Average CO2 Concentration Research Articles

Numerical Simulation of the Smoke Distribution Characteristics in a T-Shaped Roadway

This paper numerically analyzes the influence of heat release rate (HRR) and longitudinal ventilation velocity on smoke distribution characteristics in a T-shaped roadway when the fire source was located upstream of the T-junction. The back-layering length, critical ventilation velocity, smoke temperature, and CO concentration in the main and branched roadway were investigated and analyzed. The results showed that the ventilation velocity is the key factor influencing back-layering length, while the effect of HRR on back-layering length is gradually weakened as HRR increases. The critical ventilation velocity in the T-shaped roadway is higher than in a single-tube roadway, and the predicted model of dimensional critical ventilation velocity in a T-shaped bifurcated roadway is proposed. The correlation between average temperature (Z = 1.6 m) (both in the main roadway I and the branched roadway) and ventilation velocity fits the power function, and the variation in average temperature (Z = 1.6 m) according to HRR fits the linear formula. The relation between average concentration of CO (Z = 1.6 m) (both inside the main roadway I and the branched roadway) and longitudinal ventilation velocity follows the power relation, and the variation in average concentration of CO (Z = 1.6 m) according to HRR follows the linear function.

Analysis of Primary Air Pollutants’ Spatiotemporal Distributions Based on Satellite Imagery and Machine-Learning Techniques

Accurate monitoring of air pollution is crucial to human health and the global environment. In this research, the various multispectral satellite data, including MODIS AOD/SR, Landsat 8 OLI, and Sentinel-2, together with the two most commonly used machine-learning models, viz. multi-layer backpropagation neural network (MLBPN) and random forest (RF), have been employed to analyze the spatiotemporal distributions of the primary air pollutant from 2019 to 2022 in Guanzhong Region, China. In the conducted experiments, the RF-based model, using the MODIS AOD data, has generally demonstrated the “optimal” estimation performance for the ground-surface concentrations of the primary air-pollutants. Then, the “optimal” estimation model has been employed to analyze the spatiotemporal distribution of the various air pollutants—in terms of temporal distribution, the annual average concentrations of PM2.5, PM10, NO2, and SO2 in the research area showed a decreasing trend from 2019 to 2022, while the annual average concentration of CO remained relatively stable and the annual average concentration of O3 slightly increased; in terms of the spatial distribution, the air pollution presents a gradual increase from west to east in the research area, with the distribution of higher concentrations in the center of the built-up areas and lower in the surrounding rural areas. The proposed estimation model and spatiotemporal analysis can provide reliable methodologies and data support for the further study of the air pollution characteristics in the research area.

Greenhouse Gas Distribution in the Niger Delta Region

Increased economic activity has resulted in higher levels of greenhouse gases and carbon emissions in Nigeria, making the country more vulnerable to the effects of climate change. To investigate the distribution of greenhouse gases in the Nigerien Delta, researchers used an ex post facto approach. The information was gathered from the six Niger Delta states that comprise BRACED: Delta, Edo, Rivers, Cross Rivers, and Akwa Ibom. The study focused on twelve refineries or gas flare sites, which represented all of the areas that fit the Niger Delta profile. Starting in September 2022 and ending in February 2023, data were collected every other week using Sage thermal mass flow metres. We used ANOVA and statistical diagrams to look for regional differences in climate-GHG concentrations. Greenhouse gas emissions from the Niger Delta area fell sharply between 1993 and 2022, reaching a low of 1.38 million square metres in 2010. In 2022, the average CO2 concentration in the area was 25.4µg/m³, and SO2 emissions were 20.1µg/m³. Carbon dioxide far outnumbered sulphur IV oxide (SO2) in greenhouse gas flares. Soil organic carbon concentrations averaged highest in Rivers State and lowest in Akwa Ibom. An examination of regional statistics revealed that NO2 and SO2 emissions varied significantly, with the greatest differences found between the states of Edo and Rivers. However, CO2 emissions were uniform across the country. Reduce the impact by collaborating, strengthening our capabilities, conducting research, and sharing our technologies.

