Global climate carbon-cycle models predict acceleration of soil organic carbon losses to the atmosphere with warming, but the size of this feedback is poorly known. The temperature sensitivity of ...soil carbon decomposition is commonly determined by measuring changes in the rate of carbon dioxide (CO ₂) production under controlled laboratory conditions. We added measurements of carbon isotopes in respired CO ₂ to constrain the age of carbon substrates contributing to the temperature response of decomposition for surface soils from two temperate forest sites with very different overall rates of carbon cycling. Roughly one-third of the carbon respired at any temperature was fixed from the atmosphere more than 10 y ago, and the mean age of respired carbon reflected a mixture of substrates of varying ages. Consistent with global ecosystem model predictions, the temperature sensitivity of the carbon fixed more than a decade ago was the same as the temperature sensitivity for carbon fixed less than 10 y ago. However, we also observed an overall increase in the mean age of carbon respired at higher temperatures, even correcting for potential substrate limitation effects. The combination of several age constraints from carbon isotopes showed that warming had a similar effect on respiration of decades-old and younger (<10 y) carbon but a greater effect on decomposition of substrates of intermediate (between 7 and 13 y) age. Our results highlight the vulnerability of soil carbon to warming that is years-to-decades old, which makes up a large fraction of total soil carbon in forest soils globally.
The response of soil organic matter (OM) decomposition to increasing temperature is a critical aspect of ecosystem responses to global change. The impacts of climate warming on decomposition dynamics ...have not been resolved due to apparently contradictory results from field and lab experiments, most of which has focused on labile carbon with short turnover times. But the majority of total soil carbon stocks are comprised of organic carbon with turnover times of decades to centuries. Understanding the response of these carbon pools to climate change is essential for forecasting longer‐term changes in soil carbon storage. Herein, we briefly synthesize information from recent studies that have been conducted using a wide variety of approaches. In our effort to understand research to‐date, we derive a new conceptual model that explicitly identifies the processes controlling soil OM availability for decomposition and allows a more explicit description of the factors regulating OM decomposition under different circumstances. It explicitly defines resistance of soil OM to decomposition as being due either to its chemical conformation (quality) or its physico‐chemical protection from decomposition. The former is embodied in the depolymerization process, the latter by adsorption/desorption and aggregate turnover. We hypothesize a strong role for variation in temperature sensitivity as a function of reaction rates for both. We conclude that important advances in understanding the temperature response of the processes that control substrate availability, depolymerization, microbial efficiency, and enzyme production will be needed to predict the fate of soil carbon stocks in a warmer world.
Current carbon cycle-climate models predict that future soil carbon storage will be determined by the balance between CO2 fertilization and warming. However, it is uncertain whether greater carbon ...inputs to soils with elevated CO2 will be sequestered, particularly since warming hastens soil carbon decomposition rates, and may alter the response of soils to new plant inputs. We studied the effects of elevated CO2 and warming on microbial soil carbon decomposition processes using laboratory manipulations of carbon inputs and soil temperature. We incubated soils from the Aspen Free Air CO2 Enrichment experiment, where no accumulation of soil carbon has been observed despite a decade of increased carbon inputs to soils under elevated CO2. We added isotopically-labeled sucrose to these soils in the laboratory to mimic and trace the effects of increased carbon inputs on soil organic carbon decomposition and its temperature sensitivity. Sucrose additions caused a positive priming of soil organic carbon decomposition, demonstrated by increased respiration derived from soil carbon, increased microbial abundance, and a shift in the microbial community towards faster growing microorganisms. Similar patterns were observed for elevated CO2 soils, suggesting that the priming effect was responsible for reductions in soil carbon accumulation at the site. Laboratory warming accelerated the rate of the priming effect, but the magnitude of the priming effect was not different amongst temperatures, suggesting that the priming effect was limited by substrate availability, not soil temperature. No changes in substrate use efficiency were observed with elevated CO2 or warming. The stimulatory effects of warming on the priming effect suggest that increased belowground carbon inputs from CO2 fertilization are not likely to be stored in mineral soils.
Effects of elevated CO2 and warming on the soil carbon cycle. Display omitted
•Increased carbon inputs in laboratory cause a positive priming of SOC decomposition.•Increased carbon inputs to soil from 10 y of eCO2 similarly altered SOC decomposition.•Warming increased the rate, not amount, of SOC primed by increased carbon inputs.•Microbial substrate use efficiency for added sucrose was unchanged by eCO2 or warming.•The priming effect did not change the proportion of different ages of C in respiration.
California's methane super-emitters Duren, Riley M; Thorpe, Andrew K; Foster, Kelsey T ...
Nature (London),
11/2019, Letnik:
575, Številka:
7781
Journal Article
Recenzirano
Odprti dostop
Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide
. Unique opportunities for mitigation are presented by ...point-source emitters-surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane
. However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude
. Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes
. We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523-0.725), equivalent to 34-46 per cent of the state's methane inventory
for 2016. Methane 'super-emitter' activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions-consistent with a study of the US Four Corners region that had a different sectoral mix
. The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California's infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity
.
