Reviewing Global Estimates of Surface Reactive Nitrogen Concentration and 1 Deposition Using Satellite Observation 2

Abstract. Since the industrial revolution, human activities have dramatically changed the nitrogen (N) cycle in natural systems. Anthropogenic emissions of reactive nitrogen (Nr) can return to the earth's surface through atmospheric Nr deposition. Increased Nr deposition may improve ecosystem productivity. However, excessive Nr deposition can cause a series of negative effects on ecosystem health, biodiversity, soil, and water. Thus, accurate estimations of Nr deposition are necessary for evaluating its environmental impacts. The United States, Canada and Europe have successively launched a number of satellites with sensors that allow retrieval of atmospheric NO2 and NH3 column density, and therefore estimation of surface Nr concentration and deposition at an unprecedented spatiotemporal scale. Atmosphere NH3 column can be retrieved from atmospheric infra-red emission measured by IASI, AIRS, CrIS or TES, while atmospheric NO2 column can be retrieved from reflected solar radiation measured by GOME, GOME-2, SCIAMACHY, OMI, TEMPO, Sentinel and GEMS. In recent years, scientists attempted to estimate surface Nr concentration and deposition using satellite retrieval of atmospheric NO2 and NH3 columns. In this study, we give a thorough review on recent advances of estimating surface Nr concentration and deposition using the satellite retrievals of NO2 and NH3, present a framework of using satellite data to estimate surface Nr concentration and deposition based on recent works, and summarize the existing challenges for estimating surface Nr concentration and deposition using the satellite-based methods. We believe that exploiting satellite data to estimate Nr deposition has a broad and promising prospect.


environmental impacts. The United States, Canada and Europe have successively 26 launched a number of satellites with sensors that allow retrieval of atmospheric NO 2 27 and NH 3 column density, and therefore estimation of surface N r concentration and 28 deposition at an unprecedented spatiotemporal scale. Atmosphere NH 3 column can be 29 retrieved from atmospheric infra-red emission measured by IASI, AIRS, CrIS or TES, 30 while atmospheric NO 2 column can be retrieved from reflected solar radiation 31 measured by GOME, GOME-2, SCIAMACHY, OMI, TEMPO,Sentinel and GEMS. 32 In recent years, scientists attempted to estimate surface N r concentration and 33 deposition using satellite retrieval of atmospheric NO 2 and NH 3 columns. In this study, 34 we give a thorough review on recent advances of estimating surface N r concentration 35 and deposition using the satellite retrievals of NO 2 and NH 3 , present a framework of 36 using satellite data to estimate surface N r concentration and deposition based on 37 recent works, and summarize the existing challenges for estimating surface N r 38 concentration and deposition using the satellite-based methods. We believe that 39 exploiting satellite data to estimate N r deposition has a broad and promising prospect.  (Canfield et al., 2010). N 2 is the main 46 component of air, accounting for 78% of the total volume of air, but it cannot be 47 directly used by most plants. N r (such as NO 3 and NH 4 + ) is the main form of N that 48 can be directly used by most plants, but the content of N r in nature is much lower 49 compared with ON and N 2 (Vitousek et al., 1997;Nicolas and Galloway, 2008). The 50 https://doi.org/10.5194/acp-2020-91 Preprint. Discussion started: 24 February 2020 c Author(s) 2020. CC BY 4.0 License.
supply of N r is essential for all life forms and contributes to the increase in 51 agricultural production, thus providing sufficient food for the growing global 52 population David et al., 2013;Galloway et al., 2004b;Erisman 53 et al., 2008). Before the industrial revolution, N r mainly came from natural sources 54 such as biological N fixation, lightning and volcanic eruption (Galloway et al., 2004a). 55 Since the industrial revolution, human activities (e.g. agricultural development, 56 combustion of mineral energy) have greatly perturbed the N cycle in natural systems 57 (Canfield et al., 2010;Kim et al., 2014;Lamarque et al., 2005).

58
N r (NO x and NH 3 ) emitted to the atmosphere will return to the earth surface through 59 atmospheric deposition (Liu et al., 2011). Atmospheric N r deposition refers to the 60 process in which N r are removed from the atmosphere, including wet (rain and snow) 61 and dry (gravitational settling, atmospheric turbulence, etc.) deposition (Xu et al.,62 2015; Zhang et al., 2012;Pan et al., 2012). The input of N r over terrestrial natural 63 ecosystems primarily comes from the N r deposition (Shen et al., 2013;Sutton et al., 64 2001; Larssen et al., 2011). In the short term, atmospheric N r deposition can increase 65 the N r input to ecosystems, which promotes plant growth and enhances ecosystem 66 productivity (Erisman et al., 2008;Sutton et al., 2013). However, excessive 67 atmospheric N r deposition also causes a series of environmental problems (Liu et al.,68 2017d). Due to the low efficiency of agricultural N application, plenty of N r is lost 69 through runoff, leaching and volatilization, causing serious environmental pollution.

