Carbon Monoxide Concentrations Research Articles

Modelling of Carbon Monoxide and Suspended Particulate Matter Concentrations in a Rural Area Using Artificial Neural Networks

Air pollution is a growing concern in rural areas where agricultural production can be reduced by it. This article analyses data obtained as part of a research project. The aim of this study is to understand the influence of atmospheric pressure, air temperature, air relative humidity, longitude and latitude of the location, and indoor and outdoor environment on local rural workplace diversity of air pollutants such as carbon monoxide (CO) and suspended particulate matter (SPM), as well as the contribution of these variables to changes in such air pollutants. The focus is on four topics: motivation, innovation and creativity, leadership, and social responsibility. Furthermore, this study developed an artificial neural network (ANN) model to predict CO and SPM concentrations in the air based on data collected from the mentioned inputs. The related sensors were assembled on an Arduino Mega 2560 board to form a field-portable device to detect air pollutants and meteorological parameters. The sensors included an MQ7 sensor for CO concentration measurement, a Sharp GP2Y1010AU0F dust sensor for SPM concentration measurement, a DHT11 sensor for air temperature and air relative humidity measurement, and a BMP180 sensor for air pressure measurements. The longitude and latitude of the location were measured using a smartphone. Measurements were conducted from 20 December 2021 to 16 July 2022. Results showed that the overall average outdoor CO and SPM concentrations were 10.97 ppm and 231.14 μg/m3 air, respectively. The overall average indoor concentrations were 12.21 ppm and 233.91 μg/m3 air for CO and SPM, respectively. Results showed that the ANN model demonstrated acceptable performance in predicting CO and SPM in both the training and testing phases, exhibiting a coefficient of determination (R2) of 0.575, a root mean square error (RMSE) of 1.490 ppm, and a mean absolute error (MAE) of 0.994 ppm for CO concentrations when applying the testing dataset. For SPM concentrations, the R2, RMSE, and MAE using the test dataset were 0.497, 30.301 μg/m3 air, and 23.889 μg/m3 air, respectively. The most influential input variable was air pressure, with contribution rates of 22.88% and 22.82% in predicting CO and SPM concentrations, respectively. The acceptable performance of the developed ANN model provides potential advances in air quality management and agricultural planning, enabling a more accurate and informed decision-making process regarding air pollution. The results of short-term estimation of CO and SPM concentrations suggest that the accuracy of the ANN model needs to be improved through more comprehensive data collection or advanced machine learning algorithms to improve the prediction results of these two air pollutants. Moreover, as even lower cost devices can predict CO and SPM concentrations, this study could lead to the development some kind of virtual sensor, as other air pollutants can be estimated from measurements of particulate matters.

ANALISIS KONTRIBUSI KEPADATAN KENDARAAN BERMOTOR TERHADAP KONSENTRASI KARBON MONOKSIDA (CO) DAN TINGKAT KEBISINGAN DI JALAN SLAMET RIYADI SURAKARTA

<div class="WordSection1"><p><em>In the current era, the transportation is growing rapidly. It has an impact such as air and noise pollution. Carbon monoxide is one of the dangerous pollutants. While the noise comes from the sound of the vehicle engine, horn, and exhaust. Slamet Riyadi street Surakarta is a protocol road that has a high level of vehicle density. So it is necessary to conduct research with the aim of knowing the effect of motor vehicle density on carbon monoxide concentrations and noise levels. The results showed that the concentration of Carbon monoxide on Slamet Riyadi street Surakarta in the morning and evening exceeded the quality standard of 16038.26 µg/Nm<sup>3</sup></em><em>and 16141.58 µg/Nm<sup>3</sup></em><em>. During the day it is still below the quality standard, which is 9425.86 µg/Nm<sup>3</sup></em><em>. Meanwhile, the daytime noise level on Slamet Riyadi street Surakarta which is calculated by the Leq formula also exceeds the quality standard of 82.33 dBA.</em></p></div>

