Trace Gas Concentrations Research Articles

Total OH Reactivity Measurements in a Suburban Site of Shanghai

AbstractTotal hydroxyl radicals (OH) reactivity, as a measure of the OH total loss rate and the significance of atmospheric oxidation, is broadly used to evaluate the OH budget in the atmosphere. Here, measurements of the total OH reactivity were performed at a suburban air quality monitoring supersite (Dianshan Lake) of Shanghai, between 1 August and 15 September, 2020, using the Comparative Reactivity Method. The measured total OH reactivity ranged from 13.9 to 107.4 s−1 with an average of 38.4 s−1. Meanwhile, the calculated total OH reactivity varied between 8.9 and 84.4 s−1 from concentrations of atmospheric trace gases measured by multiple in‐situ techniques including an online gas chromatograph equipped with mass spectrometry and flame ionization detection (GC‐MS/FID) and two proton‐transfer‐reaction time‐of‐flight mass spectrometers (PTR‐ToF‐MSs). A 12.1% missing OH reactivity was evident from the comparison between the measured and calculated total OH reactivities. Inorganic trace gases, methane, and 54 observed Photochemical Assessment Monitoring Station compounds detected by GC‐MS/FID, accounted for 25.7%, 1.3%, and 10%, respectively, of the calculated total OH reactivity. In addition, 292 species detected by PTR‐ToF‐MSs contributed the rest 63%. The top 10 VOC contributors to the measured total OH reactivity were C5H8, CH2O, C2H4O, C6H6O, C4H8O, C3H6O, C10H16, C5H10O, C5H8O2, and C8H10, respectively, whose total contribution reached 42%. Correlation analysis for the missing OH reactivity suggests that primary biogenic VOCs could be a potential source for the missing OH reactivity during the daytime, and that secondary oxidation products might also be connected to the missing OH reactivity.

Traffic, transport, and vegetation drive VOC concentrations in a major urban area in Texas

The population of Texas has increased rapidly in the past decade. The San Antonio Field Study (SAFS) was designed to investigate ozone (O3) production and precursors in this rapidly changing, sprawling metropolitan area. There are still many questions regarding the sources and chemistry of volatile organic compounds (VOCs) in urban areas like San Antonio which are affected by a complex mixture of industry, traffic, biogenic sources and transported pollutants. The goal of the SAFS campaign in May 2017 was to measure inorganic trace gases, VOCs, methane (CH4), and ethane (C2H6). The SAFS field design included two sites to better assess air quality across the metro area: an urban site (Traveler's World; TW) and a downwind/suburban site (University of Texas at San Antonio; UTSA). The results indicated that acetone (2.52 ± 1.17 and 2.39 ± 1.27 ppbv), acetaldehyde (1.45 ± 1.02 and 0.93 ± 0.45 ppbv) and isoprene (0.64 ± 0.49 and 1.21 ± 0.85 ppbv; TW and UTSA, respectively) were the VOCs with the highest concentrations. Additionally, positive matrix factorization showed three dominant factors of VOC emissions: biogenic, aged urban mixed source, and acetone. Methyl vinyl ketone and methacrolein (MVK + MACR) exhibited contributions from both secondary photooxidation of isoprene and direct emissions from traffic. The C2H6:CH4 demonstrated potential influence of oil and gas activities in San Antonio. Moreover, the high O3 days during the campaign were in the NOx-limited O3 formation regime and were preceded by evening peaks in select VOCs, NOx and CO. Overall, quantification of the concentration and trends of VOCs and trace gases in a major city in Texas offers vital information for general air quality management and supports strategies for reducing O3 pollution. The SAFS campaign VOC results will also add to the growing body of literature on urban sources and concentrations of VOCs in major urban areas.

