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In the lower atmosphere, CO2 emissions impact human health and ecosystems, making data at this level essential for addressing carbon-cycle and public-health questions. The atmospheric concentration of CO2 is crucial in urban areas due to its connection with air quality, pollution, and climate change, becoming a pivotal parameter for environmental management and public safety. In volcanic zones, geogenic CO2 profoundly affects the environment, although hydrocarbon combustion is the primary driver of increased atmospheric CO2 and global warming. Distinguishing geogenic from anthropogenic emissions is challenging, especially through air CO2 concentration measurements alone. This study presents survey results on the stable isotope composition of carbon and oxygen in CO2 and airborne CO2 concentration in Naples' urban area, including the Campi Flegrei caldera, a widespread hydrothermal/volcanic zone in the metropolitan area. Over the past 50 years, two major volcanic unrests (1969–72 and 1982–84) were monitored using seismic, deformation, and geochemical data. Since 2005, this area has experienced ongoing unrest, involving the pressurization of the underlying hydrothermal system as a causal factor of the current uplift in the Pozzuoli area and the increased CO2 emissions in the atmosphere. To better understand CO2 emission dynamics and to quantify its volcanic origin a mobile laboratory was used. Results show that CO2 levels in Naples' urban area exceed background atmospheric levels, indicating an anthropogenic origin from fossil fuel combustion. Conversely, in Pozzuoli's urban area, the stable isotope composition reveals a volcanic origin of the airborne CO2. This study emphasizes the importance of monitoring stable isotopes of atmospheric CO2, especially in volcanic areas, contributing valuable insights for environmental and public health management. [ABSTRACT FROM AUTHOR]

Abstract In the lower atmosphere, CO2 emissions impact human health and ecosystems, making data at this level essential for addressing carbon-cycle and public-health questions. The atmospheric concentration of CO2 is crucial in urban areas due to its connection with air quality, pollution, and climate change, becoming a pivotal parameter for environmental management and public safety. In volcanic zones, geogenic CO2 profoundly affects the environment, although hydrocarbon combustion is the primary driver of increased atmospheric CO2 and global warming. Distinguishing geogenic from anthropogenic emissions is challenging, especially through air CO2 concentration measurements alone. This study presents survey results on the stable isotope composition of carbon and oxygen in CO2 and airborne CO2 concentration in Naples’ urban area, including the Campi Flegrei caldera, a widespread hydrothermal/volcanic zone in the metropolitan area. Over the past 50 years, two major volcanic unrests (1969–72 and 1982–84) were monitored using seismic, deformation, and geochemical data. Since 2005, this area has experienced ongoing unrest, involving the pressurization of the underlying hydrothermal system as a causal factor of the current uplift in the Pozzuoli area and the increased CO2 emissions in the atmosphere. To better understand CO2 emission dynamics and to quantify its volcanic origin a mobile laboratory was used. Results show that CO2 levels in Naples’ urban area exceed background atmospheric levels, indicating an anthropogenic origin from fossil fuel combustion. Conversely, in Pozzuoli's urban area, the stable isotope composition reveals a volcanic origin of the airborne CO2. This study emphasizes the importance of monitoring stable isotopes of atmospheric CO2, especially in volcanic areas, contributing valuable insights for environmental and public health management.

In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote measurements to be dependable. Providing open-source options to rapidly prototype environmental datalogging systems allows quick advancement of research and monitoring programs. This paper introduces Loom, a development environment for low-power Arduino-programmable microcontrollers. Loom accommodates a range of integrated components including sensors, various datalogging formats, internet connectivity (including Wi-Fi and 4G Long Term Evolution (LTE)), radio telemetry, timing mechanisms, debugging information, and power conservation functions. Additionally, Loom includes unique applications for science, technology, engineering, and mathematics (STEM) education. By establishing modular, reconfigurable, and extensible functionality across components, Loom reduces development time for prototyping new systems. Bug fixes and optimizations achieved in one project benefit all projects that use Loom, enhancing efficiency. Although not a one-size-fits-all solution, this approach has empowered a small group of developers to support larger multidisciplinary teams designing diverse environmental sensing applications for water, soil, atmosphere, agriculture, environmental hazards, scientific monitoring, and education. This paper not only outlines the system design but also discusses alternative approaches explored and key decision points in Loom's development. [ABSTRACT FROM AUTHOR]

The databases of optical coefficients were generated for calculating the optical characteristics of water vapor using approximate methods, namely, a statistical narrow-band model and the k-distribution method. The calculation results of these methods were compared with the exact calculation method using spectral lines, which was used as a reference. A comparison of the calculation results with the available experimental data shows a satisfactory agreement. [ABSTRACT FROM AUTHOR]

