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Marni R, Malla M, Chakraborty A, Voonna MK, Bhattacharyya PS, Kgk D, Malla RR. Combination of ionizing radiation and 2-thio-6-azauridine induces cell death in radioresistant triple negative breast cancer cells by downregulating CD151 expression. Cancer Chemother Pharmacol 2024:10.1007/s00280-024-04709-w. [PMID: 39167147 DOI: 10.1007/s00280-024-04709-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 08/10/2024] [Indexed: 08/23/2024]
Abstract
BACKGROUND Triple-negative breast cancer (TNBC) represents the most aggressive subtype of breast cancer and is frequently resistant to therapy, ultimately resulting in treatment failure. Clinical trials have demonstrated the potential of sensitizing radiation therapy (RT)-resistant TNBC through the combination of chemotherapy and RT. This study sought to explore the potential of CD151 as a therapy response marker in the co-treatment strategy involving ionizing radiation (IR) and the repurposed antiviral drug 2-Thio-6-azauridine (TAU) for sensitizing RT-resistant TNBC (TNBC/RR). METHODS The investigation encompassed a variety of assessments, including viability using MTT and LDH assays, cell proliferation through BrdU incorporation and clonogenic assays, cell cycle analysis via flow cytometry, cell migration using wound scratch and Boyden chamber invasion assays, DNA damage assessment through γH2AX analysis, apoptosis evaluation through acridine-orange and ethidium bromide double staining assays, as well as caspase 3 activity measurement using a colorimetric assay. CD151 expression was examined through ELISA, flow cytometry and RT-qPCR. RESULTS The results showed a significant reduction in TNBC/RR cell viability following co-treatment. Moreover, the co-treatment reduced cell migration, induced apoptosis, downregulated CD151 expression, and increased caspase 3 activity in TNBC/RR cells. Additionally, CD151 was predicted to serve as a therapy response marker for co-treatment with TAU and IR. CONCLUSION These findings suggest the potential of combination treatment with IR and TAU as a promising strategy to overcome RT resistance in TNBC. Furthermore, CD151 emerges as a valuable therapy response marker for chemoradiotherapy.
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Affiliation(s)
- Rakshmitha Marni
- Cancer Biology Laboratory, Department of Life Sciences, GITAM (Deemed to Be University), GITAM School of Science, Visakhapatnam, 530045, A.P, India
| | - Manas Malla
- Department of Computer Science and Engineering, GITAM (Deemed to Be University), GITAM School of Technology, Visakhapatnam, 530045, A.P, India
| | | | - Murali Krishna Voonna
- Mahatma Gandhi Cancer Hospital & Research Institute, Visakhapatnam-, 530017, A.P, India
| | | | - Deepak Kgk
- Mahatma Gandhi Cancer Hospital & Research Institute, Visakhapatnam-, 530017, A.P, India
| | - Rama Rao Malla
- Cancer Biology Laboratory, Department of Life Sciences, GITAM (Deemed to Be University), GITAM School of Science, Visakhapatnam, 530045, A.P, India.
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2
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Zhang W, Liu D, Tian H, Pan N, Yang R, Tang W, Yang J, Lu F, Dayananda B, Mei H, Wang S, Shi H. Parsimonious estimation of hourly surface ozone concentration across China during 2015-2020. Sci Data 2024; 11:492. [PMID: 38744849 PMCID: PMC11094007 DOI: 10.1038/s41597-024-03302-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/24/2024] [Indexed: 05/16/2024] Open
Abstract
Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015-2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.
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Affiliation(s)
- Wenxiu Zhang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Di Liu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hanqin Tian
- Schiller Institute of Integrated Science and Society, Boston College, Chestnut Hill, MA, 02467, USA
| | - Naiqin Pan
- Schiller Institute of Integrated Science and Society, Boston College, Chestnut Hill, MA, 02467, USA
- College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL, 36849, USA
| | - Ruqi Yang
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Wenhan Tang
- Department of Atmospheric Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jia Yang
- Natural Resource Ecology & Management, Oklahoma State University, Stillwater, OK, 74078, USA
| | - Fei Lu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Buddhi Dayananda
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Han Mei
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, 999077, China
| | - Siyuan Wang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hao Shi
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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3
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Soto GH. The impact of Chinese foreign direct investment and environmental tax revenues on air degradation in Europe: a spatial regression approach, 2000-2020. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:33819-33836. [PMID: 38691281 DOI: 10.1007/s11356-024-33399-3] [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: 08/01/2023] [Accepted: 04/16/2024] [Indexed: 05/03/2024]
Abstract
This study analyzes air pollution through the effects of China's FDI in 27 European countries over a 20-year period, with a focus on the impact of environmental tax revenues (ETRs) and the environmental context in China. The relationship is estimated through spatial regressions that account for the presence of air pollutants in neighboring countries. The findings suggest that China's FDI in Europe does not contribute to air pollution but rather has a positive impact. The presence of environmental charges filters out non-polluting investments, which has a non-linear relationship with PM2.5 pollution rates. The study also concludes that air pollution is closely linked to the global environmental context, highlighting the positive effects of international agreements in the fight against climate change. Specifically, the study finds a link between China's efforts to address its polluting activities and their impact on European air quality.
