1
|
Siddiquee T, Bhaskaran NA, Nathani K, Sawarkar SP. Empowering lung cancer treatment: Harnessing the potential of natural phytoconstituent-loaded nanoparticles. Phytother Res 2024. [PMID: 38806412 DOI: 10.1002/ptr.8241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 04/29/2024] [Accepted: 04/29/2024] [Indexed: 05/30/2024]
Abstract
Lung cancer, the second leading cause of cancer-related deaths, accounts for a substantial portion, representing 18.4% of all cancer fatalities. Despite advances in treatment modalities such as chemotherapy, surgery, and immunotherapy, significant challenges persist, including chemoresistance, non-specific targeting, and adverse effects. Consequently, there is an urgent need for innovative therapeutic approaches to overcome these limitations. Natural compounds, particularly phytoconstituents, have emerged as promising candidates due to their potent anticancer properties and relatively low incidence of adverse effects compared to conventional treatments. However, inherent challenges such as poor solubility, rapid metabolism, and enzymatic degradation hinder their clinical utility. To address these obstacles, researchers have increasingly turned to nanotechnology-based drug delivery systems (DDS). Nanocarriers offer several advantages, including enhanced drug stability, prolonged circulation time, and targeted delivery to tumor sites, thereby minimizing off-target effects. By encapsulating phytoconstituents within nanocarriers, researchers aim to optimize their bioavailability and therapeutic efficacy while reducing systemic toxicity. Moreover, the integration of nanotechnology with phytoconstituents allows for a nuanced understanding of the intricate molecular pathways involved in lung cancer pathogenesis. This integrated approach holds promise for modulating key cellular processes implicated in tumor growth and progression. Additionally, by leveraging the synergistic effects of phytoconstituents and nanocarriers, researchers seek to develop tailored therapeutic strategies that maximize efficacy while minimizing adverse effects. In conclusion, the integration of phytoconstituents with nanocarriers represents a promising avenue for advancing lung cancer treatment. This synergistic approach has the potential to revolutionize current therapeutic paradigms by offering targeted, efficient, and minimally toxic interventions. Continued research in this field holds the promise of improving patient outcomes and addressing unmet clinical needs in lung cancer management.
Collapse
Affiliation(s)
- Taufique Siddiquee
- Department of Pharmaceutics, SVKM's Dr. Bhanuben Nanavati College of Pharmacy, University of Mumbai, Mumbai, India
| | - Navya Ajitkumar Bhaskaran
- Department of Pharmaceutics, SVKM's Dr. Bhanuben Nanavati College of Pharmacy, University of Mumbai, Mumbai, India
| | - Khushali Nathani
- Department of Pharmaceutics, SVKM's Dr. Bhanuben Nanavati College of Pharmacy, University of Mumbai, Mumbai, India
| | - Sujata P Sawarkar
- Department of Pharmaceutics, SVKM's Dr. Bhanuben Nanavati College of Pharmacy, University of Mumbai, Mumbai, India
| |
Collapse
|
2
|
Wong PY, Su HJ, Candice Lung SC, Liu WY, Tseng HT, Adamkiewicz G, Wu CD. Explainable geospatial-artificial intelligence models for the estimation of PM 2.5 concentration variation during commuting rush hours in Taiwan. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 349:123974. [PMID: 38615837 DOI: 10.1016/j.envpol.2024.123974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 04/08/2024] [Accepted: 04/11/2024] [Indexed: 04/16/2024]
Abstract
PM2.5 concentrations are higher during rush hours at background stations compared to the average concentration across these stations. Few studies have investigated PM2.5 concentration and its spatial distribution during rush hours using machine learning models. This study employs a geospatial-artificial intelligence (Geo-AI) prediction model to estimate the spatial and temporal variations of PM2.5 concentrations during morning and dusk rush hours in Taiwan. Mean hourly PM2.5 measurements were collected from 2006 to 2020, and aggregated into morning (7 a.m.-9 a.m.) and dusk (4 p.m.-6 p.m.) rush-hour mean concentrations. The Geo-AI prediction model was generated by integrating kriging interpolation, land-use regression, machine learning, and a stacking ensemble approach. A forward stepwise variable selection method based on the SHapley Additive exPlanations (SHAP) index was used to identify the most influential variables. The performance of the Geo-AI models for morning and dusk rush hours had accuracy scores of 0.95 and 0.93, respectively and these results were validated, indicating robust model performance. Spatially, PM2.5 concentrations were higher in southwestern Taiwan for morning rush hours, and suburban areas for dusk rush hours. Key predictors included kriged PM2.5 values, SO2 concentrations, forest density, and the distance to incinerators for both morning and dusk rush hours. These PM2.5 estimates for morning and dusk rush hours can support the development of alternative commuting routes with lower concentrations.
