Air CO2 Concentration Research Articles

Hidden Markov models for presence detection based on CO2 fluctuations.

Presence sensing systems are gaining importance and are utilized in various contexts such as smart homes, Ambient Assisted Living (AAL) and surveillance technology. Typically, these systems utilize motion sensors or cameras that have a limited field of view, leading to potential monitoring gaps within a room. However, humans release carbon dioxide (CO2) through respiration which spreads within an enclosed space. Consequently, an observable rise in CO2 concentration is noted when one or more individuals are present in a room. This study examines an approach to detect the presence or absence of individuals indoors by analyzing the ambient air's CO2 concentration using simple Markov Chain Models. The proposed scheme achieved an accuracy of up to 97% in both experimental and real data demonstrating its efficacy in practical scenarios.

Synthesis of Inexpensive Ternary Metal Oxides by a Co-Precipitation Method for Catalytic Oxidation of Carbon Monoxide.

By using a simple co-precipitation method, new Fe2 O3 -based nanocatalysts (samples) were synthesized. The samples were composites of two or three transition metal oxides, MOx (M=Fe, Mn, Co, Ni, and Cu). The average size of CuO crystallites in the composites composed of two oxide components (CuO-Fe2 O3 ) was about 14.3 nm, while in those composed of three (CuO-MnOx -Fe2 O3 ), the composite's phase compositions were almost in the amorphous form when annealing the sample at 300 °C. The latter sample had a specific surface area higher than that of the former, 207.9 and 142.1 g/m2 , respectively, explaining its higher catalytic CO oxidation. The CO conversion over the CuO-MnOx -Fe2 O3 -300 catalyst (1 g of catalyst, 2600 ppm of CO concentration in air, and 1.0 L/min of gas flow rate) begins at about 40 °C; the temperature for 50 % CO conversion (t50 ) is near 82 °C; and CO removal is almost complete at t99 ≈110 °C. The activity of the optimal sample was tested in different catalytic conditions, thereby observing a high durability of 99-100 % CO conversion at 130 °C. The obtained results were derived from XRD, FTIR, BET, SEM, elemental analysis and mapping, as well as catalytic experiments.

Monitoring of carbon dioxide and equilibrium moisture content for early detection of physicochemical and morphological changes in soybeans stored in vertical silos

In the context of grain storage, impurities and soybeans defects in soybeans can significantly impact the equilibrium moisture content. This, cause moisture migration and heating of the stored product, leading to increased respiratory activity. Furthermore, temperature measurements within stored grain mass do not provide sufficient information for effective grain quality monitoring, primarily due to the grains excellent thermal insulating properties. To address this issue, we propose a different approach: monitoring the equilibrium moisture content and CO2 concentration as indicators of soybean respiration within the intergranular spaces of the stored grain mass. This study propose monitoring the CO2 concentration in the intergranular air along with environmental variables for early detection of physicochemical and morphological changes in soybeans stored in vertical silos using near infrared spectroscopy, X-ray diffraction and scanning electron microscopy. Thermogravimetry and spectrometry analyses revealed that the interrelationships among variables had a direct impact on soybean quality attributes. Specifically, the presence of soybeans with 5.2 % impurities led to an increased in respiration rates, resulting in a CO2 concentration of up to 5000 ppm and the consumption of up to 3.6 % of dry matter. Consequently, there were changes in the percentage of ash, proteins, fibers, and oils compositions. These findings highlight the potential for indirect assessments, enabling the prediction of physicochemical quality and contamination of soybeans stored in vertical silos through continuous monitoring of CO2 concentration and equilibrium moisture content.

A systematic review of the relationship between housing environmental factors and bovine respiratory disease in preweaned calves - Part 2: Temperature, relative humidity and bedding