During COP26, Canada joined the Global Methane Pledge aiming to reduce global methane (CH4) emissions by 30% below 2020 levels by 2030. Rapid reduction of anthropogenic CH4 emissions in the atmosphere is considered one of the most effective strategies to slow global warming in concert with carbon dioxide mitigation measures. In Canada, a large part of anthropogenic CH4 emissions can be attributed to the oil and gas industry in the Western Canada Sedimentary Basin (WCSB), which is the fourth largest reserve of fossil fuel in the world. Recent studies highlighted big discrepancies between CH4 emissions reported in Canada's National Inventory and emissions estimated with approaches using atmospheric measurements for the oil and gas sector. Measuring the isotopic signature of CH4 (δ13CH4) at different atmospheric monitoring stations and comparing these measurements to detailed archives of δ13CH4 from oil and gas wells and associated CH4 leaks in the WCSB could help better characterize the emissions from different CH4 sources over the region. In this study, we compare two independent sets of data: (1) thousands of δ13CH4 of samples from oil and gas production wells and their associated leaks (surface casing vents and ground migration) collected across the WCSB, and (2) atmospheric mixing ratios of CH4 and their δ13CH4 measured successively at three locations across this region between 2016 and 2020 combined with their atmospheric footprints modeled with HYSPLIT-STILT. We observed a gradient in the isotopic signatures of the oil and gas samples within the WCSB with δ13CH4 being more depleted in the Southeast than in the Northwest. The analysis of these samples showed that the isotopic signature of CH4 emitted by the production of fossil fuel depends on the geological formations from which it is extracted. Also, CH4 isotopic signatures vary more depending on the region where CH4 comes from than on the type of fossil fuel extracted (natural gas, oil, heavy oil, shale gas). The atmospheric measurements showed a strong seasonality of δ13CH4 at one of the atmospheric monitoring sites with isotopic signatures associated with thermogenic sources in winter and isotopic signatures associated with a mix of biogenic and thermogenic sources in summer. Using the δ13CH4 archive database from oil and gas samples, we estimated that 28–39 % of the CH4 emitted near this site in summer was coming from a biogenic source (most likely wetlands). Ultimately, atmospheric measurements collected during winter combined with their associated HYSPLIT-STILT footprints presented a spatial distribution of δ13CH4 over the WCSB comparable to the one observed in the archive database from the oil and gas sector, confirming that the oil and gas sector is the main source of CH4 in this region.

The paper presents the results of studies of the content of particulate matter PM1–PM10 in the atmosphere of the western coast of Southern Baikal with high temporal resolution. It has been established that PM are emitted into the atmosphere of Southern Baikal from both anthropogenic and natural sources. In winter, the influence of thermal power facilities increases, as evidenced by synchronous increases in the concentrations of submicron aerosol PM1 and sulfur dioxide. In summer, remote forest fires make a significant contribution to atmospheric pollution with particulate matter. The relationship between the increase in the concentration of PM1 in the atmosphere in the region under study and mesometeorological features (temperature inversions and mesoscale transfer of plumes from large thermal power plants) has been revealed. Increases in PM1 concentrations in most cases occur during the night and morning hours, which is associated with a decrease in the thickness of the atmospheric boundary layer. [ABSTRACT FROM AUTHOR]

The editorial in "Frontiers in Physics" discusses recent advancements in cavity-enhanced optical spectroscopy, highlighting improvements in precision, sensitivity, and applications in various fields such as environmental monitoring, quantum electrodynamics, and biomedical research. Different studies featured in the research topic showcase innovative methodologies and theoretical insights in cavity ring-down spectroscopy, optical frequency comb techniques, and the use of cavities for precise comb characterization and absorption measurements. These developments are crucial for enhancing environmental monitoring, medical diagnostics, and understanding molecular dynamics. [Extracted from the article]

In this study, an unmanned aerial vehicle (UAV) platform with sensing and sampling systems was developed for three-dimensional (3D) measurements of air pollutant concentrations. The sensing system of this platform contains multiple microsensors and Internet of Things devices for determining the 3D distributions of four critical air pollutants and two meteorological parameters in real time. Moreover, the sampling system comprises remote-controllable gas sampling kits, each of which contains a Tedlar bag of 1 L for the 3D measurement of volatile organic compound concentrations according to the TO-15 method of the US Environmental Protection Agency. The performance of the developed UAV platform was verified in experiments where it was used to detect air pollutant emissions from a large industrial zone in Taiwan that included a traditional industrial park, precision machinery park, and municipal waste incineration plant. Three locations were selected as field measurement sites according to the prevailing local wind direction. The vertical distributions of four critical air pollutants, ambient temperature, and relative humidity were determined from data gathered at the aforementioned sites in March and May 2023. A total of 56 and 72 chemical species were qualitatively and quantitatively analyzed in these two periods, respectively. The experimental results verified the feasibility of using the proposed UAV platform for accurately evaluating the air pollutant concentration distribution and transport in an industrial zone. The sampling system can be used as a sampling part of the Method To-15, thus extending the method to measure the 3D distribution of VOCs in an area. The UAV platform can serve as a useful tool in the management and decision-making process of air pollution in industrial areas. [ABSTRACT FROM AUTHOR]

Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources, chemical mechanisms, and transport processes of air pollution in land, sea, and atmosphere. We present an overview of coastal ocean boundary layer detection technology and equipment in China and summarize the progress and main achievements in recent years. China has developed a series of coastal ocean boundary layer detection technologies, including Light Detection and Ranging (LIDAR), turbulent exchange analyzer, air-sea flux analyzer, stereoscopic remote sensing of air pollutants, and oceanic aerosol detection equipment to address the technical bottleneck caused by harsh environmental conditions in coastal ocean regions. Advances in these technologies and equipment have provided scientific assistance for addressing air pollution issues and understanding land-sea-atmosphere interactions over coastal ocean regions in China. In the future, routine atmospheric observations should cover the coastal ocean boundary layer of China. [Display omitted] [ABSTRACT FROM AUTHOR]

Accurate monitoring of the atmospheric environment and its evolution are important for understanding the sources, chemical mechanisms, and transport processes of air pollution and carbon emissions in China, and for regulatory and control purposes. This study gives an overview of atmospheric environment monitoring technology and equipment in China and summarizes the major achievements obtained in recent years. China has made great progress in the development of atmospheric environment monitoring technology and equipment with decades of effort. The manufacturing level of atmospheric environment monitoring equipment and the quality of products have steadily improved, and a technical & production system that can meet the requirements of routine monitoring activities has been initiated. It is expected that domestic atmospheric environment monitoring technology and equipment will be able to meet future demands for routine monitoring activities in China and provide scientific assistance for addressing air pollution problems. [Display omitted] [ABSTRACT FROM AUTHOR]

Currently, the three-dimensional (3D) distribution and characteristics of air pollution cannot be understood based on the application of any single atmospheric monitoring technology. Long-term, high-precision and large-scale 3D atmospheric monitoring might become practical by combining heterogeneous modern technologies; for this purpose, the Space-Air-Ground integrated system is a promising concept. In this system, optical remote sensing technologies employing fixed or mobile platforms are used as the main means for ground-based observations. Tethered balloons, unmanned aerial vehicles (UAV) and airborne platforms serve as the air-based observation segment. The final part, satellite remote sensing, corresponds to space-based observations. Aside from obtaining the 3D distribution of air pollution, research on emission estimation and pollution mechanisms has been extensively implemented based on the strengths of this system or some portion of it. Moreover, further research on the fusion of multi-source data, optimization of inversion algorithms, and coupling with atmospheric models is of great importance to the realization of this system. [Display omitted] [ABSTRACT FROM AUTHOR]

This research aims to develop a quadrotor system as unmanned aircraft vehicles (UAVs, or drones) for monitoring atmospheric conditions in a targeted area. The system consists of an APM 2.8 arducopter flight controller, Ublox NEO M8N GPS module with compass, Racerstar 920kV 2-4S Brushless Motor, Flysky Receiver FS-iA6B with FS-i6 Remote Control Transmitter, DJI F450 quadcopter frame kits with tall landing gear skid, and a LiPo Battery 3300 mAh 35C. The system is set up and run through a Mission Planner. As for monitoring atmospheric conditions, the system consists of an Arduino Uno ATmega328P, BME280 sensors, and several modules (DS3231 Real-Time Clock (RTC), micro SD card, and 16×2 LCD). Our vehicle with a total weight of 1 kg can fly into space and maneuver to an altitude of more than 200 meters in an average of 10 minutes. Atmospheric conditions such as air temperature, relative humidity, air pressure, altitude, and precipitable water vapor can be measured and logged properly from drones. By this development, the system can be applied in the future to detect or measure weather extremes, air pollution, or monitoring aerial topography automatically when equipped with gas sensors and cameras, respectively.

