Similar experimental study on diffusion and distribution of diesel exhaust in confined space of a coal mine.

In the confined space of the underground coal mine, which is dominated by transportation lanes, explosion-proof diesel-powered trackless rubber-wheeled vehicles are becoming the main transportation equipment, and the exhaust gas produced by them is hazardous to the health of workers and pollutes the underground environment. In this experiment, a similar test platform is built to study the effects of wind speed, vehicle speed, and different wind directions on the diffusion characteristics of exhaust gas. In this paper, CO and SO2 are mainly studied. The results show that the diffusion of CO and SO2 gas is similar and the maximum SO2 concentration only accounts for 11.4% of the CO concentration. Exhaust gas is better diluted by increasing the wind speed and vehicle speed, respectively. Downwind is affected by the reverse wind flow and diffuses to the driver's position, which is easy to cause occupational diseases. When the wind is a headwind, the exhaust gases spread upwards and make a circumvention movement, gathering at the top. When the wind speed and vehicle speed are both 0.6 m/s, the CO concentration corresponds to the change trend of the Lorentz function when the wind is downwind and the CO concentration corresponds to the change trend of the BiDoseResp function when the wind is headwind. The study of exhaust gas diffusion characteristics is of great significance for the subsequent purification of the air in the restricted mine space and the protection of the workers' occupational health.

Particulate and gaseous air pollutants exceed WHO guideline values and have the potential to damage human health in Faisalabad, Metropolitan, Pakistan.

First-ever measurements of particulate matter (PM2.5, PM10, and TSP) along with gaseous pollutants (CO, NO2, and SO2) were performed from June 2019 to April 2020 in Faisalabad, Metropolitan, Pakistan, to assess their seasonal variations; Summer 2019, Autumn 2019, Winter 2019-2020, and Spring 2020. Pollutant measurements were carried out at 30 locations with a 3-km grid distance from the Sitara Chemical Industry in District Faisalabad to Bhianwala, Sargodha Road, Tehsil Lalian, District Chiniot. ArcGIS 10.8 was used to interpolate pollutant concentrations using the inverse distance weightage method. PM2.5, PM10, and TSP concentrations were highest in summer, and lowest in autumn or winter. CO, NO2, and SO2 concentrations were highest in summer or spring and lowest in winter. Seasonal average NO2 and SO2 concentrations exceeded WHO annual air quality guide values. For all 4 seasons, some sites had better air quality than others. Even in these cleaner sites air quality index (AQI) was unhealthy for sensitive groups and the less good sites showed Very critical AQI (> 500). Dust-bound carbon and sulfur contents were higher in spring (64 mg g-1) and summer (1.17 mg g-1) and lower in autumn (55 mg g-1) and winter (1.08 mg g-1). Venous blood analysis of 20 individuals showed cadmium and lead concentrations higher than WHO permissible limits. Those individuals exposed to direct roadside pollution for longer periods because of their occupation tended to show higher Pb and Cd blood concentrations. It is concluded that air quality along the roadside is extremely poor and potentially damaging to the health of exposed workers.

IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon.

This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predict the level of particulate matter and gases in the air based on the air quality index (AQI). It is an air quality assessor and therefore a means of achieving the Sustainable Development Goals (SDGs), in particular, SDG 3.9 (substantial reduction of the health impacts of hazardous substances) and SDG 11.6 (reduction of negative impacts on cities and populations). AQI quantifies and informs the public about air pollutants and their adverse effects on public health. The proposed air quality monitoring device is low-cost and operates in real-time. It consists of a hardware unit that detects various pollutants to assess air quality as well as other airborne particles such as carbon dioxide (CO2), methane (CH4), volatile organic compounds (VOCs), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter with an aerodynamic diameter of 2.5 microns or less (PM2.5). To predict air quality, the device was deployed from November 1, 2022, to February 4, 2023, in certain bauxite-rich areas of Adamawa and certain volcanic sites in western Cameroon. Therefore, machine learning algorithm models, namely, multiple linear regression (MLR), support vector regression (SVR), random forest regression (RFR), XGBoost (XGB), and K-nearest neighbors (KNN) were applied to analyze the collected concentrations and predict the future state of air quality. The performance of these models was evaluated using mean absolute error (MAE), coefficient of determination (R-square), and root mean square error (RMSE). The obtained data in this study show that these pollutants are present in selected localities albeit to different extents. Moreover, the AQI values obtained range from 10 to 530, with a mean of 132.380 ± 63.705, corresponding to moderate air quality state but may induce an adverse effect on sensitive members of the population. This study revealed that XGB regression performed better in air quality forecasting with the highest R-squared (test score of 0.9991 and train score of 0.9999) and lowest RMSE (test score of 1.5748 and train score of 0. 0073) and MAE (test score of 0.0872 and train score of 0.0020), while the KNN model had the worst prediction (lowest R-squared and highest RMSE and MAE). This embryonic work is a prototype for projects in Cameroon as measurements are underway for a national spread over a longer period of time.

Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings.

The optimal indoor environment is associated with comfortable temperatures along with favorable indoor air quality. One of the air pollutants, particulate matter (PM), is potentially harmful to animals and humans. Most farms have monitoring systems to identify other hazardous gases rather than PM due to the sensor cost. In recent decades, the application of environmental monitoring systems based on Internet of Things (IoT) devices that incorporate low-cost sensors has elevated extensively. The current study develops a low-cost air quality monitoring system for swine buildings based on Raspberry Pi single-board computers along with a sensor array. The system collects data using 11 types of environmental variables along with temperature, humidity, CO2, light, pressure, and different types of gases, namely PM1, PM2.5, and PM10. The system is designed with a central web server that provides real-time data visualization and data availability through the Internet. It was tested in actual pig barns to ensure stability and functionality. In addition, there was a collocation test conducted by placing the system in two different pig barns to validate the sensor data. The Wilcoxon rank sum test demonstrates that there are no significant differences between the two sensor datasets, as all variables have a p-value greater than 0.05. However, except for carbon monoxide (CO), none of the variables exhibit correlation exceeding 0.5 with PM concentrations. Overall, a scalable, portable, non-complex, low-cost air quality monitoring system was successfully developed within a cost of USD 94.

Quantifying CO-release from a photo-CORM using 19F NMR: An investigation into light-induced CO delivery.

Carbon monoxide (CO) is an innate signaling molecule that can regulate immune responses and interact with crucial elements of the circadian clock. Moreover, pharmacologically, CO has been substantiated for its therapeutic advantages in animal models of diverse pathological conditions. Given that an excessive level of CO can be toxic, it is imperative to quantify the necessary amount for therapeutic use accurately. However, estimating gaseous CO is notably challenging. Therefore, novel techniques are essential to quantify CO in therapeutic applications and overcome this obstacle precisely. The classical Myoglobin (Mb) assay technique has been extensively used to determine the amount of CO-release from CO-releasing molecules (CORMs) within therapeutic contexts. Nevertheless, specific challenges arise when applying the Mb assay to evaluate CORMs featuring innovative molecular architectures. Here, we report a fluorinated photo-CORM (CORM-FBS) for the photo-induced CO-release. We employed the 19F NMR spectroscopy approach to monitor the release of CO as well as quantitative evaluation of CO release. This new 19F NMR approach opens immense opportunities for researchers to develop reliable techniques for identifying molecular structures, quantitative studies of drug metabolism, and monitoring the reaction process.

Ambient air pollution exposure and COVID-19 related hospitalizations in Santiago, Chile.

Morbidity and mortality from several diseases are increased on days of higher ambient air pollution. We carried out a daily time-series analysis with distributive lags to study the influence of short-term air pollution exposure on COVID-19 related hospitalization in Santiago, Chile between March 16 and August 31, 2020. Analyses were adjusted for temporal trends, ambient temperature, and relative humidity, and stratified by age and sex. 26,579 COVID-19 hospitalizations were recorded of which 24,501 were laboratory confirmed. The cumulative percent change in hospitalizations (95% confidence intervals) for an interquartile range increase in air pollutants were: 1.1 (0.2, 2.0) for carbon monoxide (CO), 0.30 (0.0, 0.50) for nitrogen dioxide (NO2), and 2.7 (1.9, 3.0) for particulate matter of diameter ≤ 2.5 microns (PM2.5). Associations with ozone (O3), particulate matter of diameter ≤ 10 microns (PM10) and sulfur dioxide (SO2) were not significant. The observed effect of PM2.5 was significantly greater for females and for those individuals ≥ 65 years old. This study provides evidence that daily increases in air pollution, especially PM2.5, result in a higher observed risk of hospitalization from COVID-19. Females and the elderly may be disproportionately affected.

