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Ammonia (NH3) is a key precursor to fine particulate matter (PM2.5) and a primary form of reactive nitrogen. The limited observations of NH3 hinders further understanding of its impacts on air quality, climate, and biodiversity. Currently, NH3 ground monitoring networks are limited in number across the globe, and even in the most established networks, large spatial gaps exist between sites and only a few sites have records that span longer than a decade. Satellite NH3 observations can be used to discern trends and fill spatial gaps in networks, but many factors influence the syntheses of the vastly different spatiotemporal scales between surface networks and satellite measurements. To this end, we intercompared surface NH3 data from the Ammonia Monitoring Network (AMoN) and satellite NH3 total columns from the Infrared Atmospheric Sounding Interferometer (IASI) in the contiguous United States (CONUS) and then performed trend analyses using both datasets. We explored the sensitivity of correlations between the two datasets to factors such as satellite data availability and distribution over the surface measurement period as well as agreement within selected spatial and temporal windows. Given the short lifetime of atmospheric ammonia and consequently sharp gradients, smaller spatial windows show better agreement than larger ones except in areas of relatively uniform, low concentrations where large windows and more satellite measurements improve the signal-to-noise ratio. A critical factor in the comparison is having satellite measurements across most of the measurement period of the monitoring site. When IASI data are available for at least 80 % days of AMoN’s 2-week sampling period within a 25 km spatial window of a given site, IASI NH3 column concentrations and the AMoN NH3 surface concentrations have a correlation of 0.74, demonstrating the feasibility of using satellite NH3 columns to bridge the spatial gaps existing in the surface network NH3 concentrations. Both IASI and AMoN show increasing NH3 concentrations across CONUS (median: 6.8 % · yr−1 vs. 6.7 % · yr−1) in the last decade (2008–2018), stressing the rising importance of NH3 in terms of nitrogen deposition. NH3 trends for AMoN sites correlates with IASI NH3 trend IASI and AMoN NH3 trend (r = 0.66) and show a similar spatial pattern, with the highest increases in the Midwest and eastern U.S., and NH3 trend for AMoN sites correlates with IASI NH3 trend (r = 0.66). In spring and summer, increases of NH3 were larger than 10 % · yr−1 in the eastern U.S. and Midwest (cropland dominated) and western U.S. (pastureland dominated), respectively. In terms of trend in NH3 hotpots (defined as regions where the IASI NH3 column is larger than the 95th percentile of 11-year CONUS map, 6.7 × 1015 molec/cm2), these largest emissions sources are also experiencing increasing concentrations over time with the median of NH3 trend is 4.7 % · yr−1. IASI data show large NH3 increases in urban areas (8.1 % · yr−1), including 8 of the top 10 most populous regions in the CONUS, where AMoN sites are sparse. The increasing NH3 could have detrimental effects on nearby eco-sensitive regions through nitrogen deposition and on aerosol chemistry in the densely populated urban areas, hence needs immediate attention.

Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large scale, intensive agricultural activities, which are often accompanied by greater use of fertilizers and concentrated animal feedlots. Ammonia is highly reactive, and thus highly variable and difficult to measure. Satellite based instruments, such as the Atmospheric Infrared Sounder (AIRS), and the Cross-Track Infrared Sounder (CrIS) sensors, have been shown to provide much greater temporal and spatial coverage of ammonia distribution and variability than is possible with in situ networks or aircraft campaigns, but the validation of these data is limited. Here we evaluate ammonia retrievals from AIRS and CrIS against ammonia measurements from aircraft in the California Central Valley and in the Colorado Front Range. The satellite datasets were small and in California were obtained under difficult conditions. We show that the surface values of the retrieved profiles are biased very low in California and slightly high in Colorado, and that the bias appears to be primarily due to smoothing error. We also compare three years of CrIS ammonia against an in situ network in the Magic Valley in Idaho We show that CrIS ammonia captures both the seasonal signal and the spatial variability in the Magic Valley, though it is biased low here also. In summary, analysis adds to the validation record but also points to the need for more validation under different conditions.

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016–2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter 2.5) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Elevated reactive nitrogen (Nr) deposition is a concern for alpine ecosystems, and dry NH3 deposition is a key contributor. Understanding how emission hotspots impact downwind ecosystems through dry NH3 deposition provides opportunities for effective mitigation. However, direct NH3 flux measurements with sufficient temporal resolution to quantify such events are rare. Here, we measured NH3 fluxes at Rocky Mountain National Park (RMNP) during two summers and analyzed transport events from upwind agricultural and urban sources in northeastern Colorado. We deployed open-path NH3 sensors on a mobile laboratory and an eddy covariance tower to measure NH3 concentrations and fluxes. Our spatial sampling illustrated an upslope event that transported NH3 emissions from the hotspot to RMNP. Observed NH3 deposition was significantly higher when backtrajectories passed through only the agricultural region (7.9 ng m–2 s–1) versus only the urban area (1.0 ng m–2 s–1) and both urban and agricultural areas (2.7 ng m–2 s–1). Cumulative NH3 fluxes were calculated using observed, bidirectional modeled, and gap-filled fluxes. More than 40% of the total dry NH3 deposition occurred when air masses were traced back to agricultural source regions. More generally, we identified that 10 (25) more national parks in the U.S. are within 100 (200) km of an NH3 hotspot, and more observations are needed to quantify the impacts of these hotspots on dry NH3 deposition in these regions.