An empirical study of indoor air quality in badminton stadiums in hot summer and cold winter regions of China during spring and fall seasons

The indoor air quality has a direct impact on human health. In order to obtain the current status of indoor air quality in typical sports buildings in hot summer and cold winter climate zones in China, indoor badminton courts in 10 cities in Hubei Province in this climate zone were selected as research objects for field testing of indoor environmental parameters in spring and autumn, and predict air quality parameters for non-testing times. All the tested stadiums are naturally ventilated in non-event conditions, and the average daily indoor CO2 concentration was 526.78 ppm in spring and 527.63 ppm in autumn, and the average daily PM2.5 concentration was 0.035 mg/m3 in spring and 0.024 mg/m3 in autumn, all of which met the requirements of GB/T 18883-2022, the average concentration of CO2 ≤ 1000 ppm and PM2.5 ≤ 0.05 mg/m3. The indoor CO2 concentration and PM2.5 concentration of the tested badminton halls under natural ventilation gradually increased with the accumulation of exercise time, making the indoor air quality of the badminton halls decrease, which would negatively affect the health of the people exercising in this environment.

Greenhouse gas levels (CH4 and CO2) in Lagos state and Oyo state, Nigeria

The proliferation of greenhouse gases has emerged as a grave menace to humanity. According to scientists, the concentration of these gases, particularly carbon dioxide and methane, is directly linked to the rapid pace of global warming and climate change. To investigate this matter, a study was conducted utilizing a portable gas detector to measure the levels of carbon dioxide and methane in four locations each in Ibadan and Lagos for three months. Readings were collected at each sampling site three times, with each collection period lasting 5 to 15 min. These readings were taken at intervals of 2 to 3 h over a period of 3 months, while also exploring their correlation with meteorological parameters (Temperature, wind speed and relative humidity). Farms, airports, residential areas, and dump sites were deliberately selected due to their contribution to greenhouse gas emissions. The study yielded the following mean concentrations of CO2 in Lagos: 717.67 ppm in Residential Areas, 751.78 ppm in Farmland, 743.78 ppm at the Airport, and 732.56 ppm at the Dumpsite. Similarly, the mean concentrations of CH4 were 0.14 ppm, 0.30 ppm, 0.36 ppm, and 0.45 ppm, respectively. In Ibadan, the average CO2 concentrations were 676.44 ppm in residential areas, 765.11 ppm in farms, 653.33 ppm at the airport, and 683.67 ppm at the dump site. The average CH4 concentrations were 0.08 ppm, 0.32 ppm, 0.43 ppm, and 0.30 ppm, respectively. Furthermore, significant relationships between CO2 and CH4 with meteorological parameters were observed, with R2 values of 0.200 for CO2 in Ibadan, 0.08 for CO2 in Lagos, 0.56 for CH4 in Ibadan, and 0.35 for CH4 in Lagos. Cities, farms, airports, and landfills are responsible for substantial greenhouse gas emissions. The massive release of CO2 and CH4 has resulted in profound impacts and consequences that fuel climate change. This research provides valuable insights into the issue, consequences, and mitigation strategies pertaining to the reduction and regulation of CO2 and CH4 emissions in Lagos and Ibadan, Nigeria.

Airborne transmission risks of tuberculosis and COVID-19 in schools in South Africa, Switzerland, and Tanzania: Modeling of environmental data.