Recent decline in carbon monoxide levels observed at an urban site in Ahmedabad, India.

Carbon monoxide (CO) is a prominent air pollutant in cities, with far-reaching implications for both local air quality and global atmospheric chemistry. The long-term change in atmospheric CO levels at a specific location is influenced by a complex interplay of local emissions, atmospheric transport, and photochemical processes, making it a subject of considerable interest. This study presents an 8-year analysis (2014-2021) of in situ CO observations using a cutting-edge laser-based analyzer at an urban site in Ahmedabad, western India. The long-term observations reveal a subtle trend in CO levels, masked by contrasting year-to-year variations, particular after 2018, across distinct diurnal time windows. Mid-afternoon (12:00-16:00 h) CO levels, reflecting background and regional conditions, remained relatively stable over the study period. In contrast, evening (18:00-21:00 h) CO levels, influenced by local emissions, exhibited substantial inter-annual variability without discernible trends from 2014 to 2018. However, post-2018, evening CO levels showed a consistent decline, predating COVID-19 lockdown measures. This decline coincided with the nationwide adoption of Bharat stage IV emission standards and other measures aimed at reducing vehicular emissions. The COVID-19 lockdown in 2020 further resulted in a noteworthy 29% reduction in evening CO levels compared to the pre-lockdown (2014-2019) period, highlighting the potential for substantial CO reduction through stringent vehicular emission controls. The observed long-term changes in CO levels do not align with the decreasing emission estimated by various inventories from 2014 to 2018, suggesting a need for improved emission statistics in Indian urban regions. This study underscores the importance of ongoing continuous CO measurements in urban areas to inform policy efforts aimed at controlling atmospheric pollutants.

Urban air pollution evaluation in downtown streets of a medium-sized Latin American city using AERMOD dispersion model.

The transport sector is considered the largest contributor of air pollutants in urban areas, mainly on-road vehicles, affecting the environment and human health. Bahía Blanca is a medium-sized Latin American city, with high levels of traffic in the downtown area during peak hours. In this regard, it is necessary to analyze air pollution using an air quality model considering that there are no air pollutant measurements in the central area. Furthermore, this type of study has not been carried out in the region and since the city is expected to grow, it is necessary to evaluate the current situation in order to make effective future decisions. In this sense, the AERMOD model (US-EPA version) and the RLINE source type were used in this work. This study analyzes the variations of pollutant concentrations coming from mobile sources in Bahía Blanca's downtown area, particularly carbon monoxide (CO) and nitrogen oxides (NOx) during the period Jul-2020 to Jun-2022. It is interesting to note the results show the maximum concentration values detected are not directly associated with maximum levels of vehicle flow or emission rates, which highlights the importance of meteorological parameters in the modeling. In addition, alternative scenarios are proposed and analyzed from a sustainable approach. Regarding the scenario analysis, it can be concluded that diesel vehicles have a large influence on NOx emissions. Moreover, restrictions as strict as those proposed for a Low Emission Zone would be less applicable in the city than alternative temporary measures that modify traffic at peak hours.

Measurement of the vertical distributions of atmospheric pollutants using an uncrewed aerial vehicle platform in Xi'an, China.

Vertical observations of atmospheric pollutants play crucial roles in a comprehensive understanding of the distribution characteristics and transport of atmospheric pollutants. A hexacopter uncrewed aerial vehicle equipped with miniature monitors was employed to measure the vertical distribution of atmospheric pollutants within a height of 1000 m at a rural site in Xi'an, China, in 2021. The concentrations of carbon monoxide (CO) and particulate matter (PM) showed generally decreasing trends with increasing height. The ozone (O3) concentration showed a general increasing trend with height followed by a gradual decreasing trend. Vertical decrements of PM2.5 and CO from 0 to 1000 m were significantly (p < 0.05) lower on observation days during summer (14.0 ± 8.1 µg m-3 and 8.7 ± 6.6 ppb, respectively), compared with those in winter (78.3 ± 14.1 µg m-3 and 34.8 ± 17.3 ppb, respectively). The horizontal transport of PM and CO mostly occurred in the morning and at night during winter observations at an altitude of 400-500 m. During the winter haze, the PM and CO profile concentrations below 500 m increased substantially with the decrease in the height of the thermal inversion layer. Vertical O3 transportation was observed in the afternoon and evening during summer, and a ∼37.7% (11.6 ppb) increase in ground-level O3 was observed in relation to vertical transport from the upper atmosphere. The results provide insights into the vertical distribution and transport of atmospheric pollutants in rural areas near cities.