Bovine respiratory disease (BRD) is a challenge in all housed farming systems that raise calves. Farm to farm variation in BRD prevalence can be partially attributed to variation in host immunity, pathogens and housing environment. Unlike host immunity and BRD pathogens, housing environment has not been well investigated. The objective of this systematic review was to identify the measurable environmental variables associated with BRD in housed preweaned calves. Pubmed, CAB Direct and Scopus databases were searched. To be considered for inclusion publications had to be published in English, before 24 November, 2022 and include at least one measurable/ manipulated environmental variable and a standardized method of BRD detection. In total 12 publications were included in this review. In this second part of the systematic review the environmental variables identified were; temperature (9 publications); relative humidity (8 publications); bedding (5 publications); ventilation (1 publication); air CO2 concentration (1 publication) and air velocity (4 publications). Of the publications that were examined a statistically significant relationship to BRD was identified in 4/9 publications examining temperature, 3/8 examining relative humidity, 2/4 examining air velocity, 2/5 examining bedding, 0/1 examining ventilation rates and 0/1 examining CO2 concentration. From this review it is clear high airspeed at calf level should be avoided as should deep, wet pack bedding. The relationship between BRD prevalence and both high and low temperature requires more investigation to identify temperature thresholds associated with increased risk of BRD as well as the most influential modifiers. An optimal environment for housed calves could not be clearly identified in this review.

Investigation of indicators for personal exposure and occupancy in offices by using smart sensors

Despite the advent of smart building sensors, real-time methods for capturing inhalation exposure and occupancy are limited. This study utilized stationary and wearable environmental sensors, along with Decision Tree and correlation analyses, to determine the optimal set of indicators for approximating dynamic inhalation exposures and occupancy in office environments. In a 2-week field campaign in two Swiss office buildings, real-time measures of air temperature, relative humidity, CO2, and size-resolved particle concentrations were taken at two scales: personal – via personalized vests with sensors for personal exposure detection; and room – via stationary sensors at sidewalls and office desks. Occupancy and activity profiles were collected at three scales: personal – via smartwatches; room – via visual inspections; and building – via a cloud-based location service system. A desk-mounted CO2 sensor in the center of an office was an effective indicator of personal exposures to CO2, PM2.5, and PM10. Sidewall CO2 measurements accurately captured room occupancy in open-plan offices, while desk-mounted PM10 sensors were effective in areas with transient occupancy (e.g., cafeteria). Findings from this study aid improved understanding of the complex dynamics of air pollutants in offices, and could support the development of refined methods for smart building monitoring and ventilation control.

Monitoring CO2 Hazards of Volcanic Origin: A Case Study at the Island of Vulcano (Italy) during 2021–2022

The La Fossa volcano is near the inhabited zone of the island of Vulcano and is a suitable case for studying gas sources of different geological origins. Since the last eruption, fumarolic-solfataric activity has interested this area with fumarolic emissions, mainly at the top of the volcanic cone and at Vulcano Porto. In recent decades, the anomalous degassing zones on the island have not significantly changed their location. On the contrary, there have been several significant changes in the emission rate due to the addition of volcanic gas. In these zones, CO2 flux from the ground is responsible for a decrease in the indoor air quality. A recent increase in volcanic degassing led to an increase in the gas hazard in the inhabited area of Vulcano Island, and people were temporarily displaced from Vulcano Porto. The results of this study show that a monitoring system can be used for the early detection of transients in soil CO2 flux (φCO2) in the anomalous degassing zone of Vulcano. Synchronous monitoring of φCO2 and outdoor air CO2 concentration has shown variations in volcanic degassing that affect outdoor air CO2 concentration in the populated zone of Faraglione.

Estimating Dynamic Non‐Water‐Limited Canopy Resistance Over the Globe: Changes, Contributors, and Implications

AbstractNon‐water‐limited canopy resistance (rcs, also known as the bulk stomatal resistance or surface resistance) is a critical variable in estimating potential evapotranspiration (PET), which is widely used in ecohydrology related fields. However, quantifying rcs is a challenging work. Here we develop an approach for estimating rcs over the globe. Comparing results over the globe and across 10 ET data sets (used as inputs), which are based on diverse mechanisms and algorithms, we find that the approach can capture canopy resistance well (mean correlation of 0.84 ± 0.04, mean relative Root Mean Squared Error of 4.4% ± 1.0%, and mean relative Mean Absolute Error of 5.8% ± 1.4%), and the estimated rcs are very close to those estimated using another method (R2 = 0.92), which is based on a quite different hypothesis that is only suitable for saturated regions. Based on these, we find that the rcs shows an overall increasing trend (0.43 ± 0.13 s m−1 year−1) over the globe (at 77.6% ± 3.9% of the land grid cells) during 1982–2014, and the air temperature dominates the variabilities of rcs in regions with decreasing rcs (mean relative contribution of 57.9% ± 11.4%), while air CO2 concentration controls the changes in rcs in regions with increasing rcs (mean relative contribution of 47.3% ± 8.0%). Moreover, we also find that the traditional PET estimator explicitly overestimates the increasing trends in PET, and tends to overestimate (underestimate) the increasing (decreasing) trends in regions with increasing (decreasing) PET. These findings can improve our knowledge on the complex water‐vegetation‐environment interactions and would be helpful for developing more accurate models for quantifying the impacts of global change on water resources.

