Identifying fire plumes in the Arctic with tropospheric FTIR measurements and transport models

We investigate Arctic tropospheric composition using ground-based Fourier transform infrared (FTIR) solar absorption spectra, recorded at the Polar Environment Atmospheric Research Laboratory (PEARL, Eureka, Nunavut, Canada, 80°05' N, 86°42' W) and at Thule (Greenland, 76°53' N, −68°74' W) from 2008 to 2012. The target species, carbon monoxide (CO), hydrogen cyanide (HCN), ethane (C_2H_6), acetylene (C_2H_2), formic acid (HCOOH), and formaldehyde (H_2CO) are emitted by biomass burning and can be transported from mid-latitudes to the Arctic. By detecting simultaneous enhancements of three biomass burning tracers (HCN, CO, and C_2H_6), ten and eight fire events are identified at Eureka and Thule, respectively, within the 5-year FTIR time series. Analyses of Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model back-trajectories coupled with Moderate Resolution Imaging Spectroradiometer (MODIS) fire hotspot data, Stochastic Time-Inverted Lagrangian Transport (STILT) model footprints, and Ozone Monitoring Instrument (OMI) UV aerosol index maps, are used to attribute burning source regions and travel time durations of the plumes. By taking into account the effect of aging of the smoke plumes, measured FTIR enhancement ratios were corrected to obtain emission ratios and equivalent emission factors. The means of emission factors for extratropical forest estimated with the two FTIR data sets are 0.40 ± 0.21 g kg^(−1) for HCN, 1.24 ± 0.71 g kg^(−1) for C_2H_6, 0.34 ± 0.21 g kg^(−1) for C_2H_2, and 2.92 ± 1.30 g kg^(−1) for HCOOH. The emission factor for CH_3OH estimated at Eureka is 3.44 ± 1.68 g kg^(−1). To improve our knowledge concerning the dynamical and chemical processes associated with Arctic pollution from fires, the two sets of FTIR measurements were compared to the Model for OZone And Related chemical Tracers, version 4 (MOZART-4). Seasonal cycles and day-to-day variabilities were compared to assess the ability of the model to reproduce emissions from fires and their transport. Good agreement in winter confirms that transport is well implemented in the model. For C_2H_6, however, the lower wintertime concentration estimated by the model as compared to the FTIR observations highlights an underestimation of its emission. Results show that modeled and measured total columns are correlated (linear correlation coefficient r > 0.6 for all gases except for H_2CO at Eureka and HCOOH at Thule), but suggest a general underestimation of the concentrations in the model for all seven tropospheric species in the high Arctic

Assessment of errors and biases in retrievals of X_(CO2), X_(CH4), X_(CO), and X_(N2O) from a 0.5 cm^(-1) resolution solar-viewing spectrometer

Bruker™ EM27/SUN instruments are commercial mobile solar-viewing near-IR spectrometers. They show promise for expanding the global density of atmospheric column measurements of greenhouse gases and are being marketed for such applications. They have been shown to measure the same variations of atmospheric gases within a day as the high-resolution spectrometers of the Total Carbon Column Observing Network (TCCON). However, there is little known about the long-term precision and uncertainty budgets of EM27/SUN measurements. In this study, which includes a comparison of 186 measurement days spanning 11 months, we note that atmospheric variations of X_(gas) within a single day are well captured by these low-resolution instruments, but over several months, the measurements drift noticeably. We present comparisons between EM27/SUN instruments and the TCCON using GGG as the retrieval algorithm. In addition, we perform several tests to evaluate the robustness of the performance and determine the largest sources of errors from these spectrometers. We include comparisons of X_(CO2), X_(CH4), X_(CO), and X_(N2)O. Specifically we note EM27/SUN biases for January 2015 of 0.03, 0.75, –0.12, and 2.43 % for X_(CO2), X_(CH4), X_(CO), and X_(N2)O respectively, with 1σ running precisions of 0.08 and 0.06 % for X_(CO2) and X_(CH4) from measurements in Pasadena. We also identify significant error caused by nonlinear sensitivity when using an extended spectral range detector used to measure CO and N_2O

NH3 spatiotemporal variability over Paris, Mexico City, and Toronto, and its link to PM2.5 during pollution events