Collapse
Affiliation(s)
- Pei-Yi Wong
- Department of Environmental and Occupational Health, National Cheng Kung University, Tainan, Taiwan
| | - Huey-Jen Su
- Department of Environmental and Occupational Health, National Cheng Kung University, Tainan, Taiwan
| | - Shih-Chun Candice Lung
- Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan; Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
| | - Wan-Yu Liu
- Department of Forestry, National Chung Hsing University, Taichung, Taiwan; Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung, Taiwan
| | - Hsiao-Ting Tseng
- Department of Information Management, National Central University, Taoyuan, Taiwan
| | - Gary Adamkiewicz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Chih-Da Wu
- Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung, Taiwan; Department of Geomatics, National Cheng Kung University, Tainan, Taiwan; National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan; Research Center for Precision Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
| |
Collapse
|
3
|
Asri AK, Lee HY, Chen YL, Wong PY, Hsu CY, Chen PC, Lung SCC, Chen YC, Wu CD. A machine learning-based ensemble model for estimating diurnal variations of nitrogen oxide concentrations in Taiwan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:170209. [PMID: 38278267 DOI: 10.1016/j.scitotenv.2024.170209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/02/2024] [Accepted: 01/14/2024] [Indexed: 01/28/2024]
Abstract
Air pollution is inextricable from human activity patterns. This is especially true for nitrogen oxide (NOx), 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. Incorporating 27 years of data, we attempted to estimate diurnal variations in NOx across Taiwan. We developed a machine learning-based ensemble model that integrated hybrid kriging-LUR, machine-learning, and an ensemble learning approach. Hybrid kriging-LUR was performed to select the most influential predictors, and machine-learning algorithms were applied to improve model performance. The three best machine-learning algorithms were suited and reassessed to develop ensemble learning that was designed to improve model performance. Our ensemble model resulted in estimates of daytime, nighttime, and daily NOx with high explanatory powers (Adj-R2) of 0.93, 0.98, and 0.94, respectively. These explanatory powers increased from the initial model that used only hybrid kriging-LUR. Additionally, the results depicted the temporal variation of NOx, with concentrations higher during the daytime than the nighttime. Regarding spatial variation, the highest NOx concentrations were identified in northern and western Taiwan. Model evaluations confirmed the reliability of the models. This study could serve as a reference for regional planning supporting emission control for environmental and human health.
Collapse
Affiliation(s)
- Aji Kusumaning Asri
- Department of Geomatics, College of Engineering, National Cheng Kung University, Tainan, Taiwan.
| | - Hsiao-Yun Lee
- Department of Leisure Industry and Health Promotion, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.
| | - Yu-Ling Chen
- Department of Geomatics, College of Engineering, National Cheng Kung University, Tainan, Taiwan.
| | - Pei-Yi Wong
- Department of Environmental and Occupational Health, National Cheng Kung University, Tainan, Taiwan.
| | - Chin-Yu Hsu
- Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, Taiwan; Center for Environmental Sustainability and Human Health, Ming Chi University of Technology, Taiwan.
| | - Pau-Chung Chen
- National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan; Institute of Environmental and Occupational Health Sciences, National Taiwan University College of Public Health, Taipei, Taiwan; Department of Environmental and Occupational Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Public Health, National Taiwan University College of Public Health, Taipei, Taiwan.
| | - Shih-Chun Candice Lung
- Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan; Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan; Institute of Environmental Health, School of Public Health, National Taiwan University, Taipei, Taiwan.
| | - Yu-Cheng Chen
- National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan; Department of Occupational Safety and Health, China Medical University, Taichung, Taiwan.
