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Identifying Ammonia Hotspots in China Using a National Observation Network

  • Yuepeng Pan*
    Yuepeng Pan
    State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    *Phone: +86 01062022285. Fax: +86 01062362389. E-mail: [email protected]
    More by Yuepeng Pan
  • Shili Tian
    Shili Tian
    State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    More by Shili Tian
  • Yuanhong Zhao
    Yuanhong Zhao
    Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
  • Lin Zhang
    Lin Zhang
    Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
    More by Lin Zhang
  • Xiaying Zhu
    Xiaying Zhu
    National Climate Center, China Meteorological Administration, Beijing 100081, China
    More by Xiaying Zhu
  • Jian Gao
    Jian Gao
    State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    More by Jian Gao
  • Wei Huang
    Wei Huang
    State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    More by Wei Huang
  • Yanbo Zhou
    Yanbo Zhou
    State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    More by Yanbo Zhou
  • Yu Song
    Yu Song
    Department of Environmental Science, Peking University, Beijing 100871, China
    More by Yu Song
  • Qiang Zhang
    Qiang Zhang
    Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
    More by Qiang Zhang
  • , and 
  • Yuesi Wang
    Yuesi Wang
    State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    More by Yuesi Wang
Cite this: Environ. Sci. Technol. 2018, 52, 7, 3926–3934
Publication Date (Web):March 2, 2018
https://doi.org/10.1021/acs.est.7b05235
Copyright © 2018 American Chemical Society
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Supporting Info (1)»

Abstract

The limited availability of ammonia (NH3) measurements is currently a barrier to understanding the vital role of NH3 in secondary aerosol formation during haze pollution events and prevents a full assessment of the atmospheric deposition of reactive nitrogen. The observational gaps motivated us to design this study to investigate the spatial distributions and seasonal variations in atmospheric NH3 on a national scale in China. On the basis of a 1-year observational campaign at 53 sites with uniform protocols, we confirm that abundant concentrations of NH3 [1 to 23.9 μg m–3] were identified in typical agricultural regions, especially over the North China Plain (NCP). The spatial pattern of the NH3 surface concentration was generally similar to those of the satellite column concentrations as well as a bottom-up agriculture NH3 emission inventory. However, the observed NH3 concentrations at urban and desert sites were comparable with those from agricultural sites and 2–3 times those of mountainous/forest/grassland/waterbody sites. We also found that NH3 deposition fluxes at urban sites account for only half of the emissions in the NCP, suggesting the transport of urban NH3 emissions to downwind areas. This finding provides policy makers with insights into the potential mitigation of nonagricultural NH3 sources in developed regions.

1. Introduction

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The intensive human activities of past decades have significantly affected the global nitrogen cycle by fixing N2, both deliberately for fertilizer production and inadvertently during fossil fuel combustion.(1) Rapid increases in reactive nitrogen emissions to the atmosphere have resulted in serious reactive nitrogen pollution in the air and excessive nitrogen deposition in natural ecosystems worldwide.(2) To reduce these adverse impacts, previous efforts have been made to reduce oxidized nitrogen, such as NOx emissions, whereas a reduction in reduced nitrogen (NHx), especially in ammonia (NH3) emissions, has not been fully implemented.(3,4) Between 2002 and 2013, NH3 levels over agricultural regions experienced significant increasing trends across the U.S. (2.6% year–1), the European Union (1.8% year–1), and China (2.3% year–1), as observed from satellite.(5) It is demonstrated that the deposition of reactive nitrogen in the U.S. has recently shifted from nitrate-dominated to ammonium-dominated conditions,(6) while NHx plays a key role in atmospheric nitrogen deposition in China, contributing from 71% to 88% of the total depositions in hotspot regions, such as the North China Plain (NCP).(7)
In addition, there is increasing evidence indicating the critical role of NH3 in the formation of secondary aerosols.(3,8) Extensive observations reveal that ammonium and related sulfate and nitrate contribute 10% and 35% of the particulate mass during haze events, respectively.(9) The profound role of NH3 in haze pollution has also been highlighted by recent studies arguing its capability to neutralize aerosol pH, which can strongly enhance the formation of sulfate through the heterogeneous oxidation of SO2 by NO2.(10) All evidence leads to increasing concerns that future progress toward reducing the nitrogen-related impacts on aerosol pollution and nitrogen deposition will be increasingly difficult without a well-resolved spatiotemporal picture of NH3.
Compared with the increasing number of rich data sets of satellite observations of atmospheric NH3 concentration,(5,11,12) surface network data sets covering large geographical areas are still lacking,(13,14) especially in China.(15,16) To fill the observational data gaps, in this study, a year-round campaign was launched to measure monthly NH3 by using uniform protocols with a diffusive technique and other supporting data across China. The objectives of the present study are to (1) identify the hotspots of NH3 in China, (2) explore the variability of atmospheric NH3, and (3) present the implications for mitigating NH3 on a national scale. To our knowledge, this study represents the first national observations of NH3 in China, especially in background regions, setting a baseline against which concentration changes resulting from future emission control strategies can be assessed. The data collected here are unique and will advance our understanding of atmospheric chemistry and related processes. The results will also be valuable for scientists and policy makers to estimate excess nitrogen inputs into ecosystems and validate atmospheric chemistry and transport models, including seasonal trends and regional variability.

2. Materials and Methods

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2.1. Ammonia Sampling Networks

Accurately measuring NH3 concentrations in the air is not an easy task because of the interference of particle-borne ammonium.(17) However, this problem can be solved using the well-known fact that when ambient air passes through a tube, gas molecules diffuse much more quickly than particles onto the tube wall.(18) The main disadvantage of this manual sampling method (hereafter referred to as the diffusive sampling technique) is its low temporal resolution when high-frequency measurements (e.g., hourly) are needed. However, such a simple and cost-effective technique can increase the spatial resolution of the measurement and aid in screening studies to evaluate monitoring site locations(14) or in long-term measurements for trend analyses.(13)
For large-scale surveys of NH3 variability across China, starting in September 2015, we implemented a passive NH3 monitoring network based on the diffusive technique with monthly integrated measurements at 53 sites. The current Ammonia Monitoring Network in China (AMoN-China) was established mainly based on the Chinese Ecosystem Research Network (CERN, http://www.cern.ac.cn/0index/index.asp) and the Regional Atmospheric Deposition Observation Network on the NCP (READ-NCP).(7) AMoN-China includes 13 mountain and forest, 5 water body, 7 grassland, 4 desert, 11 farmland, and 13 urban/suburban/industrial sites (Figure 1). All of the sites are selected to be far away (>1 km) from a known source of NH3 (e.g., feedlot areas) considering that the NH3 concentrations decrease significantly away from the source (several hundred meters).(19) More details on the site selection and siting protocols can be found in Supporting Information (SI, text and Table S1).

Figure 1

Figure 1. Spatial distribution of ammonia concentrations observed from the surface network (site) versus satellite column data (grid) in China. The detailed surface observation site information can be found in Table 1 and SI. Satellite NH3 total column distributions were derived from the infrared atmospheric sounding interferometer (IASI) aboard MetOp-A for the year 2015. We collected the observations from morning overpass time (9:30 LTC) and filtered the columns with relative error above 100% following procedures presented in Van Damme et al.(12) The filtered IASI satellite columns were then mapped to a 0.25° × 0.25° horizontal resolution by averaging available observations within each grid cell. The provincial boundary layer with a scale of 1:4,000,000 was obtained from the National Geomatics Center of China (http://ngcc.sbsm.gov.cn/). Maps were generated based upon a geospatial analysis using ESRI ArcGIS software (version 10.1, http://www.esri.com/software/arcgis/arcgis-for-desktop).

Sites were assigned to regions to assess whether the seasonal variations and spatial distributions of NH3 concentrations show different patterns in different broad areas of China (Figure 2). The regions are defined as follows: the NCP (11 sites), northeast China (NE, 9 sites); northwest China (NW, 5 sites), southeast China (SE, 13 sites), southwest China (SW, 9 sites), and Central China (Central, 6 sites). The regions were chosen based on the spatially different geographical, climate, and available characteristics of the sites.

Figure 2

Figure 2. Seasonal variations of ammonia concentrations observed from the surface network (53 sites) in China.

2.2. Chemical Analysis and Validation of Ammonia Samplers

The year-round sampling campaign was carried out from September 2015 to August 2016. In total, 636 samples of NH3 were collected using diffusive samplers (Analysts, CNR-Institute of Atmospheric Pollution, Roma, Italy). The passive sampler is made of polyethylene and employs a phosphorus-acid-impregnated glass microfiber filter as an adsorption layer. The sampler is a robust and reliable tool for measuring atmospheric NH3; the development, theory, laboratory validation, and field application of the sampler have been fully described elsewhere.(20)
During sample collection, the passive samplers were exposed at a height of 2 m with their open ends oriented downward to exclude the dry deposition of particles. In addition, the sampler was protected from rain and direct sunlight by an inverted stainless-steel shield. After exposure, the passive samplers were returned to Beijing for analysis at the State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences. In the laboratory, 5 mL of deionized water was used to extract the exposed samples, and the ammonium ion concentration in the extraction was determined via ion chromatography with a cation separator and conductivity detector (Dionex Corp., Sunnyvale, CA, USA).
The ambient NH3 concentrations (cNH3, μg m–3) were calculated based on the amount of ammonium (mNH4+, μg) collected on the exposed filter and the sample collection time (t, hour), which can be expressed using the following equation:where 9.06 × 102 is the conversion factor from the manufacturer’s description, which is a function of the parameters of the passive sampler. This formula assumes that the average temperature (T) during sampling is 20 °C. In the case that temperature is different, a correction coefficient of is applied to cNH3. Such a temperature effect is negligible, with the corrected NH3 concentrations being less than 5% at each 5 °C interval. Most of the sampling sites belong to the CERN, where the temperature was measured at each site using an automatic meteorological observation instrument (Milos520, Vaisala, Finland). In the case that the temperature was not measured at the site, the nearest meteorological observation station available on the China Meteorological Data Sharing Services System Web site (http://cdc.cma.gov.cn/) was used in this study.
Before and during the study period, comparisons with automatic reference methods were performed during two campaigns. During 2013, the Analysts passive sampler (monthly samples) were compared to the continuously active analyzers of MARGA (a model ADI 2080 online analyzer for the Monitoring of Aerosols and Gases, Applikon Analytical B.V. Corp., The Netherlands, aggregated to monthly data points), showing a linear regression slope of 1.10 ± 0.14 and R2 of 0.94 (Figure 3a). This strong linear relationship indicates that the Analyst passive sampler is reliable for such a study, assuming that the NH3 concentration values measured by the wet chemistry instruments are more accurate.(17) During this study, we also compared the Analysts passive samplers to DELTA (Denuder for Long-Term Atmospheric Sampling, Centre for Ecology and Hydrology, UK) at a monthly resolution. This comparison shows a linear regression slope close to unity (1.04 ± 0.17) and an intercept of 2.06 ± 2.23 μg m–3 (Figure 3b); the bias appears to be systematic and thus does not impact the patterns of the spatial distributions or seasonal variations.

