Concentrations Of Gaseous Pollutants Research Articles

Effect of UV Scattering on Detection Limit of SO2 Cameras

SO2 ultraviolet (UV) camera technology has been successfully applied to the accurate imaging detection of pollutant gas concentration; however, the actual detection ability of this technology has not been intensively studied, especially the detection accuracy and limit under the influence of the light dilution effect. Here, we theoretically and experimentally investigate the UV scattering on SO2 concentration inversion. The radiation transfer model of the light dilution effect is reconstructed, and the concept of the optimized detection limit is discussed. An outfield experiment is conducted on a ship exhaust, and the results are compared with the theoretical calculations, which indicates that the detection limit of the SO2 UV camera is 15 ppm·m at close range and increases to 25 ppm·m when the detection distance is 3.5 km. This study proves that the detection limit of the SO2 UV camera deteriorates with the decreasing atmospheric visibility, the lengthening detection distance, and the increasing aerosol content within the plume. In addition, the hardware indicators of the camera systems also play a key role in the detection limit, and taking reasonable image processing can significantly release the instruments’ performance and extend the applicability of the SO2 UV camera.

A Review of Gas Measurement Practices and Sensors for Tunnels.

The concentration of pollutant gases emitted by traffic in a tunnel affects the indoor air quality and contributes to structural deterioration. Demand control ventilation systems incur high operating costs, so reliable measurement of the gas concentration is essential. Numerous commercial sensor types are available with proven experience, such as optical and first-generation electrochemical sensors, or novel materials in detection methods. However, all of them are subjected to measurement deviations due to environmental conditions. This paper presents the main types of sensors and their application in tunnels. Solutions will also be discussed in order to obtain reliable measurements and improve the efficiency of the extraction systems.

Assessment of Dust, Chemical, Microbiological Pollutions and Microclimatic Parameters of Indoor Air in Sports Facilities.

The aim of this study was to analyse the quality of indoor air in sport facilities in one of the sport centres in Poland with respect to microclimatic parameters (temperature, humidity, and air flow velocity), particulate matter concentrations (PM10, PM4, PM2.5, and PM1), gas concentrations (oxygen, ozone, hydrogen sulphide, sulphur dioxide, volatile organic compounds, and benzopyrene), and microbial contamination (the total number of bacteria, specifically staphylococci, including Staphylococcus aureus, haemolytic bacteria, Enterobacteriaceae, Pseudomonas fluorescens, actinomycetes, and the total number of fungi and xerophilic fungi). Measurements were made three times in May 2022 at 28 sampling points in 5 different sporting areas (the climbing wall, swimming pool, swimming pool changing room, and basketball and badminton courts) depending on the time of day (morning or afternoon) and on the outside building. The obtained results were compared with the standards for air quality in sports facilities. The air temperature (21−31 °C) was at the upper limit of thermal comfort, while the air humidity (RH < 40%) in the sports halls in most of the locations was below demanded values. The values for dust pollution in all rooms, except the swimming pool, exceeded the permissible limits, especially in the afternoons. Climatic conditions correlated with a high concentration of dust in the indoor air. Particulate matter concentrations of all fractions exceeded the WHO guidelines in all researched premises; the largest exceedances of standards occurred for PM2.5 (five-fold) and for PM10 (two-fold). There were no exceedances of gaseous pollutant concentrations in the air, except for benzopyrene, which resulted from the influence of the outside air. The total number of bacteria (5.1 × 101−2.0 × 104 CFU m−3) and fungi (3.0 × 101−3.75 × 102 CFU m−3) was exceeded in the changing room and the climbing wall hall. An increased number of staphylococci in the afternoon was associated with a large number of people training. The increased concentration of xerophilic fungi in the air correlated with the high dust content and low air humidity. Along with the increase in the number of users in the afternoon and their activities, the concentration of dust (several times) and microorganisms (1−2 log) in the air increased by several times and 1−2 log, respectively. The present study indicates which air quality parameters should be monitored and provides guidelines on how to increase the comfort of those who practice sports and work in sports facilities.

