Average Carbon Monoxide Concentrations Research Articles

Assessing school children's personal exposure to PM2.5 in Suva, Fiji

Globally, there is little information on children's personal exposure to particle pollution in developing countries, and hardly any in the Pacific Island Countries. This study was conducted with school children in Suva, Fiji, with the aim of assisting to fill this gap in knowledge. The participants included eighty-four children ranging from 10 to 15 years of age from five schools and two communities, defined as Group A and Group B, respectively. Each child was fitted with a KOALA air quality monitor which measured PM2.5 and carbon monoxide (CO) concentrations in real time over 24 h. Time activity diaries (TAD) and questionnaires were used by the students to record the start and end times of each activity in the different microenvironments occupied. For both groups, the PM2.5 concentration averaged over all children showed three distinct peaks in the morning, midday and in the evening. Several CO peaks were formed at different times of the day. The 24-h average CO concentrations for Group A and Group B students were 0.35 mg/m3 and 0.43 mg/m3, respectively. Time spent in the bedroom showed the highest average exposure (94.3 μg/m3, 301.1 μg/m3) and exposure intensity (5.8, 14.3), with the indoor exposure at home being significantly higher than the outdoor exposure for both groups. Based on the information obtained from the time activity diaries, questionnaires and follow-up interviews, the sources of these particles were most probably from cooking, smoking, burning of mosquito repellent coils, resuspension of dust in the classroom.Although this study could not apportion the specific contributions of emissions from cooking, cigarette smoke and mosquito coils, it may be concluded that these are significant sources for children's exposure and should be controlled.

Study on the Relationship between Hotspots and Air Pollution Standard Index Based on Carbon Monoxide Concentration in West Kalimantan

Hotspots, indicating active fires and potential sources of air pollution, are a major concern due to their impact on air quality in West Kalimantan. In this study, an analysis was carried out regarding the relationship of hotspots to the Air Pollution Standard Index (ISPU) based on the carbon monoxide (CO) parameter. This study aimed to determine the relationship between forest fires and air pollution levels. The data used in this study is in the form of monthly average CO concentration data and coordinates of hotspots in 2017-2021. To determine the effect of CO concentration, CO concentration was converted into ISPU and then mapped using the Inverse Distance Weighting (IDW) interpolation method. In addition, the overlay technique is also applied to the map and the correlation coefficient calculation between ISPU data and hotspot data. The study results show that the annual average number of hotspots ranges from 769 to 3,612, while the average ISPU ranges from 22.21 to 59.03. The highest average number of hotspots occurred in 2019, with 3,612 hotspots and the highest average ISPU value of 59.03, categorized as moderate. However, when examined monthly, the highest average number of hotspots is observed in August and September, with 8,505 and 8,321 hotspots, respectively, and average ISPU values of 55.36 and 88.32, categorized as moderate. Furthermore, the correlation coefficient between the average number of hotspots and the average ISPU per month is 0.91, and per year is 0.98, indicating a very high relationship. Spatially, clustered hotspot locations correspond to higher ISPU values. This implies that as the number of hotspots increases, the ISPU value based on CO concentration increases.

Experimental study on the purification capacity of potted plants on low-concentration carbon monoxide in indoor environment.

Indoor low-concentration carbon monoxide (CO) exposure is widespread worldwide, and potted plants may be a potential means for CO purification. The objective is to evaluate common indoor plants' CO purification and tolerance capacities. Epipremnum aureum (Linden ex André) G.S.Bunting, Chlorophytum comosum (Thunb.) Jacques, Spathiphyllum kochii Engl. & K.Krause, and Sansevieria trifasciata Hort. ex Prain with similar sizes were tested in the glass chamber with initial CO concentrations of 10, 25, 50, 100, 200, and 400 ppm, respectively. (1) The CO purification capacity of the four potted plants is ranked as Epipremnum aureum (Linden ex André) G.S.Bunting > Chlorophytum comosum (Thunb.) Jacques > Spathiphyllum kochii Engl. & K.Krause > Sansevieria trifasciata Hort. ex Prain. Under the purification effect of each plant, the CO concentration in the chamber decreases linearly and significantly (p < 0.05), and within a specific time period, the time-weighted average (TWA) CO concentrations can be reduced to below the corresponding permissible exposure limits specified by some countries and organizations. (2) With the increase of the stomatal number of each plant and the increase in CO concentration, the hourly and cumulative absorbed CO of each plant increase linearly and significantly (p < 0.05). (3) With the increase in CO concentration, the CO purification efficiency of each plant decreases exponentially and significantly (p < 0.05). (4) When the CO concentration was ≤ 50 ppm, all plants could effectively purify CO without damage. When the CO concentration was in the range of 100 ~ 400 ppm, within 2 weeks after the 48-h experiment, the leaf tips of Chlorophytum comosum (Thunb.) Jacques and Epipremnum aureum (Linden ex André) G.S.Bunting were damaged one after another, and the damaged leaf area increased with the increase of CO concentration. However, each plant as a whole still survived. This study demonstrated that different species of potted plants can effectively absorb low concentrations of CO to varying degrees, but higher concentrations of CO will damage the survival of specific species of potted plants.

