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The emissions of volatile organic compounds (VOCs) from volatile chemical products (VCPs) – specifically personal care products, cleaning agents, coatings, adhesives, and pesticides – are emerging as the largest source of petroleum-derived organic carbon in US cities. Previous work has shown that the ambient concentration of markers for most VCP categories correlates strongly with population density, except for VOCs predominantly originating from solvent- and water-borne coatings (e.g., parachlorobenzotrifluoride (PCBTF) and Texanol®, respectively). Instead, these enhancements were dominated by distinct emission events likely driven by industrial usage patterns, such as construction activity. In this work, the headspace of a variety of coating products was analyzed using a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) and a gas chromatography (GC) preseparation front end to identify composition differences for various coating types (e.g., paints, primers, sealers, and stains). Evaporation experiments of several products showed high initial VOC emission rates, and for the length of these experiments, the majority of the VOC mass was emitted during the first few hours following application. The percentage of mass emitted as measured VOCs (<1 % to 83 %) mirrored the VOC content reported by the manufacturer (<5 to 550 g L−1). Ambient and laboratory measurements, usage trends, and ingredients compiled from architectural coatings surveys show that both PCBTF and Texanol account for ∼10 % of the total VOC ingredient sales and, therefore, can be useful tracers for solvent- and water-borne coatings.

The magnitude of termite methane (CH4) emissions is still an uncertain part of the global CH4 budget and current emission estimates are based on limited field studies. We present in situ CH4 emission measurements of termite mounds and termite mound subsamples performed in the Amazon rainforest. Emissions from five termite mounds of the species Neocapritermes brasiliensis were measured by use of a large flux chamber connected to a portable gas analyser measuring CH4 and CO2. In addition, the emissions of mound subsamples were measured, after which the termites were counted so that a termite CH4 and CO2 emission factor could be determined. Mound emissions were found to range between 17.0 and 34.8 nmol mound−1 s−1 for CH4 and between 1.1 and 13.0 µmol mound−1 s−1 for CO2. A termite emission factor of 0.35 µmol CH4 gtermite-1 h−1 was found, which is almost twice as high as the only other reported value for the Amazon. By combining mound emission measurements with the termite emission factor, colony sizes could be estimated, which were found to range between 55–125 thousand individuals. Estimates were similar to literature values, and we therefore propose that this method can be used as a quick non-intrusive method to estimate termite colony size in the field. The role of termites in the ecosystem's CH4 budget was evaluated by use of two approaches. Termite mound emission values were combined with local mound density numbers, leading to an estimate of 0.15–0.71 nmol CH4 m−2 s−1, on average, emitted by termite mounds. In addition, the termite CH4 emission factor from this study was combined with termite biomass numbers, resulting in an estimate of termite-emitted CH4 of ∼1.0 nmol m−2 s−1. Considering the relatively low net CH4 emissions previously measured at this ecosystem, we expect that termites play an important role in the CH4 budget of this terra firme ecosystem.

The NOAA Chemical Sciences Laboratory (CSL) conducted the Southwest Urban NO x and VOCs Experiment (SUNVEx) to study emissions and the role of boundary layer (BL) dynamics and sea-breeze (SB) transitions in the evolution of coastal air quality. The study presented utilizes remote sensing and in situ observations in Pasadena, California. Separate analyses are conducted on the synoptic conditions during ozone (O 3) exceedance (>70 ppb) and non-exceedance (<70 ppb) days, as well as the fine-structure variability of in situ chemistry measurements during BL growth and SB transitions. Diurnal analyses spanning August 2021 revealed a markedly different wind direction during evenings preceding O 3 exceedance (northerly) versus non-exceedance (easterly) days. Increased O 3 occurred simultaneously with warmer and drier conditions, a reduction in winds, and an increase in volatile organic compounds (VOCs) and fine particulate matter (PM 2.5). While the average BL height was lower and surface pressure was higher, the day-to-day variability of these quantities led to an overall weak statistical relationship. Investigations focused on the fine-structure variability of in situ chemistry measurements superimposed on background trends were conducted using a novel multivariate spectral coherence mapping (MSCM) technique that combined the spectral structure of two or more independent measurements through a wavelet analysis as reported by maximum-normalized scaleograms. A case study was chosen to illustrate the MSCM technique, where the dominant peaks in scaleograms were identified and compared to BL height during the growth phase. The temporal widths of peaks (τmax) derived from VOC and nitrogen oxide (NO x) scaleograms, as well as scaleograms combining VOCs, NO x , and variations in BL height, indicated a broadening with respect to time as the BL increased in depth. A separate section focused on comparisons between τmax and BL height during August 2021 revealed uncorrelated or weakly correlated scatter, except in the case of VOCs when really large τmax and relatively deep BL heights were ignored. Instances of large τmax and relatively deep BL heights occurred near sunrise and as onshore flow entered Pasadena, respectively. Wind transitions likely influenced both the dynamical evolution of the BL and tracer advection and thus offer additional challenges when separating factors contributing to the fine structure. Other insights gained from this work include observations of descending wind jets from the San Gabriel Mountains that were not resolved by the High-Resolution Rapid Refresh (HRRR) model and the derivation of intrinsic properties of oscillations observed in NO x and O 3 during the interaction between an SB and enhanced winds above the BL that flowed in opposition to the SB. [ABSTRACT FROM AUTHOR]

