<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0"><?xmltex \makeatother\@nolinetrue\makeatletter?>
  <front>
    <journal-meta><journal-id journal-id-type="publisher">ACP</journal-id><journal-title-group>
    <journal-title>Atmospheric Chemistry and Physics</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1680-7324</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-18-17933-2018</article-id><title-group><article-title>Rapid SO<inline-formula><mml:math id="M1" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> emission reductions significantly increase tropospheric
ammonia concentrations over the North China Plain</article-title><alt-title>Trend of ammonia concentrations in China</alt-title>
      </title-group><?xmltex \runningtitle{Trend of ammonia concentrations in China}?><?xmltex \runningauthor{M. Liu et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Liu</surname><given-names>Mingxu</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-1419-1990</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Huang</surname><given-names>Xin</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-0922-5014</ext-link></contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Song</surname><given-names>Yu</given-names></name>
          <email>songyu@pku.edu.cn</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Xu</surname><given-names>Tingting</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Wang</surname><given-names>Shuxiao</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-9727-1963</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Wu</surname><given-names>Zhijun</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Hu</surname><given-names>Min</given-names></name>
          <email>minhu@pku.edu.cn</email>
        <ext-link>https://orcid.org/0000-0003-4816-9123</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Zhang</surname><given-names>Lin</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Zhang</surname><given-names>Qiang</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Pan</surname><given-names>Yuepeng</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-5547-0849</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Liu</surname><given-names>Xuejun</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Zhu</surname><given-names>Tong</given-names></name>
          <email>tzhu@pku.edu.cn</email>
        <ext-link>https://orcid.org/0000-0002-2752-7924</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>State Key Joint Laboratory of Environmental Simulation and Pollution
Control, Department of Environmental Science, Peking University, Beijing
100871, China</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Joint International Research Laboratory of Atmospheric and Earth
System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing
210023, China</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, <?xmltex \hack{\newline}?>Tsinghua University, Beijing 100084, China</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Laboratory for Climate and Ocean–Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, <?xmltex \hack{\newline}?>School of Physics, Peking University,
Beijing 100871, China</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Ministry of Education Key Laboratory for Earth System Modeling, Center
for Earth System Science, <?xmltex \hack{\newline}?>Institute for Global Change Studies, Tsinghua
University, Beijing 100084, China</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry (LAPC), <?xmltex \hack{\newline}?>Institute of Atmospheric Physics, Chinese
Academy of Sciences 100029, Beijing, China</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>Beijing Key Laboratory of Farmland Soil Pollution Prevention and
Remediation, College of Resources and Environmental Sciences, China
Agricultural University, Beijing 100193, China</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Yu Song (songyu@pku.edu.cn), Min Hu (minhu@pku.edu.cn) and
Tong Zhu (tzhu@pku.edu.cn)</corresp></author-notes><pub-date><day>18</day><month>December</month><year>2018</year></pub-date>
      
      <volume>18</volume>
      <issue>24</issue>
      <fpage>17933</fpage><lpage>17943</lpage>
      <history>
        <date date-type="received"><day>26</day><month>August</month><year>2018</year></date>
           <date date-type="rev-request"><day>5</day><month>September</month><year>2018</year></date>
           <date date-type="rev-recd"><day>29</day><month>November</month><year>2018</year></date>
           <date date-type="accepted"><day>4</day><month>December</month><year>2018</year></date>
      </history>
      <permissions>
        
        
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>
      <abstract>
    <p id="d1e243">The North China Plain has been identified as a significant hotspot of ammonia
(<inline-formula><mml:math id="M2" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) due to extensive agricultural activities. Satellite
observations suggest a significant increase of about 30 % in tropospheric
gas-phase <inline-formula><mml:math id="M3" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations in this area during 2008–2016.