Figure 3

Figure 3. Comparisons of passive diffusion sampler to the continuously active analyzers of MARGA and DELTA. Ammonia concentrations are aggregated to monthly data points.

2.3. Dry Deposition Velocity Simulation

The inferential technique,(7) which combines the measured NH3 concentration and a modeled dry deposition velocity (Vd) from the Goddard Earth Observing System-Chem (GEOS-Chem; http://geos-chem.org) chemical transport model, was used to estimate the dry deposition fluxes of NH3. The GEOS-Chem simulation of nitrogen dry deposition has been described by Zhao et al.(21) The model is driven by the latest version of GEOS-FP assimilated meteorological fields from the NASA Global Modeling and Assimilation Office (GMAO), which has been applied to analyze particle pollution over the NCP.(22) Our simulation used the native GEOC-FP resolution of 0.25° latitude ×0.3125° longitude over East Asia (70°E–140°E, 15°N–55°N) and a coarse resolution of 2° latitude ×2.5° longitude over other places of the world.
Follow the standard big-leaf resistance-in-series model,(23)Vd in GEOS-Chem was calculated by considering the aerodynamic resistance, the boundary layer resistance, and the surface resistance. We did not consider air–surface bidirectional exchange of NH3,(24) and we treated the NH3 fluxes as uncoupled emission and deposition processes. The model was run from 2014 to 2016, and we applied the monthly Vd at a reference height of 2 m to the observed NH3 concentrations to obtain monthly NH3 dry deposition fluxes. The NH3 monthly dry deposition fluxes calculated using the monthly mean concentration and Vd are approximately 7% higher than the hourly integrated values, reflecting some small covariance between the NH3 concentrations and Vd in the model.

3. Results and Discussion

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3.1. Spatial Distribution of Ammonia in China

Large spatial differences in NH3 concentrations were found at the 53 sites in the sampling network, with annual mean NH3 concentrations during the 1-year period ranging from 1 to 23.9 μg m–3, as illustrated in Table 1 and Figure 1. The upper range is higher than the concentrations observed in China around 2012 (0.3–13.1 μg m–3)(16) and Asia around 2000 (<0.7–13.9 μg m–3).(14) The overall mean NH3 concentrations in this study reached 7.0 ± 5.4 μg m–3, which is much higher than the values observed in the U.S. AMoN network using a similar diffusive sampling technique,(13) although the AMoN sites are mainly located outside the intensive source areas of the U.S. At the Colorado near-agricultural sites, the NH3 concentrations reach 42.7 μg m–3.(25)
Table 1. Seasonal and Annual Concentrations of Ammonia (μg m–3) Observed at the 53 Sites in China during This Study Perioda
codelocationlatitudelongitudeelvation (m)land use typesregionSONDJFMAMJJAmean
FQAFengqiu35.0114.667farmlandNCP19.214.312.821.116.8
LCALuancheng37.9114.757farmlandNCP21.917.217.520.719.3
YCAYucheng37.0116.623farmlandNCP21.312.810.045.222.3
TSMTainshan36.3117.11506mountain and shrubberyNCP3.32.85.63.83.9
XLMXinglong40.4117.6872mountain and shrubberyNCP3.60.96.15.13.9
YFSYangfang40.2116.173suburbanNCP6.04.16.011.97.0
CZSCangzhou38.3116.910suburbanNCP22.022.225.626.023.9
TJUTianjin39.1117.26urbanNCP12.37.211.014.511.3
BJUBeijing40.0116.457urbanNCP16.67.214.916.313.7
BDIBaoding38.9115.521urbanNCP12.710.512.425.715.3
TGITanggu39.0117.70urban and coastalNCP8.48.011.912.710.2
CLDCele37.080.71319desertNW7.33.15.19.16.1
FKDFukang43.387.9475desert and suburbanNW8.314.717.217.414.4
AKAAkesu40.680.81031farmlandNW3.83.210.917.68.9
HCAHuocheng44.080.7590farmlandNW9.011.226.613.415.1
ALTAltai Mountains47.686.0847mountain and shrubberyNW2.4/9.36.25.5
SPTShapotou37.5105.01258desertcentral4.22.35.19.05.1
ASAAnshai36.9109.41207farmlandcentral1.63.85.46.74.3
LZALinze39.4100.11385farmlandcentral3.52.33.710.45.0
WNAWeinan34.7109.3411farmlandcentral8.37.713.120.312.4
WLGWaliguan36.3100.93772grasslandcentral2.02.02.22.32.1
HBGHaibei37.6101.33198grasslandcentral2.12.03.27.23.6
HTFHuitong26.9109.6524forestSE2.11.90.81.81.7
QYFQianyanzhou26.4115.074mountain and forestSE2.51.92.43.22.5
DHMDinghushan23.2112.644mountain and forestSE3.82.63.21.72.8
HJKHuanjiang24.7108.3293mountain and karstSE2.51.03.610.14.3
XMUXiamen24.7118.12urbanSE6.04.05.75.05.2
GZUGuangzhou23.1113.314urbanSE4.94.46.96.95.8
THLTaihu31.6120.37urbanSE3.45.76.010.36.3
MMUMaoming21.6110.716urbanSE10.15.98.015.19.8
NJUNanjing32.1118.415urbanSE11.67.59.514.610.8
YXIYongxing island16.8112.310waterbody and islandSE3.21.92.03.72.7
PYLPoyang lake29.4116.124waterbody and lakeSE1.62.52.04.42.6
DTLDongting lake29.5112.828waterbody and lakeSE3.74.16.09.05.7
DHLDonghu lake30.5114.420waterbody and lakeSE3.83.87.310.46.3
NMDNaiman42.9120.7362desertNE5.62.93.49.45.3
SYAShenyang41.5123.438farmlandNE5.12.36.712.66.7
MHFMohe52.9122.8467forestNE1.31.10.71.01.0
ERGErgun50.2119.4525grasslandNE1.50.38.91.33.0
INGInner Mongolia43.6116.71187grasslandNE2.22.03.27.23.6
DAGDaan45.6123.81299grasslandNE2.71.65.19.94.8
CCUChangchun44.0125.4195grassland and suburbanNE2.90.73.46.43.4
CBMChangbaishan42.4128.1736mountain and forestNE0.70.78.323.48.3
SJWSanjiang47.6133.555waterbody and wetlandNE3.21.23.24.93.1
YTAYanting31.3105.5437farmlandSW3.61.62.89.64.4
LSALhasa29.691.03640farmlandSW6.02.94.46.14.8
BNFXishuangbanna22.0100.8648forestSW4.95.56.44.25.3
ALDAli33.479.74256grasslandSW1.30.90.76.31.7
ALMAilaoshan24.3101.02483mountain and forestSW1.11.10.62.81.4
GGMGonggashan29.6102.02977mountain and forestSW0.70.90.55.01.8
MXFMaoxian31.7103.91826mountain and shrubberySW2.31.43.92.92.6
GZAGuizhou26.3105.91468urbanSW3.42.34.75.33.9
CDUChengdu30.6104.0490urbanSW7.95.59.610.58.4
a

SON = Sept–Oct–Nov, DJF = Dec–Jan–Feb, MAM = Mar–Apr–May, JJA = Jun–Jul–Aug.

The sites were assigned to six regions to assess the regional variations among them. The highest regional averaged ambient NH3 concentrations were found over the NCP (13.4 μg m–3), followed by those in the NW (10.0 μg m–3), Central (5.4 μg m–3), SE (5.1 μg m–3), NE (4.4 μg m–3), and SW (3.8 μg m–3). The spatial distributions of the surface NH3 concentrations were consistent with the top-down satellite NH3 columns,(12) as shown in Figure 1, and similar to the bottom-up NH3 emissions inventory from agriculture sources in China, as included in Figure 4. NCP is then confirmed to be the largest region with high surface concentrations and highest emissions. This region accounts for 43% of the NH3 emitted from fertilization in China.(26)

Figure 4

Figure 4. Spatial distribution of the site-based dry deposition fluxes versus the gridded agriculture emission inventory of ammonia in China. The legend for gridded ammonia inventory was also shown in units of kg N ha–1 year–1 (numbers in the left corner), in addition to units of t year–1 per 0.25° by 0.25°. The NH3 inventory used in this study was obtained from the Multi-Resolution Emission Inventory of China (MEIC, http://meicmodel.org),(36) originally developed and described by Huang et al.(26) The MEIC inventory is provided with monthly gridded emissions of NH3 at 0.25° × 0.25° for five sectors, that is, power generation, industry, residential, transportation, and agriculture. The agriculture sector is a dominant source of NH3 emissions at the national scale, mainly contributed by fertilizer applications and manure managements. The year of 2012 was chosen to conduct the spatial comparison because emissions after 2012 are currently unavailable. The provincial boundary layer with a scale of 1:4 000 000 was obtained from the National Geomatics Center of China (http://ngcc.sbsm.gov.cn/). Maps were generated based upon a geospatial analysis using ESRI ArcGIS software (version 10.1, http://www.esri.com/software/arcgis/arcgis-for-desktop).

In addition, several smaller hotspots were observed in China, for example, in Dzungaria and surrounding the Tarim basin (NW), Chengdu Plain (SW), and Guanzhong Plain (Central). These hotspots coincided with intensive agricultural activities, suggesting the major contribution of volatilized fertilizer and livestock waste to atmospheric NH3.(26) In vast regions surrounding these hotspots, for example, the Tibetan Plateau, South China, and Inner Mongolia, NH3 levels were low and can be treated as the background values. In addition to the limited NH3 sources in these background regions, cold weather, or acidic soil is unfavorable for NH3 emissions. Heavy rainfall may also contribute to the scavenging of atmospheric NH3,(21) resulting in the lower concentrations observed in South China.