The COVID-19 pandemic renewed interest in airborne transmission of respiratory infections, particularly in congregate indoor settings, such as schools. We modeled transmission risks of tuberculosis (caused by Mycobacterium tuberculosis, Mtb) and COVID-19 (caused by SARS-CoV-2) in South African, Swiss and Tanzanian secondary schools. We estimated the risks of infection with the Wells-Riley equation, expressed as the median with 2.5% and 97.5% quantiles (credible interval [CrI]), based on the ventilation rate and the duration of exposure to infectious doses (so-called quanta). We computed the air change rate (ventilation) using carbon dioxide (CO2) as a tracer gas and modeled the quanta generation rate based on reported estimates from the literature. The share of infectious students in the classroom is determined by country-specific estimates of pulmonary TB. For SARS-CoV-2, the number of infectious students was estimated based on excess mortality to mitigate the bias from country-specific reporting and testing. Average CO2 concentration (parts per million [ppm]) was 1,610 ppm in South Africa, 1,757 ppm in Switzerland, and 648 ppm in Tanzania. The annual risk of infection for Mtb was 22.1% (interquartile range [IQR] 2.7%-89.5%) in South Africa, 0.7% (IQR 0.1%-6.4%) in Switzerland, and 0.5% (IQR 0.0%-3.9%) in Tanzania. For SARS-CoV-2, the monthly risk of infection was 6.8% (IQR 0.8%-43.8%) in South Africa, 1.2% (IQR 0.1%-8.8%) in Switzerland, and 0.9% (IQR 0.1%-6.6%) in Tanzania. The differences in transmission risks primarily reflect a higher incidence of SARS-CoV-2 and particularly prevalence of TB in South Africa, but also higher air change rates due to better natural ventilation of the classrooms in Tanzania. Global comparisons of the modeled risk of infectious disease transmission in classrooms can provide high-level information for policy-making regarding appropriate infection control strategies.

Robustness of point measurements of carbon dioxide concentration for the inference of ventilation rates in a wintertime classroom

Indoor air quality in schools and classrooms is paramount for the health and well-being of pupils and staff. Carbon dioxide sensors offer a cost-effective way to assess and manage ventilation provision. However, often only a single point measurement is available which might not be representative of the CO₂ distribution within the room. A relatively generic UK classroom in wintertime is simulated using Computational Fluid Dynamics. The natural ventilation provision is driven by buoyancy through high- and low-level openings in both an opposite-ended or single-ended configuration, in which only the horizontal location of the high-level vent is modified. CO₂ is modelled as a passive scalar and is shown not to be ‘well-mixed’ within the space. Perhaps surprisingly, the single-ended configuration leads to a ‘more efficient’ ventilation, with lower average CO₂ concentration. Measurements taken near the walls, often the location of CO₂ sensors, are compared with those made throughout the classroom and found to be more representative of the ventilation rate if made above the breathing zone. These findings are robust with respect to ventilation flow rates and to the flow patterns observed, which were tested by varying the effective vent areas and the ratio of the vent areas.

Investigation of combined ventilation in the comfort conditions of an isolated room

An air conditioning system is characterized as a device that controls the air's temperature, flow, and humidity within a specific space. If an air conditioning system can guarantee that a room is comfortable, then it functions well. This investigation has assessed the properties of air dispersion and evaluated the factors and conditions outside the classroom. These variables include temperature, relative humidity, air speed, and CO2 content. The average relative humidity of the air exhibits a similar pattern to that of the average CO2 concentration, beginning to decline as air input via the valve increases. Furthermore, CO2 content is a primary determinant of indoor air quality; numerical simulation results are used to assess its value in relation to people's mouths and noses. Because of its distance from the flow source, the air velocity distribution near the ground is minimal and falls within the advised thermal comfort range. The room's air temperature is managed by the existing ceiling air conditioner, which enters the space at a 45-degree angle. An excellent combination of appropriate room air quality conditions and energy conservation can be accomplished by utilizing the ceiling cooler and the ventilation system's airflow rate.

Investigation of combined ventilation in the comfort conditions of an isolated room

An air conditioning system is characterized as a device that controls the air's temperature, flow, and humidity within a specific space. If an air conditioning system can guarantee that a room is comfortable, then it functions well. This investigation has assessed the properties of air dispersion and evaluated the factors and conditions outside the classroom. These variables include temperature, relative humidity, air speed, and CO2 content. The average relative humidity of the air exhibits a similar pattern to that of the average CO2 concentration, beginning to decline as air input via the valve increases. Furthermore, CO2 content is a primary determinant of indoor air quality; numerical simulation results are used to assess its value in relation to people's mouths and noses. Because of its distance from the flow source, the air velocity distribution near the ground is minimal and falls within the advised thermal comfort range. The room's air temperature is managed by the existing ceiling air conditioner, which enters the space at a 45-degree angle. An excellent combination of appropriate room air quality conditions and energy conservation can be accomplished by utilizing the ceiling cooler and the ventilation system's airflow rate.