Biogenic Amine Content and Shelf-Life of Salmon Fillets Packaged in Modified Atmospheres of Low-Level Carbon Monoxide and Different Carbon Dioxide Concentrations

Biogenic Amine Content and Shelf-Life of Salmon Fillets Packaged in Modified Atmospheres of Low-Level Carbon Monoxide and Different Carbon Dioxide Concentrations

Varying Performance of Low-Cost Sensors During Seasonal Smog Events in Moravian-Silesian Region

Air pollution monitoring in industrial regions like Moravia-Silesia faces challenges due to complex environmental conditions. Low-cost sensors offer a promising, cost-effective alternative for supplementing data from regulatory-grade air quality monitoring stations. This study evaluates the accuracy and reliability of a prototype node containing low-cost sensors for carbon monoxide (CO) and particulate matter (PM), specifically tailored for the local conditions of the Moravian-Silesian Region during winter and spring periods. An analysis of the reference data observed during the winter evaluation period showed a strong positive correlation between PM, CO, and NO2 concentrations, attributable to common pollution sources under low ambient temperature conditions and increased local heating activity. The Sensirion SPS30 sensor exhibited high linearity during the winter period but showed a systematic positive bias in PM10 readings during Polish smog episodes, likely due to fine particles from domestic heating. Conversely, during Saharan dust storm episodes, the sensor showed a negative bias, underestimating PM10 levels due to the prevalence of coarse particles. Calibration adjustments, based on the PM1/PM10 ratio derived from Alphasense OPC-N3 data, were initially explored to reduce these biases. For the first time, this study quantifies the influence of particle size distribution on the SPS30 sensor’s response during smog episodes of varying origin, under the given local and seasonal conditions. In addition to sensor evaluation, we analyzed the potential use of data from the Copernicus Atmospheric Monitoring Service (CAMS) as an alternative to increasing sensor complexity. Our findings suggest that, with appropriate calibration, selected low-cost sensors can provide reliable data for monitoring air pollution episodes in the Moravian-Silesian Region and may also be used for future adjustments of CAMS model predictions.

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model

Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and contributes to the formation of secondary atmospheric pollutants, such as ozone (O3). This study aims to elucidate global CO pollution in relation to health risks and the influence of natural events like wildfires. Utilizing artificial intelligence (AI) big data techniques, we developed a high-performance Convolutional Neural Network (CNN)-based Residual Network (ResNet) model to estimate daily global CO concentrations at a high spatial resolution of 0.07° from June 2018 to May 2021. Our model integrated the global TROPOMI Total Column of atmospheric CO (TCCO) product and reanalysis datasets, achieving desirable estimation accuracies with R-values (correlation coefficients) of 0.90 and 0.96 for daily and monthly predictions, respectively. The analysis reveals that the CO concentrations were relatively high in northern and central China, as well as northern India, particularly during winter months. Given the significant role of wildfires in increasing surface CO levels, we examined their impact in the Indochina Peninsula, the Amazon Rain Forest, and Central Africa. Our results show increases of 60.0%, 28.7%, and 40.8% in CO concentrations for these regions during wildfire seasons, respectively. Additionally, we estimated short-term mortality cases related to CO exposure in 17 countries for 2019, with China having the highest mortality cases of 23,400 (95% confidence interval: 0–99,500). Our findings highlight the critical need for ongoing monitoring of CO levels and their health implications. The daily surface CO concentration dataset is publicly available and can support future relevant sustainable studies, which is accessible at https://doi.org/10.5281/zenodo.11806178.