3.2. Differences among Land Use Types

From the aspect of land use types, the highest values were observed at urban/suburban/industrial sites (10.8 μg m–3), followed by those at farmland (10.2 μg m–3), desert (7.8 μg m–3), mountain and forest (3.6 μg m–3), water body (3.6 μg m–3), and grassland (3.4 μg m–3) sites. Given the influences of volatilized fertilizer, the mean NH3 concentrations at the WNA, HCA, FQA, LCA, and YCA agricultural sites reached 12.4, 15.1, 16.8, 19.3, and 22.3 μg m–3, respectively (Table 1, where the abbreviations of the site names are defined, the same below). These values are much higher than the results from the other farmland sites, that is, AKA, SYA, LZA, LSA, YTA, and ASA, observed in this study. The difference is likely attributed to the different fertilizer inputs, climate zones, and soil pH values in these regions.
As shown in Table 1, the results also demonstrated relatively high NH3 values at urban sites in the NCP, for example, TGI (10.2 μg m–3), TJU (11.3 μg m–3), BJU (13.7 μg m–3), BDI (15.3 μg m–3), and CZS (23.9 μg m–3). Although agricultural activities are intensive in this region, nonagricultural emissions are an important contributor to atmospheric NH3 in the region, as evidenced by the isotopic signatures.(27)
In addition, relatively high concentrations of NH3 were also observed at urban sites in South China, for example, at NJU (10.8 μg m–3), MMU (9.8 μg m–3), CDU (8.4 μg m–3), THL (6.3 μg m–3), and GZU (5.8 μg m–3). These values were higher than or comparable to those of nearby farmlands. For example, the average NH3 concentration measured at the urban site CDU was twice that of the agricultural site YTA (4.4 μg m–3). Such high values observed in urban areas are one of the distinct features in this study. Therefore, nonagricultural sources are suggested to be important contributors to atmospheric NH3 in developed regions across China. An improved global NH3 emission inventory for combustion and industrial sources provided distinct evidence that the emissions density of NH3 in urban areas is an order of magnitude higher than in rural areas.(8)
Another important finding is the higher NH3 concentrations observed at the desert sites of SPT, NMD, CLD, and FKD, which have values of 5.1, 5.3, 6.1, and 14.4 μg m–3, respectively. These values are higher than those observed in background regions, including mountain and forest, water body and grassland sites, averaging 3.5 μg m–3. This is the first observational evidence showing high NH3 values over NW dry lands, in addition to over farmlands. This finding indicates an important regional source of NH3 from dried saline soils nearby;(28) considering that a certain amount of non-sea-salt crustal sulfate has been observed from deserts and Gobi region in the north China.(29) The unexpected high values at the desert site of FKD (60 km to the NE of the Urumqi city) may be explained by the transport of nearby industrial and/or urban sources.

3.3. Seasonal Variations in Ammonia Concentration in China

When the data were aggregated at seasonal levels, the seasonal maximum NH3 concentrations were observed in the summer, whereas the minimum values occurred in the winter at most sites (Figure 2). Note that pulse peaks were also observed during August at GGM, in May at ERG, in Dec at ASA and in July at HJK. At the mountainous/forest/grassland sites, the NH3 concentrations exhibited weaker seasonal variations during the observational periods, with nearly constant values of less than 3.5 μg m–3, reflecting the remoteness of the monitoring site and its ability to serve as the background value in China.
In contrast, the seasonal variations in NH3 at agricultural sites were evident, with low values in the winter, elevated values in the late spring, peaks in the summer, and decreased values in the autumn. The relatively high values in the warmer seasons correspond with peak emissions from agricultural activities and high temperatures. A similar seasonal pattern can also be found at urban sites, for example, BDI and NJU, although the agricultural activities in urban regions were less evident.
Although the volatilization of NH3 in agricultural regions was sufficient to justify the high NH3 observed in developed regions during the warm season, the contribution of nonagricultural sources of NH3 can not be neglected in urban areas.(30) In a case study, the NH3 emissions from vehicles in urban Beijing may have contributed to the observed summer maximum.(31) However, such sources do not always have obvious seasonal changes. The recycling of predeposited NHx offers an alternative explanation for these seasonal changes, which was mentioned in a recent study.(32) This speculation was partially supported by a good correlation of NH3 concentrations and ambient temperature at urban sites (e.g., BJU; Figure S1). Note that changes in emissions do not necessarily relate to changes in concentrations, and vice versa. Low NH3 concentrations in winter may also be attributable to gas-to-particle conversion under cold weather conditions. Thus, nonagricultural emissions in urban areas may still be quite high in winter, for example. To fill the gap, concurrent measurements of NH3 and NH4+ concentrations and fluxes covering different seasons are needed.

3.4. Ammonia Dry Deposition versus Emissions in China

We estimated the dry deposition flux of NH3 to assess the bulk input to ecosystems by combining the monthly observed concentrations with modeled Vd. The mean monthly Vd values of NH3 modeled at most sites during the study period ranged from 0.20 to 0.55 cm s–1, except for one coastal site (MMU, 1.02–1.42 cm s–1) and an island site (YXI, 0.74–1.73 cm s–1). These ranges agree well with the previous estimations in the target region.(7,16) The seasonal variations in Vd (data not shown) were weaker than the seasonal variations in the concentrations, implying that the ambient concentration plays a more important role in determining the dry deposition flux of NH3. As a consequence, the spatial pattern of NH3 dry deposition (Figure 4) was similar to that of the concentrations in China (Figure 1), as mentioned in section 3.1.
The annual dry deposition of NH3 estimated in this study falls within the range of 0.8–30.3 kg N ha–1 year–1, with a national mean of 7.3 ± 6.1 kg N ha–1 year–1, which is slightly lower than the estimation (8.2 kg N ha–1 year–1) produced a few years ago.(16) Because of the relatively high ambient concentrations, the dry deposition of more than 10 kg N ha–1 year–1 of NH3 was mostly estimated at those sites located in agricultural areas (e.g., YCA, LCA, FQA, HCA, and WNA) and in or near developed regions (e.g., CZS, BDI, BJU, NJU, TJU, and FKD). Note that the highest deposition was estimated for MMU because of both the high local concentrations and Vd.
Figure 5 compares the dry deposition fluxes estimated at the sites with the gridded agriculture emissions, showing that the NW sites exhibited deposition fluxes that were a factor of 2 (or more) greater than their emissions. Because dry deposition is the major sink of NH3 in this region, the unexpected high deposition at the NW sites indicates missing sources in the current inventory. In contrast, the SE sites had higher emissions than deposition, highlighting the significant removal of NH3 via precipitation (wet deposition) in South China.(21) At the NCP sites, estimated dry deposition fluxes accounted for 25%–75% of the emissions of NH3. Considering the wet/dry deposition ratio,(7) the total NHx depositions at the YCA, LCA, YFS, and CZU sites would be much closer to those of the emissions, whereas the NHx deposition fluxes at the BDI, BJU, TJU, and FQA sites would be 50% of the emissions, suggesting the possible regional transport of NH3 to the surrounding regions.

Figure 5

Figure 5. Comparison of the site-based dry deposition fluxes versus the gridded agriculture emission inventory of ammonia in China (1° by 1°). The sites are colored by region. The units of emission data were converted to kg N ha–1 year–1 for comparison with that of ammonia deposition. The 1:1 line represents equal ammonia dry deposition and emissions.

Uncertainties in both the emissions and deposition fluxes may also contribute to the discrepancies. For example, emission uncertainty is associated with activity data and emission factors (EFs).(26) The activity data were obtained via statistical information and were subject to systemic errors rather than regional inconsistencies. However, the EFs that are parametrized by the ambient temperature, soil properties, fertilizer types, and other factors may vary regionally;(33) thus, these speculations should be validated with future work. Uncertainties also exist in dry deposition estimations. In particular, NH3 fluxes over vegetated land are bidirectional,(34) and the net direction of this flux is often uncertain. A so-called canopy compensation point was used in previous studies to determine the direction of the NH3 flux.(24) Because the principle of bidirectional NH3 exchange has been not employed in this study, the flux calculated here represents a rather nonconservative deposition estimate (upper boundary). In this study, NH3 deposition may be overestimated at vegetated sites with relatively high canopy compensation points (e.g., up to 5 μgN m–3) due to fertilized croplands(7) or vegetation.(35) We recommend future research to evaluate the effects of the stomatal compensation point on NH3 deposition in agricultural sites due to the counterbalance between deposition and emission.

Supporting Information

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The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.7b05235.

  • Figure S1 illustrates the ammonia concentration and temperature correlation. Table S1 summarizes the site information. The text details the site selection and siting protocols with accompanying references (PDF)

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  • Corresponding Author
  • Authors
    • Shili Tian - State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    • Yuanhong Zhao - Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
    • Lin Zhang - Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
    • Xiaying Zhu - National Climate Center, China Meteorological Administration, Beijing 100081, China
    • Jian Gao - State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    • Wei Huang - State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    • Yanbo Zhou - State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    • Yu Song - Department of Environmental Science, Peking University, Beijing 100871, China
    • Qiang Zhang - Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
    • Yuesi Wang - State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • Author Contributions

    Y.P. and Y.W. conceived and designed the project, Y.P., Y. Z., and S.T. conducted the field work, Y.Z. and L.Z. performed the dry deposition modeling experiments, J.G. performed the MARGA measurements, Y.S. and Q.Z. prepared the ammonia emission inventory, Y.P., X.Z., and W.H. analyzed the data and drew figures, and Y.P. wrote the paper with comments from the coauthors.

  • Notes

    The authors declare no competing financial interest.

Acknowledgments

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This work was supported by the National Key Research and Development Program of China (Grant 2017YFC0210100), the National Natural Science Foundation of China (Grant 41405144), and the State Key Special Project on “Agricultural emissions status and enhanced pollution control plan” (Grant DQGG0208). We are indebted to the staff who collected the samples at the sites (listed in Table 1) during the study period. We also thank three anonymous reviewers for insightful comments that helped to improve an earlier version of the manuscript.

References

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This article references 36 other publications.

