Average Emission Rate Research Articles

On the flammability and mechanical responses of abaca-reinforced composites: a machine learning-oriented approach

ABSTRACT This paper presents a comprehensive investigation into the predictive modeling of eco-friendly composite materials reinforced by Abaca fibers, Halloysite Nanotubes (HNT), and Egg Shell Powder (ESP) additives. Deep Neural Networks (DNNs) were employed to capture the complex behaviors of these materials under various testing conditions, including Cone Calorimeter Tests (CCT), micro-indentation with Vickers and Conical indenters, and three-point bending tests. The trained DNNs exhibited remarkable accuracy in predicting critical parameters such as Heat Release Rate (HRR), Average Rate of Heat Emission (ARHE), Total Heat Release (THR), Total Smoke Production (TSP), and Total Oxygen Consumption (TOC) during CCT. Additionally, the DNNs successfully replicated force-depth diagrams from Vickers and Conical indentations, showcasing their proficiency in modeling loading and unloading profiles. Furthermore, the flexural responses during three-point bending tests were accurately predicted, encompassing flexural modulus, the maximum flexural stress, strain at break, and energy. Validation through metrics such as Mean Squared Error (MSE) and coefficient of determination (R2) demonstrated the reliability of the DNNs in capturing material behaviors. Consequently, the study showcases the potential of machine learning, particularly DNNs, as a robust tool for predictive modeling in material science so that R2 values below 0.995 were not obtained for the trained DNNs as well as MSEs in the order of e−4.

Quantifying particulate matter emission rates from naturally ventilated dairy buildings by considering roof opening contributions

Roof openings are typically fitted to naturally ventilated dairy building (NVDB) for better ventilation but their impact on air pollutant emission calculations has not been fully considered. Particulate matter (PM) emission rate (ER) for NVDB rely on the total ventilation rate (VR), outdoor PM concentration and average indoor PM concentration sampled either under the roof (Roof Sampling) or in the cubicle area (Cubicle Sampling), which may show large deviations due to its spatiotemporal variation of PM concentrations and complex airflow patterns. This study utilised a novel ER calculation method (Joint Sampling) that computes the respective emission from the roof and sidewall openings by matching each outlet's VR and PM concentration. By year-round field measurements of PM2.5 and the total suspended particulates (TSP), results showed that annual average ERs of PM2.5 and TSP were 10.8 mg h−1 cow−1 and 45.7 mg h−1 cow−1 for Roof Sampling, 12.7 mg h−1 cow−1 and 40.7 mg h−1 cow−1 for Cubicle Sampling, and 11.7 mg h−1 cow−1 and 45.9 mg h−1 cow−1 for Joint Sampling. Considering the Joint Sampling results were relatively true, Roof Sampling exhibited a maximum underestimate of PM2.5 emissions of 20.8% when sidewall curtains were fully opened, whilst Cubicle Sampling demonstrated a maximum overestimate of TSP of 10.2% when the aperture was closed. Using Joint Sampling, the roof opening contributed 39.3% and 24.4% of the annual PM2.5 and TSP emissions. When sidewall openings are partially or fully closed, the Joint Sampling calculation is preferable to estimate the ER of PM.

Patterns and Drivers of Greenhouse Gas Emissions in a Tropical Rubber Plantation from Hainan, Danzhou

The intensification of global climate change has made the study of greenhouse gas (GHG) emissions increasingly important. To gain a deeper understanding of the emission characteristics and driving factors of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) from rubber plantation soils, this study conducted a 16-month continuous observation in a rubber plantation in Danzhou, Hainan, employing the static chamber method for the monthly sampling and measurement of GHG emissions while analyzing the soil’s physical and chemical properties. The results indicated that the N2O flux exhibited no significant diurnal variation between the dry and rainy seasons, with an average emission rate of 0.03 ± 0.002 mg·m−2·h−1. A clear seasonal trend was observed, with higher emissions in summer than in winter, resulting in an annual flux of 3 kg·hm−2·a−1 (equivalent to 1.9 kg N·hm−2·a−1). N2O emissions were significantly correlated with soil temperature and moisture, explaining 46% and 40% of the variations, respectively, while soil ammonium nitrogen content also significantly influenced N2O and CO2 emissions. The rubber plantation soil acted as a source of N2O and CO2 emissions and a sink for CH2, with lower emissions of N2O and CO2 during the daytime compared to nighttime, and higher CH4 uptake during the daytime. In the dry season, there was a significant positive correlation between N2O and CO2 emissions (R2 = 0.74, p < 0.001). This study reveals the diurnal and seasonal patterns of GHG emissions from rubber plantation soils in Hainan and their interrelationships, providing a scientific basis for the low-carbon management of rubber plantations and GHG mitigation strategies, thereby contributing to attempts to reduce the impact of rubber cultivation on climate change.

