Laboratory Simulation Studies Research Articles

Colloid mobilization and transport in response to freeze-thaw cycles: Insights into the heavy metal(loid)s migration at a smelting site

Smelting sites often exhibit significant heavy metal(loid)s (HMs) contamination in the soil and groundwater, which are inevitably subjected to environmental disturbances. However, there is limited information available regarding the migration behaviors of HMs in a disturbed scenario. Thus, this work explored the migration of HMs-bearing colloids in response to freeze-thaw treatments by laboratory simulation and pore-scale study. Ultrafiltration results of soil effluents revealed that 61.5 %, 47.6 %, 68.0 %, and 59.2 % of Zn, Cd, Pb, and As were present in colloidal phase, and co-transported during treatments. Nanoparticle tracking analysis (NTA) further confirmed that freeze-thaw cycles were conducive to the generation of colloidal particles and showed the heteroagglomeration among different particles. Pore-network model (PNM) was used to quantify the soil macropore characteristics (macropore diameter, macropore number, coordination number, and Euler value) after treatments. It is evident that freeze-thaw cycles induced the formation of larger macropores while simultaneously enhancing macropore connectivity, thereby establishing an optimal pathway for colloid migration. These findings underscored the importance of environmental disturbances as a trigger for the release and migration of HMs in the smelting site, offering valuable insights for controlling HMs pollution. Environmental implicationThe contaminated site has been subjected to prolonged environmental disturbances, causing the exacerbation of pollutants leaching and frequent occurrences of unstable pollution situations. This work explored the migration of HMs-bearing colloids in response to freeze-thaw treatments by laboratory simulation and pore-scale study. The distinct effects of freeze-thaw treatment on colloidal particle number concentration and macropore characteristics may explain the generation and migration of colloid-associated HMs driven by environmental disturbances. This work revealed the underlying mechanisms driving the redistribution of HMs under freeze-thaw cycles, offering valuable insights for risk assessment of soil and groundwater associated with HMs migration.

Photosynthetic response to a winter heatwave in leading and trailing edge populations of the intertidal red alga Corallina officinalis (Rhodophyta)

Marine heatwaves (MHWs) caused by anthropogenic climate change are becoming a key driver of change at the ecosystem level. Thermal conditions experienced by marine organisms across their distribution, particularly towards the equator, are likely to approach their physiological limits, resulting in extensive mortality and subsequent changes at the population level. Populations at the margins of their species’ distribution are thought to be more sensitive to climate-induced environmental pressures than central populations, but our understanding of variability in fitness-related physiological traits in trailing versus leading-edge populations is limited. In a laboratory simulation study, we tested whether two leading (Iceland) and two trailing (Spain) peripheral populations of the intertidal macroalga Corallina officinalis display different levels of maximum potential quantum efficiency (Fv/Fm) resilience to current and future winter MHWs scenarios. Our study revealed that ongoing and future local winter MHWs will not negatively affect leading-edge populations of C. officinalis, which exhibited stable photosynthetic efficiency throughout the study. Trailing edge populations showed a positive though non-significant trend in photosynthetic efficiency throughout winter MHWs exposure. Poleward and equatorward populations did not produce significantly different results, with winter MHWs having no negative affect on Fv/Fm of either population. Additionally, we found no long-term regional or population-level influence of a winter MHWs on this species’ photosynthetic efficiency. Thus, we found no statistically significant difference in thermal stress responses between leading and trailing populations. Nonetheless, C. officinalis showed a trend towards higher stress responses in southern than northern populations. Because responses rest on a variety of local population traits, they are difficult to predict based solely on thermal pressures.