Emission control in a dual fuel low temperature combustion engine at intermediate loads

Intermediate to high load operation in dual fuel reactivity controlled compression ignition (RCCI) techniques is restricted due to uncontrolled combustion that causes engine knocking. Dual fuel strategies with advanced pilot injection and near-top dead center (TDC) main injection timings are reported to enhance combustion control, albeit with increased soot emissions, reduction of thermal efficiency, and emergence of an intricate trade-off between total hydrocarbon (THC) and oxides of nitrogen (NOx) emissions. In order to address these conflicting issues, an intermediate engine load, corresponding to 6 bar gross indicated mean effective pressure at 1500 and 2200 rev/min engine speeds was investigated in this work. The main objectives of this work are (1) to obtain combination of control parameters to achieve near-zero engine-out NOx and soot emissions and high thermal efficiency while minimizing THC and CO emissions; (2) to understand the effectiveness of diesel oxidation catalysts (DOCs) for the oxidation and reduction of exhaust gas species in the dual fuel mode; and (3) to understand the oxidation characteristics of the soot generated from the dual fuel mode. Optimum dual fuel low temperature combustion strategies, in terms of diesel injection timings, quantity and exhaust gas recirculation levels, were identified using the statistical multi response signal to noise (MRSN) ratio method in which NOx, soot and indicated efficiency were response variables. The performance of commercial DOCs, with different precious metal (Pt and/or Pd) loadings, were also studied at optimum dual fuel strategies for gasoline-diesel dual fuel operations. High DOC outlet temperatures (>∼340°C), due to the exotherm generated by the oxidation of high concentrations of THC and carbon monoxide (CO) emissions from dual fuel operations, resulted in greater than 90% THC conversion efficiency. The exotherm decreased the nitric oxide (NO) oxidation whereas the nitrogen dioxide (NO2) reduction reactions were favored over the DOC in the dual fuel mode at the intermediate load operating condition. Thermogravimetric analysis of the soot showed higher activation energy (177.2 kJ/mol), formed at the dual fuel optimum condition, relative to the activation energy (162.7 kJ/mol) of the soot formed in conventional diesel combustion (CDC).

Ultratrace CO/SF6 Detection System Based on Differential Fourier Transform Infrared Spectroscopy Combined with the Weighted Sine Spectral Reconstruction Convolutional Neural Network (WSSR-CNN) Model.

Carbon monoxide (CO), as an indicator gas for fault diagnosis of gas-insulated switchgear, has the strongest absorption coefficient in the mid-infrared region, making Fourier transform infrared (FTIR) spectroscopy an ideal method for its concentration detection. However, there is extremely abundant absorption of SF6 in this region, resulting in a great challenge for CO/SF6 detection. To address this challenge, we report a high sensitivity online detection system for ultratrace levels of CO, which combines differential Fourier transform infrared (DFTIR) spectroscopy with a weighted sine spectral reconstruction convolutional neural network (WSSR-CNN). The differential technique is first introduced into FTIR for baseline correction of CO absorption signals. The novel WSSR method achieves feature extraction and denoising of weak spectral signals in strong interference by discretizing interfering signals and enhancing target signals. On this basis, the detection of CO concentration is realized using the CNN model. Finally, WSSR-CNN is compared with four other methods. Results showed that WSSR-CNN outperforms all four models with evaluation index R2 reaching 0.99982 and 0.99999 in the range of low concentration (0.096-0.986 ppm) and high concentration (1.984-52.193 ppm) and mean absolute percentage error of 0.97% and 0.22%, respectively. The lowest detection limit of the system at 1σ is 13 ppb, which is the best result reported so far for detecting CO/SF6 concentration based on FTIR.

Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble results

The international field campaign, GMAP/SIJAQ 2021, was conducted in Korea from October 18th to November 25th to enhance the performance and validation of the Geostationary Environment Monitoring Spectrometer (GEMS) products algorithm and obtain a better understanding of the current air pollution status of the Korean Peninsula. Five chemical transport models (CTMs), including CMAQ, CMAQ-GIST, CAMx, WRF-Chem, and WRF GEOS-Chem, were utilized during the campaign to assist in organizing the observation plan and identifying changes in pollutant concentrations and their spatiotemporal distribution in Korea following the Korea–United States Air Quality (KORUS-AQ) 2016. In this study, we evaluated the forecasting performance, strengths, and limitations of these five CTMs and their ensemble in simulating air quality. Intensive measurement data and intercomparisons were employed to explain discrepancies between observed and simulated results. A comparison of the CTM ensemble results for PM2.5 and various gaseous pollutants between the current GMAP/SIJAQ 2021 and previous KORUS-AQ 2016 campaigns showed the R-value for the total mass PM2.5 concentration increased from 0.88 to 0.94. This improvement is related to CTM updates, including the emission inventory and better reproductions of the concentrations of gaseous species. However, the models consistently underestimated carbon monoxide (CO) concentrations, similar to the results from KORUS-AQ. This finding still suggests a further challenge that requires consideration of missing anthropogenic sources. The results of the ensemble model agreed well with the chemical composition of PM2.5 observed at the intensive monitoring station. However, for NO3− and NH4+, discrepancies were primarily due to inaccuracies in the meteorological inputs, such as precipitation, relative humidity (RH), and nighttime planetary boundary layer height (PBLH) in the CTMs. Hence, all models overestimated the concentration of elemental carbon (EC), therefore, it is necessary to revise EC emissions in the SIJAQv2 inventory, as these apply to unusual levels recorded in Seoul during the reference year of 2018.

A Comparative Study of Hydrothermally Leached Al3TM and Al3TM-Rh (TM=Zr, V, Ce) Intermetallic Compounds for Catalytic Oxidation of Carbon Monoxide.

Rise of the mute assassin "carbon monoxide (CO)" levels impact all aerobic life. The elevated rates of CO concentration endure climatic and geographical characteristics that exacerbate air pollution. Herein, a simple approach for hydrothermal leaching (HyTL) of Al3TM-Rh0.5 (Target material (TM)=Zr, V, Ce) and Al3TM (TM=Zr, V, Ce) intermetallic compounds produces leached products of ZrO2, VO2, and CeO2 with Rhodium (Rh) as an active component. The characterization result reveals the HyTL process and the presence of the active Rh element that elevated the performance of HyTL-Al3Zr-Rh0.5 towards CO conversion compared to other samples. Further, the cubic ZrO2 phase selectively forms after HyTL at 130 °C even though the formation of the cubic ZrO2 phase takes place at a high temperature. Moreover, the presence of Rh promotes higher catalytic activity in all the cases with low temperatures. The advancement in the present study towards the catalytic oxidation of CO over the hydrothermally leached ZrO2-Rh nanocatalyst guarantees the perspective of the aggregation-activation process.

Differential effects of heat-not-burn, electronic cigarettes and conventional cigarettes on endothelial glycocalyx