Air Pollutant Emission Factors of Inland River Ships under Compliance

Inland river ships (IRSs) use diesel with a lower sulfur content and emit relatively low emissions, making it challenging to monitor their emissions. Sniffer monitoring equipment was installed from August 2020 to June 2022 at the Gezhou Dam of the Yangtze River and monitored emissions from 8,238 IRSs passing through the lock. We partnered with the maritime department to select 100 ships passing through the lock to extract fuel oil samples for direct fuel sulfur content (FSC) detection, which determined the actual FSC of the passing ships. The monitoring data from these 100 ships indicated that the relative error of the SO2 emission factors (EFs) and FSC results is significant at the 10-parts-per-million level. The monitoring data from the remaining 8,138 ships showed that the EFs of NO, NO2, PM2.5, and PM10 were 24.02 ± 16.92 g kg−1, 10.30 ± 18.08 g kg−1, 0.72 ± 0.60 g kg−1, and 0.92 ± 0.70 g kg−1, respectively. The NOx EFs of container ships are higher than those of other ship types, while the PM EFs for different ship types do not significantly differ. Based on these EFs, we calculated the average emission rates for different types of ships passing through locks, which is a real-time measurement method for estimating ship emissions. In addition, a comparison of ship EF measurements over the past 20 years revealed that EF values for SO2, NOx, and PM exhibited a downward trend, with the calculated results of the current study determined to be the lowest numerical level.

Purcell-Induced Bright Single Photon Emitters in Hexagonal Boron Nitride.

Single photon emitters (SPEs) in hexagonal boron nitride (hBN) are elementary building blocks for room-temperature on-chip quantum photonic technologies. However, fundamental challenges, such as slow radiative decay and nondeterministic placement of the emitters, limit their full potential. Here, we demonstrate large-area arrays of plasmonic nanoresonators (PNRs) for Purcell-induced room-temperature SPEs by engineering emitter-cavity coupling and enhancing radiative emission. Gold-coated silicon pillars with an alumina spacer enable a 10-fold local-field enhancement in the emission band of native hBN defects. We observe bright SPEs with an average saturated emission rate surpassing 5 million counts per second, an average lifetime of <0.5 ns, and 29% yield. Density functional theory reveals the beneficial role of an alumina spacer between hBN and gold, mitigating the electronic broadening of emission from defects proximal to the metal. Our results offer arrays of bright, heterogeneously integrated single-photon sources, paving the way for robust and scalable quantum information systems.

Flame Retarded Adhesive Tapes and Their Influence on the Fire Behavior of Bonded Parts

AbstractPressure-sensitive adhesive tapes are used in automotives, railway vehicles and construction, where flame retardancy is of major importance. This is why industrial applicants often buy, and industrial tape manufacturers often produce, flame-retardant adhesive tapes, advertised for their good flammability characteristics. Yet, how flame-retardant tapes influence the fire behavior of bonded materials is a rather open question. To investigate this issue, three different substrates were bonded, using eight double-sided adhesive tapes containing two different carriers and two different flame retardants. The bonded substrates were compared to their monolithic counterparts in terms of flammability, fire behavior and fire stability. The fire behavior of adhesive tape bonded materials differed significantly from the monolithic substrates. The usage of different adhesive tapes let to different burning behavior of the bonded materials mainly due to different carrier systems. In contrast, the implementation of flame retardant into the adhesive had rather minor or no effect on the burning behavior of the bonded substrates despite their positive effect on the flammability of the free-standing tape. The carrier changed the HRR curve in the cone calorimeter and was able to both, reduce and increase fire hazards. Using the carrier with the better fire performance can lower the fire growth rate by 20%, the peak of heat release rate by 27%, and the maximum average rate of heat emission by 30% in cone calorimeter tests. Overall, the fire behavior of bonded materials is a complex interaction between substrate, adhesive, and carrier, and depends on the fire scenario the materials are exposed to.

