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Investigation and calibration of thermal and salinity layering in surface water resources using Ce-Qual-W2 model

Tzu-Chia Chen Shu-Yan Yu Chang-Ming Wang Sen Xie Hanif Barazandeh
Journal of Water and Land Development | 2021 | No 51 | 117-123 | DOI: 10.24425/jwld.2021.139021
Keywords Ce-Qual-W2 model salinity surface water thermal layering water quality modelling water resources
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Abstract

In the discussion of water quality control, the first and most effective parameter that affects other variables and water quality parameters is the temperature situation and water temperature parameters that control many ecological and chemical processes in reservoirs. Additionally, one of the most important quality parameters studied in the quality of water resources of dams and reservoirs is the study of water quality in terms of salinity. The salinity of the reservoirs is primarily due to the rivers leading into them. The control of error in the reservoirs is always considered because the outlet water of the reservoirs, depending on the type of consumption, should always be standard in terms of salinity. Therefore, in this study, using the available statistics, the Ce-Qual-W2 two-dimensional model was used to simulate the heat and salinity layering of the Latyan Dam reservoir. The results showed that with warming and shifting from spring to late summer, the slope of temperature changes at depth increases and thermal layering intensifies, and a severe temperature difference occurs at depth. The results of sensitivity analysis also showed that by decreasing the wind shear coefficient (WSC), the reservoir water temperature increases, so that by increasing or decreasing the value of this coefficient by 0.4, the average water temperature by 0.56°C changes inversely, and the results also show that by increasing or decreasing the value of the shade coefficient by 0.85, the average water temperature changes by about 7.62°C, directly.
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Bibliography

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Authors and Affiliations

Tzu-Chia Chen
1
ORCID: ORCID
Shu-Yan Yu
1
Chang-Ming Wang
1
Sen Xie
1
Hanif Barazandeh
2
  1. International College, Krirk University, Bangkok, 3 Ram Inthra Rd, Khwaeng Anusawari, Khet Bang Khen, Krung Thep Maha Nakhon 10220, Thailand
  2. Ferdowsi University of Mashhad, Iran

The improvement of Beijing ambient air quality resulting from the upgrade of vehicle emission standards

Chang Wang Xiaohan Miao Maodong Fang Yuan Chen Taosheng Jin
Archives of Environmental Protection | 2024 | 50 | 3 | 109-121 | DOI: 10.24425/aep.2024.151690
Keywords emission standards; response surface model (RSM); environmental improvement; ozone (O3); particulate matter (PM):
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Abstract

To investigate the effects and improvements of tightening vehicle emission standards from China Ⅲ to China Ⅴ on ozone (O3) and particulate matter (PM) pollution in the atmospheric environment, this study obtained emission factors of O3 and PM precursors such as nitrogen oxides (NOx), volatile organic compounds (VOCs), and primary PM from gasoline and diesel vehicles through actual testing. Response surface models (RSM) were then created for the environmental concentrations of the target pollutants O3 (RSM-O3_HSS6-200) and PM (RSMPM_HSS9-300) as functions of precursor pollutant emissions. Beijing was chosen as the main receptor region, with the China Ⅲ emission standard serving as the baseline scenario and the China Ⅳ and Ⅴ standards as control scenarios. The results indicate that as vehicle emission standards tightened from China Ⅲ to China Ⅳ and Ⅴ, O3 concentrations in Beijing's environment decreased from 92.7 ppbv to 78.47 ppbv and 72.20 ppbv, respectively, while PM concentrations decreased from 64.12 μg/m3 to 48.23 μg/m3 and 38.60 μg/m3, respectively. Furthermore, the environmetal benefits achieved from China Ⅲ to China Ⅳ were higher than those from China Ⅳ to China Ⅴ. Additionally, an analysis of pollutant source contributions revealed that NOx played a major role in reducing O3 concentrations, while primary PM was crucial in controlling PM pollution.
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Authors and Affiliations

Chang Wang
1
Xiaohan Miao
1
Maodong Fang
2
Yuan Chen
1
Taosheng Jin
1
  1. Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
  2. National Engineering Laboratory for Mobile Source Emission Control Technology, China Automotive Technology and Research Center Co., Ltd., Tianjin 300300, China

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