Current Pollution Reports

, Volume 1, Issue 2, pp 95–116 | Cite as

Sources and Impacts of Atmospheric NH3: Current Understanding and Frontiers for Modeling, Measurements, and Remote Sensing in North America

  • Liye Zhu
  • Daven K. HenzeEmail author
  • Jesse O. Bash
  • Karen E. Cady-Pereira
  • Mark W. Shephard
  • Ming Luo
  • Shannon L. Capps
Air Pollution (S Wu, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Air Pollution


Ammonia (NH3) contributes to widespread adverse health impacts, affects the climate forcing of ambient aerosols, and is a significant component of reactive nitrogen, deposition of which threatens many sensitive ecosystems. Historically, the scarcity of in situ measurements and the complexity of gas-to-aerosol NH3 partitioning have contributed to large uncertainties in our knowledge of its sources and distributions. However, recent progress in measurements and modeling has afforded new opportunities for improving our understanding of NH3 and the role it plays in these important environmental issues. In the past few years, passive measurements of NH3 have been added to monitoring networks throughout the USA, now in place at more than 60 stations, while mobile measurements aboard aircrafts and vehicles have provide detailed observations during several recent field campaigns. In addition, new remote sensing observations from multiple satellite instruments have begun to provide vast amounts of NH3 observations throughout the globe. These sources of information have collectively driven new air quality modeling capabilities, by revealing deficiencies in current air quality models and spurring development of mechanistic enhancements to models’ physical representation of the diurnal variability and bidirectional nature of NH3 fluxes. In turn, these advanced models require further observational constraints, as existing NH3 measurements are still limited in spatiotemporal coverage. We thus evaluate the potential value of a new geostationary remote sensing instrument (GCIRI) for providing constraints on NH3 fluxes through multiple Observing System Simulation Experiments (OSSEs).


Ammonia North America Sources and impacts Measurements techniques Low-earth-orbit and geostationary remote sensing Diurnal variability Bidirectional exchange 


The nitrogen in ammonia (NH3) is an important component of the global nitrogen cycle, which plays an important role in every ecosystem. While by itself NH3 has a residence time in the atmosphere of only a day or less, it contributes to the formation of atmospheric aerosols that reside in the atmosphere for several days to a week [64, 127, 130, 178]. NH3 is thus responsible for a significant fraction of the long-range transport (hundreds of kilometer) of reactive nitrogen [62]. However, the natural nitrogen cycle has shifted dramatically in recent decades due to human activities. Widespread dispersion, transport, and deposition of NH3 through the atmosphere contribute to a number of environmental and human health concerns. Largely unregulated emissions of NH3 from anthropogenic actives have increased several folds since pre-industrial times, and they are the only such sources of ambient aerosol particles whose emissions are projected to rise, globally, throughout the next century [113]. Compared to measurement capabilities for other aerosol precursors or sources of reactive nitrogen, observations of NH3 have been sparse until recent years. This historical lack of data has contributed to large uncertainties in our present understanding of the role NH3 plays in the nexus of air quality, climate, ecosystems, and food security.

Here, we review current knowledge of atmospheric NH3, beginning with an overview of NH3 sources (Section “Sources of NH3 ”) and the impacts of NH3 on human health and the environment (Section “Impacts of Atmospheric NH3 ”). We next review current measurements techniques for NH3, from both passive and active in situ observations to new remote sensing techniques. Lastly, we consider the value of a recently proposed geostationary remote sensing instrument (GCIRI) that would provide the first geostationary measurements of NH3 over North America. Given the state of knowledge of NH3, we conclude that the potential of such an instrument to enhance our understanding of NH3 sources and distributions at a mechanistic level could significantly improve our ability to treat NH3 in chemistry and climate models, thereby increasing the value of such tools for environmental decision-making.

Sources of NH3

The primary source of global NH3 emissions is agriculture (∼85 %), which includes NH3 emissions from livestock and NH3-based fertilizer applications. Other sources of NH3 emissions include industrial processes, motor vehicles, plant decomposition, biomass burning, and volatilization from soils and oceans. Early nitrogen cycle studies estimated that NH3 emissions contribute ∼75 Tg N year−1 of the global N budget (∼250 Tg year−1) [152]. Global emission inventories were subsequently developed [21, 42]; however, owing to the lack of NH 3 measurements in most regions of the globe, such estimates were hard to evaluate and contained large uncertainties. For example, the global estimate of NH3 emissions is 54 Tg N year−1 with 25 % uncertainty in Bouwman et al. [21], which is lower than 75 Tg N year−1 (with potential range from 50 to 128 Tg N year−1) of Schlesinger and Hartley [152] and somewhat higher than 45 Tg N year−1 with 50 % uncertainty by Dentener and Crutzen [42]. More recently, the Emissions Database for Global Atmospheric Research (EDGAR) compiled NH3 anthropogenic emissions for the past and present day, and Beusen et al. [19] derived a global inventory of NH3 emissions from agriculture with 0.08×0.08 resolution for 2000. A new global, monthly, emission inventory, Magnitude And Seasonality of Agricultural Emissions for NH3 (MASAGE_NH3), was developed based on the worldwide emission estimates on regional agricultural activities [130]. In addition to global emissions estimates, there are numerous studies on regional NH3 emissions, for example, in China [79, 165, 189], the USA [65, 66, 127, 134], India [5], Europe [58, 160, 161], France [71], and Canada [174]. Summaries of some of these inventories are included in Table 1.
Table 1

Summary of global and regional NH3 emission estimates in teragram N per year



North America

Contiguous US

Spatial resolution




   Schlesinger and Hartley [152]





   Dentener and Crutzen [42]






   Bouwman et al. [21]






   EDGAR v4.2






   Moss et al. [113]






   Moss et al. [113]d






Livestock and fertilizer


   Beusen et al. [19]






   Paulot et al. [130]






   US National Emissions Inventory 2005



4 ×4 km2


a Data not available

b North and Central America (including anthropogenic, wild animals, and vegetation)

c Livestock operations only (including manure spreading and excluding fertilizer use)

d Ranges span the RCP 4.5 to RCP 8.5 estimates, which had the widest range of global values across all RCPs in 2050

Recent studies have indicated that global emissions of NH3 have already increased by a factor of two to five since pre-industrial times [94], following increases in the demand for food for growing populations, especially for increasing agriculture activities in developing countries [4, 38, 49]. Global emissions of NH3 are projected to continue to rise over the next 100 years in all Representative Concentration Pathways (RCPs) [113]. The projected anthropogenic emissions of NH3 are estimated to double by 2100 in RCP2.6 and RCP 8.5 (67 Tg N year−1) and increase the least in RCP4.5 (43.6 Tg N year−1) relative to year 2000 estimates of 38.5 Tg N year−1 [142]. While such projections have yet to be widely evaluated, in some regions, NH3 emissions have and are expected to continue to decline, such as in the EU, where a 26 % reduction was found in EEA-33 (33 member countries of European Environment Agency) NH3 emissions from agricultural between the years 1990 and 2011 [44], mainly due to reduced livestock and improved handling and management of manure. Although NH3 emissions are generally from agricultural productions, NH3 fluxes are extremely climate-sensitive [169]. The NH3 volatilization potential could double every 5 K. NH3 could also be absorbed by organisms through decomposition associated with water availability. Thus, for future NH3 emission estimates, further attention should be paid to the impact of climate change, interaction of the vegetation canopy and soil wetness, agricultural management practices, and land use changes.