  1. 1
    Vitousek, P.; Mooney, H.; Lubchenco, J.; Melillo, J. Human domination of Earth’s ecosystems. Science 1997, 277 (5325), 494499,  DOI: 10.1126/science.277.5325.494
  2. 2
    Galloway, J. N.; Townsend, A. R.; Erisman, J. W.; Bekunda, M.; Cai, Z.; Freney, J. R.; Martinelli, L. A.; Seitzinger, S. P.; Sutton, M. A. Transformation of the Nitrogen Cycle: Recent Trends, Questions, and Potential Solutions. Science 2008, 320 (5878), 889892,  DOI: 10.1126/science.1136674
  3. 3
    Fu, X.; Wang, S.; Xing, J.; Zhang, X.; Wang, T.; Hao, J. Increasing Ammonia Concentrations Reduce the Effectiveness of Particle Pollution Control Achieved via SO2 and NOX Emissions Reduction in East China. Environ. Sci. Technol. Lett. 2017, 4 (6), 221227,  DOI: 10.1021/acs.estlett.7b00143
  4. 4
    Liu, X.; Zhang, Y.; Han, W.; Tang, A.; Shen, J.; Cui, Z.; Vitousek, P.; Erisman, J. W.; Goulding, K.; Christie, P.; Fangmeier, A.; Zhang, F. Enhanced nitrogen deposition over China. Nature 2013, 494 (7438), 459462,  DOI: 10.1038/nature11917
  5. 5
    Warner, J. X.; Dickerson, R. R.; Wei, Z.; Strow, L. L.; Wang, Y.; Liang, Q. Increased atmospheric ammonia over the world’s major agricultural areas detected from space. Geophys. Res. Lett. 2017, 44 (6), 28752884,  DOI: 10.1002/2016GL072305
  6. 6
    Li, Y.; Schichtel, B. A.; Walker, J. T.; Schwede, D. B.; Chen, X.; Lehmann, C. M.; Puchalski, M. A.; Gay, D. A.; Collett, J., Jr Increasing importance of deposition of reduced nitrogen in the United States. Proc. Natl. Acad. Sci. U. S. A. 2016, 113 (21), 58745879,  DOI: 10.1073/pnas.1525736113
  7. 7
    Pan, Y.; Wang, Y.; Tang, G.; Wu, D. Wet and dry deposition of atmospheric nitrogen at ten sites in Northern China. Atmos. Chem. Phys. 2012, 12 (14), 65156535,  DOI: 10.5194/acp-12-6515-2012
  8. 8
    Meng, W.; Zhong, Q.; Yun, X.; Zhu, X.; Huang, T.; Shen, H.; Chen, Y.; Chen, H.; Zhou, F.; Liu, J.; Wang, X.; Zeng, E. Y.; Tao, S. Improvement of a Global High-Resolution Ammonia Emission Inventory for Combustion and Industrial Sources with New Data from the Residential and Transportation Sectors. Environ. Sci. Technol. 2017, 51 (5), 28212829,  DOI: 10.1021/acs.est.6b03694
  9. 9
    Tian, S.; Pan, Y.; Liu, Z.; Wen, T.; Wang, Y. Size-resolved aerosol chemical analysis of extreme haze pollution events during early 2013 in urban Beijing, China. J. Hazard. Mater. 2014, 279, 452460,  DOI: 10.1016/j.jhazmat.2014.07.023
  10. 10
    Wang, G.; Zhang, R.; Gomez, M. E.; Yang, L.; Levy Zamora, M.; Hu, M.; Lin, Y.; Peng, J.; Guo, S.; Meng, J.; Li, J.; Cheng, C.; Hu, T.; Ren, Y.; Wang, Y.; Gao, J.; Cao, J.; An, Z.; Zhou, W.; Li, G.; Wang, J.; Tian, P.; Marrero-Ortiz, W.; Secrest, J.; Du, Z.; Zheng, J.; Shang, D.; Zeng, L.; Shao, M.; Wang, W.; Huang, Y.; Wang, Y.; Zhu, Y.; Li, Y.; Hu, J.; Pan, B.; Cai, L.; Cheng, Y.; Ji, Y.; Zhang, F.; Rosenfeld, D.; Liss, P. S.; Duce, R. A.; Kolb, C. E.; Molina, M. J. Persistent sulfate formation from London Fog to Chinese haze. Proc. Natl. Acad. Sci. U. S. A. 2016, 113 (48), 1363013635,  DOI: 10.1073/pnas.1616540113
  11. 11
    Beer, R.; Shephard, M. W.; Kulawik, S. S.; Clough, S. A.; Eldering, A.; Bowman, K. W.; Sander, S. P.; Fisher, B. M.; Payne, V. H.; Luo, M.; Osterman, G. B.; Worden, J. R. First satellite observations of lower tropospheric ammonia and methanol. Geophys. Res. Lett. 2008, 35 (9), L09801  DOI: 10.1029/2008GL033642
  12. 12
    Van Damme, M.; Clarisse, L.; Heald, C. L.; Hurtmans, D.; Ngadi, Y.; Clerbaux, C.; Dolman, A. J.; Erisman, J. W.; Coheur, P. F. Global distributions, time series and error characterization of atmospheric ammonia (NH3) from IASI satellite observations. Atmos. Chem. Phys. Discuss. 2014, 14 (6), 29052922,  DOI: 10.5194/acpd-13-24301-2013
  13. 13
    Butler, T.; Vermeylen, F.; Lehmann, C. M.; Likens, G. E.; Puchalski, M. Increasing ammonia concentration trends in large regions of the USA derived from the NADP/AMoN network. Atmos. Environ. 2016, 146, 132140,  DOI: 10.1016/j.atmosenv.2016.06.033
  14. 14
    Carmichael, G. R.; Ferm, M.; Thongboonchoo, N.; Woo, J.-H.; Chan, L. Y.; Murano, K.; Viet, P. H.; Mossberg, C.; Bala, R.; Boonjawat, J.; Upatum, P.; Mohan, M.; Adhikary, S. P.; Shrestha, A. B.; Pienaar, J. J.; Brunke, E. B.; Chen, T.; Jie, T.; Guoan, D.; Peng, L. C.; Dhiharto, S.; Harjanto, H.; Jose, A. M.; Kimani, W.; Kirouane, A.; Lacaux, J.-P.; Richard, S.; Barturen, O.; Cerda, J. C.; Athayde, A.; Tavares, T.; Cotrina, J. S.; Bilici, E. Measurements of sulfur dioxide, ozone and ammonia concentrations in Asia, Africa, and South America using passive samplers. Atmos. Environ. 2003, 37 (9), 12931308,  DOI: 10.1016/S1352-2310(02)01009-9
  15. 15
    Meng, Z.-Y.; Xu, X.-B.; Wang, T.; Zhang, X.-Y.; Yu, X.-L.; Wang, S.-F.; Lin, W.-L.; Chen, Y.-Z.; Jiang, Y.-A.; An, X.-Q. Ambient sulfur dioxide, nitrogen dioxide, and ammonia at ten background and rural sites in China during 2007–2008. Atmos. Environ. 2010, 44 (21), 26252631,  DOI: 10.1016/j.atmosenv.2010.04.008
  16. 16
    Xu, W.; Luo, X. S.; Pan, Y. P.; Zhang, L.; Tang, A. H.; Shen, J. L.; Zhang, Y.; Li, K. H.; Wu, Q. H.; Yang, D. W.; Zhang, Y. Y.; Xue, J.; Li, W. Q.; Li, Q. Q.; Tang, L.; Lu, S. H.; Liang, T.; Tong, Y. A.; Liu, P.; Zhang, Q.; Xiong, Z. Q.; Shi, X. J.; Wu, L. H.; Shi, W. Q.; Tian, K.; Zhong, X. H.; Shi, K.; Tang, Q. Y.; Zhang, L. J.; Huang, J. L.; He, C. E.; Kuang, F. H.; Zhu, B.; Liu, H.; Jin, X.; Xin, Y. J.; Shi, X. K.; Du, E. Z.; Dore, A. J.; Tang, S.; Collett, J. L.; Goulding, K.; Sun, Y. X.; Ren, J.; Zhang, F. S.; Liu, X. J. Quantifying atmospheric nitrogen deposition through a nationwide monitoring network across China. Atmos. Chem. Phys. 2015, 15 (21), 1234512360,  DOI: 10.5194/acp-15-12345-2015
  17. 17
    von Bobrutzki, K.; Braban, C. F.; Famulari, D.; Jones, S. K.; Blackall, T.; Smith, T. E. L.; Blom, M.; Coe, H.; Gallagher, M.; Ghalaieny, M.; McGillen, M. R.; Percival, C. J.; Whitehead, J. D.; Ellis, R.; Murphy, J.; Mohacsi, A.; Pogany, A.; Junninen, H.; Rantanen, S.; Sutton, M. A.; Nemitz, E. Field inter-comparison of eleven atmospheric ammonia measurement techniques. Atmos. Meas. Tech. 2010, 3 (1), 91112,  DOI: 10.5194/amt-3-91-2010
  18. 18
    Ferm, M. Method for determination of atmospheric ammonia. Atmos. Environ. 1979, 13 (10), 13851393,  DOI: 10.1016/0004-6981(79)90107-0
  19. 19
    Felix, J. D.; Elliott, E. M.; Gish, T.; Maghirang, R.; Cambal, L.; Clougherty, J. Examining the transport of ammonia emissions across landscapes using nitrogen isotope ratios. Atmos. Environ. 2014, 95, 563570,  DOI: 10.1016/j.atmosenv.2014.06.061
  20. 20
    Perrino, C.; Catrambone, M. Development of a variable-path-length diffusive sampler for ammonia and evaluation of ammonia pollution in the urban area of Rome, Italy. Atmos. Environ. 2004, 38 (38), 66676672,  DOI: 10.1016/j.atmosenv.2004.08.032
  21. 21
    Zhao, Y.; Zhang, L.; Chen, Y.; Liu, X.; Xu, W.; Pan, Y.; Duan, L. Atmospheric nitrogen deposition to China: A model analysis on nitrogen budget and critical load exceedance. Atmos. Environ. 2017, 153, 3240,  DOI: 10.1016/j.atmosenv.2017.01.018
  22. 22
    Zhang, L.; Shao, J.; Lu, X.; Zhao, Y.; Hu, Y.; Henze, D. K.; Liao, H.; Gong, S.; Zhang, Q. Sources and Processes Affecting Fine Particulate Matter Pollution over North China: An Adjoint Analysis of the Beijing APEC Period. Environ. Sci. Technol. 2016, 50 (16), 87318740,  DOI: 10.1021/acs.est.6b03010
  23. 23
    Wesely, M. L. Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models. Atmos. Environ. 1989, 23 (6), 12931304,  DOI: 10.1016/0004-6981(89)90153-4
  24. 24
    Sutton, M. A.; Burkhardt, J. K.; Guerin, D.; Nemitz, E.; Fowler, D. Development of resistance models to describe measurements of bi-directional ammonia surface–atmosphere exchange. Atmos. Environ. 1998, 32 (3), 473480,  DOI: 10.1016/S1352-2310(97)00164-7
  25. 25
    Li, Y.; Thompson, T. M.; Van Damme, M.; Chen, X.; Benedict, K. B.; Shao, Y.; Day, D.; Boris, A.; Sullivan, A. P.; Ham, J.; Whitburn, S.; Clarisse, L.; Coheur, P. F.; Collett, J. L., Jr. Temporal and spatial variability of ammonia in urban and agricultural regions of northern Colorado, United States. Atmos. Chem. Phys. 2017, 17 (10), 61976213,  DOI: 10.5194/acp-17-6197-2017
  26. 26
    Huang, X.; Song, Y.; Li, M.; Li, J.; Huo, Q.; Cai, X.; Zhu, T.; Hu, M.; Zhang, H. A high-resolution ammonia emission inventory in China. Global. Biogeochem. Cy 2012, 26 (1), GB1030  DOI: 10.1029/2011GB004161
  27. 27
    Pan, Y.; Tian, S.; Liu, D.; Fang, Y.; Zhu, X.; Zhang, Q.; Zheng, B.; Michalski, G.; Wang, Y. Fossil fuel combustion-related emissions dominate atmospheric ammonia sources during severe haze episodes: Evidence from 15N-stable isotope in size-resolved aerosol ammonium. Environ. Sci. Technol. 2016, 50 (15), 80498056,  DOI: 10.1021/acs.est.6b00634
  28. 28
    McCalley, C. K.; Sparks, J. P. Controls over nitric oxide and ammonia emissions from Mojave Desert soils. Oecologia 2008, 156 (4), 871881,  DOI: 10.1007/s00442-008-1031-0
  29. 29
    Sun, Y.; Zhuang, G.; Huang, K.; Li, J.; Wang, Q.; Wang, Y.; Lin, Y.; Fu, J. S.; Zhang, W.; Tang, A.; Zhao, X. Asian dust over northern China and its impact on the downstream aerosol chemistry in 2004. J. Geophys. Res. 2010, 115 (D7), D00K09  DOI: 10.1029/2009JD012757
  30. 30
    Sun, K.; Tao, L.; Miller, D. J.; Pan, D.; Golston, L. M.; Zondlo, M. A.; Griffin, R. J.; Wallace, H. W.; Leong, Y. J.; Yang, M. M.; Zhang, Y.; Mauzerall, D. L.; Zhu, T. Vehicle Emissions as an Important Urban Ammonia Source in the United States and China. Environ. Sci. Technol. 2017, 51 (4), 24722481,  DOI: 10.1021/acs.est.6b02805
  31. 31
    Ianniello, A.; Spataro, F.; Esposito, G.; Allegrini, I.; Rantica, E.; Ancora, M.; Hu, M.; Zhu, T. Occurrence of gas phase ammonia in the area of Beijing (China). Atmos. Chem. Phys. 2010, 10, 94879503,  DOI: 10.5194/acp-10-9487-2010
  32. 32
    Teng, X.; Hu, Q.; Zhang, L.; Qi, J.; Shi, J.; Xie, H.; Gao, H.; Yao, X. Identification of Major Sources of Atmospheric NH3 in an Urban Environment in Northern China During Wintertime. Environ. Sci. Technol. 2017, 51 (12), 68396848,  DOI: 10.1021/acs.est.7b00328
  33. 33
    Zhang, X.; Wu, Y.; Liu, X.; Reis, S.; Jin, J.; Dragosits, U.; Van Damme, M.; Clarisse, L.; Whitburn, S.; Coheur, P.-F.; Gu, B. Ammonia Emissions May Be Substantially Underestimated in China. Environ. Sci. Technol. 2017, 51 (21), 1208912096,  DOI: 10.1021/acs.est.7b02171
  34. 34
    Fu, X.; Wang, S. X.; Ran, L. M.; Pleim, J. E.; Cooter, E.; Bash, J. O.; Benson, V.; Hao, J. M. Estimating NH3 emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model. Atmos. Chem. Phys. 2015, 15 (12), 66376649,  DOI: 10.5194/acp-15-6637-2015
  35. 35
    Denmead, O. T.; Freney, J. R.; Dunin, F. X. Gas exchange between plant canopies and the atmosphere: Case-studies for ammonia. Atmos. Environ. 2008, 42 (14), 33943406,  DOI: 10.1016/j.atmosenv.2007.01.038
  36. 36
    Li, M.; Zhang, Q.; Kurokawa, J. I.; Woo, J. H.; He, K.; Lu, Z.; Ohara, T.; Song, Y.; Streets, D. G.; Carmichael, G. R.; Cheng, Y.; Hong, C.; Huo, H.; Jiang, X.; Kang, S.; Liu, F.; Su, H.; Zheng, B. MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP. Atmos. Chem. Phys. 2017, 17 (2), 935963,  DOI: 10.5194/acp-17-935-2017