Status of atmospheric air pollution in Ukraine prior to the full-scale russian invasion. Part 1: ground-level content of pollutants

The paper is dedicated to examination of atmospheric air pollution in Ukraine that is aimed at establishing basic air quality conditions prior to the full-scale Russian invasion. Analyses cover five air pollutants (dust, sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and formaldehyde (CH2O)) across 126 monitoring stations in 39 cities. It was found that the most dangerous excess of air pollution levels in cities was associated with dust, NO2, and CO. At the same time, SO2 content usually did not reach dangerous levels. The highest frequency of exceeding the threshold one-time levels was common for the cities with well-developed industrial facilities. Dangerous air pollution was observed in 15–60% of cases, depending on a pollutant. Dust and NO2 concentrations of the most polluted cities were 10 times higher than their concentrations in smaller cities having no significant industrial emissions. The difference in average CO, SO2, and CH2O concentrations among monitoring stations constituted 3-5 times. We studied the patterns of pollutants' seasonal variability recorded at the monitoring stations. Normally, no significant seasonality except for CH2O and dust was observed. The interannual variability of pollutants, emissions, and their trends were analyzed for the period since 2008. We identified a certain discrepancy in trends between pollutants’ concentrations and emission data over the last years. Pollutant content often continued to grow concurrently with emission reductions. The impact of atmospheric phenomena and wind parameters was studied mainly in terms of its role in formation of high and low atmospheric pollution levels. The analysis indicated a crucial role of local conditions in the formation of an atmospheric pollution field next to monitoring stations. Varying atmospheric pollution values across different monitoring stations within a specific city can be different even under the influence of the same atmospheric phenomena. The wind impact also formed different patterns of atmospheric pollution within same city. 12% to 22% of all monitoring stations (depending on a pollutant) indicated a prevailing impact of a single emission source (or a combined impact of a group of sources). At the same time, air pollution at other monitoring stations was highly variable, with elevated pollution levels being transported from numerous directions. The analysis of the air pollution-affected condition presented in the paper could be used as a basis for comparing ground-level pollution and assessing the warfare consequences in Ukraine. The research emphasizes the importance of updating the information about ground-based monitoring stations.

Intensive carbon combustion in sintering packed bed via steam spraying: An experimental study on carbon monoxide emission reduction.

Improving the combustion efficiency of solid fuels is important for reducing carbon monoxide emissions in the iron ore sintering process. In this paper, the surface steam spraying technology is introduced in the sintering process based on the auxiliary combustion effect of steam on coke, and its potential to reduce carbon monoxide emissions is demonstrated. Thermogravimetric analysis experiments of coke breeze in air and air-steam mixed atmosphere are carried out, and the results show that the introduction of steam can reduce the concentration of carbon monoxide in the exhaust gas from 183×10-6 to 78×10-6. At the same time, the mechanisms of carbon monoxide emission reduction by surface steam spraying technology are analyzed from the thermodynamic and kinetic perspectives. Then, a series of laboratory-scale sintering pot tests are carried out under no spraying operation, interval spraying operation, and continuous spraying operation. The results indicate that both interval and continuous spraying operations can reduce carbon monoxide emissions. The optimal mode of steam spraying under the present experimental conditions is continuously spraying for 13 min at a volume rate of 0.053 m3/min. Compared with no spraying, the average carbon monoxide concentration in the exhaust gas is reduced from 7565×10-6 to 6231×10-6, and total carbon monoxide emissions for per ton sinter are reduced from 13.46 m3/t to 9.51 m3/t.

COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo

Air pollution has become one of the factors that most affect the quality of life, human health, and the environment. Gaseous pollutants from motor vehicles have a significantly harmful effect on air quality in the Metropolitan Area of São Paulo (MASP)—Brazil. Motor vehicles emit large amounts of particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and volatile organic compounds (VOCs), the last three acting as the main tropospheric ozone (O3) precursors. In this study, we evaluated the effects of these pollutants on air quality in the MASP during the partial lockdown that was imposed to ensure the social distancing necessitated by the COVID-19 pandemic. We compared the monthly data for nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) and CO, SO2, and BC from MERRA-2 for the period between April and May 2020 (during the pandemic) with the average for the same period for the (pre-pandemic) years 2017 to 2019 in the southeast region of Brazil. The meteorological and pollutant concentration data from the CETESB air quality monitoring stations for the MASP were compared with the diurnal cycle of three previous years, with regard to the monthly averages of April and May (2017, 2018, and 2019) and the same period in 2020, when the partial lockdown was first imposed in southeast Brazil. Our findings showed that there was a decrease in NO2 concentrations ranging from 10% to more than 60% in the MASP and the Metropolitan Area of Rio de Janeiro (MARJ), whereas in the Metropolitan Area of Belo Horizonte and Vitoria (MABH and MAV, respectively), there was a reduction of around 10%. In the case of the concentrations of CO and BC from MERRA-2, there was a considerable decrease (approx. 10%) during the period of partial lockdown caused by COVID-19 throughout almost the entire state of São Paulo, particularly in the region bordering the state of Rio de Janeiro. The concentration of SO2 from MERRA-2 was 5 to 10% lower in the MASP and MARJ and the west of the MABH, and there was a decrease of 30 to 50% on the border between the states of São Paulo and Rio de Janeiro, while in the MAV region, there was an increase in pollutant levels, as this region was not significantly affected by the COVID-19 pandemic. Sharp reductions in the average hourly concentrations of CO (38.8%), NO (44.9%), NO2 (38.7%), and PM2.5 (6%) were noted at the CETESB air quality monitoring stations in the MASP during the partial lockdown in 2020 compared with the hourly average rate in the pre-pandemic period. In contrast, there was an increase of approximately 16.0% in O3 concentrations in urban areas that are seriously affected by vehicular emissions, which is probably related to a decrease in NOx.

ВЛИЯНИЕ КУРЕНИЯ НА ПОКАЗАТЕЛИ ОКИСИ УГЛЕРОДА И ОКСИДА АЗОТА В ВЫДЫХАЕМОМ ВОЗДУХЕ У ПАЦИЕНТОВ С ХРОНИЧЕСКОЙ ОБСТРУКТИВНОЙ БОЛЕЗНЬЮ ЛЕГКИХ

To date, points of view regarding the effect of smoking on the indicators of exhaled air are very contradictory, especially with regard to the examination of patients with chronic obstructive pulmonary disease (COPD) suffering from tobacco dependence. Basically, a comparative analysis is carried out by researchers solely on the fact of the presence of tobacco dependence, without taking into account the indicator of the smoking index (CI), as such, or the data obtained from the examination of smoking COPD patients and healthy volunteers are compared. Objective: to evaluate the change in the concentration of carbon monoxide (CO), nitric monoxide (NO) and carboxyhemoglobin (COHb) in the exhaled air of patients with COPD, depending on the status of smoking and CI. Material and research methods. 96 patients with COPD were examined, the average age of which was 54.6±5.9 years, the duration of the disease was 15±4.8 years. 70 patients (72.9%) who participated in the study suffered from tobacco dependence, while CI ≤10 pack-year was observed in 2.8% of them, 11-20 pack-year in 42.9%, 21-30 pack-year in 40.0% and &gt;30 pack-year in 14.3%. As part of a comprehensive examination, all patients underwent determination of CO (ppm) and COHb (%) in exhaled air using the MicroCO device (Micro medica, UK) and the level of NO was assessed using the Niox Mino analyzer (Aerocline, Sweden). The results of the study. During the analysis of the obtained data, we noted an increase in the average concentration of CO in the exhaled air in all smoking patients, while the increase in the indicator was directly proportional to the CI. A similar picture was observed with respect to the COHb level. The concentration of NO in the exhaled air, on the contrary, showed a tendency to decrease with increasing CI. A comparative analysis of the obtained data was carried out in three groups: I - non-smoking patients with COPD (n=26), II - patients with COPD with an IC of 11-20 pack-years (n=30) and III – patients with COPD with an IC of 21-30 pack-years (n=28). In terms of peripheral blood saturation, significant differences compared with the group of non-smokers were found in patients with IC 11-20 pack-years and with IC 21-30 pack-years, while there were no statistically significant differences between these groups of smoking patients. The CO level in smokers, regardless of CI, was significantly higher than in non-smokers, while in COPD patients with CI 21-30 pack-year it was also significantly higher than in patients with CI 11-20 pack-year. The COHb index in smokers with COPD was also significantly higher than in non-smokers, but when comparing data in the group with IC 11-20 pack-years and IC 21-30 pack/years, no statistically significant differences were found. In terms of NO in exhaled air, statistically significant differences were noted when comparing data in the group of non-smoking patients with COPD with the results obtained in groups of patients with IC 11-20 pack-years and with IC 21-30 pack-years, as well as when comparing data in these groups of smokers among themselves. Conclusions. The study revealed a statistically significant increase in the level of CO in the exhaled air, depending on the status of smoking and CI. It was determined that the smoking factor in COPD patients affects the level of NO in the exhaled air, causing its significant decrease in COPD patients with CI &gt;10 pack-year compared to non-smoking COPD patients.