Spatial, Temporal, and Vertical Variability of Ambient Environmental Conditions in Chinese Solar Greenhouses during Winter

The monitoring and control of environmental conditions are crucial as they influence crop quality and yield in Chinese solar greenhouses (CSGs). The objectives of this study were to assess the spatial, temporal, and vertical variability of major environmental parameters in CSGs during winter and to provide greenhouse climate/microclimate characteristics in order to facilitate the monitoring and control of greenhouse environmental conditions. A wireless sensor network (WSN) was deployed in two CSGs: one with crops and one without. Sensors were placed at different locations inside and outside the greenhouses, and the air temperature, humidity, CO2 concentration, light intensity, solar radiation, and wind conditions were measured and analyzed. Significant variability in the spatial, temporal, and vertical distribution of environmental factors was observed in both greenhouses. The average minimum and maximum temperatures and humidity inside the CSG with crops were 9.96 °C (4:00 h) and 24.5 °C (12:00 h), and 32.6% (12:00 h) and 92.1% (5:00 h), respectively. The temperature difference was 2.2 °C between layers in the CSG without crops and 1.4 °C between layers in the CSG with crops. The CO2 concentration in the different layers inside the CSG with crops was highest at night. The average maximum light intensity inside the CSG with crops was 32,660.19 lx, 36,618.12 lx, and 40,660.48 lx (12:00 h to 13:00 h) in the bottom, middle, and top layers, respectively. Sensor positioning in the greenhouse was evaluated by considering the sensors’ data variability. The findings of this study could aid in the development of a better monitoring and control system for CSG’s microclimate during winter. More research is needed on greenhouse microclimate control systems based on this variability analysis, which could improve crop quality and yield in greenhouses.

Rapeseed plant: Bio-stimulation effects of plant growth-promoting actinobacteria on metabolites and antioxidant defense system under elevated CO2 conditions.

The present study set out to evaluate the potential of plant growth-promoting actinobacteria (PGPR) in improving some physiological and molecular parameters of rapeseed (Brassica napus L.) plants under ambient and elevated CO2 conditions by assessing some nitrogen and sulfur-containing metabolites, antioxidant defense system, and antimicrobial activity. With this aim, a pot experiment was conducted where the rapeseed plants were treated with Actinobacterium sp. strain NCO2 (OQ451136) and were grown under two levels of air CO2 concentrations (ambient CO2 (aCO2 , 410 μmol CO2 mol-1 ; and elevated CO2 (eCO2 , 710 μmol CO2 mol-1 )). Increasing the photosynthetic pigments (+35%-80%) and photosynthesis rate (+20%-34%) in PGPB-treated plants under eCO2 compared to control plants, resulting in further growth and biomass production (+53%-294%). These results were associated with an enhancement in the content of total antioxidant capacity (+15%-128%), polyphenols (+21%-126%), and alpha-tocopherols (+20%-138%) under both elevated CO2 and PGPB application (in combination or individual application), while only the combined treatment (eCO2 + PGPB) had a significantly higher accumulation of antioxidant enzymes (+88%-197%), beta-tocopherols (+177%), and flavonoids (+155%). Moreover, nitrogen and sulfur-containing metabolites (glucosinolates and amino acids) were improved by PGPB treatment and/or CO2 levels, in which PGPB increased the amino acid-derived glucosinolates induction by eCO2 with low levels of effective sulforaphane. Therefore, the interaction effects of beneficial actinobacteria and elevated CO2 are expected to boost the level of such antioxidant molecules and to have a helpful designation in improving plant biomass and adaptability to complicated climate changes in the future. This article is protected by copyright. All rights reserved.