Global climate change is one of the most important scientific, societal and economic contemporary challenges. Fundamental understanding of the major processes driving climate change is the key problem which is to be solved not only on a global but also on a regional scale. The accuracy of regional climate modelling depends on a number of factors. One of these factors is the adequate and comprehensive information on the anthropogenic impact which is highest in industrial regions and areas with dense population – modern megacities. Megacities are not only “heat islands”, but also significant sources of emissions of various substances into the atmosphere, including greenhouse and reactive gases. In 2019, the mobile experiment EMME (Emission Monitoring Mobile Experiment) was conducted within the St. Petersburg agglomeration (Russia) aiming to estimate the emission intensity of greenhouse (CO2, CH4) and reactive (CO, NOx) gases for St. Petersburg, which is the largest northern megacity. St. Petersburg State University (Russia), Karlsruhe Institute of Technology (Germany) and the University of Bremen (Germany) jointly ran this experiment. The core instruments of the campaign were two portable Bruker EM27/SUN Fourier transform infrared (FTIR) spectrometers which were used for ground-based remote sensing measurements of the total column amount of CO2, CH4 and CO at upwind and downwind locations on opposite sides of the city. The NO2 tropospheric column amount was observed along a circular highway around the city by continuous mobile measurements of scattered solar visible radiation with an OceanOptics HR4000 spectrometer using the differential optical absorption spectroscopy (DOAS) technique. Simultaneously, air samples were collected in air bags for subsequent laboratory analysis. The air samples were taken at the locations of FTIR observations at the ground level and also at altitudes of about 100 m when air bags were lifted by a kite (in case of suitable landscape and favourable wind conditions). The entire campaign consisted of 11 mostly cloudless days of measurements in March–April 2019. Planning of measurements for each day included the determination of optimal location for FTIR spectrometers based on weather forecasts, combined with the numerical modelling of the pollution transport in the megacity area. The real-time corrections of the FTIR operation sites were performed depending on the actual evolution of the megacity NOx plume as detected by the mobile DOAS observations. The estimates of the St. Petersburg emission intensities for the considered greenhouse and reactive gases were obtained by coupling a box model and the results of the EMME observational campaign using the mass balance approach. The CO2 emission flux for St. Petersburg as an area source was estimated to be 89 ± 28 ktkm-2yr-1, which is 2 times higher than the corresponding value in the EDGAR database. The experiment revealed the CH4 emission flux of 135 ± 68 tkm-2yr-1, which is about 1 order of magnitude greater than the value reported by the official inventories of St. Petersburg emissions (∼ 25 tkm-2yr-1 for 2017). At the same time, for the urban territory of St. Petersburg, both the EMME experiment and the official inventories for 2017 give similar results for the CO anthropogenic flux (251 ± 104 tkm-2yr-1 vs. 410 tkm-2yr-1) and for the NOx anthropogenic flux (66 ± 28 tkm-2yr-1 vs. 69 tkm-2yr-1).

We deployed an extractive electrospray ionization time-of-flight mass spectrometer (EESI-MS) for airborne measurements of biomass burning aerosol during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) study onboard the NASA DC-8 research aircraft. Through optimization of the electrospray working solution, active control of the electrospray region pressure, and precise control of electrospray capillary position, we achieved 1 Hz quantitative measurements of aerosol nitrocatechol and levoglucosan concentrations up to pressure altitudes of 7 km. The EESI-MS response to levoglucosan and nitrocatechol was calibrated for each flight, with flight-to-flight calibration variability of 60 % (1σ). Laboratory measurements showed no aerosol size dependence in EESI-MS sensitivity below particle geometric diameters of 400 nm, covering 82 % of accumulation-mode aerosol mass during FIREX-AQ. We also present a first in-field intercomparison of EESI-MS with a chemical analysis of aerosol online proton-transfer-reaction mass spectrometer (CHARON PTR-MS) and a high-resolution Aerodyne aerosol mass spectrometer (AMS). EESI-MS and CHARON PTR-MS levoglucosan concentrations were well correlated, with a regression slope of 0.94 (R2=0.77). AMS levoglucosan-equivalent concentrations and EESI-MS levoglucosan showed a greater difference, with a regression slope of 1.36 (R2=0.96), likely indicating the contribution of other compounds to the AMS levoglucosan-equivalent measurement. The total EESI-MS signal showed correlation (R2=0.9) with total organic aerosol measured by AMS, and the EESI-MS bulk organic aerosol sensitivity was 60 % of the sensitivity to levoglucosan standards.