Air quality monitoring in cities is significant for both human health and environment. Here, an innovative miniaturized active air sampler wearable by free-flying birds is presented. The device integrates a GPS logger and atmospheric calibrated sensors allowing for high spatiotemporal resolution measurements of carbon dioxide (CO2) concentration, barometric pressure, air temperature, and relative humidity. A field campaign, carried out from January to June 2021, involved the repeated release of homing pigeons (Columba livia) from downtown Rome (Italy), to sample the air on their way back to the loft, located in a rural area out of the city. The measurements suggest the importance of green urban areas in decreasing CO2 levels. Moreover, a positive relation between CO2 levels, relative humidity, and air temperature was revealed. In contrast, a negative relation with distance from the point of release, month, and time of day was found. Flight speed and the altitude of flight were related to rising CO2 levels. The easy use of such devices paves the way for the application of miniaturized air samplers to other synanthropic species (i.e., gulls), making birds convenient biomonitors for the urban environment. [ABSTRACT FROM AUTHOR]

Anthropogenic release of tritium from nuclear facilities is expected to increase significantly in the coming decades, which may cause radiation exposure to humans through the contamination of water and food chains. It is necessary and urgent to acquire detailed information about tritium in various environments for studying its behavior and assessing the potential radiation risk. In the atmosphere, although the passive sampling technique provides a low-cost and convenient way to characterize the dynamics of tritiated water vapor (HTO), a single, simple sampler configuration makes it difficult to collect sufficient and representative samples within the expected period from different environments. In this study, we systematically studied the impacts of sampler configurations on sampling performance and proposed a modifiable sampler design by scaling sampler geometry and adjusting absorbent to achieve different monitoring demands. The samplers were subsequently deployed at five sites in China and Germany for the field calibration and the measured results exhibited a good agreement between the adsorption process obtained in sites corrected with diffusion coefficient and the one calibrated in Shanghai. This suggests the feasibility of predicting sampling performance in the field based on known data. Finally, we developed a strategy for sampler modification and selection in different environments and demonstrated that using easily obtainable environmental data, our sampler can be optimized for any area without any time-consuming preliminary experiments. This work provides a scientific basis for establishing high-resolution atmospheric HTO database and expands the conventional empirical sampler design paradigm by demonstrating the feasibility of using quantitative indices for sampler performance customization.

Progress in the development of infrared (IR) laser diodes, photodetector elements of matrices in the visible and IR ranges, lidar systems allows the use of optical location methods to detect and track moving objects in the atmosphere. This is primarily related to unmanned aerial vehicles (UAVs), which are widely used in many areas of human activity. This paper describes an experimental setup that makes it possible to detect a moving object in the atmosphere at a distance of more than 1 km, determine the distance to it, and automatically track it. The installation consists of a matrix photodetector of the visible and IR ranges, an active illumination source in the form of an IR laser diode emitting at a wavelength of λ = 808 nm with an output power of 30 W, and an IR lidar module with an energy per pulse of up to 15 mJ, emitting at a wavelength of λ = 1540 nm. It is shown that a combination of passive and active optical methods makes it possible to detect moving objects in the atmosphere, such as aerosol clouds or UAVs. For the automatic detection of moving objects of various types in the process of image processing in the visible and IR ranges, deep learning methods (convolutional neural networks) are used. With the help of the described installation, the linear dimensions of UAVs were estimated on routes of up to 1 km. [ABSTRACT FROM AUTHOR]

A high-precision gas detection system with a dual-incidence multi-pass cell (D-MPC) based on TDLAS was developed, which can simultaneously measure quadruple component gases. Two Distributed Feedback (DBF) Laser Diodes with central wavelength of 1654 nm and 2004 nm were utilized to measure methane (CH 4) and carbon dioxide (CO 2) for evaluating the performance of the system. High sensitivity and low frequency drift were accomplished by utilizing the second harmonic signals (WMS-2 f) detection and peak-locking technology. A LabVIEW-based control and acquisition program, which could be used for direct absorption and wavelength modulation, was developed. Kalman adaptive filtering, Least Mean Squares (LMS) adaptive filtering and S-G filtering were employed for denoising in direct absorption spectroscopy (DAS), respectively, and optimal denoising technology of S-G filtering was selected. According to Allan deviation analysis, the optimal detection precision for CH 4 and CO 2 was 12 ppb at an integration time of 36 s and 270 ppb at an integration time of 43 s, respectively. A two-day continuous monitoring of atmospheric CO 2 and CH 4 was implemented to verify the system stability and can be applied to other trace gases monitoring. • A high-precision gas detection system with a dual-incidence multi-pass cell (D-MPC) based on TDLAS was developed. • The D-MPC was designed with four path length of 51.85 m, 61.65 m, 85.5 m and 50.4 m. • High sensitivity and low drift were accomplished by utilizing the peak-locking technology. • The frequency drifts were controlled within ± 1.2 × 10−3 cm−1 by a method that was to adjust current by digital PID. • A control and acquisition program, which can work in direct measurements and wavelength modulation was developed. [ABSTRACT FROM AUTHOR]