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Affiliation(s)
- Gonzalo Hernández Soto
- School of Business and Administration, Hong Kong Metropolitan University, 30 Good Shepherd St., Ho Man Tin, Block C, 0417, Kowloon, Hong Kong.
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4
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Chen W, Zhang F, Shang X, Zhang T, Guan F. The effects of surface vegetation coverage on the spatial distribution of PM 2.5 in the central area of Nanchang City, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:125977-125990. [PMID: 38008837 DOI: 10.1007/s11356-023-31031-4] [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: 05/22/2023] [Accepted: 11/08/2023] [Indexed: 11/28/2023]
Abstract
The frequent occurrence of haze has caused widespread concern in China, and PM2.5 is thought to be the main cause. Previous research showed that PM2.5 was not only influenced by meteorological conditions but also by land cover especially surface vegetation. It was concluded that PM2.5 concentration is significantly influenced by surface vegetation, but spatially how and in what manner are still unanswered. Taking the central area of Nanchang City, China, as a case, this study firstly applied land use regression (LUR) model to simulate the distribution of PM2.5 in 2020. Then, the dichotomous model was used to determine vegetation coverage. A statistical regression model was used to analyze the influence of vegetation cover on PM2.5 and the scale effects. The results showed that (1) vegetation coverage and PM2.5 concentration were both significantly negatively correlated at the spatial scales selected for this study. (2) The effect of vegetation coverage on PM2.5 varied with season and the 500 m had the best correlation. (3) The non-linear regression model fits better than the linear model, and the effect of vegetation coverage on PM2.5 was complex. (4) The effect of vegetation coverage on PM2.5 concentration was different with PM2.5 concentration level. The higher the PM2.5 concentration, the more pronounced the effect of vegetation coverage on it. This study proposed the idea and method of coupling vegetation coverage with PM2.5 concentration at the regional scale from gradient landscape's point of view and provided some references for mitigating PM2.5 pollution through optimizing urban vegetation patterns.
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Affiliation(s)
- Wenbo Chen
- School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang, 330013, China
| | - Fuqing Zhang
- School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang, 330013, China.
| | - Xue Shang
- Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, Nanchang, 330013, China
| | - Tongyue Zhang
- Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, Nanchang, 330013, China
| | - Feiying Guan
- Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, Nanchang, 330013, China
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5
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Lertsinsrubtavee A, Kanabkaew T, Raksakietisak S. Detection of forest fires and pollutant plume dispersion using IoT air quality sensors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122701. [PMID: 37804907 DOI: 10.1016/j.envpol.2023.122701] [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: 05/19/2023] [Revised: 10/03/2023] [Accepted: 10/04/2023] [Indexed: 10/09/2023]
Abstract
The widespread adoption of Internet of Things (IoT) sensors has revolutionized our understanding of the formation and mitigation of air pollution, significantly improving the accuracy of predictions related to air quality and emission sources. This study demonstrates the use of IoT air quality sensors to detect forest fire incidents by focusing on an area affected by forest fires in Tak Province, Thailand, from January to May 2021. We employed PM2.5 and carbon monoxide measurements from IoT sensors for forest fire detection and utilized the number of hotspots reported through satellite and human observations to identify forest fire incidents. Our data analysis revealed three distinct periods with forest fires and three periods without fires (non-forest fires). For model training, two forest fire and non-forest fire periods were selected and the remaining periods were set aside for validation. J48, a computer algorithm that helps make decisions by organizing information into a tree-like structure based on key characteristics, was used to construct the decision-tree model. Our model achieved an accuracy rate of 72% when classifying forest fire incidents using the training data and a solid accuracy of 69% on the validation data. In addition, we investigated the dispersion of PM2.5 plumes using a regression model. Notably, our findings highlighted the robust explanatory power of the lag time in PM2.5, for predicting PM2.5, in the next 15 min. Our analysis highlights the potential of IoT-based air quality sensors to enhance forest fire detection and predict pollution plume dispersion once fires are detected.