The fate of 17β-estradiol in snowmelt from a field with a history of manure application: A laboratory simulation and field study

17β-estradiol is a naturally occurring estrogen, and livestock manure applied to agricultural fields is a major source to the environment. Liquid swine manure is widely applied to agricultural fields in the Canadian Prairies, a region where the majority of the annual runoff occurs during a brief snowmelt period over frozen soil. Transport of estrogens from manure amendments to soil during this important hydrological period is not well understood but is critical to mitigating the snowmelt-driven offsite transport of estrogens. This study quantified the concentration and load of 17β-estradiol in snowmelt from an agricultural field with a history of manure application under manure application methods: no manure applied, manure applied on the sub-surface, and on the surface, using a laboratory simulation study with flooded intact soil cores and a field study during snowmelt. A higher concentration of 17β-estradiol was in the laboratory simulation than in the field (mean laboratory pore water = 1.65 ± 1.2 μg/L; mean laboratory flood water = 0.488 ± 0.58 μg/L; and mean field snowmelt = 0.0619 ± 0.048 μg/L). There were no significant differences among manure application methods for 17β-estradiol concentration. Laboratory pore water concentrations significantly increased over time, corresponding with changes in pH. In contrast, there was no significant change in the field snowmelt concentrations of 17β-estradiol over time. However, for both laboratory simulation experiments and field-based snowmelt experiments, mean concentrations of 17β-estradiol were higher with subsurface than surface-applied manure, and the cumulative load of 17β-estradiol was significantly higher in the sub-surface than in surface applied. The mean cumulative load from the field study across all treatments (6.91 ± 3.7 ng/m2) approximates the magnitude of 17β-estradiol that could be mobilized from manured fields. The sub-surface application of manure seems to increase the persistence of 17β-estradiol in soil, thus enhancing the potential loss to snowmelt runoff.

Hydro‐pedo‐transfer‐functions expressing drought and memory effects on pine tree growth

AbstractOver the last 30 years, the impact of climate change in Berlin, Germany, has manifested in the form of reduced summer rainfall, elevated temperatures, and a notable rise in the frequency of days with temperatures surpassing 30°C. All of them are leading to a decreasing water supply and increasing risk of drought. Various field, laboratory, and numerical simulation studies have been done for deriving information on long‐term potential and actual evapotranspiration, water stress during the vegetation period (April–September), and tree ring growth of various pine tree stands in Berlin. Data analysis highlights periodical climate patterns and complex interactions between drought, water supply, and plant growth. Annual tree ring growth is not only related to the actual weather conditions but also to the past climate years. With decreasing water supply, this kind of drought memory effect increases up to 5 years into the past. For Berlin's climate, it is noteworthy that late summer, particularly the water stress in August, represents the most sensitive indicator for tree ring growth.For regionalization purposes, long‐term numerical simulations were done to derive hydro‐pedo‐transfer‐functions (HPTFs) predicting the water stress coefficient of the growing season (Eact‐s/Epot‐s). They only need easily available information such as soil texture, climate water balance, and groundwater depth. Two HPTFs were successfully tested and can be easily applied by geo‐information systems. However, for other climate regions and tree species, HPTFs need to be adapted.

Micro-environmental factors impact breathing zone exposures: A simulated petrochemical manufacturing facility task

This study investigates the impact of micro-environmental factors on worker breathing zone exposure levels in petrochemical facilities. A laboratory simulation study evaluated near-field exposure to methane for a typical maintenance task. Individual and combinations of micro-environmental factors significantly affected methane exposure. Airflow direction and speed were significant determinants of exposure concentration reduction. A side airflow direction at medium to high speed produced the lowest gas concentration in the breathing zone. Worker body orientation relative to the methane emission point was also a critical factor affecting gas concentration in the worker's breathing zone. The study provides insights into how variations in airflow and small changes in position impact near-field exposures for petrochemical tasks, guiding industrial hygiene professionals' training on qualitative exposure estimation and providing input for near-field exposure modeling to guide quantitative exposure and risk assessment.