An uncrewed aerial vehicle (UAV) platform equipped with dual imaging cameras, a gas sampling system, and a remote synchronous monitoring system was developed to sample and analyze volatile organic compounds (VOCs) emitted from landfills. The remote synchronous monitoring system provided real-time video to administrators with specific permissions to assist in identifying sampling sites within extensive landfill areas. The sampling system included four kits capable of collecting samples from different locations during a single flight mission. Each kit comprised a 1 L Tedlar bag for measuring landfill VOC concentrations according to the TO-15 method prescribed by the US Environmental Protection Agency. The air sample was introduced into a Tedlar bag via pumping. A known volume of the sample was subsequently concentrated using a solid multisorbent concentrator. Following this, the sample underwent cold trap concentration and thermal desorption. The concentrated sample was then transferred to a chromatography-mass spectrometry system for separation and analysis. Since the anaerobic catabolism of organic waste is exothermic and emits VOCs, this study employed UAV thermal imaging to locate principal emission sources for sampling. Visible-light imaging helped identify newer or older landfill sections, aiding in the selection of appropriate sampling sites, particularly when surfaces were thermally disturbed by solar radiation. Field measurements were conducted under three meteorological conditions: sunny morning, cirrus morning, and thin cloud evening (2 h after sunset), identifying 119, 122, and 111 chemical species respectively. The sequence of total VOC concentrations measured correlated with the meteorological conditions as follows: cirrus morning > thin cloud evening > sunny morning. The results indicated that ambient temperature and global solar radiation significantly influenced daytime gas emissions from landfills. Evening thermal images, unaffected by solar heating, facilitated more accurate identification of major VOC emission points, resulting in higher VOC concentrations compared to those recorded in the sunny morning. VOCs from the landfill were categorized into nine organic groups: alkanes, alkenes, carbonyls, aromatics, alcohols, esters, ethers, organic oxides, and others. The classification was based on carbon-containing compounds (C n , where the compound contains n carbon atoms). Alkanes were predominant in terms of C n presence, followed by alcohols and carbonyls. Among the organic groups, organic oxides, particularly 2-heptyl-1,3-dioxolane, exhibited the highest concentrations, succeeded by alkenes. Sampling under cloudy conditions or in the evening is recommended to minimize the effects of surface temperature anomalies caused by solar radiation, which vary due to differences in land composition. • Develop a UAV platform with dual cameras, remote monitoring, and sampling systems. • Extend the US EPA method-15 with a UAV system to measure air pollutants emission from landfills. • Present an approach for evaluating volatile organic compounds emission from landfills. • A system provided real-time video to managers for remote monitoring and decision. [ABSTRACT FROM AUTHOR]

Carbon capture and storage (CCS) in subsurface formations has emerged as a promising strategy to address global warming. In light of this, this review aims to provide a comprehensive understanding of the mechanisms involved in the geological trapping of CO 2. Additionally, it aims to identify the techniques used to evaluate the potential for CO 2 sequestration before injecting CO 2 into subsurface formations and the methods used to monitor the progress of CO 2 sequestration after injection. The review also presents future research directions based on current research trends in the field. Four principal trapping mechanisms were identified: structural, capillary (residual), solubility, and mineral trapping. These mechanisms vary in their CO 2 trapping capacity over time and the storage security they offer. Structural trapping provides the most significant contribution to CO 2 trapping, whereas mineral trapping offers the highest storage security. In terms of monitoring and assessment, three main approaches were identified, including seismic and borehole geophysical methods, atmospheric monitoring methods, and laboratory-scale experiments. One of the novel aspects of this review is that it outlines the various experimental techniques used for investigating CO 2 trapping mechanisms, an area that prior reviews have not addressed. At the laboratory level, various tests and experiments are used to study CO 2 trapping characteristics. These are categorized into petrophysical characterization, pore-scale experiments, CO 2 -fluid-rock interaction experiments, and CO 2 adsorption evaluation. Another novel contribution of this review is the development of a qualitative assessment approach for the applicability of various monitoring techniques throughout the stages of CO 2 sequestration projects. This innovative approach has not been reported in the previous literature. Our review was prepared following a scoping review methodology, ensuring the inclusion of the most recent and relevant studies. • CO 2 trapping mechanisms in subsurface formations were reviewed. • Structural trapping provides the most trapping contribution. • Mineral trapping ensures the highest storage security. • Monitoring methods include seismic, borehole, atmospheric, and laboratory methods. [ABSTRACT FROM AUTHOR]