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Affiliation(s)
- Adisorn Lertsinsrubtavee
- Internet Education and Research Laboratory (intERLab), Asian Institute of Technology, Pathum Thani, Thailand
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6
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Wu S, Yao J, Wang Y, Zhao W. Influencing factors of PM 2.5 concentration in the typical urban agglomerations in China based on wavelet perspective. ENVIRONMENTAL RESEARCH 2023; 237:116641. [PMID: 37442257 DOI: 10.1016/j.envres.2023.116641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 07/15/2023]
Abstract
PM2.5 is one of the most harmful air pollutants affecting sustainable economic and social development in China. The analysis of influencing factors affecting PM2.5 concentration is significant for the improvement of air quality. In this study, three typical urban agglomerations in China (Beijing‒Tianjin‒Hebei [BTH], the Yangtze River Delta [YRD], and the Pearl River Delta [PRD]) were studied using innovative trend analysis, a Bayesian statistical model, and partial wavelet and multiwavelet coherence to analyze PM2.5 concentration variations and multi-scale coupled oscillations between PM2.5 concentration and air pollutants/meteorological factors. The results showed that: (1) PM2.5 concentration time-series showed significant downward trends, which decreased as follows: BTH > YRD > PRD. The higher the pollution level, the greater the change trend. In BTH and the PRD, PM2.5 had obvious trends and seasonal change points; whereas, the PM2.5 time-series change point in the YRD was not obvious. (2) PM2.5 had significant intermittent resonance cycles with air pollutants and meteorological factors in different time domains. There were differences in the main controlling factors affecting PM2.5 among the three urban agglomerations. (3) The explanatory ability of air pollutant combinations for variations in PM2.5 was higher than that of meteorological factor combinations. However, the synergistic effect of air pollutants/meteorological factors could better explain the PM2.5 concentration variations on all time-frequency scales. The results of this study provide a reference for ecological improvement as well as collaborative governance of air pollution.
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Affiliation(s)
- Shuqi Wu
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048; China.
| | - Jiaqi Yao
- Academy of Eco-civilization Development for Jing-Jin-Ji Megalopolis, Tianjin Normal University, Tianjin, 300382; China.
| | - Yongcai Wang
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048; China.
| | - Wenji Zhao
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048; China.
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7
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Wu S, Yan X, Yao J, Zhao W. Quantifying the scale-dependent relationships of PM 2.5 and O 3 on meteorological factors and their influencing factors in the Beijing-Tianjin-Hebei region and surrounding areas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 337:122517. [PMID: 37678736 DOI: 10.1016/j.envpol.2023.122517] [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: 06/13/2023] [Revised: 08/28/2023] [Accepted: 09/03/2023] [Indexed: 09/09/2023]
Abstract
To investigate the variations of PM2.5 and O3 and their synergistic effects with influencing factors at different time scales, we employed Bayesian estimator of abrupt seasonal and trend change to analyze the nonlinear variation process of PM2.5 and O3. Wavelet coherence and multiple wavelet coherence were utilized to quantify the coupling oscillation relationships of PM2.5 and O3 on single/multiple meteorological factors in the time-frequency domain. Furthermore, we combined this analysis with the partial wavelet coherence to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationships. The results obtained from this comprehensive analysis are as follows: (1) The seasonal component of PM2.5 exhibited a change point, which was most likely to occur in January 2017. The trend component showed a discontinuous decline and had a change point, which was most likely to appear in February 2017. The seasonal component of O3 did not exhibit a change point, while the trend component showed a discontinuous rise with two change points, which were most likely to occur in July 2018 and May 2017. (2) The phase and coherence relationships of PM2.5 and O3 on meteorological factors varied across different time scales. Stable phase relationships were observed on both small- and large-time scales, whereas no stable phase relationship was formed on medium scales. On all-time scales, sunshine duration was the best single variable for explaining PM2.5 variations and precipitation was the best single variable explaining O3 variations. When compared to single meteorological factors, the combination of multiple meteorological factors significantly improved the ability to explain variations in PM2.5 and O3 on small-time scales. (3) Atmospheric teleconnection factors were important driving factors affecting the response relationships of PM2.5 and O3 on meteorological factors and they had greater impact on the relationship at medium-time scales compared to small- and large-time scales.