In this study, we test the performance of a compact gas chromatograph with photoionization detector (GC-PID) and optimize the configuration to detect ambient (sub-ppb) levels of benzene, toluene, ...ethylbenzene, and xylene isomers (BTEX). The GC-PID system was designed to serve as a relatively inexpensive (~10 k USD) and field-deployable air toxic screening tool alternative to conventional benchtop GCs. The instrument uses ambient air as a carrier gas and consists of a Tenax-GR sorbent-based preconcentrator, a gas sample valve, two capillary columns, and a photoionization detector (PID) with a small footprint and low power requirement. The performance of the GC-PID has been evaluated in terms of system linearity and sensitivity in field conditions. The BTEX-GC system demonstrated the capacity to detect BTEX at levels as high as 500 ppb with a linear calibration range of 0-100 ppb. A detection limit lower than 1 ppb was found for all BTEX compounds with a sampling volume of 1 L. No significant drift in the instrument was observed. A time-varying calibration technique was established that requires minimal equipment for field operations and optimizes the sampling procedure for field measurements. With an analysis time of less than 15 min, the compact GC-PID is ideal for field deployment of background and polluted atmospheres for near-real time measurements of BTEX. The results highlight the application of the compact and easily deployable GC-PID for community monitoring and screening of air toxics.
We report continuous surface observations of carbon dioxide (CO
) and methane (CH
) from the Los Angeles (LA) Megacity Carbon Project during 2015. We devised a calibration strategy, methods for ...selection of background air masses, calculation of urban enhancements, and a detailed algorithm for estimating uncertainties in urban-scale CO
and CH
measurements. These methods are essential for understanding carbon fluxes from the LA megacity and other complex urban environments globally. We estimate background mole fractions entering LA using observations from four "extra-urban" sites including two "marine" sites located south of LA in La Jolla (LJO) and offshore on San Clemente Island (SCI), one "continental" site located in Victorville (VIC), in the high desert northeast of LA, and one "continental/mid-troposphere" site located on Mount Wilson (MWO) in the San Gabriel Mountains. We find that a local marine background can be established to within ~1 ppm CO
and ~10 ppb CH
using these local measurement sites. Overall, atmospheric carbon dioxide and methane levels are highly variable across Los Angeles. "Urban" and "suburban" sites show moderate to large CO
and CH
enhancements relative to a marine background estimate. The USC (University of Southern California) site near downtown LA exhibits median hourly enhancements of ~20 ppm CO
and ~150 ppb CH
during 2015 as well as ~15 ppm CO
and ~80 ppb CH
during mid-afternoon hours (12:00-16:00 LT, local time), which is the typical period of focus for flux inversions. The estimated measurement uncertainty is typically better than 0.1 ppm CO
and 1 ppb CH
based on the repeated standard gas measurements from the LA sites during the last 2 years, similar to Andrews et al. (2014). The largest component of the measurement uncertainty is due to the single-point calibration method; however, the uncertainty in the background mole fraction is much larger than the measurement uncertainty. The background uncertainty for the marine background estimate is ~10 and ~15 % of the median mid-afternoon enhancement near downtown LA for CO
and CH
, respectively. Overall, analytical and background uncertainties are small relative to the local CO
and CH
enhancements; however, our results suggest that reducing the uncertainty to less than 5 % of the median mid-afternoon enhancement will require detailed assessment of the impact of meteorology on background conditions.
California's dairy sector accounts for ∼50% of anthropogenic CH
emissions in the state's greenhouse gas (GHG) emission inventory. Although California dairy facilities' location and herd size vary ...over time, atmospheric inverse modeling studies rely on decade-old facility-scale geospatial information. For the first time, we apply artificial intelligence (AI) to aerial imagery to estimate dairy CH
emissions from California's San Joaquin Valley (SJV), a region with ∼90% of the state's dairy population. Using an AI method, we process 316,882 images to estimate the facility-scale herd size across the SJV. The AI approach predicts herd size that strongly (>95%) correlates with that made by human visual inspection, providing a low-cost alternative to the labor-intensive inventory development process. We estimate SJV's dairy enteric and manure CH
emissions for 2018 to be 496-763 Gg/yr (mean = 624; 95% confidence) using the predicted herd size. We also apply our AI approach to estimate CH
emission reduction from anaerobic digester deployment. We identify 162 large (90th percentile) farms and estimate a CH
reduction potential of 83 Gg CH
/yr for these large facilities from anaerobic digester adoption. The results indicate that our AI approach can be applied to characterize the manure system (
, use of an anaerobic lagoon) and estimate GHG emissions for other sectors.