Abstract Background Heat-not-burn cigarette (HNBC) and electronic cigarette (Ecig) constitute non-combustible smoke products. Their effect on endothelial glycocalyx has not been investigated so far. Patients and Methods: Out of 100 subjects attending smoking cessation clinic: α) 50 smokers were randomized to usage of HNBC (n=25) or Ecig (n=25) and β) 50 smokers were used as control group. Participants randomized to the newer tobacco products had similar clinical and demographic characteristics to the control group. Smoking status was verified by measuring the concentration of exhaled carbon monoxide [(e CO) (ppm), Bedfont Scientific, Maidstone, Kent UK]. Perfused Boundary Region (PBR), which is inversely related to endothelial glycocalyx thickness in sublingual arterioles (range 5–25 μm) and blood levels of cotinine, a stable metabolite of nicotine, was assessed in all participants. Exhaled CO, endothelial glycocalyx, and blood cotinine were assessed at baseline and after 1 month. Results Conventional cigarette smokers were aged: 48 ± 5 years, 53% female and used 27 ± 9 cigarettes/day, 29 ± 9 pack-years. HNBC users were aged: 46 ± 14 years, 55% female and used 26 ± 8 cigarettes/day, 30 ± 8 pack-years. Ecig users were aged: 45 ± 8 years, 51% female and used 27 ± 10 cigarettes/day, 28 ± 10 pack-years. Compared to baseline, switching to HNBC for 1 month improved only PBR20-25 (2.55±0.49 vs 2.34±0.34 μm, p=0.002). Ecig use did not alter endothelial glycocalyx in any range of microvessels throughout the study (p>0.05). In contrast, Tcig smoking for one month further worsened endothelial glycocalyx in all microvessels ranges compared to baseline (p<0.05). Blood cotinine levels were similar at baseline and after 1 month using HNBC (p=0.432), Ecig (p=0.535) or conventional cigarette (p=0.489). Compared to baseline, exhaled CO decreased in HNBC or Ecig users (mean percent change: -55% and -58% respectively p<0.001), while remained unchanged in Tcig smokers (p=0.312) at 1 month. Thus, Tcig smokers had higher CO than those who switched to HNBC or E-cig after one month (p<0.01). Conclusion Conventional cigarette users further worsened endothelial glycocalyx after continuing to smoke for one month. In contrast, smokers who switched to Ecig maintained glycocalyx integrity, while those who switched to HNBC showed modest improvement in glycocalyx integrity in microvessels ranging from 20 to 25 μm. Cotinine levels, which reflect nicotine exposure, were similar between the Tcig, HNBC and Ecig groups. Thus, endothelial glycocalyx impairment in the conventional cigarette group was independent of nicotine consumption and possibly related to greater exposure to toxic emissions, such as CO, after Tcig use than after switching to HNBC or Ecig.

Air quality in different urban hotspots in a metropolitan city in India and the environmental implication.

This research study investigates hourly data on concentrations of five major air pollutants such as particulate matter (PM10, PM2.5) and gaseous pollutants (SO2, NO2, CO) measured during 2022 at four hotspot sites (industrial site, traffic site, commercial site, harbour, and one residential site) in Chennai, India. The analysis encompasses temporal variations spanning annual, seasonal, and diurnal variations in the pollutants. Notably, PM10 and CO emerge as the predominant pollutants, with the highest concentrations at industrial and traffic sites (PM10: 67.64 ± 40.77µg/m3, CO: 1.41 ± 0.84mg/m3; traffic site: PM10: 58.67 ± 20.05µg/m3, CO: 0.99 ± 0.57mg/m3). Seasonal dynamics reveal prominent winter spikes in particulate matter (PM10, PM2.5) and carbon monoxide (CO) concentrations, while nitrogen dioxide (NO2) and sulphur dioxide (SO2) levels peak during the summer season, particularly in the harbour area. The proximity to roadways exerts a discernible influence on diurnal patterns, with traffic sites showcasing broader rush hour peaks compared to sharper spikes observed at other sites. Furthermore, distinct bimodal patterns are evident for PM10 and PM2.5 concentrations in residential and harbour areas. A common lognormal distribution pattern is identified across the studied sites, suggesting consistent air quality trends despite contrasting locations. The conditional probability function (CPF) is used in conjunction with local meteorological conditions for identifying key pollution sources in each location. The implementation of polar plots emphasizes industries as principal local sources of pollution, at industrial sites significantly contributing to PM10, SO2, and NO2 concentrations under specific wind conditions. The main objective of the present study is to facilitate a good understanding of pollutant dynamics, pollution sources, and their intricate interplay with meteorological factors, thereby contributing to the formulation and implementation of effective air pollution control and mitigation strategies.

Exposure to cooking fumes in cafeteria workers in Korean schools: a pilot study.

