Introducing an application method for industries air pollutants emission control planning by preparing environmental flow diagram maps

Eslami, Siamak; Sekhavatjou, Mohammad Sadegh

doi:10.1016/j.jclepro.2018.01.071

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…For the evacuated Belarusians, the Gy estimates were 1-4.3, 1 and 0.68 Gy, respectively. These studies showed an important inverse correlation between 131I dose to the thyroid and age at exposure [36].…”

Section: Analysis Of the Impact Of Radionuclides On The Environment A...mentioning

confidence: 90%

Disposal methods for radioactive waste from nuclear power plants and environmental radiation monitoring methods

Shchipalkina,

Smirnova

2023

E3S Web Conf.

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Air pollution has a serious impact on human health. Deterioration of the air environment causes 7 million premature deaths annually. Despite the active implementation of various environmental programmes and technical resources aimed at preserving and protecting the environment from anthropogenic factors, over 90% of the world's population live in cities that do not meet the air quality recommendations of the World Health Organisation (WHO). Intense and constant technogenic load necessitates continuous monitoring of atmospheric air quality. Sufficient, systematic and representative information is needed to study the spatial and temporal distribution of substances in the air basin, to predict pollution levels and to make correct environmental decisions. Environmental monitoring is a tool for obtaining such information. In this work the analysis of influence of radioactive waste of nuclear power plants on a radiation level of environment is executed and the tasks of its ecological monitoring in areas of location of the enterprises of nuclear power industry are considered.

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Section: Analysis Of the Impact Of Radionuclides On The Environment A...mentioning

confidence: 90%

Disposal methods for radioactive waste from nuclear power plants and environmental radiation monitoring methods

Shchipalkina,

Smirnova

2023

E3S Web Conf.

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“…(2) Industrial air pollutants: The mean AQI includes O 3 , PM 10 , PM 2.5 , NO 2 , SO 2 , and CO concentrations (Tan et al, 2021). In addition to the six pollutants used as air quality indicators, industrial pollutants include other pollutants, and NO x , SO 2 , PMs, CO, and CO 2 are the most commonly released substances [66]. Based on the industrial monitoring station (Table 4), we found that PM 2.5 , PM 10 , O 3 , SO 2 , CO, NO x , and NO 2 impact air quality, and these pollutants were listed in [19,66].…”

Section: (A) Finding Air Pollutantsmentioning

confidence: 99%

“…In addition to the six pollutants used as air quality indicators, industrial pollutants include other pollutants, and NO x , SO 2 , PMs, CO, and CO 2 are the most commonly released substances [66]. Based on the industrial monitoring station (Table 4), we found that PM 2.5 , PM 10 , O 3 , SO 2 , CO, NO x , and NO 2 impact air quality, and these pollutants were listed in [19,66]. From the PM 10 forecast of the Mailiao dataset (Table 8), AR(p) = 11.55 indicates the best performance, showing that the industrial air pollutant PM 10 has nothing to do with climatic factors and related pollutants but is only related to its own lag period.…”

Section: (A) Finding Air Pollutantsmentioning

confidence: 99%

An Intelligent Time Series Model Based on Hybrid Methodology for Forecasting Concentrations of Significant Air Pollutants

Cheng

Tsai

2022

Atmosphere

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Rapid industrialization and urban development are the main causes of air pollution, leading to daily air quality and health problems. To find significant pollutants and forecast their concentrations, in this study, we used a hybrid methodology, including integrated variable selection, autoregressive distributed lag, and deleted multiple collinear variables to reduce variables, and then applied six intelligent time series models to forecast the concentrations of the top three pollution sources. We collected two air quality datasets from traffic and industrial monitoring stations and weather data to analyze and compare their results. The results show that a random forest based on selected key variables has better classification metrics (accuracy, AUC, recall, precision, and F1). After deleting the collinearity of the independent variables and adding the lag periods using the autoregressive distributed lag model, the intelligent time-series support vector regression was found to have better forecasting performance (RMSE and MAE). Finally, the research results could be used as a reference by all relevant stakeholders and help respond to poor air quality.

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Systematic energy and exergy assessment of a hydropurification process: Theoretical and practical insights

Azarpour

Mohamadi‐Baghmolaei

Hajizadeh

et al. 2022

Energy

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Introducing an application method for industries air pollutants emission control planning by preparing environmental flow diagram maps

Cited by 3 publications

References 7 publications

Disposal methods for radioactive waste from nuclear power plants and environmental radiation monitoring methods

Disposal methods for radioactive waste from nuclear power plants and environmental radiation monitoring methods

An Intelligent Time Series Model Based on Hybrid Methodology for Forecasting Concentrations of Significant Air Pollutants

Systematic energy and exergy assessment of a hydropurification process: Theoretical and practical insights

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