Developing NH3 emission inventories such as those discussed above is challenging in many aspects owing to uncertainties in management practices (i.e., activity data), emission factors, and variability at different temporal scales. There are several approaches to building emissions inventories. “Bottom-up” emission inventories are built from spatial and temporal information of the emission sources and source-specific emission factors (e.g., [12, 130, 133, 134]). This requires a detailed knowledge of climate conditions and farming practices, or detailed reporting practices, which may not be readily available. In contrast, inverse modeling approaches generate “top-down” emission estimates by optimizing model predictions in order to match the available observations from in situ monitoring sites [65, 66, 77, 130, 187] and remote sensing [190]. Ultimately, both approaches are required.

Impacts of Atmospheric NH3

Atmospheric NH3 readily condenses onto sulfuric acid and with nitric acid to form what is often a ternary mixture of sulfate (\(\text {SO}_{4}^{2-}\)), ammonium (\(\text {NH}_{4}^{+}\)), and nitrate (\(\text {NO}_{3}^{-}\)) in water, which commonly contains salts such as ammonium sulfate ((NH4)2SO4) and ammonium nitrate (NH4NO3). Uptake of nitric acid to form \(\text {NO}_{3}^{-}\) is largely controlled by the presence of NH3 concentrations in excess of the amount required to neutralize sulfate; thus, aerosol nitrate (\(\text {NO}_{3}^{-}\)) is often considered a byproduct of NH3. The presence of NH3 can also play a role in the formation of secondary organic aerosol (SOA) via processes such as ozonolysis of α-pinene through condensation of organic salts [116], although an impact on SOA from oxidation of other species such as isoprene has not been found [104]. In turn, pre-existing organic aerosol may also impact NH3 uptake (e.g., [20, 96, 102, 106, 171]). NH3 also contributes to new particle formation through ternary homogenous nucleation, multicomponent nucleation, and ion-induced nucleation (e.g., [9, 68, 89, 93, 117, 162]).

Philip et al. [131] synthesized the remote sensing observations and global model simulations to estimate that ammonium, sulfate, and nitrate constitute about a third of the global average population-weighted fine particulate matter (particles with aerodynamic diameter less than 2.5 μm, i.e., PM2.5) concentration of 37 μg m−3, with \(\text {NH}_{4}^{+}\) contributing 2.7 ± 1.2 μg m−3. Surface-based composition measurements using aerosol mass spectrometers (AMS) in urban areas worldwide consistently report Northern Hemisphere urban PM1 concentration fractions (excluding dust) of 14, 18, and 23 % for ammonium, nitrate, and sulfate [188]. These are consistent with the composition breakdown from Philip et al. [131], considering that the latter includes a 30 % contribution from mineral dust. In contrast to background concentrations, driven primarily by agricultural sources, episodic pollution events in urban locations such as New York and Beijing are often significantly influenced by traffic emissions [70, 149] even though these are a small fraction of total global emissions.

The contribution of ammonia to PM2.5 poses significant health concerns. Numerous studies have shown that exposure to PM2.5 is associated with a range deleterious impacts on human health, such as increased hospital admissions, cardiovascular, respiratory, and all-cause mortality [24, 36, 98, 140, 141, 146, 153]. Exposure to ambient air pollution is ranked as one of the top ten risk factors for mortality worldwide [103], annually causing an estimated 3 million premature deaths globally [23] and more than 100,000 premature deaths in the USA alone [51]. While \(\text {NH}_{4}^{+}\) and \(\text {NO}_{3}^{-}\) may have health impacts unique from those of total PM2.5 mass (e.g., [16, 26, 99]), most current air quality policies rely upon well established relationships between total PM2.5 mass and health [27, 48].

While NH3 is not the largest contributor to PM2.5, the response of human health impacts to changes in NH3 can be quite significant, owing to the highly nonlinear relationship between ambient NH3 concentrations and the formation of ammonium nitrate. Several studies have shown that the most efficient control of PM2.5 is often NH3 emissions [77, 127, 135, 175, 184], owing to NH3 concentrations controlling ammonium nitrate concentrations, especially in winter, with notable exceptions being regions with consistently elevated NH3 concentrations such as India [86]. Recent studies have attempted to evaluate the economic or health impact per unit emission of NH3, i.e., the marginal damages of NH3 emissions (e.g., [69, 167]). For example, using a combination of remote sensing and adjoint sensitivity analysis, Lee et al. [97] evaluated the contribution of aerosol and aerosol precursor emissions to global premature deaths. They found that for a 1 kg km−2 year−1 reduction of any PM2.5 precursor emission, anywhere in the world, the largest reduction in global prematures death occurred for NH3 emissions in Europe [97], with damages of up to 15 premature deaths per kilogram (km−2 year−1). Fann et al. [50] estimated monetized damages (using a statistical value of life of US$6 million) of US$38,000 and US$95,000 per ton of NH3 emitted from area and mobile sources, respectively, averaged across nine urban areas within the USA. Dedoussi and Barrett [37] used adjoint sensitivity analysis to estimate the spatial, sectoral, and seasonal impact of NH3 emissions on premature deaths in the USA, finding that urban NH3 emissions had ∼20 times as large the damages of NO x per ton of emission. Paulot and Jacob [128] estimated that the damages from agricultural emissions of NH3 for food export alone contributed to US$36 billion annually from premature deaths in the USA. Buonocore et al. [25] estimated that power plant emissions in the USA lead to US$16,000 in damages per ton of NO x emissions, 34 % of which is owing to formation of ammonium nitrate. These responses may be overestimated in models that do not include the uptake of nitrate on sea salt [7]. They also do not consider the potential role of NH3 in terms of particle acidity [81] and its impact on secondary organic aerosol formation (e.g., [82]), although verifying such mechanisms in ambient conditions has been elusive (e.g., [104]). Nevertheless, many models used for evaluation of air quality control strategies may still underestimate the response of PM2.5 to ammonia reductions [18].

Along with its impact on air quality, NH3 can have significant impacts on climate. Ammonium sulfate and ammonium nitrate aerosol scatter incoming solar radiation, which causes a negative direct radiative forcing (i.e., cooling effect). Early estimates of the pre-industrial to present day ammonium aerosol direct radiative forcing crudely accounted for ammonium via spatially uniform ratios applied to prognostic estimates of aerosol sulfate to represent neutralization by ammonium (e.g., [30, 54, 74, 75]). The first direct global simulation of ammonium nitrate to include spatially heterogenous thermodynamic calculations [2] was used to estimate a nitrate aerosol direct radiative forcing of −0.2 W m−2 since pre-industrial times [3]. The overall magnitude of this forcing has been refined by subsequent individual global modeling estimates (e.g., [13, 17, 73, 78, 83, 101, 114, 158, 186]); multi-model assessments have ranged from −0.10 ± 0.04 W m−2 [115] to −0.19 ± 0.18 W m−2 [159], and in situ measurements have confirmed large regional contributions of ammonium nitrate to total aerosol extinction near large agricultural NH3 sources [95]. While NH3 is not the largest contributor to the total pre-industrial to present aerosol radiative forcing estimate of −0.5 ± 4 W m−2 [115], box model calculations [183] and global model sensitivity studies [78] have shown that NH3 has the largest aerosol direct radiative forcing efficiency (W m−2 per kg of emission) of all aerosol and aerosol precursor emissions. The impact of NH3 on climate will therefore likely become even more pronounced as sulfate concentrations decrease in regions with low SO2 emissions [112]. Projections of future radiative forcing thus include large effects of NH 3 (up to −0.15 Wm−2 by 2050) via enhanced direct radiative forcing of ammonium nitrate [3, 13, 73, 78, 101], emphasizing the importance of NH3 as the role of other species declines [163].