This study measured cooking fumes to which workers in school cafeterias may be exposed. The measurement items were respirable dust, formaldehyde, and carbon monoxide. A total of 111 samples were obtained from 55 schools. Data on variables such as school size and daily cooking oil usage were collected. Correlation and association analysis were performed. The median of concentrations of respirable dust was 38.37 µg/m3 (min-max: 20.73-49.71 µg/m3). The concentrations of formaldehyde and carbon monoxide also showed levels that did not exceed 20% for occupational exposure limits. The increase in school size was significantly correlated with the increase in daily cooking oil usage and had a significant correlation with respirable dust concentration (Spearman's correlation coefficient, 0.36; P <0.05). The linear regression test results adjusting for other variables were also similar. Cooking food by frying at high heat using cooking oil can increase the exposure of kitchen workers to respirable dust.

Peat smoke exposure as a risk factor for deterioration of postnatal development

Introduction. In connection with the growing number and scale of wildfires, the problem of the toxic effect of biomass combustion products is relevant both in Russia and abroad. Data on the consequences of wildfire smoke exposure at various stages of ontogenesis are extremely scarce. The presence in smoke substances that, in addition to general toxic effects, have reprotoxic, gonadotoxic, and genotoxic effects, determines the need to study its effect on the reproductive potential and health of offspring. The purpose of the study was to assess the postnatal development of the offspring, the parent generation of which was exposed to peat smoke during puberty. Materials and methods. Exposure to peat smoke was carried out once for four hours on the 35th day of life for female and on the 45th day for male rats. The average concentrations of carbon monoxide in the exposure chambers were 29.3±11.1 mg/m3, and ultrafine PM2.5 particles – 0.39±0.61 mg/m3. At puberty, peat smoke exposed rats were mated with intact partners. In rat pups from the offspring there was studied the trend in body weight gain, physical development, and sensory-motor reflexes were assessed. Results. Acute exposure to peat smoke during puberty in white rats adversely affects the development of their offspring. A significant lag in the physical and sensory-motor development of rat pups from the offspring of animals exposed to smoke was revealed in comparison with rat pups from the control group. Limitations. The study was limited to the study of postnatal development of offspring obtained from rats exposed to peat smoke during puberty. Conclusion. Exposure to peat smoke during puberty leads to a delay in the physical and somatosensory development of the offspring during early postnatal ontogenesis.

Integrating Flow Field Dynamics and Chemical Atmosphere Predictions for Enhanced Sulfur Corrosion Risk Assessment in Power Boilers.

In this work, we attempt to explain the phenomenon of sulfur corrosion of power boiler water walls under the conditions of large fluctuations in carbon monoxide concentrations. To assess the conditions required for corrosion formation, a criterion based on the chemical and flow field parameters of the flue gas is proposed. The formulated sulfur corrosion criterion is based on the mixture fraction variance and the turbulence time scale. Numerical modeling of coal combustion in a 250 MW power boiler is performed using ANSYS. Two cases of combustion in a boiler are analyzed, with the first simulating the boiler operated using classic high-swirl burners and the second one accounting for boiler operation with modified low-swirl burners. Calculations of pulverized coal combustion are performed using the standard k-ε turbulence model and the combustion described by the mixture fraction. The simulation results reveal that the low-swirl burner is characterized by higher values of the mixture fraction variance and a higher frequency of fluctuation of the velocity field, which is strongly related to an increased corrosion rate. The study outcomes show the validity of using the criterion of the mixture fraction variance and velocity field fluctuations to determine the areas at risk of sulfur corrosion.

Statistical modeling of the effects of wind speed, air temperature and relative humidity on the concentration of carbon monoxide in the urban atmosphere

The high carbon monoxide content in the urban atmosphere is one of the most important indicators of poor air quality in megacities such as Moscow. This study is to evaluate the importance of wind speed, air temperature, and relative air humidity for predicting the concentrations of carbon monoxide for the day ahead using a simplified one-dimensional quasistationary statistical model. It is shown that the concentration of carbon monoxide in the Moscow atmosphere is determined by a combination of internal (previous days CO concentration) and external (meteorological conditions) factors. The variation of carbon monoxide concentration at one station differs from the variation at another station due to the differences in local conditions. Taking into account wind speed and air temperature increases the predictive value of the onedimensional quasi-stationary statistical model for most of the stations. In contrast to wind, relative air humidity decreases the predictive value of the model for most of the stations. This means that meteorological factors considered in this study could have different effects on predicting carbon monoxide concentration in the case of Moscow. The data from the Balchug weather station, located in the city center, offers a more accurate CO concentration forecast for most Moscow stations compared to the VDNKh weather station. For a more complete description of the influence of meteorological conditions on the predicted low concentration of gases, it is useful to take into account the model wind direction, surface air pressure, and the intensity of mixing in the urban boundary layer.