Combining Chamber Experiments and Model Simulations to Evaluate an Indoor HONO Source with Surface Photochemical Properties

Nitrous acid (HONO) is an emerging indoor pollutant that can exert adverse health effects. The chemical production of indoor HONO has been attributed to NO2 heterogeneous reactions, and the source strength has been extensively evaluated via laboratory and model simulation studies. Photolysis of surface nitrate has recently been proposed as an indoor HONO source based on correlation analysis between indoor HONO accumulation and visible light radiation. However, neither experimental validation of the proposed mechanism nor source strength characterization is currently available. In this work, we designed an outdoor photochemical chamber (OPC) to simulate indoor HONO accumulation and established an indoor photochemical model (ICM) to calculate the indoor HONO budget. Indoor HONO accumulation revealed a distinct diel variation with a daytime maximum. Only with this indoor HONO source, the ICM reproduced the indoor HONO budget determined in the OPC. The enhanced reactive cross section of surface nitrate in visible light accounted for the major portion of the HONO source budget (77.2%) and the distinct diel variation. Success with the ICM encouraged us to simulate the HONO budget in real indoor environments. The calculated HONO production rates from surface nitrate photolysis at noon ranged from 1.4 to 4.1 ppbv h-1 under different indoor scenarios. On a daily average, this indoor HONO source contributed 42.4–52.7% to the total chemical sources in the living room but only contributed 4.7% to that in the kitchen, where NO2 heterogeneous reactions dominated.

Physicochemical and biological changes on naturally aged microplastic surfaces in real environments over 10 months

Microplastics (MPs) undergo aging over time, which can influence their behavior in the environment. While laboratory-simulated studies have investigated MP aging, research on natural aging in various real environments remains limited. This study aims to investigate the physical, chemical and biological changes that occur in five types of MPs after more than 10 months of natural aging in three different real environments: seawater, air and soil. Results are compared with previous laboratory experiments. The surface roughness of all types of aged MPs was found to be higher in seawater than in air and soil, which differed from previous simulated studies that showed the highest roughness in air. All aged MPs exhibited the occurrence of hydroxyl and carbonyl groups due to the oxidation processes. Interestingly, the MPs aged in soil showed the lowest level of these functional groups, while in seawater or air, some MPs demonstrated the highest. This contrasts with previous studies indicating the highest level of oxygen-containing functional groups in aged MPs in air. Bacterial analysis identified fourteen bacterial phyla on the surface of aged MPs in all three real environments, with varying abundance in specific environments. Notably, the composition of bacterial communities in the microplastisphere was determined by the surrounding environments, independent of MP types. Natural aging is more complex than laboratory simulations, and the degree of MP aging increases with the complexity of environmental factors. These findings enhance our understanding of the natural aging of MPs in different real environments.

Oxidation 1-methyl naphthalene based on the synergy of environmentally persistent free radicals (EPFRs) and PAHs in particulate matter (PM) surface

Studies of the environmental fate through the interactions of particle-associated polycyclic aromatic hydrocarbons (PAHs) with environmentally persistent free radicals (EPFRs) are presented. The formation of PAHs and EPFRs typically occurs side by side during combustion-processes. The laboratory simulation studies of the model PAH molecule 1-Methylnaphthalene (1-MN) interaction with model EPFRs indicate a transformational synergy between these two pollutants due to mutual and matrix interactions. EPFRs, thorough its redox cycle result in the oxidation of PAHs into oxy-/hydroxy-PAHs. EPFRs have been shown before to produce OH radical during its redox cycle in aqueous media and this study has shown that produced OH radical can transform other PM constituents resulting in alteration of PM chemistry.In model PM, EPFRs driven oxidation process of 1-MN produced 1,4-naphthoquinone, 1-naphthaldehyde, 4-hydroxy-4-methylnaphthalen-1-one, and various isomers of (hydroxymethyl) naphthalene. Differences were observed in oxidation product yields, depending on whether EPFRs and PAHs were cohabiting the same PM or present on separate PM. This effect is attributed to the OH radical concentration gradient as a factor in the oxidation process, further strengthening the hypothesis of EPFRs’ role in the PAH oxidation process.This finding is revealing new environmental role of EPFRs in a natural degradation process of PAHs. Additionally, it points to implications of such PM surface chemistry in the changing mobility of PAHs into an aqueous medium, thus increasing their bioavailability.

