Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Nonlinearity Strength Indicators for Numerical Simulation Based Load Reduction-Water Quality Responses
SU Han, ZOU Rui, LIANG Zhongyao, YE Rui, WANG Zhiyun, LIU Yong
Acta Scientiarum Naturalium Universitatis Pekinensis    2023, 59 (4): 695-703.   DOI: 10.13209/j.0479-8023.2023.036
Abstract157)   HTML    PDF(pc) (799KB)(83)       Save
This study developed four nonlinearity strength indicators for water quality responses based on cross sample entropy, Fourier transformation, non-sequence counting, and adjusted R2 according to typical nonlinear load reduction-water quality responses suggested by previous studies. All the indicators were applied on typical numerical water quality simulation samples. Based on the calculation, the four indicators were compared with each other to provide suggestions on how to use them to detect the nonlinearity and measure the nonlinearity strength. Results show some overlaps among the four indicators, however, they are not interchangeable. The four indicators suggest seasonal differences, peak changes, short-term water quality deterioration, and averaged water quality changes respectively. After providing suggestions on how to use the four indicators to detect nonlinearity of water quality responses, this study further discusses the limitations on the nonlinearity definition and potential applications of the four indicators. This study will contribute to understanding, distinguishing, and analyzing the type of nonlinear water quality responses.
Related Articles | Metrics | Comments0
Object-Oriented Precise Decision-Making (OOPD) for Water Quality Improvementin Lake Yilong
ZOU Rui, SU Han, YU Yanhong, WANG Junsong, YE Rui, LIU Yong
Acta Scientiarum Naturalium Universitatis Pekinensis    2018, 54 (2): 426-434.   DOI: 10.13209/j.0479-8023.2017.164
Abstract999)   HTML2)    PDF(pc) (2337KB)(452)       Save

A framework called Object-Oriented Precise Decision-making (OOPD) was proposed which oriented to the lake itself. The framework was based on Numerical Source Apportionment powered by 3-dimensional water quality model, which then quantified the causality of water quality improvement and load reduction. The proposed framework was applied to support short-term decision making of Lake Yilong, a eutrophic lake. Results showed that Chenghe sub-watershed and Chengbeihe sub-watershed were important pollution source no matter considering which monitoring station and under which water diversion scenario. In addition, comprehensive pollution control should be considered to ensure that Huzhong monitoring station or Hudong monitoring station meet water quality standards. However, considerable load reduction cannot guarantee water quality if there was no water diversion. Water quality of three monitoring stations would be improved a lot under 20 and 30 million m³ annual water diversion scenario. Finally, based on the analyses above, suggestion of focused pollution control project was given for each sub-watershed and an evaluation of one bean product wastewater treatment extension project was given to illustrate how to combine micro and macro aspects in OOPD.

Related Articles | Metrics | Comments0
Chemical Characters and Sources Identification of PM_10 in Guangzhou Area
CUI Mingming,WANG Xuesong,SU Hang,ZHANG Yuanhang
Acta Scientiarum Naturalium Universitatis Pekinensis   
Abstract610)            Save
PM10 samples were collected from seven sites in Gua ngzhou area and associated chemical species including seventeen elements(Na, Mg,Al, K, Ca, Ti, V, Mn, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, and Pb), five water solub le ions(SO2-, NO-, F-,Cl- and NH4+) ,and organic an d elemental carbons were a nalyzed. This paper discusses chemical characters, the changes of PM10 and maincomponents under different meteorological conditions, and also sources identification of PM10 by principal factor analysis. The results indicated that the averagePM10 concentration was 125.8μg/m3 and organic matter, sulfate and crustal dustwere maj or components with proportions of 24%-32% ,17%-21% and 10%-12%, respective ly in the seven sites. Principal factor analysis indicated that soil dust, oil burning, industry source(including metallurgy, chemistry and electric industry), coalburning, secondary source (by photochemical reaction) and biomass burning were t he main sources of PM10, accounting for 20.7%, 17.8%, 16.3%, 14.3%, 10.4%, and 6.3%, respectively of the total variance in the data set.
Related Articles | Metrics | Comments0
Current Status of Nitrogen Oxides Related Pollution in China and Integrated Control Strategy
ZHOU Wei,WANG Xuesong ,ZHANG Yuanhang,SU Hang,LU Keding
Acta Scientiarum Naturalium Universitatis Pekinensis   
Abstract538)            Save
Current status of nitrogen oxides-related pollution in China was analyzed, including NOx pollution and the related pollution of ozone, acid rain,particulate matter. Then the NOx and related air quality standards were reviewed. Finally, strategy for integrated and multi-target control of NOx pollution were put forward: executing ozone air quality standard, establishing the regional photochemical smog monitoring network; pursuing air quality modeling and control for Beijing, Pearl River Delta etc megacities; strengthening the control of NOx emission from power station and vehicles and setting NOx-related scientific research program.
Related Articles | Metrics | Comments0
Adjoint Model of Atmospheric Chemistry Transport Model CAMx: Construction and Application
LIU Feng,ZHANG Yuanhang,SU Hang,HU Jianlin
Acta Scientiarum Naturalium Universitatis Pekinensis   
Abstract809)            Save
Based on the atmospheric chemistry transport model CAMx, its adjoint model is constructed. The adjoint model code is hand-generated and numerical experiments are designed to test and validate the code. CAMx and its adjoint model are applied for simulation and sensitivity analysis of air pollution in the Pearl River Delta. The sensitivities of high ground level sulfur dioxide and ozone respect to pollutant sources are calculated, and the applicability of linear sensitivity coefficients is discussed through numerical experiments, which provide important information for extensive analysis of pollution mechanisms and control strategies. Using the adjoint model, the sensitivities of an object function respect to thousands of input variables can be calculated efficiently. With the introduction of the adjoint method, the function of CAMx is considerably extended, and provides a powerful tool for inverse problems on emission parameters as well as for management of atmospheric environment.
Related Articles | Metrics | Comments0