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Shao Y, Zhao W, Wei J, Wang S, Wang Y, Zhang Y. Growth and reproduction effects and transgenerational effects of nonylphenol in Moina mongolica Daday (Crustacea: Cladocera). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:29221-29230. [PMID: 33559073 DOI: 10.1007/s11356-021-12592-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 01/18/2021] [Indexed: 06/12/2023]
Abstract
An experimental ecology method was used to study the acute toxicity of nonylphenol (NP) and the effects of NP on growth, reproduction, and population growth in Moina mongolica. The effects were studied in a parent generation exposed to NP and three generations of offspring (F1, F2, and F3) not exposed to NP. The acute 24- and 48-h median lethal concentrations (LC50) of M. mongolica were 0.066 and 0.046 mg L-1, respectively, indicating that NP is very toxic to M. mongolica. In chronic exposure experiments using parent M. mongolica, NP clearly inhibited the lifespan, reproductive volume, total molting time, end-body length, and population growth parameters. In the recovery generations in a clean environment, three generations still suffered from toxic effects, with toxic amplification in generation F1. Generations F2 and F3 clearly followed a recovery trend in the groups in which the parents were exposed to 0.001-0.007 mg L-1 NP but recovered slowly in the groups in which the parents were exposed to 0.009 and 0.011 mg L-1 NP. The results indicated that NP has overt reproductive toxic and transgenerational effects on M. mongolica. Further studies of the damage caused to the aquatic environment by hormone-like chemicals such as NP should therefore be performed.
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Affiliation(s)
- Yingdi Shao
- College of Fisheries and Life Science, Key Laboratory of Hydrobiology in Liaoning Province, Dalian Ocean University, Dalian, 116023, Liaoning, China
| | - Wen Zhao
- College of Fisheries and Life Science, Key Laboratory of Hydrobiology in Liaoning Province, Dalian Ocean University, Dalian, 116023, Liaoning, China.
| | - Jie Wei
- College of Fisheries and Life Science, Key Laboratory of Hydrobiology in Liaoning Province, Dalian Ocean University, Dalian, 116023, Liaoning, China
| | - Shan Wang
- College of Fisheries and Life Science, Key Laboratory of Hydrobiology in Liaoning Province, Dalian Ocean University, Dalian, 116023, Liaoning, China
| | - Yu Wang
- College of Fisheries and Life Science, Key Laboratory of Hydrobiology in Liaoning Province, Dalian Ocean University, Dalian, 116023, Liaoning, China
| | - Yu Zhang
- College of Fisheries and Life Science, Key Laboratory of Hydrobiology in Liaoning Province, Dalian Ocean University, Dalian, 116023, Liaoning, China
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The Impact of Air Pollution on Neurodegenerative Diseases. Ther Drug Monit 2021; 43:69-78. [PMID: 33009291 DOI: 10.1097/ftd.0000000000000818] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 09/23/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND With the development of industrialization in human society, ambient pollutants are becoming more harmful to human health. Epidemiological and toxicological studies indicate that a close relationship exists between particulate matter with a diameter ≤2.5 µm (PM2.5) and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). To further confirm the relationship, we focus on possible relevant mechanisms of oxidative stress and neuroinflammation underlying the association between PM2.5 and neurodegenerative diseases in the review. METHODS A literature search was performed on the studies about PM2.5 and neurodegenerative diseases via PubMed. A total of 113 articles published were selected, and 31 studies were included. RESULTS PM2.5 can enter the central nervous system through 2 main pathways, the blood-brain barrier and olfactory neurons. The inflammatory response and oxidative stress are 2 primary mechanisms via which PM2.5 leads to toxicity in the brain. PM2.5 abnormally activates microglia, inducing the neuroinflammatory process. Inflammatory markers such as IL-1β play an essential role in neurodegenerative diseases such as AD and PD. Moreover, the association between lipid mechanism disorders related to PM2.5 and neurodegenerative diseases has been gaining momentum. CONCLUSIONS In conclusion, PM2.5 could significantly increase the risk of neurological disorders, such as AD and PD. Furthermore, any policy aimed at reducing air-polluting emissions and increasing air quality would be protective in human beings.