China’s gains in food production over the past four decades have been associated with substantial agricultural nitrogen losses, which contribute to air and water pollution, greenhouse gas emissions and damage to human health. Here, we explore the potential to improve agricultural production practices that simultaneously increase yields while addressing these environmental challenges. We link agronomic research with air quality modelling for an integrated assessment of four improved nitrogen management strategies: improved farm management practices with nitrogen use reductions; machine deep placement of fertilizer; enhanced-efficiency fertilizer use; and improved manure management. We find that simultaneous implementation of the four strategies provides the largest benefits, which include: reductions in PM2.5 concentrations and associated premature deaths; increases in grain yields and grain nitrogen use efficiency; reductions in NO3− leaching and runoff and greenhouse gas emissions. Total benefits of US$30 billion per year exceed the US$18 billion per year in costs. Our findings indicate that policies that improve farmers’ agricultural nitrogen management in China will improve both food security and public health while addressing multiple environmental challenges. Similar increases in attention on agricultural policy around the world are likely to provide large benefits in food security, environmental integrity and public health. Nitrogen use has increased food security in China but also poses environmental problems. Agricultural nitrogen management strategies are identified for China that will improve food security and public health while addressing multiple environmental challenges.

Low-power, open-path gas sensors enable eddy covariance (EC) flux measurements in remote areas without line power. However, open-path flux measurements are sensitive to fluctuations in air temperature, pressure, and humidity. Laser-based, open-path sensors with the needed sensitivity for trace gases like methane (CH4 ) and nitrous oxide (N2 O) are impacted by additional spectroscopic effects. Corrections for these effects, especially those related to temperature fluctuations, often exceed the flux of gases, leading to large uncertainties in the associated fluxes. For example, the density and spectroscopic corrections arising from temperature fluctuations can be one or two orders of magnitude greater than background N2 O fluxes. Consequently, measuring background fluxes with laser-based, open-path sensors is extremely challenging, particularly for N2 O and gases with similar high-precision requirements. We demonstrate a new laser-based, open-path N2 O sensor and a general approach applicable to other gases that minimizes temperature-related corrections for EC flux measurements. The method identifies absorption lines with spectroscopic effects in the opposite direction of density effects from temperature and, thus, density and spectroscopic effects nearly cancel one another. The new open-path N2 O sensor was tested at a corn (Zea mays L.) field in Southwestern Michigan, United States. The sensor had an optimal precision of 0.1 ppbv at 10 Hz and power consumption of 50 W. Field trials showed that temperature-related corrections were 6% of density corrections, reducing EC random errors by 20-fold compared to previously examined lines. Measured open-path N2 O EC fluxes showed excellent agreement with those made with static chambers (m = 1.0 ± 0.3; r2 = .96). More generally, we identified absorption lines for CO2 and CH4 flux measurements that can reduce the temperature-related corrections by 10-100 times compared to existing open-path sensors. The proposed method provides a new direction for future open-path sensors, facilitating the expansion of accurate EC flux measurements.

A large-scale study of methane emissions from well pads was conducted in the Marcellus shale (Pennsylvania), the largest producing natural gas shale play in the United States, to better identify the prevalence and characteristics of superemitters. Roughly 2100 measurements were taken from 673 unique unconventional well pads corresponding to ∼18% of the total population of active sites and ∼32% of the total statewide unconventional natural gas production. A log-normal distribution with a geometric mean of 2.0 kg h-1 and arithmetic mean of 5.5 kg h-1 was observed, which agrees with other independent observations in this region. The geometric standard deviation (4.4 kg h-1) compared well to other studies in the region, but the top 10% of emitters observed in this study contributed 77% of the total emissions, indicating an extremely skewed distribution. The integrated proportional loss of this representative sample was equal to 0.53% with a 95% confidence interval of 0.45-0.64% of the total production of the sites, which is greater than the U.S. Environmental Protection Agency inventory estimate (0.29%), but in the lower range of other mobile observations (0.09-3.3%). These results emphasize the need for a sufficiently large sample size when characterizing emissions distributions that contain superemitters.