Concentration, seasonality, and sources of trace elements in atmospheric aerosols from Godavari in the southern Himalayas

Atmospheric pollution has detrimental effects on human health and ecosystems. The southern region of the Himalayas, undergoing rapid urbanization and intense human activities, faces poor air quality marked by high aerosol loadings. In this study, we conducted a two-year PM10 sampling in the suburban area (Godavari) of Kathmandu, a representative metropolis situated in the southern part of the central Himalayas. The trace elements were measured to depict aerosol-bound element loadings, seasonality, and potential sources. The mean concentrations of trace elements varied considerably, ranging from 0.27 ± 0.19 ng m−3 for Tl to 1252.78 ng m−3 for Zn. The average concentration of Co and Ni was 1.2 and 22.4 times higher, respectively, than those in Lhasa city in Tibet in the northern Himalayas. The concentration of Pb was 38 times lower than that in Lahore, Pakistan, and 9 times lower than urban sites in India. For the seasonality, the trace element concentrations displayed remarkable variation, with higher concentrations during the non-monsoon seasons and lower concentrations during the monsoon season. This trend was primarily influenced by anthropogenic activities such as low-grade fuel combustion in vehicles, coal combustion in brick kilns, and biomass burning, along with seasonal rainfall that induced aerosol washout. The enrichment factors (EFs) analysis revealed that Cd, Zn, Sb, Ni, Cu, Cr, and Pb had higher EFs, indicating their significant contributions from anthropogenic sources. In contrast, elements like Tl, Co, V, Cs, U, Ba, Th, and Sr, characterized by lower EFs, were mainly associated with natural sources. The Pb isotopic ratio profiles exhibited the Pb in PM10 are derived major contribution from legacy lead. Biomass burning contributed to the Pb source in winter. These findings provide policymakers with valuable insights to develop guidelines and strategies aimed at improving air quality and mitigating the impact of aerosol pollution on human health in the Himalayan region.

The Spatio-Temporal Distribution Characteristics of Carbon Dioxide Derived from the Trajectory Mapping of Ground Observation Network Data in Shanxi Province, One of China’s Largest Emission Regions

In this study, the trajectory mapping domain-filling technology, which can provide more reliable statistical estimates of long-lived gas concentrations in a broader geographical area based on limited station data, is used to map the CO2 concentration data of six ground observation stations to the entire Shanxi Province. The technology combines a dynamical model of the atmosphere with trace gas observations, combining forward and backward trajectories to greatly expand the information on long-lived CO2 gas concentrations over a trajectory path. The mapped results show good agreement with the observation results, which reveals the generalizability of the trajectory mapping domain-filling technology. The results show that the spatio-temporal distribution characteristics of CO2 concentration in the entire Shanxi region is significant: during the five years, the provincial average CO2 concentration exhibits an overall increasing trend. The CO2 concentration increases from the north to the south across the province. Influenced by the economic growth rate and COVID-19, there are differences in the annual variation characteristics of the CO2 concentration across the entire province, with the highest year-on-year growth in 2019 and a year-on-year decrease in 2020. The increasing rate of the CO2 concentration in the northern low-value areas is faster than that in the southern high-value areas. Overall, there is a decreasing trend in the CO2 concentration growth from the north to the south in the entire province. There are seasonal differences in the CO2 concentration distribution across the entire province. The CO2 concentration and amplitude are higher in autumn and winter than they are in spring and summer. This study can provide scientific support and methodological reference for the spatio-temporal distribution characteristics analysis of GHGs at the provincial–regional scale, as well as at the national and global scales.