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Fan MY, Zhang YL, Lin YC, Li L, Xie F, Hu J, Mozaffar A, Cao F. Source apportionments of atmospheric volatile organic compounds in Nanjing, China during high ozone pollution season. CHEMOSPHERE 2021; 263:128025. [PMID: 33297048 DOI: 10.1016/j.chemosphere.2020.128025] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 07/27/2020] [Accepted: 08/11/2020] [Indexed: 06/12/2023]
Abstract
Atmospheric volatile organic compounds (VOCs) are not only harmful to human health, but also lead to ozone (O3) formation. From July 3 to August 1 of 2018, online measurements of atmospheric VOCs were conducted in Nanjing City, in order to investigate the source apportionments to VOCs since the Empirical Kinetic Modelling Approach (EKMA) suggested that O3 formation was VOC-limited at the receptor site. Using positive matrix factorization (PMF) model, we quantified eight sources of VOCs, including vehicle exhausts (23%), industrial source (18%), fuel evaporation (17%), petrochemical industry (12%), solvent usage (12%), biogenic emission (8%) and liquefied petroleum gas (7%) along with gasoline additive (3%). The diurnal distributions showed that the contributions of traffic-related sources maximized during the traffic rush hours. In contrast, biogenic sources had the highest contribution at noontime. Backward trajectory results showed that local traffic emissions were the main sources of VOC in Nanjing. Our results revealed that strict control of VOC emissions from local vehicle exhaust might be an important way to decrease high VOC pollution in Nanjing.
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Affiliation(s)
- Mei-Yi Fan
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yan-Lin Zhang
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Yu-Chi Lin
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Lin Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Feng Xie
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Ahsan Mozaffar
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Fang Cao
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
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Bao Z, Chen L, Li K, Han L, Wu X, Gao X, Azzi M, Cen K. Meteorological and chemical impacts on PM 2.5 during a haze episode in a heavily polluted basin city of eastern China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 250:520-529. [PMID: 31026699 DOI: 10.1016/j.envpol.2019.04.045] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Revised: 03/24/2019] [Accepted: 04/08/2019] [Indexed: 06/09/2023]
Abstract
Haze formation involves many interacting factors, such as secondary aerosol formation, unfavourable synoptic conditions and regional transport. The interaction between these factors complicates scientific understanding of the mechanism behind haze formation. In this study, we investigated the factors resulting in haze events in Longyou, a city located in a basin in China. Aerosol samples of PM2.5 were collected for subsequent chemical composition analysis between 11 January and 5 February 2018. The impacts of wind on PM2.5, SO2 and NO2 concentrations were analysed. Besides, the origin of air parcels and potential sources of PM2.5 were analysed by backward trajectory, potential source contribution function (PSCF) and concentration-weighted trajectories (CWT). Among the water-soluble ions identified, NO3- had the highest concentration, with further analysis demonstrating the haze evolution was mainly driven by the reactions involving NO3- formation. The dramatic increase of nitrate is mainly due to the homogeneous reaction of nitric acid with ammonia, while sulfate is likely due to heterogeneous reactions of NO2, SO2 and NH3. The average wind speed was less than 2 m/s during the aerosol sampling period, which could be considered as a stagnant state. Pollutants emitted by industrial area located in the northeast Longyou were probably brought to observation sites by continuous wind from northeast and accumulated gradually. Air parcels originating from the northeast of Zhejiang province also had large effects on haze pollution in Longyou. Together, our results showed that rapid secondary aerosol formation and unfavourable synoptic conditions are the main factors resulting in haze pollution in Longyou.
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Affiliation(s)
- Zhier Bao
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China
| | - Linghong Chen
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China.
| | - Kangwei Li
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China
| | - Lixia Han
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China
| | - Xuecheng Wu
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China
| | - Xiang Gao
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China
| | - Merched Azzi
- CSIRO Energy, PO Box 52, North Ryde, NSW, 1670, Australia
| | - Kefa Cen
- State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou, 310027, China
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