The relationship between maritime phosphate pollution and socioeconomic wellbeing

Phosphate rock reserves are expected to deplete in the next 50-100 years, with the point of highest phosphorus production predicted to be in 2030. Phosphate, the base of many fertilizers, is a non-renewable resource. Ocean phosphate concentrations provide a good indication of global fertilizer use, since agricultural runoff often contributes to increases in ocean phosphate concentration. This study explores the relationship between the concentration of phosphate in a nation’s maritime borders and the nation’s score on the Social Progress Index. The study aims to link findings with possible approaches to help meet two of the United Nations’ (UN) Sustainable Development Goals: creating sustainable communities, and conserving and sustainably using oceans. Phosphate concentration data were acquired from the National Oceanic and Atmospheric Administration and compared with factors of social welfare from the 2018 Social Progress Index. For each nation on the Social Progress Index, the nation’s score on every factor was separately compared to ocean phosphate concentration data within that nation’s maritime borders, and a linear regression was performed for each comparison. The results indicate countries ranking higher on the Social Progress Index generally have greater ocean phosphate concentrations, suggesting that countries of higher social welfare contribute more to global phosphate use or have greater amounts of fertilizer runoff. The findings should be considered by developed nations to inform decisions around pollution reduction as well as developing nations aiming for sustainable social progress. Both should consider the environmental effects that social progress has or will have on the greater global community, of which the significance to sustainable resource development and environmental protection is invaluable.

On methods of modifying natural minerals

Recently, more and more attention is paid to the ecological safety of the republic due to the increased threat of environmental pollution by radionuclides, particularly by uranium, while the processing of uranium-containing raw materials generates a significant amount of liquid industrial waste. The main waste disposal method is a sorption, which requires the use of inexpensive sorbents. Such sorbents can be obtained on the basis of domestic natural raw materials. The significant disadvantages of natural sorbents are a low sorption capacity, which can be increased by developing effective and relatively cheap methods for their modification. The absence of the methods of modification is a limiting factor for the widespread using of natural sorbents for environmental purposes. Variants of modification of natural aluminosilicate and coal-mineral raw materials of Kazakhstan by physical and chemical methods are considered. The chemical methods include the modification with a mixture of tributylphostat and di-2-ethylhexylphosphoric acid in kerosene to obtain "solid-phase extractants", a mixture of phosphoric acid and polyacrylamide, and the synthesis of organominerals. The possibility of using technogenic raw materials as a modifying reagent has been studied. Zeolite of the previously unexplored Kosmurun deposit and shungite of the Koksu deposit were selected for research, and slags of phosphorus production were selected as a technogenic raw materials. Their physical and chemical properties have been studied.

Intelligent Control System Architecture for Phosphorus Production from Apatite-Nepheline Ore Waste

This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat and polymodal information, and control goals differ at different levels not only in effectiveness criteria, but also in the structuredness of the level problems. On this basis, it is proposed that intelligent methods be used for the implementation of information processes and control goals at individual levels and the whole system. The artificial intelligence methods underlying the informational model of a control system offer solutions to problems of analyzing control processes at different hierarchy levels, namely the initial level of sensing devices, the levels of programmable logic controllers, dispatching of control and production processes, enterprise management and strategic planning. Besides, the intelligent control system architecture includes analytical and simulation models of processes occurring in the multistage procedure of ore waste processing by a plant consisting of a granulating machine, a conveyor-type multichambercalcining machine, and an ore thermal furnace. The architecture of information support for the control system comprises a knowledge-based inference block intended for implementing the self-refinement of neural network and simulation models. Fuzzy logic methods are proposed for constructing this block. The paper considers the deployment of control algorithms for a phosphorus production system using the Matlab software environment on the basis of a modern complex system development paradigm known as the model-oriented design concept.

RISK-BASED PROFESSIONAL HEALTH PROGRAM FOR WORKERS IN THE CHEMICAL INDUSTRY

В работе представлены результаты исследования по формированию риск-ориентированной программы профилактики профессиональной интоксикации у рабочих основных профессий фосфорного производства. Показано, что в процессе трудовой деятельности у рабочих фосфорного производства появляются донозологические и нозологические признаки профессионального поражения органов и систем организма, которые возникают от негативного действия пыле - и газообразных токсических соединений фосфора. В зависимости от степени выраженности выделены группы риска, и соответственно рекомендованы индивидуальные и групповые программы профилактики. The paper presents the results of the study on the formation of a risk-oriented program for the prevention of occupational intoxication among workers of the main professions of phosphorus production. It is shown that in the process of labor activity, workers of phosphorus production develop prenosological and nosological signs of occupational damage to organs and systems of the body, which arise from the negative effect of dust and gaseous toxic phosphorus compounds. Depending on the severity, risk groups are identified, and, accordingly, individual and group prevention programs are recommended.

Energy and Resource Efficiency in Apatite-Nepheline Ore Waste Processing Using the Digital Twin Approach

The paper presents a structure of the digital environment as an integral part of the “digital twin” technology, and stipulates the research to be carried out towards an energy and recourse efficiency technology assessment of phosphorus production from apatite-nepheline ore waste. The problem with their processing is acute in the regions of the Russian Arctic shelf, where a large number of mining and processing plants are concentrated; therefore, the study and creation of energy-efficient systems for ore waste disposal is an urgent scientific problem. The subject of the study is the infoware for monitoring phosphorus production. The applied study methods are based on systems theory and system analysis, technical cybernetics, machine learning technologies as well as numerical experiments. The usage of “digital twin” elements to increase the energy and resource efficiency of phosphorus production is determined by the desire to minimize the costs of production modernization by introducing advanced algorithms and computer architectures. The algorithmic part of the proposed tools for energy and resource efficiency optimization is based on the deep neural network apparatus and a previously developed mathematical description of the thermophysical, thermodynamic, chemical, and hydrodynamic processes occurring in the phosphorus production system. The ensemble application of deep neural networks allows for multichannel control over the phosphorus technology process and the implementation of continuous additional training for the networks during the technological system operation, creating a high-precision digital copy, which is used to determine control actions and optimize energy and resource consumption. Algorithmic and software elements are developed for the digital environment, and the results of simulation experiments are presented. The main contribution of the conducted research consists of the proposed structure for technological information processing to optimize the phosphorus production system according to the criteria of energy and resource efficiency, as well as the developed software that implements the optimization parameters of this system.