Application of Gauss's theorem to quantify localized surface emissions from airborne measurements of wind and trace gases

Airborne estimates of greenhouse gas emissions are becoming more prevalent with the advent of rapid commercial development of trace gas instrumentation featuring increased measurement accuracy, precision, and frequency, and the swelling interest in the verification of current emission inventories. Multiple airborne studies have indicated that emission inventories may underestimate some hydrocarbon emission sources in US oil- and gas-producing basins. Consequently, a proper assessment of the accuracy of these airborne methods is crucial to interpreting the meaning of such discrepancies. We present a new method of sampling surface sources of any trace gas for which fast and precise measurements can be made and apply it to methane, ethane, and carbon dioxide on spatial scales of  ∼ 1000 m, where consecutive loops are flown around a targeted source region at multiple altitudes. Using Reynolds decomposition for the scalar concentrations, along with Gauss's theorem, we show that the method accurately accounts for the smaller-scale turbulent dispersion of the local plume, which is often ignored in other average mass balance methods. With the help of large eddy simulations (LES) we further show how the circling radius can be optimized for the micrometeorological conditions encountered during any flight. Furthermore, by sampling controlled releases of methane and ethane on the ground we can ascertain that the accuracy of the method, in appropriate meteorological conditions, is often better than 10 %, with limits of detection below 5 kg h−1 for both methane and ethane. Because of the FAA-mandated minimum flight safe altitude of 150 m, placement of the aircraft is critical to preventing a large portion of the emission plume from flowing underneath the lowest aircraft sampling altitude, which is generally the leading source of uncertainty in these measurements. Finally, we show how the accuracy of the method is strongly dependent on the number of sampling loops and/or time spent sampling the source plume

Comparison of global inventories of CO emissions from biomass burning derived from remotely sensed data

We compare five global inventories of monthly CO emissions named VGT, ATSR, MODIS, GFED3 and MOPITT based on remotely sensed active fires and/or burned area products for the year 2003. The objective is to highlight similarities and differences by focusing on the geographical and temporal distribution and on the emissions for three broad land cover classes (forest, savanna/grassland and agriculture). Globally, CO emissions for the year 2003 range between 365 Tg CO (GFED3) and 1422 Tg CO (VGT). Despite the large uncertainty in the total amounts, some common spatial patterns typical of biomass burning can be identified in the boreal forests of Siberia, in agricultural areas of Eastern Europe and Russia and in savanna ecosystems of South America, Africa and Australia. Regionally, the largest difference in terms of total amounts (CV > 100%) and seasonality is observed at the northernmost latitudes, especially in North America and Siberia where VGT appears to overestimate the area affected by fires. On the contrary, Africa shows the best agreement both in terms of total annual amounts (CV = 31%) and of seasonality despite some overestimation of emissions from forest and agriculture observed in the MODIS inventory. In Africa VGT provides the most reliable seasonality. Looking at the broad land cover types, the range of contribution to the global emissions of CO is 64–74%, 23–32% and 3–4% for forest, savanna/grassland and agriculture, respectively. These results suggest that there is still large uncertainty in global estimates of emissions and it increases if the comparison is carried by out taking into account the temporal (month) and spatial (0.5° × 0.5° cell) dimensions. Besides the area affected by fires, also vegetation characteristics and conditions at the time of burning should also be accurately parameterized since they can greatly influence the global estimates of CO emissions

Measurements of hydrogen sulfide (H2S) using PTR-MS: Calibration, humidity dependence, inter-comparison and results from field studies in an oil and gas production region

Natural gas production is associated with emissions of several trace gases, some of them classified as air toxics. While volatile organic compounds (VOCs) have received much attention, hydrogen sulfide (H2S) can also be of concern due to the known health impacts of exposure to this hazardous air pollutant. Here, we present quantitative, fast time-response measurements of H2S using proton-transfer-reaction mass-spectrometry (PTR-MS) instruments. An ultra-light-weight PTR-MS (ULW-PTR-MS) in a mobile laboratory was operated for measurements of VOCs and H2S in a gas and oil field during the Uintah Basin Winter Ozone Study (UBWOS) 2012 campaign. Measurements of VOCs and H2S by a PTR-MS were also made at the Horse Pool ground site in the Uintah Basin during UBWOS 2013. The H2S measurement by PTR-MS is strongly humidity dependent because the proton affinity of H2S is only slightly higher than that of water. The H2S sensitivity of PTR-MS ranged between 0.6–1.4 ncps ppbv−1 during UBWOS 2013. We compare the humidity dependence determined in the laboratory with in-field calibrations and determine the H2S mixing ratios for the mobile and ground measurements. The PTR-MS measurements at Horse Pool are evaluated by comparison with simultaneous H2S measurements using a PTR time-of-flight MS (PTR-ToF-MS) and a Picarro cavity ring down spectroscopy (CRDS) instrument for H2S / CH4. On average 0.6 ± 0.3 ppbv H2S was present at Horse Pool during UBWOS 2013. The correlation between H2S and methane enhancements suggests that the source of H2S is associated with oil and gas extraction in the basin. Significant H2S mixing ratios of up to 9 ppmv downwind of storage tanks were observed during the mobile measurements. This study suggests that H2S emissions associated with oil and gas production can lead to short-term high levels close to point sources, and elevated background levels away from those sources. In addition, our work has demonstrated that PTR-MS can make reliable measurements of H2S at levels below 1 ppbv

The Chemistry Mechanism in the Community Earth System Model Version 2 (CESM2)