However, the estimated <inline-formula><mml:math id="M4" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions decreased slightly by 7 %
because of changes in Chinese agricultural practices, i.e., the transition in
fertilizer types from ammonium carbonate fertilizer to urea, and in the
livestock rearing system from free-range to intensive farming. We note that
the emissions of sulfur dioxide (<inline-formula><mml:math id="M5" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) have rapidly declined by
about 60 % over the recent few years. By integrating measurements from
ground and satellite, a long-term anthropogenic <inline-formula><mml:math id="M6" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission
inventory, and chemical transport model simulations, we find that this large
<inline-formula><mml:math id="M7" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reduction is responsible for the <inline-formula><mml:math id="M8" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
increase over the North China Plain. The simulations for the period
2008–2016 demonstrate that the annual average sulfate concentrations
decreased by about 50 %, which significantly weakens the formation of
ammonium sulfate and increases the average proportions of gas-phase
<inline-formula><mml:math id="M9" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> within the total <inline-formula><mml:math id="M10" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations from
26 % (2008) to 37 % (2016). By fixing <inline-formula><mml:math id="M11" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions of 2008
in those multi-year simulations, the increasing trend of the tropospheric
<inline-formula><mml:math id="M12" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations is not observed. Both the decreases in sulfate
and increases in <inline-formula><mml:math id="M13" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations show highest values in summer,
possibly because the formation of sulfate aerosols is more sensitive to
<inline-formula><mml:math id="M14" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions in summer than in other seasons. Besides,
the changes in <inline-formula><mml:math id="M15" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions and meteorological conditions
both decreased the <inline-formula><mml:math id="M16" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations by about 3 % in
the study period. Our simulations suggest that the moderate reduction in
<inline-formula><mml:math id="M17" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions (16 %) favors the formation of
particulate nitrate by elevating ozone concentrations in the lower
troposphere.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

      <?xmltex \hack{\newpage}?>
<?pagebreak page17934?><sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p id="d1e433">Ammonia (<inline-formula><mml:math id="M18" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) is considered the most important alkaline gas in the
atmosphere. On both a global and regional scale, <inline-formula><mml:math id="M19" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> is mostly
emitted from agricultural activities, mainly including the fertilization and
livestock industry (Bouwman et al., 1997). Gas-phase <inline-formula><mml:math id="M20" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> can react
with ambient sulfuric and nitric acids to form ammonium sulfate/bisulfate and
ammonium nitrate aerosols (SNAs), which constitute a significant fraction of
atmospheric fine particles (PM<inline-formula><mml:math id="M21" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula>) associated with potential human
health impacts (Pope et al., 2009; Seinfeld and Pandis, 2006). Ammonia and
ammonium (<inline-formula><mml:math id="M22" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>) is ultimately deposited back to the earth
surface, contributing to acid deposition and eutrophication (Asman, 1998;
Behera et al., 2013; Pozzer et al., 2017).</p>
      <p id="d1e491">As a major agricultural country, China is one of the world's largest emitters
of <inline-formula><mml:math id="M23" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, the amount of which (<inline-formula><mml:math id="M24" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> Tg yr<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) exceeds the
sum of those in Europe (<inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">4.0</mml:mn></mml:mrow></mml:math></inline-formula> Tg yr<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and North America
(<inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">4.0</mml:mn></mml:mrow></mml:math></inline-formula> Tg yr<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) (Huang et al., 2012; Bouwman et al., 1997; Paulot
et al., 2014). Fertilizer application and livestock manure management
contribute to nearly 90 % of China's <inline-formula><mml:math id="M30" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions (Huang et
al., 2012; Zhang et al., 2018). Until now, <inline-formula><mml:math id="M31" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions have not
been regulated by the Chinese government, although they serve as an important
contributor to haze pollution in China.</p>
      <p id="d1e594">The North China Plain (the spatial definition of this area is illustrated in
Fig. S1 in the Supplement) is a hotspot of <inline-formula><mml:math id="M32" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> loadings, as