Satellite remote sensing of the Earth's atmospheric composition usually samples irregularly in space and time, and many applications require spatially and temporally averaging the satellite observations (level 2) to a regular grid (level 3). When averaging level 2 data over a long period to a target level 3 grid that is significantly finer than the sizes of level 2 pixels, this process is referred to as. An agile, physics-based oversampling approach is developed to represent each satellite observation as a sensitivity distribution on the ground, instead of a point or a polygon as assumed in previous methods. This sensitivity distribution can be determined by the spatial response function of each satellite sensor. A generalized 2-D super Gaussian function is proposed to characterize the spatial response functions of both imaging grating spectrometers (e.g. OMI, OMPS, and TROPOMI) and scanning Fourier transform spectrometers (e.g. GOSAT, IASI, and CrIS). Synthetic OMI and IASI observations were generated to compare the errors due to simplifying satellite fields of view (FOVs) as polygons (tessellation error) and the errors due to discretizing the smooth spatial response function on a finite grid (discretization error). The balance between these two error sources depends on the target grid size, the ground size of the FOV, and the smoothness of spatial response functions. Explicit consideration of the spatial response function is favorable for fine-grid oversampling and smoother spatial response. For OMI, it is beneficial to oversample using the spatial response functions for grids finer than ∼ 16 km. The generalized 2-D super Gaussian function also enables smoothing of the level 3 results by decreasing the shape-determining exponents, which is useful for a high noise level or sparse satellite datasets. This physical oversampling approach is especially advantageous during smaller temporal windows and shows substantially improved visualization of trace gas distribution and local gradients when applied to OMI NO2 products and IASI NH3 products. There is no appreciable difference in the computational time when using the physical oversampling versus other oversampling methods., SCOPUS: ar.j, info:eu-repo/semantics/published

We present a methane sensing system based on chirped laser dispersion spectroscopy. The system is capable of actively tracking a drone-based retroreflector at up to 40m distance. The system has also shown sensitivities of 2.3 ppm-m.

Monthly, high-resolution (∼2 km) ammonia (NH3) column maps from the Infrared Atmospheric Sounding Interferometer (IASI) were developed across the contiguous United States and adjacent areas. Ammonia hotspots (95th percentile of the column distribution) were highly localized with a characteristic length scale of 12 km and median area of 152 km2. Five seasonality clusters were identified with k-means++ clustering. The Midwest and eastern United States had a broad, spring maximum of NH3 (67% of hotspots in this cluster). The western United States, in contrast, showed a narrower midsummer peak (32% of hotspots). IASI spatiotemporal clustering was consistent with those from the Ammonia Monitoring Network. CMAQ and GFDL-AM3 modeled NH3 columns have some success replicating the seasonal patterns but did not capture the regional differences. The high spatial-resolution monthly NH3 maps serve as a constraint for model simulations and as a guide for the placement of future, ground-based network sites., SCOPUS: ar.j, info:eu-repo/semantics/published

We present localization and quantitative concentration analysis of controlled methane releases using chirped laser dispersion spectroscopy (CLaDS) in conjunction with an unmanned aerial vehicle (UAV) in an open-path sensing configuration. The system was operational with gusts up to 10 m/s, at distances up to 40 meters, and without using jacks to mechanically stabilize of the instrument vehicle.

The combination of unmanned aerial systems (sUAS) with advances in laser spectroscopic sensors has resulted in unprecedented capabilities for atmospheric sensing. Small sUAS (also known as drones) allow for measurements around local emission sources at small spatial scales (10s-100s of meters), vertical profiling in the lowermost atmosphere (particularly

International audience; Satellite ammonia (NH3) observations provide unprecedented insights into NH3 emissions, spatiotemporal variabilities and trends, but validation with in‐situ measurements remains lacking. Here, total columns from the Infrared Atmospheric Sounding Interferometer (IASI) were intercompared to boundary layer NH3 profiles derived from aircraft‐ and surface‐based measurements primarily in Colorado, USA, in the summer of 2014. IASI‐NH3 version 3 near real‐time dataset compared well to in‐situ derived columns (windows ±15 km around centroid, ±1 hour around overpass time) with a correlation of 0.58, a slope of 0.78±0.14, and an intercept of 2.1×1015±1.5×1015 molecules cm‐2. Agreement degrades at larger spatiotemporal windows, consistent with the short atmospheric lifetime of NH3. We also examined IASI version 3R data, which relies on temperature retrievals from the ERA Reanalysis, and a third product generated using aircraft‐measured temperature profiles. The overall agreement improves slightly for both cases, and neither is biased within their combined measurement errors. Thus, spatiotemporal averaging of IASI over large windows can be used to reduce retrieval noise. Nonetheless, sampling artifacts of airborne NH3 instruments result in significant uncertainties of the in‐situ‐derived columns. For example, large validation differences exist between ascent and descent profiles, and the assumptions of the free tropospheric NH3 profiles used above the aircraft ceiling significantly impact the validation. Because short‐lived species like NH3 largely reside within the boundary layer with complex vertical structures, more comprehensive validation is needed across a wide range of environments. More accurate and widespread in‐situ NH3 datasets are therefore required for improved validations of satellite products.