The Community Earth System Model version 2 (CESM2) includes a detailed representation of chemistry throughout the atmosphere in the Community Atmosphere Model with chemistry and Whole Atmosphere Community Climate Model configurations. These model configurations use the Model for Ozone and Related chemical Tracers (MOZART) family of chemical mechanisms, covering the troposphere, stratosphere, mesosphere, and lower thermosphere. The new MOZART tropospheric chemistry scheme (T1) has a number of updates over the previous version (MOZART‐4) in CESM, including improvements to the oxidation of isoprene and terpenes, organic nitrate speciation, and aromatic speciation and oxidation and thus improved representation of ozone and secondary organic aerosol precursors. An evaluation of the present‐day simulations of CESM2 being provided for Climate Model Intercomparison Project round 6 (CMIP6) is presented. These simulations, using the anthropogenic and biomass burning emissions from the inventories specified for CMIP6, as well as online calculation of emissions of biogenic compounds, lightning NO, dust, and sea salt, indicate an underestimate of anthropogenic emissions of a variety of compounds, including carbon monoxide and hydrocarbons. The simulation of surface ozone in the southeast United States is improved over previous model versions, largely due to the improved representation of reactive nitrogen and organic nitrate compounds resulting in a lower ozone production rate than in CESM1 but still overestimates observations in summer. The simulation of tropospheric ozone agrees well with ozonesonde observations in many parts of the globe. The comparison of NOx and PAN to aircraft observations indicates the model simulates the nitrogen budget well

Contribution of isoprene to chemical budgets:A model tracer study with the NCAR CTM MOZART-4

We present a study of the sensitivity of isoprene emission calculations in a global chemistry transport model (CTM) to input land cover characteristics and analyze the impacts of changes in isoprene on the tropospheric budgets of atmospheric key species. The CTM Model for Ozone and Related Chemical Species, version 4 (MOZART-4) includes the online calculation of isoprene emissions based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN), which is driven by three different land parameter inputs. We also included a tagging scheme in the CTM, which keeps track of the production of carbon containing species from isoprene oxidation. It is found that the amount of tropospheric carbon monoxide (CO), formaldehyde (HCHO) and peroxyacetylnitrate (PAN) explained by isoprene oxidation ranges from 9-16%, 15-27%, and 22-32%, depending on the isoprene emissions scenario. Changes in the global tropospheric burden with different land cover inputs can reach up to 10% for CO, 15% for HCHO, and 20% for PAN. Changes for ozone are small on a global scale, but regionally differences are as large as 3DU in the tropospheric column and as large as 5 ppbv in the surface concentrations. Our results demonstrate that a careful integration of isoprene emissions and chemistry in CTMs is very important for simulating the budgets of a number of atmospheric trace gases. We further demonstrate that the model tagging scheme has the capability of improving conventional methods of constraining isoprene emissions from space-borne HCHO column observations, especially in regions where a considerable part of the variability in the HCHO column is not related to isoprene. Copyright 2008 by the American Geophysical Union

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Despite the consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass, and remote detection of fire hotspots and burned area. Here, we use 16 years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon Basin between 2003 and 2018. Through data assimilation, we produce 3 d average maps of fire CO emissions over the Amazon, which we verified to be consistent with a long-term monitoring programme of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than 4-fold increase in basin-wide fire emissions relative to wet years. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon Basin between 2019 and 2021

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Despite consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass as well as remote detection of fire hotspots, and burned area. Here, we use sixteen years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon basin between 2003 and 2018. Through data assimilation, we produce 3-daily maps of fire CO emissions over the Amazon that we verified to be consistent with a long-term monitoring program of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than fourfold increase in basin-wide fire emissions. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon basin in 2019&ndash;2021.</p

Impact of CO2 measurement bias on CarbonTracker surface flux estimates

For over 20 years, atmospheric measurements of CO2 dry air mole fractions have been used to derive estimates of CO2 surface fluxes. Historically, only a few research laboratories made these measurements. Today, many laboratories are making CO2 observations using a variety of analysis techniques and, in some instances, using different calibration scales. As a result, the risk of biases in individual CO2 mole fraction records, or even in complete monitoring networks, has increased over the last decades. Ongoing experiments comparing independent, well-calibrated measurements of atmospheric CO2 show that biases can and do exist between measurement records. Biases in measurements create artificial spatial and temporal CO2 gradients, which are then interpreted by an inversion system, leading to erroneous flux estimates. Here we evaluate the impact of a constant bias introduced into the National Oceanic and Atmospheric Administration (NOAA) quasi-continuous measurement record at the Park Falls, Wisconsin (LEF), tall tower site on CarbonTracker flux estimates. We derive a linear relationship between the magnitude of the introduced bias at LEF and the CarbonTracker surface flux responses. Temperate North American net flux estimates are most sensitive to a bias at LEF in our CarbonTracker inversion, and its linear response rate is 68 Tg C yr-1 (~10% of the estimated North American annual terrestrial uptake) for every 1 ppm of bias in the LEF record. This sensitivity increases when (1) measurement biases approached assumed model errors and (2) fewer other measurement records are available to anchor the flux estimates despite the presence of bias in one record. Flux estimate errors are also calculated beyond North America. For example, biospheric uptake in Europe and boreal Eurasia combined increases by 25 Tg C yr-1 per ppm CO2 to partially compensate for changes in the North American flux totals. These results illustrate the importance of well-calibrated, high-precision CO2 dry air mole fraction measurements, as well as the value of an effective strategy for detecting bias in measurements. This study stresses the need for a monitoring network with the necessary density to anchor regional, continental, and hemispheric fluxes more tightly and to lessen the impact of potentially undetected biases in observational networks operated by different national and international research programs