Laboratory-scale Tests Research Articles

Effect of Fiber Cross-Sectional and Surface Properties on the Degradation of Biobased Polymers

Biobased polymers such as polylactic acid (PLA) and polybutylene succinate (PBS) break down naturally under certain environmental conditions. The efficiency of degradation can be linked directly to fiber surface properties, which influence polymer accessibility. Here, the degradation of PLA and PBS fibers with six different cross-sections was investigated. The fibers were aged by hydrolysis and UV exposure in an accelerated weathering test, followed by an ISO 20200 laboratory-scale disintegration test with non-aged fibers as controls. The polymers were analyzed by differential scanning calorimetry, Fourier transform infrared spectroscopy, and gel permeation chromatography, comparing the polymer granulate, virgin fibers, and UV-exposed fibers. It was found that the molecular mass and crystallinity of PBS changed more than PLA during spinning. Several PLA samples were completely degraded, whereas all the PBS samples remained intact. Furthermore, surface openings appeared on the PLA fibers during weathering, suggesting greater sensitivity to UV exposure and hydrolysis than PBS. A clear correlation between the fiber surface area and the degradation rate was observed for all samples, but the correlation was positive for PLA and negative for PBS. The slower degradation of PBS fibers with a larger surface area may reflect the ability of PBS to preserve itself by further crystallization during degradation processes at temperatures higher than the glass transition point. The data clearly show that the analysis of single degradation mechanisms is insufficient to predict the behavior of material under real-world conditions, where different degradation mechanisms may work in parallel or consecutively, and may show interdependencies.

Influence of initial state and residual stresses on the modulus-density relationship of geomaterials: insights from multiple experimental setups

ABSTRACT Quality control in pavement construction traditionally relies on density measurements of geomaterials. With the introduction of modulus measurement methods, a shift has occurred due to the operational advantages of modulus-estimating devices over conventional density measurement techniques. Modulus-based methods also provide valuable information for the mechanistic-empirical (ME) design of pavement layers. However, a challenge emerges as a single modulus measurement does not directly correspond to a specific density measurement, leading to concerns about replacing density measurements in quality control processes. While it is generally accepted that a geomaterial's modulus primarily depends on its moisture content and density or void ratio, this study explores the complex relationship between modulus and density, particularly in field scenarios with consistent moisture content. Using three different laboratory-scale test set-ups, characterised by unique loading and boundary conditions, the research highlights the significant role of a geomaterial's initial state in obtaining accurate modulus estimates. The results reveal that identical densities can exhibit variations in modulus due to differences in initial densities and the development of residual lateral stresses. These variations in field conditions often stem from different paving or spreading techniques, emphasising the need for a comprehensive approach when establishing density-modulus correlations..

Critical comparison of potential machine learning methods for lightning thermal damage assessment of composite laminates

The present study assesses the potential of using machine learning (ML) methods to predict the extent of lightning thermal damage in fiber-reinforced composite laminates using three supervised machine learning (SML) algorithms: (1) linear regression (LR), (2) decision tree (DT)-based, and (3) MLP models. These models were based on the 10 most significant factors that influence the severity of lightning damage, including three current waveform parameters, four material configurations, and three orthogonal electrical conductivities of each composite. All models demonstrated good performance with coefficient of determination (R2) values between 0.84 ~ 0.96. The multilayer perceptron (MLP) regression model trained with the lightning matrix damage dataset showed the most promising results (R2 > 0.94). Additional hyperparameter optimization was performed to improve the prediction performance of the baseline MLP model. The hyperparameter optimization (Adam optimizer, tanh activation function, and three hidden layers with 234 neurons) slightly improved the performance of the baseline MLP model by ~0.02, but achieved faster convergence. This result suggests that the baseline MLP model trained with the lightning matrix damage dataset is sufficiently accurate and robust. This paper highlights that ML-informed regression models can serve as an efficient first pass-estimator of lightning matrix damage in composite laminates, potentially reducing the amount of extremely time-consuming and expensive laboratory-scale lightning tests or streamlining the development of complex lightning damage models for future design.