Natural gas vehicles (NGVs) have been promoted in China to mitigate air pollution, yet our measurements and analyses show that NGV growth in China may have significant negative impacts on climate change. We conducted real-world vehicle emission measurements in China and found high methane emissions from heavy-duty NGVs (90% higher than current emission limits). These emissions have been ignored in previous emission estimates, leading to biased results. Applying our observations to life-cycle analyses, we found that switching to NGVs from conventional vehicles in China has led to a net increase in greenhouse gas (GHG) emissions since 2000. With scenario analyses, we also show that the next decade will be critical for China to reverse the trend with the upcoming China VI standard for heavy-duty vehicles. Implementing and enforcing the China VI standard is challenging, and the method demonstrated here can provide critical information regarding the fleet-level CH4 emissions from NGVs., The methane emissions from natural gas vehicles (NGVs) are unclear. Here the authors report high methane emissions from heavy-duty NGVs, and by using a scenario analysis show that strictly implementing the upcoming China VI standard could reduce GHG emissions by 509 Mt CO2eq for 2020-2030.

Concentrated animal feeding operations (CAFOs) are major emitters of both ammonia (NH3) and methane (CH4). However, current emission inventories have limited temporal resolution and use data derived from a small subset of farms. To this end, we deployed three mobile laboratories during the DISCOVER-AQ campaign in summer 2014 with a focus on northeastern Colorado. Observations of NH3 and CH4 plumes downwind of 43 CAFOs were used to investigate the diurnal and site-to-site variability of emissions with an inverse area source plume modeling approach. Ammonia emissions scaled to all permitted animals in Weld, Morgan, and Larimer counties were estimated at 1.9 Gg month-1, 50% greater than the U.S. NEI 2014 and 360% greater than EDGAR for the month of August. Methane emissions were likewise estimated at 10.6 Gg month-1, consistent with the U.S. GHGI but 99% greater than EDGAR. Significant differences between individual CAFOs with repeat observations were also observed for both CH4 and NH3 emissions. The large subfarm, site-to-site, and diurnal variabilities observed show the importance of measurements taken across these scales in order to derive representative emission factors.

Ammonia (NH3) is a key precursor to fine particulate matter (PM2.5) and has remarkable impacts on air quality, climate, and ecosystem diversity. Satellite NH3 observations from the Infrared Atmospheric Sounding Interferometer (IASI) provide long-term measurements of ammonia globally since 2007 and have been validated by both ground based and airborne measurements. In this study, IASI Level 2 NH3 columns were oversampled at high-resolution (0.02°×0.02°) from 2008 to 2017 to yield monthly NH3 maps covering the two top agricultural exporting regions in the world, the contiguous U.S. (CONUS) and Europe. K-means clustering was applied to identify NH3 seasonality observations. The U.S. and Europe showed large temporal variabilities that differed by region and agricultural activities. For example, in the U.S., areas dominated by livestock waste emissions had peak NH3 column abundances in the summer, while cropland-dominated regions tended to have spring peak and sometimes a fall shoulder. We also compared IASI NH3 column amounts to NH3 surface concentrations provided by the Ammonia Monitoring Network (AMoN) in the CONUS. Since IASI provides column NH3 at ~ 9:30 LST while AMoN provides biweekly averaged surface NH3, different factors were examined to find out the most important factors for the comparison between the two datasets (spatial window, temporal coverage, data averaging). We found that IASI data temporal coverage of the 2-week AMoN sampling period was the key factor in improving correlations. The r value increased from 0.38 to 0.73 when at least 80% of the two-week AMoN period had concurrent satellite measurements within a 25 km radius of the site. Neglecting interannual variability, the r value of multiyear monthly averaged AMoN and IASI NH3 is 0.68, indicating the importance of temporal averaging. The good agreement between AMoN and IASI NH3 concentrations demonstrates the feasibility of utilizing satellite NH3 retrievals to better understand NH3 variability in these agricultural intensive regions. With the global coverage and long data record, satellite measurements are likely to be a cost-effective approach as a supplemental source of information for understanding NH3 variability, as well as guiding the locations of future sites within ground monitoring network. Finally, IASI NH3 spatiotemporal variabilities will be compared to AM3 model output with bottom-up emission inventory (Magnitude And Seasonality of Agricultural Emissions model for NH3, MASAGE_NH3).

An open-path ammonia sensor based on 9.06 pm hollow core fiber coupled quantum cascade laser was developed to atmospheric NH3 monitoring, measurement precision of 0.25 ppb was obtained with fast time response of 0.1 s.

