Possibility of Carbon Dioxide Sequestration by Catch Crops

Pawłowska, Małgorzata; Pawłowski, Artur; Pawłowski, Łucjan; Cel, Wojciech; Wójcik-Oliveira, Katarzyna; Kwiatkowski, Cezary A.; Harasim, Elżbieta; Wang, Lei

doi:10.1515/eces-2019-0046

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…Rising concerns for balanced development triggered various institutions supervising the quality of the environment to implementation of innovative solutions for the reduction of working costs and energy. Statistical and numerical methods are more commonly applied for environmental research i. a. for the comparison of empirical data [1,2] modelling of cavitation erosion process [3,4,5] modelling processes in sewage treatment plants [6], monitoring chemical processes inside reactors [7], or for models of pollution forecasting, such as, quality indoor air [8], the number of produced waste [9].…”

Section: Introductionmentioning

confidence: 99%

Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

Kulisz

Kujawska

2021

J. Phys.: Conf. Ser.

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The aim of this paper is to present the potential of using neural network modelling for the prediction of the surface water quality index (WQI). An artificial neural network modelling has been performed using the physicochemical parameters (TDS, chloride, TH, nitrate, and manganese) as an input layer to the model, and the WQI as an output layer. The physicochemical parameters have been taken from five measuring stations of the river Warta in the years 2014-2018 via the Chief Inspectorate of Environmental Protection (GIOŚ). The best results of modelling were obtained for networks with 5 neurons in the hidden layer. A high correlation coefficient (general and within subsets) 0.9792, low level of MSE in each subset (training, test, validation), as well as RMSE at a level of 0.624507639 serve as a confirmation. Additionally, the maximum percentage of an error for WQI value did not exceed 4%, which confirms a high level of conformity of real data in comparison to those obtained during prediction. The aforementioned results clearly present that the ANN models are effective for the prediction of the value of the Surface water quality index and may be regarded as adequate for application in simulation by units monitoring condition of the environment.

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Section: Introductionmentioning

confidence: 99%

Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

Kulisz

Kujawska

2021

J. Phys.: Conf. Ser.

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“…Waste is generally characterized by diverse and unbalanced properties, which in natural management may reduce their fertilization efficiency. In such a case, it is justified to combine the wastes, thanks to which the properties of the created composite are optimized [5][6][7]. Such activities regarding drilling waste were undertaken in the research carried out as part of the project "Optimization of drilling waste management methods", the aim of which was to use drilling spoil to produce a composite that meets the properties of an agent improving the properties of poor quality soil and useful for soil reconstruction in devastated areas.…”

Section: Introductionmentioning

confidence: 99%

Innovative Technologies for the Use of Drilling Waste in Reclamation and Shaping the Physicochemical Properties of Degraded Soils

Bik-Małodzińska¹,

Żukowska²,

Paśmionka³

2023

Adv. Sci. Technol. Res. J.

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This paper presents an evaluation of the use of drilling tailings in reclamation and development of physical and chemical properties of degraded soils. Composites with drilling wastes and other wastes, useful for the reclamation of degraded soils and their reconstruction in devastated areas, were used in the tests. Comparative objects were anthropogenic soil fertilized with NPK and manure at a dose of 30 Mg/ha + NPK. The research shows that the tested anthropogenic soil was characterized by very poor sorption properties, and especially the composites with the participation of the tested waste improved the described properties. The composite with sewage sludge from ZA Puławy had a more favorable (by approx. 20%) effect on the sorption capacity of the reclaimed anthropogenic soil than the composite with municipal sewage sludge from Lublin. The effect of the tested composites on reducing the hydrolytic acidity of the reclaimed soil was similar, but much more favorable than that of manure. The results of the conducted research confirmed that drilling wastes have environmentally valuable properties, but due to their unbalance, they should not be used alone, but in composites with properly selected other wastes, such as manure or sewage sludge.

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“…The soils of EU-27 Member States are estimated to store round 73 to 79•10 15 g (billion tonnes) of carbon, which is more than 50 times the anthropogenic emissions of the 27 Member States of the European Union in 2009 year [1]. An especially dramatic growth in the CO 2 emission from pollution sources occurred after 1956, reaching the value of 36.8 Pg CO 2 /yr in 2017 [2]. Air pollution is considered as one of the main factors affecting the health of the population.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Total Organic Carbon Quantity and Emissions of CO₂ from Soil Into the Atmosphere Near Street

Pranskevičius¹,

Paliulis²

2021

Ecological Chemistry and Engineering S

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Soil as an ecosystem is actively involved into climate formation process. Therefore, it is important to assess such soil quality indicators as total organic carbon (TOC) and CO2 emissions. Soil organic matter is considered to be its indicator of quality, which is one of the most important components of biosphere consistency and stability. Soil respiration shows carbon emission from soil into the atmosphere. This is a great indicator, illustrating soil biological activity. Impact of soil temperature, air humidity, time of day was evaluated on CO2 emission from the soil. The highest CO2 emission is observed in afternoon hours, up to 0.201 g CO2∙m–2·h–1.

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Possibility of Carbon Dioxide Sequestration by Catch Crops

Cited by 4 publications

References 22 publications

Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

Innovative Technologies for the Use of Drilling Waste in Reclamation and Shaping the Physicochemical Properties of Degraded Soils

Evaluation of Total Organic Carbon Quantity and Emissions of CO₂ from Soil Into the Atmosphere Near Street

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Possibility of Carbon Dioxide Sequestration by Catch Crops

Cited by 4 publications

References 22 publications

Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

Innovative Technologies for the Use of Drilling Waste in Reclamation and Shaping the Physicochemical Properties of Degraded Soils

Evaluation of Total Organic Carbon Quantity and Emissions of CO2 from Soil Into the Atmosphere Near Street

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Product

Resources

About

Evaluation of Total Organic Carbon Quantity and Emissions of CO₂ from Soil Into the Atmosphere Near Street