This paper mainly studies the impact of environmental protection tax (EPT) on the illegal emission behaviors of heavy polluting enterprises. Based on the real-time data from the nearest air monitoring points, this paper calculates the day-night difference of PM2.5 to measure whether there are illegal emission behaviors. And, difference in difference method (DID) is used based on the quasi-natural experiment of EPT. First, the baseline DID results show that EPT reduces day-night difference of PM2.5, and inhibits illegal emissions. Second, the influence paths results show that EPT can inhibit illegal emission by increasing innovation, environmental responsibility performance, and environmental penalty cost, and EPT aggravate illegal emissions by increasing environmental costs and environmental corruption. Third, the influence of different pollutant pricing on illegal emissions is further analyzed. The effect of air pollutant pricing on illegal emissions is inhibited first and then promoted, while higher water pollutant pricing will aggravate illegal emissions. This paper provides enlightenment on adjusting EPT policy for local governments to curb illegal emissions, and provides an economic explanation for the differences of illegal pollution discharge in different places. [ABSTRACT FROM AUTHOR]

In cave ecosystems tourists represent moving sources of discontinuous disturbances, able to induce transient system responses whose knowledge is crucial in defining appropriate conservation measures. Here we propose an approach to evaluate the amplitude and scales of cave alterations based on high-resolution air monitoring, through the use of purposely developed low-cost monitoring stations and a consistent analytical framework for information retrieval based on time series analysis. In particular, monitoring stations adopt a modular structure based on physical computing platforms acquiring data through several sensors, with means of preventing humidity damages and guaranteeing their continuous operation. Data are then analyzed using wavelet periodograms and cross-periodograms to extract the scales of tourism-induced alterations. The approach has been exemplified in the Pertosa-Auletta Cave, one of the most important underground environments in Southern Italy, highlighting the development of monitoring stations and the information obtainable with the proposed analytical workflow. Here, 2 monitoring stations acquiring data for 1 year at 1′ sampling time on temperature, relative humidity, CO2, VOCs, and particulate matter were deployed in trails subjected to different levels of tourism. In terms of Pertosa-Auletta Cave air dynamics, the approach allowed estimating the temporal and spatial scales of tourism-induced alterations in the order of minutes and meters, respectively, with parameter-dependent variations. On more general terms, the approach proved reliable and effective, with its modularity and low-cost fostering its straightforward adoption in other underground ecosystems, where it can support the development of tailored management strategies. [ABSTRACT FROM AUTHOR]

Despite the fact that the majority of large industrial enterprises in Omsk comply with environmental legislation, the problem of air pollution is acute in the city. The expansion of the network of air pollution observation posts allows us to improve the quality of determining background pollution, but it is not able to answer the question of who is to blame for excess air pollution. The article presents the development aimed at improving the existing monitoring system, which allows, on the one hand, to determine the level of pollution at any point in the area, and, on the other hand, to quickly respond to complaints from the population about the violation of atmospheric air quality and identify sources of excess emissions in the city.

Air quality monitoring in cities is significant for both human health and environment. Here, an innovative miniaturized active air sampler wearable by free-flying birds is presented. The device integrates a GPS logger and atmospheric calibrated sensors allowing for high spatiotemporal resolution measurements of carbon dioxide (CO2) concentration, barometric pressure, air temperature, and relative humidity. A field campaign, carried out from January to June 2021, involved the repeated release of homing pigeons (Columba livia) from downtown Rome (Italy), to sample the air on their way back to the loft, located in a rural area out of the city. The measurements suggest the importance of green urban areas in decreasing CO2 levels. Moreover, a positive relation between CO2 levels, relative humidity, and air temperature was revealed. In contrast, a negative relation with distance from the point of release, month, and time of day was found. Flight speed and the altitude of flight were related to rising CO2 levels. The easy use of such devices paves the way for the application of miniaturized air samplers to other synanthropic species (i.e., gulls), making birds convenient biomonitors for the urban environment.

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A new passive sampler reinforced with a composite membrane was developed to determine the 8-h ozone (O3) concentration in ambient air. The composite membrane's water absorption capacity and porosity values were found analyzing its surface morphology using Scanning Electron Microscopy (SEM).Ozone adsorption performance of this sampler was tested by a badge-type sampler and automated measurement results. The developed sampler gave results equivalent (R² = 0.85) to those of automated O3 monitors, and its experimental sampling rate was determined to be 55 cm³/min, approximately two times higher than the rate of the badge-type sampler. The detection limit obtained (5.3 μg/m³, 8 h sampling) in the study was adequate for winter-period samplings where in the ozone concentration is low in urban and semi-urban areas. Multimedia sampling results revealed that the results of the developed passive sampler had a high repeatability (RSD < 20%). Passive samplers reinforced with composite membranes were tested by badge-type samplers performing simultaneous samplings in land conditions. Area sampling results indicated that badge-type samplers were not suitable for 8-h area samplings, but tube-type samplers could be used. [ABSTRACT FROM AUTHOR]