Influence of spatial distribution pattern of buildings on the distribution of urban gaseous pollutants.

Buildings are the main component of urban, and their three-dimensional spatial patterns affect meteorological conditions and consequently, the spatial distribution of gaseous pollutants (CO, NO, NO2, and SO2). This study uses the Jinan Central District as the study area and constructs a building spatial distribution index system based on DEM, urban road network, and building big data. ANOVA and spatial regression models were used to study the effects of building spatial distribution indicators on the distribution of gaseous pollutants along with their spatial heterogeneity. The results showed that (1) the effects of most of spatial distribution indexes of building on the concentration distribution of the four gaseous pollutants were significant, with one-way ANOVA outcomes reaching a significance level of 0.01 or more. The DEM mean, building altitude, and their interaction with other building spatial distribution indicators are important factors affecting the distribution of gaseous pollutants; The interaction of other three-factor indicators did not have a significant effect on the distribution of gaseous pollutant concentrations. (2) The spatial distribution of CO and NO2 is mainly influenced by the indicators of the spatial distribution of buildings in this study unit, and the effects of CO and NO2 concentrations in adjacent study units are the result of the action of stochastic factors. The NO and SO2 concentrations are influenced by the spatial distribution index of buildings in this study unit, the neighborhood homogeneity index, and NO and SO2 concentrations. (3) Spatial heterogeneity was observed in the effects of building spatial distribution indicators on the concentrations of different pollutants. The GWR models constructed using CO and NO concentrations and building spatial distribution indicators were well fitted globally and locally. The CO and NO concentrations were negatively correlated with the mean topographic elevation and NO concentrations were correlated with building density.

Substantial changes in Gaseous pollutants and health effects during COVID-19 in Delhi, India.

Coronavirus disease has affected the entire population worldwide in terms of physical and environmental consequences. Therefore, the current study demonstrates the changes in the concentration of gaseous pollutants and their health effects during the COVID-19 pandemic in Delhi, the national capital city of India. In the present study, secondary data on gaseous pollutants such as nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ammonia (NH3), and ozone (O3) were collected from the Central Pollution Control Board (CPCB) on a daily basis. Data were collected from January 1, 2020, to September 30, 2020, to determine the relative changes (%) in gaseous pollutants for pre-lockdown, lockdown, and unlockdown stages of COVID-19. The current findings for gaseous pollutants reveal that concentration declined in the range of 51%-83% (NO), 40%-69% (NOx), 31%-60% (NO2), and 25%-40% (NH3) during the lockdown compared to pre-lockdown period, respectively. The drastic decrease in gaseous pollutants was observed due to restricted measures during lockdown periods. The level of ozone was observed to be higher during the lockdown periods as compared to the pre-lockdown period. These gaseous pollutants are linked between the health risk assessment and hazard identification for non-carcinogenic. However, in infants (0-1 yr), Health Quotient (HQ) for daily and annual groups was found to be higher than the rest of the exposed group (toddlers, children, and adults) in all the periods. The air quality values for pre-lockdown were calculated to be "poor category to "very poor" category in all zones of Delhi, whereas, during the lockdown period, the air quality levels for all zones were calculated as "satisfactory," except for Northeast Delhi, which displayed the "moderate" category. The computed HQ for daily chronic exposure for each pollutant across the child and adult groups was more than 1 (HQ > 1), which indicated a high probability to induce adverse health outcomes.