High rates of hydrogen sulfide emissions measured from marginal oil wells near Austin and San Antonio, Texas

Marginal oil and gas wells, or wells that produce less than 15 barrels of oil equivalent per day, represent 80% of actively producing wells in the United States, although they produce less than 10% of energy supply. Marginal wells are a disproportionate source of methane (CH4) relative to their production, and they emit harmful air pollutants, such as benzene and other hydrocarbons found in oil and natural gas. We made direct measurements of CH4 and hydrogen sulfide (H2S) emissions from 46 wellheads in the Luling Field, Caldwell County, Texas, just east of the Austin/San Antonio Metroplex. We found that these wells are venting natural gas and are a large source of hydrogen sulfide (H2S), a poisonous air pollutant. Hydrogen sulfide emission rates ranged from 0 to 5 ± 0.5 g H2S hr−1 with an average emission rate of 1.6 ± 0.1 g H2S hr−1. We also found ambient concentrations of H2S at dangerous levels (>100 ppm) near many of the wells. Methane emission rates were in line with previous studies of marginal wells, ranging from 0.0 to 2770 ± 390 g CH4 hr−1, with a skewed distribution and average emission rate of 710 ± 100 g CH4 hr−1. Oil production records from Texas were incomplete: some wells had oil production data from the year of sampling, but many had no production data for several years or decades, although they were actively pumping while we were on site. Interviews with local residents indicate that the closing of the county gas processing plant and subsequent loss of gathering lines may be the cause of gas venting and CH4 and H2S emissions from production sites. This deserves further scrutiny, as marginal wells in this region are a major source of H2S, a health hazard to people living and working nearby.

Human exposure to aerosol from indoor gas stove cooking and the resulting cardiovascular system responses

The effect of cooking aerosol on the human heart was investigated in this study. The heart rate and blood pressure of 33 healthy adults were monitored before, exactly after, and two hours post-exposure (30 minutes, 60 minutes, 90 minutes, and 120 minutes after cooking). One hundred twenty grams of ground beef was fried in sunflower oil for twenty minutes using a gas stove without ventilation. Ultrafine particles, indoor temperature, relative humidity, carbon dioxide, oil, and meat temperatures were monitored during the experiment. The average particle emission rate (S) and average decay rate (a+k) for meat frying were found to be 2.09×1013 (SD=3.94 ×1013, R2=0.98, P <0.0001) particles/min, and 0.055 (SD=0.019, R2=0.91, P <0.0001) particles/min, respectively. No statistically significant changes in diastolic blood pressure (DBP) and heart rate (HR) were observed. The average systolic blood pressure (SBP) statistically significantly increased from 98 mmHg (before the exposure) to 106 mmHg 60 minutes after the exposure. The results suggested that frying emission statistically significantly impacted blood pressure.

A fuel cell powered rack prototype for data center application with waste heat recovery: design consideration and experimental verification

The combination of data center and PEMFC has been a promising data center zero-carbon emission solution. However, the relevant experimental studies are very rare and most work only solved the simple electrical coupling. This paper proposed a new in-rack data center servers and PEMFC coupling design scheme considering both the electrical coupling and thermal management coupling of the servers and PEMFC, and built a cabinet prototype for the first time. The complete multi-condition continuous experiment on the PEMFC system fully demonstrates the servers power supply stability of the prototype with the fast tested power response capability of 4.9 kW in 0.1 s. The experiments under rated condition (when the servers power is 5 kW) were conducted and the carbon emission level and efficiency performance of the prototype are analyzed. Under the rated condition, the highest prototype CHP efficiency is 64.1 % while the prototype can provide 41.6 ℃ hot water with 3.04 L·min-1 and the lowest prototype CHP efficiency is 59.8 % while the prototype can provide 61.1 ℃ hot water with 1.33 L·min-1. The prototype maintains the zero-carbon (or negative carbon) emission of servers. The average operation carbon emission rate is -35 g·h-1. Compared with the full grid supporting data center, the power average prototype operation carbon reduction rate is 0.13 g·s-1·kW-1. The application potential of the proposed data center and PEMFC coupling scheme is demonstrated with the prototype experiment results from the advantage of carbon emission and heat recovery potential.