Influence of hydrological features on CO2 and CH4 concentrations in the surface water of lakes, Southwest China: A seasonal and mixing regime analysis

Due to the large spatiotemporal variability in the processes controlling carbon emissions from lakes, estimates of global lake carbon emission remain uncertain. Identifying the most reliable predictors of CO2 and CH4 concentrations across different hydrological features can enhance the accuracy of carbon emission estimates locally and globally. Here, we used data from 71 lakes in Southwest China varying in surface area (0.01‒702.4 km2), mean depth (< 1‒89.6 m), and climate to analyze differences in CO2 and CH4 concentrations and their driving mechanisms between the dry and rainy seasons and between different mixing regimes. The results showed that the average concentrations of CO2 and CH4 in the rainy season were 23.9 ± 18.8 μmol L−1 and 2.5 ± 4.9 μmol L−1, respectively, which were significantly higher than in the dry season (10.5 ± 10.3 μmol L−1 and 1.8 ± 4.2 μmol L−1, respectively). The average concentrations of CO2 and CH4 at the vertically mixed sites were 24.1 ± 21.8 μmol L−1 and 2.6 ± 5.4 μmol L−1, being higher than those at the stratified sites (14.8 ± 13.4 μmol L−1 and 1.7 ± 3.5 μmol L−1, respectively). Moreover, the environmental factors were divided into four categories, i.e., system productivity (represented by the contents of total nitrogen, total phosphorus, chlorophyll a and dissolved organic matter), physicochemical factors (water temperature, Secchi disk depth, dissolved oxygen and pH value), lake morphology (lake area, water depth and drainage ratio), and geoclimatic factors (altitude, wind speed, precipitation and land-use intensity). In addition to the regression and variance partitioning analyses between the concentrations of CO2 and CH4 and environmental factors, the cascading effects of environmental factors on CO2 and CH4 concentrations were further elucidated under four distinct hydrological scenarios, indicating the different driving mechanisms between the scenarios. Lake morphology and geoclimatic factors were the main direct drivers of the carbon concentrations during the rainy season, while they indirectly affected the carbon concentrations via influencing physicochemical factors and further system productivity during the dry season; although lake morphology and geoclimatic factors directly contributed to the carbon concentrations at the vertically mixed and stratified sites, the direct effect of system productivity was only observed at the stratified sites. Our results emphasize that, when estimating carbon emissions from lakes at broad spatial scales, it is essential to consider the influence of precipitation-related seasons and lake mixing regimes.

Ambient Air Pollution Monitoring and Health Studies Using Low-Cost Internet of Things Monitor within KNUST Community

Urban environments with high industrialization are infested with hazardous chemicals and airborne pollutants. These pollutants CO, O3, SO2, NO2, and PM can have devastating effects on human health, causing both acute and chronic diseases such as respiratory infections, lung cancer, and heart disease. Air pollution monitoring is vital to warn citizens of the health risks associated with exposure to high concentrations of these criteria pollutants. This study designed a low-cost IoT monitor to measure concentration levels of criteria pollutants emitted from transportation sources within Kwame Nkrumah University of Science and Technology environs. Three monitoring sites, KNUST Tech junction, Ayeduase gate junction and KNUST campus junction, were identified as the locations within the proximity of the University for the Deployment of the monitor. Hourly and mean daily CO, NO2, O3 and SO2 concentrations at each of the three sites were measured for a week using the IoT monitor, when students were in school and when students were on vacation. The average daily CO, NO2 and O3 concentrations measured at the selected locations when school was in session and during vacation were presented on histogram. The mean weekly concentrations of CO, NO2 and O3 were also estimated as 13.2ppm, 0.277ppm and 0.106ppb respectively at KNUST Tech junction; 10.1ppm, 0.254ppm and 0.110ppb respectively at Ayeduase gate junction; and 8.0ppm, 0.415ppm and 0.100ppb respectively at the KNUST campus junction when school was in session. The results show that the concentrations of all the pollutants were higher and exceeded the EPA standards except for CO at KNUST Campus junction monitoring site. These high levels of emissions is an indication of a health concern for the students at the university and university authorities can device means of curbing it.