A Descriptive Assessment of Household Air Pollution in Rural Kitchens in Kenya

Efforts to ensure households transition to modern fuels are expected to reduce household air pollution. However, exposure to toxic particles and gases in fuel stacking households remains under-researched. We implemented a household survey to identify household energy sources and assess exposure to particulate matter with diameter of ≤5 microns (PM2.5), ≤10 microns (PM10) and select polluting gases (Sulfur Dioxide (SO2), Total Volatile Organic Compounds (TVOCs), Carbon Dioxide (CO2), Nitrogen Dioxide (NO2), Carbon Monoxide (CO)) in a rural community. Wood was the main cooking fuel in 94.2% (1615/1703) households with fuel stacking reported in 86.1% (1462/1703) of total households. Daily time-weighted average concentrations of PM2.5 and PM10 were beyond World Health Organization (WHO) limits in wood-using households (189.53 (Standard deviation (SD) = 268.80) µg/m3 and 592.38 (SD = 623) µg/m3, respectively) and Liquid Petroleum Gas (LPG) -using households (57.2 (SD = 53.6) µg/m3 and 189.86 (SD = 168) µg/m3, respectively). Only daily average CO and TVOC concentration in wood-using households exceeded recommended levels. Household socio-economic status, education level of the head of household, use of a separate kitchen and household size influenced household energy choices. Rural households using wood as the main cooking fuel are exposed to high levels of particulate matter, carbon monoxide and total volatile organic compounds. LPG-using households may not realize health benefits if stacking with polluting fuels is practiced.

Carbon monoxide levels in households using coal-briquette fuelled stoves exceed WHO air quality guidelines in Ulaanbaatar, Mongolia

ABSTRACT In 2019, a domestic raw coal ban (RCB) was introduced in Ulaanbaatar, Mongolia. Coal-briquettes have since been promoted in Ger district households, however implications for carbon monoxide (CO) exposure remains uncertain. We obtained 48-hour indoor CO concentrations in 23 Ger district households and compared these to 10 raw-coal households. Information on household characteristics, fuel use behaviour and stove venting practices was collected by survey. Mean 48-hour CO concentrations in coal-briquette households was 6.1 ppm (range 1.5–35.8 ppm) with no signfiicant differences by household, stove or venting factors. Peak time-weighted average CO concentrations exceeded WHO Indoor Air Quality guidelines in 9 (39%) households; with all surpassing the 8-hour guideline (>8.6 ppm); 3(13%) the 24-hour guideline (>6 ppm) and 2(9%) the 1-hour guideline (>30 ppm). Median CO levels were significantly lower in coal-briquette compared to raw coal households (p = 0.049). Indoor CO reduction was associated with RCB implementation although hazardous levels persist in this setting.