Mobile laboratory measurements provide information on the distribution of CH4 emissions from point sources such as oil and gas wells, but uncertainties are poorly constrained or justified. Sources of uncertainty and bias in ground-based Gaussian-derived emissions estimates from a mobile platform were analyzed in a combined field and modeling study. In a field campaign where 1009 natural gas sites in Pennsylvania were sampled, a hierarchical measurement strategy was implemented with increasing complexity. Of these sites, ∼ 93 % were sampled with an average of 2 transects in 4 concentrations in a turbulent environment. The LES output and LES-derived emission estimates were used to compare with the results of a standard Gaussian approach. The LES and Gaussian-derived emission rates agreed within a factor of 2 in all except one case; the average difference was 25 %. A controlled release was also used to investigate sources of bias in either technique. The Gaussian method agreed with the release rate more closely than the LES, underlining the importance of inputs as sources of uncertainty for the LES. The LES was also used as a virtual experiment to determine an optimum number of repeat transects and spacing needed to produce representative statistics. Approximately 10 repeat transects spaced at least 1 min apart are required to produce statistics similar to the observed variability over the entire LES simulation period of 30 min. Sources of uncertainty from source location, wind speed, background concentration and atmospheric stability were also analyzed. The largest contribution to the total uncertainty was from atmospheric variability; this is caused by insufficient averaging of turbulent variables in the atmosphere (also known as random errors). Atmospheric variability was quantified by repeat measurements at individual sites under relatively constant conditions. Accurate quantification of atmospheric variability provides a reasonable estimate of the lower bound for emission uncertainty. The uncertainty bounds calculated for this work for sites with > 50 ppb enhancements were 0.05–6.5q (where q is the emission rate) for single-transect sites and 0.5–2.7q for sites with 10+ transects. More transects allow a mean emission rate to be calculated with better precision. It is recommended that future mobile monitoring schemes quantify atmospheric variability, and attempt to minimize it, under representative conditions to accurately estimate emission uncertainty. These recommendations are general to mobile-laboratory-derived emissions from other sources that can be treated as point sources.

We report an open-path chirped laser dispersion spectrometer capable of detecting the atmospheric methane concentration above the background using both specular and diffusive reflective surfaces via two distinct operation modes in a stand-off detection configuration. The system is integrated with simultaneous ranging functionality, which enables average concentration measurements for varying optical pathlengths. The system was first tested for accuracy and characterized to achieve sensitivity of 2.9 p p m - m / H z 1 / 2 and pathlength precision of 0.2 m / H z 1 / 2 with a controlled release of methane outside the laboratory. The instrument was subsequently field-deployed in the proximity of a natural gas compressor station for fugitive methane detection. The instrument successfully detected methane plumes and narrowed down the location of the plume through multi-path measurement. The field measurements were verified by a co-located reference mobile methane sensor.

Pyrolysis is a viable option for the production of renewable energy and agricultural resources from diverted organic waste streams. This high temperature thermochemical process yields material with beneficial reuses, including bio-oil and biochar. Gaseous forms of carbon (C) and nitrogen (N) are also emitted during pyrolysis. The effluent mass emission rates from pyrolysis are not well characterized, thus limiting proper evaluation of the environmental benefits or costs of pyrolysis products. We present the first comprehensive suite of C and N mass emission rate measurements of a biomass pyrolysis process that uses chicken manure as the feedstock to produce biochar and bio-oil. Two chicken manure fast pyrolysis experiments were conducted at controlled temperature ranges of 450–485 °C and 550–585 °C. Mass emission rates of nitrous oxide (N2O), nitric oxide (NO), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), and ammonia (NH3) were measured using trace gas analyzers. Based on the system mass bal...

Occurrence frequency and dynamical conditions of ice supersaturation (ISS, where relative humidity with respect to ice (RHi) greater than 100%) are examined in the upper troposphere around convective activity. Comparisons are conducted between in situ airborne observations and the Weather Research and Forecasting model simulations using four double-moment microphysical schemes at temperatures less than or or equal to -40degdegC. All four schemes capture both clear-sky and in-cloud ISS conditions. However, the clear-sky (in-cloud) ISS conditions are completely (significantly) limited to the RHi thresholds of the Cooper parameterization. In all of the simulations, ISS occurrence frequencies are higher by approximately 3-4 orders of magnitude at higher updraft speeds (greater than 1 m s(exp -1) than those at the lower updraft speeds when ice water content (IWC) greater than 0.01 gm(exp -3), while observations show smaller differences up to approximately 1-2 orders of magnitude. The simulated ISS also occurs less frequently at weaker updrafts and downdrafts than observed. These results indicate that the simulations have a greater dependence on stronger updrafts to maintain/generate ISS at higher IWC. At lower IWC (less than or equal or 0.01 gm(exp -3), simulations unexpectedly show lower ISS frequencies at stronger updrafts. Overall, the Thompson aerosol-aware scheme has the closest magnitudes and frequencies of ISS greater than 20% to the observations, and the modified Morrison has the closest correlations between ISS frequencies and vertical velocity at higher IWC and number density. The Cooper parameterization often generates excessive ice crystals and therefore suppresses the frequency and magnitude of ISS, indicating that it should be initiated at higher ISS (e.g.,lees than or equal to 25%).

Ammoniated aerosols are important for urban air quality, but emissions of the key precursor NH3 are not well quantified. Mobile laboratory observations are used to characterize fleet-integrated NH3 emissions in six cities in the U.S. and China. Vehicle NH3:CO2 emission ratios in the U.S. are similar between cities (0.33–0.40 ppbv/ppmv, 15% uncertainty) despite differences in fleet composition, climate, and fuel composition. While Beijing, China has a comparable emission ratio (0.36 ppbv/ppmv) to the U.S. cities, less developed Chinese cities show higher emission ratios (0.44 and 0.55 ppbv/ppmv). If the vehicle CO2 inventories are accurate, NH3 emissions from U.S. vehicles (0.26 ± 0.07 Tg/yr) are more than twice those of the National Emission Inventory (0.12 Tg/yr), while Chinese NH3 vehicle emissions (0.09 ± 0.02 Tg/yr) are similar to a bottom-up inventory. Vehicle NH3 emissions are greater than agricultural emissions in counties containing near half of the U.S. population and require reconsideration in u...