Predictive modeling for coiled tubing fatigue using advanced machine learning techniques

Coiled tubing CT plays Pivotal role in oil and gas well intervention operations due to its advantages such as flexibility, fast mobilization, safe, low cost and wide range of applications, including: well intervention, cleaning, stimulation, fluid displacement, cementing, and drilling. However, CT is subject of fatigue and mechanical damage caused by repeated bending cycles, internal pressure and environmental factors which can lead to a premature failure, high operational cost and production downtime. With the development of CT proprieties and application traditional fatigue life prediction methods based on analytical models integrated in tracking process showed in some cases an underestimate or overestimate of the actual fatigue life of CT particularly when complex factor like welding type, corrosive environment, and high-pressure variation are involved. This study addresses this limitation by introducing a comprehensive machine learning-based approach to improve the accuracy of CT fatigue life prediction, using a data set derived from over 350 tests both lab scale and full-scale fatigue test. The study has incorporated the impact of different parameters such as CT, grades, wall, thickness, CT diameter, internal pressure and welding types. By using advanced machine learning techniques such as artificial network (ANN), Gradient boosting regressor we got a more precise estimation of the number of cycles to failure than traditional models. The results of this study shown the importance of integration of machine learning for CT fatigue life analysis and demonstrating its capacity to enhance the prediction accuracy and reduce the uncertainty. A detailed machine Learning models is presented, emphasizing their capability to handle complex data and improve prediction under diverse operational conditions. This study contributes to more reliable, CT management and safer more cost-efficient well intervention operations.

A self-adaptive fractional-order PID controller for the particle velocity regulation in a pneumatic conveying system

This paper presents the methodical development of a state-error-driven self-adaptive fractional-order proportional–integral–derivative (AFOPID) control algorithm to efficiently regulate the velocity of pneumatically conveyed particles at the desired set point and to prevent the blockage of particles in a pipe due to an imbalanced combination of their velocity and corresponding mass flow rate. The proposed fractional control law is constituted by adaptively modulating fractional orders of the integral and differential operators in the control based on the state-error variations in the velocity of solid particles. The particle’s velocity is measured and updated via electrostatic sensors in conjunction with cross-correlation signal processing algorithms. All the other fixed hyper-parameters associated with the proportional–integral–derivative (PID) control scheme are meta-heuristically optimized by using a genetic algorithm. The proposed AFOPID is benchmarked against conventional integer-order PID and the fractional-order proportional–integral–derivative (FOPID) controllers. Experiments are performed on a laboratory-scale test rig to comparatively analyze the aforesaid control schemes, where each controller is examined for three velocity set points and three disturbance levels. The experimental results validate the superior time optimality and robustness of the proposed AFOPID controller against bounded disturbances and abrupt velocity set-point variations by manifesting relatively faster settling time, low overshoots (and undershoots), and smaller steady-state fluctuations.

Temperature Dependence of Aerated Turbine Lubricating Oil Degradation from a Lab-Scale Test Rig

Temperature Dependence of Aerated Turbine Lubricating Oil Degradation from a Lab-Scale Test Rig

Pure copper extrusion additive manufacturing of lattice structures for enabling enhanced thermal efficiency in hydrogen production

The high geometrical complexity allowed by Additive Manufacturing (AM) of pure copper can support the development of more efficient catalytic supports that can enable the design of efficient reactors for key processes for energy transition, i.e., hydrogen production with methane steam reforming or CO2 conversion to synthetic methane, thanks to the enhanced thermal conductivity of the catalytic support. Low relative density lattice geometries with open cell copper geometries can be adopted as catalyst supports in the new generation chemical reactors to improve the heat transfer. This work presents a manufacturability study about pure copper lattice filters produced via metal Extrusion AM i.e., via feedstock 3D printing and sintering. The results show that feasible parts design can be reached and produced and that heat-exchange performances can be increased with respect to conventional supports, as confirmed by lab-scale heat transfer tests. A specific metrological assessment based on CTscan data is implemented on the printed parts to qualify them and to ensure a good thermal coupling between the printed filters and the heat exchanger main tube elements.