The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor (S5-P) satellite provides methane (CH4) measurements with high accuracy and exceptional temporal and spatial resolution and sampling. TROPOMI CH4 measurements are highly valuable to constrain emissions inventories and for trend analysis, with strict requirements on the data quality. This study describes the improvements that we have implemented to retrieve CH4 from TROPOMI using the RemoTeC full-physics algorithm. The updated retrieval algorithm features a constant regularization scheme of the inversion that stabilizes the retrieval and yields less scatter in the data and includes a higher resolution surface altitude database. We have tested the impact of three state-of-the-art molecular spectroscopic databases (HITRAN 2008, HITRAN 2016 and Scientific Exploitation of Operational Missions – Improved Atmospheric Spectroscopy Databases SEOM-IAS) and found that SEOM-IAS provides the best fitting results. The most relevant update in the TROPOMI XCH4 data product is the implementation of an a posteriori correction fully independent of any reference data that is more accurate and corrects for the underestimation at low surface albedo scenes and the overestimation at high surface albedo scenes. After applying the correction, the albedo dependence is removed to a large extent in the TROPOMI versus satellite (Greenhouse gases Observing SATellite – GOSAT) and TROPOMI versus ground-based observations (Total Carbon Column Observing Network – TCCON) comparison, which is an independent verification of the correction scheme. We validate 2 years of TROPOMI CH4 data that show the good agreement of the updated TROPOMI CH4 with TCCON (−3.4 ± 5.6 ppb) and GOSAT (−10.3 ± 16.8 ppb) (mean bias and standard deviation). Low- and high-albedo scenes as well as snow-covered scenes are the most challenging for the CH4 retrieval algorithm, and although the a posteriori correction accounts for most of the bias, there is a need to further investigate the underlying cause.

This work presents the latest release (v9.0) of the University of Leicester GOSAT Proxy XCH4 dataset. Since the launch of the GOSAT satellite in 2009, these data have been produced by the UK National Centre for Earth Observation (NCEO) as part of the ESA Greenhouse Gas Climate Change Initiative (GHG-CCI) and Copernicus Climate Change Services (C3S) projects. With now over a decade of observations, we outline the many scientific studies achieved using past versions of these data in order to highlight how this latest version may be used in the future. We describe in detail how the data are generated, providing information and statistics for the entire processing chain from the L1B spectral data through to the final quality-filtered column-averaged dry-air mole fraction (XCH4) data. We show that out of the 19.5 million observations made between April 2009 and December 2019, we determine that 7.3 million of these are sufficiently cloud-free (37.6 %) to process further and ultimately obtain 4.6 million (23.5 %) high-quality XCH4 observations. We separate these totals by observation mode (land and ocean sun glint) and by month, to provide data users with the expected data coverage, including highlighting periods with reduced observations due to instrumental issues. We perform extensive validation of the data against the Total Carbon Column Observing Network (TCCON), comparing to ground-based observations at 22 locations worldwide. We find excellent agreement with TCCON, with an overall correlation coefficient of 0.92 for the 88 345 co-located measurements. The single-measurement precision is found to be 13.72 ppb, and an overall global bias of 9.06 ppb is determined and removed from the Proxy XCH4 data. Additionally, we validate the separate components of the Proxy (namely the modelled XCO2 and the XCH4∕XCO2 ratio) and find these to be in excellent agreement with TCCON. In order to show the utility of the data for future studies, we compare against simulated XCH4 from the TM5 model. We find a high degree of consistency between the model and observations throughout both space and time. When focusing on specific regions, we find average differences ranging from just 3.9 to 15.4 ppb. We find the phase and magnitude of the seasonal cycle to be in excellent agreement, with an average correlation coefficient of 0.93 and a mean seasonal cycle amplitude difference across all regions of −0.84 ppb. These data are available at https://doi.org/10.5285/18ef8247f52a4cb6a14013f8235cc1eb (Parker and Boesch, 2020).