The Explainable Potential of Coupling Metaheuristics-Optimized-XGBoost and SHAP in Revealing VOCs’ Environmental Fate

In this paper, we explore the computational capabilities of advanced modeling tools to reveal the factors that shape the observed benzene levels and behavior under different environmental conditions. The research was based on two-year hourly data concentrations of inorganic gaseous pollutants, particulate matter, benzene, toluene, m, p-xylenes, total nonmethane hydrocarbons, and meteorological parameters obtained from the Global Data Assimilation System. In order to determine the model that will be capable of achieving a superior level of performance, eight metaheuristics algorithms were tested for eXtreme Gradient Boosting optimization, while the relative SHapley Additive exPlanations values were used to estimate the relative importance of each pollutant level and meteorological parameter for the prediction of benzene concentrations. According to the results, benzene levels are mostly shaped by toluene and the finest aerosol fraction concentrations, in the environment governed by temperature, volumetric soil moisture content, and momentum flux direction, as well as by levels of total nonmethane hydrocarbons and total nitrogen oxide. The types of conditions which provided the environment for the impact of toluene, the finest aerosol, and temperature on benzene dynamics are distinguished and described.

Gaseous Pollutants and Particulate Matter in Ambient Air: First Field Experiment in an Urban Mediterranean Area (Nador, Morocco)

Mediterranean urban areas are reportedly affected by poor air quality due to numerous emission sources, as well as topography and meteorological conditions that facilitate the accumulation of pollution. This present study makes an initial attempt to assess the effect of gaseous pollutants (NO2, CO, and O3) and particulate matter (PM2.5 and PM10) on the air quality of Nador city, which lies on the Mediterranean coast of Morocco. Three daily, short-term sampling campaigns were conducted between 2016 and 2018 in an urban area. The concentrations of PM2.5 and PM10 together with elemental compositions (up to 16 elements) and black carbon content were determined. The obtained data were characterized using descriptive analysis, correlation matrices, elemental enrichment factors (EFs), and elemental ratios. On average, the particulate matter and gaseous pollutant concentrations were below the national standard limits. Two categories of PM2.5 and PM10 sources, as derived from the EF investigation, were defined as soil/crustal (Ti, Al, Mn, Sr, K, Na, Ba, and V) and anthropogenic (Ni, Cr, Cu, Zn, and Pb). For black carbon, biomass burning was found to be the largest contributing source (3.1–8.4 µg m–3), more so than fossil fuels (0.9–1.8 µg m–3). This study highlights that an air quality management plan should be established for Nador city, including the implementation of a network of monitoring stations to help with identifying and controlling the activities causing air pollution.

İstanbul İli Merkez İlçelerindeki NO2 ve CO emisyonlarının zamansal değişimleri

This study focused on the temporal changes of pollutant gas concentrations (NO2 and CO) in the air data from different resources, the cornerstone of living life. As a result of the analyzes carried out for a total of seventeen months (January 2020 – May 2021) with consistent data, the increase and decrease trends of two of the polluting gases in the atmosphere were revealed. Geographical studies were carried out with data from one terrestrial station (Üsküdar and Mecidiyeköy) from the Anatolian and European sides of Istanbul, the most populated city in Turkiye. Satellite-based research was also carried out with the Sentinel-5 Precursor (S5p), which the European Space Agency (ESA) created to detect and monitor the concentration of gases in the atmosphere. It has been determined that either terrestrial station-based or S5p satellite data based analyzes can detect and monitor temporal changes in air quality.

Impacts of COVID-19 Lockdown on Traffic Flow, Active Travel and Gaseous Pollutant Concentrations; Implications for Future Emissions Control Measures in Oxford, UK