| | - Chih-Da Wu
- Department of Geomatics, College of Engineering, National Cheng Kung University, Tainan, Taiwan; National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan; Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung City 402, Taiwan.
| |
Collapse
|
4
|
Arfin T, Pillai AM, Mathew N, Tirpude A, Bang R, Mondal P. An overview of atmospheric aerosol and their effects on human health. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:125347-125369. [PMID: 37674064 DOI: 10.1007/s11356-023-29652-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/29/2023] [Indexed: 09/08/2023]
Abstract
Epidemiologic investigations have previously been published in more than 200 papers, and several studies have examined the impacts of particle air pollution on health. The main conclusions now being made about the epidemiological evidence of particle pollution-induced health impacts are discussed in this article. Although there is no universal agreement, most reviewers conclude that particulate air pollution, particularly excellent combustion-cause contamination prevalent in many municipal and manufacturing environments, is a significant risk for cardiopulmonary sickness and mortality. Most epidemiological research has concentrated on the impacts of acute exposure, although the total public health implications of chronic acquaintance's outcome may be more extraordinarily significant. According to some reviewers, prolonged, repeated exposure raises the risk of cardiorespiratory death and chronic respiratory illness. A more general (but still universal) agreement is that short-term particle pollution exposure has been shown to aggravate pre-existing pulmonary and cardiovascular diseases and increase the number of community members who become sick, require medical treatment, or die. Several in-depth studies conducted in the global and Indian regions are addressed.
Collapse
Affiliation(s)
- Tanvir Arfin
- Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440020, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
| | - Anupama M Pillai
- Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440020, India
| | - Nikhila Mathew
- Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440020, India
| | - Abha Tirpude
- Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440020, India
| | - Roshani Bang
- Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440020, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Pabitra Mondal
- Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440020, India
| |
Collapse
|
5
|
Berg CD, Schiller JH, Boffetta P, Cai J, Connolly C, Kerpel-Fronius A, Kitts AB, Lam DCL, Mohan A, Myers R, Suri T, Tammemagi MC, Yang D, Lam S. Air Pollution and Lung Cancer: A Review by International Association for the Study of Lung Cancer Early Detection and Screening Committee. J Thorac Oncol 2023; 18:1277-1289. [PMID: 37277094 DOI: 10.1016/j.jtho.2023.05.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 05/26/2023] [Indexed: 06/07/2023]
Abstract
INTRODUCTION The second leading cause of lung cancer is air pollution. Air pollution and smoking are synergistic. Air pollution can worsen lung cancer survival. METHODS The Early Detection and Screening Committee of the International Association for the Study of Lung Cancer formed a working group to better understand issues in air pollution and lung cancer. These included identification of air pollutants, their measurement, and proposed mechanisms of carcinogenesis. The burden of disease and the underlying epidemiologic evidence linking air pollution to lung cancer in individuals who never and ever smoked were summarized to quantify the problem, assess risk prediction models, and develop recommended actions. RESULTS The number of estimated attributable lung cancer deaths has increased by nearly 30% since 2007 as smoking has decreased and air pollution has increased. In 2013, the International Agency for Research on Cancer classified outdoor air pollution and particulate matter with aerodynamic diameter less than 2.5 microns in outdoor air pollution as carcinogenic to humans (International Agency for Research on Cancer group 1) and as a cause of lung cancer. Lung cancer risk models reviewed do not include air pollution. Estimation of cumulative exposure to air pollution exposure is complex which poses major challenges with accurately collecting long-term exposure to ambient air pollution for incorporation into risk prediction models in clinical practice. CONCLUSIONS Worldwide air pollution levels vary widely, and the exposed populations also differ. Advocacy to lower sources of exposure is important. Health care can lower its environmental footprint, becoming more sustainable and resilient. The International Association for the Study of Lung Cancer community can engage broadly on this topic.