Reconciling Airborne Disease Transmission Concerns with Energy Saving Requirements: The Potential of UV-C Pathogen Deactivation and Air Distribution Optimization

The COVID-19 pandemic caused a paradigm shift in our way of using heating, ventilation, and air-conditioning (HVAC) systems in buildings. In the early stages of the pandemic, it was indeed advised to reduce the reuse and thus the recirculation of indoor air to minimize the risk of contamination through inhalation of virus-laden aerosol particles emitted by humans when coughing, sneezing, speaking, or breathing. However, such recommendations are not compatible with energy saving requirements stemming from climate change and energy price increase concerns, especially in winter and summer when the fraction of outdoor air supplied to the building needs to be significantly heated or cooled down. In this experimental study, we aim at providing low-cost and low-energy solutions to modify the ventilation strategies currently used in many buildings to reduce the risk of respiratory disease transmission. Measurements of the indoor air bacterial concentration in a typical office building reveal that ultraviolet germicidal irradiation (UVGI) modules added to the HVAC system are very efficient at inactivating pathogens present in aerosols, leading to indoor concentrations as low as outdoor concentrations, even with significant indoor air recirculation. Moreover, measurements of the CO2 and aerosol air concentration reveal that, with air supply vents placed in the ceiling, placing the air exhaust vents near the floor instead of on the ceiling can improve the ventilation capacity in terms of effective flow rate, with significant consequences in terms of energy savings.

Estimating canopy stomatal conductance and photosynthesis in apple trees by upscaling parameters from the leaf scale to the canopy scale in Jinzhong Basin on Loess Plateau

The estimations of stomatal conductance and photosynthesis performed by upscaling the parameters from the leaf scale to the canopy scale are key points in the fields of forest ecohydrology and physiology. The foundation for solving this scientific problem is determining the optimal models for calculating the leaf stomatal conductance (gl) and photosynthetic rate (Pl). In this study, we used the Jarvis model combined with modification factors, including leaf–air temperature (ΔT) and CO2 concentration inside and outside the stomata (ΔC), to estimate gl and the new Ye light–response model to estimate the Pl of apple trees in Jinzhong Basin on Loess Plateau. The results show that the modified Jarvis (JarvisΔT-ΔC) model and the new Ye light–response model could estimate gl and Pl, respectively, with very high accuracy, with R2 values of 0.926 and 0.959 for the former, and 0.987 and 0.983 for the latter in 2019 and 2021, respectively. Then, we estimated the canopy stomatal conductance (gc) and photosynthetic rate (Pc) by first dividing the apple tree canopy into sunlit and shaded leaves and then summing the contribution of sunlit and shaded gl, Pl and leaf area index. Our efforts will be a valid reference for estimating the gc and Pc of other tree or crop species in the future.

Life cycle assessment of microgreen production: effects of indoor vertical farm management on yield and environmental performance

The global production of plant-based foods is a significant contributor to greenhouse gas emissions. Indoor vertical farms (IVFs) have emerged as a promising approach to urban agriculture. However, their environmental performance is not well understood, particularly in relation to operational choices where global warming potentials (GWP) can vary between 0.01–54 kg CO2e/kg−1 of leafy greens produced. We conducted a life cycle assessment (LCA) of a building-integrated IVF for microgreen production to analyse a range of operational conditions for cultivation: air temperature, CO2 concentration, and photoperiod. We analyzed a dynamic LCA inventory that combined a process-based plant growth model and a mass balance model for air and heat exchange between the chamber and the outside. Results showed that the GWP of IVFs can vary greatly depending on the operation conditions set, ranging from 3.3 to 63.3 kg CO2e/kg−1. The optimal conditions for minimizing GWP were identified as 20 ℃, maximum CO2 concentration in the chamber, and maximum photoperiod, which led to a minimum GWP of 3.3 kg CO2e/kg−1 and maximum production of 290.5 kg fresh weight week-1. Intensification of production thus led to lower impacts because the marginal increase in yield due to increased resource use was larger than the marginal increase in impact. Therefore, adjusting growing conditions is essential for the sustainability of urban food production.

Assessment of the impacts of balconies on indoor environmental quality in mild climate conditions, Portugal

ABSTRACT The configuration of balconies can affect the indoor environmental performance of dwellings, but there is not enough knowledge regarding how a balcony simultaneously impacts all the parameters of indoor environmental quality (IEQ). Therefore, this study aims to evaluate, for the first time, the impacts of different balcony configurations on IEQ. A comprehensive in-situ campaign was carried out on ten balconies and their contiguous rooms in a building in Porto. Air temperature, relative humidity, CO2, PM2.5 and TVOCs concentration, illuminance and sound pressure level were simultaneously monitored. The results show that an open balcony has a positive impact on hygrothermal conditions, controlled daylight illuminance, and reduced traffic noise by up to 10 dBa. The presence of a glazed balcony improved hygrothermal conditions in winter and increased the noise reduction by up to 15 dBA, but caused a reduction in the daylight of up to 64%. The rooms, in which the balcony was eliminated presented the worst hygrothermal conditions, lost the benefits of noise reduction and had an increase in daylight illuminance of up to 136%. It was also found that the impacts are interrelated and that a balcony influences the occupants’ behaviour by enhancing window opening.