Association between risk of preterm birth and long-term and short-term exposure to ambient carbon monoxide during pregnancy in chongqing, China: a study from 2016-2020.

BACKGROUND: Preterm birth (PTB) is an important predictor of perinatal morbidity and mortality. Previous researches have reported a correlation between air pollution and an increased risk of preterm birth. However, the specific relationship between short-term and long-term exposure to carbon monoxide (CO) and preterm birth remains less explored. METHODS: A population-based study was conducted among 515,498 pregnant women in Chongqing, China, to assess short-term and long-term effects of CO on preterm and very preterm births. Generalized additive models (GAM) were applied to evaluate short-term effects, and exposure-response correlation curves were plotted after adjusting for confounding factors. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using COX proportional hazard models to estimate the long-term effect. RESULTS: The daily incidence of preterm and very preterm birth was 5.99% and 0.41%, respectively. A positive association between a 100 µg/m³ increase in CO and PTB was observed at lag 0-3 days and 12-21 days, with a maximum relative risk (RR) of 1.021(95%CI: 1.001-1.043). The exposure-response curves (lag 0 day) revealed a rapid increase in PTB due to CO. Regarding long-term exposure, positive associations were found between a 100 µg/m3 CO increase for each trimester(Model 2 for trimester 1: HR = 1.054, 95%CI: 1.048-1.060; Model 2 for trimester 2: HR = 1.066, 95%CI: 1.060-1.073; Model 2 for trimester 3: HR = 1.007, 95%CI: 1.001-1.013; Model 2 for entire pregnancy: HR = 1.080, 95%CI: 1.073-1.088) and higher HRs of very preterm birth. Multiplicative interactions between air pollution and CO on the risk of preterm and very preterm birth were detected (P- interaction<0.05). CONCLUSIONS: Our findings suggest that short-term exposure to low levels of CO may have protective effects against preterm birth, while long-term exposure to low concentrations of CO may reduce the risk of both preterm and very preterm birth. Moreover, our study indicated that very preterm birth is more susceptible to the influence of long-term exposure to CO during pregnancy, with acute CO exposure exhibiting a greater impact on preterm birth. It is imperative for pregnant women to minimize exposure to ambient air pollutants.

The short-term effects of individual and mixed ambient air pollutants on suicide mortality: A case-crossover study.

It is critical to explore intervenable environmental factors in suicide mortality. Based on 30,688 suicide cases obtained from the Mortality Surveillance System of the Jiangsu Provincial Centre for Disease Control and Prevention, we utilized a case-crossover design, and found that the OR of suicide deaths increased by a maximum of 0.71 % (95 % CI: 0.09 %, 1.32 %), 0.68 % (95 % CI: 0.12 %, 1.25 %), 0.77 % (95 % CI: 0.19 %, 1.37 %), 2.95 % (95 % CI: 1.62 %, 4.29 %), 4.18 % (95 % CI: 1.55 %, 6.88 %), and 0.93 % (95 % CI: 0.10 %, 1.77 %), respectively, for per 10 µg/m3 increase in the particulate matter (PM) with diameters ≤ 2.5 µm (PM2.5), PM with diameters ≤ 10 µm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and per 0.1 mg/m3 increase in carbon monoxide (CO) concentrations with the conditional logistic regression analysis. People living in county-level cities were more susceptible. Particularly, a significant positive association was found between air pollutant mixture exposure and suicide deaths (OR=1.04,95 % CI: 1.01, 1.06). The excess fraction of suicide deaths due to air pollution reached a maximum of 8.07 %. In conclusion, we found associations between individual and mixed ambient air pollutants and suicide deaths, informing the development of integrated air pollution management and targeted measures for suicide prevention and intervention. ENVIRONMENTAL IMPLICATION: As a major contributor to the global burden of disease, air pollution was confirmed by accumulating studies to have adverse impact on mental health, and potentially lead to suicide deaths. However, systematic studies on the association between air pollution and suicide mortality are lacking. We explored the associations of multiple air pollutants and pollution mixtures with suicide deaths and assessed excess suicide mortality due to air pollution, emphasizing the importance of air pollution control on suicide prevention. Our study provides evidence to support mechanistic studies on the association between air pollution and suicide, and informs comprehensive air pollution management.