Using metal oxide gas sensors to estimate the emission rates and locations of methane leaks in an industrial site: assessment with controlled methane releases

Abstract. Fugitive methane (CH4) emissions occur in the whole chain of oil and gas production, including from extraction, transportation, storage, and distribution. Such emissions are usually detected and quantified by conducting surveys as close as possible to the source location. However, these surveys are labour-intensive, are costly, and fail to not provide continuous emissions monitoring. The deployment of permanent sensor networks in the vicinity of industrial CH4 emitting facilities would overcome the limitations of surveys by providing accurate emission estimates, thanks to continuous sampling of emission plumes. Yet high-precision instruments are too costly to deploy in such networks. Low-cost sensors using a metal oxide semiconductor (MOS) are presented as a cheap alternative for such deployments due to their compact dimensions and to their sensitivity to CH4. In this study, we demonstrate the ability of two types of MOS sensors (TGS 2611-C00 and TGS 2611-E00) manufactured by Figaro® to reconstruct a CH4 signal, as measured by a high-precision reference gas analyser, during a 7 d controlled release campaign conducted by TotalEnergies® in autumn 2019 near Pau, France. We propose a baseline voltage correction linked to atmospheric CH4 background variations per instrument based on an iterative comparison of neighbouring observations, i.e. data points. Two CH4 mole fraction reconstruction models were compared: multilayer perceptron (MLP) and second-degree polynomial. Emission estimates were then computed using an inversion approach based on the adjoint of a Gaussian dispersion model. Despite obtaining emission estimates comparable with those obtained using high-precision instruments (average emission rate error of 25 % and average location error of 9.5 m), the application of these emission estimates is limited to adequate environmental conditions. Emission estimates are also influenced by model errors in the inversion process.

The effect of human heterogeneity on the transmission of viral respiratory diseases under air pollution

The impact of air pollutants on the human respiratory system has received more and more attention. However, due to the differences in human characteristics and the strength of protective measures, different people have different symptoms in air pollution and viral infection environments. In this paper, an SI1I2P dynamic model of respiratory diseases infected by virus under air pollution is established by introducing air pollutant concentration compartment. Qualitative research shows that there are seven equilibria in the system, the daily average emission and clearance rate of pollutants are the key parameters affecting the existence and stability of equilibria. In this paper, by using Sotomayor’s theorem and center manifold theory, it is proved that the system undergoes saddle–node bifurcation or Bogdanov–Takens bifurcation of co-dimension 3 at the boundary equilibrium, and exhibits saddle–node bifurcation at the endemic equilibrium. Numerical simulation results show that wearing masks in haze weather can not only reduce the number of allergic patients, but also reduce the number of viral patients. In addition, reducing the daily average emission of air pollution and increasing its clearance rate can also reduce the number of allergic patients. It is worth mentioning that this measure is more effective in controlling viral respiratory diseases.

Cascade computational model for prediction impact of transient depth change on combustion parameters of certain timber species under continuous heating rate

The purpose of this research is to examine the effects of depth variation and exposure duration on the combustion characterization of the Maple wood species (Acer platanoides L.) and Walnut (Juglans regia L.) according to ISO 5660–1 in case of exposing the specimens to a constant heating rate 50 kWm−2. The delivered experimental data by cone calorimeter apparatus is used to train, test, and validate the optimized cascade forward artificial neural network with topology 2–8–8–12–2. This structure is simulated to predict the target parameters: the heat release rate (HRR) and the mass burning rate (MBR). With real systems, it is possible to achieve a reasonable performance and the closest approximations for the cascade model. The experimental combustion parameters: time of flame out, average specific mass burning rate, total heat release, maximum average rate of heat emission, and fire growth index are considered to make a systematic analysis and assessment with change depth. Three regions are considered for investigation of output target curves, thermally thin (d ≤ 1.1 cm), thermally medium (1.1 cm < d< 1.5 cm), thermally thick (d≥ 1.5cm). The findings demonstrate that independent of exposure period, an increase in depth change causes a sizable reduction in the HRR and MBR. Beyond 1.5 cm of depth in thermally thick regions, there is no discernible effect of time instant on changes in target parameters. In contrast, HRR and MBR gradients across depth in thermally thin regions are striking.

