Search

Laboratory incubations and field measurements have provided valuable information on the production of green-house gases. However, information about the effects of pre-incubation and closure time on soil-induced gas emissions is currently limited. Our findings showed that different closure times and pre-incubation times altered gas emissions from incubated soils. A standardised procedure to investigate gas fluxes is needed for application to other studied soils. Different sampling times for greenhouse gas measurements have been proposed in many incubation studies. Little is known about effects of closure time on denitrification and nitrification rates from incubation experiments. The objectives of this study were to analyse greenhouse gas (carbon dioxide, methane and nitrous oxide) production from different soils with different times of lid closure and to assess effects of different activation times (defined as additional pre-incubation periods before incubation experiments) on gas emissions from soils. Forty grams of air-dried soil samples (depth 0-10 cm) were incubated in 125-mL jars at 25[degrees]C with the addition of glucose and nitrate. The first experiment measured greenhouse gas fluxes at different lid-closure times (40, 80, 120 and 1440 min). The second experiment assessed the effects of different durations of soil activation (0.7, 1.3, 2 and 24 h) on gas emissions. Both were conducted with a completely randomised design, with three replicates per treatment. Our findings showed closure time 2h may cause an underestimate of greenhouse gas emissions. Lengthening activation times resulted in different emission rates consistent with soil characteristics. To measure gas fluxes based on linear regression would require four or five sampling points and sampling at a 20-min interval over a maximum period of 80 min for estimating gas fluxes from soil. Because pre-incubation time is critical and a driving factor in the measurement of soil-induced gas emissions, a standardised procedure to quantify gas fluxes is needed for application to other soils. Additional keywords: amendment, greenhouse gas emissions, incubation, nitrogen cycle, soil activation., Introduction The most important greenhouse gases (GHGs) contributing to global warming from the biosphere are carbon dioxide (C[O.sub.2]), nitrous oxide ([N.sub.2]O) and methane (C[H.sub.4]). Soils are a major terrestrial source [...]

Water-based lubricants (WBLs) have been at the forefront of recent research, due to the abundant availability of water at a low cost. However, in metallic tribo-systems, WBLs often exhibit poor performance compared to petroleum-based lubricants. Research and development indicate that nano-additives improve the lubrication performance of water. Some of these additives could be categorized as solid nanoparticles, ionic liquids, and bio-based oils. These additives improve the tribological properties and help to reduce friction, wear, and corrosion. This review explored different water-based lubricant additives and summarized their properties and performances. Viscosity, density, wettability, and solubility are discussed to determine the viability of using water-based nano-lubricants compared to petroleum-based lubricants for reducing friction and wear in machining. Water-based liquid lubricants also have environmental benefits over petroleum-based lubricants. Further research is needed to understand and optimize water-based lubrication for tribological systems completely.

There is interest in and significant uncertainty about the emissions of oxygenated volatile organic compounds (oxVOCs) from vegetation to the atmosphere. Here, we measured the fluxes of selected oxVOCs from an alfalfa field, before, during, and after cutting, using a combination of disjunct eddy covariance and proton‐transfer‐reaction mass spectrometry. Over the course of 1 day a significant methanol flux of 4 mg m−2 h−1 was observed from undisturbed alfalfa with a maximum at 0800 LT, possibly caused by the evaporation of dew. A smaller release of hexenals during this day (0.04 mg m−2 h−1) demonstrated the sensitivity of the method. Other results suggested that acetaldehyde and acetone were released in the afternoon but were lost by dry deposition in the evening and morning; deposition velocities were estimated to be 0.2 cm s−1 (acetaldehyde) and 0.09 cm s−1 (acetone). After the alfalfa was cut the emissions of methanol, acetaldehyde, acetone, and hexenals were significantly enhanced and remained high for three days during which the alfalfa was drying. After a rainstorm the oxVOC emissions from the cut, wet alfalfa increased even more. Nighttime measurements yielded low oxVOC fluxes in general, but the high variability of the concentrations during the night and the high degree of correlation between different oxVOCs suggest that the nighttime releases of oxVOCs from alfalfa were nonzero. This work suggests that the global source of oxVOCs due to the production of hay is of minor importance. The emission flux of methanol from vegetation during the growing season may be very large on a global basis.