Quantum-level investigation of air decomposed pollutants gas sensor (Pd-modified g-C3N4) influenced by micro-water content.

In the electrical industry, there are many hazardous gases that pollute the environment and even jeopardize human health, so timely detection and effective control of these hazardous gases is of great significance. In this work, the gas-sensitive properties of Pd-modified g-C3N4 interface for each hazardous gas molecule were investigated from a microscopic viewpoint, taking the hazardous gases (CO, NOx) that may be generated in the power industry as the detection target. Then, the performance of Pd-modifiedg-C3N4 was evaluated for practical applications as a gas sensor material. Novelly, an unconventional means was designed to briefly predict the effect of humidity on the adsorption properties of this sensor material. The final results found that Pd-modified g-C3N4 is most suitable as a potential gas-sensitizing material for NO2 gas sensors, followed by CO. Interestingly, Pd-modified g-C3N4 is less suitable as a potential gas-sensitizing material for NO gas sensors, but has the potential to be used as a NO cleaner (adsorbent). Unconventional simulation explorations of humidity effects show that in practical applications Pd-modified g-C3N4 remains a promising material for gas sensing in specific humidity environments. This work reveals the origin of the excellent properties of Pd-modified g-C3N4 as a gas sensor material and provides new ideas for the detection and treatment of these three hazardous gases.

Experimental assessment of pollutant emissions from residential fuel cells and comparative benchmark analysis.

Energy transition currently brings focus on fuel cell micro-combined heat and power (mCHP) systems for residential uses. The two main technologies already commercialized are the Proton Exchange Membrane Fuel Cells (PEMFCs) and Solid Oxide Fuel Cells (SOFCs). The pollutant emissions of one system of each technology have been tested with a portable probe both in laboratory and field-test configurations. In this paper, the nitrogen oxides (NOx), sulphur dioxide (SO2), and carbon monoxide (CO) emission levels are compared to other combustion technologies such as a recent Euro 6 diesel automotive vehicle, a classical gas condensing boiler, and a gas absorption heat pump. At last, a method of converting the concentration of pollutants (in ppm) measured by the sensors into pollutant intensity per unit of energy (in mg/kWh) is documented and reported. This allows for comparing the pollutant emissions levels with relevant literature, especially other studies conducted with other measuring sensors. Both tested residential fuel cell technologies fed by natural gas can be considered clean regarding SO2 and NOx emissions. The CO emissions can be considered quite low for the tested SOFC and even nil for the tested PEMFC. The biggest issue of natural gas fuel cell technologies still lies in the carbon dioxide (CO2) emissions associated with the fossil fuel they consume. The gas absorption heat pump however shows worse NOx and CO levels than the classical gas condensing boiler. At last, this study illustrates that the high level of hybridization between a fuel cell and a gas boiler may be responsible for unexpected ON/OFF cycling behaviours and therefore prevent both sub-systems from operating as optimally and reliably as they would have as standalone units.

Assessing Tunisia's urban air quality using combined lichens and Sentinel-5 satellite integration.

In Tunisia, urban air pollution is becoming a bigger problem. This study used a combined strategy of biomonitoring with lichens and satellite mapping with Sentinel-5 satellite data processed in Google Earth Engine (GEE) to assess the air quality over metropolitan Tunis. Lichen diversity was surveyed across the green spaces of the Faculty of Science of Tunisia sites, revealing 15 species with a predominance of pollution-tolerant genera. The Index of Atmospheric Purity (IAP) calculated from the lichen data indicated poor air quality. Spatial patterns of pollutants sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), carbon monoxide (CO), and aerosol index across Greater Tunis were analyzed from Sentinel-5 datasets on the GEE platform. The higher values of these indices in the research area indicate that it may be impacted by industrial activity and highlight the considerable role that vehicle traffic plays in air pollution. The results of the IAP, IBL, and the combined ground-based biomonitoring and satellite mapping techniques confirm poor air quality and an environment affected by atmospheric pollutants which will enable proactive air quality management strategies to be put in place in Tunisia's rapidly expanding cities.

