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Dairies emit roughly half of total methane (CH4) emissions in California, generating CH4 from both enteric fermentation by ruminant gut microbes and anaerobic decomposition of manure. Representation of these emission processes is essential for management and mitigation of CH4 emissions and is typically done using standardized emission factors applied at large spatial scales (e.g., state level). However, CH4-emitting activities and management decisions vary across facilities, and current inventories do not have sufficiently high spatial resolution to capture changes at this scale. Here, we develop a spatially explicit database of dairies in California, with information from operating permits and California-specific reports detailing herd demographics and manure management at the facility scale. We calculated manure management and enteric fermentation CH4 emissions using two previously published bottom-up approaches and a new farm-specific calculation developed in this work. We also estimate the effect of mitigation strategies – the use of mechanical separators and installation of anaerobic digesters – on CH4 emissions. We predict that implementation of digesters at the 106 dairies that are existing or planned in California will reduce manure CH4 emissions from those facilities by an average of 26 % and total state CH4 emissions by 5 % (or ∼36.5 Gg CH4/yr). In addition to serving as a planning tool for mitigation, this database is useful as a prior for atmospheric observation-based emissions estimates, attribution of emissions to a specific facility, and validation of CH4 emissions reductions from management changes. Raster files of the datasets and associated metadata are available from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics (ORNL DAAC; Marklein and Hopkins, 2020; https://doi.org/10.3334/ORNLDAAC/1814).

Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.

Methane (CH4) inventory uncertainties are large, requiring robust emission derivation approaches. We report on a fused airborne–surface data collection approach to derive emissions from an active oil field near Bakersfield, central California. The approach characterizes the atmosphere from the surface to above the planetary boundary layer (PBL) and combines downwind trace gas concentration anomaly (plume) above background with normal winds to derive flux. This approach does not require a well-mixed PBL; allows explicit, data-based, uncertainty evaluation; and was applied to complex topography and wind flows. In situ airborne (collected by AJAX – the Alpha Jet Atmospheric eXperiment) and mobile surface (collected by AMOG – the AutoMObile trace Gas – Surveyor) data were collected on 19 August 2015 to assess source strength. Data included an AMOG and AJAX intercomparison transect profiling from the San Joaquin Valley (SJV) floor into the Sierra Nevada (0.1–2.2 km altitude), validating a novel surface approach for atmospheric profiling by leveraging topography. The profile intercomparison found good agreement in multiple parameters for the overlapping altitude range from 500 to 1500 m for the upper 5 % of surface winds, which accounts for wind-impeding structures, i.e., terrain, trees, buildings, etc. Annualized emissions from the active oil fields were 31.3 ± 16 Gg methane and 2.4 ± 1.2 Tg carbon dioxide. Data showed the PBL was not well mixed at distances of 10–20 km downwind, highlighting the importance of the experimental design.

Megacities are major sources of anthropogenic fossil fuel CO2 (FFCO2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as ∼ 1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with ∼ 1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO2 mole fractions and Δ14C and δ13C values of CO2 in the Los Angeles megacity observed in inland Pasadena (2006–2013) and coastal Palos Verdes peninsula (autumn 2009–2013), we have determined time series for CO2 contributions from fossil fuel combustion (Cff) for both sites and broken those down into contributions from petroleum and/or gasoline and natural gas burning for Pasadena. We find a 10 % reduction in Pasadena Cff during the Great Recession of 2008–2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO2 from our observations are used to infer seasonality of natural gas and petroleum combustion. The trend of CO2 contributions to the atmosphere from natural gas combustion is out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but is consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO2 contributions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare Cff from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO2 reflect seasonal variations in wind direction. The seasonality of the local CO2 excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in autumn and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO2 signals are consistent with sampling the bottom-up Hestia-LA fossil CO2 emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

A reliable and precise in situ CO2 and CO analysis system has been developed and deployed at eight sites in the NOAA Earth System Research Laboratory's (ESRL) Global Greenhouse Gas Reference Network. The network uses very tall (> 300 m) television and radio transmitter towers that provide a convenient platform for mid-boundary-layer trace-gas sampling. Each analyzer has three sample inlets for profile sampling, and a complete vertical profile is obtained every 15 min. The instrument suite at one site has been augmented with a cavity ring-down spectrometer for measuring CO2 and CH4. The long-term stability of the systems in the field is typically better than 0.1 ppm for CO2, 6 ppb for CO, and 0.5 ppb for CH4, as determined from repeated standard gas measurements. The instrumentation is fully automated and includes sensors for measuring a variety of status parameters, such as temperatures, pressures, and flow rates, that are inputs for automated alerts and quality control algorithms. Detailed and time-dependent uncertainty estimates have been constructed for all of the gases, and the uncertainty framework could be readily adapted to other species or analysis systems. The design emphasizes use of off-the-shelf parts and modularity to facilitate network operations and ease of maintenance. The systems report high-quality data with > 93% uptime. Recurrent problems and limitations of the current system are discussed along with general recommendations for high-accuracy trace-gas monitoring. The network is a key component of the North American Carbon Program and a useful model for future research-grade operational greenhouse gas monitoring efforts.

