Chemical Plant Research Articles

Study on treatment of chemical plant wastewater by using a integrated anaerobic–aerobic bioreactor

ABSTRACT In this work, a new type of integrated anaerobic aerobic bioreactor (IAAB) was formed by optimizing the structure of the anaerobic baffle bioreactor and aerobic biological contact oxidation pool. IAAB was used to treat the production wastewater of a chemical plant. The whole process was divided into two stages of domestication and stable operation. With increasing the proportion of chemical wastewater, the total amount of extracellular polymeric substances increased, and the ratio of protein to polysaccharide decreased. Dehydrogenase activity of anaerobic granular sludge in each compartment increased about 1.5 times with time, and decreased about 42% along the flow direction from the first compartment to the third compartment. The coenzyme F420 increased about 4 times with time, and increased about 1.2 times along the flow direction. The IAAB showed excellent removal rate of chemical oxygen demand (85%), ammonia nitrogen (94%), nitrobenzenes (98%).

Novel nano-fertilizers derived from drinking water industry waste for sustained release of macronutrients: performance, kinetics and sorption mechanisms

Nanotechnology has emerged as a promising approach for the controlled release of nutrients, particularly phosphorus and potassium. These essential plant nutrients are often applied in excess, leading to environmental pollution and loss of efficiency in crop production. Innovative economic and highly efficient fertilizers are urgently needed to achieve the targeted crop production worldwide in the presence of limited land and water resources. Therefore, in this study, novel, eco-friendly, cost-effective and enhanced efficiency nano-enabled fertilizers, NEF (nWTF1and nWTF2) were synthesized by impregnation of nanostructured water treatment residuals (nWTR) with (KH2PO4 + MgO) at 1:1 and 3:1 (w/w) ratios respectively using a planetary ball mill. The nWTR, nWTF1 and nWTF2 were extensively characterized. The water retention behavior and the sustained release of nutrients from the fabricated nano-enabled fertilizers (nWTF1 and nWTF2) in distilled water and sandy soil were investigated and monitored over time. The water retention capacity of the soil treated with nWTF2 after 26 days was 9.3 times higher than that of soil treated with conventional fertilizer. In addition, the nWTF2 exhibited lower release rates of P, K and Mg nutrients for longer release periods in comparison with the conventional fertilizers. This is a significant advantage over traditional fertilizers, which release nutrients quickly and can lead to leaching and nutrient loss. The main interaction mechanisms of PO4–K–Mg ions with nWTR surface were suggested. The results of the kinetics study revealed that power function was the best suitable model to describe the kinetics of P, K and Mg release data from NEF in water and soil. The produced NEF were applied to Zea maize plants and compared to commercial chemical fertilizer control plants. The obtained results revealed that the nano-enabled fertilizers (nWTF1 and nWTF2) significantly promoted growth, and P content compared with the commercial chemical fertilizer treated plants. The present work demonstrated the power of nano enabled fertilizers as efficient and sustained release nano-fertilizers for sustainable agriculture and pollution free environment.

Review on Factors Affecting Efficiency of Shell and Tube Heat Exchanger

Heat exchanger is one amongst promising thermal device in which heat transfer takes place between hot fluid and cold fluid. Among various classifications of warmth exchangers, the main focus was shown by researchers on indirect contact type compact heat exchangers. Among them the shell and tube device belongs to fluid to fluid type heat transfer device. Main applications of shell and tube device feed device in process industries, refineries, chemical plants and power plants. Usually the analysis of shell and tube heat exchangers are divided into two parts namely shell side and tube side analysis. Shell side analysis is easy and doesn't involve much modification. Whereas the tube side analysis is complex and it's done by varying baffle design and elevation with regard to arrangements of tubes. The most disadvantage of shell and tube device is pressure drop which occur at the end of tubes. To overcome this problem, drilled cylindrical copper block has been introduced to switch the tube part through which the new fluid flows and therefore the cold fluid is circulated through the shell. With this design modification, the effectiveness, mass rate, overall heat transfer co efficient are simulated and analysed.

Exposure of honey bees to mixtures of microbial biopesticides and their effects on bee survival under laboratory conditions.