70
Excessive N r deposition may aggravate the plant's susceptibility to drought or frost, 71 reduce the resistance of plant to pathogens or pests, and further affect the physiology 72 and biomass distribution of vegetation (ratio of roots, stems and leaves) (Stevens et al.,73 2004; Nadelhoffer et al., 1999;Bobbink et al., 2010;Janssens et al., 2010). Excessive 74 N r leads to eutrophication and related algal blooms over aquatic ecosystems, reducing 75 https://doi.org/10.5194/acp-2020-91 Preprint. Discussion started: 24 February 2020 c Author(s) 2020. CC BY 4.0 License.
water biodiversity (Paerl et al., 2014), while excessive N r in drinking water also poses 76 a threat to human health (Zhao et al., 2013). Therefore, monitoring and estimation of 77 surface N r concentration and deposition on the global scale are of great importance 78 and urgency.

79
The methods of estimating atmospheric N r deposition can be divided into three An ACTM can simulate N r deposition at regional or global scales through explicitly 138 representing the physical and chemical processes of atmospheric N r components 139 (Zhao et al., 2017;Zhang et al., 2012). Wet N r deposition flux is parameterized as 140 in-cloud, under-cloud and precipitation scavenging (Amos et al., 2012;Levine and 141 Schwartz, 1982;Liu et al., 2001;Mari et al., 2000), while dry deposition flux can be 142 obtained as the product of surface N r concentration and V d , which is typically 143 parameterized as a network of resistances (Wesely and Hicks, 1977 (Kharol et al., 2015) 195 found that the satellite-derived surface NO 2 concentration using the above method is  Comparing with NO 2 , the development of satellite NH 3 monitoring is relatively late.

236
The spatial coverage of ground monitoring sites focusing on N r deposition is still not 237 adequate, and the monitoring standards and specifications in different regions of the 238 world are not consistent, presenting a barrier to integrating different regional 239 monitoring data. Large uncertainties exist in N r emission inventory used to drive the 240 ACTMs, and the spatial resolution of the modeled N r deposition by ACTMs is coarse.

241
Using satellite monitoring data to estimate surface N r concentration and deposition is 242 still in its infancy, especially for reduced N r .

243
Some scholars tried to use satellite NO 2 and NH 3 column to estimate the surface N r 244 concentration and dry N r deposition. However, there are relatively few studies on and NH 3 column, and the vertical profiles by an ACTM; (b) shows dry and wet N r deposition 266 including the major N r species (gaseous NO 2 , HNO 3 , NH 3 , particulate NO 3 and NH 4 + , as well as 267 wet NO 3 and NH 4 + in precipitation); (c) illustrates atmospheric vertical structures including the 268 troposphere (satellite observation), atmospheric boundary layer (ABL), interfacial sub-layer; (d) 269 and (e) represent procedures of calculating the dry and wet N r deposition.

279
Another approach tries to fit general vertical profiles of NO 2 and NH 3 (Zhang et al.,280 2017; Liu et al., 2017b;Liu et al., 2017c), and then estimate the ratio of N r 281 concentration at any height to total N r columns, and finally multiply the ratio by 282 satellite NO 2 and NH 3 columns. This approach has an advantage compared with the 283 previous one for that NO 2 and NH 3 concentration at all altitude included in ACTM 284 simulations can be estimated.

285
Taking the estimation of surface NO 2 concentration using the latter approach as an 286 example, the methods and steps are introduced in the following.

287
Step 1: Calculate the monthly mean NO 2 concentrations at all layers simulated by an 288 ACTM.

289
Step 2: Construct the vertical profile function of NO 2 . Multiple Gaussian functions are 290 used to fit the vertical distribution of NO 2 based on the monthly NO 2 concentrations at 291 all layers calculated in Step 1, in which the independent variable is the height 292 (altitude), and the dependent variable is NO 2 concentration at a certain height.
(2) 307 Step 3: Calculate the ratio of NO 2 concentration at the height of h G to total columns satellite-derived N r concentration at the height of h G can be calculated as: Step 4: Convert the instantaneous satellite-derived surface NO 2 concentration (S G_NO2 ) 312 to daily average (S G_NO2 * ) using the ratio of average surface NO 2 concentration 313 (G ACTM 1−24 ) to that at satellite overpass time (G ACTM overpass ) by an ACTM: The method for estimating the surface NH 3 concentration (S G_NH3 * ) is similar to that 316 for estimating the surface NO 2 concentration.
is the estimated ratio of between NO 2 and NO 3 -, 327 NO 2 and HNO 3 , NH 3 and NH 4 + . The resistance of dry N r deposition mainly comes from three aspects: aerodynamic 330 resistance (R a ), quasi laminar sub-layer resistance (R b ) and canopy resistance (R c ).