Inverse modelling is a useful tool for retrieving CH4 fluxes; however, evaluation of the applied chemical transport model is an important step before using the inverted emissions. For inversions using column data one concern is how well the model represents stratospheric and tropospheric CH4 when assimilating total column measurements. In this study atmospheric CH4 from three inverse models is compared to FTS (Fourier transform spectrometry), satellite and in situ measurements. Using the FTS measurements the model biases are separated into stratospheric and tropospheric contributions. When averaged over all FTS sites the model bias amplitudes (absolute model to FTS differences) are 7.4 ± 5.1, 6.7 ± 4.8, and 8.1 ± 5.5 ppb in the tropospheric partial column (the column from the surface to the tropopause) for the models TM3, TM5-4DVAR, and LMDz-PYVAR, respectively, and 4.3 ± 9.9, 4.7 ± 9.9, and 6.2 ± 11.2 ppb in the stratospheric partial column (the column from the tropopause to the top of the atmosphere). The model biases in the tropospheric partial column show a latitudinal gradient for all models; however there are no clear latitudinal dependencies for the model biases in the stratospheric partial column visible except with the LMDz-PYVAR model. Comparing modelled and FTS-measured tropospheric column-averaged mole fractions reveals a similar latitudinal gradient in the model biases but comparison with in situ measured mole fractions in the troposphere does not show a latitudinal gradient, which is attributed to the different longitudinal coverage of FTS and in situ measurements. Similarly, a latitudinal pattern exists in model biases in vertical CH4 gradients in the troposphere, which indicates that vertical transport of tropospheric CH4 is not represented correctly in the models.

Many applications in atmospheric science involve ill-posed inverse problems. A crucial component of many inverse problems is the proper formulation of a priori knowledge about the unknown parameters. In most cases, this knowledge is expressed as a Gaussian prior. This formulation often performs well at capturing smoothed, large-scale processes but is often ill equipped to capture localized structures like large point sources or localized hot spots. Over the last decade, scientists from a diverse array of applied mathematics and engineering fields have developed sparse reconstruction techniques to identify localized structures. In this study, we present a new regularization approach for ill-posed inverse problems in atmospheric science. It is based on Tikhonov regularization with sparsity constraint and allows bounds on the parameters. We enforce sparsity using a dictionary representation system. We analyze its performance in an atmospheric inverse modeling scenario by estimating anthropogenic US methane (CH4) emissions from simulated atmospheric measurements. Different measures indicate that our sparse reconstruction approach is better able to capture large point sources or localized hot spots than other methods commonly used in atmospheric inversions. It captures the overall signal equally well but adds details on the grid scale. This feature can be of value for any inverse problem with point or spatially discrete sources. We show an example for source estimation of synthetic methane emissions from the Barnett shale formation.

VOCs related to oil and gas extraction operations in the United States were measured by H3O+ chemical ionization time-of-flight mass spectrometry (H3O+ ToF-CIMS/PTR-ToF-MS) from aircraft during the Shale Oil and Natural Gas Nexus (SONGNEX) campaign in March–April 2015. This work presents an overview of major VOC species measured in nine oil- and gas-producing regions, and a more detailed analysis of H3O+ ToF-CIMS measurements in the Permian Basin within Texas and New Mexico. Mass spectra are dominated by small photochemically produced oxygenates and compounds typically found in crude oil: aromatics, cyclic alkanes, and alkanes. Mixing ratios of aromatics were frequently as high as those measured downwind of large urban areas. In the Permian, the H3O+ ToF-CIMS measured a number of underexplored or previously unreported species, including aromatic and cycloalkane oxidation products, nitrogen heterocycles including pyrrole (C4H5N) and pyrroline (C4H7N), H2S, and a diamondoid (adamantane) or unusual monoterpene. We additionally assess the specificity of a number of ion masses resulting from H3O+ ion chemistry previously reported in the literature, including several new or alternate interpretations.