Tropospheric ozone production and chemical regime analysis during the COVID-19 lockdown over Europe

Abstract. The COVID-19 (coronavirus disease 2019) European lockdowns have led to a significant reduction in the emissions of primary pollutants such as NO (nitric oxide) and NO2 (nitrogen dioxide). As most photochemical processes are related to nitrogen oxide (NOx≡ NO + NO2) chemistry, this event has presented an exceptional opportunity to investigate its effects on air quality and secondary pollutants, such as tropospheric ozone (O3). In this study, we present the effects of the COVID-19 lockdown on atmospheric trace gas concentrations, net ozone production rates (NOPRs) and the dominant chemical regime throughout the troposphere based on three different research aircraft campaigns across Europe. These are the UTOPIHAN (Upper Tropospheric Ozone: Processes Involving HOx and NOx) campaigns in 2003 and 2004, the HOOVER (HOx over Europe) campaigns in 2006 and 2007, and the BLUESKY campaign in 2020, the latter performed during the COVID-19 lockdown. We present in situ observations and simulation results from the ECHAM5 (fifth-generation European Centre Hamburg general circulation model, version 5.3.02)/MESSy2 (second-generation Modular Earth Submodel System, version 2.54.0) Atmospheric Chemistry (EMAC), model which allows for scenario calculations with business-as-usual emissions during the BLUESKY campaign, referred to as the “no-lockdown scenario”. We show that the COVID-19 lockdown reduced NO and NO2 mixing ratios in the upper troposphere by around 55 % compared to the no-lockdown scenario due to reduced air traffic. O3 production and loss terms reflected this reduction with a deceleration in O3 cycling due to reduced mixing ratios of NOx, while NOPRs were largely unaffected. We also study the role of methyl peroxyradicals forming HCHO (αCH3O2) to show that the COVID-19 lockdown shifted the chemistry in the upper-troposphere–tropopause region to a NOx-limited regime during BLUESKY. In comparison, we find a volatile organic compound (VOC)-limited regime to be dominant during UTOPIHAN.

Air Quality during the COVID–19 Lockdown and Unlock Periods in India Analyzed Using Satellite and Ground-based Measurements

A nationwide lockdown was imposed in India from 24 March 2020 to 31 May 2020 to contain the spread of COVID-19. The lockdown has changed the atmospheric pollution across the continents. Here, we analyze the changes in two most important air quality related trace gases, nitrogen dioxide (NO2) and tropospheric ozone (O3) from satellite and surface observations, during the lockdown (April–May 2020) and unlock periods (June–September 2020) in India, to examine the baseline emissions when anthropogenic sources were significantly reduced. We use the Bayesian statistics to find the changes in these trace gas concentrations in different time periods. There is a strong reduction in NO2 during the lockdown as public transport and industries were shut during that period. The largest changes are found in IGP (Indo-Gangetic Plain), and industrial and mining areas in Eastern India. The changes are small in the hilly regions, where the concentrations of these trace gases are also very small (0–1 × 1015 molec./cm2). In addition, a corresponding increase in the concentrations of tropospheric O3 is observed during the period. The analyses over cities show that there is a large decrease in NO2 in Delhi (36%), Bangalore (21%) and Ahmedabad (21%). As the lockdown restrictions were eased during the unlock period, the concentrations of NO2 gradually increased and ozone deceased in most regions. Therefore, this study suggests that pollution control measures should be prioritized, ensuring strict regulations to control the source of anthropogenic pollutants, particularly from the transport and industrial sectors.Highlights• Most cities show a reduction up to 15% of NO2 during the lockdown• The unlock periods show again an increase of about 40–50% in NO2• An increase in tropospheric O3 is observed together with the decrease in NO2Supplementary InformationThe online version contains supplementary material available at 10.1007/s40710-022-00585-9.

The climate roles of H2 O and CO2 from longwave absorption

In search for reproducibility of the results from sophisticated scientific research, the present work focuses on the longwave absorption in the atmosphere. It is found that the variability of Earth’s surface temperature follows a near-proportional relationship between longwave absorption and the atmospheric trace gas concentrations of water vapor and CO2 . Furthermore, estimates are attempted on the CO2 V/R-T (vibrational/rotational-totranslational) energy transfer as a dominant heating process.

Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 1: Synthetic dataset for validation of trace gas retrieval algorithms

Abstract. Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data, and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering. In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC (Monte Carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres). The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMFs) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos. Two cloud setups are considered: the first includes simple box clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical of central Europe such as shallow cumulus, convective cloud cells, cirrus and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically. Along with the dataset, the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analysed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %. The dataset is available for the scientific community to assess the behaviour of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.

Soil surface flux measurements are a reliable means for assessing fugitive gas migration across soils and seasons

As oil and gas wells age and the number of wells drilled increases to meet demand, we may see more instances of fugitive soil gas migration (GM) and associated methane (CH4) emissions. Due to the immense spatiotemporal variability of soils and uncertainty in measurement practice, the detection and quantification of GM emissions is a challenge. Two common measurement techniques include the shallow in-soil gas concentration approach and soil surface flux measurements using flux chambers. In this numerical modeling study, both methods were compared to determine how soil texture, environmental conditions (water content, temperature), and CH4 leak rates into the soil profile influenced in-soil CH4 concentration and surface CH4 flux rates. We observed that in-soil CH4 concentration was strongly controlled by soil texture and environmental conditions, whereas surface CH4 flux rates were far less sensitive to those same parameters. Flux measurements were more useful for determining severity of the CH4 leak into the soil and allowed us to differentiate between leak and nonleak scenarios in soils with biological CH4 production which could complicate a GM assessment. We also evaluated field measurements of carbon dioxide from an enhanced oil recovery site to demonstrate how seasonal conditions can influence concentrations of trace gases in shallow soil. Based on our model results and supplemental field measurements, we propose that flux chamber measurements present a more reliable tool to assess the incidence and severity of fugitive GM.

Large Eddy simulation of tracer gas dispersion in a cavity

This paper assesses the prediction of inert tracer gas dispersion within a cavity of height (H) 1.0 m, and unity aspect ratio, using large Eddy simulation (LES). The flow Reynolds number was 67 000, based on the freestream velocity and cavity height. The flow upstream of the cavity was laminar, producing a cavity shear layer which underwent a transition to turbulence over the cavity. Three distinct meshes are used, with grid spacings of (coarse), (intermediate), and (fine) respectively. The Smagorinsky, WALE, and Germano-Lilly subgrid-scale models are used on each grid to quantify the effects of subgrid-scale modelling on the simulated flow. Coarsening the grid led to small changes in the predicted velocity field, and to substantial over-prediction of the tracer gas concentration statistics. Quantitative metric analysis of the tracer gas statistics showed that the coarse grid simulations yielded results outside of acceptable tolerances, while the intermediate and fine grids produced acceptable output. Interrogation of the fluid dynamics present in each simulation showed that the evolution of the cavity shear layer is heavily influenced by the grid and subgrid scale model. On the coarse and intermediate grids the development of the shear layer is delayed, inhibiting the entrainment and mixing of the tracer gas into the shear layer, reducing the removal of the tracer gas from the cavity. On the fine grid, the shear layer developed more rapidly, resulting in enhanced removal of the tracer gas from the cavity. Concentration probability density functions showed that the fine grid simulations accurately predicted the range, and the most probable value, of the tracer gas concentration towards both walls of the cavity. The results presented in this paper show that the WALE and Germano-Lilly models may be advantageous over the standard Smagorinsky model for simulations of pollutant dispersion in the urban environment.