Collapse
Affiliation(s)
| | - Joan H Schiller
- Department of Medicine, University of Virginia, Charlottesville, Virginia
| | - Paolo Boffetta
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, New York
| | - Jing Cai
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, People's Republic of China
| | - Casey Connolly
- The International Association for the Study of Lung Cancer, Denver, Colorado
| | - Anna Kerpel-Fronius
- Department of Radiology National Korányi Institute for Pulmonology, Budapest, Hungary
| | | | - David C L Lam
- University Department of Medicine, Queen Mary Hospital, University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Anant Mohan
- Department of Pulmonary Medicine, Critical Care, and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Renelle Myers
- Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada
| | - Tejas Suri
- Department of Pulmonary Medicine, Critical Care, and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Martin C Tammemagi
- Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada
| | - Dawei Yang
- Department of Pulmonary Medicine and Critical Care, Zhongshan Hospital Fudan University, Shanghai, People's Republic of China
| | - Stephen Lam
- Department of Medicine, British Columbia Cancer Agency and The University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
6
|
Tariba Lovaković B, Jagić K, Dvoršćak M, Klinčić D. Trace elements in indoor dust-Children's health risk considering overall daily exposure. INDOOR AIR 2022; 32:e13104. [PMID: 36168220 DOI: 10.1111/ina.13104] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/04/2022] [Accepted: 08/09/2022] [Indexed: 06/16/2023]
Abstract
Indoor dust presents an important source of daily exposure to toxic elements. The present study reports for the first time the levels of Al, As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb, Sn, Se, Sr, Tl, V, and Zn measured in dust samples collected from 10 kindergartens and 21 cars from Zagreb, Croatia. Based on the obtained data, we assessed the health risks from overall daily exposure to trace elements for children aged 2-6 years taking into account three pathways of dust intake-ingestion, dermal absorption, and inhalation. The median concentration of most elements was significantly higher in dust obtained from cars compared to kindergartens, especially in the cases of Co (11.62 vs. 3.60 mg kg-1 ), Cr (73.55 vs. 39.89 mg kg-1 ), Cu (186.33 vs. 26.01 mg kg-1 ), Mo (8.599 vs. 0.559 mg kg-1 ), Ni (37.05 vs. 17.38 mg kg-1 ), and Sn (9.238 vs. 1.159 mg kg-1 ). Oral intake was identified as the most important exposure pathway, except for Cr, Ni, and Sb where dermal contact was the main route of exposure. Health risk assessment indicated that no adverse effects are expected from overall exposure to trace elements. Although the cases of high exposure to toxic elements are not common in areas with no significant environmental pollutants, due to the health threat they may present even at low levels, their status should be carefully monitored.
Collapse
Affiliation(s)
| | - Karla Jagić
- Biochemistry and Organic Analytical Chemistry Unit, Institute for Medical Research and Occupational Health, Zagreb, Croatia
| | - Marija Dvoršćak
- Biochemistry and Organic Analytical Chemistry Unit, Institute for Medical Research and Occupational Health, Zagreb, Croatia
| | - Darija Klinčić
- Biochemistry and Organic Analytical Chemistry Unit, Institute for Medical Research and Occupational Health, Zagreb, Croatia
| |
Collapse
|
7
|
Plass D, Hilderink H, Lehtomäki H, Øverland S, Eikemo TA, Lai T, Gorasso V, Devleesschauwer B. Estimating risk factor attributable burden - challenges and potential solutions when using the comparative risk assessment methodology. Arch Public Health 2022; 80:148. [PMID: 35624479 PMCID: PMC9137119 DOI: 10.1186/s13690-022-00900-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 05/12/2022] [Indexed: 03/21/2024] Open
Abstract
Background Burden of disease analyses quantify population health and provide comprehensive overviews of the health status of countries or specific population groups. The comparative risk assessment (CRA) methodology is commonly used to estimate the share of the burden attributable to risk factors. The aim of this paper is to identify and address some selected important challenges associated with CRA, illustrated by examples, and to discuss ways to handle them. Further, the main challenges are addressed and finally, similarities and differences between CRA and health impact assessments (HIA) are discussed, as these concepts are sometimes referred to synonymously but have distinctly different applications. Results CRAs are very data demanding. One key element is the exposure-response relationship described e.g. by a mathematical function. Combining estimates to arrive at coherent functions is challenging due to the large variability in risk exposure definitions and data quality. Also, the uncertainty attached to this data is difficult to account for. Another key issue along the CRA-steps is to define a theoretical minimal risk exposure level for each risk factor. In some cases, this level is evident and self-explanatory (e.g., zero smoking), but often more difficult to define and justify (e.g., ideal consumption of whole grains). CRA combine all relevant information and allow to estimate population attributable fractions (PAFs) quantifying the proportion of disease burden attributable to exposure. Among many available formulae for PAFs, it is important to use the one that allows consistency between definitions, units of the exposure data, and the exposure response functions. When combined effects of different risk factors are of interest, the non-additive nature of PAFs and possible mediation effects need to be reflected. Further, as attributable burden is typically calculated based on current exposure and current health outcomes, the time dimensions of risk and outcomes may become inconsistent. Finally, the evidence of the association between exposure and outcome can be heterogeneous which needs to be considered when interpreting CRA results. Conclusions The methodological challenges make transparent reporting of input and process data in CRA a necessary prerequisite. The evidence for causality between included risk-outcome pairs has to be well established to inform public health practice.