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  15. Hong-Wei Xiao, Jing-Feng Wu, Li Luo, Cheng Liu, Ya-Jun Xie, Hua-Yun Xiao. Enhanced biomass burning as a source of aerosol ammonium over cities in central China in autumn. Environmental Pollution 2020, 266 , 115278. https://doi.org/10.1016/j.envpol.2020.115278
  16. Juyan Cui, Jian Cui, Ying Peng, Dongrui Yao, Andy Chan, Zhiyuan Chen, Yueming Chen. Sources and trends of oxidized and reduced nitrogen wet deposition in a typical medium-sized city of eastern China during 2010–2016. Science of The Total Environment 2020, 744 , 140558. https://doi.org/10.1016/j.scitotenv.2020.140558
  17. X. J. Liu, W. Xu, E. Z. Du, A. H. Tang, Y. Zhang, Y. Y.  Zhang, Z. Wen, T. X. Hao, Y. P. Pan, L. Zhang, B. J.  Gu, Y. Zhao, J. L. Shen, F. Zhou, Z. L. Gao, Z. Z.  Feng, Y. H. Chang, K. Goulding, J. L.  Collett, P. M. Vitousek, F. S.  Zhang. Environmental impacts of nitrogen emissions in China and the role of policies in emission reduction. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2020, 378 (2183) , 20190324. https://doi.org/10.1098/rsta.2019.0324
  18. Weiwei Pu, Zhiqiang Ma, Jeffery L. Collett Jr, Heng Guo, Weili Lin, Ying Cheng, Weijun Quan, Yingruo Li, Fan Dong, Di He. Regional transport and urban emissions are important ammonia contributors in Beijing, China. Environmental Pollution 2020, 265 , 115062. https://doi.org/10.1016/j.envpol.2020.115062
  19. Yansheng Cao, Zhongyi Zhang, Hongwei Xiao, Yajun Xie, Yue Liang, Huayun Xiao. How aerosol pH responds to nitrate to sulfate ratio of fine-mode particulate. Environmental Science and Pollution Research 2020, 27 (28) , 35031-35039. https://doi.org/10.1007/s11356-020-09810-0
  20. Arshad Arjunan Nair, Fangqun Yu. Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling. Atmosphere 2020, 11 (10) , 1092. https://doi.org/10.3390/atmos11101092
  21. Xu Yu, Dejun Li, Dan Li, Guohua Zhang, Huaishan Zhou, Sheng Li, Wei Song, Yanli Zhang, Xinhui Bi, Jianzhen Yu, Xinming Wang. Enhanced Wet Deposition of Water‐Soluble Organic Nitrogen During the Harvest Season: Influence of Biomass Burning and In‐Cloud Scavenging. Journal of Geophysical Research: Atmospheres 2020, 125 (18) https://doi.org/10.1029/2020JD032699
  22. Yuepeng Pan, Mengna Gu, Yuexin He, Dianming Wu, Chunyan Liu, Linlin Song, Shili Tian, Xuemei Lü, Yang Sun, Tao Song, Wendell W. Walters, Xuejun Liu, Nicholas A. Martin, Qianqian Zhang, Yunting Fang, Valerio Ferracci, Yuesi Wang. Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia. Advances in Atmospheric Sciences 2020, 37 (9) , 933-938. https://doi.org/10.1007/s00376-020-2111-2
  23. Yuexin He, Yuepeng Pan, Guozhong Zhang, Dongsheng Ji, Shili Tian, Xiaojuan Xu, Renjian Zhang, Yuesi Wang. Tracking ammonia morning peak, sources and transport with 1 Hz measurements at a rural site in North China Plain. Atmospheric Environment 2020, 235 , 117630. https://doi.org/10.1016/j.atmosenv.2020.117630
  24. Danny M. Leung, Hongrong Shi, Bin Zhao, Jing Wang, Elizabeth M. Ding, Yu Gu, Haotian Zheng, Gang Chen, Kuo‐Nan Liou, Shuxiao Wang, Jerome D. Fast, Guangjie Zheng, Jingkun Jiang, Xiaoxiao Li, Jonathan H. Jiang. Wintertime Particulate Matter Decrease Buffered by Unfavorable Chemical Processes Despite Emissions Reductions in China. Geophysical Research Letters 2020, 47 (14) https://doi.org/10.1029/2020GL087721
  25. Yajun Xie, Haibo Lu, Aijun Yi, Zhongyi Zhang, Nengjian Zheng, Xiaozhen Fang, Huayun Xiao. Characterization and source analysis of water–soluble ions in PM2.5 at a background site in Central China. Atmospheric Research 2020, 239 , 104881. https://doi.org/10.1016/j.atmosres.2020.104881
  26. Peng Xu, Anping Chen, Benjamin Z. Houlton, Zhenzhong Zeng, Song Wei, Chenxu Zhao, Haiyan Lu, Yajun Liao, Zhonghua Zheng, Shengji Luan, Yi Zheng. Spatial Variation of Reactive Nitrogen Emissions From China's Croplands Codetermined by Regional Urbanization and Its Feedback to Global Climate Change. Geophysical Research Letters 2020, 47 (12) https://doi.org/10.1029/2019GL086551
  27. Ming Chang, Jiachen Cao, Mingrui Ma, Yimou Liu, Yuqi Liu, Weihua Chen, Qi Fan, Wenhui Liao, Shiguo Jia, Xuemei Wang. Dry deposition of reactive nitrogen to different ecosystems across eastern China: A comparison of three community models. Science of The Total Environment 2020, 720 , 137548. https://doi.org/10.1016/j.scitotenv.2020.137548
  28. Sheng-Cheng Shao, Yan-Lin Zhang, Yun-Hua Chang, Fang Cao, Yu-Chi Lin, Ahsan Mozaffar, Yi-Hang Hong. Online characterization of a large but overlooked human excreta source of ammonia in China's urban atmosphere. Atmospheric Environment 2020, 230 , 117459. https://doi.org/10.1016/j.atmosenv.2020.117459
  29. Can Wu, Gehui Wang, Jin Li, Jianjun Li, Cong Cao, Shuangshuang Ge, Yuning Xie, Jianmin Chen, Shijie Liu, Wei Du, Zhuyu Zhao, Fang Cao. Non-agricultural sources dominate the atmospheric NH3 in Xi'an, a megacity in the semi-arid region of China. Science of The Total Environment 2020, 722 , 137756. https://doi.org/10.1016/j.scitotenv.2020.137756
  30. Zhipeng Sha, Xin Ma, Nadine Loick, Tiantian Lv, Laura M. Cardenas, Yan Ma, Xuejun Liu, Tom Misselbrook. Nitrogen stabilizers mitigate reactive N and greenhouse gas emissions from an arable soil in North China Plain: Field and laboratory investigation. Journal of Cleaner Production 2020, 258 , 121025. https://doi.org/10.1016/j.jclepro.2020.121025
  31. Yuepeng PAN, Shili TIAN, Dianming WU, Wen XU, Xiaying ZHU, Chunyan LIU, Dejun LI, Yunting FANG, Lei DUAN, Xuejun LIU, Yuesi WANG. Ammonia should be considered in field experiments mimicking nitrogen deposition. Atmospheric and Oceanic Science Letters 2020, 13 (3) , 248-251. https://doi.org/10.1080/16742834.2020.1733919
  32. Yuepeng Pan, Mengna Gu, Linlin Song, Shili Tian, Dianming Wu, Wendell W. Walters, Xingna Yu, Xuemei Lü, Xue Ni, Yanjun Wang, Jing Cao, Xuejun Liu, Yunting Fang, Yuesi Wang. Systematic low bias of passive samplers in characterizing nitrogen isotopic composition of atmospheric ammonia. Atmospheric Research 2020, , 105018. https://doi.org/10.1016/j.atmosres.2020.105018
  33. Hao Li, An Ning, Jie Zhong, Haijie Zhang, Ling Liu, Yunling Zhang, Xiuhui Zhang, Xiao Cheng Zeng, Hong He. Influence of atmospheric conditions on sulfuric acid-dimethylamine-ammonia-based new particle formation. Chemosphere 2020, 245 , 125554. https://doi.org/10.1016/j.chemosphere.2019.125554
  34. Italia De Feis, Guido Masiello, Angela Cersosimo. Optimal Interpolation for Infrared Products from Hyperspectral Satellite Imagers and Sounders. Sensors 2020, 20 (8) , 2352. https://doi.org/10.3390/s20082352
  35. Xiaosheng Luo, Xuejun Liu, Yuepeng Pan, Zhang Wen, Wen Xu, Lin Zhang, Changlin Kou, Jinling Lv, Keith Goulding. Atmospheric reactive nitrogen concentration and deposition trends from 2011 to 2018 at an urban site in north China. Atmospheric Environment 2020, 224 , 117298. https://doi.org/10.1016/j.atmosenv.2020.117298
  36. Ye Kuang, Wanyun Xu, Weili Lin, Zhaoyang Meng, Huarong Zhao, Sanxue Ren, Gen Zhang, Linlin Liang, Xiaobin Xu. Explosive morning growth phenomena of NH3 on the North China Plain: Causes and potential impacts on aerosol formation. Environmental Pollution 2020, 257 , 113621. https://doi.org/10.1016/j.envpol.2019.113621
  37. Xuejun Liu, Wen Xu, Lei Liu, Enzai Du, Jianlin Shen, Xiaosheng Luo, Xiuying Zhang, Keith Goulding. Monitoring Atmospheric Nitrogen Deposition in China. 2020,,, 41-65. https://doi.org/10.1007/978-981-13-8514-8_3
  38. Yuepeng Pan, Yang Zeng, Shili Tian, Qianqian Zhang, Xiaying Zhu. Contribution of Atmospheric Reactive Nitrogen to Haze Pollution in China. 2020,,, 113-134. https://doi.org/10.1007/978-981-13-8514-8_6