Biopesticides, having as active ingredients viruses, bacteria, or fungi, are developed to substitute or reduce the use of chemical plant protection products in different agrosystems. Though the application of mixtures containing several products is a common practice, interactions between microbial biopesticides and related effects on bees as non-target organisms have not been studied yet. In the current study, we exposed winter bees to five different microbial-based products and their combinations at the maximum recommended application rate to assess their responses. Laboratory oral exposure tests (acute/chronic) to single or binary products were conducted. Survival and food consumption of the tested bees were evaluated over the experimental duration. Our results show that some product combinations have potential additive or synergistic effects on bees, whereas others did not affect the bee's survival compared to the control. Exposure of tested bees to the most critical combination of products containing Bacillus thuringiensis aizawai ABTS-1857 and B. amyloliquefaciens QST 713 strongly resulted in a median lifespan of 4.5days compared to 8.0 and 8.5days after exposure to the solo products, respectively. The exposure to inactivated microorganisms by autoclaving them did not differ from their respective uncontaminated negative controls, indicating effects on bee mortality might originate in the treatment with the different microorganisms or their metabolites. Further investigations should be conducted under field conditions to prove the magnitude of observed effects on bee colonies and other bee species.

Improved Fault Detection Method based on HSMM

This paper proposes a fault detection method for multivariate statistical process control. The proposed method combines the Forward-Backward Hidden Semi-Markov Model (HSMM) and Principal Component Analysis (PCA). A stochastic automaton was used for multi-mode detection with many observation sequences. We used agglomerative clusters to find the initial parameters of HSMM. We allocated an adaptive threshold and a fixed threshold in each mode for fault detection with PCA, including Hotelling T2 statistic and squared predictive error (Q statistic). We simulated this method on the Tennessee Eastman Process (TEP). Some faults were designed with various runs and times of occurrence. The experimental results were compared with the Mixture Bayesian PCA, Hidden Markov Model (HMM), and HSMM methods. The results are robust with an efficient detection rate. This activity recommends ways to find action plans for multi-mode process monitoring in chemical plants.

Evaluation of Student Perceived Learning Effectiveness and Motivation for a Capstone Design Web-based Virtual Reality Activity

This study reports on the second implementation of a chemical processing plant web-based VR for a fourth-year chemical engineering capstone design course. The web-based VR provides a high fidelity representation of an ampicillin processing facility. To examine the effect of the web-based VR on student motivation and perceived learning effectiveness, a broken plant scenario was developed, and the class was divided into two groups: paper based, and web-based VR. Students completed the scenario in teams, either as a paper-based activity or using the web-based VR. This was followed by completion of an individual tutorial assignment and a survey. Survey findings indicated that students in the web-based VR group had a significantly higher positive response for motivation and perceived learning effectiveness compared to students in the paper-based group. However, students in the paper group scored higher on the individual follow-up assignment. Possible factors contributing to the results are discussed.

Plant geographic distribution influences chemical defences in native and introduced Plantago lanceolata populations

Abstract Plants growing outside their native range may be confronted by new regimes of herbivory, but how this affects plant chemical defence profiles has rarely been studied. Using Plantago lanceolata as a model species, we investigated whether introduced populations show significant differences from native populations in several growth and chemical defence traits. Plantago lanceolata (ribwort plantain) is an herbaceous plant species native to Europe and Western Asia that has been introduced to numerous countries worldwide. We sampled seeds from nine native and 10 introduced populations that covered a broad geographic and environmental range and performed a greenhouse experiment, in which we infested half of the plants in each population with caterpillars of the generalist herbivore Spodoptera littoralis. We then measured size‐related and resource‐allocation traits as well as the levels of constitutive and induced chemical defence compounds in roots and shoots of P. lanceolata. When we considered the environmental characteristics of the site of origin, our results revealed that populations from introduced ranges were characterized by an increase in chemical defence compounds without compromising plant biomass. The concentrations of iridoid glycosides and verbascoside, the major anti‐herbivore defence compounds of P. lanceolata, were higher in introduced populations than in native populations. In addition, introduced populations exhibited greater rates of herbivore‐induced volatile organic compound emission and diversity, and similar chemical diversity based on untargeted analyses of leaf methanol extracts. In conclusion, the geographic origin of the populations had a significant influence on morphological and chemical plant traits, suggesting that P. lanceolata populations are not only adapted to different environments in their native range, but also in their introduced range. Read the free Plain Language Summary for this article on the Journal blog.

Transformation of the Geological Environment under the Influence of Liquid Radioactive Waste (Russian Experience in Studying Historical Nuclear Disposal)

Due to various historical events, in the Russian Federation, in addition to the radioactive waste storage facilities used in world practice, there are various nuclear and radiation hazardous facilities that require special procedures for monitoring and decommissioning. One of these facilities is the disposal site for LRW on the territory of the JSC Siberian Chemical Plant, where specially prepared waste is injected into sand reservoirs lying at depths of 300–350 m between clayey strata. This study examines in detail the features of the lithological and mineral composition of reservoir sands and aquitards. The processes of environmental transformation in reservoir sands, which lead to changes in the composition and structure of rocks, were characterized. These processes manifest themselves in the form of the development of leaching zones and their “healing” with newly formed smectite, the destruction of terrigenous grains, including the development of cracks, and the growth of newly formed smectite in the pore space of reservoirs. The forms of occurrence and localization of authigenic smectite formed as a result of technogenic impact are described. It has been shown that, despite the obvious impact of highly reactive solutions accompanying liquid radioactive waste, the insulating properties of the geological environment are maintained and even improved to some extent.