Effects of fuel and driving conditions on particle number emissions of China-VI gasoline vehicles: based on corrections to test results.

The increasing number of vehicles are emitting a large amount of particles into the atmosphere, causing serious harm to the ecological environment and human health. This study conducted the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) to investigate the emission characteristics of particle number (PN) of China-VI gasoline vehicles with different gasoline. The gasoline with lower aromatic hydrocarbons and olefins reduced particulate matter (PM) and PN emissions by 24% and 52% respectively. The average PN emission rate of the four vehicles during the first 300s (the cold start period) was 7.2 times that of the 300s-1800s. Additionally, because the particle transmission time and instrument response time, the test results of instantaneous emissions of PN were not synchronized with vehicle specific power (VSP). By calculating the Spearman correlation coefficient between pre-average vehicle specific power (PAVSP) and the test results of PN instantaneous emissions, the delay time was determined as 10s. After the PN emissions results were corrected, the PN emissions were found to be more related to VSP. By analyzing the influence of driving status on emission, this study found that vehicles in acceleration mode increased PN emissions by 76% compared to those in constant speed mode.

The effect of repeated washings on thermal protective performances of one most used structural firefighting turnout gear in the Gauteng Province in South Africa

Fire performance measurements of one of the most used firefighting protective ensembles (also called turnout gears), in terms of thermal and smoke hazards, were determined with the cone calorimeter, that of thermal stability were determined with thermogravimetric analyzer, the physical inspection (physical degradation) of the surface done with the scanning electron microscopy, and energy dispersive spectroscopy measurements determined the elemental compositions of the detergent used in washing and the residual elements in the turnout gears. The cone calorimeter results indicated that the values of the thermal performance parameters, namely: peak heat release rate, maximum average rate of heat emission, and fire growth rate index, all decrease with increasing number of washing cycles, while the smoke parameters: peak smoke production rate, smoke growth rate index, total smoke release, and related sustained flaming values, all increase with increasing number of washing cycles. From the thermogravimetric analyzer measurements, the thermal stability of the turnout gears decrease with increasing number of washings.

Effects of water-nitrogen interactions on NH3 and N2O emissions and yield in winter wheat cropland

To investigate the effects of different irrigation and nitrogen application modes on nitrogen gaseous loss in winter wheat farmland, we conducted a field experiment at Changqing Irrigation Experiment Station in Shandong Province, with two irrigation levels (80%-90% θf(I1) and 70%-80% θf(I2)) and three nitrogen application levels (conventional nitrogen application of 240 kg·hm-2(N1), nitrogen reduction of 12.5% (N2), and nitrogen reduction of 25% (N3)). The results showed that ammonia volatilization and nitrous oxide emission rate peak appeared within 2-4 days after fertilization or irrigation. The ammonia volatilization rate during the chasing fertilizer period was significantly higher than that during the basal fertilizer period. Compared with other treatments, the ave-rage ammonia volatilization rate of I2N2 treatment during the chasing fertilizer period was reduced by 10.1%-51.6%, and the average nitrous oxide emission rate over the whole growth period was reduced by 15.4%-52.2%. The ammonia volatilization rate was significantly positively associated with surface soil pH value and ammonium nitrogen content, while the nitrous oxide emission rate was significantly positively associated with nitrate content in topsoil. The accumulation amount of soil ammonia volatilization and nitrous oxide emission ranged from 0.83-1.42 and 0.11-0.33 kg·hm-2, respectively. Moderate reduction of irrigation water and nitrogen input could effectively reduce cumulative amounts of ammonia volatilization and nitrous oxide emission from winter wheat farmland. The cumulative amounts of ammonia volatilization and nitrous oxide emission under I1N3 and I2N2 treatments were signi-ficantly lower than those under other treatments. The highest winter wheat yield (5615.6 kg·hm-2) appeared in I2N2 treatment. The irrigation water utilization efficiency of I2 was significantly higher than that of I1, with the maximum increase rate of 45.2%. Compared with N1 and N3 treatments, the maximum increase rate of nitrogen fertilizer productivity and agricultural utilization efficiency in N2 reached 15.2% and 31.8%, respectively. In conclusion, the treatment with 70%-80% θf irrigation level and 210 kg·hm-2 nitrogen input could effectively improve the utilization efficiency of irrigation water and nitrogen fertilization and reduce gaseous loss from winter wheat farmland.