  39. Xiao Han, Lingyun Zhu, Mingxu Liu, Yu Song, Meigen Zhang. Numerical analysis of agricultural emissions impacts on PM2.5 in China using a high-resolution ammonia emission inventory. Atmospheric Chemistry and Physics 2020, 20 (16) , 9979-9996. https://doi.org/10.5194/acp-20-9979-2020
  40. Baozhu Ge, Syuichi Itahashi, Keiichi Sato, Danhui Xu, Junhua Wang, Fan Fan, Qixin Tan, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Hong Liao, Meigen Zhang, Zhe Wang, Meng Li, Jung-Hun Woo, Junichi Kurokawa, Yuepeng Pan, Qizhong Wu, Xuejun Liu, Zifa Wang. Model Inter-Comparison Study for Asia (MICS-Asia) phase III: multimodel comparison of reactive nitrogen deposition over China. Atmospheric Chemistry and Physics 2020, 20 (17) , 10587-10610. https://doi.org/10.5194/acp-20-10587-2020
  41. Jian Xu, Jia Chen, Na Zhao, Guochen Wang, Guangyuan Yu, Hao Li, Juntao Huo, Yanfen Lin, Qingyan Fu, Hongyu Guo, Congrui Deng, Shan-Hu Lee, Jianmin Chen, Kan Huang. Importance of gas-particle partitioning of ammonia in haze formation in the rural agricultural environment. Atmospheric Chemistry and Physics 2020, 20 (12) , 7259-7269. https://doi.org/10.5194/acp-20-7259-2020
  42. Guohua Zhang, Xiufeng Lian, Yuzhen Fu, Qinhao Lin, Lei Li, Wei Song, Zhanyong Wang, Mingjin Tang, Duohong Chen, Xinhui Bi, Xinming Wang, Guoying Sheng. High secondary formation of nitrogen-containing organics (NOCs) and its possible link to oxidized organics and ammonium. Atmospheric Chemistry and Physics 2020, 20 (3) , 1469-1481. https://doi.org/10.5194/acp-20-1469-2020
  43. Yu Zhao, Mengchen Yuan, Xin Huang, Feng Chen, Jie Zhang. Quantification and evaluation of atmospheric ammonia emissions with different methods: a case study for the Yangtze River Delta region, China. Atmospheric Chemistry and Physics 2020, 20 (7) , 4275-4294. https://doi.org/10.5194/acp-20-4275-2020
  44. Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Joshua S. Fu, Xuemei Wang, Syuichi Itahashi, Kazuyo Yamaji, Tatsuya Nagashima, Hyo-Jung Lee, Cheol-Hee Kim, Chuan-Yao Lin, Lei Chen, Meigen Zhang, Zhining Tao, Jie Li, Mizuo Kajino, Hong Liao, Zhe Wang, Kengo Sudo, Yuesi Wang, Yuepeng Pan, Guiqian Tang, Meng Li, Qizhong Wu, Baozhu Ge, Gregory R. Carmichael. Evaluation and uncertainty investigation of the NO2, CO and NH3 modeling over China under the framework of MICS-Asia III. Atmospheric Chemistry and Physics 2020, 20 (1) , 181-202. https://doi.org/10.5194/acp-20-181-2020
  45. Zhen Wang, Xiuying Zhang, Lei Liu, Shanqian Wang, Xiaodi Wu, Wuting Zhang, Limin Zhao, Xuehe Lu, Xiaofeng Zhao. Evaluating the effects of nitrogen deposition on rice ecosystems across China. Agriculture, Ecosystems & Environment 2019, 285 , 106617. https://doi.org/10.1016/j.agee.2019.106617
  46. Qianqian Zhang, Yuepeng Pan, Yuexin He, Yuanghong Zhao, Liye Zhu, Xingying Zhang, Xiaojuan Xu, Dongsheng Ji, Jian Gao, Shili Tian, Wenkang Gao, Yuesi Wang. Bias in ammonia emission inventory and implications on emission control of nitrogen oxides over North China Plain. Atmospheric Environment 2019, 214 , 116869. https://doi.org/10.1016/j.atmosenv.2019.116869
  47. Baozhu Ge, Xiaobin Xu, Zhiqiang Ma, Xiaole Pan, Zhe Wang, Weili Lin, Bin Ouyang, Danhui Xu, James Lee, Mei Zheng, Dongsheng Ji, Yele Sun, Huabin Dong, Freya Anne Squires, Pingqing Fu, Zifa Wang. Role of Ammonia on the Feedback Between AWC and Inorganic Aerosol Formation During Heavy Pollution in the North China Plain. Earth and Space Science 2019, 6 (9) , 1675-1693. https://doi.org/10.1029/2019EA000799
  48. Shuping Zhang, Jia Xing, Golam Sarwar, Yanli Ge, Hong He, Fengkui Duan, Yan Zhao, Kebin He, Lidan Zhu, Biwu Chu. Parameterization of heterogeneous reaction of SO2 to sulfate on dust with coexistence of NH3 and NO2 under different humidity conditions. Atmospheric Environment 2019, 208 , 133-140. https://doi.org/10.1016/j.atmosenv.2019.04.004
  49. Ya Meng, Yilong Zhao, Rui Li, Junlin Li, Lulu Cui, Lingdong Kong, Hongbo Fu. Characterization of inorganic ions in rainwater in the megacity of Shanghai: Spatiotemporal variations and source apportionment. Atmospheric Research 2019, 222 , 12-24. https://doi.org/10.1016/j.atmosres.2019.01.023
  50. Tianling Li, Ming Zhou, Yuan Qiu, Jianyin Huang, Yonghong Wu, Shanqing Zhang, Huijun Zhao. Membrane-based conductivity probe for real-time in-situ monitoring rice field ammonia volatilization. Sensors and Actuators B: Chemical 2019, 286 , 62-68. https://doi.org/10.1016/j.snb.2019.01.099
  51. Jishao Jiang, Youwei Pan, Xianli Yang, Juan Liu, Haohao Miao, Yuqing Ren, Chunyan Zhang, Guangxuan Yan, Jinghua Lv, Yunbei Li. Beneficial influences of pelelith and dicyandiamide on gaseous emissions and the fungal community during sewage sludge composting. Environmental Science and Pollution Research 2019, 26 (9) , 8928-8938. https://doi.org/10.1007/s11356-019-04404-x
  52. Saehee Lim, Meehye Lee, Claudia I. Czimczik, Taekyu Joo, Sandra Holden, Gergana Mouteva, Guaciara M. Santos, Xiaomei Xu, Jennifer Walker, Saewung Kim, Hyun Seok Kim, Soyoung Kim, Sanguk Lee. Source signatures from combined isotopic analyses of PM2.5 carbonaceous and nitrogen aerosols at the peri-urban Taehwa Research Forest, South Korea in summer and fall. Science of The Total Environment 2019, 655 , 1505-1514. https://doi.org/10.1016/j.scitotenv.2018.11.157
  53. Pan Wu, Xiaojuan Huang, Junke Zhang, Bin Luo, Jinqi Luo, Hongyi Song, Wei Zhang, Zhihan Rao, Yanpeng Feng, Jianqiang Zhang. Characteristics and formation mechanisms of autumn haze pollution in Chengdu based on high time-resolved water-soluble ion analysis. Environmental Science and Pollution Research 2019, 26 (3) , 2649-2661. https://doi.org/10.1007/s11356-018-3630-6
  54. Lei Liu, Xiuying Zhang, Anthony Y. H. Wong, Wen Xu, Xuejun Liu, Yi Li, Huan Mi, Xuehe Lu, Limin Zhao, Zhen Wang, Xiaodi Wu, Jing Wei. Estimating global surface ammonia concentrations inferred from satellite retrievals. Atmospheric Chemistry and Physics 2019, 19 (18) , 12051-12066. https://doi.org/10.5194/acp-19-12051-2019
  55. Zhaofeng Tan, Keding Lu, Meiqing Jiang, Rong Su, Hongli Wang, Shengrong Lou, Qingyan Fu, Chongzhi Zhai, Qinwen Tan, Dingli Yue, Duohong Chen, Zhanshan Wang, Shaodong Xie, Limin Zeng, Yuanhang Zhang. Daytime atmospheric oxidation capacity in four Chinese megacities during the photochemically polluted season: a case study based on box model simulation. Atmospheric Chemistry and Physics 2019, 19 (6) , 3493-3513. https://doi.org/10.5194/acp-19-3493-2019
  56. Biwu Chu, Veli-Matti Kerminen, Federico Bianchi, Chao Yan, Tuukka Petäjä, Markku Kulmala. Atmospheric new particle formation in China. Atmospheric Chemistry and Physics 2019, 19 (1) , 115-138. https://doi.org/10.5194/acp-19-115-2019
  57. Yang Zeng, Shili Tian, Yuepeng Pan. Revealing the Sources of Atmospheric Ammonia: a Review. Current Pollution Reports 2018, 4 (3) , 189-197. https://doi.org/10.1007/s40726-018-0096-6
  58. Mingxu Liu, Xin Huang, Yu Song, Tingting Xu, Shuxiao Wang, Zhijun Wu, Min Hu, Lin Zhang, Qiang Zhang, Yuepeng Pan, Xuejun Liu, Tong Zhu. Rapid SO2 emission reductions significantly increase tropospheric ammonia concentrations over the North China Plain. Atmospheric Chemistry and Physics 2018, 18 (24) , 17933-17943. https://doi.org/10.5194/acp-18-17933-2018
  59. Yangyang Zhang, Aohan Tang, Dandan Wang, Qingqing Wang, Katie Benedict, Lin Zhang, Duanyang Liu, Yi Li, Jeffrey L. Collett Jr., Yele Sun, Xuejun Liu. The vertical variability of ammonia in urban Beijing, China. Atmospheric Chemistry and Physics 2018, 18 (22) , 16385-16398. https://doi.org/10.5194/acp-18-16385-2018
  • Abstract