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Affiliation(s)
- Shuqi Wu
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048, China.
| | - Xing Yan
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China.
| | - Jiaqi Yao
- Academy of Eco-civilization Development for Jing-Jin-Ji Megalopolis, Tianjin Normal University, Tianjin, 300382, China.
| | - Wenji Zhao
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048, China.
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8
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Baryshnikova NV, Wesselbaum D. Air pollution and motor vehicle collisions in New York city. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 337:122595. [PMID: 37734635 DOI: 10.1016/j.envpol.2023.122595] [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: 05/20/2023] [Revised: 09/17/2023] [Accepted: 09/19/2023] [Indexed: 09/23/2023]
Abstract
Road traffic accidents are a pervasive feature of everyday life, killing 36,500 people, injuring 4.5 million and, overall, generating costs to the American society of $340 billion in 2019. Understanding the underlying factors can improve the design of prevention strategies. We use all road traffic collisions in New York City between 2013 and 2021 (N = 1,269,600) and match each individual collision to the nearest weather and air pollution station. Our study uses highly disaggregated data using an hourly frequency of collisions at a fine spatial level incorporating various air pollutants and weather factors. We employ an instrumental variable approach using temperature inversions to provide exogenous variation in air pollution addressing endogeneity and measurement error concerns. We find that higher concentrations of carbon monoxide (CO) and sulfur dioxide (SO2) increase the number of collisions but leave the severity (persons injured or killed) unaffected. Part of this can be explained by the effect of air pollutants on aggressive behavior: CO (p < .05) and SO2 (p < .01) increase the number of collisions caused by aggressive driving. Interestingly, this channel is only present in male drivers. Our results provide additional evidence that air pollution not only adversely affects health, but also has "non-health" related effects which are costly for the society.
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Affiliation(s)
- Nadezhda V Baryshnikova
- School of Economics, University of Adelaide, 10 Pulteney Street, Adelaide, South Australia, 5005, Australia
| | - Dennis Wesselbaum
- Department of Economics, University of Otago, 60 Clyde Steet, Dunedin, 9054, New Zealand.
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Ma X, Yin Z, Cao B, Wang H. Meteorological influences on co-occurrence of O 3 and PM 2.5 pollution and implication for emission reductions in Beijing-Tianjin-Hebei. SCIENCE CHINA. EARTH SCIENCES 2023; 66:1-10. [PMID: 37359777 PMCID: PMC10205161 DOI: 10.1007/s11430-022-1070-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 01/17/2023] [Accepted: 01/30/2023] [Indexed: 06/28/2023]
Abstract
Co-occurrence of surface ozone (O3) and fine particulate matter (PM2.5) pollution (CP) was frequently observed in Beijing-Tianjin-Hebei (BTH). More than 50% of CP days occurred during April-May in BTH, and the CP days reached up to 11 in two months of 2018. The PM2.5 or O3 concentration associated with CP was lower than but close to that in O3 and PM2.5 pollution, indicating compound harms during CP days with double-high concentrations of PM2.5 and O3. CP days were significantly facilitated by joint effects of the Rossby wave train that consisted of two centers associated with the Scandinavia pattern and one center over North China as well as a hot, wet, and stagnant environmental condition in BTH. After 2018, the number of CP days decreased sharply while the meteorological conditions did not change significantly. Therefore, changes in meteorological conditions did not really contribute to the decline of CP days in 2019 and 2020. This implies that the reduction of PM2.5 emission has resulted in a reduction of CP days (about 11 days in 2019 and 2020). The differences in atmospheric conditions revealed here were helpful to forecast the types of air pollution on a daily to weekly time scale. The reduction in PM2.5 emission was the main driving factor behind the absence of CP days in 2020, but the control of surface O3 must be stricter and deeper. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s11430-022-1070-y.