Megacities can experience high levels of fine particulate matter (PM2.5) pollution linked to ammonia (NH3) mainly emitted from agricultural activities. Here, we investigate such pollution in the cities of Paris, Mexico, and Toronto, each of which have distinct emission sources, agricultural regulations, and topography. Ten years of measurements from the infrared atmospheric sounding interferometer (IASI) are used to assess the spatiotemporal NH3 variability over and around the three cities. In Europe and North America, we determine that temperature is associated with the increase in NH3 atmospheric concentrations with a coefficient of determination (r2) of 0.8 over agricultural areas. The variety of the NH3 sources (industry and agricultural) and the weaker temperature seasonal cycle in southern North America induce a lower correlation factor (r2=0.5). The three regions are subject to long-range transport of NH3, as shown using HYSPLIT cluster back trajectories. The highest NH3 concentrations measured at the city scale are associated with air masses coming from the surrounding and north/northeast regions of Paris, the south/southwest areas of Toronto, and the southeast/southwest zones of Mexico City. Using NH3 and PM2.5 measurements derived from IASI and surface observations from 2008 to 2017, annually frequent pollution events are identified in the three cities. Wind roses reveal statistical patterns during these pollution events with dominant northeast/southwest directions in Paris and Mexico City, and the transboundary transport of pollutants from the United States in Toronto. To check how well chemistry transport models perform during pollution events, we evaluate simulations made using the GEOS-Chem model for March 2011. In these simulations we find that NH3 concentrations are underestimated overall, though day-to-day variability is well represented. PM2.5 is generally underestimated over Paris and Mexico City, but overestimated over Toronto.</p

Intercomparability of X_(CO_2) and X_(CH_4) from the United States TCCON sites

The Total Carbon Column Observing Network (TCCON) has become the standard for long-term column-averaged measurements of CO_2 and CH_4. Here, we use a pair of portable spectrometers to test for intra-network bias among the four currently operating TCCON sites in the United States (US). A previous analytical error analysis has suggested that the maximum 2σ site-to-site relative (absolute) bias of TCCON should be less than 0.2% (0.8ppm) in X_(CO_2) and 0.4% (7ppb) in X_(CH_4). We find here experimentally that the 95% confidence intervals for maximum pairwise site-to-site bias among the four US TCCON sites are 0.05–0.14% for X_(CO_2) and 0.08–0.24% for X_(CH_4). This is close to the limit of the bias we can detect using this methodology

Methane emissions from dairies in the Los Angeles Basin

We estimate the amount of methane (CH_4) emitted by the largest dairies in the southern California region by combining measurements from four mobile solar-viewing ground-based spectrometers (EM27/SUN), in situ isotopic ^(13∕12)CH_4 measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport simulation with a Weather Research and Forecasting model in large-eddy simulation mode (WRF-LES). The remote sensing spectrometers measure the total column-averaged dry-air mole fractions of CH_4 and CO_2 (X_(CH)_4 and X_(CO)_2) in the near infrared region, providing information on total emissions of the dairies at Chino. Differences measured between the four EM27/SUN ranged from 0.2 to 22 ppb (part per billion) and from 0.7 to 3 ppm (part per million) for X_(CH)_4 and X_(CO)_2, respectively. To assess the fluxes of the dairies, these differential measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111 m resolution. Our top-down CH_4 emissions derived using the Fourier transform spectrometers (FTS) observations of 1.4 to 4.8 ppt s^(−1) are in the low end of previous top-down estimates, consistent with reductions of the dairy farms and urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by the heterogeneity of the sources and meteorology. Inverse modeling from WRF-LES is utilized to resolve the spatial distribution of CH_4 emissions in the domain. Both the model and the measurements indicate heterogeneous emissions, with contributions from anthropogenic and biogenic sources at Chino. A Bayesian inversion and a Monte Carlo approach are used to provide the CH_4 emissions of 2.2 to 3.5 ppt s^(−1) at Chino

A roadmap to estimating agricultural ammonia volatilization over Europe using satellite observations and simulation data