Abstract Background Gastric cancer is the fourth most common cancer and the second leading cause of cancer death worldwide. In order to understand the genetic background, we sequenced the whole exome and the whole genome of one microsatellite stable as well as one microsatellite unstable tumor and the matched healthy tissue on two different NGS platforms. We here aimed to provide a comparative approach for individual clinical tumor sequencing and annotation using different sequencing technologies and mutation calling algorithms. Results We applied a population-based whole genome resource as a novel pathway-based filter for interpretation of genomic alterations from single nucleotide variations (SNV), indels, and large structural variations. In addition to a comparison with tumor genome database resources and a filtering approach using data from the 1000 Genomes Project, we performed pyrosequencing analysis and immunohistochemistry in a large cohort of 428 independent gastric cancer cases. Conclusion We here provide an example comparing the usefulness and potential pitfalls of different technologies for a clinical interpretation of genomic sequence data of individual gastric cancer samples. Using different filtering approaches, we identified a multitude of novel potentially damaging mutations and could show a validated association between a mutation in GNAS and gastric cancer.

Solar absorption spectroscopy in the near infrared has been performed in Ny-Ålesund (78.9° N, 11.9° E) since 2002; however, due to the high latitude of the site, the sun is below the horizon from October to March (polar night) and no solar absorption measurements are possible. Here we present a novel method of retrieving the total column dry-air mole fractions (DMFs) of CO2 and CH4 using moonlight in winter. Measurements have been taken during the polar nights from 2012 to 2016 and are validated with TCCON (Total Carbon Column Observing Network) measurements by solar and lunar absorption measurements on consecutive days and nights during spring and autumn. The complete seasonal cycle of the DMFs of CO2 and CH4 is presented and a precision of up to 0.5 % is achieved. A comparison of solar and lunar measurements on consecutive days during day and night in March 2013 yields non-significant biases of 0. 66 ± 4. 56 ppm for xCO2 and −1. 94 ± 20. 63 ppb for xCH4. Additionally a model comparison has been performed with data from various reanalysis models.

A ground-based high-resolution Fourier transform spectrometer (FTS) station has been established in Hefei, China to remotely measure CO2, CO and other greenhouse gases based on near-infrared solar absorption spectra. Total column measurements of atmospheric CO2 and CO were successfully obtained from July 2014 to April 2016. The spectra collected with an InSb detector in the first year were compared with those collected by an InGaAs detector from July 2015, demonstrating that InGaAs spectra have better signal-to-noise ratios and rms of spectral fitting residuals relative to InSb spectra. Consequently, the measurement precision of the retrieved XCO2 and XCO for InGaAs spectra is superior to InSb spectra, with about 0.04 and 0.09 % for XCO2, and 1.07 and 2.00 % for XCO within clear-sky days respectively. Daily and monthly averages of column-averaged dry air mole fraction of CO2 show a clear seasonal cycle, while the daily and monthly averages of XCO displayed no seasonal variation. Also, we analysed the relationship of the anomalies of XCO and XCO2, found that the correlations are only observable for individual days, and the data under different prevailing wind conditions during the observations displayed weak correlation. The observations based on the high-resolution FTS were also compared with the temporally coinciding measurements taken with a low-resolution solar FTS instrument, the EM27/SUN. Ratioing the daily averaged XCO2 of EM27 and FTS gives an overall calibration factor of 0.996 ± 0.001. We also compared ground-based observations from the Tsukuba TCCON station with our observations, the results showing that the variation in phase and seasonal amplitude of XCO2 are similar to our results, but the variation of XCO in Tsukuba is quite different from our data in Hefei. To further evaluate our retrieved data, we made use of satellite measurements. The direct comparison of our observations with the Greenhouse Gases Observing Satellite (GOSAT) data shows good agreement of daily median XCO2, with a bias of −0.52 ppm and standard deviation of 1.63 ppm. The correlation coefficient (R2) is 0.79 for daily median XCO2 between our FTS and GOSAT observations. Daily median Orbiting Carbon Observatory 2 (OCO-2) data produce a positive bias of 0.81 ppm and standard deviation of 1.73 ppm relative to our ground-based data. Our daily median XCO2 also show strong correlation with OCO-2 data, with correlation coefficient (R2) of 0.83. Although there were a limited number of data during the observations due to instrument downtime and adverse weather, the results confirm the suitability of the observatory for ground-based long-term measurements of greenhouse gases with high precision and accuracy, and fulfil the requirements of the Total Carbon Column Observing Network (TCCON).

NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, XCO2, in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and XCO2 from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 XCO2 retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 XCO2 data quality throughout its mission.

Concentrated animal feeding operations (CAFOs) emit a large number of volatile organic compounds (VOCs) to the atmosphere. In this study, we conducted mobile laboratory measurements of VOCs, methane (CH4) and ammonia (NH3) downwind of dairy cattle, beef cattle, sheep and chicken CAFO facilities in northeastern Colorado using a hydronium ion time-of-flight chemical-ionization mass spectrometer (H3O+ ToF-CIMS), which can detect numerous VOCs. Regional measurements of CAFO emissions in northeastern Colorado were also performed using the NOAA WP-3D aircraft during the Shale Oil and Natural Gas Nexus (SONGNEX) campaign. Alcohols and carboxylic acids dominate VOC concentrations and the reactivity of the VOCs with hydroxyl (OH) radicals. Sulfur-containing and phenolic species provide the largest contributions to the odor activity values and the nitrate radical (NO3) reactivity of VOC emissions, respectively. VOC compositions determined from mobile laboratory and aircraft measurements generally agree well with each other. The high time-resolution mobile measurements allow for the separation of the sources of VOCs from different parts of the operations occurring within the facilities. We show that the emissions of ethanol are primarily associated with feed storage and handling. Based on mobile laboratory measurements, we apply a multivariate regression analysis using NH3 and ethanol as tracers to determine the relative importance of animal-related emissions (animal exhalation and waste) and feed-related emissions (feed storage and handling) for different VOC species. Feed storage and handling contribute significantly to emissions of alcohols, carbonyls, carboxylic acids and sulfur-containing species. Emissions of phenolic species and nitrogen-containing species are predominantly associated with animals and their waste.

Volatile organic compounds were quantified during two aircraft-based field campaigns using highly automated, whole air samplers with expedited post-flight analysis via a new custom-built, field-deployable gas chromatography–mass spectrometry instrument. During flight, air samples were pressurized with a stainless steel bellows compressor into electropolished stainless steel canisters. The air samples were analyzed using a novel gas chromatograph system designed specifically for field use which eliminates the need for liquid nitrogen. Instead, a Stirling cooler is used for cryogenic sample pre-concentration at temperatures as low as −165 °C. The analysis system was fully automated on a 20 min cycle to allow for unattended processing of an entire flight of 72 sample canisters within 30 h, thereby reducing typical sample residence times in the canisters to less than 3 days. The new analytical system is capable of quantifying a wide suite of C2 to C10 organic compounds at part-per-trillion sensitivity. This paper describes the sampling and analysis systems, along with the data analysis procedures which include a new peak-fitting software package for rapid chromatographic data reduction. Instrument sensitivities, uncertainties and system artifacts are presented for 35 trace gas species in canister samples. Comparisons of reported mixing ratios from each field campaign with measurements from other instruments are also presented.

A new approach for eddy covariance flux measurements is developed and applied for trace gas fluxes in the atmospheric surface layer. In disjunct eddy covariance technique, quick samples with a relatively long time interval between them are taken instead of continuously sampling air. This subset of the time series together with vertical wind velocity data at corresponding sampling times can be correlated to give a flux. The disjunct eddy sampling gives more time to analyze the trace gas concentrations and thus makes eddy covariance measurements possible using slower sensors. In this study a proton-transfer-reaction mass spectrometer with response time of about 1 second was used with a disjunct eddy sampler to measure fluxes of volatile organic compounds from an alfalfa field. The measured day-time maximum methanol fluxes ranged from 1 mg m-2 h-1 from uncut alfalfa to 8 mg m-2 h-1 from freshly cut alfalfa. Night-time fluxes were around zero.