In addition to impacting direct radiative forcing by contributing to the mass concentrations of ammonium nitrate and ammonium sulfate, NH3 contributes to climate by multiple indirect mechanisms. The presence of ammonium can impact aerosol radiative forcing by influencing the phase of secondary inorganic aerosol [180], which modulates aerosol direct radiative forcing by ∼25 % globally, with larger variations regionally [109, 181]. There is also a growing body of literature indicating that NH3 enhances the light-absorbing properties of organic aerosol (e.g., [20, 171]), a mechanism by which increasing NH3 emissions would exert a positive radiative forcing. Ammonium sulfate also enhances (relative to sulfate alone) indirect aerosol radiative forcing through heterogeneous ice nucleation [1]. Enhanced nitrate concentrations over large NH3 sources have been observed to contribute to activation of cloud condensation nucleii (CCN) [164]. The contribution of NH3 to the deposition of reactive nitrogen has been estimated to induce a negative climate forcing by altering carbon fluxes that is similar in magnitude to the direct aerosol radiative forcing of ammonium nitrate itself [137, 138], a larger effect than previously recognized [145].

In addition to the impact of NH3 on human health and the environment from aerosol formation, the contribution of anthropogenic NH3 to reactive nitrogen deposition in the form of NH3 and \(\text {NH}_{4}^{+}\) (and associated \(\text {NO}_{3}^{-}\)) impacts the nitrogen cascade [57, 60, 63] and poses a threat to sensitive ecosystems [84, 92, 176]. Excessive deposition of NH3 causes eutrophication in surface water and soil acidification (e.g., [28, 43, 126, 132, 168]) and can further cause nutrient imbalances in sensitive ecosystems [105]. Levels of reactive nitrogen deposition exceed those deemed critical for the protection of biodiversity in many regions throughout the USA [47] and the world [41, 129], now or in the next few decades, underscoring concerns not only of past but also future impacts of anthropogenic activity on the global nitrogen cycle [22, 61, 62, 151]. Despite the recognized importance of this issue, uncertainties in our ability to model such processes may hinder efforts in the USA to develop secondary air quality standards to protect ecosystems from the hazards of this type of pollutant deposition [90].

Current Observations of NH3 in North America

In Situ Measurements

The measurement of ambient NH3 is difficult due to the tendency of the small, polar gas molecule to adhere to instrument surfaces or to volatilize from passive samplers. As with other in situ observations, techniques used to evaluate atmospheric ammonia range from simpler approaches deployed broadly to more highly resolved measurements used in specific field campaigns. A summary of techniques employed in North America is provided in Table 2. The largest scale measurements are taken through the National Atmospheric Deposition Program (NADP), which prototyped the Ammonia Monitoring Network (AMoN) in 2007 and then launched a full-fledged network in 2010 in order to establish continuous records of atmospheric NH3 concentrations (doi: Currently, at more than 60 sites nationwide, AMoN provides 2-week integrated samples of ammonia using Radiello® passive sampling devices that contain phosphoric acid in the filter to ensure absorption of ammonia [144]. Although other passive samplers performed similarly to this instrument in a year-long intercomparison, the ease of sample preparation led the NADP to select the Radiello [143].
Table 2

Summary of instruments measuring NH3 that have been evaluated and deployed in North America




Temporal resolution

Precision (uncertainty)

Detection limit


   Phosphoric acid-based passive sampler



2 weeks

10 % (±40 %)

0.16 μg m−3

Puchalski et al. [143]

   Mini-parallel plate denuders

Met One

CSN (3 sites)

1 week

13 % (±40 %)

0.004 μg m−3

Puchalski et al. [144]

   Filter/denuder system


Boulder, WY

∼3.5 days

5.4 %(NR)

0.012 μg m−3

Li et al. [100]

   Polypropylene filters w/ phosphoric acid

SKC, Inc.

IMPROVE (select)

24 h

<5 % a (±10 %)

0.018 μg m−3

Chen et al. [29]

   Denuder difference w/ chemiluminescence

URG, Thermo Scientific


5 m

NR (±15–20 %) b

250 ppt

Saylor et al. [150]



Range (ppbv)

Temporal resolution

Precision (uncertainty)

Detection limit



Aerodyne Research, Inc.


5 m avgc

14 pptv (NR)

42 ppt with 5 m avg

Ellis et al. [45]

   CIMS (ground-based)



10 s avgd

NR (±30 %)

100 pptv

Fehsenfeld et al. [53]

   CIMS (aircraft-based)



1 s

NR (25 % ± 0.07 ppbv)

70 pptv

Nowak et al. [123]

   Open-path QC laser

Zondlo (Princeton)

0.20– >2000

0.1 s

0.15 ppbv (0.20 ppbv ± 10 %)

300 pptv at 10 Hz

Miller et al. [111]

aBased on correlation coefficient between collocated measurements being 0.97

bBias adjustment performed regularly against citric acid denuders

c1-s resolution of measurement; averaged for optimal signal

d4-s resolution of measurement; averaged for reliable signal

Regional observational networks have also been established for shorter periods of time. At select sites in the Southeastern Aerosol Research and Characterization (SEARCH) network [72], a more highly resolved approach has produced continuous 5-min observations of NH3 since 2007 [150]. The NH3 concentration is calculated based on the difference between the amount of oxidized nitrogen species produced through >95 % oxidation of flow through one denuder that does not collect NH3 and another that does strip it from the air [150]. At a site collocated with an Interagency Monitoring of Protected Visual Environments (IMPROVE) site near Rocky Mountain National Park, two chemiluminescence monitors were deployed side by side to provide the reactive nitrogen gas concentration by difference for 1 year during the Rocky Mountain Atmospheric Nitrogen and Sulfur study [108]. Building upon this effort, a prototype of accurate and precise filter-based measurements of NH x (NH3+ NH4=NH x ) were added to select western USA IMPROVE sites from April 2011 to August 2012 [29]. This project demonstrated the potential for cost-effective monitoring of NH x across the entire IMPROVE network and provided insight into seasonal NH3 trends and influences [29]. The University Research Glassware (URG) denuder/filter system (URG, Inc., Model 3000CA) has often been deployed at specific locations as a benchmark for new techniques or for longer term measurements such as those taken in Boulder, Wyoming, during 2007–2011 [100]. These longer term measurements in single locations typically provide measurements integrated over multiple days or weeks and characterizations of larger trends.