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Affiliation(s)
- Xiaoqing Ma
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
| | - Zhicong Yin
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519080 China
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Bufan Cao
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
| | - Huijun Wang
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519080 China
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
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Parida T, Daka G, Murapala D, Kolli SK, Malla RR, Namuduri S. PM2.5: Epigenetic Alteration in Lung Physiology and Lung Cancer Pathogenesis. Crit Rev Oncog 2023; 28:51-58. [PMID: 38050981 DOI: 10.1615/critrevoncog.2023049651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Particulate matter (PM) has a very negative impact on human health, specifically the respiratory system. PM comes in many forms, among these is PM2.5,which is a major risk factor for lung cancer and other cardiovascular diseases. PM is inherent in emissions from industrial production, manufacturing, vehicle exhaust, mining, and cigarette smoking. For this reason, the composition of PM differs from area to area although its primary constituents are heavy metals and petroleum elements. PM has a long and toxic impact on human health. After extended exposure to PM2.5 the mortality rate for lung cancer patients increases. Already, lung cancer is the leading cause of death globally with the highest mortality rate. PM2.5 creates epigenetic changes in miRNA, histone modification, and DNA methylation, causing tumorigenesis followed by lung cancer.
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Affiliation(s)
- Tamanna Parida
- Department of Environmental Science, GITAM School of Science, GITAM (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India
| | - Gopamma Daka
- Department of Environmental Science, GITAM School of Science, GITAM (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India
| | - Deepthi Murapala
- Department of Environmental Science, GITAM School of Science, GITAM (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India
| | - Suresh Kumar Kolli
- Department of Environmental Science, GITAM School of Science, GITAM (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India
| | - Rama Rao Malla
- Cancer Biology Laboratory, Department of Biochemistry and Bioinformatics, School of Science, Gandhi Institute of Technology and Management (GITAM) (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India; Department of Biochemistry and Bioinformatics, School of Science, GITAM (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India
| | - Srinivas Namuduri
- Department of Environmental Science, GITAM School of Science, GITAM (Deemed to be University), Visakhapatnam-530045, Andhra Pradesh, India
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Impact of the ‘Coal-to-Natural Gas’ Policy on Criteria Air Pollutants in Northern China. ATMOSPHERE 2022. [DOI: 10.3390/atmos13060945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
During the last decades, China had issued a series of stringent control measures, resulting in a large decline in air pollutant concentrations. To quantify the net change in air pollutant concentrations driven by emissions, we developed an approach of determining the closed interval of the deweathered percentage change (DPC) in the concentration of air pollutants on an annual scale, as well as the closed intervals of cumulative DPC in a year compared with that in the base year. Thus, the hourly mean mass concentrations of criteria air pollutants to determine their interannual variations and the closed intervals of their DPCs during the heating seasons from 2013 to 2019 in Qingdao (a coastal megacity) were analyzed. The seasonal mean SO2 concentration decreased from 2013 to 2019. The seasonal mean CO, NO2, and PM2.5 concentrations also generally decreased from 2013 to 2017, but increased unexpectedly in 2018 (from 0.9 mg m−3 (CO), 42 µg m−3 (NO2), and 51 µg m−3 (PM2.5) in 2017 to 1.1 mg m−3, 48 µg m−3, and 64 µg m−3 in 2018, respectively). The closed intervals of DPC in concentrations of CO, NO2, and PM2.5 from the 2017 heating season (2017/2018) to the 2018 heating season (2018/2019) were obtained at (27%, 30%), (15%, 18%), and (30%, 33%), respectively. Such high positive endpoint values of the closed intervals, in contrast to their small interval lengths, indicate increased emissions of these pollutants and/or their precursors in 2018/2019 compared with 2017/2018, by minimizing the meteorological influences. The rebounds of CO, NO2, and PM2.5 in 2018/2019 were likely associated with a doubled increase in natural gas (NG) consumption implemented by the “coal-to-NG” project, as the total energy consumption showed little difference. Our results suggested an important role of the “coal-to-NG” project in driving concentrations of air pollutant increases in China in 2018/2019, which need integrated assessments.