Exploring environmental and physiological drivers of the annual carbon budget of biocrusts from various climatic zones with a mechanistic data-driven model

Abstract. Biocrusts are a worldwide phenomenon, contributing substantially to ecosystem functioning. Their growth and survival depend on multiple environmental factors, including climatic ones, and the relations of these factors to physiological processes. Responses of biocrusts to individual environmental factors have been examined in a large number of field and laboratory experiments. These observational data, however, have rarely been assembled into a comprehensive, consistent framework that allows quantitative exploration of the roles of multiple environmental factors and physiological properties for the performance of biocrusts, in particular across climatic regions. Here we used a data-driven mechanistic modelling framework to simulate the carbon balance of biocrusts, a key measure of their growth and survival. We thereby assessed the relative importance of physiological and environmental factors for the carbon balance at six study sites that differ in climatic conditions. Moreover, we examined the role of seasonal acclimation of physiological properties using our framework, since the effects of this process on the carbon balance of biocrusts are poorly constrained so far. We found substantial effects of air temperature, CO2 concentration, and physiological parameters that are related to respiration on biocrust carbon balance, which differ, however, in their patterns across regions. The ambient CO2 concentration is the most important factor for biocrusts from drylands, while air temperature has the strongest impact at alpine and temperate sites. Metabolic respiration cost plays a more important role than optimum temperature for gross photosynthesis at the alpine site; this is not the case, however, in drylands and temperate regions. Moreover, we estimated a small annual carbon gain of 1.5 gm-2yr-1 by lichen-dominated biocrust and 1.9 gm-2yr-1 by moss-dominated biocrust at a dryland site, while the biocrusts lost a large amount of carbon at some of the temperate sites (e.g. −92.1 for lichen-dominated and −74.7 gm-2yr-1 for moss-dominated biocrust). These strongly negative values contradict the observed survival of the organisms at the sites and may be caused by the uncertainty in environmental conditions and physiological parameters, which we assessed in a sensitivity analysis. Another potential explanation for this result may be the lack of acclimation in the modelling approach, since the carbon balance can increase substantially when testing for seasonally varying parameters in the sensitivity analysis. We conclude that the uncertainties in air temperature, CO2 concentration, respiration-related physiological parameters, and the absence of seasonal acclimation in the model for humid temperate and alpine regions may be a relevant source of error and should be taken into account in future approaches that aim at estimating the long-term biocrust carbon balance based on ecophysiological data.

Adaptive model predictive control with ensembled multi-time scale deep-learning models for smart control of natural ventilation

Model predictive control (MPC) offers promising solutionsfor the smart control of natural ventilation. However, challenges arise in constructing precise models for such nonlinear systems, preserving accuracy over a long-prediction horizon while capturing short-term dynamics, and handling disturbances uncertainties. This study proposes a novel Ensembled Multi-time scale deep-learning-based Adaptive Model Predictive Control (EMA-MPC) system. It integrates an ensembled Long-Short-Term Memory (ensembled-LSTM) model, comprising two LSTM models for fast and slow time-scale dynamics, respectively, and continuously evolving to changing conditions through online model adaptation. A bound control module is incorporated as an additional safety mechanism ensuring the environmental control within the desired threshold during unforeseen scenarios. A multi-objective optimization problem is formulated to maintain indoor air temperature and CO2 concentration within the predefined comfort range while optimizing energy efficiency by controlling automated windows in a naturally ventilated room in winter. The EMA-MPC system demonstrates superior performance in balancing indoor air quality, temperature regulation, and energy efficiency. The ensembled-LSTM model significantly reduces the mean absolute error by 78.6% and 88.9% for CO2 and indoor air temperature predictions respectively, against a single LSTM model. The proposed EMA-MPC system achieves an 86% reduction in unmet CO2 hours compared to rule-based control and reduces occupied hours with temperature below 19 °C by 44% and 93% compared to enhanced MPC and basic MPC, respectively, while maintaining similar heating demand as other controllers. In conclusion, the proposed EMA-MPC system reduces modeling efforts and provides an effective approach towards reliable use of ML models in smart building control.