The COVID-19 lockdown provided a unique opportunity to test the impacts of changes in travel patterns on air quality and the environment. Therefore, this study provides insights into the impacts of COVID-19 emergency public health “lockdown” measures upon traffic flow, active travel and gaseous pollutant concentrations (NO, NO2 and O3) in Oxford city centre during 2020 using time-series analysis and linear regression methods. Comparisons of traffic counts indicated pronounced changes in traffic volume associated with national lockdown periods. Car volume reduced by 77.5% (statistically significant) during the first national lockdown, with lesser changes in goods vehicles and public transport (bus) activity during the second lockdown. Cycle flow reduced substantively during the first lockdown only. These changes resulted in a reduction in nitric oxide (NO) and nitrogen dioxide (NO2) concentrations of 75.1% and 47.4%, respectively, at roadside, and 71.8% and 34.1% at urban background during the first lockdown period. In contrast ozone (O3) concentrations increased at the urban background site by 22.3% during the first lockdown period, with no significant changes in gaseous concentrations during the second lockdown at either roadside or urban background location. The diurnal pattern of peak mean NO and NO2 concentrations reduced in magnitude and was shifted approximately 2 h earlier in the morning and 2 h later in the evening (roadside) and 3 h earlier in the morning and 3 h later in the evening (urban background). Our findings provide an example of how gaseous air quality in urban environments could respond to future urban traffic restrictions, suggesting benefits from reductions in peak and daily NO2 exposures may be offset by health harms arising from increases in ground level O3 concentrations in the summer months.

Effects of impurities in the cathode airflow on proton exchange membrane fuel cell stacks

AbstractFuel cells for mobile applications obtain their oxygen from the ambient air in road traffic. This air has contaminations of various impurities that can have negative effects on the lifetime of fuel cell systems in vehicles. The identified most relevant contaminants are toluene, nitrogen dioxide, ammonia, and sulfur dioxide. A modified test bench enables different dosages of the above‐mentioned pollutant gas concentrations on the cathode side. We examined influences both in static cycles for quasi‐steady states and in dynamic cycles for rapid load changes to examine reversible and irreversible degradation effects. We showed that the harmful cathode gases examined could lead to a shortening of the service life of fuel cells. Whereas this is well known for higher concentrations of pollutants, this contribution provides data in the sub‐ppm range – including the effects of gas mixtures – for which literature data is still limited.Additionally, a physical fuel cell model is developed to analyze the effects of various contaminants. The overall intention is to determine acceptable contamination levels and thereby increase the lifetime of fuel cells with the help of simulations. The presented model allows for the computation of cell voltage dependent on cathode side media conditions.

Application of Remote Sensing Methodology for Vehicle Emission Inspection

Remote sensing detection of vehicle emissions is an effective supplement to the statutory periodic inspection of in-use vehicle emissions and it is a convenient technical method for real-time screening of high-emission vehicles. The principle of remote sensing detection is to inversely calculate the absolute concentrations of gaseous pollutants in vehicle exhaust according to the relative volume concentration ratio of each exhaust component to carbon dioxide (CO2) in the vehicle exhaust plume. Because the combustion mechanisms of gasoline engines and diesel engines are different, different inversion calculation methods of remote sensing data must be applied. The absolute concentrations of gasoline vehicle gaseous emissions measured by remote sensing can be calculated by the inversion calculation method based on the theoretical air–fuel ratio combustion mechanism. However, the absolute concentrations of diesel vehicle nitrogen oxide (NOx) measured by remote sensing must be calculated by the inversion calculation method based on the correction of the excess air coefficient. For the integrated remote sensing test system of gasoline and diesel vehicles, it is necessary to determine the vehicle category according to the vehicle type and license plate and adopt different inversion calculation methods to obtain the correct remote sensing results of vehicle emissions. The big data statistical analysis method for vehicle emission remote sensing results can quickly screen high-emission vehicles and dynamically determine the remote sensing emission screening threshold of high-emission vehicles as the composition of in-use vehicles changes and the overall emission of vehicles declines, so as to achieve dynamic and accurate screening of high-emission vehicles.

The Effect of Rare Earths on the Response of Photo UV-Activate ZnO Gas Sensors.