Methane Emissions From the Qinghai‐Tibet Plateau Ponds and Lakes: Roles of Ice Thaw and Vegetation Zone

AbstractComprehensive seasonal observation is essential for accurately quantifying methane (CH4) emissions from ponds and lakes in permafrost regions. Although CH4 emissions during ice thaw are important and highly variable in high‐latitude freshwater ponds and lakes (north of ∼50°N), their contribution is seldom included in estimates of aquatic‐atmospheric CH4 exchange across different alpine ecosystems. Here, we characterized annual CH4 emissions, including emissions during ice thaw, from ponds and lakes across four alpine vegetation zones in the Qinghai‐Tibet Plateau (QTP) permafrost region. We observed significant spatial variability in annual CH4 emission rates (8.44−421.05 mmol m−2 yr−1), CH4 emission rates during ice thaw (0.26−144.39 mmol m−2 yr−1), and the contribution of CH4 emissions during ice thaw to annual emissions (3−33%) across different vegetation zones. Dissolved oxygen concentration under ice, along with substrate availability and water salinity, played critical roles in influencing CH4 flux during ice thaw. We estimated annual CH4 emissions from ponds and lakes in the QTP permafrost region as 0.04 (0.03−0.05) Tg CH4 yr−1 (median (first quartile−third quartile)), with approximately 20% occurring during ice thaw. Notably, the average areal CH4 emission rate from ponds and lakes in the QTP permafrost region amounts to only 8% of that from high‐latitude waterbodies, primarily due to the dominance of large saline lakes with lower CH4 emission rates in the alpine permafrost region. Our findings emphasize the significance of incorporating comprehensive seasonal observation of CH4 emissions across different vegetation zones in better predicting CH4 emissions from alpine ponds and lakes.

Tree stem methane emissions: Global patterns and controlling factors

Growing evidence suggests that methane (CH4) emissions from tree stems are a potentially significant atmospheric source. However, a comprehensive global assessment of the general pattern and the controlling factors of stem CH4 emissions is still unavailable. Here, we present a global data-synthesis of 1081 observations from 62 studies to explore the patterns of stem CH4 emission rate in upland and wetland ecosystems and their controlling factors. The global average stem CH4 emission rate in uplands was 2.04 ± 0.61 nmol m−2s−1, which was significantly lower than in wetlands (87.08 ± 19.49 nmol m−2s−1). Angiosperm stem CH4 emission rates were significantly higher than gymnosperm in both upland and wetland ecosystems. Meanwhile, stem CH4 emission rate in inland wetlands (101.78 ± 27.44 nmol m−2s−1) was significantly higher than in coastal wetlands (56.21 ± 19.23 nmol m−2s−1). In both wetland and upland ecosystems, stem CH4 emission rate decreased with increasing sampling height, but increased as soil CH4 emission rate increased. However, the relationship between stem CH4 emissions and soil CH4 fluxes was much weaker for uplands, but very strong for wetlands. In wetlands, stem CH4 emission rate was also regulated by plant properties, as it was negatively correlated with wood specific density, but positively correlated with stem lenticel density. In uplands, tree diameter negatively affected stem CH4 emission rate. Overall, our results shed light on the magnitude and controlling factors of stem CH4 emissions in upland and wetland ecosystems and could facilitate their upscaling to ecosystems and identify the role of stem CH4 emissions in global CH4 budgets.