Background: In animal studies long-term stretching interventions up to several hours per day have shown large increases in muscle mass as well as maximal strength. The aim of this study was to investigate the effects of a long-term stretching on maximal strength, muscle cross sectional area (MCSA) and range of motion (ROM) in humans.Methods: 52 subjects were divided into an Intervention group (IG, n = 27) and a control group (CG, n = 25). IG stretched the plantar flexors for one hour per day for six weeks using an orthosis. Stretching was performed on one leg only to investigate the contralateral force transfer. Maximal isometric strength (MIS) and 1RM were both measured in extended knee joint. Furthermore, we investigated the MCSA of IG in the lateral head of the gastrocnemius (LG) using sonography. Additionally, ROM in the upper ankle was investigated via the functional “knee to wall stretch” test (KtW) and a goniometer device on the orthosis. A two-way ANOVA was performed in data analysis, using the Scheffé Test as post-hoc test.Results: There were high time-effects (p = 0.003, ƞ² = 0.090) and high interaction-effect (p < 0.001, ƞ²=0.387) for MIS and also high time-effects (p < 0.001, ƞ²=0.193) and interaction-effects (p < 0.001, ƞ²=0,362) for 1RM testing. Furthermore, we measured a significant increase of 15.2% in MCSA of LG with high time-effect (p < 0.001, ƞ²=0.545) and high interaction-effect (p=0.015, ƞ²=0.406). In ROM we found in both tests significant increases up to 27.3% with moderate time-effect (p < 0.001, ƞ²=0.129) and high interaction-effect (p < 0.001, ƞ²=0.199). Additionally, we measured significant contralateral force transfers in maximal strength tests of 11.4% (p < 0.001) in 1RM test and 1.4% (p=0.462) in MIS test. Overall, there we no significant effects in control situations for any parameter (CG and non-intervened leg of IG).Discussion: We hypothesize stretching-induced muscle damage comparable to effects of mechanical load of strength training, that led to hypertrophy and thus to an increase in maximal strength. Increases in ROM could be attributed to longitudinal hypertrophy effects, e.g., increase in serial sarcomeres. Measured cross-education effects could be explained by central neural adaptations due to stimulation of the stretched muscles.

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the tnzuncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

Abstract It took decades of political discussion for lawmakers to begin adjusting the income tax tariff for inflation in order to curb the fiscal drag. Since 2016, the fiscal drag has been reduced by almost € 32 billion according to our estimates. That is certainly a substantial amount given the low inflation rates in the period 2016–2021. We illustrate these effects graphically and also numerically for individual taxpayers. We find that further reforms are needed. A specific formula should be integrated into the Income Tax Act so that the tariff is adjusted automatically to inflation. In the long run, average income growth rates should be used for indexation instead of inflation rates.

We present a multiyear time series of column abundances of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) measured using Fourier-transform infrared (FTIR) spectrometers at 10 sites affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC). Six are high-latitude sites: Eureka, Ny-Ålesund, Thule, Kiruna, Poker Flat, and St. Petersburg, and four are midlatitude sites: Zugspitze, Jungfraujoch, Toronto, and Rikubetsu. For each site, the interannual trends and seasonal variabilities of the CO time series are accounted for, allowing background column amounts to be determined. Enhancements above the seasonal background were used to identify possible wildfire pollution events. Since the abundance of each trace gas emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution. A GEOS-Chem tagged CO simulation with Global Fire Assimilation System (GFASv1.2) biomass burning emissions was used to determine the source attribution of CO concentrations at each site from 2003 to 2018. For each detected wildfire pollution event, FLEXPART back-trajectory simulations were performed to determine the transport times of the smoke plume. Accounting for the loss of each species during transport, the enhancement ratios of HCN and C2H6 with respect to CO were converted to emission ratios. We report mean emission ratios with respect to CO for HCN and C2H6 of 0.0047 and 0.0092, respectively, with a standard deviation of 0.0014 and 0.0046, respectively, determined from 23 boreal North American wildfire events. Similarly, we report mean emission ratios for HCN and C2H6 of 0.0049 and 0.0100, respectively, with a standard deviation of 0.0025 and 0.0042, respectively, determined from 39 boreal Asian wildfire events. The agreement of our emission ratios with literature values illustrates the capability of ground-based FTIR measurements to quantify biomass burning emissions. We provide a comprehensive dataset that quantifies HCN and C2H6 emission ratios from 62 wildfire pollution events. Our dataset provides novel emission ratio estimates, which are sparsely available in the published literature, particularly for boreal Asian sources.

The GEOS-Chem simulation of atmospheric CH4 was evaluated against observations from the Thermal and Near Infrared Sensor for Carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Total Carbon Column Observing Network (TCCON). We focused on the model simulations at the 4∘×5∘ and 2∘×2.5∘ horizontal resolutions for the period of February–May 2010. Compared to the GOSAT, TCCON, and ACE-FTS data, we found that the 2∘×2.5∘ model produced a better simulation of CH4, with smaller biases and a higher correlation to the independent data. We found large resolution-dependent differences such as a latitude-dependent XCH4 bias, with higher column abundances of CH4 at high latitudes and lower abundances at low latitudes at the 4∘×5∘ resolution than at 2∘×2.5∘. We also found large differences in CH4 column abundances between the two resolutions over major source regions such as China. These differences resulted in up to 30 % differences in inferred regional CH4 emission estimates from the two model resolutions. We performed several experiments using 222Rn, 7Be, and CH4 to determine the origins of the resolution-dependent errors. The results suggested that the major source of the latitude-dependent errors is excessive mixing in the upper troposphere and lower stratosphere, including mixing at the edge of the polar vortex, which is pronounced at the 4∘×5∘ resolution. At the coarser resolution, there is weakened vertical transport in the troposphere at midlatitudes to high latitudes due to the loss of sub-grid tracer eddy mass flux in the storm track regions. The vertical air mass fluxes are calculated in the model from the degraded coarse-resolution wind fields and the model does not conserve the air mass flux between model resolutions; as a result, the low resolution does not fully capture the vertical transport. This produces significant localized discrepancies, such as much greater CH4 abundances in the lower troposphere over China at 4∘×5∘ than at 2∘×2.5∘. Although we found that the CH4 simulation is significantly better at 2∘×2.5∘ than at 4∘×5∘, biases may still be present at 2∘×2.5∘ resolution. Their importance, particularly in regards to inverse modeling of CH4 emissions, should be evaluated in future studies using online transport in the native general circulation model as a benchmark simulation.