In this work, ZnO nanoparticle resistive sensors decorated with rare earths (REs; including Er, Tb, Eu and Dy) were used at room temperature to detect atmospheric pollutant gases (NO2, CO and CH4). Sensitive films were prepared by drop casting from aqueous solutions of ZnO nanoparticles (NPs) and trivalent RE ions. The sensors were continuously illuminated by ultraviolet light during the detection processes. The effect of photoactivation of the sensitive films was studied, as well as the influence of humidity on the response of the sensors to polluting gases. Comparative studies on the detection properties of the sensors showed how the presence of REs increased the response to the gases detected. Low concentrations of pollutant gases (50 ppb NO2, 1 ppm CO and 3 ppm CH4) were detected at room temperature. The detection mechanisms were then discussed in terms of the possible oxidation-reduction (redox) reaction in both dry and humid air atmospheres.

Continuous estimations of daily PM2.5 chemical components from temporally sparse monitoring data using a machine learning approach

Accurate estimates of the concentrations of fine particulate matter (PM2.5) components at high spatial and temporal resolution is essential for assessing their impact on human health. In this study, we developed prediction models of daily concentrations of major PM2.5 components (sulfate, nitrate, ammonium, elemental carbon, and organic carbon) in the Kansai region, Japan, from 2010 to 2017 using the random forest algorithm. The objective is to establish a modeling approach for obtaining accurate daily estimates of PM2.5 component concentrations using temporally sparse monitoring data covering only 15% of the study period. We used gaseous and particulate pollutant concentrations, chemical transport model outputs, simulated meteorological parameters, and conventional land use and traffic-related variables to produce daily estimations at 1 km × 1 km resolution. We evaluated our models via spatial and temporal cross-validation and obtained R2 values of 0.59–0.86 for individual components. The model reproduced the day-to-day variations well, with Pearson’s correlation coefficients of 0.75–0.88 between estimates and independent data collected at continuous monitors. We estimated the daily concentrations of PM2.5 components from 2010 to 2017 at a 1 km × 1 km resolution. The annual trends of the components were obtained by temporally and spatially aggregating the daily estimations. Our modeling approach enabled accurate estimates of the daily PM2.5 component levels using temporally sparse monitoring data. The estimated concentrations will be further utilized in a birth cohort study to assess the potential health impacts of PM2.5 components.

Links between the concentrations of gaseous pollutants measured in different regions of Estonia.

The factors that determine the concentrations of air pollutants (NO, NO2, SO2, O3), measured in 8 monitoring stations (4 rural background, 3 urban, and 1 industrial) in Estonia, are studied applying the factor analysis. The factor analysis reveals remarkable impact of COVID-19 lockdown, effects caused by dramatic decrease in oil-shale based energy production in Estonia provoked by new socio-economic conditions such as elevated price for CO2 emission quota, differences between rural and urban stations, maritime-continental difference for NO2 and ozone, and specific industrial impact in case of SO2. The multiple regression analysis to predict the ozone concentration in one rural background station at Tahkuse was performed, based on the ozone concentrations measured in other stations and the concentrations of NO, NO2, and CO2, recorded in the same station. It was found that the ozone concentration at Tahkuse is rather well predictable (determination coefficient, i.e., correlation coefficient squared, R2 = 0.714), using only the concentrations from another rural station at Saarejärve that is about 110 km away from Tahkuse. Adding all the available data into the list of regression analysis arguments, the model predictability is improved moderately (determination coefficient R2 = 0.795). Large model residuals above all tend to occur with the values measured and predicted at summer nights. Surprisingly, neither NO nor NO2 concentration measured in the Tahkuse station did appear a good predictor for ozone (R2 = 0.02 and 0.05, respectively), possibly long-range transport of ozone (that has also experienced NO and/or NO2 influence during transport) overrides the local effects of NO and/or NO2.

