies specifically related to the IA's local contribution to PM. To effectively reduce the IA load, however, the contribution of local IA sources needs to be identified.

Proximity to petrochemical industrial parks and risk of chronic glomerulonephritis.

This study determined whether individuals residing near petrochemical industrial parks (PIPs) have a higher risk of chronic glomerulonephritis (CGN). We performed population-based 1:4 case-control study by using Taiwan's National Health Insurance Research Database from 2000 to 2016. The subjects were aged 20-65 years, residing in western Taiwan, and did not have a history of any renal or urinary system disease in 2000.

Effectiveness of palonosetron versus granisetron in preventing chemotherapy-induced nausea and vomiting: a systematic review and meta-analysis.

Purpose: Chemotherapy-induced nausea and vomiting (CINV) commonly occurs after chemotherapy, adversely affecting patients' quality of life. Recently, studies have shown inconsistent antiemetic effects of two common 5-hydroxytryptamine 3 receptor antagonists, namely, palonosetron and granisetron. Therefore, we conducted a meta-analysis to evaluate the effectiveness of palonosetron versus granisetron in preventing CINV.

Integrated analysis of source-specific risks for PM-bound metals in urban, suburban, rural, and industrial areas.

The levels and characteristics of atmospheric metals vary in time and location, can result in various health impacts, which increases the challenge of air quality management. We aimed to investigate PM-bound metals in multiple locations and propose a methodology for comparing metal elements across study regions and prioritizing source contributions through integrated health risk assessments. PM-bound metals were collected in the urban, suburban, rural, and industrial regions of Taiwan between 2016 and 2018.

Maternal proximity to petrochemical industrial parks and risk of premature rupture of membranes.

Background: Living near petrochemical industries has been reported to increase the risks of adverse birth outcomes, such as low birth weight and preterm delivery. However, evidence regarding the role of petrochemical exposure in pregnancy complications remains limited. This study evaluated the association between maternal proximity to petrochemical industrial parks (PIPs) during pregnancy and the occurrence of premature rupture of membranes (PROM).

Comparison of Spatial Modelling Approaches on PM and NO Concentration Variations: A Case Study in Surabaya City, Indonesia.

Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM) and nitrogen dioxide (NO) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia.

Predicting carbonaceous aerosols and identifying their source contribution with advanced approaches.

Organic carbon (OC) and elemental carbon (EC) play important roles in various atmospheric processes and health effects. Predicting carbonaceous aerosols and identifying source contributions are important steps for further epidemiological study and formulating effective emission control policies. However, we are not aware of any study that examined predictions of OC and EC, and this work is also the first study that attempted to use machine learning and hyperparameter optimization method to predict concentrations of specific aerosol contaminants.

Kriging-Based Land-Use Regression Models That Use Machine Learning Algorithms to Estimate the Monthly BTEX Concentration.

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.

Impacts of hazardous metals and PAHs in fine and coarse particles with long-range transports in Taipei City.

This study assessed the impact on air quality and health risk by long-range transported (LRT) PM- and PM-bound metals and PAHs in Taipei City, Taiwan. Several methods with receptor aerosol measurements were used to quantify the effect of LRT. The hybrid single particle lagrangian integrated trajectory model (HYSPLIT) was used in conjunction with the potential source contribution function (PSCF) to distinguish the LRT aerosols.

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

This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O₃ concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency's (EPA) data of O₃ 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.

PM- and PM-bound polycyclic aromatic hydrocarbons (PAHs) in the residential area near coal-fired power and steelmaking plants of Taichung City, Taiwan: In vitro-based health risk and source identification.

We investigated spatial and season variations in particle-bound PAH concentrations, identified their potential sources and estimated resultant health risk of activate toxicity pathways in a residential area near coal-fired power and steelmaking plants. Both atmospheric PM and PM samples (n = 94) were simultaneously collected for summer and winter in the Wuqi and Shalu districts of Taichung City, central Taiwan. The principal component analysis (PCA) measure was used to evaluate the sources of particle-bound PAHs.