revealed by satellite detection and ground measurements (Clarisse et al.,
2009; Pan et al., 2018). Interestingly, satellite observations over the past
decade have shown an increase in tropospheric columns of gaseous
<inline-formula><mml:math id="M33" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in this area (Warner et al., 2017). But no sensitivity studies
have been performed to explain it, especially from a modeling perspective. A
long-term bottom-up inventory indicates that <inline-formula><mml:math id="M34" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in China
have displayed a slightly decreasing tendency (Kang et al., 2016). During
2006–2016, ammonium bicarbonate for crop fertilization was replaced by urea
fertilizer (its fraction of application increasing from 60 % to 90 % of all
mineral nitrogen fertilizers). In the meantime, the traditional free-range
livestock system was gradually replaced by the intensive animal rearing system
(i.e., raising livestock in confinement at a high stocking density) in the
livestock industry (increasing from 21 % in 2006 to 48 % in 2016;
shown in Table S1 in the Supplement). These changes in agricultural practices
have lowered the volatilization rates of <inline-formula><mml:math id="M35" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> (Kang et al., 2016).</p>
      <p id="d1e641">Several studies have proposed that reduction in <inline-formula><mml:math id="M36" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions or
<inline-formula><mml:math id="M37" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions is an important factor in determining the
increase in atmospheric <inline-formula><mml:math id="M38" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations on the global and
regional scales (Warner et al., 2017; Yu et al., 2018; Saylor et al., 2015). Through
the widespread use of the flue gas desulfurization in power plants since 2006
in China, <inline-formula><mml:math id="M39" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions have gradually decreased (Lu et al., 2011;
Li et al., 2010). Li et al. (2017) found it was reduced by 70 % from the
peak year (around 2006) to 2016 based on satellite observations and bottom-up
methods. Specifically, the initiation of the Action Plan for Air Pollution
Prevention and Control (referred to as the national Ten Measures for
Air) since 2013 resulted in a rapid reduction of about 50 % over recent
few years, from <inline-formula><mml:math id="M40" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">30</mml:mn></mml:mrow></mml:math></inline-formula> Tg in 2012 to <inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula> Tg in 2016 according to the
Multi-resolution Emission Inventory for China (MEIC) (Zheng et al., 2018). To
our knowledge, such a strong decrease in <inline-formula><mml:math id="M42" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions is only
found in China. In contrast, emissions of nitrogen oxides
(<inline-formula><mml:math id="M43" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) in MEIC peaked around 2012 with only a moderate
decrease of <inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula> % from 2012 to 2016 (Liu et al., 2016).</p>
      <p id="d1e742">Here, we hypothesize that the rapid <inline-formula><mml:math id="M45" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reduction is the
main cause of the increase in tropospheric <inline-formula><mml:math id="M46" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations over
the North China Plain. To verify this, we first used observation datasets
from the ground and space to infer the relationship between the trends in
<inline-formula><mml:math id="M47" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M48" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations. A comprehensive long-term
<inline-formula><mml:math id="M49" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission inventory, developed by our recent studies based on
bottom-up methods, was also used to demonstrate the inter-annual variations
of <inline-formula><mml:math id="M50" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in this region. Then, we performed multi-year
simulations with a chemical transport model to examine the impact of changes
in <inline-formula><mml:math id="M51" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions on tropospheric <inline-formula><mml:math id="M52" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations in
terms of the magnitude and seasonal variation. Besides, other potential
mechanisms (<inline-formula><mml:math id="M53" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emission and meteorology) were discussed.</p>
</sec>
<sec id="Ch1.S2">
  <title>Methods</title>
<sec id="Ch1.S2.SS1">
  <title>Observation datasets</title>
      <p id="d1e856">Observations from space and ground stations were used in this study.
Tropospheric vertical column densities (VCDs) of <inline-formula><mml:math id="M54" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> were derived
from the measurements of Infrared Atmospheric Sounding Interferometer (IASI)
on board MetOp-A (Van Damme et al., 2015, 2017; Clarisse et al., 2009). We
determined the annual averages of <inline-formula><mml:math id="M55" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations over
the North China Plain on a 0.25<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M57" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.25<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid during