    Figure 1

    Figure 1. Spatial distribution of ammonia concentrations observed from the surface network (site) versus satellite column data (grid) in China. The detailed surface observation site information can be found in Table 1 and SI. Satellite NH3 total column distributions were derived from the infrared atmospheric sounding interferometer (IASI) aboard MetOp-A for the year 2015. We collected the observations from morning overpass time (9:30 LTC) and filtered the columns with relative error above 100% following procedures presented in Van Damme et al.(12) The filtered IASI satellite columns were then mapped to a 0.25° × 0.25° horizontal resolution by averaging available observations within each grid cell. The provincial boundary layer with a scale of 1:4,000,000 was obtained from the National Geomatics Center of China (http://ngcc.sbsm.gov.cn/). Maps were generated based upon a geospatial analysis using ESRI ArcGIS software (version 10.1, http://www.esri.com/software/arcgis/arcgis-for-desktop).

    Figure 2

    Figure 2. Seasonal variations of ammonia concentrations observed from the surface network (53 sites) in China.

    Figure 3

    Figure 3. Comparisons of passive diffusion sampler to the continuously active analyzers of MARGA and DELTA. Ammonia concentrations are aggregated to monthly data points.

    Figure 4

    Figure 4. Spatial distribution of the site-based dry deposition fluxes versus the gridded agriculture emission inventory of ammonia in China. The legend for gridded ammonia inventory was also shown in units of kg N ha–1 year–1 (numbers in the left corner), in addition to units of t year–1 per 0.25° by 0.25°. The NH3 inventory used in this study was obtained from the Multi-Resolution Emission Inventory of China (MEIC, http://meicmodel.org),(36) originally developed and described by Huang et al.(26) The MEIC inventory is provided with monthly gridded emissions of NH3 at 0.25° × 0.25° for five sectors, that is, power generation, industry, residential, transportation, and agriculture. The agriculture sector is a dominant source of NH3 emissions at the national scale, mainly contributed by fertilizer applications and manure managements. The year of 2012 was chosen to conduct the spatial comparison because emissions after 2012 are currently unavailable. The provincial boundary layer with a scale of 1:4 000 000 was obtained from the National Geomatics Center of China (http://ngcc.sbsm.gov.cn/). Maps were generated based upon a geospatial analysis using ESRI ArcGIS software (version 10.1, http://www.esri.com/software/arcgis/arcgis-for-desktop).

    Figure 5

    Figure 5. Comparison of the site-based dry deposition fluxes versus the gridded agriculture emission inventory of ammonia in China (1° by 1°). The sites are colored by region. The units of emission data were converted to kg N ha–1 year–1 for comparison with that of ammonia deposition. The 1:1 line represents equal ammonia dry deposition and emissions.

  • References

    ARTICLE SECTIONS
    Jump To

    This article references 36 other publications.