High-resolution impacts of green areas on air quality in Madrid

This study numerically investigates the influence of trees on air quality in Madrid urban area (Spain). Simulations are performed using the mesoscale model WRF/Chem (EPA, US) and the microclimate computational fluid dynamics (CFD) model PALM4U (IMUK, DE) configured as LES (Large Eddy Simulation). PALM4U is running over one of the 1 km × 1 km grid cells with 5 m very high spatial resolution using three different scenarios. In the simulation domain, there is a zone (approximately 25% of the domain) of vegetation where the dominant species are broadleaf trees included in the BAU (Business as Usual) scenario. The second scenario is focused on changing the type of the tree from broad leaf at BAU scenario to needle leaf the so-called ND scenario and the third scenario called NOTREE which comprise the replacement of the trees located in the green zone. The base simulations (BAU) are compared with data from the Madrid air quality monitoring network for the evaluation of the simulation results. The effects of the trees are calculated comparing scenarios (BAU-NOTREE and BAU-ND), so a brute force methodology has been used. This paper shows that the effects of the trees and type of trees are not uniform across the urban area because there are variations in the energy fluxes and the aerodynamic effect and there are important interactions of trees with wind flow dynamics. The mitigation potential effect of trees on gaseous air pollutants concentrations is showed and also may enhance substantially air pollution in other areas.

Impacts of COVID-19 Restrictions on Regional and Local Air Quality Across Selected West African Cities.

The emergence of COVID‐19 brought with it panic and a sense of urgency causing governments to impose strict restrictions on human activities and vehicular movements. With anthropogenic emissions, especially waste management (domestic and municipal), traffic, and industrial activities, said to be a significant contributor to ambient air pollution, this study assessed the impacts of the imposed restrictions on the concentrations and size distribution of atmospheric aerosols and concentration of gaseous pollutants over West African subregion and seven major COVID‐19 epicenters in the subregion. Satellite retrievals and reanalysis data sets were used to study the impact of the restrictions on Aerosol Optical Depth (AOD) and atmospheric concentrations NO2, SO2, CO, and O3. The anomalies were computed for 2020 relative to 2017–2019 (the reference years). In 2020 relative to the reference years, for area‐averaged AOD levels, there was a consequential mean percentage change between −6.7% ± 21.0% and 19.2% ± 27.9% in the epicenters and −10.1% ± 15.4% over the subregion. The levels of NO2 and SO2 also reduced substantially at the epicenters, especially during the periods when the restrictions were highly enforced. However, the atmospheric levels of CO and ozone increased slightly in 2020 compared to the reference years. This study shows that “a one cap fits all” policy cannot reduced the level of air pollutants and that traffic and industrial processes are not the predominant sources of CO in major cities in the subregion.

Assessment of exposure to dust, gaseous pollutants and endotoxins in sewage treatment plants of Ahmedabad city, India.

Sewage treatment plant workers (STPs) are exposed to gaseous pollutants (H2S) and bioaerosols and their health is at risk. The aim of the study was to evaluate exposures to dust, 1,3 Beta D Glucans, endotoxins and gaseous pollutants in different process plants and to provide suitable recommendations. Gaseous pollutants and bioaerosols (inhalable dust, 1,3 beta D-glucans and endotoxins) were evaluated in two sewage treatment plants (STPs) of Ahmedabad city, India. The concentration of H2S, CO, CH4 and Cl2 were monitored in two process areas of STPs using real-time gas detectors. The dust, 1,3 beta D-glucans and endotoxins were evaluated as per standard methods. The mean concentration of H2S exceeded the permissible exposure limit of 10 ppm, whereas the concentration of other gaseous pollutants (CO, Cl2 and CH4) were below the permissible exposure limits of Indian Factories Act, 1948. The inhalable dust concentration was also within the permissible exposure limit of 10 mg/m3 as per Indian Factories Act, 1948. Significant exposures to gaseous and bioaerosols were found in the work environment of STPs. The paired t-test result showed a significant difference between two STPs for H2S, 1,3 beta D-Glucans and endotoxins. STPs were advised to reduce the exposure to H2S and bioaerosols as per CPCB guidelines applicable to India to prevent health effects.

Impact of the SARS-CoV-2 lockdown measures in Southern Spain on PM10 trace element and gaseous pollutant concentrations.