Midwave infrared interband-cascade light-emitting devices (ICLEDs) have the potential to improve the selectivity, stability, and sensitivity of low-cost gas sensors. We demonstrate a broadband direct absorption CH4 sensor with an ICLED coupled to a plastic hollow-core fiber (1 m length, 1500 µm inner diameter). The sensor achieves a 1σ noise equivalent absorption of approximately 0.2 ppmv CH4 at 1 Hz, while operating at a low drive power of 0.5 mW. A low-cost sub-ppmv CH4 sensor would make monitoring emissions more affordable and more accessible for many relevant industries, such as the petroleum, agriculture, and waste industries.

A long-path methane (CH4) sensor was developed and field deployed using an 8-μm quantum cascade laser. The high optical power (40 mW) of the laser allowed for path-integrated measurements of ambient CH4 at total pathlengths from 100 to 1200 m with the use of a retroreflector. Wavelength modulation spectroscopy was used to make high-precision measurements of atmospheric pressure–broadened CH4 absorption over these long distances. An in-line reference cell with higher harmonic detection provided metrics of system stability in rapidly changing and harsh environments. The system consumed less than 100 W of power and required no consumables. The measurements intercompared favorably (typically less than 5% difference) with a commercial in situ methane sensor when accounting for the different spatiotemporal scales of the measurements. The sensor was field deployed for 2 weeks at an arctic lake to examine the robustness of the approach in harsh field environments. Short-term precision over a 458-m pathlength was 10 ppbv at 1 Hz, equivalent to a signal from a methane enhancement above background of 5 ppmv in a 1-m length. The sensor performed well in a range of harsh environmental conditions, including snow, rain, wind, and changing temperatures. These field measurements demonstrate the capabilities of the approach for use in detecting large but highly variable emissions in arctic environments.

International audience; In this paper, we describe a new flexible and robust NH3 retrieval algorithm from measurements of the Infrared Atmospheric Sounding Interferometer (IASI). The method is based on the calculation of a spectral hyperspectral range index (HRI) and subsequent conversion to NH3 columns via a neural network. It is an extension of the method presented in Van Damme et al. (2014a) who used lookup tables (LUT) for the radiance-concentration conversion. The new method inherits the advantages of the LUT-based method while providing several significant improvements. These include the following: (1) Complete temperature and humidity vertical profiles can be accounted for. (2) Third-party NH3 vertical profile information can be used. (3) Reported positive biases of LUT retrieval are reduced, and finally (4) a full measurement uncertainty characterization is provided. A running theme in this study, related to item (2), is the importance of the assumed vertical NH3 profile. We demonstrate the advantages of allowing variable profile shapes in the retrieval. As an example, we analyze how the retrievals change when all NH3 is assumed to be confined to the boundary layer. We analyze different averaging procedures in use for NH3 in the literature, introduced to cope with the variable measurement sensitivity and derive global averaged distributions for the year 2013. A comparison with a GEOS-Chem modeled global distribution is also presented, showing a general good correspondence (within ±3 × 1015 molecules.cm−2) over most of the Northern Hemisphere. However, IASI finds mean columns about 1–1.5 × 1016 molecules.cm−2 (∼50–60%) lower than GEOS-Chem for India and the North China plain.

Natural gas is an abundant resource across the United States, of which methane (CH4) is the main component. About 2% of extracted CH4 is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH4 mixing ratio and can semi-autonomously monitor CH4 leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 &times, 10 &minus, 6 m3/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.

The San Joaquin Valley (SJV) of California experiences high concentrations of particulate matter NH(4)NO(3) during episodes of meteorological stagnation in winter. A rich data set of observations related to NH(4)NO(3) formation was acquired during multiple periods of elevated NH(4)NO(3) during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign in SJV in January and February 2013. Here NH(4)NO(3) is simulated during the SJV DISCOVER-AQ study period with the Community Multiscale Air Quality (CMAQ) model, diagnostic model evaluation is performed using the DISCOVER-AQ data set, and integrated reaction rate analysis is used to quantify HNO(3) production rates. Simulated NO(3)(−) generally agrees well with routine monitoring of 24-hr average NO(3)(−), but comparisons with hourly average NO(3)(−) measurements in Fresno revealed differences at higher time resolution. Predictions of gas-particle partitioning of total nitrate (HNO(3) + NO(3)(−)) and NHx (NH(3) + NH(4)(+)) generally agree well with measurements in Fresno, although partitioning of total nitrate to HNO(3) is sometimes overestimated at low relative humidity in afternoon. Gas-particle partitioning results indicate that NH(4)NO(3) formation is limited by HNO(3) availability in both the model and ambient. NH(3) mixing ratios are underestimated, particularly in areas with large agricultural activity, and additional work on the spatial allocation of NH(3) emissions is warranted. During a period of elevated NH(4)NO(3), the model predicted that the OH + NO(2) pathway contributed 46% to total HNO(3)production in SJV and the N(2)O(5) heterogeneous hydrolysis pathway contributed 54%. The relative importance of the OH + NO(2) pathway for HNO(3) production is predicted to increase as NOx emissions decrease.

