Assessment of carbon monoxide concentration in indoor/outdoor air of Sarayan city, Khorasan Province of Iran

Characterising Carbon Monoxide Household Exposure and Health Impacts in High- and Middle-Income Countries-A Rapid Literature Review, 2010-2024

Carbon monoxide (CO) is a toxic gas, and faulty gas appliances or solid fuel burning with incomplete combustion are possible CO sources in households. Evaluating household CO exposure models and measurement studies is key to understanding where CO exposures may result in adverse health outcomes. This assists the assessment of the burden of disease in high- and middle-income countries and informs public health interventions in higher-risk environments. We conducted a literature review to identify themes that characterise CO exposure in household dwellings. A keyword-structured search using literature databases was conducted to find studies published in the period of 1 January 2010-5 June 2024. We focused on studies from high- and middle-income countries, excluding animal and biomass studies, and narratively synthesised themes. We identified 5294 papers in the literature search and included 22 papers from thirteen countries in the review. Most measured CO levels were below the WHO or country guidance levels, with sporadic peaks of measured CO linked to fuel-burning activities. To understand CO exposure in households, we identified sixteen themes grouped into five main categories: dwelling characteristics, source characteristics, temporal variation, environmental characteristics, and socioeconomic status of occupants. Seasonal variation (temporal variation), size of room and ventilation (dwelling characteristics), and cooking and outdoor CO levels (source characteristics) had the most evidence. These themes characterising CO exposure in household dwellings are important to aid the development of indoor exposure models and for understanding where CO exposures result in adverse health outcomes. These themes should be validated by household CO monitoring studies, which will enable the identification of higher-risk household dwellings and inform public health actions.

Investigating the impact of urban-environmental factors on air pollutants: a land use regression model approach and health risk assessment

The presence of pollutants in the earth's atmosphere has a direct impact on human health and the environment. So that pollutants such as carbon monoxide (CO) and particulate matter (PM) cause respiratory diseases, cough headache, etc. Since the amount of pollutants in the air is related to environmental and urban factors, the aim of the current research is to investigate the relationship between the concentration of CO, PM2.5 and PM10 with urban-environmental factors including land use, wind speed and wind direction, topography, traffic, road network, and population through a Land use regression (LUR) model. The concentrations of CO, PM2.5 and PM10 were measured during four seasons from 26th of March 2022 to 16th of March 2023 at 25 monitoring stations and then the information about pollutant measurement points and Land use data were entered into the ArcGIS software. The annual average concentrations of CO, PM2.5 and PM10 were 0.7 ppm, 18.94 and 60.76 µg/m3, respectively, in which the values of annual average concentration of CO and PMs were outside the air quality guideline standard. The results of the health risk assessment showed that the hazard quotient values for all three investigated pollutants were lower than 1 and therefore, they were not in adverse conditions in terms of health effects. Among the urban-environmental factors affecting air pollution, the traffic variable is the most important factor affecting the annual LUR model of CO, PM2.5 and PM10, and then the topography variable is the second most effective factor on the annual LUR model of the aforementioned pollutants.

Concentration of heavy metals in soil and leaves of Conocarpus Erectus Tree: A Biomonitoring Study, Ahvaz, Iran

Heavy metals biomonitoring was performed using the Conocarpus erectus tree in Ahvaz city. Composite leaf and soil samples were collected from 23 selected stations. The concentrations of heavy metals (Pb, Zn, Cd, Cu, Fe and Mn) in leaf and soil samples, and bioavailability of metals in soil samples were determined. Examination of soil physicochemical parameters proved neutral to slightly alkaline nature, and low organic matter content in the soil samples. The mean concentration of heavy metals in soil was: Fe > Mn > Zn > Pb > Cu. Ecological risk assessment of heavy metals was in the range of safe to low risk (RI < 150). Although the concentration of metals in the more polluted areas was higher in both leaf and soil samples, there was no significant relationship between the concentrations of metals in the leaf and soil samples. This relationship is even lower between the bioavailable component of metals in the soil and the concentration of metals in the leaves. Transfer factor values based on total contents of metals in soil samples indicated that Conocarpus erectus is mostly contaminated with Zn and Cu. The results of Accumulation factor of plant revealed that Pb, Zn, and Fe were mostly enriched in the plant by anthropogenic activities. MAI values in heavy and light traffic, and industrial areas were 11.88, 8.01 and 8.15, respectively. In general, it is evident that the Conocarpus erectus leaves accumulate heavy metals in polluted areas, so it can be used as a bioindicator of air pollution with heavy metals in regions with similar conditions.