Relationship of Surface Ozone (O3) with its precursors and meteorological parameters over New Delhi, India

In the present study, continuous measurements of Surface Ozone (O3), Oxides of Nitrogen (NOx (NO+ NO2)), and carbon monoxide (CO), monitored at five different locations in Delhi National Capital Region have been studied for the period 2013 – 2019. The five monitoring locations used are namely IMD Lodi Road, IGI Airport Palam, CV Raman Dheerpur, CRRI Mathura Road, and NCMRWF Noida. The average hourly concentration of O3, NO, NO2, CO, NOx (NO + NO2), and OX(NO2 +O3) are found in the range of 32.44 ppb to 36.57 ppb, 19.46 to 28.09 ppb, 20.83 to 26.89 ppb,1.67 to 1.89 ppm,43.04 to 54.99 ppb, and 54.06 to 60.99 ppb respectively during the study period. Diurnal variation of NOx and CO Concentrations show higher values during the morning (0600-0900h) and late evening (1900-2400h) hours while the highest concentrations of ozone have been observed during afternoon hours. The relationship between NO, NO2, and surface O3 as a function of NOx has also been examined during daylight hours (0500hrs IST to 1900 hrs IST) and chemical coupling of the three species i.e. NO, NO2 and O3 have been studied. The ground-level concentration of Ozone has been found to decrease with increasing NOx concentration during the daytime. The variations in concentrations of oxidants (NO2 + O3) with the concentration of [NOx] have been studied to examine the contributing pollution sources of oxidants at all the study sites. The average rate of change of O3 concentrations (dO3/dt) has been examined at all five locations. The monthly and diurnal variation of oxidants [OX] at all the study locations has shown a strong positive correlation with temperature whereas a negative correlation with humidity.

Associations between ambient air pollution, obesity, and serum vitamin D status in the general population of Korean adults

BackgroundAlthough a growing body of evidence suggests air pollution is associated with low serum vitamin D status, few studies have reported whether obesity status affects this relationship. The aim of this study was to identify associations between ambient air pollution exposure, obesity, and serum vitamin D status in the general population of South Korea.MethodsThis study was conducted in a cross-sectional design. A total of 30,242 Korean adults from a nationwide general population survey were included for our final analysis. Air pollutants included particulate matter with an aerodynamic diameter ≤ 10 μm (PM10), nitrogen dioxide (NO2), and carbon monoxide (CO). We measured serum 25-hydroxyvitamin D concentration to assess vitamin D status for each participant. Multiple linear and logistic regression analyses were performed to identify associations between ambient air pollution and vitamin D status in each subgroup according to body mass index level.ResultsThe annual average concentrations of PM10, NO2, and CO were significantly associated with a lower serum vitamin D concentration and higher risk of vitamin D deficiency. The results show a significant association between serum vitamin D status and PM10 exposure in obese subgroup. Based on the gender, females with obesity showed more strong association (negative) between different air pollutants and low serum vitamin D concentration and a higher risk of vitamin D deficiency. However, this pattern was not observed in men.ConclusionsThis study provides the first evidence that women with obesity may be more vulnerable to vitamin D deficiency in the context of persistent exposure to air pollution.

Spatial Analyses of Air Pollutants Concentration around the Warri Refining and Petrochemical Company (WRPC), Delta State, Nigeria

This study investigates air pollution from the Warri Refining and Petrochemical Company (WRPC) of DeltaSate, Nigeria with the intent of determining the variations in pollution levels associated with increasingdistance from the refinery. The following pollutant gases: Carbon monoxide (CO), Volatile organiccompounds (VOC), Hydrogen sulphide (H2S), Nitrogen dioxide (NO2), Sulphur dioxide (SO2) andParticulate Matter (PM2.5 and PM10), were monitored intermittently with the use of digital hand-heldprobes, at sampling points located between 1,500 meters to 16,000 meters from WRPC. Air sampling wascarried out on a weekly basis, for a duration of one (1) year. The average annual concentration of CO, VOC,H2S, NO2, SO2, PM2.5 and PM10 measured were 0.2543 ppm, 4.4922 mg/m3, 0.0004 ppm, 0.0063 ppm,0.5263 ppm, 36.3825 μg/m3, 91.7346 μg/m3 respectively. The results of the spatial analyses of air pollutantsshow that concentrations of VOC, NO2, PM2.5, and PM10 shared a significant inverse relationship withdistance (p values 0.00 ≤.0.05). The study suggests a minimum of 10,250 meters radial extent of buffersaround WRPC, as a long-term strategy in reducing exposure of residents to air pollution. Short-termstrategies include enforcement of legislation reducing/banning emissions from industries and bush fires, useof alternative eco-friendly technologies and energy sources, tree planting, revamp of the hydroelectricitypower sector and general sanitization of the environment.

Analysis of Atmospheric CO2 and CO at Akedala Atmospheric Background Observation Station, a Regional Station in Northwestern China.