In this study, airborne pollen grains in the atmosphere of Dursunbey (Balıkesir, Turkey) were collected using a gravimetric method. The pollen grains were investigated by light microscopy and a total of 6265 pollen grains per cm2 were counted. 42 different pollen types were identified of which 24 belonged to the arboreal plants (86.17% of the annual pollen index) and 18 to non-arboreal plants (13.16% of the annual pollen index). A small portion of the pollens (42 grains, 0.67%) were not identified. The most frequent pollen types, which constituted more than 1% of annual pollen count were regarded as the predominating pollen types for the region. The predominating group was determined to be consisted of pollens of Pinus L. (48.23%), Cupressaceae Rich. ex Bartl./Taxaceae Gray (16.74%), Poaceae Barnhart (8.32%), Quercus L.(5.31%), Acer L. (4.07%), Platanus L. (3.10%), Juglans L. (2.26%), Abies Mill. (1.75%), Plantago L. (1.25%), Amaranthaceae Juss. (1.22%) and Olea europaea L. (1.16%). The highest pollen count was determined in May and it is striking that most of the determined predominant pollen types have previously been reported as main causes of pollinosis.

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in developing countries where it is present in significant quantities. It greatly increases the risk of heart and lung diseases and harms agricultural crops. This study hypothesized that, as a secondary pollutant, ground-level ozone is amenable to 24 h forecasting based on measurements of weather conditions and primary pollutants such as nitrogen oxides and volatile organic compounds. We developed software to analyze hourly records of 12 air pollutants and 5 weather variables over the course of one year in Delhi, India. To determine the best predictive model, eight machine learning algorithms were tuned, trained, tested, and compared using cross-validation with hourly data for a full year. The algorithms, ranked by R2 values, were XGBoost (0.61), Random Forest (0.61), K-Nearest Neighbor Regression (0.55), Support Vector Regression (0.48), Decision Trees (0.43), AdaBoost (0.39), and linear regression (0.39). When trained by separate seasons across five years, the predictive capabilities of all models increased, with a maximum R2 of 0.75 during winter. Bidirectional Long Short-Term Memory was the least accurate model for annual training, but had some of the best predictions for seasonal training. Out of five air quality index categories, the XGBoost model was able to predict the correct category 24 h in advance 90% of the time when trained with full-year data. Separated by season, winter is considerably more predictable (97.3%), followed by post-monsoon (92.8%), monsoon (90.3%), and summer (88.9%). These results show the importance of training machine learning methods with season-specific data sets and comparing a large number of methods for specific applications.

Ammonia(NH3) concentrations were measured at nine locations using passive samplers where the malodor is intense in the central wastewater treatment plant (WWTP) in Konya, Turkey. A badge-type passive sampler suitable for both indoor and outdoor use was developed in the study to sample the NH3 gas released. The detection limit for a two-week exposure period is approximately μ0.34 g/m3. Validation of the passive samplers' performance was carried out by means of an experimental setup located in a laboratory environment. The field performance of the passive samplers was evaluated by analyzing samples simultaneously collected from nine different locations in the Konya WWTP during summer and fall periods. Higher NH3 concentrations were measured in the samples collected in summer than in those collected in fall. The 15-day average NH3 concentrations determined in the air samples collected from the plant inlet, pump unit 1, pump unit 2, bar screen, grit chamber, primary setting, and the sludge thickener (two locations) were determined to vary in the range of 21.58-61.70 ^g/m3 for the samples collected in summer and in the range of 11.10-63.0 μg/m3 for those collected in fall. The highest concentrations were found in the bar screen, prior to the induction of chemical- biological treatment. [ABSTRACT FROM AUTHOR]

The total solar eclipse on August 21, 2017, provided a rare opportunity to observe and test our understanding of atmospheric dynamics and photochemical dependency on solar irradiance. Here, we utilize observations from the continuous monitoring of both inert and photoreactive trace gases near Boulder, Colorado, for contrasting the unique dynamic and photochemical forcings on the eclipse day. The monitoring station saw a 93% solar obstruction during the peak of the eclipse. Eclipse day data are contrasted with the full month's record from this site. The loss of irradiance caused cooling of the surface air by ~3oC, and weakened convective and tur-bulent mixing. This resulted in a buildup of non-reactive gases (methane, volatile organic com-pounds) as well as nitrogen oxides (NO, NO2) in the surface layer. In contrast, ozone (O3) de-clined by ~15 ppb during the first part of the eclipse compared to median August diurnal mixing ratios. Similar O3 signatures were observed at a series of network stations along the Northern Colorado Front Range. With the loss of irradiance, the initial ratio of NO/(NO+NO2) of ~0.2 dropped steadily, bottoming out at