Enhancing flame and electrical surface discharge resistance in silicone rubber composite insulation through aluminium hydroxide, clay, and glass fibre additives

Silicone rubber (SR) is a leading polymer used in electrical outdoor insulation applications due to its superior hydrophobic characteristics. However, the low flame and electrical surface discharge resistance of SR limit its broad viability and challenge its integrity in severe outdoor working conditions. This work attempts to explore the flame retardancy and surface discharge characteristics of SR co-filled with aluminium hydroxide (ATH), nanoclay montmorillonite (MMT), and chopped glass fibre (GF). Results indicate that the incorporation of ATH/MMT/GF could assist in improving the fire and surface discharge resistance of the SR material. It is noted that the maximum average rate of heat emission (MARHE) and total smoke production (TSP) are measured at 24.93 kW/m2 and 0.48 m2 in SRE, relative to 61.29 kW/m2 and 6.02 m2 in SRB. Using finite element analysis (FEA), the maximum electric field strength is computed at 4.66 × 106 V/m in the air gap coupled with a high-voltage (HV) plate and sample. SRE exhibits a higher partial discharge inception voltage (PDIV) value of 2.32 kVrms than its counterparts, while the maximum discharge magnitude (Qmax) is computed at 7095 pC, relative to 7746 pC in SRB. SRE emerges as a preferable SR composite to be used in electrical insulation applications with excellent flame and surface discharge resistance characteristics.

Burning Properties of Combined Glued Laminated Timber

This study delved into the combustion properties of combined glulam bonded using polyurethane (PUR) and resorcinol-phenol-formaldehyde (RPF) adhesives. The experiment involved three distinct wood species, namely, spruce, alder, and beech, which were combined in homogeneous, non-homogeneous symmetrical, and non-homogeneous asymmetrical arrangements. These species were selected to represent a spectrum, namely, softwood (spruce), low-density hardwood (alder), and high-density hardwood (beech). The varying combinations of wood species illustrate potential compositions within structural elements, aiming to optimize mechanical bending resistance. Various parameters were measured during combustion, namely, the heat release rate (HRR), peak heat release rate (pHRR), mass loss rate (MLR), average rate of heat emission (ARHE), peak average rate of heat emission (MARHE), time to ignition (TTI), and effective heat of combustion (EHC). The findings indicate that incorporating beech wood into the composite glulam resulted in an increase in heat release, significantly altering the burning characteristics, which was particularly evident at the second peak. Conversely, the use of spruce wood exhibited the lowest heat release rate. Alder wood, when subjected to heat flux at the glued joint, displayed the highest heat emission, aligning with the results for EHC and MARHE. This observation suggests that wood species prone to early thermal decomposition emit more heat within a shorter duration. The time to ignition (TTI) was consistent, occurring between the first and second minute across all tested wood species and combinations. Notably, when subjected to heat flux, the glulam samples bonded with PUR adhesive experienced complete delamination of the initial two glued joints, whereas those bonded with RPF adhesive exhibited only partial delamination.

Spatiotemporal variations in emission and particulate matter concentration outside a concentrated layer feeding operation

A year-round monitoring of Particulate Matter (PM) less than 2.5 μm in aerodynamic diameter (PM2.5) and Total Suspended Particulate (TSP) from a conventional cage laying hen house was conducted to reveal their spatiotemporal variations of concentrations downwind of tunnel fans. The PM Emission Rate (ER) and the correlations between PM with meteorological parameters and ventilation rate were studied. Ten self-developed Particle Concentration Monitoring Units were distributed to multiple horizontal (2, 25, and 50 m) and vertical (2 and 5 m) locations for PM examination. Four PM2.5 concentration categories were classified: good (0–35 μg m−3), moderate (35–75 μg m−3), unhealthy (75–150 μg m−3), and very unhealthy (150–350 μg m−3). Annual and monthly percentages of PM2.5 and TSP sampling hours for each category were calculated. Significant temporal variations in ER were observed, with monthly average ER ranging from 0.05 to 0.86 mg d−1 hen−1 for PM2.5 and 1.40–8.90 mg d−1 hen−1 for TSP. Approximately 10–40% of PM2.5 sampling hours exceeded 75 μg m−3, while no TSP concentration was higher than the recommended threshold. The monthly percentage for the “very unhealthy” PM2.5 category was higher in winter, whereas the highest monthly percentage for the 800–1,200 μg m−3 TSP category was found in summer. Higher PM2.5 concentrations were prone to be observed at further sampling points, while higher TSP concentrations were mostly detected near the fans or on both sides of the sampling area. PM2.5 and TSP were positively correlated with ambient temperature and ventilation rate, while negatively correlated with relative humidity.