Trace element concentrations within PM10, gaseous pollutants (NO2 and SO2), and PM10 levels were studied during the Covid-19 lockdown at a regional level in Southern Spain (Andalusia). Pollutant concentrations were compared considering different mobility periods (pre-lockdown, lockdown, and relaxation) in 2020 and previous years (2013-2016). An acute decrease in NO2 levels (<50%) was observed as a consequence of traffic diminution during the confinement period. Moreover, a lower reduction in PM10 levels and a non-clear pattern for SO2 levels were observed. During the lockdown period, PM10 elements released from traffic emissions (Sn and Sb) showed the highest concentration diminution in the study area. Regarding the primary industrial sites, there were no significant differences in V, Ni, La, and Cr concentration reduction during 2020 associated with industrial activity (stainless steel and oil refinery) in Algeciras Bay. Similarly, concentrations of Zn showed the same behaviour at Cordoba, indicating that the Zn-smelter activity was not affected by the lockdown. Nevertheless, stronger reductions of Cu, Zn, and As in Huelva during the confinement period indicated a decrease in the nearby Cu-smelter emissions. Brick factories in Bailen were also influenced by the confinement measures, as corroborated by the marked decrease in concentrations of Ni, V, Cu, and Zn during the lockdown compared to that from previous years. This work has shown the baseline concentrations of trace elements of PM10, which is of great value to air quality managers in order to minimise pollution levels by applying the confinement of the population, affecting both traffic and industrial anthropogenic activities.

AN EFFECTIVE WAY TO CLEAN THE SUPPLY AIR ALONG THE HEIGHT OF BUILDINGS WITH THE HELP OF A VENTILATION SYSTEM VALVE

Statement of the problem. The most important task at present is to improve the quality of cleaning the incoming air into the premises from sources of atmospheric air pollution using an effective local ventilation system with air purification. The introduction into design practice of effective methods of air purification in forced ventilation valves along the height of the building requires the development of scientifically sound methods of their calculations and design for buildings in conditions of high pollution of the city atmosphere. Results. An effective method of cleaning the air from gaseous pollutants for the premises of buildings made it possible to obtain in the summer the cleaning efficiency: for carbon (II) oxide - 93.75%; for aliphatic hydrocarbons - 80.59%, for phenol - 79.84%, for formaldehyde - 71.88%. In winter: for carbon (II) oxide - 95%, for aliphatic hydrocarbons - 84.78%; for phenol - 80.84%, for formaldehyde - 75.89%. Conclusions. The results of the study allow us to conclude about the effectiveness of using the developed method of cleaning the incoming air into the room using the developed valve of the ventilation system to the maximum permissible concentrations of gaseous pollutants in the room.

Evaluation and Parameterization of Air Pollutants as A Function of Meteorological Parameters in Zakho City, Kurdistan Region -Iraq

Many cities in Iraq are facing environmental issues, such as air, and noise pollution, due to huge increases in population, vehicles density, heavy traffic congestion, as well as petroleum extraction. Therefore, the quality of the air has deteriorated and has threatened citizens’ health. In this research, the concentration of gaseous pollutants like carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), methane (CH4), and hydrogen sulfide (H2S) were measured at five locations near heavy traffic jams in Zakho City, (north of Iraq) during autumn and winter 2021-2022. In addition, the relationship between these pollutants and the meteorological parameter was investigated such as temperature (T, °C), relative humidity (RH, %), atmospheric pressure (AP, mbar), wind speed (WS, m/s), and wind direction (WD). Methane (CH4), and hydrogen sulfide (H2S) gases were not detected at all locations. In autumn, carbon monoxide (CO), carbon dioxide (CO2), and ozone (O3) concentrations ranged from 0.0468-8.852 ppm, 0.0497-0.071%, and 0.0012-0.145 ppm, respectively, and 0.056-8.667 ppm, 0.0417-0.06 Vol%, and 0.0006-0.0571ppm respectively during winter. The results show that concentrations of recorded gases and meteorological parameters were weakly correlated.