Particles in smoke emitted from biomass combustion have a large impact on global climate and urban air quality. There is limited understanding of how particle optical properties – especially the contributions of black carbon (BC) and brown carbon (BrC) – evolve with photochemical aging of smoke. We analyze the evolution of the optical properties and chemical composition of particles produced from combustion of a wide variety of biomass fuels, largely from the western United States. The smoke is photochemically aged in a reaction chamber over atmospheric-equivalent timescales ranging from 0.25 to 8 d. Various aerosol optical properties (e.g., the single-scatter albedo, the wavelength dependence of absorption, and the BC mass absorption coefficient, MACBC) evolved with photochemical aging, with the specific evolution dependent on the initial particle properties and conditions. The impact of coatings on BC absorption (the so-called lensing effect) was small, even after photochemical aging. The initial evolution of the BrC absorptivity (MACBrC) varied between individual burns but decreased consistently at longer aging times; the wavelength dependence of the BrC absorption generally increased with aging. The observed changes to BrC properties result from a combination of secondary organic aerosol (SOA) production and heterogeneous oxidation of primary and secondary OA mass, with SOA production being the major driver of the changes. The SOA properties varied with time, reflecting both formation from precursors having a range of lifetimes with respect to OH and the evolving photochemical environment within the chamber. Although the absorptivity of BrC generally decreases with aging, the dilution-corrected absorption may actually increase from the production of SOA. These experimental results provide context for the interpretation of ambient observations of the evolution of particle optical properties in biomass-combustion-derived smoke plumes.

Reactive nitrogen (Nr, defined as all nitrogen-containing compounds except for N2 and N2O) is one of the most important classes of compounds emitted from wildfire, as Nr impacts both atmospheric oxidation processes and particle formation chemistry. In addition, several Nr compounds can contribute to health impacts from wildfires. Understanding the impacts of wildfire on the atmosphere requires a thorough description of Nr emissions. Total reactive nitrogen was measured by catalytic conversion to NO and detection by NO–O3 chemiluminescence together with individual Nr species during a series of laboratory fires of fuels characteristic of western US wildfires, conducted as part of the FIREX Fire Lab 2016 study. Data from 75 stack fires were analyzed to examine the systematics of nitrogen emissions. The measured Nr ∕ total-carbon ratios averaged 0.37 % for fuels characteristic of western North America, and these gas-phase emissions were compared with fuel and residue N∕C ratios and mass to estimate that a mean (±SD) of 0.68 (±0.14) of fuel nitrogen was emitted as N2 and N2O. The Nr detected as speciated individual compounds included the following: nitric oxide (NO), nitrogen dioxide (NO2), nitrous acid (HONO), isocyanic acid (HNCO), hydrogen cyanide (HCN), ammonia (NH3), and 44 nitrogen-containing volatile organic compounds (NVOCs). The sum of these measured individual Nr compounds averaged 84.8 (±9.8) % relative to the total Nr, and much of the 15.2 % “unaccounted” Nr is expected to be particle-bound species, not included in this analysis. A number of key species, e.g., HNCO, HCN, and HONO, were confirmed not to correlate with only flaming or with only smoldering combustion when using modified combustion efficiency, MCE=CO2/(CO+CO2), as a rough indicator. However, the systematic variations in the abundance of these species relative to other nitrogen-containing species were successfully modeled using positive matrix factorization (PMF). Three distinct factors were found for the emissions from combined coniferous fuels: a combustion factor (Comb-N) (800–1200 ∘C) with emissions of the inorganic compounds NO, NO2, and HONO, and a minor contribution from organic nitro compounds (R-NO2); a high-temperature pyrolysis factor (HT-N) (500–800 ∘C) with emissions of HNCO, HCN, and nitriles; and a low-temperature pyrolysis factor (LT-N) ( ∘C) with mostly ammonia and NVOCs. The temperature ranges specified are based on known combustion and pyrolysis chemistry considerations. The mix of emissions in the PMF factors from chaparral fuels (manzanita and chamise) had a slightly different composition: the Comb-N factor was also mostly NO, with small amounts of HNCO, HONO, and NH3; the HT-N factor was dominated by NO2 and had HONO, HCN, and HNCO; and the LT-N factor was mostly NH3 with a slight amount of NO contributing. In both cases, the Comb-N factor correlated best with CO2 emission, while the HT-N factors from coniferous fuels correlated closely with the high-temperature VOC factors recently reported by Sekimoto et al. (2018), and the LT-N had some correspondence to the LT-VOC factors. As a consequence, CO2 is recommended as a marker for combustion Nr emissions, HCN is recommended as a marker for HT-N emissions, and the family NH3 ∕ particle ammonium is recommended as a marker for LT-N emissions.