The effect of tree planting on traffic pollutant dispersion in an urban street canyon using large eddy simulation with a recycling and rescaling inflow generation method

The influence of various tree planting configurations on tracer gas dispersion in an urban street canyon is studied numerically, using OpenFOAM Large Eddy Simulation (LES). A recycling and rescaling turbulent inflow generation method is implemented and validated against a canonical backwards-facing step case. The street canyon simulations are based on the CODASC experiments, where the tracer gas was emitted from line sources at street level. The effect of tree stand density on the pollutant dispersion is studied for the first time using LES. Performance metric analysis of the CODASC simulations shows that the influence of tree crown porosity, and tree stand density, on the concentration field within the canyon can be captured by LES. The simulations show that tree crowns reduce the effectiveness of the canyon vortex at ventilating the street, and enhance the mean tracer gas concentration at pedestrian level on the leeward wall. A novel feature of the research arises from concentration probability density functions at pedestrian height in the canyon. Pedestrians can be exposed to pollutant concentrations almost three times the mean value at the leeward wall. The results have implications for urban greening strategies in city streets with heavy traffic.

Experimental evaluation of the airborne infection probability in ventilated office room at different supply airflow rates

The impact of the supplied airflow rate on the distribution and exposure of exhaled airborne pathogens in a room with mixing ventilation was studied. Experiments were conducted in a field laboratory at three supply airflow rates: 20, 40, 60 L/s. Two breathing thermal manikins were used to resemble infected and susceptible occupants. Nitrous oxide (N2O) was dosed into the air exhaled by the infected manikin to simulate the emission of infectious aerosols. N2O concentration was measured in the air inhaled by the susceptible manikin. The measured data were used to calculate infection probability by modified Wells-Riley model. The highest infection probability of 4.3-5.1%, obtained in the case of 20 L/s, decreased with increasing the supply airflow rate. The decrease slowed with the increase of the supply flow. The calculated infection probability based on the tracer gas concentration in the inhaled air of the exposed manikin was in all studied cases higher than the infection probability obtained in the occupied zone and the exhaust. The infection probability based on the tracer gas concentration in the inhaled air of the exposed manikin was up to 65% higher than the infection probability calculated by the Wells-Riley method, which assumes complete room air mixing.

Long-term measurements of aerosol optical properties and radiative forcing (2011-2017) over Central Amazonia

The Amazon region is one of the most pristine continental areas whose concentrations of atmospheric trace gases and aerosol particles are very low, mainly in the wet season. This study provides observational results of aerosol optical and radiative characteristics in situ as well as atmospheric columnar at a pristine forest in Central Amazonia. Spectral variation of the aerosol properties (aerosol optical depth [AOD], single scattering albedo [SSA], and asymmetry parameter [AP]) was evaluated using the AErosol RObotic NETwork (AERONET) data. The SSA values under natural atmospheric column conditions (AERONET) were compared to the SSA values calculated with in situ measurements. The values of shortwave aerosol radiative forcing (SWARF) on top of the atmosphere (TOA) and the surface (SUR) were estimated using the SBDART model and were validated with the AERONET values with regression analysis. SWARF had a high correlation to TOA (0.97) and SUR (0.92), including dry and wet seasons. Monthly, seasonal and annual mean values of SWARFTOA and SWARFSUR were negative while SWARFATM values were positive. SWARFTOA was –9.18 ± 2.80 W m–2 and SWARFSUR was –20.77 ± 5.04 W m–2 in the dry season, inducing a heating rate (HR) of 0.37 ± 0.13 K.day–1. This study showed that, for a long series of measurements, the effects caused by aerosols on the radiative flux in the pristine forest of Central Amazonia were of the order of SWARFTOA of –3.66 ± 1.59 W m–2 and SWARFSUR of –11.86 ± 2.35 W m–2 during the wet season

Optimization of distribution of permanent magnetrings for Faraday rotation spectroscopy