Feeling negative or positive about fresh blood? Understanding veterans' affective reactions toward newcomer entry in teams from an affective events perspective.

To meet the ever-changing work demands in today's organizations, new employees are often placed into existing work teams. Although research on organizational socialization has advanced our understanding of how newcomers adjust after joining a team, it remains largely unclear how team veterans navigate the same period of adjustment. Drawing upon affective events theory, we conceptualize newcomer entry into a team as a salient affective event that can trigger multiplex affective reactions among team veterans and ultimately shape team functioning (i.e., team processes and team performance). We propose that when a newcomer differs more from veterans in relational characteristics, such as trait likeability, veterans will have stronger negative affective reactions (i.e., stronger negative affect and weaker positive affect), whereas when the newcomer differs more from veterans in task-related characteristics, such as educational background, veterans will have stronger positive affective reactions (i.e., weaker negative affect and stronger positive affect) after newcomer entry. In addition, we propose that team performance prior to newcomer entry attenuates the strength of the relationships between newcomer-veteran dissimilarities and veteran affective reactions. We tested our hypotheses in a laboratory simulation (Study 1) and a field survey study (Study 2). The results provided support for our theoretical model that the entry of a newcomer can bring multiplex affective consequences for veterans, depending on the type of newcomer dissimilarity to the team and the team's prior performance. Theoretical and practical implications of our findings are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Do biotransformation data from laboratory experiments reflect micropollutant degradation in a large river basin?

Identifying a chemical's potential for biotransformation in the aquatic environment is crucial to predict its fate and manage its potential hazards. Due to the complexity of natural water bodies, especially river networks, biotransformation is often studied in laboratory experiments, assuming that study outcomes can be extrapolated to compound behavior in the field. Here, we investigated to what extent outcomes of laboratory simulation studies indeed reflect biotransformation kinetics observed in riverine systems. To determine in-field biotransformation, we measured loads of 27 wastewater treatment plant effluent-borne compounds along the Rhine and its major tributaries during two seasons. Up to 21 compounds were detected at each sampling location. Measured compound loads were used in an inverse model framework of the Rhine river basin to derive k’bio,field values – a compound-specific parameter describing the compounds’ average biotransformation potential during the field studies. To support model calibration, we performed phototransformation and sorption experiments with all the study compounds, identifying 5 compounds that are susceptible towards direct phototransformation and determining Koc values covering four orders of magnitude. On the laboratory side, we used a similar inverse model framework to derive k’bio,lab values from water-sediment experiments run according to a modified OECD 308-type protocol. The comparison of k’bio,lab and k’bio,field revealed that their absolute values differed, pointing towards faster transformation in the Rhine river basin. Yet, we could demonstrate that relative rankings of biotransformation potential and groups of compounds with low, moderate and high persistence agree reasonably well between laboratory and field outcomes. Overall, our results provide evidence that laboratory-based biotransformation studies using the modified OECD 308 protocol and k’bio values derived thereof bear considerable potential to reflect biotransformation of micropollutants in one of the largest European river basins.

Framework of the Integrated Approach to Formation Mechanisms of Typical Combustion Byproducts─Polyhalogenated Dibenzo-p-dioxins/Dibenzofurans (PXDD/Fs).

