Valorization of petroleum refinery oil sludges via anaerobic co-digestion with food waste and swine manure.

Valorization of oil sludge has been gaining attention to improve the sustainability of the petroleum industry. This study aimed to assess the possibility of anaerobic co-digestion of oil scum and secondary sludge with food waste (or swine manure). Oil scum and secondary sludge were obtained from a wastewater treatment plant (WWTP) of a petrochemical plant. Physicochemical properties, hazardous materials, and microbial community were characterized and biochemical methane potential was performed by a simplex-lattice mixture design. More than 87% (wet wt.) of the oil scum consisted of total petroleum hydrocarbons (TPHs) (21,762 mg/L) that are difficult to be degraded by anaerobes. The secondary sludge showed low TPHs (5 mg/L) and a bacterial community similar to that of municipal WWTPs. The heavy metal (Cu, As, Cr, Ni, Mn, Zn, and V) concentrations in the oil scum and secondary sludge were similar (20-600 mg/L). The maximum methane potentials of the oil sludge and secondary sludges were 20 ± 2 and 56 ± 3 mL CH4/g-volatile solid, respectively. The co-digestion with food waste or swine manure led to a synergy effect on methane production of the co-digestion substrate (10-40% increase compared to the calculated value; v/v) by balancing the C/N ratio. Due to the high TPH contents, oil scum is not appropriate for co-digestion. The co-digestion of secondary sludge with food waste and/or swine manure is recommended. It is necessary to consider whether the concentration of heavy metals is at a level that inhibits the anaerobic co-digestion depending on the operating conditions such as mixing ratios and solid contents.

Evaluation of error inducing factors in unmanned aerial vehicle mounted detector to measure fugitive methane from solid waste landfill.

Many methods have been applied to monitor fugitive methane gas from landfills. Recently, there have been suggestions to use a framework utilizing an unmanned aerial vehicle (UAV) for landfill gas monitoring, and several field campaigns have proved that a rotary UAV-based measurement has advantages of ease of control and high-resolution concentration mapping on the target planes. However, research on the evaluation of error-inducing factors in the suggested system is limited so far. This study prepared a measurement system with a lightweight methane detector and a rotary UAV to support the applicability of rotary UAV in landfill gas monitoring. Then, the validity of the system was tested experimentally and theoretically. In the detector reliability test, the methane detector had sufficient resolution for field application. The critical UAV velocity required was obtained to ensure the credibility of the proposed measurement system. When spatial interpolators were applied to field data from the measurement system, the empirical Bayesian kriging demonstrated the best prediction of methane concentrations at unmeasured points. With the verifications provided in this study, this proposed method may contribute to reducing uncertainty in estimating fugitive landfill gas emission.

Data stratification toward advanced flood waste estimation: A case study in South Korea.

Flood waste management is important for reducing the damage and secondary environmental pollution caused by delays in disaster recovery. One key issue related to flood waste management concerns estimating the precise quantity of waste to plan recovery strategies and policies. In this study, an advanced flood waste estimation technique was devised using data stratification. In total 90 flood cases in South Korea were sorted by three strata characteristics: administrative region (AR; equivalent to special city or province), urbanization rate (UR), and disaster type and coastal accessibility (DC). According to the results, such data stratification led to flood waste prediction improvement not only by the single-stage stratification but also by successive stratifications. Data stratification was effective both for identifying groups with similar contexts and for eliminating disparities in the dataset that impede accurate waste prediction. Among the stratification sequences tested, the order resulted in the most improvement in flood waste prediction was UR, AR, and DC. This stratification order yielded enhanced waste prediction in 74 cases. Since this study deals with a strategy to resolve gaps in disaster data, which is a crucial issue in many countries, it is envisaged that this strategy can be transferred to other countries.

Bayesian approach in estimating flood waste generation: A case study in South Korea.

Accurate estimations of flood waste generation are a crucial issue in disaster waste management. Multilinear regression of related parameters has been recognized as a promising technique for flood waste estimation. There are two types of flood waste estimation methods: pre-event predictions using factors related to regional properties and rainfall hazards, and post-event predictions using damage variables due to floods, such as the number of damaged buildings. Previous attempts to establish these models used deterministic approaches; however, probabilistic methods have never been applied. Considering the large degrees of uncertainty in waste generation from floods, a probabilistic approach can provide a more accurate model compared to models developed by the conventional deterministic approach. This study applied Bayesian inference to develop a flood waste regression model in South Korea. The aims of the study are as follows: (1) to analyze the characteristics of coefficients estimated by the Bayesian approach; (2) evaluate the performance of the prediction model by Bayesian inference; and (3) assess the effectiveness of Bayesian updating in a flood waste estimation. According to the results, the coefficients obtained via Bayesian inference showed a more significant p-value compared to those developed through the deterministic approach. Bayesian inference with a null prior distribution was effective in error reduction, specifically for post-event prediction. Bayesian updating did not effectively increase the accuracy of the model, while iterative updating required a complex calculation process. These results reveal the potential of the Bayesian approach in flood waste estimations, which can be transferred to other countries.