Circularity assessment in a chemical company. Evaluation of mass-based vs. impact-based circularity

Assessing the circularity of a chemical company can be challenging due to the lack of recorded data on chemical flows. This study evaluates the circularity of solvents in a Swiss chemical plant by analyzing material flows and environmental impacts. The recycling rate and retained environmental value are used as indicators. The company achieved a recycling rate of over 95 %, but the retained environmental value was only about 52 %. Maximizing circularity is not always enough to ensure environmental sustainability. Impact-based metrics are also necessary. This is evidenced by the fact that despite having extremely high mass-based circularity, the retained environmental value is remarkably lower. Since the mass-based circularity is already close to its maximum, additional measures such as using renewable energy for the distillation process or renewable feedstocks for solvent production would be required to further reduce the environmental impact.

Local Instability and Deformation Control of Steel Roof of Factory Building in a Smart City

Abstract The traditional control methods of instability and deformation of steel structure neglect the analysis of its natural vibration characteristics, which lead to the poor effect of hysteretic vibration of steel structure nodes, and the stability optimization of steel structure is not ideal. Therefore, a new method to control the local instability and deformation of the steel roof is proposed. According to the steel structure composition of the upper door rigid frame and the connection mode of the frame beam and column, the roof steel structure characteristics of the workshop are analyzed. Multi-order natural frequency method is used to obtain the cumulative modal mass contribution rate of steel structure and analyze the natural vibration characteristics of steel structure. Based on the characteristics of natural vibration and element transfer matrix, the local instability control method of roof steel structure is designed. Simulation of strong vibration, using space analysis of tall-building with wall-elements (SATWE) software analysis of strong vibration under elastic load state, to obtain the external deformation of steel structure, under simulation of vibration deformation control model. Taking a chemical plant as an example, a finite element model was established to simulate the vibration wave, and the numerical simulation results of plastic deformation resistance of steel structure were analyzed. The experimental results show that the proposed method can effectively enhance the stability of steel structure and reduce its deformation degree.

Integrated Analysis of Per- and Polyfluoroalkyl Substance Exposure and Metabolic Profiling of Elderly Residents Living near Industrial Plants.

Per- and polyfluoroalkyl substances (PFASs) are widely used in industrial production, causing potential health risks to the residents living around chemical industrial plants; however, the lack of data on population exposure and adverse effects impedes our understanding and ability to prevent risks. In this study, we performed screening and association analysis on exogenous PFAS pollutants and endogenous small-molecule metabolites in the serum of elderly residents living near industrial plants. Exposure levels of 11 legacy and novel PFASs were determined. PFOA and PFOS were major contributors, and PFNA, PFHxS, and 6:2 Cl-PFESA also showed high detection frequencies. Association analysis among PFASs and 287 metabolites identified via non-target screening was performed with adjustments of covariates and false discovery rate. Strongly associated metabolites were predominantly lipid and lipid-like molecules. Steroid hormone biosynthesis, primary bile acid biosynthesis, and fatty-acid-related pathways, including biosynthesis of unsaturated fatty acids, linoleic acid metabolism, α-linolenic acid metabolism, and fatty acid biosynthesis, were enriched as the metabolic pathways associated with mixed exposure to multiple PFASs, providing metabolic explanation and evidence for the potential mediating role of adverse health effects as a result of PFAS exposure. Our study achieved a comprehensive screening of PFAS exposure and associated metabolic profiling, demonstrating the promising application for integrated analysis of exposome and metabolome.

Safety attitudes among workers in Malaysian chemical manufacturing plants

AbstractStatistics in Malaysia show that accident cases in the manufacturing industry are the highest compared with other sectors. Concerns regarding changing workers' attitudes, controlling their current perceptions, and installing knowledge and experiences that travel through the culture are necessary. This study investigates workers' attitudes to safety between executives and operators. A total number of 309 respondents voluntarily participated. Results report that respondents' attitude toward individual responsibility (M = 4.24, SD = 0.63) is the highest, followed by the effectiveness of safety arrangements (M = 3.91, SD = 0.81) and safeness of the work environment (M = 3.17, SD = 0.73). Results revealed a significant difference between groups (t = 6.67, p = 0.014) for personal skepticism and (t = 15.775, p = 0.001) for personal immunity. There was a statistically positive correlation between attitudes measured with selected demographic factors. It can be concluded that increases in the level of education were associated with increases in individual responsibility, and an increase in age was directly correlated with increases in the effectiveness of safety arrangements. Furthermore, different groups of workers influence their attitudes toward safety arrangements and safeness of the work environment. This study can be used as a preliminary study or the first step for enhancing an organizational safety culture through behavior and attitude change.

