Efficiency modeling of serial stabilization ponds in treatment of phenolic wastewater by response surface methodology

Qaderi, Farhad; Sayahzadeh, A H; Azizpour, F.; Vosughi, P.

doi:10.1007/s13762-018-1816-6

Cited by 20 publications

(5 citation statements)

References 37 publications

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“…One of the most important factors in the deterioration of soil physical and chemical properties is human activities such as mining, industry, agriculture, transport, and waste disposal [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Contamination level and risk assessment of heavy metals in the topsoil around cement factory: A case study

Amiri

Daneshvar²,

Azadi

2021

Environmental Engineering Research

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The cement industry is considered as a major source of heavy metals pollution in topsoil. This study aims at measuring the heavy metal contamination level in the vicinity of Shiraz cement factory, and assessing the ecological and environmental risks associated with the factory's activities in the surrounding topsoil. To do so, 10 samples of soil were taken from around the Shiraz cement factory at the depth of 0-10 cm and the concentration of some heavy metals including Al, Cd, Ni, and Pb was measured. Enrichment factor (EF), geo-accumulation (Igeo), and pollution load (PLI) indices were used to assess the ecological risk of heavy metals.Based on the results, the mean concentration of Al, Ni, Cd, and Pb was 6,937.14, 88.09, 1.96, and 30.74 mg/kg, respectively. The EF results showed that due to anthropogenic activities, the Ni, Pb, and Cd element has moderate, severe, and very severe enrichment in the study area, respectively. The Igeo result for Al, Ni, Pb, and Cd was -0.82, -0.17, 0.16, and 0.68, respectively, which indicates non- to slightly pollution of these heavy metals in this region. The mean PLI in the study area was 1.4 indicating the low to medium pollution of heavy metal. The results of this study can be useful in determining and investigating the environmental effects of Shiraz cement factory.

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Section: Introductionmentioning

confidence: 99%

Contamination level and risk assessment of heavy metals in the topsoil around cement factory: A case study

Amiri

Daneshvar²,

Azadi

2021

Environmental Engineering Research

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“…Modeling of environmental phenomena have been studied many times. Response surface methodology is one of the most used methods in environmental studies [5,8,14,31,33,34,53,54]. Statistical methods have many advantages compared with the traditional ones due to the rapid calculations and the identification of relationships between effective factors.…”

Section: Methodology Of Experiments Planning To Evaluate the Concrete Mixing Planmentioning

confidence: 99%

Optimizing the tensile strength of concrete containing coal waste considering the cost

Khataei

Nasrollahi

2019

SN Appl. Sci.

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Nowadays, removal of the waste from industrial activities is one of the serious problems in the world. Contrarily, needing the development of industrial construction and reduce its costs, with considering the construction quality, are the main priorities of progress. Therefore, in this paper, for the first time, all these issues are considered related to using the waste of coal extraction; also, the application of coal wash rejects in the concrete manufacture and its impact on tensile strength of concrete have been investigated. To this goal, coal waste was prepared from the Central Alborz Coal Preparation Plant in northern Iran. Designing the experiments by the response surface methodology (RSM), the influence of parameters like water/cement (0.4-0.6), cement content (305-445 kg/m 3 ), aggregate volume (0.4-0.6%) and coal waste (0.5-9.75%) on the tensile strength to cost of concrete construction were evaluated. Presenting the model, optimizing and investigating the individual, reciprocal and simultaneous effects of independent variables on the tensile strength to cost of concrete by RSM were conducted for the first time. Based on the results of tensile strength tests and estimating the cost of concrete construction, the highest ratio of tensile strength to cost was obtained by using the cement content of 340 kg/m 3 , water/cement of 0.45, gravel volume of 0.55% and coal waste of 7.5%. In this case, the response value was 1.29E−6 MPa/USD. These results indicate the high potential of these wastes in the production of concrete in terms of tensile strength and also economic aspect.

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“…In some previous researches, the data have been investigated or normalized before modeling in order to reaching to the best optimization or prediction [29][30][31]. Some parameters affecting the CO concentration change in different seasons, such as rainfall, temperature and moisture, and since data is recorded on a daily basis, data input is normalized to help training of artificial neural network.…”

Section: Data Normalizationmentioning

confidence: 99%

Determining Effective Parameters on CO Concentration in Tehran Air by Sensitivity Analysis based on Neural Network Prediction

Qaderi¹,

Babanezhad²,

Ghadi³

2019

J. Model. Optim.

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One of the most toxic pollutant gases produced by fossil fuels is carbon monoxide. Hence, the accurate and regular estimation and control of CO in the cities such as Tehran is inevitable. In this research, for the first time, CO concentration in ambient air was predicted based on 12 important urban and meteorological parameters by neural network. Also, the sensitivity analysis of the factors that effect on the concentration of carbon monoxide in Tehran was investigated based on the pollutant concentration predictive model. In this research, the daily statistical data of Tehran metropolis over the course of five consecutive years from 12 factors affecting the amount of carbon monoxide in Tehran, such as population, density, precipitation, temperature, urban traffic, wind speed, gasoil consumption, moisture, air flow, effective vision and air pressure was used. Based on this database, the artificial neural network with the best possible algorithm had been trained to predict this contaminant and root mean square error of model was equal to 2.54. Then, sensitivity analysis was done to find the most effective factor on the concentration of carbon monoxide, urban density and air pressure. In order to control this hazardous contaminant in urban management, these parameters should be taken into account. Based on the result, by preventing the construction of high towers in Tehran, wind speed average will increase and increasing in wind speed (25%) caused to reducing in carbon monoxide concentration (about 12%). Also, prevention of urban density (25%) will cause to prevention of increasing CO concentration (about 10%).

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Efficiency modeling of serial stabilization ponds in treatment of phenolic wastewater by response surface methodology

Cited by 20 publications

References 37 publications

Contamination level and risk assessment of heavy metals in the topsoil around cement factory: A case study

Contamination level and risk assessment of heavy metals in the topsoil around cement factory: A case study

Optimizing the tensile strength of concrete containing coal waste considering the cost

Determining Effective Parameters on CO Concentration in Tehran Air by Sensitivity Analysis based on Neural Network Prediction

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