Air samples were collected by flasks and analyzed via a Picarro G2401 gas analyzer for carbon dioxide (CO2) and carbon monoxide (CO) at the Akedala Atmospheric Background Station in Xinjiang, China, from September 2009 to December 2019, to analyze the changes in the characteristics of atmospheric CO2 and CO and determine the sources. The results show that the annual average CO2 concentration showed an increasing trend (growth rate: 1.90 ppm year−1), ranging from 389.80 to 410.43 ppm, and the annual average CO concentration also showed an increasing trend (growth rate: 1.78 ppb year−1), ranging from 136.30 to 189.82 ppb. The CO2 concentration and growth rate were the highest in winter, followed by autumn, spring, and summer. The CO concentration and growth rate were also the highest in winter due to anthropogenic emissions, ecosystem effects, and diffusion conditions. The main trajectories of CO2 and CO determined by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were parallel to the Irtysh River valley and then passed through the Old Wind Pass. Furthermore, the main source regions of CO2 and CO at the Akedala Station were eastern Kazakhstan, southern Russia, western Mongolia, and the Xinjiang Tianshan North Slope Economic Zone of China. This study reflects the characteristics of long-term changes in CO2 and CO concentrations at the Akedala station and provides fundamental data for the studies on environmental changes and climate change in Central Asia.

Prediction of Smoke Risk Ratings in the Combustion of Different Species of Wood

In this study, smoke performance index-V and smoke growth index-V were calculated to expand Chung's equations 1, 2, and 3 and to standardize smoke hazard rating evaluation in case of fire. For this purpose, six types of wood were selected and measured by the cone calorimeter method according to ISO 5660-1. Also, overall, smoke risk was graded by smoke risk index-VI according to Chung's equation-VI. As a results, smoke hazard index-VI was found in the order of oyster oak (0.03) ≈ chestnut (0.04) ≈ zelkova (0.08) &lt; PMMA (1.00) &lt; pitch pine (3.13) &lt; spruce (10.08) &lt; lauan (11.65). Therefore, it was predicted that oyster oak, chestnut, and zelkova had the lowest smoke risk, and lauan had the highest. However, the average concentration of carbon monoxide in the specimen is 53-142 ppm, which is higher than the OSHA limit (PEL), it is concerned that it will harm health.

Ambient air pollution and epileptic seizures: A panel study in Australia.

ObjectiveEmerging evidence has shown that ambient air pollution affects brain health, but little is known about its effect on epileptic seizures. This work aimed to assess the association between daily exposure to ambient air pollution and the risk of epileptic seizures.MethodsThis study used epileptic seizure data from two independent data sources (NeuroVista and Seer App seizure diary). In the NeuroVista data set, 3273 seizures were recorded using intracranial electroencephalography (iEEG) from 15 participants with refractory focal epilepsy in Australia in 2010–2012. In the seizure diary data set, 3419 self‐reported seizures were collected through a mobile application from 34 participants with epilepsy in Australia in 2018–2021. Daily average concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), particulate matter ≤10 μm in diameter (PM10), and sulfur dioxide (SO2) were retrieved from the Environment Protection Authority (EPA) based on participants’ postcodes. A patient‐time‐stratified case‐crossover design with the conditional Poisson regression model was used to determine the associations between air pollutants and epileptic seizures.ResultsA significant association between CO concentrations and epileptic seizure risks was observed, with an increased seizure risk of 4% (relative risk [RR]: 1.04, 95% confidence interval [CI]: 1.01–1.07) for an interquartile range (IQR) increase of CO concentrations (0.13 parts per million), whereas no significant associations were found for the other four air pollutants in the whole study population. Female participants had a significantly increased risk of seizures when exposed to elevated CO and NO2, with RRs of 1.05 (95% CI: 1.01–1.08) and 1.09 (95% CI: 1.01–1.16), respectively. In addition, a significant association was observed between CO and the risk of subclinical seizures (RR: 1.20, 95% CI: 1.12–1.28).SignificanceDaily exposure to elevated CO concentrations may be associated with an increased risk of epileptic seizures, especially for subclinical seizures.

Can Exhaled Carbon Monoxide Be Used as a Marker of Exposure? A Cross-Sectional Study in Young Adults.

