Prediction of Wastewater Emission in China

2014 ◽  
Vol 955-959 ◽  
pp. 2667-2672 ◽  
Author(s):  
Yi Shu Kong ◽  
Xiu Li Liu
Keyword(s):  
Factor Analysis ◽  
Chemical Industry ◽  
Value Added ◽  
Haihe River Basin ◽  
Haihe River ◽  
Processing Industry ◽  
Positive Effects ◽  
Unit Value ◽  
Water Conservancy ◽  
Very High

A model to predict the wastewater emission in China was established with comprehensive factor analysis, combining the ARMA and OLS methods. Applied the model, the wastewater emission from 2013 to 2015 in China was predicted. Industry characteristics of wastewater emission between the whole nation and Haihe River basin were analyzed using the 1999 and 2002 water conservancy input-occupancy-output (IOO) tables. The results showed that the national wastewater emission of 2013-2015 will reach 72998, 76897 and 81071 million tons respectively, and industries like paper printing and educational goods manufacturing, chemical industry, discharged a large amount of wastewater and their wastewater emission by unit value added were also very high. In the meantime, wastewater by unit value added of metal smelting and rolling processing industry went down largely from 1999 to 2002, which revealed that the strict supervision had positive effects on reducing wastewater emission.

Hydro-ecological impact of water conservancy projects in the Haihe River Basin

2012 ◽  
Vol 44 ◽  
pp. 67-74 ◽  
Author(s):  
Shanlong Lu ◽  
Bingfang Wu ◽  
Hao Wang ◽  
Ninglei Ouyang ◽  
Shuying Guo
Keyword(s):  
River Basin ◽  
Ecological Impact ◽  
Haihe River Basin ◽  
Haihe River ◽  
Water Conservancy ◽  
The Haihe River Basin

Long-term variation of water vapor content and precipitation in the Haihe river basin

2014 ◽  
Vol 6 (2) ◽  
pp. 341-351 ◽  
Author(s):  
Chun Chang ◽  
Ping Feng ◽  
Fawen Li ◽  
Yunming Gao
Keyword(s):  
Water Vapor ◽  
River Basin ◽  
Reanalysis Data ◽  
Water Vapor Content ◽  
Haihe River Basin ◽  
Haihe River ◽  
Annual Water ◽  
Environmental Prediction ◽  
High Consistency ◽  
The Haihe River Basin

Based on the Haihe river basin National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data from 1948 to 2010 and the precipitation data of 53 hydrological stations during 1957–2010, this study analyzed the variation of water vapor content and precipitation, and investigated the correlation between them using several statistical methods. The results showed that the annual water vapor content decreased drastically from 1948 to 2010. It was comparatively high from the late 1940s to the late 1960s and depreciated from the early 1970s. From the southeast to the northwest of the Haihe river basin, there was a decrease in water vapor content. For vertical distribution, water vapor content from the ground to 700 hPa pressure level accounted for 72.9% of the whole atmospheric layer, which indicated that the water vapor of the Haihe river basin was mainly in the air close to the ground. The precipitation in the Haihe river basin during 1957–2010 decreased very slightly. According to the correlation analysis, the precipitation and water vapor content changes showed statistically positive correlation, in addition, their break points were both in the 1970s. Furthermore, the high consistency between the precipitation efficiency and precipitation demonstrates that water vapor content is one of the important factors in the formation of precipitation.

scholarly journals Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu
Keyword(s):  
Temporal Variation ◽  
River Basin ◽  
Spatial And Temporal Variation ◽  
Haihe River Basin ◽  
Temperature Threshold ◽  
Threshold Method ◽  
Exponential Equation ◽  
Haihe River ◽  
The Haihe River Basin ◽  
Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

Do older workers really reduce firm productivity?

2018 ◽  
Vol 29 (4) ◽  
pp. 521-542 ◽  
Author(s):  
Bokwon Lee ◽  
Joowoong Park ◽  
Jae-Suk Yang
Keyword(s):  
Older Workers ◽  
Value Added ◽  
Manufacturing Firms ◽  
Future Research ◽  
Organisational Performance ◽  
Jel Codes ◽  
Positive Effects ◽  
Financial Conditions ◽  
Negative Effect ◽  
Growing Conditions

In this article, we examine the effect of workforce ageing on company productivity, using an analysis based on Korean firms. We found that an increase in the ratio of workers aged over 50 years to total workers had a negative effect on value added per worker, which was consistent with the findings of most previous studies based on European data. However, the results of the analysis, including various classifications such as size, industry and several financial conditions, revealed that an increase in the ratio of older workers had positive effects on value added per worker in large manufacturing firms under risky or growing conditions. As the productivity of older workers may vary, future research may determine under what conditions – size, industry, region and financial conditions – older workers contribute positively to productivity. Firms with financial troubles or those planning to downsize should be cautious about laying off older workers as an approach to improving organisational performance because these workers contribute positively to productivity under certain conditions. JEL Codes: J24, J54, N3

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