331
The V d can be expressed as 333 V g is gravitational settling velocity. For gases, the V g is negligible (V g =0).

334
Dry NO 2 , NO 3 -, HNO 3 , and NH 4 + deposition can be calculated by: Unlike above species, NH 3 is bi-directional, presenting both upward and downward 337 fluxes. There is a so-called "canopy compensation point" (C o ) controlling dry NH 3 338 deposition. Dry NH 3 deposition can be calculated by: The calculation of C o is very complex including the leaf stomatal and soil emission as zero Kharol et al., 2018) or set fixed values in each land use 344 type based on ground-based measurements (Jia et al., 2016).  The scavenging process of wet N r deposition usually starts from the height of rainfall 362 rather than the top of the troposphere, so it is more reasonable to use NO 2 and NH 3 363 column below the height of rainfall to build the wet N r deposition model. The NO 2

364
and NH 3 column within ABL is used to build the wet deposition model since 365 precipitation height is close to the height of the ABL (generally less than 2-3 km). Geddes et al. (Geddes et al., 2016) followed previous studies, and used NO 2 column 401 from the GOME, SCIAMACHY, and GOME-2 to estimate surface NO 2 concentration. ground-based observation, it is obvious that their surface NO 2 estimates were higher 404 than Nowlan's estimates (Nowlan et al., 2014) based on OMI (Fig. 2). This may be 405 because the OMI-derived NO 2 column is much lower than that derived by GOME, 406 SCIAMACHY, and GOME-2, especially over polluted regions. For example, in China, 407 the OMI NO 2 column is about 30% lower than that of SCIAMACHY and GOME-2 408 consistently (Fig. 3).  In this study, we used the framework in Sect. 3 to estimate the OMI-derived surface 437 NO 2 concentration globally. To validate the OMI-derived surface NO 2 concentrations, 438 ground-measured surface NO 2 concentration in China, the US and Europe in 2014 439 was collected (Fig. 4). The total number of NO 2 observations in China, the US and 440 https://doi.org/10.5194/acp-2020-91 Preprint. Discussion started: 24 February 2020 c Author(s) 2020. CC BY 4.0 License.
Europe are 43, 373 and 88 respectively. The OMI-derived annual average for all sites 441 was 3.74 µg N m -3 , which was close to the measured average (3.06 µg N m -3 ). The R 2 442 between OMI-derived surface NO 2 concentrations and ground-based NO 2 443 measurements was 0.75 and the RMSE was 1.23 µg N m -3 (Fig. 5), which is better and ground-measured surface NO 2 concentrations (b). The ground-based monitoring sites are 458 shown in Fig. 4 high correlation was found between surface NO 2 and NO 3 concentration at monthly 466 or annual timescales (Fig. 6) (Liu et al., 2017c annual and monthly scales, which were adopted from Liu et al. (Liu et al., 2017c).  ACTM) (Fig. 9), and found a good agreement with ground-based surface NH 3 525 concentration. The correlation between the measured and satellite-derived annual 526 mean surface NH 3 concentrations over all sites was 0.87 as shown in Fig. 10, while 527 the average satellite-derived and ground-measured surface NH 3 concentration was  and comparison between yearly modeling (by an ACTM as GEOS-Chem) and measured surface 539 NH 3 concentrations (b) (Liu et al., 2019). The ground-based monitoring sites are shown in Fig. 4.