Treatment of textile dyes with steel flakes via Fenton and Electro-Fenton processes: An experimental analysis

The textile production process is well recognised as one of the most water-intensive industries, with an estimated daily water consumption of several thousand cubic metres. The main objective of the study is to remove the colour and COD of three reactive dyes namely reactive blue, reactive yellow and reactive black by Fenton and Electro Fenton Process. In this research paper, new novel catalyst steel flakes have been employed as part of the Fenton and Electro-Fenton process, replacing the conventional Fenton and Electro-Fenton catalyst. Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Analysis (EDAX), Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Thermo Gravimetric Analysis (TGA) was done to characterize the steel flakes. The pH, dye concentration, FeSO4 dosage and H2O2 dosage were studied. The maximum colour and Chemical Oxygen Demand (COD) removal in Fenton process was 98.47 % and 74 % respectively. In Electro Fenton Oxidation the maximum colour and COD removal was 99.65 % and 78 % respectively. The best colour and COD removal was observed by Fenton and Electro Fenton oxidation with optimum Fenton molar ratio of 50:1 and pH 3 in all three dyes. In the laboratory-scale feasibility tests on the Electro-Fenton process, the highest colour removal effectiveness was observed at catalyst dosages of 1 g/L, 132 mM H2O2, and pH 3. The novel modified heterogeneous Electro-Fenton approach presents a distinct cost-effectiveness benefit in comparison to both the conventional Electro-Fenton reaction and the Electro-Fenton reaction employing alternative iron sources.

Assessment of salt-free electrodialysis metathesis: A novel process for brine management in brackish water desalination using monovalent selective ion exchange membranes

Since reverse osmosis (RO) is often limited to a water recovery of 70–85 %, implementing a secondary process like electrodialysis metathesis (EDM) to treat concentrate can increase system water recovery. This study explores salt-free electrodialysis metathesis (SF-EDM) as an alternative to conventional EDM to investigate its performance in the zero discharge desalination (ZDD) process. SF-EDM utilizes monovalent-selective ion exchange membranes, eliminating the need for sodium chloride (NaCl) as a substitution solution. This approach generates one diluate stream and two highly soluble concentrate streams enriched in calcium and sulfate, respectively. In this article, a series of lab-scale tests based on synthetic and real RO concentrate were performed to investigate how SF-EDM performs operating at high water recovery with a feedwater with high scaling potential. We critically analyze the performance in terms of salinity reduction, selectivity, and energy consumption. Results of the study show that without the addition of NaCl, the process was able to selectively separate sulfate and calcium into two concentrate streams achieve a salinity reduction of 93 % and a total system water recovery (RO and SF-EDM) of 90 %. A technoeconomic analysis found SF-EDM to be 80 % of the cost of conventional EDM making it a competitive technology for brackish water RO concentrate management.

LAVOLUTION: Tunable structured light for bridge displacement measurement

Assessing bridge conditions is critical, but field measurements often face challenges like sensor installation and accuracy requirements. This paper introduces a novel approach using structured light (SL) for non-target-based measurements, eliminating the need for physical markers. A tunable SL system, featuring four laser pointers aligned with a commercial camera, was developed to estimate the relative angle between the camera and the target structure, and to accurately calculate the scale factor. The proposed method involves three main processes: (1) laser alignment, (2) angle estimation, and (3) real-time displacement measurement. By precisely aligning the SL system and minimizing discrepancies between projected SL points and an ideal numerical model, the method achieves accurate results. Validation through numerical simulations, lab-scale tests, and full-scale bridge tests demonstrated a maximum error of 2.69% in scale and 2.53% in displacement, confirming the method’s effectiveness and applicability.

Phytotoxicity Testing of Atmospheric Polycyclic Aromatic Hydrocarbons

Atmospheric polycyclic aromatic hydrocarbons (PAHs) have well-known phytotoxicity on higher plants. However, while numerous bioindication studies have been targeted on how different symptoms indicate the deleterious effects of PAHs in the field, laboratory-scale phytotoxicity tests are much rarer. While ecotoxicity tests might rely on the very same end-points as bioindication studies, they have to comply with quality assurance criteria, repeatability being the most important. As such, proper reporting involves the description of the test compound, experimental design and conditions, test organism used, and end-points measured. The recent review intends to give an overview of studies available in the literature complying with these requirements. PAHs occur in the atmosphere both in gaseous form and bound to particles. As plants are exposed to both phases, test protocols available represent different exposure pathways, fumigation chambers vs. direct foliar treatment. Reported studies, therefore, are grouped based on the exposure route they intend to simulate.

