Optimization and Selection of Automatic Monitoring Indicators in Beer Manufacturing

Article Preview

Abstract:

Automatic monitoring indicators system of pollution is the key and foundation to construct network of pollutions in total amount monitoring.Scientific and reasonable indicators system can reflect pollutant situation and influence on water environment.Automatic monitoring indicators in pollution of sources are confined to COD and ammonia nitrogen as well as short of monitoring indicators to character features of pollutional sources.It is necessary to conduct optimization and selection of automatic monitoring indicators.Based on beer manufacturing in demonstration area as the research object,analyze sources of pollution in Qinghe basin producing and sewage situation;adopt screening methods to complete optimization and selection of automatic monitoring indicators.Build the system of automatic monitoring indicators in beer manufacturing successfully to provide theoretical support for constructing network of water pollutant total amount monitoring.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

795-799

Citation:

Online since:

July 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Technical Specifications Requirements for Monitoring of Surface Water and Waste Water HJ/T-2002. State Environmental Protection Administration, (2003).

Google Scholar

[2] Hairong Wang, Study on Rural Environment Quality Composite Evaluation Models,. Taiyuan: Taiyuan University of Technology, (2011).

Google Scholar

[3] Licai Wang. Study of Hayi Gas Industry Sudden Water Pollution Accident Risk Assessment-Emergency Response System,. Harbin: Harbin Institute of Technology, (2010).

Google Scholar

[4] Yi Cai. Principal Component Method in the Application of the Comprehensive Evaluation,. China Statistcs, (2005).

Google Scholar

[5] Xiaoqiu Chen. Disscussing on the Filtering Method of Prior Controlled Organic Pollutants in Water,. Fujian Analysis Testing, 2006, 15(1).

Google Scholar

[6] Mingyu Fan. Study on Comparison and Technical Model of Domestic and Overseas Urban Water Environment Indicator Systems,. Chongqing: ChongqingUniversity, (2011).

Google Scholar

[7] Jinsong Guo. Research on Artifficial Neural Networks(ANN) for Water Quality Assessment and Simulation,. Chongqing: Chongqing University, (2002).

Google Scholar

[8] Ping Yuan. The Security Risk Assessment of Command Automation Information Net work Based on Multiple Indexes Synthetic Evaluation,. Beijing: Qinghua University, (2008).

Google Scholar

[9] Saaty. The Analytic Hierarchy Process: Planning Priority Setting, ResourceAllocation. NewYork: McGrarw-Hill, (1980).

Google Scholar

[10] Feng Yan . OCTVE and FAHP Based on The Information System of Risk Assessment Model,. Chongqing: Chongqing Normal University, (2011).

Google Scholar

[11] Xikang Wu. East China University. Organic Compounds Compiled Environmental Data SummaryTable (2009).

Google Scholar