Oxidation resistance of nanoscale zero-valent iron supported on exhausted coffee grounds.

In this study, nanoscale zero-valent iron (NZVI) was supported by exhausted coffee grounds. Exhausted coffee grounds are a crucial waste generated in enormous amounts. Since supported nanoscale particles have a lower free energy than bare particles, oxidation resistance of supported NZVI on coffee grounds (NZVI-Coffee ground) is postulated. The main aim of this study was to ascertain the enhanced oxidation resistance of NZVI-Coffee ground. Synthesized materials were dried and stored in the air at temperatures of 4, 20, and 35 °C. Changes in the surface characteristics and cadmium removal efficiency of the supported NZVI were investigated. Fourier transformation infrared spectroscopy and X-ray photoelectron spectroscopy showed that supported NZVI underwent less oxidation compared to bare NZVI. Cadmium removal efficiencies of supported NZVI did not deteriorate with age, while those of bare NZVI decreased by 9.5 ±â€¯0.1, 13.0 ±â€¯0.1, and 18.3 ±â€¯0.2% compared to their initial removal efficiencies when stored 8 weeks at 4, 20, and 35 °C, respectively. This is because the surface free energy of the NZVI decreased via strong interaction with the functional groups of the coffee grounds. According to the results, exhausted coffee grounds are an effective supporting material for NZVI to enhance its storage stability.

Removal of aqueous-phase Pb(II), Cd(II), As(III), and As(V) by nanoscale zero-valent iron supported on exhausted coffee grounds.

Nanoscale zero-valent iron (NZVI) is recognized as an excellent adsorbent for metallic contaminants. Nevertheless, NZVI itself tends to agglomerate, so that its performance deterioriates without supporting materials. The use of exhausted coffee grounds as a supporting material for NZVI is expected to resolve this problem and provide the social benefits of waste minimization and resource recycling. In this study, NZVI was supported on exhausted coffee grounds (NZVI-Coffee ground) to enhance its dispersion. The aims of this study were to characterize NZVI-Coffee ground with a focus on atomic dispersion, evaluate NZVI-Coffee ground as an adsorbent for typical metallic contaminants and arsenic, and assess the effects of solution chemistry on the adsorption process. In order to achieve these goals, characterization, adsorption kinetics, adsorption equilibrium, and the effects of pH and temperature on adsorption were studied. Pb(II), Cd(II), As(III), and As(V) were selected as target contaminants. The characterization study showed that atomic dispersion was enhanced four-fold by supporting NZVI on coffee grounds. The enhanced dispersion resulted in rapid kinetic characteristics and large adsorption capacity. The optimum pH for adsorption of Pb(II) and Cd(II) was 4-6, and that for As(III) and As(V) was 2-4. The pH effect can be explained by surface protonation/deprotonation and adsorbate speciation. Only the adsorption of Pb(II) was an exothermic process; those of other species were endothermic. In every tested case, the adsorption process was spontaneous. According to the results, NZVI-Coffee ground is an effective adsorbent for the removal of aqueous phase Pb(II), Cd(II), As(III), and As(V).

Innovation of flux chamber network design for surface methane emission from landfills using spatial interpolation models.

Solid waste landfills are one of the primary anthropogenic sources of methane emissions which are often estimated by flux chamber measurements on landfill surfaces. Due to the small footprint of the flux chamber on the surface coverage, however, it is important to design a proper spatial deployment of the chambers with an optimal number of measurement points such that the measured fluxes are correctly scaled up to the whole landfill area. In order to improve the design of flux chamber network, several deterministic interpolation models were applied and results of reproducibility tests with 22 flux measurement data sets from ten municipal solid waste landfills in the Republic of Korea were compared one another. The bilinear model and natural neighbor model among the deterministic models showed stable results in all cases. The surface methane emissions estimated from arithmetic or geometric mean resulted in significant under- or overestimation compared to spatial interpolation methods in all data sets. As a result of this study, minimal number of flux measurement points could be determined for target error levels. Innovative flux chamber network design with proper measurement points will improve the accuracy of methane emission estimate from solid waste landfills.

Room Temperature Compressive Property and Deformation Behavior of Microporous STS 316L Stainless Steel Tube Manufactured with Powder Sintering Process.

This study investigated the room-temperature compressive property and deformation behavior of microporous STS 316L stainless steel tube for catalyst manufactured with powder sintering after two-way compression molding. The microporous tube was manufactured using STS 316L powder stocks with an outer diameter of 30 mm, inner diameter of 25 mm and length of 120 mm. In initial microstructure observed from different directions and locations, the porosity was measured as 32%, and the relative density obtained using micro-computed tomography was 0.54. Phase analysis did not identify phases other than γ-Fe. In a room temperature compression test, compressive yield strength measured 32 MPa. Observation of fractpgraphy after compression test revealed that dimples were formed at the powder-powder interface during the process where necks were disconnected. Based on the above findings, this study attempted to identify the deformation behavior of microporous STS 316L material manufactured with powder sintering after two-way compression molding and powder sintering process.