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Chen PC, Sung FC, Mou CH, Chen CW, Tsai SP, Hsieh DHP, Hsu CY. A cohort study evaluating the risk of stroke associated with long-term exposure to ambient fine particulate matter in Taiwan. Environ Health 2022; 21:43. [PMID: 35439956 PMCID: PMC9017007 DOI: 10.1186/s12940-022-00854-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 04/11/2022] [Indexed: 05/06/2023]
Abstract
BACKGROUND Evidences have shown that the stroke risk associated with long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5) varies among people in North America, Europe and Asia, but studies in Asia rarely evaluated the association by stroke type. We examined whether long-term exposure to PM2.5 is associated with developing all strokes, ischemic stroke and hemorrhagic stroke. METHODS The retrospective cohort study consisted of 1,362,284 adults identified from beneficiaries of a universal health insurance program in 2011. We obtained data on air pollutants and meteorological measurements from air quality monitoring stations across Taiwan in 2010-2015. Annual mean levels of all environmental measurements in residing areas were calculated and assigned to cohort members. We used Cox proportional hazards models to estimate hazard ratio (HR) and 95% confidence interval (CI) of developing stroke associated with 1-year mean levels of PM2.5 at baseline in 2010, and yearly mean levels from 2010 to 2015 as the time-varying exposure, adjusting for age, sex, income and urbanization level. RESULTS During a median follow-up time of 6.0 years, 12,942 persons developed strokes, 9919 (76.6%) were ischemic. The adjusted HRs (95% CIs) per interquartile range increase in baseline 1-year mean PM2.5 were 1.03 (1.00-1.06) for all stroke, 1.06 (1.02-1.09) for ischemic stroke, and 0.95 (0.89-1.10) for hemorrhagic stroke. The concentration-response curves estimated in the models with and without additional adjustments for other environmental measurements showed a positively linear association between baseline 1-year mean PM2.5 and ischemic stroke at concentrations greater than 30 μg/m3, under which no evidence of association was observed. There was an indication of an inverse association between PM2.5 and hemorrhagic stroke, but the association no longer existed after controlling for nitrogen dioxide or ozone. We found similar shape of the concentration-response association in the Cox regression models with time-varying PM2.5 exposures. CONCLUSION Long-term exposure to PM2.5 might be associated with increased risk of developing ischemic stroke. The association with high PM2.5 concentrations remained significant after adjustment for other environmental factors.
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Affiliation(s)
- Pei-Chun Chen
- Department of Public Health, China Medical University College of Public Health, 100 Jingmao Rd Sec. 1, Taichung, 406040, Taiwan.
| | - Fung-Chang Sung
- Department of Health Services Administration, China Medical University College of Public Health, 100 Jingmao Rd Sec. 1, Taichung, 406040, Taiwan.
- Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan.
- Department of Food Nutrition and Health Biotechnology, Asia University, Taichung, Taiwan.
| | - Chih-Hsin Mou
- Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan
| | - Chao W Chen
- University of Maryland Global Campus, Adelphi, MD, USA
| | - Shan P Tsai
- School of Public Health, Texas A&M University, College Station, TX, USA
| | - Dennis H P Hsieh
- Department of Environmental Toxicology, University of California, Davis, CA, USA
| | - Chung Y Hsu
- Graduate Institute of Biomedical Sciences, China Medical University College of Public Health, Taichung, Taiwan
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Airborne bacterial community associated with fine particulate matter (PM2.5) under different air quality indices in Temuco city, southern Chile. Arch Microbiol 2022; 204:148. [PMID: 35061108 PMCID: PMC8776980 DOI: 10.1007/s00203-021-02740-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 11/02/2022]
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Interpolation-Based Fusion of Sentinel-5P, SRTM, and Regulatory-Grade Ground Stations Data for Producing Spatially Continuous Maps of PM2.5 Concentrations Nationwide over Thailand. ATMOSPHERE 2022. [DOI: 10.3390/atmos13020161] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Atmospheric pollution has recently drawn significant attention due to its proven adverse effects on public health and the environment. This concern has been aggravated specifically in Southeast Asia due to increasing vehicular use, industrial activity, and agricultural burning practices. Consequently, elevated PM2.5 concentrations have become a matter of intervention for national authorities who have addressed the needs of monitoring air pollution by operating ground stations. However, their spatial coverage is limited and the installation and maintenance are costly. Therefore, alternative approaches are necessary at national and regional scales. In the current paper, we investigated interpolation models to fuse PM2.5 measurements from ground stations and satellite data in an attempt to produce spatially continuous maps of PM2.5 nationwide over Thailand. Four approaches are compared, namely the inverse distance weighted (IDW), ordinary kriging (OK), random forest (RF), and random forest combined with OK (RFK) leveraging on the NO2, SO2, CO, HCHO, AI, and O3 products from the Sentinel-5P satellite, regulatory-grade ground PM2.5 measurements, and topographic parameters. The results suggest that RFK is the most robust, especially when the pollution levels are moderate or extreme, achieving an RMSE value of 7.11 μg/m3 and an R2 value of 0.77 during a 10-day long period in February, and an RMSE of 10.77 μg/m3 and R2 and 0.91 during the entire month of March. The proposed approach can be adopted operationally and expanded by leveraging regulatory-grade stations, low-cost sensors, as well as upcoming satellite missions such as the GEMS and the Sentinel-5.
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