Faraday rotation spectroscopy (FRS) is generally used to detect the concentrations of various paramagnetic trace gases because of its high detection sensitivity, zero background noise and the ability to get rid of the interference of diamagnetic materials effectively. In most of FRS technologies, the used electromagnetic fields are produced by coils, thereby triggering off some problems such as high energy consumption and excessive heat generation. Thus the modeling and the simulation study of spatial magnetic field distribution based on the combined ring permanent magnets are carried out to establish an axially distributed homogeneous magnetic field and provide a permanent magnet-based homogeneous magnetic field along the optical axis for FRS measurement. In this simulation, the method of finite element mesh division is adopted based on basic electromagnetic relationship in Maxwell equations. By the simulation study of the magnetic field distribution of the actual Nd-Fe-B permanent magnet magnetic ring array, the physical model proves to be reliable. Basically, three methods of optimizing the permanent magnetic ring arrays. i.e. single ideal value optimization method, the multi-part single objective optimization method, and the gradient optimization method, are proposed. The single ideal value optimization method and the multiple ideal value optimization method are used to realize the optimization of magnets. However, by analyzing the two methods, it is clear that compared with the single ideal value optimization method, the multiple ideal value optimization method in which the whole region is divided into several small parts can achieve good uniformity of permanent magnet array. In this way, the third method, i.e. the gradient optimization method is used to realize the construction of a homogeneous magnetic field with a uniform central axis magnetic flux density distribution used for FRS. Finally, the standard magnetic field uniformity for measuring the quality of magnet field is suggested, and through the calculation and evaluation of the magnetic field uniformity, the optimization effects of different optimization methods are analyzed and compared with each other. And the final results about realizing a homogeneous magnetic field provide a reference for developing the FRS equipment based on permanent magnets.

Unsupervised Sparse Unmixing of Atmospheric Trace Gases From Hyperspectral Satellite Data

In this letter, a new approach for the retrieval of the vertical column concentrations of trace gases from hyperspectral satellite observations, is proposed. The main idea is to perform a linear spectral unmixing by estimating the abundances of trace gases spectral signatures in each mixed pixel collected by an imaging spectrometer in the ultraviolet region. To this aim, the sparse nature of the measurements is brought to light and the compressive sensing paradigm is applied to estimate the concentrations of the gases' endemembers given by an a priori wide spectral library, including reference cross sections measured at different temperatures and pressures at the same time. The proposed approach has been experimentally assessed using both simulated and real hyperspectral dataset. Specifically, the experimental analysis relies on the retrieval of sulfur dioxide during volcanic emissions using data collected by the TROPOspheric Monitoring Instrument. To validate the procedure, we also compare the obtained results with the sulfur dioxide total column product based on the differential optical absorption spectroscopy technique and the retrieved concentrations estimated using the blind source separation.

Highly Sensitive Sphere-Tube Coupled Photoacoustic Cell Suitable for Detection of a Variety of Trace Gases: NO2 as an Example

The concentration of trace gases in the atmospheric environment is extremely low, but it has a great impact on the living environment of organisms. Photoacoustic spectroscopy has attracted extensive attention in the field of trace gas detection because of its high sensitivity, good selectivity, and fast response. As the core of a photoacoustic detection setup, the photoacoustic cell has a significant impact on detection performance. To improve detection sensitivity, a sphere-tube coupled photoacoustic cell (STPAC) was developed, which was mainly composed of a diffuse-reflective sphere and an acoustic resonance tube. Modulated light was reflected multiple times in the sphere to increase optical path, and photoacoustic (PA) signals were further amplified by the tube. Based on STPAC, a PA gas detection setup was built with a laser diode (LD) at 450 nm as the light source. The experimental results showed that the minimum detection limit (noise equivalent concentration, NEC) of NO2 was ~0.7 parts per billion (ppb). Compared with the T-type PA cell (TPAC) in which the modulated light passed through the sphere, the signal-to-noise ratio of STPAC was increased by an order of magnitude at the same concentration of the NO2 sample.