Verifying anthropogenic carbon dioxide (CO2) emissions globally is essential to inform about the progress of institutional efforts to mitigate anthropogenic climate forcing. To monitor localized emission sources, spectroscopic satellite sensors have been proposed that operate on the CO2 absorption bands in the shortwave-infrared (SWIR) spectral range with ground resolution as fine as a few tens of meters to about a hundred meters. When designing such sensors, fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, such sensors are envisioned to fly in fleets of satellites, requiring low-cost and simple design, e.g., by restricting the spectrometer to a single spectral band. Here, we use measurements of the Greenhouse Gases Observing Satellite (GOSAT) to evaluate the spectral resolution and spectral band selection of a prospective satellite sensor with fine ground resolution. To this end, we degrade GOSAT SWIR spectra of the CO2 bands at 1.6 (SWIR-1) and 2.0 µm (SWIR-2) to coarse spectral resolution, without a further addition of noise, and we evaluate single-band retrievals of the column-averaged dry-air mole fractions of CO2 (XCO2) by comparison to ground truth provided by the Total Carbon Column Observing Network (TCCON) and by comparison to global “native” GOSAT retrievals with native spectral resolution and spectral band selection. Coarsening spectral resolution from GOSAT's native resolving power of >20 000 to the range of 700 to a few thousand makes the scatter of differences between the SWIR-1 and SWIR-2 retrievals and TCCON increase moderately. For resolving powers of 1200 (SWIR-1) and 1600 (SWIR-2), the scatter increases from 2.4 (native) to 3.0 ppm for SWIR-1 and 3.3 ppm for SWIR-2. Coarser spectral resolution yields only marginally worse performance than the native GOSAT configuration in terms of station-to-station variability and geophysical parameter correlations for the GOSAT–TCCON differences. Comparing the SWIR-1 and SWIR-2 configurations to native GOSAT retrievals on the global scale, however, reveals that the coarse-resolution SWIR-1 and SWIR-2 configurations suffer from some spurious correlations with geophysical parameters that characterize the light-scattering properties of the scene such as particle amount, size, height and surface albedo. Overall, the SWIR-1 and SWIR-2 configurations with resolving powers of 1200 and 1600 show promising performance for future sensor design in terms of random error sources while residual errors induced by light scattering along the light path need to be investigated further. Due to the stronger CO2 absorption bands in SWIR-2 than in SWIR-1, the former has the advantage that measurement noise propagates less into the retrieved XCO2 and that some retrieval information on particle scattering properties is accessible.

Satellite retrievals of column-averaged dry-air mole fractions of carbon dioxide (CO2) and methane (CH4), denoted XCO2 and XCH4, respectively, have been used in recent years to obtain information on natural and anthropogenic sources and sinks and for other applications such as comparisons with climate models. Here we present new data sets based on merging several individual satellite data products in order to generate consistent long-term climate data records (CDRs) of these two Essential Climate Variables (ECVs). These ECV CDRs, which cover the time period 2003–2018, have been generated using an ensemble of data products from the satellite sensors SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT and (for XCO2) for the first time also including data from the Orbiting Carbon Observatory 2 (OCO-2) satellite. Two types of products have been generated: (i) Level 2 (L2) products generated with the latest version of the ensemble median algorithm (EMMA) and (ii) Level 3 (L3) products obtained by gridding the corresponding L2 EMMA products to obtain a monthly 5∘×5∘ data product in Obs4MIPs (Observations for Model Intercomparisons Project) format. The L2 products consist of daily NetCDF (Network Common Data Form) files, which contain in addition to the main parameters, i.e., XCO2 or XCH4, corresponding uncertainty estimates for random and potential systematic uncertainties and the averaging kernel for each single (quality-filtered) satellite observation. We describe the algorithms used to generate these data products and present quality assessment results based on comparisons with Total Carbon Column Observing Network (TCCON) ground-based retrievals. We found that the XCO2 Level 2 data set at the TCCON validation sites can be characterized by the following figures of merit (the corresponding values for the Level 3 product are listed in brackets) – single-observation random error (1σ): 1.29 ppm (monthly: 1.18 ppm); global bias: 0.20 ppm (0.18 ppm); and spatiotemporal bias or relative accuracy (1σ): 0.66 ppm (0.70 ppm). The corresponding values for the XCH4 products are single-observation random error (1σ): 17.4 ppb (monthly: 8.7 ppb); global bias: −2.0 ppb (−2.9 ppb); and spatiotemporal bias (1σ): 5.0 ppb (4.9 ppb). It has also been found that the data products exhibit very good long-term stability as no significant long-term bias trend has been identified. The new data sets have also been used to derive annual XCO2 and XCH4 growth rates, which are in reasonable to good agreement with growth rates from the National Oceanic and Atmospheric Administration (NOAA) based on marine surface observations. The presented ECV data sets are available (from early 2020 onwards) via the Climate Data Store (CDS, https://cds.climate.copernicus.eu/, last access: 10 January 2020) of the Copernicus Climate Change Service (C3S, https://climate.copernicus.eu/, last access: 10 January 2020).