Recent advances in atmospheric transport model inversions could significantly reduce uncertainties in land carbon uptake through the assimilation of CO2 concentration measurements at weekly and shorter timescales. The potential of these measurements for reducing biases in estimated land carbon sinks depends on the strength of covariation between surface fluxes and atmospheric transport at these timescales and how well transport models represent this covariation. Daily to seasonal covariation of surface fluxes and atmospheric transport was estimated in observations at the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility, and compared to an atmospheric transport model inversion (CarbonTracker). Covariation of transport and surface fluxes was stronger in CarbonTracker than in observations on synoptic (daily to weekly) timescales, with a wet year (2007) having significant covariation compared to a dry year (2006). Differences between observed and CarbonTracker synoptic covariation resulted in a 0.3 ppm CO2 enhancement in boundary layer concentrations during the growing season, and a corresponding enhancement in carbon uptake by 13% of the seasonal cycle amplitude in 2007, as estimated by an offline simplified transport model. This synoptic rectification of surface flux variability was of similar magnitude to the interannual variability in carbon sinks alone, and indicates that interannual variability in the inversions can be affected by biases in simulated synoptic rectifier effects. The most significant covariation of surface fluxes and transport had periodicities of 10 days and greater, suggesting that surface flux inversions would benefit from improved simulations of the effects of soil moisture on boundary layer heights and surface CO2 fluxes. Soil moisture remote sensing could be used along with CO2 concentration measurements to further constrain atmospheric transport model inversions.

Attributing observed CO2 variations to human or natural cause is critical to deducing and tracking emissions from observations. We have used in situ CO2, CO, and planetary boundary layer height (PBLH) measurements recorded during the CalNex-LA (CARB et al., 2008) ground campaign of 15 May–15 June 2010, in Pasadena, CA, to deduce the diurnally varying anthropogenic component of observed CO2 in the megacity of Los Angeles (LA). This affordable and simple technique, validated by carbon isotope observations and WRF-STILT (Weather Research and Forecasting model – Stochastic Time-Inverted Lagrangian Transport model) predictions, is shown to robustly attribute observed CO2 variation to anthropogenic or biogenic origin over the entire diurnal cycle. During CalNex-LA, local fossil fuel combustion contributed up to ~50% of the observed CO2 enhancement overnight, and ~100% of the enhancement near midday. This suggests that sufficiently accurate total column CO2 observations recorded near midday, such as those from the GOSAT or OCO-2 satellites, can potentially be used to track anthropogenic emissions from the LA megacity.

Direct quantification of fossil fuel CO2 (CO2ff) in atmospheric samples can be used to examine several carbon cycle and air quality questions. We collected in situ CO2, CO, and CH4 measurements and flask samples in the boundary layer and free troposphere over Sacramento, California, USA, during two aircraft flights over and downwind of this urban area during spring of 2009. The flask samples were analyzed for Δ14CO2 and CO2 to determine the recently added CO2ff mole fraction. A suite of greenhouse and other trace gases, including hydrocarbons and halocarbons, were measured in the same samples. Strong correlations were observed between CO2ff and numerous trace gases associated with urban emissions. From these correlations we estimate emission ratios between CO2ff and these species, and compare these with bottom-up inventory-derived estimates. Recent county level inventory estimates for carbon monoxide (CO) and benzene from the California Air Resources Board CEPAM database are in good agreement with our measured emission ratios, whereas older emissions inventories appear to overestimate emissions of these gases by a factor of two. For most other trace species, there are substantial differences (200–500%) between our measured emission ratios and those derived from available emission inventories. For the first flight, we combine in situ CO measurements with the measured CO:CO2ff emission ratio of 14 ± 2 ppbCO/ppmCO2 to derive an estimate of CO2ff mole fraction throughout this flight, and also estimate the biospheric CO2 mixing ratio (CO2bio) from the difference of total and fossil CO2. The resulting CO2bio varies dramatically from up to 8 ± 2 ppm in the urban plume to −6 ± 1 ppm in the surrounding boundary layer air. Finally, we use the in situ estimates of CO2ff mole fraction to infer total fossil fuel CO2 emissions from the Sacramento region, using a mass balance approach. The resulting emissions are uncertain to within a factor of two due to uncertainties in wind speed and boundary layer height. Nevertheless, this first attempt to estimate urban-scale CO2ff from atmospheric radiocarbon measurements shows that CO2ff can be used to verify and improve emission inventories for many poorly known anthropogenic species, separate biospheric CO2, and indicates the potential to constrain CO2ff emissions if transport uncertainties are reduced.

The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total column data within error.