Techniques to measure NH3 with much higher temporal resolution have been developed more recently and deployed primarily in field campaigns. One such instrument is the chemical ionization mass spectrometer (CIMS) [52, 80]; two novel designs were deployed in the Aerosol Nucleation and Real-Time Characterization Experiment (ANARChE) campaign in 2002 [121]. Subsequently, an instrument was developed that was suitable for use in aircraft because of higher temporal resolution (approximately 5 s) and precision (100 ppt) needed for low NH3 concentrations observed aloft [122]. With improvements in the inlet configuration and more effective purging of the instrument between flights, the CIMS has been employed in additional field campaigns including TexAQS [123] and CalNex [124] with 1-s time resolution. Another method of ascertaining NH3 concentrations is the Aerodyne Research, Inc. Quantum Cascade Tunable Infrared Laser Differential Absorption Spectrometer (QC-TILDAS), which correlated well with a chemiluminescence-based measurement at 1-min resolution during an intercomparison campaign [45]. This closed-path instrument infers the ambient concentration from the absorption spectrum at 967 cm−1, and it was deployed in the Border Air Quality and Meteorology study (BAQS-Met) [46]. The logistical limitations of these approaches, including power consumption and size, led to the innovation of a compact, open-path, high-sensitivity, QC laser-based atmospheric NH3 sensor, which isolates the absorption signal of NH3 at 9.062 μm [111]. To achieve a minimum detection limit of 0.30 ppbv at 10-Hz resolution, absorption at multiple points in the spectrum is isolated with multi-harmonic wavelength spectroscopy [111]. Online calibration reduces the effect of sensor drift, and the open-path design eliminates the measurement artifacts and time lag introduced by the inlet [111]. The dynamic range of the instrument is evident in the on-road observations collected with the instrument mounted atop a passenger vehicle in California and New Jersey in 2012 [166]. Together, these instruments have provided measurements of ambient atmospheric ammonia at the surface and aloft during field campaigns at higher temporal resolution than available through long-term monitoring networks. For comparison, a wide array of in situ NH3 measurement techniques has been undertaken in other parts of the world. For example, simultaneous measurements were conducted of three different approaches in summer 2006 in Switzerland [120] and eleven in summer 2008 in Scotland [177]. Both of these studies highlighted the importance of careful inlet design, and the latter emphasized the robust agreement of the techniques at concentrations greater than 10 ppbv but discrepancies at lower concentrations.

Remote Sensing

While there have been tremendous strides in the availability of in situ measurements as described above, still the spatiotemporal coverage of such measurements is limited on continental to global scales. In contrast, remote sensing measurements of NH3 provide a new means of broadening our understanding of the sources and distribution of reactive nitrogen, especially over regions where there are little or no observations and the emission sources are poorly known. To date, there are lower tropospheric NH3 retrievals from several infrared instruments in sun-synchronous low-earth orbits (LEO), and their attributes are summarized in Table 3.
Table 3

Overview of current and potential NH3 remote sensing capabilities


Across track scanning





Footprint area




level (K)

time (local)

or diameter




0.10 (0.06 unapodized)


1:30 a.m., p.m.

8 × 5 km2

IASI (MetOp-A)





9:30 a.m., p.m.

12 km

IASI (MetOp-B)





9:30 a.m., p.m.

12 km






1:30 a.m., p.m.

14 km






1:30 a.m., p.m.

13.5 km



0.10 (0.06 unapodized)



4 × 4 km2

aIn the 967 cm−1 NH3 spectral band

bAt 280 K

The NASA Tropospheric Emissions Spectrometer (TES) [14] Fourier Transform Spectrometer (FTS) was launched on the Aura satellite on July 15, 2004. TES has a high spectral resolution of 0.1 cm−1 (apodized), good radiometric noise of ∼0.1−0.2 K at 280 K [156, 185], is in an orbit that includes a mid-day overpass (∼1:30 a.m. and 1:30 p.m. LST), and has a relatively small spatial footprint of 5 ×8 km2 , all of which are favorable conditions for boundary layer NH3 detection. One limitation of the TES global survey NH3 observations is the lack of spatial density, as the spacing between consecutive observations can be as large as 180 km, with a repeat cycle of 16 days. TES provided the first detection of boundary layer NH3 from space [15], but since then, there have been a number of space-based lower tropospheric NH3 observations that have contributed to improving our understanding of atmospheric NH3. The Infrared Atmospheric Sounder Interferometer (IASI) [33] FTS launched on two MetOp satellites has also provided very valuable NH3 observations [67, 76, 86, 147, 169, 172]. IASI is a scanning sensor that provides broad spatial coverage approximately 3 h earlier than TES. The spectral resolution of IASI is coarser than TES while the spectral radiometric noise in the NH3 retrieval regions is similar (see Table 3). Both TES and IASI have measured temporal and spatial distributions of lower tropospheric NH3 concentration values regionally (e.g., [15, 32]) and globally [31, 157, 172] and thus far have provided the bulk of the available satellite NH3 observations for air quality purposes.

However, there are new observations from the Cross-track Infrared Sounder (CrIS) FTS instrument on board the NOAA/NASA/DoD Suomi National Polar-orbiting Partnership (NPP) satellite launched in 2011 that have demonstrated to also provide lower tropospheric NH3 observations [155]. Many of the CrIS instrument characteristics are very similar to IASI (see Table 3), but it has four times lower noise than TES and IASI, and the early afternoon daytime overpass time, allowing it to approach the retrieval capabilities of the higher spectral resolution TES observations. There are also potential NH3 observations (Warner et al. 2014) from the Atmospheric Infrared Sounder (AIRS) grating spectrometer [8] launched on the LEO NASA Aqua satellite in 2002 with similar overpass times to TES and CrIS. AIRS also has the broad spatial coverage of a scanning instrument (similar to IASI and CrIS, see Table 3) but with a slightly reduced spectral resolution and similar radiometric noise [170].

Satellite observations of NH3 are inferred from measured spectral radiances, which generally requires a complex retrieval inversion process with assumptions on the profile shape and variability (e.g., [32, 155, 157, 172]). Since the infrared NH3 signal is relatively small (<1 K brightness temperature) compared to the overall background signal (order of 300 K brightness temperature), there is limited information that can be obtained from satellite retrievals. TES has the most sensitivity to NH3 concentrations on a per retrieval basis. Shephard et al. [157] showed that the TES NH3 retrievals: (i) have a minimum detection level corresponding to a profile with a surface volume mixing ratio of ∼1 ppbv, (ii) typically have peak vertical sensitivity in the boundary layer between 900 and 700 hPa (1–3 km), and (iii) provide ∼1 piece of information (degrees-of-freedom-for-signal, DOFS) under favorable retrieval conditions. While TES recovers a vertically resolved NH3 profile, we often consider the averaging kernel weighted mean of this profile, aka the Representative Volume Mixing Ratio or RVMR. This single concentration estimate has less dependence on the algorithm’s a priori profile and is more easily visualized in 2D. A full description of the RVMR and the determination of measurement limits is provided in Shephard et al. [157]. Typical measured RVMR values directly over NH3 source regions in North America are above 10 ppbv; mean values over the entire central USA are ∼1.5 ppbv [157].

