Determination of thermal pollution of water resources caused by Neka power plant through processing satellite imagery

Yavari, Seyed Mehdi; Qaderi, Farhad

doi:10.1007/s10668-018-0272-2

Cited by 19 publications

(6 citation statements)

References 32 publications

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“…Supporting infrastructure for urbanization also causes negative thermal impacts. Examples of direct sources of thermal pollution include wastewater treatment plant discharge from standard treatment practices (Kinouchi et al 2007; Laszewski 2018) and effluent from power plants, such as nuclear facilities (Walker 1989; Webb 1996; Prats et al 2010; Kirillin et al 2013; Yavari and Qaderi 2020). Even traditional SWM practices such as shallow lakes (Pluhowski 1970; Booth et al 2014) and detention basins (Jones and Hunt 2010) increase downstream temperatures due to heat absorption during impoundment.…”

Section: Introductionmentioning

confidence: 99%

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Chen

Hodges²,

Dymond

2020

J American Water Resour Assoc

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Stream ecosystems are increasingly at risk for thermal impairment as urbanization intensifies, resulting in more heated runoff from impervious cover that is less likely to be cooled naturally. While several best management practices, including bioretention filters, have been able to reduce thermal pollution, success has been limited. The extent of thermal mitigation required to prevent ecological damage remains unknown. A calibrated runoff temperature model of a case study watershed in Blacksburg, VA was developed to determine the cumulative treatment volume of bioretention filters required to reduce thermal impacts caused by runoff from development in the watershed to regulated biologically acceptable levels. A future build out scenario of the study watershed was also analyzed. Results from this study established that runoff thermal pollution cannot be fully reduced to goal thresholds during all storms using bioretention filter retrofits. While retrofitting significantly decreased temperatures and heat exports relative to the controls, increasing treatment volumes did not really enhance mitigation. Alternate thermal mitigation methods that actively remove runoff volume should be considered where more thermal mitigation is required.

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Section: Introductionmentioning

confidence: 99%

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Chen

Hodges²,

Dymond

2020

J American Water Resour Assoc

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“…On the other hand, rapid development of construction industries and consuming the natural resources have led to reduction of natural resources and environmental degradation by various ways. Therefore, many efforts have been made focusing on by-products and industrial wastes in order to protect the natural resources [3,4,12,17,26,29,32,43,44,57]. For example, reducing the use of construction materials by applying the industrial wastes in concrete is a positive step towards sustainable development [15].…”

Section: Introductionmentioning

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 the past researches, the effect of different parameters on the dependent environmental variables have been investigated [16][17][18][19][20][21]. A lot of studies were conducted on sensitivity analysis to determine the effect of each parameter.…”

Section: Introductionmentioning

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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Determination of thermal pollution of water resources caused by Neka power plant through processing satellite imagery

Cited by 19 publications

References 32 publications

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

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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