We present carbon dioxide (CO2) estimates from the Tropospheric Emission Spectrometer (TES) on the EOS-Aura satellite launched in 2004. For observations between 40° S and 45° N, we find about 1 degree of freedom with peak sensitivity at 511 hPa. The estimated error is ~10 ppm for a single target and 1.3–2.3 ppm for monthly averages on spatial scales of 20°×30°. Monthly spatially-averaged TES data from 2005–2008 processed with a uniform initial guess and prior are compared to CONTRAIL aircraft data over the Pacific ocean, aircraft data at the Southern Great Plains (SGP) ARM site in the southern US, and the Mauna Loa and Samoa surface stations. Comparisons to Mauna Loa data show a correlation of 0.92, a standard deviation of 1.3 ppm, a predicted error of 1.2 ppm, and a ~2% low bias, which is subsequently corrected. Comparisons to SGP aircraft data over land show a correlation of 0.67 and a standard deviation of 2.3 ppm. TES data between 40° S and 45° N for 2006–2007 are compared to surface flask data, GLOBALVIEW, the Atmospheric Infrared Sounder (AIRS), and CarbonTracker. Comparison to GLOBALVIEW-CO2 ocean surface sites shows a correlation of 0.60 which drops when TES is offset in latitude, longitude, or time. At these same locations, TES shows a 0.62 and 0.67 correlation to CarbonTracker at the surface and 5 km, respectively. We also conducted an observing system simulation experiment to assess the potential utility of the TES data for inverse modeling of CO2 fluxes. We find that if biases in the data and model are well characterized, the averaged data have the potential to provide sufficient information to significantly reduce uncertainty on annual estimates of regional CO2 sources and sinks. Averaged pseudo-data at 10°×10° reduced uncertainty in flux estimates by as much as 70% for some tropical regions.

This study presents the epidemiological analysis of 20,699 reported spider bites involving the Loxosceles genus in the state of Paraná, Brazil, from 1993 to 2000. The incidence rate in the period was 290.24/100,000 inhabitants. The results show that 95.04% of the accidents occurred in two Health Regions of the state: greater metropolitan Curitiba (92.9%) and Irati (2.14%). The major incidence was recorded in greater metropolitan Curitiba (559.1/100,000). Loxosceles bites were more frequent in females (61%) than in males. Antivenin therapy was not necessary in 95.4% (19,662) of the cases. From the cases in which information about the time elapsed between the bite and medical treatment was recorded (9,679), 31.8% received treatment from 6 to 48 hours after the bite. Among the cases with severity rate recorded (12,096), 2.1% were severe, 50.4% moderate, and 47.4% mild. Seven deaths from Loxosceles bites were recorded, corresponding to a fatality rate of 0.03%.

The aim of this study was to study of the properties and characterization of conventional concrete and reinforced concrete with polypropylene fiber. Themes were theoretically addressed: concrete, composites, fibers, polypropylene fibers. In addition, practical tests were carried out, with test specimens of these two materials, of compressive strength, water absorption and heat resistance, to verify the differences in the properties of these two materials. The tests were completed and it can be noted that the application of the polypropylene fiber in the concrete as reinforcement for the concrete is satisfactory, because the water absorption test obtained similar results for the two materials, and performing the test of resistance to compression, it was observed that the test specimens with fiber, obtained better results than the conventional concrete. Finally, the heat resistance test showed that the fiber actually degrades in the temperature range informed by the supplier, being another advantage for its application in tunnels, in front of the fires.

The use of reflective surfaces offers one low-cost solution for reducing solar loading to urban environments and the Earth that should be considered as part of sustainable urban design. Here, we characterize the radiative benefits, i.e. the additional shortwave radiation leaving the atmosphere, from the installation of highly reflective ‘cool’ roofs in urban areas in India that face relatively large local aerosol burdens. We use a previously tested column radiative transfer model to estimate the energy per unit area reflected to space from increasing the surface albedo at six cities within India. The model is used to characterize radiative transfer each day over five years (2008–2012) based on mid-day satellite retrievals of MODIS aerosol depth, cloud water path, and average surface albedo and MERRA atmospheric profiles of temperature and composition. Compared against ten months of field observations in two cities, the model derived incoming surface shortwave radiation estimates relative to observations show small biases (0.5% and −2.6%, at Pantnagar and Nainital, respectively). Despite the high levels of local aerosols we found cool roofs provided significant radiative benefits at all locations. Averaged over the five year period we found that increasing the albedo of 1 m ^2 of roof area by 0.5 would reflect to space 0.9–1.2 kWh daily from 08:30–15:30 LST, depending on location. This is equivalent to a constant forcing of 37–50 W m ^−2 (equivalent to reducing CO _2 emissions by 74 to 101 kg CO _2 m ^−2 roof area). Last, we identify a co-benefit of improving air quality, in that removing aerosols from the atmosphere could increase the radiative benefits from cool roofs by 23–74%, with the largest potential increase found at Delhi and the smallest change found at Nainital.