Summary: Life history theory predicts a trade-off between the quantity and quality of offspring. Short interbirth intervals—the time between successive births—may increase the quantity of offspring but harm offspring quality. In contrast, long interbirth intervals may bolster offspring quality while reducing overall reproductive output. Further research is needed to determine whether this relationship holds among primates, which have intensive parental investment. Using Cox proportional hazards models, we examined the effects of interbirth intervals (short, normal, or long) on infant survivorship using a large demographic dataset (n = 15,852) of captive callitrichine monkeys (marmosets, tamarins, and lion tamarins). In seven of the nine species studied, infants born after short interbirth intervals had significantly higher risks of mortality than infants born after longer interbirth intervals. These results suggest that reproduction in callitrichine primates may be limited by physiologic constraints, such that short birth spacing drives higher infant mortality.

Chamber oxidation experiments conducted at the Fire Sciences Laboratory in 2016 are evaluated to identify important chemical processes contributing to the hydroxy radical (OH) chemistry of biomass burning non-methane organic gases (NMOGs). Based on the decay of primary carbon measured by proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS), it is confirmed that furans and oxygenated aromatics are among the NMOGs emitted from western United States fuel types with the highest reactivities towards OH. The oxidation processes and formation of secondary NMOG masses measured by PTR-ToF-MS and iodide-clustering time-of-flight chemical ionization mass spectrometry (I-CIMS) is interpreted using a box model employing a modified version of the Master Chemical Mechanism (v. 3.3.1) that includes the OH oxidation of furan, 2-methylfuran, 2,5-dimethylfuran, furfural, 5-methylfurfural, and guaiacol. The model supports the assignment of major PTR-ToF-MS and I-CIMS signals to a series of anhydrides and hydroxy furanones formed primarily through furan chemistry. This mechanism is applied to a Lagrangian box model used previously to model a real biomass burning plume. The customized mechanism reproduces the decay of furans and oxygenated aromatics and the formation of secondary NMOGs, such as maleic anhydride. Based on model simulations conducted with and without furans, it is estimated that furans contributed up to 10 % of ozone and over 90 % of maleic anhydride formed within the first 4 h of oxidation. It is shown that maleic anhydride is present in a biomass burning plume transported over several days, which demonstrates the utility of anhydrides as markers for aged biomass burning plumes.

Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and methane (CH4) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments.The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which was successfully launched in October 2017, is a spaceborne nadir-viewing imaging spectrometer measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR), combining a high spatial resolution with daily global coverage. These characteristics enable the determination of both gases with an unprecedented level of detail on a global scale, introducing new areas of application.Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH4 are simultaneously retrieved from TROPOMI's radiance measurements in the 2.3 µm spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). This algorithm is intended to be used with the operational algorithms for mutual verification and to provide new geophysical insights. We introduce the algorithm in detail, including expected error characteristics based on synthetic data, a machine-learning-based quality filter, and a shallow learning calibration procedure applied in the post-processing of the XCH4 data. The quality of the results based on real TROPOMI data is assessed by validation with ground-based Fourier transform spectrometer (FTS) measurements providing realistic error estimates of the satellite data: the XCO data set is characterised by a random error of 5.1 ppb (5.8 %) and a systematic error of 1.9 ppb (2.1 %); the XCH4 data set exhibits a random error of 14.0 ppb (0.8 %) and a systematic error of 4.3 ppb (0.2 %). The natural XCO and XCH4 variations are well-captured by the satellite retrievals, which is demonstrated by a high correlation with the validation data (R = 0.97 for XCO and R = 0.91 for XCH4 based on daily averages).We also present selected results from the mission start until the end of 2018, including a first comparison to the operational products and examples of the detection of emission sources in a single satellite overpass, such as CO emissions from the steel industry and CH4 emissions from the energy sector, which potentially allows for the advance of emission monitoring and air quality assessments to an entirely new level.

Despite the known biochemical production of a range of aromatic compounds by plants and the presence of benzenoids in floral scents, the emissions of only a few benzenoid compounds have been reported from the biosphere to the atmosphere. Here, using evidence from measurements at aircraft, ecosystem, tree, branch and leaf scales, with complementary isotopic labeling experiments, we show that vegetation (leaves, flowers, and phytoplankton) emits a wide variety of benzenoid compounds to the atmosphere at substantial rates. Controlled environment experiments show that plants are able to alter their metabolism to produce and release many benzenoids under stress conditions. The functions of these compounds remain unclear but may be related to chemical communication and protection against stress. We estimate the total global secondary organic aerosol potential from biogenic benzenoids to be similar to that from anthropogenic benzenoids (~10 Tg y(-1)), pointing to the importance of these natural emissions in atmospheric physics and chemistry.