An experimental investigation of the effect of barrier trench on vibration propagation on a laboratory scale model

Vibration waves caused by construction or mining operations may cause damage to nearby structures or sensitive machinery and equipment. Some measures are implemented to eliminate or reduce this negative environmental effect of vibration. The barrier trench, one of these methods, aims to reduce the vibration by creating a suitable barrier between the structure and the vibration source on the ground. In this study, the effect of trench depth and distance from the source on vibration waves was simulated with a designed laboratory-scale test set-up to determine the effective parameters in barrier trench use. In addition, the effects of the superimposition of the source vibration wave with the reflected and refracted vibration waves from the trench, which has not been previously discussed in the literature, were also investigated. A laboratory scale gypsum-plaster block with dimensions of 200 cm × 90 cm x 70 cm was prepared and a Schmidt hammer was used as the impact energy source to generate vibration throughout the gypsum block. A trench barrier was opened at different depths on the test block and 588 vibration recordings were taken by the vibration monitor in different locations of the designed set-up. Statistical analyses were performed using vibration measurement results, trench source distance, and trench depths. As a result, vibration estimation equations depending on trench depth and the distance between the vibration source point and the trench were developed and how the presence of trench affects vibration propagation is revealed. It was found that vibrations increase due to the superposition of the source and reflected waves in front of the barrier trench. As the barrier depth increases, it is understood that the vibrations emanating from the near-surface vibration energy source are better blocked by the barrier. Thus, this study provides fundamental information on designing barrier trenches to avoid adverse effects of vibrations.

Towards maximization of parameters identifiability: Development of the CalOpt tool and its application to the anaerobic digestion model

This work addresses the need for robust approaches to estimate kinetic parameters in continuous anaerobic co-digestion plants. Specifically, it outlines a procedure for including data from batch activity tests on digestate samples, in addition to the poorly informative dataset from conventional monitoring of biogas facilities. To profitably make use of activity tests, the estimation of the biomass composition in digestate samples is required to improve parameter identifiability. To this purpose, an open-source tool (CalOpt) was developed and tested on a pilot-scale co-digester, simultaneously using data from both conventional monitoring and lab-scale activity tests. Targeting the prediction of volatile fatty acids (VFAs) concentrations in the digestate of the continuous co-digester, the kinetic parameters of different microbial groups were selected for calibration based on parameters importance ranking and collinearity index. The results demonstrate that the CalOpt tool significantly improved the fitting of acetic, propionic, and butyric acid concentrations in digestate as well as the methane flowrate from the digester. Furthermore, the study assessed the necessity of modifying the Monod kinetics to account for substrate inhibition by incorporating the Haldane term in the VFAs uptake kinetic model, which proved to be essential for better interpreting batch activity tests.

Critical Factors in Lab-Scale Compostability Testing

Critical Factors in Lab-Scale Compostability Testing

A Comprehensive Review on Studying and Developing Guidelines to Standardize the Inspection of Properties and Production Methods for Mycelium-Bound Composites in Bio-Based Building Material Applications.

Mycelium-bound composites (MBCs) represent a promising advancement in bio-based building materials, offering sustainable alternatives for engineering and construction applications. This review provides a comprehensive overview of the current research landscape, production methodologies, and standardization ideas related to MBCs. A basic search on Scopus revealed over 250 publications on MBCs between 2020 and 2024, with more than 30% focusing on engineering and materials science. Key studies have investigated the physical and mechanical properties of MBCs, optimizing parameters such as substrate type, fungal species, incubation time, and post-processing to enhance material performance. Standardizing the inspection of MBC properties is crucial for ensuring quality and reliability. Various testing standards, including those from the American Society for Testing and Materials (ASTM), the International Organization for Standardization (ISO), the Japanese Industrial Standard (JIS), European Standards (EN), Deutsches Institut für Normung (DIN), and the Thai Industrial Standards Institute (TIS), are utilized to evaluate density, water absorption, compression strength, tensile strength, insulation, and other critical properties. This review highlights the distinction between lab-scale and apply-scale testing methodologies, emphasizing the need for comprehensive evaluation protocols. Additionally, the production process of MBCs involves critical steps like substrate preparation, fungal species selection, and mycelium growth, necessitating the implementation of good manufacturing practices (GMPs) to ensure consistency and quality. The internal and external structures of MBCs significantly influence their performance, necessitating standardized inspection methods using advanced techniques such as scanning electron microscopy (SEM), X-ray computed tomography (CT) scanning, and surface profilometry. By establishing robust inspection protocols and production standards, the industry can enhance the reliability and adoption of MBCs, contributing to innovations in materials science and promoting environmental sustainability. This review underscores the importance of interdisciplinary collaboration, advanced characterization tools, and regulatory frameworks to address challenges and advance the field of MBCs.