Understanding the mechanisms through which persistent organic pollutants (POPs) form during combustion processes is critical for controlling emissions of POPs, but the mechanisms through which most POPs form are poorly understood. Polyhalogenated dibenzo-p-dioxins and dibenzofurans (PXDD/Fs) are typical toxic POPs, and the formation mechanisms of PXDD/Fs are better understood than the mechanisms through which other POPs form. In this study, a framework for identifying detailed PXDD/Fs formation mechanisms was developed and reviewed. The latest laboratory studies in which organic free radical intermediates of PXDD/Fs have been detected in situ and isotope labeling methods have been used to trace transformation pathways were reviewed. These studies provided direct evidence for PXDD/Fs formation pathways. Quantum chemical calculations were performed to determine the rationality of proposed PXDD/Fs formation pathways involving different elementary reactions. Many field studies have been performed, and the PXDD/Fs congener patterns found were compared with PXDD/Fs congener patterns obtained in laboratory simulation studies and theoretical studies to mutually verify the dominant PXDD/Fs formation mechanisms. The integrated method involving laboratory simulation studies, theoretical calculations, and field studies described and reviewed here can be used to clarify the mechanisms involved in PXDD/Fs formation. This review brings together information about PXDD/Fs formation mechanisms and provides a methodological framework for investigating PXDD/Fs and other POPs formation mechanisms during combustion processes, which will help in the development of strategies for controlling POPs emissions.

Single-Particle Analysis of Atmospheric Aerosols: Applications of Raman Spectroscopy

Atmospheric aerosols, produced as a consequence of different anthropogenic and natural processes, impart significant control over the global energy budget, climate, and human–environmental health. Their size varies across the nano–micrometer scale. Based on their origin, they may be classified into primary or secondary aerosols. Biomass burning, incomplete combustion of fossil fuels, volcanic eruptions, and traffic-related and wind-driven suspensions contribute to primary aerosol emissions. In contrast, gas-to-particle conversion within the atmosphere leads to secondary particle production. The study of atmospheric aerosols is vital to the field of atmospheric research. The dynamic nature (highly variable concentration composition and size with space and time) of aerosols makes them difficult to investigate. Today, aerosol research involves the application of various spectrometric and spectroscopic techniques. The single-particle analysis of aerosols is yet a challenge. In this review, the merits and demerits of various offline and online techniques used for aerosol research are discussed in a nutshell. Mass spectrometric techniques fail in distinguishing certain species. However, Raman spectroscopy’s emergence for the compositional analysis of aerosols resolves most of the present characterization challenges. This review focuses on Raman spectroscopy applications, the merits of this technique, and its immense scope for the measurement of various types of aerosols and their properties. Surface-enhanced Raman spectroscopy (SERS) has an advantage over conventional micro-Raman spectroscopy (MRS). The review depicts the dominance of SERS, specifically in the context of the measurement of ambient atmospheric aerosols. This review discusses two important components, namely laboratory simulation and ambient aerosol studies.

Biodiagnostics of Resistance to the Copper (Cu) Pollution of Forest Soils at the Dry and Humid Subtropics in the Greater Caucasus Region

Forest ecosystems perform important forestry and ecological functions. However, mining and processing companies cause significant soil contamination by heavy metals, in particular, copper (Cu). The resistance of nine types and subtypes of forest soils of the dry and humid subtropics in the Greater Caucasus region to Cu contamination at concentrations of 100, 1000, and 10,000 mg/kg was evaluated for the first time following the most sensitive and informative biological (microbiological, biochemical, and phytotoxic) indicators via a laboratory simulation study. Contamination was simulated under laboratory conditions. The series of forest soils was established following their resistance to Cu pollution: brown leached soils (Haplic Cambisols Eutric) = brown typical soils (Haplic Cambisols Eutric) > brown carbonate soils (Haplic Cambisols Eutric) = sod-carbonate typical soils (Rendzic Leptosols Eutric) ≥ yellow soils (Albic Luvisols Abruptic) ≥ leached sod-carbonate soils (Rendzic Leptosols Eutric) > brown forest slightly unsaturated soils (Haplic Cambisols Eutric) > acid brown forest soils (Haplic Cambisols Eutric) > acid brown forest podzolized soils (Haplic Cambisols Eutric). Regional environmentally safe standards for the Cu content in forest soils of the dry and humid subtropics of the Greater Caucasus were proposed: for brown typical soils, brown leached soils, brown carbonate soils, brown forest slightly unsaturated soils, sod-carbonate typical soils, leached sod-carbonate soils, and yellow soils, the rMPC was 100 mg/kg; for acid brown forest soils and acid brown forest podzolized soils, the rMPC was 70 mg/kg.