Indoor air quality guidelines from across the world: An appraisal considering energy saving, health, productivity, and comfort

Buildings are constructed and operated to satisfy human needs and improve quality of life. Good indoor air quality (IAQ) and thermal comfort are prerequisites for human health and well-being. For their provision, buildings often rely on heating, ventilation, and air conditioning (HVAC) systems, which may lead to higher energy consumption. This directly impacts energy efficiency goals and the linked climate change considerations. The balance between energy use, optimum IAQ and thermal comfort calls for scientifically solid and well-established limit values for exposures experienced by building occupants in indoor spaces, including homes, schools, and offices. The present paper aims to appraise limit values for selected indoor pollutants reported in the scientific literature, and to present how they are handled in international and national guidelines and standards. The pollutants include carbon dioxide (CO2), formaldehyde (CH2O), particulate matter (PM), nitrogen dioxide (NO2), carbon monoxide (CO), and radon (Rn). Furthermore, acknowledging the particularly strong impact on energy use from HVAC, ventilation, indoor temperature (T), and relative humidity (RH) are also included, as they relate to both thermal comfort and the possibilities to avoid moisture related problems, such as mould growth and proliferation of house dust mites. Examples of national regulations for these parameters are presented, both in relation to human requirements in buildings and considering aspects related to energy saving. The work is based on the Indoor Environmental Quality (IEQ) guidelines database, which spans across countries and institutions, and aids in taking steps in the direction towards a more uniform guidance for values of indoor parameters. The database is coordinated by the Scientific and Technical Committee (STC) 34, as part of ISIAQ, the International Society of Indoor Air Quality and Climate.

Crosscutting of the pollutants and building ventilation systems: a literature review

Considering the time spent in enclosed environments, it is essential to study the relationship between pollutants and building ventilation systems to find whether the types and levels of pollutants and greenhouse gasses, which are expected to be exhaled through ventilation systems into the atmosphere, have been adequately evaluated. We propose the hypothesis that the exhaled air from residential buildings contains pollutants that may become another source of contamination affecting urban air quality and potentially contributing to climate drivers. Thus, the main goal of this article is to present a cross-review of the identification of pollutants expected to be exhaled through ventilation systems in residential buildings. This approach has created the concept of "exhalation of buildings" a new concept enclosed within the research project in which this article is included. We analyze the studies related to the most significant pollutants found in buildings and the studies about the relation of buildings' ventilation systems with such pollutants. Our results show that, on the one hand, the increase in the use of mechanical ventilation systems in residential buildings has been demonstrated to enhance the ventilation rate and generally improve the indoor air quality conditions. But no knowledge could be extracted about the corresponding environmental cost of this improvement, as no systematic data were found about the total mass of contaminants exhaled by those ventilation systems. At the same time, no projects were found that showed a quantitative study on exhalation from buildings, contrary to the existence of studies on pollutants in indoor air.

Locally weighted total least-squares variance component estimation for modeling urban air pollution

Land use regression (LUR) models are one of the standard methods for estimating air pollution concentration in urban areas. These models are usually low accurate due to inappropriate stochastic models (weight matrix). Furthermore, the measurement or modeling of dependent and independent variables used in LUR models is affected by various errors, which indicates the need to use an efficient stochastic and functional model to achieve the best estimation. This study proposes a locally weighted total least-squares variance component estimation (LW-TLS-VCE) for modeling urban air pollution. In the proposed method, in the first step, a locally weighted total least-squares (LW-TLS) regression is developed to simultaneously considers the non-stationary effects and errors of dependent and independent variables. In the second step, the variance components of the stochastic model are estimated to achieve the best linear unbiased estimation of unknowns. The efficiency of the proposed method is evaluated by modeling PM_2.5 concentrations via meteorological, land use, and traffic variables in Isfahan, Iran. The benefits provided by the proposed method, including considering non-stationary effects and random errors of all variables, besides estimating the actual variance of observations, are evaluated by comparing four consecutive methods. The obtained results demonstrate that using a suitable stochastic and functional model will significantly increase the proposed method's efficiency in PM_2.5 modeling.