2008–2016, based on the relative error weighting mean method (Van Damme et
al., 2014). The monthly <inline-formula><mml:math id="M59" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations were measured using
passive <inline-formula><mml:math id="M60" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> diffusive samplers (Analyst, CNR Institute of
Atmospheric Pollution, Rome, Italy), from September 2015 to August 2016 at
11 sites over northern China (Pan et al., 2018). The <inline-formula><mml:math id="M61" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> VCDs were
provided by the Ozone Monitoring Instrument (OMI) measurements to test the
trend of <inline-formula><mml:math id="M62" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations. They were derived from the Level-3
Aura/OMI Global <inline-formula><mml:math id="M63" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> Data Products (OMSO2e), released by the NASA
Goddard Earth Sciences Data and Information Services Center (Krotkov et al.,
2015). Besides, daily PM<inline-formula><mml:math id="M64" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> was sampled by quartz-fiber filters at an
urban atmosphere environment monitoring station in Peking University
(39.99<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 116.3<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) of Beijing, China, since 2013. The
major water-soluble inorganic compounds (e.g., <inline-formula><mml:math id="M67" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>,
<inline-formula><mml:math id="M68" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M69" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>) were analyzed by ion
chromatography.</p>
</sec>
<?pagebreak page17935?><sec id="Ch1.S2.SS2">
  <title>WRF-Chem simulations</title>
      <p id="d1e1038">In this study, the simulations with the Weather Research and Forecasting Model
coupled with Chemistry (Grell et al., 2005) version 3.6.1 (WRF-Chem) were
conducted for the domain of the North China Plain for the years 2008, 2010, 2012,
2014, 2015, and 2016 (referred to as Run_08–16). We ran the model with a
horizontal resolution of 30 <inline-formula><mml:math id="M70" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 30 km and 24 vertical layers,
extending from the surface to 50 hPa. The initial and boundary
meteorological condition was derived from 6 h National Centers for
Environmental Prediction reanalysis data. The detailed model configurations
were described in our previous study (Huang et al., 2014). The anthropogenic
emissions from power plant, industrial, residential, and vehicle sectors were
taken from the MEIC database. The MEIC data show that the annual
<inline-formula><mml:math id="M71" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in the North China Plain were reduced by about 60 %,
from 9.9 Tg in 2008 to 4.2 Tg in 2016, while <inline-formula><mml:math id="M72" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>
emissions first increased from 8.0 to 8.8 Tg during 2008–2012, and then
decreased to 6.7 Tg in 2016.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <?xmltex \opttitle{NH${}_{{3}}$ emission inventory}?><title>NH<inline-formula><mml:math id="M73" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> emission inventory</title>
      <p id="d1e1086">A high-resolution <inline-formula><mml:math id="M74" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission inventory (1 km <inline-formula><mml:math id="M75" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1 km,
month) was developed based on the bottom-up method. The emission factors were
parameterized with regional farming practices, ambient temperature, soil pH,
and wind speeds. The full details can be found in studies by Kang et
al. (2016), Huang et al. (2012), and Huo et al. (2015). The inventory has
similar spatial features with recent satellite observations (Van Damme et
al., 2014), and its amount is close to the emission estimated by the
inversion model using ammonium wet deposition data (Paulot et al., 2014).
Recent modeling results also showed its good performance by comparing with
ammonium observations in China (Huang et al., 2015). The inventory has
covered the period from 1980 to 2016 and considered the inter-annual
variability in activity levels and agricultural practices. It shows a distinct
seasonal feature in <inline-formula><mml:math id="M76" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions over the North China Plain. A total of
75 % of annual <inline-formula><mml:math id="M77" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions are released in the spring and summer
months (March–September), during which intensive agricultural fertilization
and elevated ambient temperature facilitate the volatilization rates of
<inline-formula><mml:math id="M78" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. Moreover, to integrate this inventory into WRF-Chem
simulations, we adopted a diurnal profile with 80 % of <inline-formula><mml:math id="M79" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
emissions in the daytime, following previous studies (Zhu et al., 2015;
Asman, 2001; Paulot et al., 2016).</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results and discussions</title>
<sec id="Ch1.S3.SS1">
  <?xmltex \opttitle{Trends in emissions and concentrations of NH${}_{{3}}$ vs.
SO${}_{{2}}$}?><title>Trends in emissions and concentrations of NH<inline-formula><mml:math id="M80" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> vs.