Electrochemical Detection of Gasotransmitters: Status and Roadmap.

Gasotransmitters, including nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2S), are a class of gaseous, endogenous signaling molecules that interact with one another in the regulation of critical cardiovascular, immune, and neurological processes. The development of analytical sensing mechanisms for gasotransmitters, especially multianalyte mechanisms, holds vast importance and constitutes a growing area of study. This review provides an overview of electrochemical sensing mechanisms with an emphasis on opportunities in multianalyte sensing. Electrochemical methods demonstrate good sensitivity, adequate selectivity, and the most well-developed potential for the multianalyte detection of gasotransmitters. Future research will likely address challenges with sensor stability and biocompatibility (i.e., sensor lifetime and cytotoxicity), sensor miniaturization, and multianalyte detection in biological settings.

Xanthene-Based Dyes for Photoacoustic Imaging and their Use as Analyte-Responsive Probes.

Developing imaging tools that can report on the presence of disease-relevant analytes in multicellular organisms can provide insight into fundamental disease mechanisms as well as provide diagnostic tools for the clinic. Photoacoustic imaging (PAI) is a light-in, sound-out imaging technique that allows for high resolution, deep-tissue imaging with applications in pre-clinical and point-of-care settings. The continued development of near-infrared (NIR) absorbing small-molecule dyes promises to improve the capabilities of this emerging imaging modality. For example, new dye scaffolds bearing chemoselective functionalities are enabling the detection and quantification of disease-relevant analytes through activity-based sensing (ABS) approaches. Recently described strategies to engineer NIR absorbing xanthenes have enabled development of analyte-responsive PAI probes using this classic dye scaffold. Herein, we present current strategies for red-shifting the spectral properties of xanthenes via bridging heteroatom or auxochrome modifications. Additionally, we explore how these strategies, coupled with chemoselective spiroring-opening approaches, have been employed to create ABS probes for in vivo detection of hypochlorous acid, nitric oxide, copper (II), human NAD(P)H: quinone oxidoreductase isozyme 1, and carbon monoxide. Given the versatility of the xanthene scaffold, we anticipate continued growth and development of analyte-responsive PAI imaging probes based on this dye class.

End-tidal carbon monoxide concentrations measured within 48 hours of birth predict hemolytic hyperbilirubinemia.

OBJECTIVES: To determine, among neonates at-risk for hyperbilirubinemia, whether measuring end-tidal carbon monoxide concentration (ETCOc) twice before 48 hours could identify those who would develop hyperbilirubinemia and differentiate hemolytic vs. non-hemolytic causes. METHODS: Prospective study on neonates meeting criteria "at-risk for hyperbilirubinemia." Routine bilirubin measurements and 10-day follow-up were used to categorize neonates as; (1) normal (no hyperbilirubinemia, all bilirubins <95th percentile of Bhutani nomogram), (2) having hemolytic hyperbilirubinemia (bilirubin ≥95th percentile, DAT+, elevated retic, or G6PD+), or (3) having non-hemolytic hyperbilirubinemia. RESULTS: 386 neonates were enrolled. 321 (83%) did not develop hyperbilirubinemia and 65 (17%) did, of which 29 were judged hemolytic and 36 non-hemolytic. High ETCOc differentiated the hemolytic group (p < 0.001). First-day ETCOc correlated with bilirubin and with reticulocyte count (r = 0.896 and 0.878) and sensitivity and specificity for predicting hyperbilirubinemia were excellent (83% and 95%). CONCLUSIONS: ETCO measurement in the first 48 hours after birth predicts hemolytic hyperbilirubinemia.

Household carbon monoxide (CO) concentrations in a large African city: An unquantified public health burden?