New Insights into the Understanding of In-Situ Combustion: Important Considerations When Modeling the Process

Summary Air-injection-based enhanced oil recovery (EOR) processes have historically been of great interest due to their high recovery potential and applicability to a wide range of reservoirs where other processes are not effective or economical. However, most operators require a certain level of confidence in the potential recovery from these (or any) process before committing resources; this is commonly achieved with the support of laboratory and reservoir simulation studies. Laboratory testing, including combustion tube, ramped temperature oxidation (RTO), and accelerating rate calorimeter (ARC) tests, can supply data for simple analytical models. It can also provide important insights into potential oxidation behaviors and oil recovery mechanisms. Similarly, reservoir simulation of some of those experiments can assist in the understanding of the process and may allow for the development of kinetic models that can be used for further reservoir modeling. However, due to sample size limitation and the unscaled nature of the experiments, these tests are not ideally suited to provide detailed or unique kinetic data for direct use in numerical simulators. In fact, the oxidation reactions are sufficiently complex that, regardless of how robust a thermal reservoir simulator may be, its predictive capability strongly depends on the engineer’s understanding of the process and ability to model the most relevant oxidation behaviors of the particular hydrocarbon reservoir under study. Over the past 50 years, the In-Situ Combustion Research Group (ISCRG) at the University of Calgary has dedicated its efforts toward the advancement of this technology. Under the leadership of Professor Gordon Moore, the ISCRG has performed a large number of combustion tests, designed and carried out many novel oxidation experiments, and also made important contributions to the numerical modeling of air-injection-based processes. Nevertheless, in spite of its long research history, the group acknowledges that there is still much that needs to be learned about the process. For example, two oils with the same physical properties such as viscosity and density can have significantly different oxidation behaviors, which are difficult to predict; this is one of the reasons the group continues to perform laboratory experiments and conduct research in this area. This paper describes some of the most important conceptual contributions made by the ISCRG based on their experimental results and how they have enhanced our understanding of the process. These continue to be an important source of knowledge toward the development of predictive reservoir simulation models, as it is very difficult, if not impossible, to properly model a physical problem one does not understand well. For instance, the fundamental equations used for mathematical modeling depend on selecting of the relevant physical mechanisms and assumptions made, and these are derived from experimental work. Similarly, when using a commercial numerical simulator, the selection of fluid pseudocomponents as well as their physical properties and chemical reactions, as well as their kinetic parameters, also depend on an understanding of the process. This paper provides a summary of the relevant physical aspects to consider when modeling the in-situ combustion (ISC) process as well as new insights on its dynamics based on the laboratory experiments performed by the ISCRG.

Effect of fire spread, flame characteristic, fire intensity on particulate matter 2.5 released from surface fuel combustion of Pinus koraiensis plantation- A laboratory simulation study.