Heavy metal toxicological analysis of vegetables cultivated in sewage-irrigated soil in the Indian metropolis of Ahmedabad City, Gujarat

Using wastewater for irrigation poses a significant health risk. We measured the concentration of (cobalt, chromium, copper, manganese, nickel, lead, and zinc) in wastewater, soil, and vegetation at 8 sites along a 60 km stretch of the Sabarmati River in Ahmedabad city. An evaluation of the potential danger from consuming contaminated vegetables was conducted using Estimated Daily Intake (EDI), Target Hazard Quotient (THQ), and Target Cancer danger (TCR). The average concentration of the metals Co, Cr, Cu, Mn, Ni, Pb, and Zn exceeds the maximum permitted limits for irrigation purposes as established by regulatory bodies. The heavy metals in the collected soil sample are ranked in descending order of concentration as follows: Zn &gt; Mn &gt; Cu &gt; Cr &gt; Ni &gt; Pb &gt; Co. The average metal concentrations in vegetables range from 0.10-11.3 µg g-1 for Co, 5.2-11.8 µg g-1 for Cr, 0.04-9.9 µg g-1 for Cu, 12.3-110 µg g-1 for Mn, 0.7-4.2 µg g-1 for Ni, 0.4-8.4 µg g-1 for Pb, and 4.4-44 µg g-1 for Zn. The mean content of heavy metals (µg g-1) in the collected vegetable samples is highest in spinach, followed by brinjal, cabbage, tomato, and cauliflower. The Hazardous Quotient (THQ) shows a high health risk for Pb (6.1) and Mn (1.02), and a medium health risk for Cr (0.9). The Target Cancer Risk (TCR) emphasized the cancer risk posed by Chromium (Cr) and Nickel (Ni), following with Lead (Pb). The study indicates a link between health risks and consuming vegetables grown in the study area. It recommends improving wastewater treatment facilities and monitoring heavy metal levels in vegetables grown in soil irrigated with wastewater at regular intervals.

Geochemical characterization and implications of soil gas and geothermal fluids in the fault zone of Xiongan new area

This study investigates the geochemical characteristics and implications of soil gas and geothermal fluids in the fault zone of Xiongan New Area (XNA). Spatial distribution analysis reveals high soil gas concentrations along the fault zone, prompting the establishment of measurement lines along specific fault segments, such as Niudong fault, with a vertical burial trend. The measured average Rn flux ranges from 71.44 to 335.35 mBq m−2s−1, while CO2 flux ranges from 25.96 to 78.23 g m−2d−1. Furthermore, the average Rn and CO2 concentration intensities range from 0.91 to 2.30 and 1.13 to 2.61, respectively, indicating significant degassing in the fault zone.Geothermal well samples are collected from the deep reservoir in XNA, displaying a predominance of Cl–Na composition. Analysis of the Na–K–Mg equilibrium diagram suggests that the chemical characteristics of deep geothermal water are a result of interactions with rocks and mixing with shallow cold water in XNA. Isotopic analysis indicates the atmospheric precipitation origin of the deep geothermal water with extensive lateral recharge from underground runoff, emphasizing strong water-rock interactions. Comparison with other tectonic units in the region reveals that the Niudong Fault Zone serves as a regional geothermal control structure, facilitating deep fluid convection.In the eastern part of XNA, the geochemical analysis reveals concentrated degassing and a relatively high proportion of mantle-derived sources near the Niudong Fault Zone. This observation suggests the fault zone serves as a primary conduit for deep gases and geothermal fluids. The findings of this research provide valuable scientific references for future urban planning, energy utilization, and geologic hazard monitoring in XNA. Continued monitoring efforts are crucial for understanding the nature of fault activity and resource distribution in the region.