With global wildfires becoming more widespread and severe, tracking their emissions of greenhouse gases and air pollutants is becoming increasingly important. Wildfire emissions have primarily been ...characterized by in situ laboratory and field observations at fine scales. While this approach captures the mechanisms relating emissions to combustion phase and fuel properties, their evaluation on regional-scale plumes has been limited. In this study, we report remote observations of total column trace gases and aerosols during the 2020 wildfire season from smoke plumes in the Sierra Nevada of California with an EM27/SUN solar Fourier transform infrared (FTIR) spectrometer. We derive total column aerosol optical depth (AOD), emission factors (EFs) and modified combustion efficiency (MCE) for these fires and evaluate relationships between them, based on combustion phase at regional scales. We demonstrate that the EM27/SUN effectively detects changes in CO, CO2, and CH4 in the atmospheric column at ∼10 km horizontal scales that are attributed to wildfire emissions. These observations are used to derive total column EFCO of 120.5±12.2 and EFCH4 of 4.3±0.8 for a regional smoke plume event in mixed combustion phases. These values are consistent with in situ relationships measured in similar temperate coniferous forest wildfires. FTIR-derived AOD was compared to a nearby AERONET (AErosol RObotic NETwork) station and observed ratios of XCO to AOD were consistent with those previously observed from satellites. We also show that co-located XCO observations from the TROPOspheric Monitoring Instrument (TROPOMI) satellite-based instrument are 9.7±1.3 % higher than our EM27/SUN observations during the wildfire period. Finally, we put wildfire CH4 emissions in context of the California state CH4 budget and estimate that 213.7±49.8 Gg CH4 were emitted by large wildfires in California during 2020, about 13.7 % of the total state CH4 emissions in 2020. Our work demonstrates a novel application of the ground-based EM27/SUN solar spectrometers in wildfire monitoring by integrating regional-scale measurements of trace gases and aerosols from smoke plumes.
Methane (CH4), an important greenhouse gas and pollutant, has been targeted for mitigation. Our recent California airborne survey identified >500 CH4 point source super-emitters, which accounted for ...34%-46% of the statewide CH4 emissions inventory for 2016 (Duren et al 2019 Nature 575 180-184). Individual plumes were observed in close proximity to expected methane emitting infrastructure, including gas storage facilities, hydrocarbon storage tanks, landfills, dairy lagoons, and pipeline leaks. In order to systematically attribute these plumes to their sources, we developed Vista-CA a geospatial database, that contains more than 900 000 validated CH4 infrastructure elements in the state of California. In parallel, we developed a complimentary algorithm that attributes any individual CH4 plume observation to the most likely Vista-CA source with 99% accuracy. The present study illustrates the capabilities of the Vista-CA CH4 database along with the Airborne Visible/Infrared Imaging Spectrometer-Next Generation airborne CH4 retrievals to locate and attribute CH4 point sources to specific economic sectors to improve the state CH4 budget and identify mitigation targets.
Estimating methane (CH4) emission rates using quantitative CH4 retrievals from the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) requires the use of wind speeds. Model ...wind speeds have limited temporal and spatial resolution, meteorological station wind data are of variable quality and are often not available near observed plumes, and the use of ultrasonic anemometers co-located with methane sources is impractical for AVIRIS-NG flight campaigns with daily coverage of thousands of square kilometers. Given these limitations, this study focused on the use of the Twin Otter Doppler Wind Lidar (TODWL) to measure near surface winds and provide coincident measurements to CH4 plumes observed with AVIRIS-NG. In a controlled release experiment, TODWL observed wind speed and direction agreed well with ultrasonic anemometer measurements and CH4 emission rates derived from TODWL observations were more accurate than those using the ultrasonic anemometer or model winds during periods of stable winds. During periods exhibiting rapid shifts in wind speed and direction, estimating emission rates proved more challenging irrespective of the use of model, ultrasonic anemometer, or TODWL wind data. Overall, TODWL was able to provide reasonably accurate wind measurements and emission rate estimates despite the variable wind conditions and excessive flight level turbulence which impacted near surface measurement density. TODWL observed winds were also used to constrain CH4 emissions at a refinery, landfill, wastewater facility, and dairy digester. At these sites, TODWL wind measurements agreed well with wind observations from nearby meteorological stations, and when combined with quantitative CH4 plume imagery, yielded emission rate estimates that were similar to those obtained using model winds. This study demonstrates the utility of combining TODWL and AVIRIS-NG CH4 measurements and emphasizes the potential benefits of integrating both instruments on a single aircraft for future deployments.
•Airborne Doppler Wind Lidar (ADWL) and AVIRIS-NG used to estimate methane emissions•Emissions characterized for controlled release and multiple emission sectors•ADWL winds agreed closely with ultrasonic anemometer and meteorological stations•ADWL derived emissions sometimes more accurate than using anemometer/modelled winds•Integrating both instruments on single aircraft would reduce emission uncertainty
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