Aerobic biostabilization of the organic fraction of municipal solid waste-monitoring hot and cold spots in the reactor as a novel tool for process optimization

The process of aerobic biostabilization (AB) has been adopted for treatment of the organic fraction of municipal solid waste (OFMSW). However, thermal gradients and some side effects in the bioreactors present difficulties in optimization of AB. Forced aeration is more effective than natural ventilation of waste piles, but “hot and cold spots” exist due to inhomogeneous distribution of air and heat. This study identified the occurrence of hot and cold spots during the OFMSW biostabilization process at full technical scale. It was shown that the number of hot and cold spots depended on the size of the pile and aeration rate. When the mass of stabilized waste was significantly lower and the aeration rate was two-fold higher the number of anaerobic hot spots decreased, while cold spots increased. In addition, the results indicated that pile construction with sidewalls decreased the number of hot spots. However, channelizing the airflow under similar conditions increased the number of cold spots. Knowledge of the spatial and temporal distribution of process gases can enable optimization and adoption of the OFMSW flow aeration regime. Temperature monitoring within the waste pile enables the operator to eliminate undesirable “hot spots” by modifying the aeration regime and hence improve the overall treatment efficiency

Modeling of CO Accumulation in the Headspace of the Bioreactor during Organic Waste Composting

Advanced technologies call for composting indoors for minimized impact on the surrounding environment. However, enclosing compost piles inside halls may cause the accumulation of toxic pollutants, including carbon monoxide (CO). Thus, there is a need to assess the occupational risk to workers that can be exposed to CO concentrations \u3e 300 ppm at the initial stage of the process. The objectives were to (1) develop a model of CO accumulation in the headspace of the bioreactor during organic waste composting and (2) assess the impact of headspace ventilation of enclosed compost. The maximum allowable CO level inside the bioreactor headspace for potential short-term occupational exposure up to 10 min was 100 ppm. The composting was modeled in the horizontal static reactor over 14 days in seven scenarios, differing in the ratio of headspace-to-waste volumes (H:W) (4:1, 3:1, 2:1, 1:1, 1:2, 1:3, 1:4). Headspace CO concentration exceeded 100 ppm in each variant with the maximum value of 36.1% without ventilation and 3.2% with the daily release of accumulated CO. The airflow necessary to maintain CO \u3c 100 ppmv should be at least 7.15 m3·(h·Mg w.m.)−1. The H:W \u3e 4:1 and the height of compost pile \u3c 1 m were less susceptible to CO accumulation

A Breakthrough Application of a Cross-Linked Polystyrene Anion-Exchange Membrane for a Hydrogencarbonate Ion-Selective Electrode

Polystyrene cross-linked with divinylbenzene and functionalized by a quaternary ammonium cation anion site is used as the membrane of a hydrogencarbonate (i.e., bicarbonate) ion-selective electrode. The polystyrene matrix membrane improves the selectivity towards interfering lipophilic ions in comparison to previously described polyvinyl chloride membranes. The reason for this behaviour is sought in coupled ion-exchange and pore-diffusion processes in the membrane and the resulting kinetic discrimination of interfering ions. The electrode is successfully used for determination of bicarbonates in mineral drinking waters. The simplex method is employed to refine the analytical outcome

Rehydration of the Tendon Fascicle Bundles Using Simulated Body Fluid Ensures Stable Mechanical Properties of the Samples

In this work, we investigate the influence of dehydration and subsequent rehydration of tendon fascicle bundles on their structural and mechanical properties by using distilled water, 0.9% NaCl, 10% NaCl, SBF, and double concentrated SBF (SBFx2). The properties of tendon fascicle bundles were investigated by means of uniaxial tests with relaxation periods and hysteresis for samples with various interfascicular matrix content, dissected from the anterior and posterior areas of bovine tendon. Uniaxial tests with relaxation periods and analysis of sample geometry and weight showed that dehydration alters the modulus of elasticity dependent on the interfascicular matrix content and influences the viscoelastic properties of tendon fascicle bundles. Tensile and relaxation tests revealed that changes resulting from excessive sample drying can be reversed by rehydration in an SBF bath solution for elastic strain range above the toe region. Rehydration in SBF solution led to minor differences in mechanical properties when compared to control samples. Moreover, anterior samples with greater interfascicular matrix content, despite their lower stiffness, are less sensitive to sample drying. The obtained results allow us to limit the discrepancies in the measurement of mechanical properties of wet biological samples and can be useful to researchers investigating soft tissue mechanics and the stability of transplant materials

Active learning for automatic classification of complaints about municipal waste management