541
The proposed methods (Liu et al., 2019) can also estimate NH 3 concentration at any 542 https://doi.org/10.5194/acp-2020-91 Preprint. Discussion started: 24 February 2020 c Author(s) 2020. CC BY 4.0 License. height using the constructed vertical profile function of NH 3 . The Gaussian function 543 can well emulate the vertical distribution of NH 3 from an ACTM outputs with 99% of 544 the grids having R 2 values higher than 0.90 (Fig. 11). This means, for regional and 545 global estimation, the vertical distribution of NH 3 concentration has a general pattern, 546 which can be mostly emulated by the Gaussian function. Once a global NH 3 vertical 547 profile was simulated, it can be easily used to estimate satellite-derived NH 3 548 concentration at any height. We can also estimate dry NH 3 deposition using the 549 IASI-derived surface NH 3 concentration combining the modeled V d . To date, there are 550 still no studies developing satellite-based methods to estimate the wet reduced N r 551 deposition on a regional scale. profiles. This is an example of Gaussian fitting using 47 layers' NH 3 and NO 2 concentration from 555 an ACTM (GEOS-Chem). 556 557 assumptions that emission inventories are compiled based on, particularly the lack of 568 reliable data over developing countries (Crippa et al., 2018). With such advantages, 569 researchers developed the satellite-based methods to estimate surface N r concentration, 570 deposition and even emissions. Satellite-based methods have advantages in 571 monitoring the recent trends of N r deposition. Geddes et al. (Geddes and Martin, 2017) 572 used NO 2 column from the GOME, SCIAMACHY, and GOME-2 to estimate 573 satellite-derived NO x emissions, and then used the calibrated NO x emission inventory 574 to drive an ACTM to simulate the long-term oxidized N r deposition globally. They 575 found oxidized N r deposition from 1996 to 2014 decreased by 60% in Eastern US, 576 doubled in East China, and declined by 20% in Western Europe (Fig. 12). We use the 577 datasets by Geddes et al. (Geddes and Martin, 2017) to calculate the trends of total 578 oxidized N r deposition during 1996-2014. It is obvious that two completely opposite 579 trends exist: (1) in East China with a steep increase of higher than 0.5 kg N ha -1 y -1 580 and (2) East US with a steep decrease of lower than -0.5 kg N ha -1 y -1 . Although it is 581 not a direct way to use satellite N r observation to estimate N r deposition, the method 582 of estimating trends of N r deposition by Geddes et al. (Geddes and Martin, 2017) can 583 be considered effective since it took account of the changes of both NO x emission and 584 climate by an ACTM. constrained with GOME, SCIAMACHY, and GOME-2 NO 2 retrievals during 1996-2014 (Geddes 588 and Martin, 2017). We gained the generated datasets 589 https://doi.org/10.5194/acp-2020-91 Preprint. Discussion started: 24 February 2020 c Author(s) 2020. CC BY 4.0 License.

Trends of Surface N r Concentration and Deposition by Satellite-based
(http://fizz.phys.dal.ca/~atmos/martin/?page_id=1520) by Geddes et al. (Geddes and Martin, 590 2017), and calculated the trends using the linear methods. First, the reduced N r deposition plays an important contribution to total N r deposition.

640
NH 3 exhibits bi-directional air-surface exchanges. The NH 3 compensation point 641 (Farquhar et al., 1980) is also an important and highly variable factor controlling dry 642 NH 3 deposition (Schrader et al., 2016;Zhang et al., 2010). However, the current 643 existing satellite-based methods did not consider this bi-directional air-surface 644 exchange. It is important to better parameterize the NH 3 compensation point, and 645 assess the effects of bi-directional air-surface exchanges on estimating the dry NH 3 646 deposition.

647
Second, the existing satellite-based methods to estimate N r deposition used the ratio 648 of the surface N r concentration to the N r column by an ACTM to convert satellite N r 649 column to surface N r concentration. However, the calculated ratio (by an ACTM) and 650 the satellite N r column have different spatial resolutions, and previous studies usually 651 applied the modeled ratio directly or interpolate the ratio into the resolution of 652 satellite N r column. This method assumes the relationship at coarse resolution by an 653 ACTM can also be effective in fine resolution as satellite indicated. When regional 654 studies are conducted, regional ACTMs coupled with another meteorological model 655 (e.g. WRF-Chem, WRF-CMAQ) (Grell et al., 2005;Wong et al., 2012) can be 656 configured to match the spatial resolution of satellite observation, but this is not as  technology, more and more N r species can be detected, such as HNO 3 . However, at 669 present, satellite HNO 3 products are not mature, and the spatial resolution is low.

670
Direct, high-resolution and reliable satellite monitoring of more N r species is critical 671 to further developing the use of using atmospheric remote sensing to estimate N r 672 deposition at global and regional scales. concentration and reduced N r deposition by satellite NH 3 data is just beginning, and 688 some scholars have carried out estimating surface NH 3 concentration and dry NH 3 689 deposition on different spatial and temporal scales, but the research degree is still 690 relatively low. We present a framework of using satellite NO 2 and NH 3 column to 691 estimate N r deposition based on recent advances. The proposed framework of using 692 Gaussian function to model vertical NO 2 and NH 3 profiles can be used to convert the 693 satellite NO 2 and NH 3 column to surface NO 2 and NH 3 concentration at any height 694 simply and quickly. The proposed framework of using satellite NO 2 and NH 3 column 695 to estimate wet N r deposition is a statistical way, and further studies should be done 696 from a mechanism perspective. Finally, we summarized current challenges of using 697 satellite NO 2 and NH 3 column to estimate surface N r concentration and deposition 698 including a lack of considering NH 3 bidirectional air-surface exchanges and the 699 problem of different spatial scales between an ACTM and satellite observation.  concentration data used to calculate the longterm trends in Fig. 13 and Fig. 14