Since these satellite retrievals can be challenging, it is important to evaluate the satellite measurements with other available observations. Given the sampling differences between satellite and in situ observations, and the fact that NH3 is very inhomogeneous over small distances, performing direct validations of the lower tropospheric satellite observations with sparsely available (mostly at the surface) in situ NH3 observations is difficult. There have been some very valuable indirect correlation comparisons performed to demonstrate the quality of the satellite NH3 observations. It has been shown that the TES NH3 observations are well correlated with the in situ observations both spatially and seasonally [136]. Similarly, IASI NH3 total column retrievals compare well with indirect in situ surface and aircraft measurements [173]. Total column values estimated from simultaneous aircraft and surface measurements during the DISCOVER-AQ campaign in California in 2013 [166] are within the estimated uncertainty of the TES total column measurements. Initial CrIS comparisons during the same campaign show that it qualitatively captures the spatial variability of the boundary layer NH3 concentrations as revealed by nearby in situ surface observations and TES satellite observations; the quantitative differences between the CrIS and TES boundary layer observations are often within the estimated retrieval uncertainty of the two measurements [155]. During a recent intensive Joint Canada-Alberta Oil Sands Monitoring (JOSM) field campaign, TES and aircraft NH3 direct volume mixing ratio profile comparisons were carried out, where the assumed prior information (i.e., profile shape) and broad vertical resolution of the satellite retrievals have been taken into account [154]. From these direct comparisons under conditions where the NH3 volume mixing ratio amounts were relatively small (median value of 1.0 ppbv at 900 hPa), the actual errors show a small bias of ∼+7 % with a standard deviation of ∼±25 % at 825 hPa height, which is consistent with the estimated TES NH3 retrieval bias of +7 % based on simulations [157] and the TES reported estimated retrieval uncertainty of ∼±30 %.

These new LEO satellite remote sensing observations have already proven useful for evaluating model estimates of NH3 distributions and inverse modeling of NH3 sources in both regional and global chemistry transport models. Both TES and IASI observations have revealed broad under-prediction of NH3 concentrations in the models. For example, Shephard et al. [157] showed using TES data that the global GEOS-Chem model (in which NH3 emissions for anthropogenic and natural sources were based on the 1990 GEIA inventory [21] with monthly variation scaled according to Gilliland et al. [65]) under-predicted NH3 concentrations over most of the globe, with a bias of monthly mean RVMR over 4 years (2006–2009) larger than 7 ppbv in Asia. Walker et al. [179] (using TES) and Heald et al. [76] (using IASI) showed underestimation of NH3 over California in GEOS-Chem (based on the EPA NEI 2005) by −79 % (normalized mean bias) of RVMR and more than 0.3×1016 molec cm−2 of the vertical column concentration, respectively, leading to a local underestimation of ammonium nitrate aerosol. Similarly, Kharol et al. [86] when investigating the sensitivity of inorganic aerosol to NO x emissions showed that GEOS-Chem generally under-predicted NH3 observations over Asia (using NH3 emissions from Streets et al. [165] with a 30 % reduction) compared with IASI NH3 observations by more than 0.5 ×1016 molec cm−2. Zhu et al. [190] used TES NH3 observations to provide top-down (inverse modeling) constraints on NH3 emissions in GEOS-Chem, which improved the normalized mean bias between model and AMoN observations by up to 90 %. Also, coincident TES observations of NH3 and CO have been used to demonstrate the potential of using remote sensing data to identify NH3 emission sources and constrain emission inventories (e.g., [107]). TES observations in combination with surface and aircraft NH3 observations have also been used to provide insight on the treatment of the diurnal variability of NH3 from livestock emissions in both GEOS-Chem and the regional Community Multiscale Air Quality (CMAQ) model (e.g., [191]).

NH3 Measurement and Modeling Frontiers

Improved Mechanistic Models of NH3 Sources and Sinks

Estimation of the global anthropogenic influence on the nitrogen cascade through NH3 production and use was first quantified with the Moguntia Eulerian tropospheric model [42]. Higher resolution estimates of NH3 emissions followed [21], and these inventories continue to be refined through top-down and bottom-up analysis (e.g., [130, 134]). Additionally, representations of inorganic aerosol thermodynamics, which capture the volatility of NH3 from suspended aerosol, were developed in tandem with these three-dimensional models (e.g., [11, 87, 88, 119]). Furthermore, the interactions of NH3 with ecosystems were determined to be a function of a canopy compensation point, which reflects the bidirectional exchange of NH3 [6]. As described below, not until recently have modeling approaches that quantify these fluxes been implemented in three-dimensional chemical transport models [56]. Integration of this model and emission inventory developments into regional (e.g., CMAQ [10]) and global chemical transport models (e.g., GEOS-Chem [191]) will enable the environmental decision-making community and scientists to better understand the dynamic interplay between NH3 emissions, deposition, and climate [169].

The dry deposition scheme in most air quality models is based on the resistance in series formulation of Wesely [182], which only considers the unidirectional flux of NH3 from the air to the surface. However, the air-surface exchange is known to actually be bidirectional, e.g., the net flux can either be evasion or deposition [56]. Two different strategies have been used in regional and global air quality models to capture the bidirectional nature of NH3 air-surface exchange: (i) Models that have parameterized the flux based on empirical relationships [91] or lookup tables for different land use types [39]. (ii) Semi-empirical process-based models that parameterize agricultural nitrogen management, the soil \(\text {NH}_{4}^{+}\) pool, and model the flux between the atmospheric and soil pools [10, 59, 191]. In the second type of model, the total air-surface exchange flux is calculated as a function of the gradient between the ambient NH3 concentration in the first (surface) layer of the model and the canopy compensation point [10, 139] (see Fig. 1). The latter is calculated as a function of temperature and NH3 emission potential, which in turn depends upon the concentrations of \(\text {NH}^{+}_{4}\) in the soil pool. More details of this bidirectional scheme can be found in Cooter et al. [34], Cooter et al. [35], and Pleim et al. [139]. The overall impact of the NH3 bidirectional exchange process is to effectively enhance the atmospheric lifetime of NH3 through the regulation of deposition, and the storage of deposited NH3 in a soil pool where it can later re-emit.
Fig. 1

Schematic of unidirectional versus bidirectional treatment of NH3 deposition and emission

Both CMAQ and GEOS-Chem have recently been updated to included representation of NH3 bidirectional exchange, as well as improved diurnal variability of NH3 from livestock. While the detailed equations governing these mechanisms are provided in these papers, here we qualitatively describe these features. The standard, static, NH3 livestock emissions in models such as GEOS-Chem are evenly distributed throughout the 24 h of each day of the month. That the simulated NH3 livestock emissions did not have significant diurnal variation is a likely explanation for large (∼×2) nighttime overestimates of NH3 of both of these models with hourly ammonia observations. European models use empirical relationships with wind speed and temperature to derive a diurnal profile [161] for livestock emissions. Here, we describe a more physically based empirical diurnal profile for the hourly NH3 livestock emissions similar to the work done for sea bird colonies by Riddick et al. [148]. Here, we assume that animal NH3 emissions originates from ammonium in the manure solution and is transported from the emission sources via atmospheric processes. The diurnal profile was applied to monthly emissions (1) to preserve the different animal emission factors and seasonality introduced in the compilation of emissions,
$$ E_{\mathrm{NH_{3}}}(t) = \frac{c_{\mathrm{T}}(t) / R_{\text{ATM}} (t)}{\overline{c_{\mathrm{T}}} / \overline{R_{\text{ATM}}}} \overline{E_{\mathrm{NH_{3}}}}, $$
where, \(E_{\text {NH}_{3}}\) is the ammonia emissions, c T is the combined Henry and dissociation equilibria for NH3 and \(\text {NH}_{4}^{+}\) following Nemitz et al. [118], R ATM is the atmospheric resistance, and t is time. The overbars indicate monthly averages. The results from Eq. 1 estimated much lower nighttime emissions and higher rates of emissions during the daytime (Fig. 2). Hourly emissions are calculated from monthly emissions using hourly changes to the aerodynamic resistance and Henry’s equilibrium coefficient as function of surface temperature. This new diurnal distribution scheme (referred to later as the dynamic scheme) for NH3 livestock emissions has been developed in CMAQ and implemented in GEOS-Chem. The overall impact of this scheme, in both models, is to decrease livestock NH3 emissions at night, when temperatures are colder, and to increase them during the day. We recognize, however, that this treatment is only an initial step given that livestock in different regions are subject to different husbandry practices.
Fig. 2

