Environmental profile analysis of particleboard production: a study in a Pakistani technological condition

2017 ◽  
Vol 23 (8) ◽  
pp. 1542-1561 ◽  
Author(s):  
Majid Hussain ◽  
Riffat Naseem Malik ◽  
Adam Taylor
CERNE ◽  
2014 ◽  
Vol 20 (3) ◽  
pp. 409-418 ◽  
Author(s):  
Cassiano Moro Piekarski ◽  
Antonio Carlos de Francisco ◽  
Leila Mendes da Luz ◽  
Tiago Henrique de Paula Alvarenga ◽  
Juliana Vitoria Messias Bittencourt

The main goal of this study was to analyze the environmental profile of MDF panel manufacturing in the Brazilian industry in terms of energy, emissions and dependence on renewable sources. The study was conducted by using the methodology of Life Cycle Assessment (LCA), specifically through the development of the first Life Cycle Inventory (LCI) of MDF in a Brazilian industry. The life cycle inventory and the production processes analysis were constructed using Umberto® v.5.6 software and following the ISO 14040 series. The study covers the life cycle of MDF production from gate-to-gate perspective, involving the on-site manufacturing system. The functional unit was defined in 1 m³ of MDF. About 76% of energy required to produce MDF is thermal (52.8% of thermal energy is required for the drying process of wood fiber). CO2 is a major emission during the MDF production, where natural gas contributes to 96.7% of total CO2 fossils. It was observed a low dependence of non-renewable source (19.2%) compared with the literature.


1994 ◽  
Vol 13 (6) ◽  
pp. 1003-1009 ◽  
Author(s):  
Beverly J. Sauer ◽  
Carol C. Hildebrandt ◽  
William E. Franklin ◽  
Robert G. Hunt

Author(s):  
S.F. Corcoran

Over the past decade secondary ion mass spectrometry (SIMS) has played an increasingly important role in the characterization of electronic materials and devices. The ability of SIMS to provide part per million detection sensitivity for most elements while maintaining excellent depth resolution has made this technique indispensable in the semiconductor industry. Today SIMS is used extensively in the characterization of dopant profiles, thin film analysis, and trace analysis in bulk materials. The SIMS technique also lends itself to 2-D and 3-D imaging via either the use of stigmatic ion optics or small diameter primary beams.By far the most common application of SIMS is the determination of the depth distribution of dopants (B, As, P) intentionally introduced into semiconductor materials via ion implantation or epitaxial growth. Such measurements are critical since the dopant concentration and depth distribution can seriously affect the performance of a semiconductor device. In a typical depth profile analysis, keV ion sputtering is used to remove successive layers the sample.


Crisis ◽  
2020 ◽  
Vol 41 (4) ◽  
pp. 288-295 ◽  
Author(s):  
Nadia Bounoua ◽  
Jasmeet P. Hayes ◽  
Naomi Sadeh

Abstract. Background: Suicide among veterans has increased in recent years, making the identification of those at greatest risk for self-injurious behavior a high research priority. Aims: We investigated whether affective impulsivity and risky behaviors distinguished typologies of self-injurious thoughts and behaviors in a sample of trauma-exposed veterans. Method: A total of 95 trauma-exposed veterans (ages 21–55; 87% men) completed self-report measures of self-injurious thoughts and behaviors, impulsivity, and clinical symptoms. Results: A latent profile analysis produced three classes that differed in suicidal ideation, suicide attempts and nonsuicidal self-injury (NSSI): A low class that reported little to no self-injurious thoughts or behaviors; a self-injurious thoughts (ST) class that endorsed high levels of ideation but no self-harm behaviors; and a self-injurious thoughts and behaviors (STaB) class that reported ideation, suicide attempts and NSSI. Membership in the STaB class was associated with greater affective impulsivity, disinhibition, and distress/arousal than the other two classes. Limitations: Limitations include an overrepresentation of males in our sample, the cross-sectional nature of the data, and reliance on self-report measures. Conclusion: Findings point to affective impulsivity and risky behaviors as important characteristics of veterans who engage in self-injurious behaviors.


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