Parametric simulations of hierarchical core–shell MOF materials for direct air capture

Metal–organic frameworks (MOFs) can separate and adsorb specific gases from a gas mixture, making them an ideal candidate for direct air carbon capture. However, MOFs that adsorb CO2 well often competitively adsorb the more abundant H2O molecules in the atmosphere, degrading their adsorptive performance and operational longevity. MOF-contained-in-MOF (MOF⊂MOF) core–shell materials may resolve this issue if a shell can be synthesized to reject water while the core receives CO2. This paper builds on our team’s prior computational screening and experimental synthesis of individual and core–shell MOFs by performing multiphysics simulations on a spherical MOF⊂MOF core–shell pellet exposed to atmospheric air. This core–shell pellet is endowed with our previously calculated and experimentally measured constituent MOF properties to demonstrate a high throughput methodology for scale-up analysis on composite adsorbent structures. We simulate and screen five UiO-67(Zr) MOF variants for use as either the core or shell materials that lead to 25 MOF⊂MOF core–shell pellet combinations, five of which are pellets whose core and shell are the same MOF. The resulting rankings suggest that adding a shell MOF to a pellet does not necessarily improve the adsorptive performance of that pellet when using these UiO-67(Zr) variants. The highest-ranked core–shell pellet combination was a pellet whose core and shell were the same MOF material. However, when considering only the core domain of the pellet as a frame of reference, the ranking results suggest that using hydrophobic MOFs as the pellet core and hydrophilic MOFs as the pellet shell show improvement compared to without the shell MOF. Using this second frame of reference, we identify the MOF⊂MOF core–shell combination UiO-67(Zr)⊂2(NH2)-UiO-67(Zr) as the highest-performing pellet of those that show improvement over their homogeneous pellet counterparts. A set of parametric simulations are performed comparing the core–shell pellet UiO-67(Zr)⊂UiO-67(Zr) against that of UiO-67(Zr)⊂2(NH2)-UiO-67(Zr) to investigate the impact of air CO2 concentration, relative humidity, and shell thickness on each respective core MOF’s performance. From these studies, the largest improvement in the core MOF’s performance was observed when using elevated CO2 concentrations of 1000 ppm, reduced relative humidity levels of 10%, and an increased shell thickness of 0.03 cm on a pellet core 0.12 cm in radius. Together, these results suggest that additional UiO-67(Zr) MOF variants will need to be screened to determine the use cases where the use of a shell is of water-rejecting benefit to the pellet in the DAC setting. Further adsorption and porosimetry experimentation is necessary to replicate the proposed pellet under DAC conditions and establish a means of comparative analysis between the simulated and measured pellet properties.

A novel method for calculation of the CO2 concentration impact on correlation between thermal comfort and human body exergy consumption

The majority of studies dealing with the correlation between human body exergy consumption and thermal comfort use adopted, constant values of metabolic rate for appropriate activity level. Taking into account correlations between metabolic rate and the occupant’s exhaled CO2 volumetric flow rate, this study proposes a novel method for the calculation of metabolic rate using measured CO2 concentration in the indoor air. Using measured values of the air and radiant temperature, relative humidity and air velocity, and calculated values of metabolic rate, the human body exergy consumption rate and corresponding Predicted Mean Vote (PMV) are calculated. Moreover, a novel polynomial relation between them is proposed. Results show that metabolic rate values vary in the range of 0.97 to 1.54 met which leads to significantly wider range of PMV and human body exergy consumption rate comparing to the assumed value of 1.2 met for sedentary school activity. According to the obtained relation, the minimal value of the human body exergy consumption rate occurs for PMV = − 0.02. Results of this study imply that treating CO2 concentration as variable does have an impact on the thermal comfort assessment, providing enhanced correlations between thermal comfort and human body exergy consumption rate.

The clean energy aspect of plastic waste - hydrogen gas production, CO2 reforming, and plastic waste management coincide with catalytic pyrolysis - an extensive review.