July, 2007, CMAQ continental US hourly emissions fraction (dimensionless) using the static profile (red) and the dynamic profile (green). Note that the static profile is the same for each day, whereas the dynamic profile varies with atmospheric conditions

The Value of Geostationary Remote Sensing Measurements for NH3

IASI and CrIS are both integral to operational meteorological polar-orbiting systems. IASI has already been launched on two MetOp satellites, and there are plans for at least one more launch. CrIS is expected to be deployed on future NASA/NOAA Joint Polar Satellite System (JPSS) satellites. Both sensors will thus continue to provide global NH3 observations for many years. Although these current LEO polar-orbiting space-based sensors are yielding unprecedented NH3 observations in the lower troposphere and boundary layer globally, the restricted diurnal sampling and large footprint size of the observations limits the characterization of some of the fundamental aspects of the NH3 emissions, especially the issues identified in the previous section: the dependence of NH3 bidirectional exchange on the surface emissions potential, and the diurnal variability of NH3 emissions from livestock operations.

The GEO-CAPE mission [55], recommended in the NASA decadal survey [125], would provide geostationary measurements of tropospheric constituents relevant to air quality and climate for the first time over North America. The high spatial and temporal resolution of GEO-CAPE (hourly observations every ∼4 km) offers new possibilities for constraining emissions that are not achievable with low-earth-orbit (LEO) platforms, such as allowing nearby pollution sources to be separated and observed individually, e.g., roads, farms, or point sources in densely populated regions. Geostationary observations would also provide critical tests for the temporal behavior of existing inventories and could improve mechanistic models that predict emissions when direct observations are not available. As part of GEO-CAPE, the Tropospheric Emissions: Monitoring of POllution (TEMPO) mission is slated for launch in 2019. This instrument will measure in the UV and visible range, making hourly observations at 4-km resolution primarily of NO2 and ozone. With this spectral range, TEMPO will not measure the absorption of species such as CO, CH4, or NH3. For these species, the GEO-CAPE science team supports a second mission, named GCIRI (GEO-CAPE InfraRed Instrument), which would complement TEMPO with measurements in the IR range necessary to detect these species.

Here, we explore the potential of a GCIRI geostationary measurement of NH3 to fundamentally improve our understanding of NH3 sources at a mechanistic level, focusing on the diurnal variability and bidirectional flux of NH3 as described in Section “6.” This will allow for enhancements to air quality models that outlast the lifetime of the instrument itself (a uniquely different goal from, e.g., forecasting or monitoring). We thus consider two case studies that address the following questions: (1) Would GCIRI observations be able to evaluate uncertainties in fertilizer application rates and bidirectional NH3 fluxes? (2) Would GCIRI observations allow for improved representation of the diurnal variability of livestock emissions in air quality models? For both, we consider the information from both GCIRI and existing LEO instruments, and we evaluate the impacts of model adjustments on estimates of aerosol nitrate.

While real geostationary measurements NH3 are not yet available for analysis, we can instead generate pseudo-observations from a geostationary instrument, GCIRI, as well as a LEO instrument, by sampling modeling values as if they were the real atmosphere, and applying satellite retrieval algorithms to these samples. For the GCIRI instrument specifications in this Observing System Simulation Experiment (OSSE), we have been fairly conservative and adopted the instrument spectral resolution and measurement noise from the TES instrument, see Table 3; its combination of spectral resolution and instrument noise provides the most accurate present day boundary layer (0–2 km) NH3 sensitivity observed from space. This approach does though neglect uncertainties owing to model transport error. However, it should be noted that a future GCIRI-type instrument is likely to benefit from even lower instrument noise (more similar to CrIS instrument noise), with spectral resolution somewhere in the 0.1 cm−1 (TES) to ∼0.5 cm−1 (IASI and CrIS) range. Furthermore, GCIRI’s actual horizontal spatial footprint of 4 km at the center of the domain will provide better sampling of local emission sources (e.g., large cities, agricultural regions, and oil extraction areas) than what is represented in our 12-km scale OSSE.

Constraints on Bidirectional Exchange

Here, we consider a case study to evaluate how variations in NH3 concentrations owing to the bidirectional exchange of NH3 at the surface may or may not be discernible using space-based measurements. Modeled WRF and CMAQ 12 ×12 km2 simulations were conducted for June of 2006 and include all anthropogenic emissions from the 2005 EPA National Emissions Inventory scaled to 2006 using 2006 continuous emissions monitoring observations and 2006 WRF modeled meteorology. These simulations are described in detail in Dennis et al. [40]. Results from CMAQ simulations with standard unidirectional NH3 emissions are shown in the left panel of Fig. 3. The impacts of bidirectional exchange are evaluated by repeating this simulation, using the bidirectional NH3 emissions scheme from Bash et al. [10], and the results are shown in the center panel. The shift in the patterns between the base and bidirectional case is due to the NEI estimation of fertilizer NH3 emissions based on fertilizer sales within the county and a prescribed seasonal profile. In the bidirectional exchange case, fertilizer application is modeled based on modeled plant nutrient demand, fertilizer application method, and modeled soil biogeochemistry at the model grid cell resolution [35]. Note that the simulations used here are a subset of the simulations in Dennis et al. [40]. In these simulations, the +50 % gamma case had a simple look up table for the mesophyll gamma while the bidirectional case used the mesophyll gamma parameterization from Massad et al. [110] resulting in higher mesophyll NH3 compensation points for crops and thus the increase in ambient NH3 seen in the center panel of Fig. 1. The model was found to be most sensitive to the fertilizer application and soil compensation point in agricultural areas [40]. One of the larger sources of uncertainties in implementing such a scheme is the fertilizer application rate. We thus also consider a third simulation, right panel, which shows surface-level NH3 concentrations when the fertilizer rate is increased by 50 %.
Fig. 3

Average surface-level NH3 concentrations over southern California from CMAQ simulations using (left) unidirectional NH3 emissions (center) bidirectional NH3 fluxes, and (right) bidirectional NH3 fluxes with enhanced fertilizer application rate