Production of Energy and Hydrogen within Chemical Plants Using Small Nuclear Reactors

The article outlines the possibility of synergistic use of small nuclear reactors and low- and high-temperature electrolysis. The small modular nuclear reactor is compared to common types of renewables. Furthermore, possible small nuclear reactors application in chemical enterprises is shown.

Comprehensive study on air-quality impacts from chemical plant flare emissions under planned or emergency shutdown operations†

Chemical plant shutdown (CPS) operations will employ a flare system to combust waste, unwanted, and off-spec gases dumped from process units to protect the plant safety and the local community. However, the incomplete combustion of flare source under CPS operations including plant planned shutdown (PPS) and plant emergency shutdown (PES) will cause considerable air pollution events. Hitherto, quantitative studies on both primary (CO and NO2) and secondary (ozone) pollutant impacts induced by CPS flaring are still lacking. In this paper, the dynamic effect of flare emissions from two types of CPS (PPS and PES) on ambient air-quality impacts will be systematically and quantitatively studied. The study integrates the dynamic process simulation via Aspen Plus Dynamics with the regional air-quality modelling via Comprehensive Air-quality Model with extensions (CAMx). Case studies indicated that the primary pollutants from flare emissions will be significantly diluted due to the atmospheric transportation, and the maximum concentrations of CO and NO2 can respectively reach 119.0 and 11.0 ppb under PPS, and 47.5 and 4.5 ppb under PES. Meanwhile, the increasing height of the flaring stack will decrease CO and NO2 concentrations but increase the ozone concentration under CPS. Furthermore, CPS in daytime periods will greatly promote ozone generations due to the enhanced photochemical reactions under solar radiation. The maximum 1-hr and 8-hr ozone increment can be 16.6 and 7.1 ppb under PPS while 10.7 and 3.3 ppb under PES, respectively. Besides, the decreasing of flare destruction and removal efficiency will increase ozone and CO under PES.

Eco-efficiency analysis and intensification of the monochlorobenzene separation process through double-effect strategy

Distillation is an energy-intensive operation with high capital and operational costs. For this reason, intensification technologies have been developed to significantly reduce the energy usage, utility costs, and carbon footprint of modern chemical plants. In this work, a double-effect intensification strategy with heat integration was proposed for an industrial-scale monochlorobenzene separation process that can be used in a retrofit design. The conventional process and the intensification configurations were designed by simulation in UniSim software. A utility plant with cooling water and steam generation sections was also considered for realistic results regarding water consumption, CO2 emissions, and utility costs. Additionally, in order to establish a qualitative and quantitative overall analysis, such indicators were grouped in a joint evaluation method using the Comparative Eco-Efficiency Index. The proposed configuration provides savings of 60.15 % and 61.79 % in energy and water consumption, respectively; therefore, savings of 60.15 % and 60.20 % in CO2 emissions and utility costs were achieved, respectively, which increased the process's eco-efficiency by 84.57 % and decreased the TAC criterion by 29.65 %. Thus, the new design prove to be a convenient strategy since it significantly improved the original process performance in alignment with the United Nations’ Sustainable Development Goals.

Conceptual range estimation for total cost of ownership of modular process‐intensified chemical plants

AbstractChemical companies have used modularization to reduce capital costs and project timelines, putting capital to work faster and lowering the risk of entering new markets. Nevertheless, the impacts of using modularization along with advanced technologies, such as process intensification, have not yet been fully realized, often due to the uncertain business risks associated with their implementation. Therefore, new methods are needed for quantifying the impact of modular chemical process intensification (MCPI) on the capital and operating costs of chemical plants to help build a business case for this novel approach. This article presents a new conceptual range estimation technique for total cost of ownership that addresses the deficiencies of existing methods for quantifying MCPI impacts. The incorporation of percentage range estimates was employed to allow for adaptability across various cost and size scales. This work also begins to elucidate how chemical engineering and construction firms can benefit from MCPI and identifies barriers that inhibit MCPI applications in the chemical industry.