Ecotoxicity testing of airborne particulate matter-comparison of sample preparation techniques for the Vibrio fischeri assay

The bioassay based on the bioluminescence inhibition of the marine bacterium Vibrio fischeri has been the most widely used test for the assessment of airborne particulate matter ecotoxicity. Most studies available use an extract of the solid sample, either made with water or organic solvents. As an alternative, a whole-aerosol test is also available where test bacteria are in actual contact with contaminated particles. In our study, different extraction procedures were compared to this direct contact test based on the V. fischeri assay and analytical measurements. The lowest PAH content and the highest EC₅₀ were determined in water extract, while the highest PAH amount and lowest EC₅₀ were measured in dichloromethane, hexane, and dimethyl-sulphoxide extracts. EC₅₀ of the direct contact test was comparable to that of the methanol extract. Our results suggest that the sensitivity of the direct contact test equals to that of extraction procedures using organic solvents, moreover, it is mimicking an environmentally realistic exposure route.

An evaluation of CO, CO2, and SO2 emissions during continuous and non-continuous operation in a gas refinery using the AERMOD

Air quality modeling can be considered as a useful tool to predict air quality in the future and determine the control strategies of emissions abatement. In this study, the AERMOD dispersion model has been applied as a tool for the analysis of the values of pollutant emissions from the flares of the Maroon gas refinery located in the suburb of Ahvaz, Iran. First, the values of pollutant emissions from the refinery's flares were investigated by measurement and using the emission factors during cold and warm seasons of 2018. The gas burns continuously in two flares and the other 11 flares are used in emergency situations and only their spark plugs are lit. The type of compounds and their molar, volumetric, and weight percentages were determined by gas chromatography (GC) injection. By entering data such as emission rate, flare characteristics, and topographic and meteorological data of the study area into the AERMOD model, dispersion of pollutants was predicted by using the AERMOD model in the region with an area of 2500 km². The statistical evaluation showed that the maximum 8-h concentration of CO in the cold season was 133441 μg/m³ which was higher than the standard and reached 9755 μg/m³ in the warm season that was close to the standard. The maximum hourly concentration of SO₂ was in the cold season with 215 μg/m³ that was higher than the standard value, occurred in a local scale of 50 km². This can be attributed to the high concentration of SO₂ wet deposition. According to the direction of the wind from the northwest, pollutant emissions can lead to adverse health effects on the population of refinery employees, residents around the refinery, and occupants of passing vehicles. The concentration of pollutants generated due to the high volume of heavier compounds in the gas in the winter season was higher than that of the warm season. Comparison of maximum concentrations of the predicted results with the national and international standards showed that SO₂ and CO concentration is higher than standard values. In total, according to the evaluation of the predictions made, the performance of the AERMOD model was acceptable in the prediction of pollutant concentrations in the study area.

A review of current air quality indexes and improvements under the multi-contaminant air pollution exposure