Eddy covariance (EC) measurements of NH3 fluxes from a cattle feedlot were made with a high-precision, fast-response (20 Hz) open-path laser-based sensor. The sensor employed a continuous wave, quantum cascade (QC) laser and targeted an isolated absorption feature of NH3 at 9.06 μm. It was deployed on a 5-m tall flux tower beside a 22,000-animal cattle feedlot in Colorado, USA for two weeks. Sensible heat, latent heat, CO2, and CH4 EC fluxes were measured concurrently on the tower. The open-path NH3 sensor showed a comparable time response to well-established commercial open-path sensors for CO2 and H2O. The average high-frequency flux loss over the measurement period was 6.6%, mainly resulting from sample path averaging. The sensor showed significant improvement over NH3 EC fluxes measured by closed-path sensors. The measured NH3 EC fluxes were well-correlated with latent heat EC fluxes. During the measurement period, the average daily NH3 EC flux was 31.7 kg ha−1 d−1. The flux-variance relationship was used to further validate the performance of the NH3 EC flux measurement. A 1σ detection limit of 1.3 ± 0.5 ng m−2 s−1 for NH3 fluxes measured in 30-min intervals was achieved in this field test. This suite of measurements enabled the evaluation of livestock NH3 emissions at unprecedented temporal resolution and accuracy in the context of other important agricultural trace gases.

Agricultural ammonia (NH3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH3 and methane (CH4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH3 and CH4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH3:CH4 enhancement ratio derived from surface measurements is 0.15 ± 0.03 ppmv ppmv–1. Individual dairy feedlots with spatially distinct NH3 and CH4 source pathways led to statistically significant correlations between NH3 and CH4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH3:CH4 enhancement ratio decreases 20–30%, suggesting the potential for NH3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surfacemore » mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH3 partitioning to submicron particles. Individual NH3 and CH4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. As a result, our analyses have important implications for constraining NH3 sink and plume variability influences on regional NH3 emission estimates and for improving NH3 emission inventory spatial allocations.« less

Halogens in the troposphere are increasingly recognized as playing an important role for atmospheric chemistry, and possibly climate. Bromine and iodine react catalytically to destroy ozone (O3), oxidize mercury, and modify oxidative capacity that is relevant for the lifetime of greenhouse gases. Most of the tropospheric O3 and methane (CH4) loss occurs at tropical latitudes. Here we report simultaneous measurements of vertical profiles of bromine oxide (BrO) and iodine oxide (IO) in the tropical and subtropical free troposphere (10 °N to 40 °S), and show that these halogens are responsible for 34% of the column-integrated loss of tropospheric O3. The observed BrO concentrations increase strongly with altitude (∼ 3.4 pptv at 13.5 km), and are 2-4 times higher than predicted in the tropical free troposphere. BrO resembles model predictions more closely in stratospheric air. The largest model low bias is observed in the lower tropical transition layer (TTL) over the tropical eastern Pacific Ocean, and may reflect a missing inorganic bromine source supplying an additional 2.5-6.4 pptv total inorganic bromine (Bry), or model overestimated Bry wet scavenging. Our results highlight the importance of heterogeneous chemistry on ice clouds, and imply an additional Bry source from the debromination of sea salt residue in the lower TTL. The observed levels of bromine oxidize mercury up to 3.5 times faster than models predict, possibly increasing mercury deposition to the ocean. The halogen-catalyzed loss of tropospheric O3 needs to be considered when estimating past and future ozone radiative effects.

The influence of random errors in turbulence measurements on scalar similarity for temperature, water vapour, $$\hbox {CO}_{2}$$ , and $$\hbox {NH}_{3}$$ is investigated using two eddy-covariance datasets collected over a lake and a cattle feedlot. Three measures of scalar similarity, namely, the similarity constant in the flux–variance relationship, the correlation coefficient between two scalars and the relative transport efficiency, are examined. The uncertainty in the similarity constant $$C_{s}$$ in the flux–variance relationship resulting from random errors in turbulence measurements is quantified based on error propagation analyses and a Monte-Carlo sampling method, which yields a distribution instead of a single value for $$C_{s}$$ . For different scalars, the distributions of $$C_{s}$$ are found to significantly overlap, implying that scalars are transported similarly under strongly unstable conditions. The random errors in the correlation coefficients between scalars and the relative transport efficiencies are also quantified through error propagation analyses, and they increase as the atmosphere departs from neutral conditions. Furthermore, the correlation coefficients between three scalars (water vapour, $$\hbox {CO}_{2}$$ , and $$\hbox {NH}_{3}$$ ) are statistically different from unity while the relative transport efficiencies are not, which highlights the difference between these two measures of scalar similarity. The results suggest that uncertainties in these measures of scalar similarity need to be quantified when using them to diagnose the existence of dissimilarity among different scalars.