Emissions of methane (CH4) and volatile organic compounds (VOCs) from oil and gas production may have large impacts on air quality and climate change. Methane and VOCs were measured over the Haynesville and Marcellus shale gas plays on board the National Center for Atmospheric Research C-130 and NOAA WP-3D research aircraft in June–July of 2013. We used an eddy covariance technique to measure in situ fluxes of CH4 and benzene from both C-130 flights with high-resolution data (10 Hz) and WP-3D flights with low-resolution data (1 Hz). Correlation (R = 0.65) between CH4 and benzene fluxes was observed when flying over shale gas operations, and the enhancement ratio of fluxes was consistent with the corresponding concentration observations. Fluxes calculated by the eddy covariance method show agreement with a mass balance approach within their combined uncertainties. In general, CH4 fluxes in the shale gas regions follow a lognormal distribution, with some deviations for relatively large fluxes (>10 μgm-2 s-1). Statistical analysis of the fluxes shows that a small number of facilities (i.e., ~10%) are responsible for up to ~40% of the total CH4 emissions in the two regions. We show that the airborne eddy covariance method can also be applied in some circumstances when meteorological conditions do not favor application of the mass balance method. We suggest that the airborne eddy covariance method is a reliable alternative and complementary analysis method to estimate emissions from oil and gas extraction.

A model intercomparison activity was inspired by the large suite of observations of atmospheric composition made during the International Polar Year (2008) in the Arctic. Nine global and two regional chemical transport models participated in this intercomparison and performed simulations for 2008 using a common emissions inventory to assess the differences in model chemistry and transport schemes. This paper summarizes the models and compares their simulations of ozone and its precursors and presents an evaluation of the simulations using a variety of surface, balloon, aircraft and satellite observations. Each type of measurement has some limitations in spatial or temporal coverage or in composition, but together they assist in quantifying the limitations of the models in the Arctic and surrounding regions. Despite using the same emissions, large differences are seen among the models. The cloud fields and photolysis rates are shown to vary greatly among the models, indicating one source of the differences in the simulated chemical species. The largest differences among models, and between models and observations, are in NOy partitioning (PAN vs. HNO3) and in oxygenated volatile organic compounds (VOCs) such as acetaldehyde and acetone. Comparisons to surface site measurements of ethane and propane indicate that the emissions of these species are significantly underestimated. Satellite observations of NO2 from the OMI (Ozone Monitoring Instrument) have been used to evaluate the models over source regions, indicating anthropogenic emissions are underestimated in East Asia, but fire emissions are generally overestimated. The emission factors for wildfires in Canada are evaluated using the correlations of VOCs to CO in the model output in comparison to enhancement factors derived from aircraft observations, showing reasonable agreement for methanol and acetaldehyde but underestimate ethanol, propane and acetone, while overestimating ethane emission factors.

Speed strength performances are substantially dependent on maximum strength. Due to their importance, various methods have been utilized to measure maximum strength (e.g., isometric or dynamic) with discussed differences regarding transferability to sport-specific movements dependent upon the testing procedure. The aim of this study was to analyze whether maximum isometric force (MIF) during isometric back squats correlates with maximum strength measurements of the one repetition maximum (1RM) in the squat, with countermovement jump (CMJ) performance, and with drop jump (DJ) performances in elite youth soccer players (n = 16, 18.4 ± 1.5 [range: 17–23] years old). Additionally, concordance correlation coefficients (CCC, [ρc]) between isometric and dynamic measurements were calculated to verify whether one measurement can actually reproduce the results of the other. To improve comprehension, differences between isometric and dynamic testing values were illustrated by providing differences between both testing conditions. For this, the mean absolute error (MAE) and the mean absolute percentage error (MAPE) were calculated. To reach equality in scale, the 1RM measures were multiplicated by 9.81 to obtain a value of N. The 1RM demonstrated correlations of τ = |0.38| to |0.52| with SJ and CMJ performances, while MIF demonstrated correlations of τ = |0.21| to |0.32|. However, the correlations of both 1RM and MIF with the DJ reactive strength index (RSI = jump height/contact time) from different falling heights were of no statistical significance. The data showed significant correlations between both the absolute (τ = |0.54|) and the relative (τ = |0.40|) performances of 1RM and MIF, which were confirmed by CCC of ρc= |0.56| to |0.66|, respectively. Furthermore, the MAE and MAPE showed values of 2080.87 N and 67.4%, respectively. The data in this study show that, despite good correlations, there is no exact coincidence between isometric and dynamic strength measurements. Accordingly, both measurements may only represent an estimation of maximal strength capacity and cannot be substituted for each other. Therefore, maximal strength should be tested by using high similarity in the contraction condition, as it is used in the training process to counteract underestimation in strength because of unfamiliarity with the testing condition.