Collapse
Affiliation(s)
- Dietrich Plass
- German Environment Agency, Section Exposure Assessment and Environmental Health Indicators, Berlin, Germany.
| | - Henk Hilderink
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Heli Lehtomäki
- Finnish Institute for Health and Welfare (THL), Health Security, Environmental Health, Helsinki, Finland.,University of Eastern Finland (UEF), Faculty of Health Sciences, School of Pharmacy, Kuopio, Finland
| | - Simon Øverland
- Section for Health Care Collaboration, Haukeland University Hospital, Bergen, Norway
| | - Terje A Eikemo
- Centre for Global Health Inequalities Research (CHAIN), Department of Sociology and Political Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Taavi Lai
- Fourth View Consulting, Tallinn, Estonia
| | - Vanessa Gorasso
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - Brecht Devleesschauwer
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.,Department of Translational Physiology, Infectiology and Public Health, Ghent University, Merelbeke, Belgium
| |
Collapse
|
8
|
Su HJ, Jung CC, Wang JH, Chen NT, Chang WH. Estimations of infiltration factors of diurnal PM 2.5 and heavy metals in children's bedrooms. INDOOR AIR 2022; 32:e13037. [PMID: 35622721 DOI: 10.1111/ina.13037] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/20/2022] [Accepted: 04/25/2022] [Indexed: 06/15/2023]
Abstract
Children are the sensitive population to fine particulate matter (PM2.5 ) exposure and spend most of their time in bedroom. Infiltration factor (Finf ) can be used to calculate the fraction of total indoor PM2.5 with outdoor origin to increase the accuracy of exposure assessment. However, studies have ignored the diurnal variations of PM2.5 Finf values, and a few studies have estimated Finf values for heavy metals in PM2.5 in children's bedrooms. To calculate the PM2.5 Finf , real-time indoor and outdoor PM2.5 concentrations and occupants' activities were collected in 56 study bedrooms. At 22 of the 56 study bedrooms, PM2.5 samples were also collected for heavy metals analysis. We noted the PM2.5 Finf was higher during the daytime (0.70 ± 0.23) than nighttime (0.54 ± 0.27) during the hot season, and the time of air conditioner use was longer at nighttime. The largest Finf value of heavy metal was V (0.88 ± 0.25), followed by Pb (0.85 ± 0.28), Mn (0.72 ± 0.26), Cr (0.69 ± 0.35), and Zn (0.61 ± 0.32), with a larger variation. Our findings suggest that the estimations of diurnal PM2.5 and heavy metals Finf values are necessary to increase the accuracy of exposure assessment.
Collapse
Affiliation(s)
- Huey-Jen Su
- Department of Environmental and Occupational Health, National Cheng-Kung University, Tainan City, Taiwan
| | - Chien-Cheng Jung
- Department of Public Health, China Medical University, Taichung City, Taiwan
| | - Jui-Hsin Wang
- Department of Environmental and Occupational Health, National Cheng-Kung University, Tainan City, Taiwan
| | - Nai-Tzu Chen
- Department of Environmental and Occupational Health, National Cheng-Kung University, Tainan City, Taiwan
| | - Wei-Hsiang Chang
- Department of Food Safety/Hygiene and Risk Management, National Cheng-Kung University, Tainan City, Taiwan
| |
Collapse
|
9
|
Abstract
Atmospheric aerosol is one of the major leading environmental risk factors for human health worldwide, potentially causing several million premature deaths per year [...]
Collapse
|