Technology for Purifying Gas Emissions of Chemical Plants from Sulfur Dioxide Using Granular Carbonate Sludge

The results of studies on purification of gas emissions (GE) with a granular sorbent based on carbonate sludge from chemical water treatment are presented. The choice of conditions for modifying carbonate sludge with a sodium silicate solution to obtain a granular sorbent has been experimentally substantiated. It is confirmed that the data obtained correspond to and complement the theoretical principles and laws of colloidal and physical chemistry, industrial ecology, which is important for the choice of engineering solutions. A technological scheme for adsorption purification with a regeneration cycle of granular sorption material based on carbonate sludge from the Naberezhnye Chelny CHPP has been developed. It was concluded that the efficiency of GE treatment increased by up to 99% when using the proposed measures. The environmental and economic indicators of the use of the resulting granular sorbent in the scheme for purifying GE from SO2 in production of sodium hydrosulfite have been calculated. The prevented environmental harm to the environment from the use of the proposed technology has been determined, as well as the cost of production of granular sorption material and the payback period.

Total Capital Investment of plastic recycling plants correlates with energy losses and capacity.

Plastic pollution is a generational problem, and stakeholders are turning to chemical recycling as a potential solution. However, decision-makers necessitate quick and reliable capital investment estimations to evaluate innovative technologies, especially in the early project stage, when limited historical data are available. To address this need, we built a database of 160+ chemical recycling plants, querying for nominal capacity, year and place of construction, total capital investment (TCI), number of long-term jobs and opportunity of subsidies. Then, we compared conventional association of the advancement of cost engineering AACE class 5 estimation methods, with literature estimates, and commercial capital expenditure confidence intervals for pyrolysis, gasification, solvolysis, and selective dissolution. We demonstrate the unreliability of classic methods, and we propose ballpark correlations based on the plant capacity, or the energy loss. Chemical recycling plants suffer from poor economy of scale (with current technologies), and capacity is not always the best indicator for TCI estimation. Pyrolysis and gasification are energy-driven technologies, and their TCI correlates very well (R2 =0.91-0.92) with the total energy losses. Solvolysis and selective dissolution, instead, are at an earlier development stage, so cost engineers or researchers will have to accept less certain TCI vs capacity (R2 =0.60).

Artificial intelligence-based forecasting model for incinerator in sulfur recovery units to predict SO2 emissions

Pollutant emissions from chemical plants are a major concern in the context of environmental safety. A reliable emission forecasting model can provide important information for optimizing the process and improving the environmental performance. In this work, forecasting models are developed for the prediction of SO2 emission from a Sulfur Recovery Unit (SRU). Since SRUs incorporate complex chemical reactions, first-principle models are not suitable to predict emission levels based on a given feed condition. Accordingly, artificial intelligence-based models such as standard machine learning (ML) algorithms, multi-layer perceptron (MLP), long short-term memory (LSTM), one-dimensional convolution (1D-CNN), and CNN-LSTM models were tested, and their performance was evaluated. The input features and hyperparameters of the models were optimized to achieve maximum performance. The performance was evaluated in terms of mean squared error (MSE) and mean absolute percentage Error (MAPE) for 1 h, 3 h and 5 h ahead of forecasting. The reported results show that the CNN-LSTM encoder-decoder model outperforms other tested models, with its superiority becoming more pronounced as the forecasting horizon increased from 1 h to 5 h. For the 5-h ahead forecasting, the proposed model showed a MAPE advantage of 17.23%, 4.41%, and 2.83%, respectively over the 1D-CNN, Deep LSTM, and single-layer LSTM models in the larger dataset.

A self-regulated network for dynamically balancing multiple precursors in complex biosynthetic pathways

Microbial synthesis has emerged as a promising and sustainable alternative to traditional chemical synthesis and plant extraction. However, the competition between synthetic pathways and central metabolic pathways for cellular resources may impair final production efficiency. Moreover, when the synthesis of target product requires multiple precursors from the same node, the conflicts of carbon flux have further negative impacts on yields. In this study, a self-regulated network was developed to relieve the competition of precursors in complex synthetic pathways. Using 4-hydroxycoumarin (4-HC) synthetic pathway as a proof of concept, we employed an intermediate as a trigger to dynamically rewire the metabolic flux of pyruvate and control the expression levels of genes in 4-HC synthetic pathway, achieving self-regulation of multiple precursors and enhanced titer. Transcriptomic analysis results additionally demonstrated that the gene transcriptional levels of both pyruvate kinase PykF and synthetic pathway enzyme SdgA dynamically changed according to the intermediate concentrations. Overall, our work established a self-regulated network to dynamically balance the metabolic flux of two precursors in 4-HC biosynthesis, providing insight into balancing biosynthetic pathways where multiple precursors compete and interfere with each other.