PM2.5 is one of major pollutants emitted from forest fires. High PM2.5 concentration not only affects short-term human respiration health, but also poses a long-term threat to human cardiopulmonary functionality. Therefore, it is of great importance to quantitatively assess the PM2.5 released by forest combustion in forest fire studies. In this study we examine relationships between the PM2.5 concentration and environment and fuel characteristics laboratory experiments. In the experiments, fuel beds with controlled moisture contents and loads were first built; then 144 ignition experiments were conducted for various combinations of wind speeds using a wind tunnel device. Fire behavior characteristics and PM2.5 concentrations released from fuel combustion were measured and analyzed. The experimental results show that the relationship between fire characteristics, fire intensity and the influencing factors of wind speed, fuel moisture content, and fuel load can be explained by the fundamental theory of forest combustion. Although PM2.5 concentration rises with the increase of wind speed, the decrease of fuel moisture content, and the increase of fuel load, there appears to be a fuel load threshold for a given combination of wind speed and fuel moisture content that the increase of PM2.5 concentration decelerates quickly after the load passes the threshold value. After screening fire behavior characteristics that affect PM2.5 concentration, we found that fire line intensity and flame width are the ones with the strongest association with the concentration. With flame width as independent variable, we have built two regression models to predict PM2.5 and fire line intensity which are treated as dependent variable; the models have high accuracy with R2=0.92 for predicting PM2.5 and R2=0.97 for predicting fire line intensity. Study results can be used as reference to protect the health of forest fire fighters, and can be helpful for forest fire smoke management.

Impact of Ergonomic Posture on the Chemical Exposure of Workers in the Petroleum and Chemical Industry.

Despite a rise in automation, workers in the petroleum refining and petrochemical manufacturing industry are potentially exposed to various chemicals through inhalation while performing routine job duties. Many factors contribute to the degree of exposure experienced in this setting. The study objective was to characterize the impact of workplace conditions, anthropometric variability, and task orientation on exposure for a simulated routine operations task. A chemical exposure laboratory simulation study was designed to evaluate the dependent variable of chemical exposure level in the breathing zone for methane and sulfur hexafluoride. The independent variables were (i) posture of the worker, (ii) worker anthropometry, (iii) process configuration, and (iv) gas density. Pipe height was a significant predictor of gas concentration measured in the breathing zone when located in a position that encouraged the gas to enter the breathing zone of the worker. Worker anthropometry had a major impact; tall worker's (male) chemical concentrations exceeded those of the short worker (female) for methane simulations but the opposite resulted for sulfur hexafluoride. Also, worker posture had a significant impact on gas exposure where nonneutral postures were found to have higher levels of chemical concentration. The study findings indicate that the breathing zone location is altered by posture and worker height, which changes the exposures relative to the emission source depending on the gas density of the chemicals that are present. As a result, qualitative risk assessment cannot be performed accurately without accounting for these factors. Practically, controls may need to account for worker size differences and posture adaptations.

Simulated degradation of low-density polyethylene and polypropylene due to ultraviolet radiation and water velocity in the aquatic environment

Low-density polyethylene (LDPE) and polypropylene (PP) are the two main polymers with extensive applications. It might lead to plastic pollution and degradation in the aquatic environment. Former laboratory simulation studies of plastic degradation have been presented. However, most of the studies were only applied a single degradation agent without specific environmental conditions, which indicated a research gap. This research aimed to investigate LDPE and PP degradation under the influence of UV radiation and water velocity with specific environmental conditions. Five reactors of simulated aquatic environments were adjusted to desire calculated UV B dose of 158.98–438.91 W.S/cm2 and water velocity variations of the Surabaya River, one of Indonesia’s urban rivers that has been polluted by microplastics. The water velocity was set in high (0.3–0.6 m/s) and low ones (0.1–0.3 m/s) to represent the fluctuated river discharge at rain and dry seasons. Total simulation time of 480 h (8 h/day for 60 days simulation) has initiated LDPE and PP degradation. LDPE experienced more weight loss (3.07%) under the combined exposure of UV and high water velocity, than PP (2.37%) under high water velocity. Synergetic effects of photodegradation, physical-mechanical, and hydrolysis degradation mechanisms could affect more severe crack tip formation of LDPE and PP rather than in single agent simulation. Major surface morphology deterioration of LDPE and PP, changes in transmittance intensities, carbonyl index in this study have revealed the importance of combined exposure of UV radiation and water velocity to plastic degradation in the aquatic environment.