The air quality is one of the major concerns in the urban environment due to the rapid changes in pollutant emissions driven by complex and intensive human activities. Therefore, quantification of the urban air quality has become an essential need for both urban residents and authorities to quickly assess air quality conditions. To reach this aim, the air quality index (AQI) is the primary way to better understand the urban air quality. However, the varied AQIs in different countries are difficult to directly compare due to the varied calculation methods. Thus, this research presents an updated review of the major AQIs worldwide by dividing them into two categories: single- and multi-contaminant-oriented AQIs. Single-contaminant-oriented AQIs are based on the maximum value of individual pollutants and are applied in most countries with location-dependent standards, such as the United States, China, the United Kingdom and New South Wales, Australia. However, these may greatly underestimate the impact of multiple contaminants, be difficult to dynamically update or to be compared internationally. Moreover, multi-contaminant-oriented AQIs are available in the literature, which consider the combined effects of exposure to multiple contaminants. Among these AQIs, arithmetic pollutant aggregation simply integrates pollutants in a linear or nonlinear way, and weighted pollutant aggregation further assigns varied weights from different perspectives. Combining the advantages and disadvantages of the existing AQIs, the general air quality health index (GAQHI) is proposed as a pollutant-aggregated, local health-based AQI paradigm suitable for the present complex multi-contaminant situation. It provides a direction for the construction of a more accurate, consistent and comparable AQI system and can help both researchers and governments improve human well-being and achieve sustainable development.

Effects of long-term exposure to PM2.5 on years of life lost and expected life remaining in Ahvaz city, Iran (2008-2017)

Ambient air pollution is one of the most significant environmental problems, and many individuals around the world die each year prematurely from diseases caused by this type of pollution. PM_2.5 can transpire deep to the lungs and induce some dangerous health effects in humans. In this study, the health effects of long-term PM_2.5 were estimated on expected life remaining (ELR) and years of life lost (YLL) indices in Ahvaz city during the years 2008-2017 using the AirQ+ software developed by WHO. Values obtained from the PM_2.5 averaging, ELR, and YLL data were processed for the whole population in the age range of 0-64 and over 64. These values were entered into AirQ+ software. The mean annual concentration of PM_2.5 was highly variable, with the highest concentration being 70.72 μg/m³ in 2010 and the lowest 41.97 μg/m³ in 2014. In all studied years, the concentration of PM_2.5 with the variations between 4.2 to 7.07 times was higher than the WHO standard (10 μg/m³). Ahvaz city also did not experience any clean day during the 10-year period, and in 2010, there were 47 very unhealthy days and 27 dangerous days, i.e., the highest number of very unhealthy and dangerous days during the period. The results estimated that the highest and lowest YLL in the next 10 years for all ages groups would be 137,760.49 (2010) and 5035.52 (2014), respectively. Also, the ELR index was lower than the Iranian standard and EPA which was significantly correlated with the concentration of PM_2.5.

Relationship between the number of hospitalized cardiovascular and respiratory disease and the average concentration of criteria air pollutants (CAP) in Ahvaz

This study aims to investigate the relationship between the number of hospitalized cardiovascular and respiratory patients and the average concentration of criteria air pollutants, including NO₂, SO₂, CO, O₃ and PM₁₀ in Ahvaz in the period of 10 years (2007-2017). Data on referrals and the number of hospitalized cardiovascular and respiratory patients and also on air pollutants are obtained through Hospital Information System and air quality monitoring stations including Department of Environment Protection Station, Naderi Square Station, University Square Station and the Meteorological Organization Station. The data were analyzed by SPSS version 4 and Poisson distribution regression model to evaluate the effects of each pollutant and the rate of hospitalization. In this study, confidence interval and the significance level are considered at 95% and 5%, respectively. Changes in air pollution indices and number of patients with cardiovascular diseases were evaluated using Excel, Stata and ARIMA models. Based on the results of Poisson regression analysis, there was a significant relationship between the average concentration of NO₂, O₃, CO and SO₂ and hospitalization of patients with cardiovascular disease, with a confidence level of less than 5%. This was the case with NO₂ more than other pollutants. Furthermore, there was a significant relationship between the average concentrations of NO₂, CO and O₃ and the hospitalization rate of patients with respiratory problems and a confidence level of 5%. The effect of NO₂ was also higher here. Due to the results, NO₂, CO, and O₃ had a significant direct correlation with cardiovascular and respiratory rates. The effect of NO₂ has been higher than other pollutants. In the study of time intervals of patients with cardiovascular, the results of time-interval analysis indicate the relationship between cardiovascular clients with the "t" time of 7 days earlier and NO₂ as a pollutant. The results of this analysis also revealed the relationship between respiratory patients at the time "t" up to 7 days before and O₃.