We next use these CMAQ simulations to generate both LEO and GCIRI pseudo observations of NH3 RVMR. The maps in Fig. 4 show differences in GCIRI pseudo observations between these scenarios. The red X’s indicate locations where LEO measurements from TES were available from a standard global survey retrieval. Their values would be the same as those from GCIRI, just limited to these locations. The maps show the difference between cases with the standard unidirectional NH3 emissions (Base), bidirectional exchange (Bidi), and bidirectional exchange with enhanced fertilizer application (Fert). The maps obtainable from a GCIRI type measurement clearly show key differences between the Base and Bidi simulations, with the latter leading to smaller RVMRs in the western part of the domain and larger values in the Central Valley (the region with concentrations above 10 ppbv in Fig. 3).
Fig. 4

Differences in GCIRI RVMR values corresponding to three different atmospheres from the CMAQ simulations showing in Fig. 3: Base (unidirectional NH3 emissions), Bidi (bidirectional fluxes of NH3), and Fert (bidirectional fluxes of NH 3 with a 50 % increase in fertilizer). Also shown (red X’s) are the locations during this time period where there were LEO observations available from TES

LEO transects from TES, on the other hand, would not have been capable of making these distinctions given their sparse sampling—the differences in RVMR across scenarios at the LEO transect locations are rarely larger than 0.4 ppbv, which is close to the retrieval uncertainty of ±30 % (although the differences are >5 ppbv elsewhere). Measurements from CrIS have similar levels of uncertainty, but a much more complete spatial coverage (see Section “Remote Sensing”), with a spatial resolution similar to that of the 12 × 12 km2 model resolution used in these tests. Assuming that CrIS measurements are normally distributed with an uncertainty of ±30 %, we consider the differences shown in the left, center, and right panels of Fig. 4 and calculate that the percentages of the grid cells for which these differences are statistically significant (p value <0.1) to be 18, 37, and 17 %, respectively. Given that GCIRI would have ∼7 times the sampling density of CrIS, we assume a ±10 % error at the 12 × 12 km2 scale and evaluate the ability of GCIRI to discriminate between these simulations. With GCIRI, differences across the left, center, and right panels are visible 43, 70, and 46 % of the time, respectively. While we have not yet performed any top-down inverse modeling studies with such datasets, these results suggest that GCIRI would be able to distinguish between fundamentally different drivers of NH3 sources much more often than existing LEO measurements. This provides qualitative evidence that GCIRI would provide new information for improving model treatment of NH3 emissions at a process level. We do note that the differences between the models tested here are admittedly quite stark, hopefully more-so than model uncertainty by a potential 2020 launch, and we have assumed clear-sky conditions which will overestimate the spatial sampling benefits of GCIRI. However, here we have also only considered measurements once-per-day; the additional benefit of hourly measurements for GCIRI are explored in the next case study.

We also evaluate the differences in these scenarios in terms of impact on \(\text {NO}_{3}^{-}\) aerosol. Figure 5 shows measured and modeled surface-level aerosol \(\text {NO}_{3}^{-}\) at CSN (top) and IMPROVE (bottom) sites. Nitrate generally increased in the Central Valley of California in the summer when using the bidirectional exchange scheme due to an increase in the NH3 concentrations largely from a reduction in the NH3 dry deposition and abundant NO x . Note that this is specific to this domain at during this time and that nitrate aerosol reductions have been observed in other parts of the country during the spring and fall due to the implementation of the bidirectional exchange option in CMAQ [10]. CMAQ hourly \(\text {NO}_{3}^{-}\) aerosol estimates were paired in time, averaged to the 24-h sampling frequency, and space with the 9 CSN sites and 11 IMROVE sites in the modeling domain. Total PM2.5 exceeded 20 μg m−3 at CSN sites during this time period, more than 10 % of which was \(\text {NO}_{3}^{-}\). First, we note that the implementation of NH3 bidirectional exchange causes \(\text {NO}_{3}^{-}\) to increase relative to the base case simulation at all times and locations—by 10 % at the CSN sites and 44 % at the IMPROVE sites. This occurs even though NH3 levels are typically quite high in the Central Valley, and nitrate formation is thought to be limited more by NO x than NH3. Increasing the fertilizer emissions by 50 % results in additional increases of \(\text {NO}_{3}^{-}\) at CSN sites by 21 % and IMPROVE sites by 19 %. In comparison to the observations, we also note that the base case version of the CMAQ model has a low-bias with regards to nitrate observations in California at this time of year. This bias is reduced by 10 % at CSN sites and by 20 % at the IMPROVE sites in the Bidi case, with even further improvements if fertilizer is increased. However, the remaining biases in nitrate in California may be related to model biases in other particulate bases or missing processes [85]. This case study indicates that such model improvements, which are potentially constrainable by GCIRI observations, could have measurable and meaningful impact on estimates of aerosol, in addition to further understanding the factors that control PM2.5 concentrations.
Fig. 5

CMAQ model estimated surface-level nitrate aerosol concentrations in CA compared to observations of (top) CSN and (bottom) IMPROVE. Simulations include the Base case (unidirectional NH3 emissions), the Bidi case (bidirectional exchange of NH3) and a bidirectional simulation with 50 % higher fertilizer application rates

Constraints on Diurnal Variability

The second question we address is whether or not GCIRI observations could provide constraints on the diurnal variability of NH3 emissions from livestock. It is known that the diurnal variability of NH3 sources strongly affects surface-level concentrations nearby. What has not been shown is whether or not the impact of this variability is significant enough to cause detectable changes in the NH3 vertical profile seen by satellites, i.e., changes occurring at altitudes in the 900–700 hPa range.

Here, we consider results from experiments performed using simulations from the CMAQ model run at the 12 ×12 km2 scale using the same statics versus dynamic emissions schemes described in Section “6.” Only days in which at least four time periods have retrievals with DOFS >0.4 are selected in the analysis. Plus, only the individual results in which there were at least 0.1 DOFS were considered to ensure that there was some information being provided by each observation. These are shown in Fig. 6, where results plotted in red indicate the simulated atmospheric conditions and results in blue show the conditions as detected by GCIRI. The top panel shows the difference between the CMAQ model surface concentrations from the dynamic case minus the static case in locations in California with dominant livestock emissions on July 22, 2006. In the second row of Fig. 6, the differences in CMAQ RVMR values are shown, and in the third row, the differences in RVMRs detectable from the GCIRI instrument are shown. The latter demonstrates that the GCIRI instrument is indeed able to detect significantly lower NH3 concentrations at night, with a mean difference of −2.6 ppbv at 4 a.m. and slight increases during the day, with a mean difference of up to 0.7 ppbv in the mid-afternoon (1–4 p.m.). These parameters highlight the reduced retrieval sensitivity and range of peak pressure sensitivity levels at 7 a.m., resulting in less valid comparisons at this time of the day. Also shown in this figure is the pressure level of the peak instrument sensitivity that contributes to the RVMR, the DOFS, and the temperature contrast. Despite the smaller temperature contrast at night, the differences in NH3 concentrations between the static and dynamic cases are still detectable. This OSSE demonstrates that a GCIRI-type geostationary would generally be able to capture the expected difference between different diurnal NH3 emission profiles, and it would be a valuable tool in advancing our understanding of NH3 emissions in North America.
Fig. 6