Photochemical method for removing methane interference for improved gas analysis

Abstract. The development of laser spectroscopy has made it possible to measure minute changes in the concentrations of trace gases and their isotopic analogs. These single or even multiply substituted species occur at ratios from percent to below parts per million and contain important information concerning trace gas sources and transformations. Due to their low abundance, minimizing spectral interference from other gases in a mixture is essential. Options including traps and membranes are available to remove many specific impurities. Methods for removing CH4, however, are extremely limited as methane has low reactivity and adsorbs poorly to most materials. Here we demonstrate a novel method for CH4 removal via chlorine-initiated oxidation. Our motivation in developing the technique was to overcome methane interference in measurements of N2O isotopic analogs when using a cavity ring-down spectrometer. We describe the design and validation of a proof-of-concept device and a kinetic model to predict the dependence of the methane removal efficiency on the methane concentration [CH4], chlorine photolysis rate JCl2, chlorine concentration [Cl2] and residence time tR. The model was validated by comparison to experimental data and then used to predict the possible formation of troublesome side products and by-products including CCl4 and HCl. The removal of methane could be maintained with a peak removal efficiency >98 % for ambient levels of methane at a flow rate of 7.5 mL min−1 with [Cl2] at 50 ppm. These tests show that our method is a viable option for continuous methane scrubbing. Additional measures may be needed to avoid complications due to the introduction of Cl2 and formation of HCl. Note that the method will also oxidize most other common volatile organic compounds. The system was tested in combination with a cavity ring-down methane spectrometer, and the developed method was shown to be successful at removing methane interference.

Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI.

Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO2. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO2 reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.

Preparation of Dr\xe4ger Atlan A350 and General Electric Healthcare Carestation 650 anesthesia workstations for malignant hyperthermia susceptible patients

BackgroundPatients at risk of malignant hyperthermia need trigger-free anesthesia. Therefore, anesthesia machines prepared for safe use in predisposed patients should be free of volatile anesthetics. The washout time depends on the composition of rubber and plastic in the anesthesia machine. Therefore, new anesthesia machines should be evaluated regarding the safe preparation for trigger-free anesthesia. This study investigates wash out procedures of volatile anesthetics for two new anesthetic workstations: Dräger Atlan A350 and General Electric Healthcare (GE) Carestation 650 and compare it with preparation using activated charcoal filters (ACF).MethodsA Dräger Atlan and a Carestation 650 were contaminated with 4% sevoflurane for 90 min. The machines were decontaminated with method (M1): using ACF, method 2 (M2): a wash out method that included exchange of internal parts, breathing circuits and soda lime canister followed by ventilating a test lung using a preliminary protocol provided by Dräger or method 3 (M3): a universal wash out instruction of GE, method 4 (M4): M3 plus exchange of breathing system and bellows. Decontamination was followed by a simulated trigger-free ventilation. All experiments were repeated with 8% desflurane contaminated machines. Volatile anesthetics were detected with a closed gas loop high-resolution ion mobility spectrometer with gas chromatographic pre-separation attached to the bacterial filter of the breathing circuits. Primary outcome was time until < 5 ppm of volatile anesthetics and total preparation time.ResultsTime to < 5 ppm for the Atlan was 17 min (desflurane) and 50 min (sevoflurane), wash out continued for a total of 60 min according to protocol resulting in a total preparation time of 96-122 min. The Carestation needed 66 min (desflurane) and 24 min (sevoflurane) which could be abbreviated to 24 min (desflurane) if breathing system and bellows were changed. Total preparation time was 30-73 min. When using active charcoal filters time to < 5 ppm was 0 min for both machines, and total preparation time < 5 min.ConclusionBoth wash out protocols resulted in a significant reduction of trace gas concentrations. However, due to the complexity of the protocols and prolonged total preparation time, feasibility in clinical practice remains questionable. Especially when time is limited preparation of the anesthetic machines using ACF remain superior.