Clean hydrogen has future fuel capable of receiving an abundance of carbon-neutral energy from hydrogen. In the recent world, new hydrogen affirmation projects have been launched for a green environment. On another side, plastic waste and CO2 threaten the green environment. Vacuum in plastic waste management, plastic waste leads to exhibiting harmful chemicals to the environment. The growth rate of the CO2 concentration in air is 2.45ppm per year, steadily increasing in 2022. It is realized that uneven climate change, temperature raising the global level, ocean mean level raising, and frequent acidification are dangerous to living and ecosystems. This review discussed tackling multiple harmful environmental fatly by pyrolysis techniques; catalytic pyrolysis is almost reaching the commercialization stage. Recent pyrolysis upgradation methods with hydrogen gas production and the continuous development and execution of sustainable solutions for plastic waste management and CO2 reforming are discussed. Production of carbon nanotubes by plastic waste, the importance of catalyst modification, and the effect of catalyst deactivation are discussed. From this study, integrating the different applications with catalytic modification creates room for multipurpose pyrolysis, CO2 reforming, and hydrogen gas production by pyrolysis techniques capable of giving a sustainable solution for climate change issues and a clean environment. Additionally, carbon utilization by way of carbon nanotube production is also done. Overall, the review supports achieving clean energy from plastic waste.

Effects of elevated CO2 concentration on cell structure and stress resistance physiology of Setaria italica under drought stress.

The frequency of drought will increase under further warming. The increase in atmospheric CO2 concentration, along with more frequent drought, will affect crop growth. We examined the changes of cell structure, photosynthetic physiology, antioxidant enzymes, osmotic regulatory substances, and yield of foxtail millet (Setaria ita-lica) leaves under different CO2 concentrations (ambient air CO2 concentration and ambient atmospheric CO2 concentration + 200 μmol·mol-1) and water treatment (soil moisture content maintained at 45%-55%, and 70%-80% of field capacity, representing mild drought and normal water condition, respectively). The results showed that elevated CO2 concentration increased the number of starch grains, the area of single starch grains, and the total area of starch grains in the chloroplast of millet mesophyll cells. Under mild drought condition, elevated CO2 concentration increased net photosynthetic rate of millet leaves at the booting stage by 37.9%, but did not affect water use efficiency at this stage. Elevated CO2 concentration increased net photosynthetic rate and water use efficiency of millet leaves under mild drought condition at the filling stage by 15.0% and 44.2%, respectively. Under mild drought condition, elevated CO2 concentration increased the content of peroxidase (POD) and soluble sugar in millet leaves at the booting stage by 39.3% and 8.0%, respectively, but decreased proline content by 31.5%. It increased the content of POD in millet leaves at the filling stage by 26.5% but decreased the content of MDA and proline by 37.2% and 39.3%, respectively. Under mild drought condition, elevated CO2 concentration significantly increased the number of grain spikes by 44.7% and yield by 52.3% in both years compared with normal water condition. The effect of elevated CO2 concentration on grain yield under mild drought conditions was higher than that under normal water condition. Under mild drought conditions, elevated CO2 concentration increased leaf thickness, vascular bundle sheath cross-sectional area, net photosynthetic rate, and water use efficiency of millet, improved the antioxidant oxidase activity, and changed the concentration of osmotic regulatory substances, alleviated the nega-tive effect of drought on foxtail millet, and finally increased the number of grains per ear and yield of foxtail millet. This study would provide a theoretical basis for millet production and sustainable agricultural development in arid areas under future climate change.

Carbon dioxide generation rates for children and adolescents

The indoor CO2 concentration in elementary and middle school classrooms is primarily influenced by the CO2 generation rate of the occupants, the outdoor air ventilation rate, and the CO2 concentration in outdoor air. While there have been numerous studies on the CO2 generation rate of adults under different activities, there are limited studies on the CO2 generation rate of children and adolescents during typical activities. It is difficult to obtain data on CO2 generation rates for children and adolescents directly from relevant standards or literature through searching. This paper synthesized CO2 generation rates using indirect calorimetry data in the literature from more than 900 children and adolescents aged 5–18 years under light to vigorous 13 activities, and summarized them into a table so that researchers or designers can easily obtain them. The results show that, as expected, CO2 generation rates increase with activity levels, and age has a highly significant effect on CO2 generation rates in children and adolescents, while gender differences manifest only after age 15. Compared to adults, children aged 5–12 years have significantly lower CO2 generation rates. The findings supplement the missing data on the CO2 generation rate of children and adolescents in the ventilation standard, and also provide basic parameters for the use of CO2 as a tracer gas to quantify the ventilation rates of buildings and spaces in primary and secondary schools classrooms.