Method for Detecting Fire Indoors Based on Differences in Sample Averages of an Arbitrary Gas Environment Dangerous Parameter at Adjacent Observation Intervals

The object of the research is the series average of the dangerous parameters of the gas environment during the ignition of materials. The practical importance consists of using the difference between the average dangerous parameters of the gas environment on the intervals of absence and the presence of ignition to detect the ignition of materials. The theoretical substantiation of the method of detecting fires in premises is carried out based on sample averages fixed samples of current measurements of an arbitrary, dangerous parameter of the gas environment, which correspond to the general population of reliable absence and presence of fire. At a given significance level, the method determines the unbiased, uniformly most powerful fire detection rule. This allows you to determine how significant differences in sample means with a given significance level are due to ignition or are random. Laboratory experiments were conducted to verify the method of detecting the ignition of test materials. It was established, for example, that the maximum size of the effect ignition on the carbon monoxide concentration is typical for alcohol (exceeds the threshold by 8.9 times) and textiles (exceeds the threshold by 9.3 times). The size of the effect of the smoke density upon ignition of all materials is approximately the same and is determined by exceeding the corresponding thresholds from 4.62 to 3.9 times. The size of the effect on the temperature of the gaseous environment during ignition of all test materials is approximately the same order. It is characterized by exceeding the corresponding thresholds from 5.95 to 3.58 times. It is shown that the method of detecting fires allows to establish the extent to which the detected differences in sample means for samples from the general population of hazardous parameters of the gas environment are reliable with a given level of significance and are due to the ignition of materials or the action of random factors.

Effectiveness of natural ventilation in controlling the smoke spread within a refuge floor of a high-rise building

Refuge floors in high-rise buildings ensure a haven for occupants to stay in an emergencyprimarily during a fire breakout. Provisions for natural ventilation of the refuge floor are mandatory in all fire codes as they help release smoke and heat build-up. However, the effectiveness of such provisions has been questioned in many studies. This research employs large eddy simulations based three-dimensional computational fluid dynamics modelling on a real-world high-rise building to investigate the efficacy of natural ventilation in a refuge floor during a fire. Consequently, the performance was assessed by evaluating the temporal and spatial distributions of temperature, visibility, smoke and carbon monoxide concentration. Emphasis was placed on determining the adequacy of window placement and openings. Analysis was started with a code-compliant window configuration. Subsequently the window size and the layout were iteratively modified using simulation results. Seasonal wind variations were also considered. Results showed that a well-engineered natural ventilation strategy can considerably improve the refuge floor habitability. Simulations also revealed limitations of natural ventilation under certain wind conditions, necessitating a backup mechanical system. This also underlined that combining fire analysis with cutting-edge modelling allows tailored natural ventilation for refuge floors, maximising safe occupancy during fires.

Daily gaseous air pollution and pediatric conjunctivitis: A case-crossover study across ten cities in China's southeastern coastal region