Carbon monoxide (CO) is a poisonous gas produced by incomplete combustion of carbon-based fuels that is linked to mortality and morbidity. Household air pollution from burning fuels on poorly ventilated stoves can lead to high concentrations of CO in homes. There are few datasets available on household concentrations of CO in urban areas of sub-Saharan African countries. CO was measured every minute over 24 h in a sample of homes in Nairobi, Kenya. Data on household characteristics were gathered by questionnaire. Metrics of exposure were summarised and analysis of temporal changes in concentration was performed. Continuous 24-h data were available from 138 homes. The mean (SD), median (IQR) and maximum 24-h CO concentration was 4.9 (6.4), 2.8 (1.0-6.3) and 44 ppm, respectively. 50% of homes had detectable CO concentrations for 847 min (14h07m) or longer during the 24-h period, and 9% of homes would have activated a CO-alarm operating to European specifications. An association between a metric of total CO exposure and self-reported exposure to vapours >15 h per week was identified, however this were not statistically significant after adjustment for the multiple comparisons performed. Mean concentrations were broadly similar in homes from a more affluent area and an informal settlement. A model of typical exposure suggests that cooking is likely to be responsible for approximately 60% of the CO exposure of Nairobi schoolchildren. Household CO concentrations are substantial in Nairobi, Kenya, despite most homes using gas or liquid fuels. Concentrations tend to be highest during the evening, probably associated with periods of cooking. Household air pollution from cooking is the main source of CO exposure of Nairobi schoolchildren. The public health impacts of long-term CO exposure in cities in sub-Saharan Africa may be considerable and should be studied further.

Isolation and identification of carbon monoxide producing microorganisms from compost.

Carbon monoxide (CO) formation has been observed during composting of various fractions of organic waste. It was reported that this production can be biotic, associated with the activity of microorganisms. However, there are no sources considering the microbial communities producing CO production in compost. This preliminary research aimed to isolate and identify microorganisms potentially responsible for the CO production in compost collected from two areas of the biowaste pile: with low (118 ppm) and high CO concentration (785 ppm). Study proved that all isolates were bacterial strains with the majority of rod-shaped Gram-positive bacteria. Both places can be inhabited by the same bacterial strains, e.g. Bacillus licheniformis and Paenibacillus lactis. The most common were Bacillus (B. licheniformis, B. haynesii, B. paralicheniformis, and B. thermolactis). After incubation of isolates in sealed bioreactors for 4 days, the highest CO levels in the headspace were recorded for B. paralicheniformis (>1000 ppm), B. licheniformis (>800 ppm), and G. thermodenitrificans (∼600 ppm). High CO concentrations were accompanied by low O2 (<6%) and high CO2 levels (>8%). It is recommended to analyze the expression of the gene encoding CODH to confirm or exclude the ability of the identified strains to convert CO2 to CO.

Deseasonalized trend of ground-level ozone and its precursors in an industrial city Kaohsiung, Taiwan.

Mitigating ground-level ozone (GLO) remains challenging due to its highly nonlinear formation process. Thus, understanding GLO pollution trends is crucial for developing effective control strategies, especially Kaohsiung industrial city, Taiwan. Based on the long-term monitoring data set of 2011-2022, temporal analysis reveals that monthly mean GLO peaks in autumn (40.66 ± 5.10 ppb), carbon monoxide (CO) and major precursors such as nitrogen oxides (NOx), nonmethane hydrocarbons (NMHC) reach their highest levels in winter. The distinct seasonal variation of air pollutants in Kaohsiung is primarily influenced by the unique blocking effect of the mountainous area under the northeasterly wind, as the city is situated downwind, causing high GLO levels during autumn due to the accumulation of stagnant air hindering the dispersion of pollutants. Over the 12 years (2011-2022), the deseasonalized trend analysis was conducted with p < 0.001, revealing a stabilization trend of GLO (+0.04 ppb/yr) from a previous sharp increase. The observed improvement is credited to a drastic decrease in total oxidants (Ox) at -0.63 ppb/yr due to significantly reducing their precursors. Furthermore, the effectiveness of precursor reduction is also supported by GLO daily maximum profile changes. While high GLO events (>120 ppb) decrease, days within midrange (60-80 ppb) rise from 24.4% to 33.3%. A notable difference emerges when comparing daytime and nighttime GLO. While daytime GLO decreased at -0.22 ppb/yr, nighttime GLO increased at +0.34 ppb/yr. Weakened nocturnal titration effects accounted for the nighttime increase. The distinct spatial variations in GLO trends on a citywide scale underscore that areas with complicated industrial activities may not benefit from a continuing reduction of precursors compared to less-polluted areas. The findings of this study hold significant implications for improving GLO control strategies in heavily industrialized city and provide valuable information to the general public about the current state of GLO pollution.