Carbon monoxide (CO) poisoning is a major public health issue worldwide. People are exposed to CO in their daily lives, with one of the common sources of CO being cigarette smoking. Inhalation of CO leads to elevated carboxyhaemoglobin (COHb) levels in the blood and also in exhaled CO concentration. Several factors have been shown to affect COHb concentration and COHb half-life. However, factors affecting exhaled CO concentration and exhaled CO half-life are not well understood. The present study aimed to investigate the potential factors related to baseline exhaled CO concentration and exhaled CO half-life among smokers. A cross-sectional study was conducted between 26 January and 30 June 2019, and young adults were recruited into the study. A total of 74 participants (mean age: 27.1 years, 71.6% males and 28.4% females) attended the study. They were invited to complete a questionnaire, including demographic, physiological, and behavioural factors. Then, exhaled CO measurements were taken. These measurements were taken before and after smoking a single cigarette for smokers and only once for non-smokers. The average baseline exhaled CO concentration was 6.9 ± 4.9 ppm for smokers and 1.9 ± 0.5 ppm for non-smokers. The mean of exhaled CO half-life was around 273.3 min (4.6 h) for smokers. No difference was seen in exhaled CO half-life between light smokers and heavy smokers in the smoking group. Gender and cigarettes smoked weekly affected baseline exhaled CO in smokers. Even though height seemed to positively associate with exhaled CO half-life, the relationship disappeared when adjusting by gender and weight. Therefore, exhaled CO could be used as a marker of CO exposure, but we cannot ignore the factors mentioned in the study. For future study, considering factors related to smoking habits and smoking style are recommended as these may affect total inhaled CO.

Risk Assessment and Air Quality Study during Different Phases of COVID-19 Lockdown in an Urban Area of Klang Valley, Malaysia

Globally, the COVID-19 pandemic has had both positive and negative impacts on humans and the environment. In general, a positive impact can be seen on the environment, especially in regard to air quality. This positive impact on air quality around the world is a result of movement control orders (MCO) or lockdowns, which were carried out to reduce the cases of COVID-19 around the world. Nevertheless, data on the effects on air quality both during and post lockdown at local scales are still sparse. Here, we investigate changes in air quality during normal days, the MCOs (MCO 1, 2 and 3) and post MCOs, namely the Conditional Movement Control Order (CMCO) and the Recovery Movement Control Order (RMCO) in the Klang Valley region. In this study, we used the air sensor network AiRBOXSense that measures carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2) and particulate matter (PM2.5 and PM10) at Petaling Jaya South (PJS), Kelana Jaya (KJ) and Kota Damansara (KD). The results showed that the daily average concentrations of CO and NO2 mostly decreased in the order of normal days &gt; MCO (MCO 1, 2 and 3) &gt; CMCO &gt; RMCO. PM10, PM2.5, SO2 and O3 showed a decrease from the MCO to RMCO. PJS showed that air pollutant concentrations decreased from normal days to the lockdown phases. This clearly shows the effects of ‘work from home’ orders at all places in the PJS city. The greatest percentage reductions in air pollutants were observed during the change from normal days to MCO 1 (24% to 64%), while during MCO 1 to MCO 2, the concentrations were slightly increased during the changes of the lockdown phase, except for SO2 and NO2 over PJS. In KJ, most of the air pollutants decreased from MCO 1 to MCO 3 except for CO. However, the percentage reduction and increments of the gas pollutants were not consistent during the different phases of lockdown, and this effect was due to the sensor location—only 20 m from the main highway (vehicle emissions). The patterns of air pollutant concentrations over the KD site were similar to the PJS site; however, the percentage reduction and increases of PM2.5, O3, SO2 and CO were not consistent. We believe that local burning was the main contribution to these unstable patterns during the lockdown period. The cause of these different changes in concentrations may be due to the relaxation phases during the lockdown at each station, where most of the common activities, such as commuting and industrial activities changed in frequency from the MCO, CMCO and RMCO. Wind direction also affected the concentrations, for example, during the CMCO and RMCO, most of the pollutants were blowing in from the Southeast region, which mostly consists of a city center and industrial areas. There was a weak correlation between air pollutants and the temperature and relative humidity at all stations. Health risk assessment analysis showed that non-carcinogenic risk health quotient (HQ) values for the pollutants at all stations were less than 1, suggesting unlikely non-carcinogenic effects, except for SO2 (HQ &gt; 1) in KJ. The air quality information showed that reductions in air pollutants can be achieved if traffic and industry emissions are strictly controlled.