Information flow is an important issue in the area of waste management. There is a need for a fast response to reported problems. Therefore we investigated the classification process of Polish wasterelated complaints sent by Wrocław’s residents. It has been noticed that residents, mostly without expert knowledge of waste management, incorrectly classify the observed problems. In response to the observed unacceptable classification accuracy, we introduced a multi-class machine learning classification. Machine learning is widely used in waste management issues like predicting waste generation or different waste fractions identification for automated sorting. However, based on the literature review, it can be stated that there is a lack of solutions in machine learning-based text classification regarding waste management. Ten chosen classifiers were used to classify considered complaints into defined categories automatically. Additionally, we incorporated the active learning approach to reduce experts' effort involved in the labeling process, which is necessary when having an unlabeled dataset. The results confirm the possibility of applying machine learning algorithms to waste-related Polish complaints

Prevalence of Dietary Behavior and Determinants of Quality of Diet among Beneficiaries of Government Welfare Assistance in Poland

Diet, as a modifiable factor for good health maintenance, reduces the risk of numerous non-communicable chronic diseases and prevents premature death. The aim of the study was to examine the prevalence of a dietary behavior and to find out what the determinants of diet quality among the low socio-economic status population are. The studied sample consisted of 1710 respondents. Only 3% of the beneficiaries had healthy dietary habits. Unhealthy dietary habits dominated in all the study group regardless of the subjects’ level of education (p < 0.001). Higher odds of unhealthy dietary habits were reported among the respondents with primary, vocational, and secondary education than among the respondents with high education (for the primary education OR = 11.10; 95% CI: 5.86⁻21.01; p ≤ 0.001; for vocational education OR = 10.54; 95% CI: 5.79⁻19.18; p ≤ 0.001 and for secondary education OR = 5.83; 95% CI: 3.48⁻9.79; p ≤ 0.001). The unhealthy dietary behavior prevalence among beneficiaries of government welfare assistance in Poland is much higher than in the general population. Since only educational level is a determinant which is significantly correlated with the unhealthy dietary behavior, promotion of a healthy diet among disadvantaged individuals should be focused on this factor

A 3D Scanning System for Inverse Analysis of Moist Biological Samples: Design and Validation Using Tendon Fascicle Bundles

In this article, we present the design and validation of a non-contact scanning system for the development of a three-dimensional (3D) model of moist biological samples. Due to the irregular shapes and low stiffness of soft tissue samples, the use of a non-contact, reliable geometry scanning system with good accuracy and repeatability is required. We propose a reliable 3D scanning system consisting of a blue light profile sensor, stationary and rotating frames with stepper motors, gears and a five-phase stepping motor unit, single-axis robot, control system, and replaceable sample grips, which once mounted onto the sample, are used for both scanning and mechanical tests. The proposed system was validated by comparison of the cross-sectional areas calculated based on 3D models, digital caliper, and vision-based methods. Validation was done on regularly-shaped samples, a wooden twig, as well as tendon fascicle bundles. The 3D profiles were used for the development of the 3D computational model of the sample, including surface concavities. Our system allowed for 3D model development of samples with a relative error of less than 1.2% and high repeatability in approximately three minutes. This was crucial for the extraction of the mechanical properties and subsequent inverse analysis, enabling the calibration of complex material models

Modeling of CO Accumulation in the Headspace of the Bioreactor during Organic Waste Composting

Advanced technologies call for composting indoors for minimized impact on the surrounding environment. However, enclosing compost piles inside halls may cause the accumulation of toxic pollutants, including carbon monoxide (CO). Thus, there is a need to assess the occupational risk to workers that can be exposed to CO concentrations > 300 ppm at the initial stage of the process. The objectives were to (1) develop a model of CO accumulation in the headspace of the bioreactor during organic waste composting and (2) assess the impact of headspace ventilation of enclosed compost. The maximum allowable CO level inside the bioreactor headspace for potential short-term occupational exposure up to 10 min was 100 ppm. The composting was modeled in the horizontal static reactor over 14 days in seven scenarios, differing in the ratio of headspace-to-waste volumes (H:W) (4:1, 3:1, 2:1, 1:1, 1:2, 1:3, 1:4). Headspace CO concentration exceeded 100 ppm in each variant with the maximum value of 36.1% without ventilation and 3.2% with the daily release of accumulated CO. The airflow necessary to maintain CO 3·(h·Mg w.m.)−1. The H:W > 4:1 and the height of compost pile This article is published as Sobieraj, K., S. Stegenta-Dabrowska, J. A. Koziel, and A. Białowiec. "Modeling of CO Accumulation in the Headspace of the Bioreactor during Organic Waste Composting." Energies 14, no. 5 (2021): 1367. DOI: 10.3390/en14051367. Posted with permission.</p