Ventilation causing an average CO2 concentration of 1,000 ppm negatively affects sleep: A field-lab study on healthy young people

Poor bedroom ventilation, leading to poor indoor air quality (IAQ), has been shown to reduce sleep quality. Ventilation causing a carbon dioxide (CO2) concentration of 1,000 ppm is assumed to permit optimal sleep quality. The effects of three ventilation levels causing average indoor CO2 concentrations of 750 ppm, 1,000 ppm and 1,300 ppm, on sleep quality, physiological response and next-day work performance were examined. After a first night for adaptation, thirty-six young and healthy participants slept alone in simulated bedrooms for two nights at each of the three ventilation levels in balanced order. Sleep quality was recorded by a wrist-worn sleep tracker. Physiological parameters were measured before sleep and after waking. The participants’ ratings of the bedroom environment, the intensity of the health symptoms they experienced, and cognitive performance were obtained using questionnaires and tests.Compared with ventilation causing an average CO2 concentration of 750 ppm, sleep quality was significantly reduced at the ventilation rates causing CO2 concentrations of 1,000 ppm and 1,300 ppm: Sleep efficiency was reduced by 1.3 % and 1.8 % and time awake increased by 5.0 min and 7.8 min, respectively. Deep sleep duration decreased at the ventilation rate causing CO2 concentration of 1,300 ppm as compared to 750 ppm along with a significant increase in salivary cortisol after waking, which suggests increased stress and sympathetic activity. Ventilation causing an average CO2 concentration of 1,000 ppm or above in bedrooms should therefore be avoided. Participants whose sleep quality was poorer performed worse on tests of cognitive performance the next day.

Comparison of PBL Heights from Ceilometer Measurements and Greenhouse Gases Concentrations in São Paulo

This paper presents a study conducted in São Paulo, Brazil, where the planetary boundary layer height (PBLH) was determined using ceilometer data and the wavelet covariance transform method. The retrieved PBLH values were subsequently compared with the concentrations of CO2 and CH4 measured at three distinct experimental sites in the city. The period of study was July 2021. This study also included a comparison between ceilometer data and lidar data, which demonstrated the favorable applicability of the ceilometer data for PBLH estimation. An examination of the correlation between changes in average CO2 concentrations and PBLH values revealed stronger correlations for the IAG and UNICID stations, with correlation coefficients (ρ) of approximately −0.86 and −0.85, respectively, in contrast to the Pico do Jaraguá station, which exhibited a lower correlation coefficient of −0.42. When assessing changes in CH4 concentrations against variations in PBL height, the retrieved correlation coefficients were approximately −0.78 for IAG, −0.66 for UNICID, and −0.38 for Pico do Jaraguá. The results indicated that CO2/CH4 concentrations are negatively correlated with PBL heights, with CO2 concentrations showing more significant correlation than CH4. Additionally, among the three measurement stations, IAG measurements displayed the most substantial correlation. The results from this study contribute to the understanding of the relationship between PBLH and greenhouse gas concentrations, emphasizing the potential of remote sensing systems like ceilometers in monitoring and studying atmospheric processes.

Characterization of Microplastics and Associated Heavy Metals in Urban Soils Affected by Anthropogenic Littering: Distribution, Spatial Variation, and Influence of Soil Properties