Biofouling control of reverse osmosis membrane in municipal wastewater recycling plants using urine as a cleaning agent

Biofouling is a major issue for reverse osmosis (RO) membranes during wastewater recycling, which requires significant chemical inputs for its cleaning. This study investigated the feasibility of using urine, a human waste that can be directly obtained from the community, as a novel and low-cost cleaning agent for RO membranes subjected to biofouling. Lab-scale immersion cleaning tests and cross-flow cleaning tests were performed on four fouled RO membranes collected from municipal wastewater recycling plants (MWRPs). In the immersion cleaning test, urine solutions (15–25 %) showed higher removal efficiency for ATP, proteins, and polysaccharide than the traditional alkaline solution (NaOH, pH=11), with a cleaning efficiency of 82 %, 53 %, and 79 %, respectively. In the cross-flow cleaning test, urine solutions (15 % − 25 %) also exhibited comparable or better performance than the conventional alkaline cleaning (NaOH, pH=11) in ATP, proteins and polysaccharide removals, reaching a removal rate of 79 % − 100 %, 61 % − 90 %, and 70 % − 100 %, respectively, and permeability increase by 7.8 % − 16.0 %. Urine solutions (15–25 %) demonstrated to be a promising agent for biofouling cleaning on RO membranes in MWRPs, providing a cost-effective and environmentally friendly alternative.

Laboratory-Scale Limestone Rock Linear Cutting Tests with a Conical Pick: Predicting Optimal Cutting Conditions from Tool Forces

This study introduces a simplified method for predicting the optimal cutting conditions to maximize excavation efficiency based on tool forces. A laboratory-scale linear rock-cutting test was conducted using a conical pick on Finike limestone. The tool forces and their ratios were analyzed in relation to cutting parameters such as penetration depth and spacing. While the cutting force (FC) and normal force (FN) increased with the penetration depth and spacing, this relationship could not predict the optimal cutting conditions. The ratio of the mean normal force to the mean cutting force (FNm/FCm) increased with the penetration depth and the ratio of spacing to penetration depth (s/d). However, even while including this relationship, predicting optimal cutting conditions remained challenging. The ratio of the peak cutting force to the mean cutting force (FCp/FCm) reached a maximum value at a specific s/d, which is similar to the relationship between the specific energy (SE) and s/d. The optimal s/d obtained through the SE methodology was found to be between 3 and 5, and FCp/FCm reached a maximum at s/d. The error between the optimal s/d and the s/d in which FCp/FCm was maximized was less than 5%. Therefore, it was confirmed that the optimal cutting conditions could be predicted through the relationship between FCp/FCm and s/d. Additionally, by using the results from previous studies, the optimal cutting conditions obtained from the SE methodology and the proposed methodology were found to agree within a margin of error of 20%. The proposed methodology can be beneficial for the design of cutter heads and the operation of excavation machines.

Electric Boats for Fisherman as a Substitute for Fuel Oil on The Belitung Island (Indonesia)

Abstract Fishing constitutes a prominent livelihood for many Indonesian coastal residents. Indonesia boasts the world’s longest coastline, which suggests that fishermen should enjoy a high standard of living and a wholesome lifestyle. Nevertheless, a significant portion of traditional Indonesian fishermen fails to experience these benefits, as they persist in outdated fishing practices inherited from their forebears, remaining untouched by the technological advancements that can enhance their economic well-being. This results in elevated operational and maintenance costs during fishing operations. This issue primarily arises from inefficient energy utilization, including fuel, and restricted fuel availability. The objective of this research is to identify solutions to these challenges, particularly by leveraging more efficient technologies to reduce costs and protect fishermen from the health hazards of pollution during their fishing activities. To achieve this research goal, various stages were undertaken, encompassing on-site observations, the design of an electric boat (e-boat) system based on conventional vessels, simulations, and laboratory-scale testing. The testing results indicate that the electric boat, equipped with a 6-kW motor and an 8.64 kWh battery capacity, can be effectively applied in the retrofit process. The initial phase of retrofitting ten electric boats incurs a total cost of $88,620, with each boat’s retrofit expected to yield a return on investment over a span of 20 years. Therefore, this retrofit process necessitates government intervention to provide a 50% subsidy for the electric boat retrofit, subsequently reducing the duration of credit installment payments for fishermen.