The evidence on associations between ambient gaseous pollutants and conjunctivitis remains inconclusive, and limited research is available, particularly regarding children. Based on a case-crossover study conducted in ten Chinese cities from 2013 to 2023, we documented 418,027 outpatient visits for conjunctivitis in children. Of these visits, 256,525 were for boys and 161,502 for girls. A one standard deviation (SD) increase in daily concentrations of carbon monoxide (CO) was related to a 1.20 % rise in same-day outpatient visits for pediatric conjunctivitis (OR = 1.012, 95 % CI: 1.005, 1.018). Similar associations were found for nitrogen dioxide (NO2: 2.90 % increase; OR = 1.029, 95 % CI: 1.019, 1.040), sulfur dioxide (SO2: 1.70 % increase; OR = 1.017, 95 % CI: 1.007, 1.028), and ozone (O3: 1.30 % increase; OR = 1.013, 95 % CI: 1.006, 1.021). The positive associations remained significant in two-pollutant and mixed-effects models. Notably, we observed stronger associations in girls compared to boys, among children at 1–5 years of age compared to other age groups, and the relationships were more pronounced during the summer months. This study reveals a link between exposure to common gaseous air pollutants and increased risks of conjunctivitis in children, indicating the potential benefits of public health interventions.

Evaluating the Impact of Renewable Energy Integration on Air Quality: A Study of Pollutant Reduction in an Urban city of Calabar

The characterization of air quality parameters was carried out in the coastal city of Calabar with the aim of reducing air pollutants in the atmosphere. Both mobile and stationary measurements were obtained. Mobile data were used for estimating air quality index and creating air quality map. The results show that the average concentration of ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2) and nitrogen Oxides (NOx) was 0.34, 4.52, 0.53 and 0.96 ppm, respectively. The air quality index determined for each station showed that 82% of the stations were classified as “marginally polluted,” 14% were classified as “good,” and the remaining 4% were classified as “unhealthy” according to the U.S. air quality standards. Correlation analysis showed that wind speed had the highest correlation with SO2, R = -0.72, while temperature had a high correlation with ozone, R = -0.68. The 2016 polar plots show that CO sources are located in the south and southeast, NOx sources are located in the south and southwest, SO2 sources are located in the southwest, and O3 sources are located in the southeast. The 2017 polar plots show that CO sources are located in the northeast, NOx sources are located in the northwest, SO2 sources are located in the northeast, and O3 sources are located in the southwest.

In-tunnel pollutant concentration measurement and ventilation control indexes for highway tunnels in mountainous area: A case study of no.1 Qinling tunnel, China

The pollutant concentration and hygiene standards in mountain tunnels are key factors determining the ventilation effectiveness of tunnel operation. Previous studies have mainly focused on the spatiotemporal distribution patterns of in-tunnel pollutants, while research on ventilation control indexes for pollutants in long mountain tunnels are relatively limited. Therefore, this paper aims to discussing the hygiene control indexes for operational ventilation of mountain tunnels. Field tests were conducted in the No.1 Qinling Tunnel of Xi'an to Han zhong Highway in China, and the distribution laws of traffic flow, wind speed, and concentrations of particulate matter (PM), carbon monoxide (CO), and nitrogen oxide (NOX) were on-site measured. The spatiotemporal distribution characteristics of pollutants in the long mountain tunnel were revealed, and the ventilation hygiene control indexes for harmful gases were calculated and compared to those of urban highway tunnels. The results show that the traffic volume of operational highway tunnels in mountainous areas of China is increasing rapidly, and the particulate matter emitted from diesel vehicle exhaust will pose a threat to the normal environmental quality in the tunnel. The average value of CO base emission factor in 2000 for the upline of No.1 Qinling tunnel was 0.0019 m3/(veh·km) by back-calculation, and the annual decline rate of CO in the ventilation design for mountain highway tunnels should be 6 %–8 % and revised every 8 years. It is recommended to consider the geographical location and traffic conditions of mountain tunnels when calculating the air demand required for diluting NO2. NOx has basically replaced CO as the primary pollutant with the most significant impact on human health in mountain tunnels. It is recommended that NOX be considered as the primary hygiene control indicator in the ventilation design of mountain tunnels in China. The pollutant distribution and ventilation control indexes of mountain and urban highway tunnels are quite different, which should be treated differently in engineering applications. The research results can provide a significant reference for ventilation design and environmental evaluation of highway tunnels in mountainous areas.