ABSTRACT Microplastics (MPs) are ubiquitous in terrestrial and marine environments. This research work studied the occurrence, distribution of MPs and heavy metals associated with these MPs in soils of different land- use types viz. residential, commercial, and industrial areas. We identified 15 types of MP polymers, of which polypropylene (15.51%), polyethylene (12.28%), polyamide (9.57%) were dominant. MPs abundance ranged from 8.54 × 104 to 8.51 × 105 particles/kg of soil. Average abundance of MPs in the three fractions viz. < 1 mm, 1–2 mm, and 2–5 mm were 1.85 × 105, 1.31 × 105, and 697.5 particles/kg of soil, respectively. Among the three land use types, MPs abundance in < 1 mm and 1–2 mm soil fractions were significantly higher in residential areas than that in commercial and industrial areas, i.e. <1 mm: 3.4 × 105, 1.26 × 104 and 9.0 × 104, and 1–2 mm: 2.35 × 105, 8.36 × 104, and 7.50 × 104 particles/kg, respectively, for residential, commercial and industrial areas respectively. The average concentration of Cr, Fe, Mn, Cd, Co, Ni, Cu and Pb in soils were 31.79, 11047.29, 423.92, 0.05, 11.86, 17.53, 125.95 and 28.29 mg/kg, respectively, whereas that in MPs were 6.27, 2181.64, 277.36, 0.24, 6.43, 8.29, 47.05 and 9.24 mg/kg, respectively. Concentration of Cd sorbed on MPs was higher than those found in soils. Also, Pb and Cd in MPs were positively correlated to MPs abundance, indicating MPs can be vectors of heavy metals in soils. The synergistic effect of MPs and heavy metals might put soil organisms at risk.

Quantifying urban heat island and pollutant nexus: A novel geospatial approach

The interaction between Urban Heat Island (UHI) effects and air pollution in urban areas significantly impacts both the well-being of inhabitants and the delicate balance of urban ecology and climate. This study investigates the interactions between UHI effects and pollutants (CO, HCHO, aerosols, NO2, O3, and SO2) distribution in Hyderabad over four years (2019–2022) within spatial and thermal interfaces. The study identified that there is a significantly higher concentration of pollutants in the urban areas compared to the rural areas. In urban areas, the UHI indicator shows a strong positive correlation with pollutants like CO, NO2, and O3, a weaker positive correlation with HCHO, and aerosols, and a weak negative correlation with SO2. A comprehensive framework to analyse the combined impact of pollutants, yielding insights into cumulative atmospheric pollution levels - UPI indicator is proposed in this study. The subsequent generation of pollution risk map identified that around 80 % of the urban expanse is highly contaminated zones. The conjunction of thermal hotspots and high contamination zones highlights nuanced UHI-pollution associations, unveiling high-risk zones with elevated temperatures and pollutants. The high-risk zones exhibit elevated annual average concentrations of NO2, aerosols, HCHO, and CO, surpassing the non-high-risk zone by 53.535 %, 21.707 %, 7.561 %, and 1.194 %, respectively. Additionally, the high-risk zones experience a temperature higher than the non-high-risk zone by 2.601 °C. This research informs urban planning and policies, contributing to a holistic understanding of UHI-pollution dynamics and their implications.

Türkiye'deki Ocaklardan Alınan Doğal Kil Mineral Örneklerinde Ağır Metal Konsantrasyonlarının Belirlenmesi

Environmental pollution of heavy metals is increasingly becoming a problem and has become of great concern due to the adverse effects it is causing around the world. Today, various chemical, biological, and physical pollutants arising as a result of rapidpopulation growth, industrialization, and excessive mining activities have become a major problem that adversely affects people, animals, plants, organisms, and ecosystems all over the world. Sepiolite is a clay mineral containing hydrated magnesium silicate and widely used in construction, agriculture, food, fertilizer, pharmaceutical, detergent, cosmetics, paint, paper, etc. The average concentrations of Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Rb, Sr, Zr, Cd, Sn, Ba and Pb analyzed in sepiolite samples collected from three quarries (Polatlı, Beylikova, and Sivrihisar) located in the Central Anatolian Region of Turkey using EDXRF spectroscopy were found as 5456.5, 361.0, 42.0, 15.5, 65.2, 3831.5, 8.6, 23.7, 7.8, 11.8, 5.3, 13.7, 1183.2, 25.3, 3.7, 7.2, 131.9 and 5.3 mg/kg, respectively. The average enrichment factor values of V, Cr, Co, Ni, Cu, Zn, As, Sr, Cd, Sn, Ba, and Pb indicated minimal to extremely high enrichment in sepiolite. The values of non-carcinogenic risk index and cancer risk estimated to evaluate potentially health risks caused by PTEs in sepiolite samples were within the acceptable limit and the safe range except for the Beylikova quarry.