Ammonia (NH3) is one of the most important gases emitted from agricultural practices. It affects air quality and the overall climate and is in turn influenced by long-term climate trends as well as by short-term fluctuations in local and regional meteorology. Previous studies have established the capability of the Infrared Atmospheric Sounding Interferometer (IASI) series of instruments, aboard the Metop satellites, to measure ammonia from space since 2007. In this study, we explore the interactions between atmospheric ammonia, land and meteorological variability, and long-term climate trends in Europe. We investigate the emission potential (Γsoil) of ammonia from the soil, which describes the soil–atmosphere ammonia exchange. Γsoil is generally calculated in-field or in laboratory experiments; here, and for the first time, we investigate a method which assesses it remotely using satellite data, reanalysis data products, and model simulations. We focus on ammonia emission potential in March 2011, which marks the start of growing season in Europe. Our results show that Γsoil ranges from 2 × 103 to 9.5 × 104 (dimensionless) in fertilized cropland, such as in the North European Plain, and is of the order of 10–102 in a non-fertilized soil (e.g., forest and grassland). These results agree with in-field measurements from the literature, suggesting that our method can be used in other seasons and regions in the world. However, some improvements are needed in the determination of mass transfer coefficient k (m s−1), which is a crucial parameter to derive Γsoil. Using a climate model, we estimate the expected increase in ammonia columns by the end of the century based on the increase in skin temperature (Tskin), under two different climate scenarios. Ammonia columns are projected to increase by up to 50 %, particularly in eastern Europe, under the SSP2-4.5 scenario and might even double (increase of 100 %) under the SSP5-8.5 scenario. The increase in skin temperature is responsible for a formation of new hotspots of ammonia in Belarus, Ukraine, Hungary, Moldova, parts of Romania, and Switzerland.</p

Human SNP links differential outcomes in inflammatory and infectious disease to a FOXO3-Regulated Pathway

The clinical course and eventual outcome, or prognosis, of complex diseases varies enormously between affected individuals. This variability critically determines the impact a disease has on a patient’s life but is very poorly understood. Here, we exploit existing genome-wide association study data to gain insight into the role of genetics in prognosis. We identify a noncoding polymorphism in FOXO3A (rs12212067: T > G) at which the minor (G) allele, despite not being associated with disease susceptibility, is associated with a milder course of Crohn’s disease and rheumatoid arthritis and with increased risk of severe malaria. Minor allele carriage is shown to limit inflammatory responses in monocytes via a FOXO3-driven pathway, which through TGFb1 reduces production of proinflammatory cytokines, including TNFa, and increases production of anti-inflammatory cytokines, including IL-10. Thus, we uncover a shared genetic contribution to prognosis in distinct diseases that operates via a FOXO3-driven pathway modulating inflammatory responses

Human SNP links differential outcomes in inflammatory and infectious disease to a FOXO3-regulated pathway

The clinical course and eventual outcome, or prognosis, of complex diseases varies enormously between affected individuals. This variability critically determines the impact a disease has on a patient’s life but is very poorly understood. Here, we exploit existing genome-wide association study data to gain insight into the role of genetics in prognosis. We identify a noncoding polymorphism in FOXO3A (rs12212067: T > G) at which the minor (G) allele, despite not being associated with disease susceptibility, is associated with a milder course of Crohn’s disease and rheumatoid arthritis and with increased risk of severe malaria. Minor allele carriage is shown to limit inflammatory responses in monocytes via a FOXO3-driven pathway, which through TGFβ1 reduces production of proinflammatory cytokines, including TNFα, and increases production of anti-inflammatory cytokines, including IL-10. Thus, we uncover a shared genetic contribution to prognosis in distinct diseases that operates via a FOXO3-driven pathway modulating inflammatory responses. PAPERCLIP

Differential column measurements using compact solar-tracking spectrometers

We demonstrate the use of compact solar-tracking Fourier transform spectrometers (Bruker EM27/SUN) for differential measurements of the column-averaged dry-air mole fractions of CH_4 and CO_2 within urban areas. Using Allan variance analysis, we show that the differential column measurement has a precision of 0.01 % for X_(CO_2) and X_(CH_4) with an optimum integration time of 10 min, corresponding to Allan deviations of 0.04 ppm and 0.2 ppb,respectively. The sensor system is very stable over time and after relocation across the continent. We report tests of the differential column measurement,and its sensitivity to emission sources, by measuring the downwind-minus-upwind column difference ΔX_(CH_4) across dairy farms in the Chino area, California, and using the data to verify emissions reported in the literature. Ratios of spatial column differences ΔX_(CH_4)∕ΔX_(CO_2) were observed across Pasadena within the Los Angeles basin, indicating values consistent with regional emission ratios from the literature. Our precise, rapid measurements allow us to determine significant short-term variations (5–10 min) of X_(CO_2) and X_(CH_4) and to show that they represent atmospheric phenomena. Overall, this study helps establish a range of new applicationsfor compact solar-viewing Fourier transform spectrometers. Byaccurately measuring the small differences in integrated column amounts acrosslocal and regional sources, we directly observe the mass loadingof the atmosphere due to the influence of emissions in theintervening locale. The inference of the source strength is muchmore direct than inversion modeling using only surface concentrationsand less subject to errors associated with small-scale transportphenomena