Historical Perspective of Bisphenol A and Phthalates in the Environment and Their Health Effects

Author(s):  
Rayees Ahmad Bhat ◽  
D. Kumar ◽  
Sajood Maqbool Bhat ◽  
Irfan Rashid Sofi

Plastics are widely used in modern life, and their unbound chemicals Bisphenol A and Phthalates, which are important chemical-building blocks, can leach out into the surrounding environment. They are also ubiquitous contaminants in the human body, wildlife, and the environment. BPA and PAEs have recently attracted the special attention of the scientific community, regulatory agencies, and the general public because of their high-production volume, widespread use of plastics, and endocrine-disrupting effects.

Dose-Response ◽  
2015 ◽  
Vol 13 (3) ◽  
pp. 155932581559830 ◽  
Author(s):  
Jone Corrales ◽  
Lauren A. Kristofco ◽  
W. Baylor Steele ◽  
Brian S. Yates ◽  
Christopher S. Breed ◽  
...  

Because bisphenol A (BPA) is a high production volume chemical, we examined over 500 peer-reviewed studies to understand its global distribution in effluent discharges, surface waters, sewage sludge, biosolids, sediments, soils, air, wildlife, and humans. Bisphenol A was largely reported from urban ecosystems in Asia, Europe, and North America; unfortunately, information was lacking from large geographic areas, megacities, and developing countries. When sufficient data were available, probabilistic hazard assessments were performed to understand global environmental quality concerns. Exceedances of Canadian Predicted No Effect Concentrations for aquatic life were >50% for effluents in Asia, Europe, and North America but as high as 80% for surface water reports from Asia. Similarly, maximum concentrations of BPA in sediments from Asia were higher than Europe. Concentrations of BPA in wildlife, mostly for fish, ranged from 0.2 to 13 000 ng/g. We observed 60% and 40% exceedences of median levels by the US Centers for Disease Control and Prevention’s National Health and Nutrition Examination Survey in Europe and Asia, respectively. These findings highlight the utility of coordinating global sensing of environmental contaminants efforts through integration of environmental monitoring and specimen banking to identify regions for implementation of more robust environmental assessment and management programs.


2006 ◽  
Vol 40 (5) ◽  
pp. 1573-1580 ◽  
Author(s):  
Jasper V. Harbers ◽  
Mark A. J. Huijbregts ◽  
Leo Posthuma ◽  
Dik van de Meent

2012 ◽  
Vol 120 (12) ◽  
pp. 1631-1639 ◽  
Author(s):  
Patricia L. Bishop ◽  
Joseph R. Manuppello ◽  
Catherine E. Willett ◽  
Jessica T. Sandler

2006 ◽  
pp. 1-19
Author(s):  
Richard Hefter ◽  
Barbara Leczynski ◽  
Charles Auer

Author(s):  
Rishi K. Malhan ◽  
Yash Shahapurkar ◽  
Ariyan M. Kabir ◽  
Brual Shah ◽  
Satyandra K. Gupta

Using fixtures for assembly operations is a common practice in manufacturing processes with high production volume. For automated assembly cells using robotic arms, trajectories are programmed manually and robots follow the same path repeatedly. It is not economically feasible to build fixed fixtures for small volume productions as they require high accuracy and are part specific. Moreover, hand coding robot trajectories is a time consuming task. The uncertainties in part localization and inaccuracy in robot motions make it challenging to automate the task of assembling two parts with tight tolerances. Researchers in past have developed methods for automating the assembly task using contact-based search schemes and impedance control-based trajectory execution. Both of these approaches may lead to undesired collision with critical features on the parts. Our method guarantees safety for parts with delicate features during the assembly process. Our approach enables us to select optimum impedance control parameters and utilizes a learning-based search strategy to complete assembly tasks under uncertainties in bounded time. Our approach was tested on an assembly of two rectangular workpieces using KUKA IIWA 7 manipulator. The method we propose was able to successfully select the optimal control parameters. The learning-based search strategy successfully estimated the uncertainty in pose of parts and converged in few iterations.


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