Recycling of heavy metal contaminated river sludge into unfired green bricks: Strength, water resistance, and heavy metals leaching behavior – A laboratory simulation study

Recycling the sludge in building materials is a promising approach to reduce construction costs and environmental pollution. However, when the sludge is used as a raw material the mechanical properties and environmental risks of sludge should be taken into consideration. In this study, heavy metals contaminated river sludge (CRS) incorporated into the production of unfired green bricks with the combination of hemihydrate phosphogypsum (HPG), ground granulated blast furnace slag (GGBFS), and Portland cement (PC). The mechanical properties of brick specimens were determined by conducting unconfined compressive strength (UCS) and water resistance tests, while the hydration products and strength formation mechanism were detected by XRD, TGA, and SEM-EDS investigation. Furthermore, the TCLP and SPLP tests were used to assess the heavy metals releasing behavior. The explored results show that the UCS of samples increases with the rise of the replacement level of PC by GGBFS. The highest UCS and softening coefficient of bricks were 15.24 MPa and 0.94 using the combinations of 60% CRS, 20% HPG along with 17% GGBFS and 3% PC. The microstructural analysis revealed that HPG could react with GGBFS and PC to generate massive ettringite (AFt). These AFt may bridge gypsum crystals to form a dense network microstructure. Additionally, specimens prepared in this study exhibited an excellent fixing capacity for heavy metals. The heavy metal immobilization rates of the optimal mixture were all higher than 99.41%.

Smart Core and Surface Temperature Estimation Techniques for Health-Conscious Lithium-Ion Battery Management Systems: A Model-to-Model Comparison

Estimation of core temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. It is impractical to measure the core temperature of each cell using physical sensors, while at the same time implementing a complex core temperature estimation strategy in onboard low-cost BMS is also challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models with different levels of accuracy and complexity. Broadly, there are first-order and second-order heat resistor–capacitor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study. The aim was to determine whether it is worth investing towards developing a second-order thermal model instead of a first-order model with respect to prediction accuracy considering the modeling complexity and experiments required. Both the thermal models along with the parameter estimation scheme were modeled and simulated in a MATLAB/Simulink environment. Models were validated using laboratory test data of a cylindrical 18,650 LIB cell. Further, a Kalman filter with appropriate process and measurement noise levels was used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models were analyzed for comparison purposes.

The Simultaneous Prediction of Soil Properties and Vegetation Coverage from Vis-NIR Hyperspectral Data with a One-Dimensional Convolutional Neural Network: A Laboratory Simulation Study

Remote sensing of land surface mostly obtains a mixture of spectral information of soil and vegetation. It is thus of great value if soil and vegetation information can be acquired simultaneously from one model. In this study, we designed a laboratory experiment to simulate land surface compositions, including various soil types with varying soil moisture and vegetation coverage. A model of a one-dimensional convolutional neural network (1DCNN) was established to simultaneously estimate soil properties (organic matter, soil moisture, clay, and sand) and vegetation coverage based on the hyperspectral data measured in the experiment. The results showed that the model achieved excellent predictions for soil properties (R2 = 0.88–0.91, RPIQ = 4.01–5.78) and vegetation coverage (R2 = 0.95, RPIQ = 7.75). Compared with the partial least-squares regression (PLSR), the prediction accuracy of 1DCNN improved 42.20%, 45.82%, 43.32%, and 36.46% in terms of the root-mean-squared error (RMSE) for predicting soil organic matter, sand, clay, and soil moisture, respectively. The improvement might be caused by the fact that the spectral preprocessing and spectral features useful for predicting soil properties were successfully identified in the 1DCNN model. For the prediction of vegetation coverage, although the prediction accuracy by 1DCNN was excellent, its performance (R2 = 0.95, RPIQ = 7.75, RMSE = 3.92%) was lower than the PLSR model (R2 = 0.98, RPIQ = 12.57, RMSE = 2.41%). These results indicate that 1DCNN can simultaneously predict soil properties and vegetation coverage. However, the factors such as surface roughness and vegetation type that could affect the prediction accuracy should be investigated in the future.