Design of a test rig for the characterization of friction and wear in hot-metal gas-forming of AA 5083 aluminium sheets

Advanced aluminium sheet-forming processes such as the hot-metal gas-forming represent a challenging solution for producing small lots in the high-end car bodies industry, and the adoption of single cavity moulds made from low-cost, easily machinable materials such as cast iron reduces the overall sheet-forming costs. The tribological properties of the mould-sheet tribopair are of great interest for optimizing the sheet forming obtaining an acceptable esthetic surface finishing. This study presents the design and construction of a lab-scale experimental test rig for the tribological characterization at high temperatures of the mould-sheet tribopair. The proposed test method reproduces the sliding at the mould-sheet interface with contemporary sheet straining up to ε = 0.8 at strain rates in the 1.2*10-3 to 2*10-2 s-1 range. A series of experiments were carried out in dry and lubricated conditions for a ductile iron EN-GJS grade sliding against a AA 5083 aluminium alloy while straining. After comparing the experimental results with the literature data from other test rigs, comparable results were obtained as COF regards, ranging between 1.2 to 2.5 in dry sliding and between 0.05 to 0.2 in lubricated sliding. The morphological characterization of the sliding surfaces and cross-sections highlights the strong tendency to galling in dry sliding conditions expecially for low strain rates.

Rhamnolipids Enhance Bioremediation of Petroleum-Contaminated Soil

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215952, “Enhancing Bioremediation of Petroleum-Contaminated Soil Using Rhamnolipids: A Combined Laboratory and Field Study,” by Pan Ni, Lehigh University; Yonglin Ren, SPE, Stepan Oilfield Solutions; and Derick G. Brown, Lehigh University, et al. The paper has not been peer reviewed. _ Hydrocarbon spills can occur at various stages of the oil and gas exploration and production process. Treating these spills onsite to avoid more-expensive excavation and incineration processes would be beneficial. The study outlined in the complete paper aims to optimize the use of rhamnolipid biosurfactants for enhancing the bioremediation of hydrocarbon-contaminated soil. The goal of this work was to explore the effects of rhamnolipid application on hydrocarbon degradation rate under both laboratory and field conditions and to examine the effects of this treatment on the indigenous soil microorganism population. Introduction The authors write that, to the best of their knowledge, previous research studies on rhamnolipid-based soil remediation focused on either laboratory or field tests and that comparison between laboratory-scale and field-scale tests is overlooked but necessary for practical applications. Materials and Methods Materials and Chemicals. The soil used for this work (23 kg for the laboratory test, 10 metric tons for the field test) was obtained from a contaminated site in Longford Mills, Canada. The soil properties are presented in Table 1 of the complete paper. The rhamnolipid stock solution featured 9.8 wt% rhamnolipid blends in deionized water. Another commercial remediation agent (enzyme-based) was used in the field test to compare with the performance of rhamnolipid. Ammonium chloride (NH4Cl) and potassium hydrogen phosphate (K2HPO4) also were used along with sodium hydroxide (NaOH). Experimental Setup. Both laboratory and field tests were ex-situ tests using simulated soil piles. The laboratory test was conducted for 193 days. For the laboratory experiments, an aerobic/anaerobic respirometer system equipped with a low-temperature incubator was used to monitor the in-situ oxygen uptake inside eight reactors (Fig. 1). Each reactor contained 250 g of soil with rhamnolipid doses of 0, 0.1, 0.5, and 1 g/kg. The temperature was set to 25°C. Inside each reactor was placed 10 mL of 4-M NaOH in a 20-mL glass beaker to adsorb the produced CO2. A parallel set of eight reactors was prepared and operated under the same conditions. The nutrients of nitrogen and phosphorous (NH4Cl and K2HPO4) were added at specific times based on the oxygen uptake rate monitored by the respirometer. To avoid the possible inhibition of the microbes in the soil as a result of high ionic strength (greater than 160 mM) in the soil pore water, NH4Cl and K2HPO4 were added so that the molar concentration in the soil pore water did not exceed 100 mM. The field test is being conducted in Longford Mills, Ontario, Canada, and is ongoing at the time of writing. For the field test, 10 metric tons of soil were mixed to achieve homogeneity before the preparation of the soil piles. Five different treatment conditions were examined using duplicate soil piles (10 piles total), with each consisting of 1 metric ton of soil. Nutrient addition was similar to that used in the laboratory tests. Temperature and moisture were monitored every few days at five points in each soil pile, and the pH was monitored once every month at five points.