    1. 1
      Vitousek, P.; Mooney, H.; Lubchenco, J.; Melillo, J. Human domination of Earth’s ecosystems. Science 1997, 277 (5325), 494499,  DOI: 10.1126/science.277.5325.494
    2. 2
      Galloway, J. N.; Townsend, A. R.; Erisman, J. W.; Bekunda, M.; Cai, Z.; Freney, J. R.; Martinelli, L. A.; Seitzinger, S. P.; Sutton, M. A. Transformation of the Nitrogen Cycle: Recent Trends, Questions, and Potential Solutions. Science 2008, 320 (5878), 889892,  DOI: 10.1126/science.1136674
    3. 3
      Fu, X.; Wang, S.; Xing, J.; Zhang, X.; Wang, T.; Hao, J. Increasing Ammonia Concentrations Reduce the Effectiveness of Particle Pollution Control Achieved via SO2 and NOX Emissions Reduction in East China. Environ. Sci. Technol. Lett. 2017, 4 (6), 221227,  DOI: 10.1021/acs.estlett.7b00143
    4. 4
      Liu, X.; Zhang, Y.; Han, W.; Tang, A.; Shen, J.; Cui, Z.; Vitousek, P.; Erisman, J. W.; Goulding, K.; Christie, P.; Fangmeier, A.; Zhang, F. Enhanced nitrogen deposition over China. Nature 2013, 494 (7438), 459462,  DOI: 10.1038/nature11917
    5. 5
      Warner, J. X.; Dickerson, R. R.; Wei, Z.; Strow, L. L.; Wang, Y.; Liang, Q. Increased atmospheric ammonia over the world’s major agricultural areas detected from space. Geophys. Res. Lett. 2017, 44 (6), 28752884,  DOI: 10.1002/2016GL072305
    6. 6
      Li, Y.; Schichtel, B. A.; Walker, J. T.; Schwede, D. B.; Chen, X.; Lehmann, C. M.; Puchalski, M. A.; Gay, D. A.; Collett, J., Jr Increasing importance of deposition of reduced nitrogen in the United States. Proc. Natl. Acad. Sci. U. S. A. 2016, 113 (21), 58745879,  DOI: 10.1073/pnas.1525736113
    7. 7
      Pan, Y.; Wang, Y.; Tang, G.; Wu, D. Wet and dry deposition of atmospheric nitrogen at ten sites in Northern China. Atmos. Chem. Phys. 2012, 12 (14), 65156535,  DOI: 10.5194/acp-12-6515-2012
    8. 8
      Meng, W.; Zhong, Q.; Yun, X.; Zhu, X.; Huang, T.; Shen, H.; Chen, Y.; Chen, H.; Zhou, F.; Liu, J.; Wang, X.; Zeng, E. Y.; Tao, S. Improvement of a Global High-Resolution Ammonia Emission Inventory for Combustion and Industrial Sources with New Data from the Residential and Transportation Sectors. Environ. Sci. Technol. 2017, 51 (5), 28212829,  DOI: 10.1021/acs.est.6b03694
    9. 9
      Tian, S.; Pan, Y.; Liu, Z.; Wen, T.; Wang, Y. Size-resolved aerosol chemical analysis of extreme haze pollution events during early 2013 in urban Beijing, China. J. Hazard. Mater. 2014, 279, 452460,  DOI: 10.1016/j.jhazmat.2014.07.023
    10. 10
      Wang, G.; Zhang, R.; Gomez, M. E.; Yang, L.; Levy Zamora, M.; Hu, M.; Lin, Y.; Peng, J.; Guo, S.; Meng, J.; Li, J.; Cheng, C.; Hu, T.; Ren, Y.; Wang, Y.; Gao, J.; Cao, J.; An, Z.; Zhou, W.; Li, G.; Wang, J.; Tian, P.; Marrero-Ortiz, W.; Secrest, J.; Du, Z.; Zheng, J.; Shang, D.; Zeng, L.; Shao, M.; Wang, W.; Huang, Y.; Wang, Y.; Zhu, Y.; Li, Y.; Hu, J.; Pan, B.; Cai, L.; Cheng, Y.; Ji, Y.; Zhang, F.; Rosenfeld, D.; Liss, P. S.; Duce, R. A.; Kolb, C. E.; Molina, M. J. Persistent sulfate formation from London Fog to Chinese haze. Proc. Natl. Acad. Sci. U. S. A. 2016, 113 (48), 1363013635,  DOI: 10.1073/pnas.1616540113
    11. 11
      Beer, R.; Shephard, M. W.; Kulawik, S. S.; Clough, S. A.; Eldering, A.; Bowman, K. W.; Sander, S. P.; Fisher, B. M.; Payne, V. H.; Luo, M.; Osterman, G. B.; Worden, J. R. First satellite observations of lower tropospheric ammonia and methanol. Geophys. Res. Lett. 2008, 35 (9), L09801  DOI: 10.1029/2008GL033642
    12. 12
      Van Damme, M.; Clarisse, L.; Heald, C. L.; Hurtmans, D.; Ngadi, Y.; Clerbaux, C.; Dolman, A. J.; Erisman, J. W.; Coheur, P. F. Global distributions, time series and error characterization of atmospheric ammonia (NH3) from IASI satellite observations. Atmos. Chem. Phys. Discuss. 2014, 14 (6), 29052922,  DOI: 10.5194/acpd-13-24301-2013
    13. 13
      Butler, T.; Vermeylen, F.; Lehmann, C. M.; Likens, G. E.; Puchalski, M. Increasing ammonia concentration trends in large regions of the USA derived from the NADP/AMoN network. Atmos. Environ. 2016, 146, 132140,  DOI: 10.1016/j.atmosenv.2016.06.033
    14. 14
      Carmichael, G. R.; Ferm, M.; Thongboonchoo, N.; Woo, J.-H.; Chan, L. Y.; Murano, K.; Viet, P. H.; Mossberg, C.; Bala, R.; Boonjawat, J.; Upatum, P.; Mohan, M.; Adhikary, S. P.; Shrestha, A. B.; Pienaar, J. J.; Brunke, E. B.; Chen, T.; Jie, T.; Guoan, D.; Peng, L. C.; Dhiharto, S.; Harjanto, H.; Jose, A. M.; Kimani, W.; Kirouane, A.; Lacaux, J.-P.; Richard, S.; Barturen, O.; Cerda, J. C.; Athayde, A.; Tavares, T.; Cotrina, J. S.; Bilici, E. Measurements of sulfur dioxide, ozone and ammonia concentrations in Asia, Africa, and South America using passive samplers. Atmos. Environ. 2003, 37 (9), 12931308,  DOI: 10.1016/S1352-2310(02)01009-9
    15. 15
      Meng, Z.-Y.; Xu, X.-B.; Wang, T.; Zhang, X.-Y.; Yu, X.-L.; Wang, S.-F.; Lin, W.-L.; Chen, Y.-Z.; Jiang, Y.-A.; An, X.-Q. Ambient sulfur dioxide, nitrogen dioxide, and ammonia at ten background and rural sites in China during 2007–2008. Atmos. Environ. 2010, 44 (21), 26252631,  DOI: 10.1016/j.atmosenv.2010.04.008
    16. 16
      Xu, W.; Luo, X. S.; Pan, Y. P.; Zhang, L.; Tang, A. H.; Shen, J. L.; Zhang, Y.; Li, K. H.; Wu, Q. H.; Yang, D. W.; Zhang, Y. Y.; Xue, J.; Li, W. Q.; Li, Q. Q.; Tang, L.; Lu, S. H.; Liang, T.; Tong, Y. A.; Liu, P.; Zhang, Q.; Xiong, Z. Q.; Shi, X. J.; Wu, L. H.; Shi, W. Q.; Tian, K.; Zhong, X. H.; Shi, K.; Tang, Q. Y.; Zhang, L. J.; Huang, J. L.; He, C. E.; Kuang, F. H.; Zhu, B.; Liu, H.; Jin, X.; Xin, Y. J.; Shi, X. K.; Du, E. Z.; Dore, A. J.; Tang, S.; Collett, J. L.; Goulding, K.; Sun, Y. X.; Ren, J.; Zhang, F. S.; Liu, X. J. Quantifying atmospheric nitrogen deposition through a nationwide monitoring network across China. Atmos. Chem. Phys. 2015, 15 (21), 1234512360,  DOI: 10.5194/acp-15-12345-2015
    17. 17
      von Bobrutzki, K.; Braban, C. F.; Famulari, D.; Jones, S. K.; Blackall, T.; Smith, T. E. L.; Blom, M.; Coe, H.; Gallagher, M.; Ghalaieny, M.; McGillen, M. R.; Percival, C. J.; Whitehead, J. D.; Ellis, R.; Murphy, J.; Mohacsi, A.; Pogany, A.; Junninen, H.; Rantanen, S.; Sutton, M. A.; Nemitz, E. Field inter-comparison of eleven atmospheric ammonia measurement techniques. Atmos. Meas. Tech. 2010, 3 (1), 91112,  DOI: 10.5194/amt-3-91-2010
    18. 18
      Ferm, M. Method for determination of atmospheric ammonia. Atmos. Environ. 1979, 13 (10), 13851393,  DOI: 10.1016/0004-6981(79)90107-0
    19. 19
      Felix, J. D.; Elliott, E. M.; Gish, T.; Maghirang, R.; Cambal, L.; Clougherty, J. Examining the transport of ammonia emissions across landscapes using nitrogen isotope ratios. Atmos. Environ. 2014, 95, 563570,  DOI: 10.1016/j.atmosenv.2014.06.061
    20. 20
      Perrino, C.; Catrambone, M. Development of a variable-path-length diffusive sampler for ammonia and evaluation of ammonia pollution in the urban area of Rome, Italy. Atmos. Environ. 2004, 38 (38), 66676672,  DOI: 10.1016/j.atmosenv.2004.08.032
    21. 21
      Zhao, Y.; Zhang, L.; Chen, Y.; Liu, X.; Xu, W.; Pan, Y.; Duan, L. Atmospheric nitrogen deposition to China: A model analysis on nitrogen budget and critical load exceedance. Atmos. Environ. 2017, 153, 3240,  DOI: 10.1016/j.atmosenv.2017.01.018
    22. 22
      Zhang, L.; Shao, J.; Lu, X.; Zhao, Y.; Hu, Y.; Henze, D. K.; Liao, H.; Gong, S.; Zhang, Q. Sources and Processes Affecting Fine Particulate Matter Pollution over North China: An Adjoint Analysis of the Beijing APEC Period. Environ. Sci. Technol. 2016, 50 (16), 87318740,  DOI: 10.1021/acs.est.6b03010
    23. 23
      Wesely, M. L. Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models. Atmos. Environ. 1989, 23 (6), 12931304,  DOI: 10.1016/0004-6981(89)90153-4
    24. 24
      Sutton, M. A.; Burkhardt, J. K.; Guerin, D.; Nemitz, E.; Fowler, D. Development of resistance models to describe measurements of bi-directional ammonia surface–atmosphere exchange. Atmos. Environ. 1998, 32 (3), 473480,  DOI: 10.1016/S1352-2310(97)00164-7
    25. 25
      Li, Y.; Thompson, T. M.; Van Damme, M.; Chen, X.; Benedict, K. B.; Shao, Y.; Day, D.; Boris, A.; Sullivan, A. P.; Ham, J.; Whitburn, S.; Clarisse, L.; Coheur, P. F.; Collett, J. L., Jr. Temporal and spatial variability of ammonia in urban and agricultural regions of northern Colorado, United States. Atmos. Chem. Phys. 2017, 17 (10), 61976213,  DOI: 10.5194/acp-17-6197-2017
    26. 26
      Huang, X.; Song, Y.; Li, M.; Li, J.; Huo, Q.; Cai, X.; Zhu, T.; Hu, M.; Zhang, H. A high-resolution ammonia emission inventory in China. Global. Biogeochem. Cy 2012, 26 (1), GB1030  DOI: 10.1029/2011GB004161
    27. 27
      Pan, Y.; Tian, S.; Liu, D.; Fang, Y.; Zhu, X.; Zhang, Q.; Zheng, B.; Michalski, G.; Wang, Y. Fossil fuel combustion-related emissions dominate atmospheric ammonia sources during severe haze episodes: Evidence from 15N-stable isotope in size-resolved aerosol ammonium. Environ. Sci. Technol. 2016, 50 (15), 80498056,  DOI: 10.1021/acs.est.6b00634
    28. 28
      McCalley, C. K.; Sparks, J. P. Controls over nitric oxide and ammonia emissions from Mojave Desert soils. Oecologia 2008, 156 (4), 871881,  DOI: 10.1007/s00442-008-1031-0
    29. 29
      Sun, Y.; Zhuang, G.; Huang, K.; Li, J.; Wang, Q.; Wang, Y.; Lin, Y.; Fu, J. S.; Zhang, W.; Tang, A.; Zhao, X. Asian dust over northern China and its impact on the downstream aerosol chemistry in 2004. J. Geophys. Res. 2010, 115 (D7), D00K09  DOI: 10.1029/2009JD012757
    30. 30
      Sun, K.; Tao, L.; Miller, D. J.; Pan, D.; Golston, L. M.; Zondlo, M. A.; Griffin, R. J.; Wallace, H. W.; Leong, Y. J.; Yang, M. M.; Zhang, Y.; Mauzerall, D. L.; Zhu, T. Vehicle Emissions as an Important Urban Ammonia Source in the United States and China. Environ. Sci. Technol. 2017, 51 (4), 24722481,  DOI: 10.1021/acs.est.6b02805
    31. 31
      Ianniello, A.; Spataro, F.; Esposito, G.; Allegrini, I.; Rantica, E.; Ancora, M.; Hu, M.; Zhu, T. Occurrence of gas phase ammonia in the area of Beijing (China). Atmos. Chem. Phys. 2010, 10, 94879503,  DOI: 10.5194/acp-10-9487-2010
    32. 32
      Teng, X.; Hu, Q.; Zhang, L.; Qi, J.; Shi, J.; Xie, H.; Gao, H.; Yao, X. Identification of Major Sources of Atmospheric NH3 in an Urban Environment in Northern China During Wintertime. Environ. Sci. Technol. 2017, 51 (12), 68396848,  DOI: 10.1021/acs.est.7b00328
    33. 33
      Zhang, X.; Wu, Y.; Liu, X.; Reis, S.; Jin, J.; Dragosits, U.; Van Damme, M.; Clarisse, L.; Whitburn, S.; Coheur, P.-F.; Gu, B. Ammonia Emissions May Be Substantially Underestimated in China. Environ. Sci. Technol. 2017, 51 (21), 1208912096,  DOI: 10.1021/acs.est.7b02171
    34. 34
      Fu, X.; Wang, S. X.; Ran, L. M.; Pleim, J. E.; Cooter, E.; Bash, J. O.; Benson, V.; Hao, J. M. Estimating NH3 emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model. Atmos. Chem. Phys. 2015, 15 (12), 66376649,  DOI: 10.5194/acp-15-6637-2015
    35. 35
      Denmead, O. T.; Freney, J. R.; Dunin, F. X. Gas exchange between plant canopies and the atmosphere: Case-studies for ammonia. Atmos. Environ. 2008, 42 (14), 33943406,  DOI: 10.1016/j.atmosenv.2007.01.038
    36. 36
      Li, M.; Zhang, Q.; Kurokawa, J. I.; Woo, J. H.; He, K.; Lu, Z.; Ohara, T.; Song, Y.; Streets, D. G.; Carmichael, G. R.; Cheng, Y.; Hong, C.; Huo, H.; Jiang, X.; Kang, S.; Liu, F.; Su, H.; Zheng, B. MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP. Atmos. Chem. Phys. 2017, 17 (2), 935963,  DOI: 10.5194/acp-17-935-2017
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    • Figure S1 illustrates the ammonia concentration and temperature correlation. Table S1 summarizes the site information. The text details the site selection and siting protocols with accompanying references (PDF)


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