Ammonia measurements from a vehicle-based, mobile open-path sensor and those from aircraft were compared with Tropospheric Emission Spectrometer (TES) NH3 columns at the pixel scale during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality field experiment. Spatial and temporal mismatches were reduced by having the mobile laboratory sample in the same areas as the TES footprints. To examine how large heterogeneities in the NH3 surface mixing ratios may affect validation, a detailed spatial survey was performed within a single TES footprint around the overpass time. The TES total NH3 column above a single footprint showed excellent agreement with the in situ total column constructed from surface measurements with a difference of 2% (within the combined measurement uncertainties). The comparison was then extended to a TES transect of nine footprints where aircraft data (5–80 ppbv) were available in a narrow spatiotemporal window (

Tropospheric chemistry of halogens and organic carbon over tropical oceans modifies ozone and atmospheric aerosols, yet atmospheric models remain largely untested for lack of vertically resolved measurements of bromine monoxide (BrO), iodine monoxide (IO) and small oxygenated hydrocarbons like glyoxal (CHOCHO) in the tropical troposphere. BrO, IO, glyoxal, nitrogen dioxide (NO2), water vapor (H2O) and O2–O2 collision complexes (O4) were measured by the University of Colorado Airborne Multi-AXis Differential Optical Absorption Spectroscopy (CU AMAX-DOAS) instrument, aerosol extinction by high spectral resolution lidar (HSRL), in situ aerosol size distributions by an ultra high sensitivity aerosol spectrometer (UHSAS) and in situ H2O by vertical-cavity surface-emitting laser (VCSEL) hygrometer. Data are presented from two research flights (RF12, RF17) aboard the National Science Foundation/National Center for Atmospheric Research Gulfstream V aircraft over the tropical Eastern Pacific Ocean (tEPO) as part of the "Tropical Ocean tRoposphere Exchange of Reactive halogens and Oxygenated hydrocarbons" (TORERO) project (January/February 2012). We assess the accuracy of O4 slant column density (SCD) measurements in the presence and absence of aerosols. Our O4-inferred aerosol extinction profiles at 477 nm agree within 6% with HSRL in the boundary layer and closely resemble the renormalized profile shape of Mie calculations constrained by UHSAS at low (sub-Rayleigh) aerosol extinction in the free troposphere. CU AMAX-DOAS provides a flexible choice of geometry, which we exploit to minimize the SCD in the reference spectrum (SCDREF, maximize signal-to-noise ratio) and to test the robustness of BrO, IO and glyoxal differential SCDs. The RF12 case study was conducted in pristine marine and free tropospheric air. The RF17 case study was conducted above the NOAA RV Ka'imimoana (TORERO cruise, KA-12-01) and provides independent validation data from ship-based in situ cavity-enhanced DOAS and MAX-DOAS. Inside the marine boundary layer (MBL) no BrO was detected (smaller than 0.5 pptv), and 0.2–0.55 pptv IO and 32–36 pptv glyoxal were observed. The near-surface concentrations agree within 30% (IO) and 10% (glyoxal) between ship and aircraft. The BrO concentration strongly increased with altitude to 3.0 pptv at 14.5 km (RF12, 9.1 to 8.6° N; 101.2 to 97.4° W). At 14.5 km, 5–10 pptv NO2 agree with model predictions and demonstrate good control over separating tropospheric from stratospheric absorbers (NO2 and BrO). Our profile retrievals have 12–20 degrees of freedom (DoF) and up to 500 m vertical resolution. The tropospheric BrO vertical column density (VCD) was 1.5 × 1013 molec cm−2 (RF12) and at least 0.5 × 1013 molec cm−2 (RF17, 0–10 km, lower limit). Tropospheric IO VCDs correspond to 2.1 × 1012 molec cm−2 (RF12) and 2.5 × 1012 molec cm−2 (RF17) and glyoxal VCDs of 2.6 × 1014 molec cm−2 (RF12) and 2.7 × 1014 molec cm−2 (RF17). Surprisingly, essentially all BrO as well as the dominant IO and glyoxal VCD fraction was located above 2 km (IO: 58 ± 5%, 0.1–0.2 pptv; glyoxal: 52 ± 5%, 3–20 pptv). To our knowledge there are no previous vertically resolved measurements of BrO and glyoxal from aircraft in the tropical free troposphere. The atmospheric implications are briefly discussed. Future studies are necessary to better understand the sources and impacts of free tropospheric halogens and oxygenated hydrocarbons on tropospheric ozone, aerosols, mercury oxidation and the oxidation capacity of the atmosphere.