- Regulatory Inspection and Control Action

2013 ◽  
pp. 52-75
Keyword(s):  
Control Action ◽  
And Control

scholarly journals Long-term trends and drivers of aerosol pH in eastern China

2021 ◽  
Author(s):  
Min Zhou ◽  
Guangjie Zheng ◽  
Hongli Wang ◽  
Liping Qiao ◽  
Shuhui Zhu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Prevention And Control ◽  
Action Plan ◽  
Health Effect ◽  
Eastern China ◽  
Pollution Prevention ◽  
Control Action ◽  
Haze Pollution ◽  
Pollution Prevention And Control ◽  
And Control

Abstract. Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers are crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China. The implementation of the Air Pollution Prevention and Control Action Plan leads to −35.8 %, −37.6 %, −9.6 %, −81.0 % and 1.2 % changes of PM2.5, SO42−, NHx, NVCs and NO3− in YRD during this period. Different from the fast changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH shows a moderate change of −0.24 unit over the 9 years. Besides the multiphase buffer effect, the opposite effects of SO42− and non-volatile cations changes play key roles in determining the moderate pH trend, contributing to a change of +0.38 and −0.35 unit, respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, SO2, NOx and NH3 emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by ~0.9, resulting in 8 % more NO3− and 35 % less NH4+ partitioning/formation in the aerosol phase, which suggests a largely reduced benefit of NH3 and NOx emission control in mitigating haze pollution in eastern China.

Modeling DCS of Nuclear Power Plant With Extended GO-FLOW Methodology

2017 ◽  
Author(s):  
Lu Hongxing ◽  
Yang Ming ◽  
Dai Xinyu ◽  
Li Wei ◽  
Yoshikawa Hidekazu
Keyword(s):  
Control System ◽  
Flow Model ◽  
Modeling Method ◽  
System Structure ◽  
Control Action ◽  
Volume Control ◽  
Flow Modeling ◽  
Control Logic ◽  
And Control ◽  
The Relationship

GO-FLOW model is a success-oriented system modeling method which describes how the system configures its resources to achieve required functions by using basic functional units in terms of substances and demand flows in the system. The GO-FLOW models, which are directly built according to system structure drawings, can be used to analyze the reliability of a system with time and phased mission problems. With the development of Digital Control System (DCS), the reliability analysis of whole DCS has become an important task. However, there are some shortcomings using the traditional GO-FLOW methodology to model DCS: 1. There are not abundant operators in the GO-FLOW model to describe the control logic in DCS; 2. It is hard to model the relationship between the control actions and hardware devices using traditional GO-FLOW methodology; This paper presents an extended GO-FLOW modeling method. In this study, the GO-FLOW model is supplemented and improved, which can accurately describe the relationship and control logic between the hardware and control action (or human control action) in the running process of the DCS. In this paper, taking the Chemical and Volume Control System (CVCS) as an example, using the extended GO-FLOW modeling method established the model of CVCS, and the model of DCS control logic. This improved modeling method can be applied to the reliability modeling and evaluation of DCS.

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