A comparison between national air quality index, india and composite air quality index for Ahmedabad, India

Ahmedabad is the 5th biggest city and 7th most populated city in India. It is the largest city in Gujarat. The city is spread over a further 450 sq. km. of area. The study report prepared by the World Health organization (WHO) in May 2014 reveals that Ahmedabad is the 9th most air polluted city in the world and 5th most air polluted city in India, based on the concentration of fine particulate matter (PM2.5). In this study, six different ambient air quality monitoring locations are selected in Ahmedabad. A sensor-based continuous ambient air quality monitoring instrument is used to monitor the ambient air quality of selected locations for the summer and winter seasons. The concentration of six pollutants is monitored: respirable suspended particulate matter (PM10), fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). The monitoring data shows that in the summer, the average concentration of all the pollutants at all selected locations is within National Ambient Air Quality Standards (NAAQS), 2009. In the winter, gaseous pollutants; an average hourly concentration of O3 and CO; and 24 hrs. the average concentration of SO2 and NO2 are within NAAQS, 2009 at all the selected locations. In the winter, the average concentration of particulate matter (PM10 and PM2.5) are exceeding the standards at four out of six selected locations during monitoring. So, pollutants concentration is more in winter as compared to summer, this may be due to meteorological parameters. The monitoring data also reveals that in Ahmedabad the major responsible pollutants are particulate matters (PM10 and PM2.5) rather than the gaseous pollutants.The monitoring data are used to determine the National Air Quality Index (NAQI), India, and the fuzzy-based Composite Air Quality Index (CAQI). The two indexing systems are compared. In this research article, determination methods of the National Air Quality Index and the Composite Air Quality Index are discussed. The comparison between the two-indexing system reveals that the CAQI estimates more efficiently the pollutants exposure to the population as compared to the NAQI. The CAQI shows the realistic situation, especially when two or more pollutants are exceeding the standards simultaneously. The composite air quality indexing tool is very useful to inform the citizens and to protect human well-being in an urban area. It can be used as a governmental and administrative tool to make abatement strategies and to take effective measures. The wider range of composite air quality indexes proves the superiority over the national air quality index, India.

Effect of the RME Biodiesel on the Diesel Engine Fuel Consumption and Emission

Road transport is the primary source of atmospheric air pollution, thus posing a threat to human health and life. The aim of the study was to determine the impact of fuel obtained from plants on the ecological properties of a compression ignition engine. The article reports the results of investigations into a modern engine with a Common Rail system, powered by the RME (rapeseed methyl esters) biodiesel and their blends with diesel. For comparison, the engine was also fuelled with conventional diesel oil without ester addition. When powering the engine with blends and pure biodiesel, brake specific fuel consumption increased. The concentrations of nitrogen oxides and carbon dioxide in the engine exhaust gas also slightly increased. At the same time, a clear reduction in average concentrations of carbon monoxide, hydrocarbons and particulates matter was obtained.

Incorporating gridded concentration data in air pollution back trajectories analysis for source identification

The identification of air pollution sources is a challenging task due to the confounding effects of local and transboundary emitters. While the Potential Source Contribution Function (PSCF) is a useful tool for trajectory analysis and source identification, it can overestimate the impact of less polluted areas in which a trajectory event passed through. In this work, we propose incorporating air pollutant concentration fields from reanalysis data to improve the PSCF method's performance that avoids the overcontribution of less polluted areas. We develop the 3D-PSCF-CONC based on an updated three-dimensional version of the PSCF method (3D-PSCF). We used as a test case the Metropolitan Area of São Paulo (MASP) in Brazil, one of the most polluted regions in the world, for comparing the results of the conventional and the new PSCF method. A monitoring station in Vitória - Espírito Santo, Brazil which has smaller local emissions than MASP was used as an auxiliary test case. Hourly carbon monoxide (CO) and sulfur dioxide (SO2) concentrations from 2015 to 2019 of monitoring stations were analyzed. The daily average concentrations of CO and SO2 were used as a threshold on the probability calculations. An overall of 1825 backward trajectories from HYSPLIT version 4 was processed using the three models. CO and SO2 surface concentrations from MERRA-2, with a resolution of 0.5° x 0.625° was incorporated in the 3D-PSCF-CONC to correct the potential contribution calculation based on the air pollutant concentration field. Our results revealed that the 3D-PSCF-CONC reached a more consistent identification of local and regional sources, rather than emphasizing mostly the regional sources as the other PSCF methods. The 3D-PSCF-CONC reduced the potential contribution of less polluted and high precipitation areas. The analysis suggests a contribution of vehicular sources close to the receptor site in MASP and long-range transport of industrial emissions and biomass burning from the land clearing of sugarcane production. This work presents an important tool for understanding the air pollution process and source identification.