Results of CMAQ model simulations using dynamic-static diurnal emissions reported as a function of local time of day. The top panel shows differences in the model surface concentrations between runs with dynamic and static diurnal Concentrated Animal Feeding Operations (CAFO) emissions. The second panel shows the same differences as the top panel, but for the model computed RVMR values, which can be compared to the corresponding pseudo geostationary satellite (GCIRI) RVMR observations shown in the third panel. The fourth panel show the pressure levels of the RVMR values used in the second and third panels. The pseudo satellite retrieved GCIRI sensitivities reported in terms of degrees-of-freedom for signal (DOFS) are plotted in the fifth panel. The bottom panel contains the atmospheric thermal contrast between the surface and the first profile level. The box edges are the 25th and 75th percentile, the line in the box is the median, and the diamond is the mean

Supposing that the dynamic emissions of NH3 from livestock are eventually an observable feature of air quality models, it is of interest to evaluate the impacts of such an enhancement to NH3 simulations more broadly. We thus consider the impact of the diurnal variability of livestock NH3 emissions over the USA. The dynamic scheme for NH3 livestock emissions described in Section “6” is implemented in 0.5×0.667 resolution GEOS-Chem simulations for July 2006. We also perform simulations using the standard livestock emissions (constant monthly values), aka the static case. Plots of the spatial distribution over the USA in July of 2006 of NH3, nitrate, and nitrogen deposition, are shown in Figs. 7, 8, and 9. The impacts of livestock emissions’ diurnal variability on monthly mean NH3 concentrations can be significant, up to 50 %. Concentrations are reduced as less NH3 is emitted into shallow boundary layers during the night using the dynamic scheme; instead, emissions peak during the day, when dynamic export away from the surface is more efficient and the increased boundary layer height (relative to nighttime) decreases the NH3 concentration. There are corresponding reductions in aerosol nitrate. For both NH3 and nitrate, some of the largest decreases are in spatially isolated regions, such as the San Joaquin Valley for NH3, or the New Jersey area for nitrate. These changes are much weaker in the global 2×2.5 simulations of Zhu et al. [191]; thus, it seems likely that the impacts of the dynamic diurnal variability scheme may be particularly important for higher-resolution nested models. Regardless, the impacts on nitrogen deposition however are fairly small, impacting total reactive nitrogen less than 10 %, as oxidized nitrogen dominates reactive nitrogen deposition in much of the country (e.g., [47]).
Fig. 7

Average surface-level NH3 over the USA during July, 2006, from GEOS-Chem high-resolution (0.5 × 0.667) simulations. Static simulations contain invariant diurnal NH3 livestock emissions

Fig. 8

Average surface particulate nitrate over the USA during July, 2006, from GEOS-Chem high-resolution (0.5 × 0.667) simulations. Static simulations contain invariant diurnal NH3 livestock emissions

Fig. 9

Total nitrogen deposition in the USA during July, 2006, from GEOS-Chem high-resolution (0.5 × 0.667) simulations. Static simulations contain invariant diurnal NH3 livestock emissions


In this review, we have considered recent progress in observing, modeling, and quantifying the impact of NH3 on many aspects of our environment. Recent research has highlighted the outsized role that NH3 plays in air quality, climate, and deposition of reactive nitrogen owing to several factors: (i) NH3 concentrations have risen considerably since pre-industrial times and are projected to continue to rise globally, (ii) particulate matter concentrations are often highly sensitivity to NH3 levels that dictate ammonium nitrate formation, (iii) declines in SO2 emissions will exacerbate the aforementioned effect, and (iv) formation of ammonium nitrate facilitates long-range transport of reactive nitrogen and its ultimate deposition in sensitive ecosystems and water bodies. Commensurate with these research developments are efforts to expand measurement and modeling capabilities for NH3. New routine monitoring, precise in situ mobile measurements, and remote sensing platforms have helped transform our ability to evaluate NH3. This in turn has spurred enhanced development of the representation of NH3 in air quality models. Ultimately, we hope this cyclic process will provide a stronger basis for developing policy that takes advantage of the efficiency of NH3 emissions controls in mitigating a wide-range of environmental concerns in North America.

In addition to considering the significant research strides made in recent years, we also look to the potential of future remote sensing measurements to help further our understanding of NH3, particularly the interplay between emissions, deposition, and climate. Towards this end, we present new work assessing the value of GEO versus LEO remote sensing observations for constraining fundamental processes governing NH3 and ammonium nitrate aerosol in air quality models: the diurnal variability of NH3 emissions from livestock sources and bidirectional exchange of NH3 from soils. In our first case study, we demonstrate that even though bidirectional exchange largely impacts surface-level NH3, whereas thermal IR instruments are most sensitive to NH3 levels 1–2 km above the surface, a theoretical geostationary IR instrument (GCIRI) would clearly detect differences in NH3 distributions owing to the bidirectional fluxes of NH3 from soils, in conditions where current LEO measurements would not. These differences, even in regions such as the Central Valley of California which are already NH3 rich, are shown to have notable impacts on model estimated aerosol nitrate, reducing the model bias by 10–20 % relative to surface-level observations.

In our second case study, we found that over the USA, the differences between a constant monthly NH3 emissions and one in which the livestock emissions respond dynamically to local environmental conditions on an hourly basis is not detectable in the national-scale average NH3 profiles by LEO instruments (e.g., TES), even though such differences may impact surface-level aerosol nitrate by up to 50 %. Some small differences are currently detectable over select locations, such as when restricting analysis to a few grid boxes in California where the satellite retrieval DOFS were high (>0.5) and the local emissions were dominated by livestock sources (>75 %), yet, the differences were still less than a fraction of a parts per billion. In contrast, simulated geostationary observations generated from CMAQ simulations similarly show large (up to 2.5 ppbv) signals in the difference between day and nighttime concentrations.

These two case studies demonstrate the advantages of the spatiotemporal coverage of geostationary observations, even when instrument sensitivities peak above the surface level, for improving our understanding of the diurnal variability and bidirectional exchange of NH3 sources. Likewise, validation of these geostationary observations with in situ observations/aircraft measurements will also be needed in the future studies. As air quality models evolve to simulate these processes, the value of a geostationary instrument to constrain these processes over wide spatial and temporal scales is becoming increasingly important. The impacts of detailed NH3 source modeling is shown here to have significant impacts on aerosol nitrate, and hence PM2.5. Further studies may also evaluate the impact on our understanding of sources of reactive nitrogen deposition and the role of the nitrogen cycle on climate forcing.



This work was supported by funding from the NASA GEO-CAPE Science Team. Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official agency policy. On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© Springer International Publishing AG 2015

Authors and Affiliations

  • Liye Zhu
    • 1
    • 2
  • Daven K. Henze
    • 1
    Email author
  • Jesse O. Bash
    • 3
  • Karen E. Cady-Pereira
    • 4
  • Mark W. Shephard
    • 5
  • Ming Luo
    • 6
  • Shannon L. Capps
    • 1
    • 3
  1. 1.Department of Mechanical EngineeringUniversity of ColoradoBoulderUSA
  2. 2.Department of Atmospheric ScienceColorado State UniversityFort CollinsUSA
  3. 3.US Environmental Protection Agency, Research Triangle ParkDurhamUSA
  4. 4.Atmospheric and Environmental Research, Inc.LexingtonUSA
  5. 5.Environment CanadaTorontoCanada
  6. 6.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA

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