Methane in Zackenberg Valley, NE Greenland: multidecadal growing season fluxes of a high-Arctic tundra

Abstract. The carbon balance of high-latitude terrestrial ecosystems plays an essential role in the atmospheric concentration of trace gases, including carbon dioxide (CO2) and methane (CH4). Increasing atmospheric methane levels have contributed to ∼ 20 % of the observed global warming since the pre-industrial era. Rising temperatures in the Arctic are expected to promote the release of methane from Arctic ecosystems. Still, existing methane flux measurement efforts are sparse and highly scattered, and further attempts to assess the landscape fluxes over multiple years are needed. Here we combine multi-year July–August methane flux monitoring (2006–2019) from automated flux chambers in the central fens of Zackenberg Valley, northeast Greenland, with several flux measurement campaigns on the most common vegetation types in the valley to estimate the landscape fluxes over 14 years. Methane fluxes based on manual chamber measurements are available from campaigns in 1997, 1999–2000, and in shorter periods from 2007–2013 and were summarized in several published studies. The landscape fluxes are calculated for the entire valley floor and a smaller subsection of the valley floor, containing the productive fen area, Rylekærene. When integrated for the valley floor, the estimated July–August landscape fluxes were low compared to the single previous estimate, while the landscape fluxes for Rylekærene were comparable to previous estimates. The valley floor was a net methane source during July–August, with estimated mean methane fluxes ranging from 0.18 to 0.67 mg m−2 h−1. The mean methane fluxes in the fen-rich Rylekærene were substantially higher, with fluxes ranging from 0.98 to 3.26 mg m−2 h−1. A 2017–2018 erosion event indicates that some fen and grassland areas in the center of the valley are becoming unstable following pronounced fluvial erosion and a prolonged period of permafrost warming. Although such physical disturbance in the landscape can disrupt the current ecosystem–atmosphere flux patterns, even pronounced future erosion of ice-rich areas is unlikely to impact methane fluxes on a landscape scale significantly. Instead, projected changes in future climate in the valley play a more critical role. The results show that multi-year landscape methane fluxes are highly variable on a landscape scale and stress the need for long-term spatially distributed measurements in the Arctic.

Scaled outdoor experimental analysis of ventilation and interunit dispersion with wind and buoyancy effects in street canyons

Driven by wind and buoyancy effects in the urban environment, ventilation performance and pollutant transmission are highly related to human health. In order to investigate characteristics of the single-sided natural ventilation and interunit dispersion problem, this study conducted scaled outdoor experiments in summer and winter periods in two-dimensional street canyons. Tracer gas method was adopted to predict the ventilation rate and simulate the pollutant dispersion. It was found the ventilation performance of windward and leeward rooms showed different trends with wind velocities. Archimedes number Ar was used to examine the interactions of the buoyancy and the wind forces. It revealed that the non-dimensional ventilation rates of all rooms were generally smaller than the results of buoyancy effect only. It indicates that interactions between the buoyancy and wind effects were destructive, which reduced the ventilation rates. The interunit dispersion characteristics with the wind effect were highly dependent on source locations. The results of the tracer gas concentrations of the reentered rooms were not showing simple increasing or decreasing trends. This study provides authentic and instant airflow and pollutant dispersion information in an urban environment. The dataset of this experiment can offer validations for further numerical simulations.

Pilot Study of Air Quality during Pre and Post COVID-19 Lockdown: An Inadvertent Assistance to the Environment

The main object of this study was to examine the levels of air quality in Karachi, Pakistan, before and during the 1st, 2nd and 3rd wave of lockdown period levied to control the spread of a novel coronavirus (COVID-19) in the environment of Karachi city. Momentous improvement in the air quality has been found during the ‘Lockdown’ being implemented due to the Corona Virus Disease (COVID -19) pandemic in Karachi city. Concentrations of trace gases and particulate matter were used to calculate the results according to the criteria of USEPA. We have analyzed data from fourteen different locations along the busy roads in commercial, residential and industrial areas of Karachi during the period of lockdown. Data were compared to the before lockdown (BL) and during the complete lockdown (CL 1stwave), smart lockdown (SL 2nd wave) and again complete lockdown (CL-2 3rd wave) of COVID pandemic. The results show drastic reductions in criteria pollutants (PM10, CO, SO2 and NOx) concentrations in all the selected area during lockdown period. This study explained the level of air quality and its relation to prepare alternative plans to mitigate the air pollutants and to improve the environment of urban areas.