Abstract We discuss a calibration method for imaging atmospheric Cherenkov telescope arrays, based on the detection of cosmic rays. The focus lies on the monitoring of transmission of Cherenkov light in the atmosphere and on the relative calibration of telescope optical throughput efficiencies. We present an approach that addresses both issues by surveying and comparing trigger rates of telescopes in a stereoscopic configuration. A Monte Carlo feasibility study was conducted to explore dependencies of stereo trigger rates on the array layout and observing conditions of the Cherenkov Telescope Array (CTA). Analytical expressions for most of these dependencies have been found and implemented in an extension of the method of the Cherenkov Transparency Coefficient (CTC). In the investigated examples, the resolution of the method for the atmospheric and array calibration has been shown to be 4% and 4–7%, respectively. [ABSTRACT FROM AUTHOR]

TomoSim comes as part of project ATMOS, a miniaturised Differential Optical Absorption Spectroscopy (DOAS) tomographic atmospheric evaluation device, designed to fit a small drone. During the development of the project, it became necessary to write a simulation tool for system validation. TomoSim is the answer to this problem. The software has two main goals: to mathematically validate the tomographic acquisition method; and to allow some adjustments to the system before reaching final product stages. This measurement strategy was based on a drone performing a sequential trajectory and gathering projections arranged in fan beams, before using some classical tomographic methods to reconstruct a spectral image. The team tested three different reconstruction algorithms, all of which were able to produce an image, validating the team’s initial assumptions regarding the trajectory and acquisition strategy. All algorithms were assessed on their computational performance and their ability for reconstructing spectral “images”, using two phantoms, one of which custom made for this purpose. In the end, the team was also able to uncover certain limitations of the TomoSim approach that should be addressed before the final stages of the system.

The European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System) operates a global-scale monitoring system for atmospheric trace gases, aerosols and clouds utilising the existing global civil aircraft. This new monitoring infrastructure builds on the heritage of the former research projects MOZAIC (Measurement of Ozone and Water Vapour on Airbus In-service Aircraft) and CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container). CARIBIC continues within IAGOS and acts as an important airborne measurement reference standard within the wider IAGOS fleet. IAGOS is a major contributor to the in-situ component of the Copernicus Atmosphere Monitoring Service (CAMS), the successor to the Global Monitoring for the Environment and Security – Atmospheric Service, and is providing data for users in science, weather services and atmospherically relevant policy. IAGOS is unique in collecting regular in-situ observations of reactive gases, greenhouse gases and aerosol concentrations in the upper troposphere and lowermost stratosphere (UTLS) at high spatial resolution. It also provides routine vertical profiles of these species in the troposphere over continental sites or regions, many of which are undersampled by other networks or sampling studies, particularly in Africa, Southeast Asia and South America. In combination with MOZAIC and CARIBIC, IAGOS has provided long-term observations of atmospheric chemical composition in the UTLS since 1994. The longest time series are 20 yr of temperature, H2O and O3, and 9–15 yr of aerosols, CO, NO y , CO2, CH4, N2O, SF6, Hg, acetone, ~30 HFCs and ~20 non-methane hydrocarbons. Among the scientific highlights which have emerged from these data sets are observations of extreme concentrations of O3 and CO over the Pacific basin that have never or rarely been recorded over the Atlantic region for the past 12 yr; detailed information on the temporal and regional distributions of O3, CO, H2O, NO y and aerosol particles in the UTLS, including the impacts of cross-tropopause transport, deep convection and lightning on the distribution of these species; characterisation of ice-supersaturated regions in the UTLS; and finally, improved understanding of the spatial distribution of upper tropospheric humidity including the finding that the UTLS is much more humid than previously assumed.

In this study, airborne pollen grains in the atmosphere of Dursunbey (Balıkesir, Turkey) were collected using a gravimetric method. The pollen grains were investigated by light microscopy and a total of 6265 pollen grains per cm2 were counted. 42 different pollen types were identified of which 24 belonged to the arboreal plants (86.17% of the annual pollen index) and 18 to non-arboreal plants (13.16% of the annual pollen index). A small portion of the pollens (42 grains, 0.67%) were not identified. The most frequent pollen types, which constituted more than 1% of annual pollen count were regarded as the predominating pollen types for the region. The predominating group was determined to be consisted of pollens of Pinus L. (48.23%), Cupressaceae Rich. ex Bartl./Taxaceae Gray (16.74%), Poaceae Barnhart (8.32%), Quercus L.(5.31%), Acer L. (4.07%), Platanus L. (3.10%), Juglans L. (2.26%), Abies Mill. (1.75%), Plantago L. (1.25%), Amaranthaceae Juss. (1.22%) and Olea europaea L. (1.16%). The highest pollen count was determined in May and it is striking that most of the determined predominant pollen types have previously been reported as main causes of pollinosis. [ABSTRACT FROM AUTHOR]