SO<inline-formula><mml:math id="M81" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></title>
      <p id="d1e1182">According to the measurements by IASI, the North China Plain showed the
highest VCDs of <inline-formula><mml:math id="M82" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in China, which mostly ranged from 15 to
30 <inline-formula><mml:math id="M83" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M84" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M85" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> during 2008–2014 and
increased to above 30 <inline-formula><mml:math id="M86" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M87" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M88" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in 2015 and
2016 (Fig. S1 in the Supplement). We found the annual <inline-formula><mml:math id="M89" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column
concentrations increased significantly (<italic>p</italic> value &lt; 0.05)
over the North China Plain between 2008 and 2016 (Fig. 1a). The average
tropospheric <inline-formula><mml:math id="M90" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns first fluctuated between 2008 and 2013,
and then rapidly increased from 21 <inline-formula><mml:math id="M91" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M92" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
in 2013 to 27 <inline-formula><mml:math id="M94" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M95" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M96" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in 2016. It showed
an overall increase of 30 %, or an average annual increase of
0.9 <inline-formula><mml:math id="M97" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M98" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yr<inline-formula><mml:math id="M100" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Seasonally, the
increase in <inline-formula><mml:math id="M101" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns was more pronounced in summertime
(June–August, JJA), with an annual increase rate of
1.8 <inline-formula><mml:math id="M102" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M103" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M104" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yr<inline-formula><mml:math id="M105" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> between 2008 and
2016, which was much higher than in other seasons
(&lt; 1 <inline-formula><mml:math id="M106" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M107" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M108" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yr<inline-formula><mml:math id="M109" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><caption><p id="d1e1470"><bold>(a)</bold> Inter-annual trends of <inline-formula><mml:math id="M110" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M111" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
VCDs averaged over the North China Plain from 2008 to 2016.
<bold>(b)</bold> Inter-annual trends of emissions of <inline-formula><mml:math id="M112" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M113" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>,
and <inline-formula><mml:math id="M114" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> in the North China Plain from 2008 to 2016, and
annual mean concentrations of PM<inline-formula><mml:math id="M115" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> sulfate, ammonium, and nitrate
derived from measurements at an urban station (Beijing, 39.99<inline-formula><mml:math id="M116" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
116.3<inline-formula><mml:math id="M117" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) in the North China Plain from 2013 to 2016.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/17933/2018/acp-18-17933-2018-f01.png"/>

        </fig>

      <p id="d1e1567">In contrast to the trends in tropospheric <inline-formula><mml:math id="M118" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations, the
annual <inline-formula><mml:math id="M119" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions first experienced a decreasing tendency from
2008 to 2011 (3.0 Tg in 2009 to 2.8 Tg in 2011) and then remained constant
at around 2.8 Tg yr<inline-formula><mml:math id="M120" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> during 2011–2016 over the North China Plain
(Fig. 1b). The overall trend of <inline-formula><mml:math id="M121" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions demonstrated a
decrease of about 7 %. It is because the changes in mineral fertilizer
use and livestock rearing practices have lowered <inline-formula><mml:math id="M122" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission
rates. The increasing use of urea fertilizer (from 4.7 to 5.2 Tg yr<inline-formula><mml:math id="M123" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and compound fertilizers (from 1.2 to 1.7 Tg yr<inline-formula><mml:math id="M124" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)
but decreased ammonium bicarbonate (from 1.5 to 0.4 Tg yr<inline-formula><mml:math id="M125" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) led to a
20 % reduction in <inline-formula><mml:math id="M126" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions from fertilizer application
during 2008–2016 (Table S1 in the<?pagebreak page17936?> Supplement). On the other hand, the number
of some major livestock increased (beef <inline-formula><mml:math id="M127" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>20 %, dairy <inline-formula><mml:math id="M128" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>39 %, goat
<inline-formula><mml:math id="M129" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>23 %, sheep <inline-formula><mml:math id="M130" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>55 %, pig <inline-formula><mml:math id="M131" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>18 %, and poultry <inline-formula><mml:math id="M132" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>19 %; see
Table S1 in the Supplement for details), while the proportion of intensive animal rearing
systems rises to nearly half of the livestock industry in 2016, compared to
only 28 % in 2008 (Table S1 in the Supplement). The intensive systems are
characterized with more effective livestock manure management in favor of
lower volatilization rates of <inline-formula><mml:math id="M133" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> (Kang et al., 2016). The
transition from the free-range to the intensive system in livestock animal rearing
offsets the effect of increased animals on the <inline-formula><mml:math id="M134" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions,
thereby resulting in the annual livestock emissions in the North China Plain
being almost constant (around 1.2 Tg yr<inline-formula><mml:math id="M135" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). Overall, the decreasing
<inline-formula><mml:math id="M136" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions cannot track the upward trend of tropospheric
<inline-formula><mml:math id="M137" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations.</p>
      <p id="d1e1775">During 2008–2016, <inline-formula><mml:math id="M138" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations were subject to a
dramatic decline (<inline-formula><mml:math id="M139" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> &lt; 0.01) due to a 60 % decrease in
<inline-formula><mml:math id="M140" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions. The annual mean <inline-formula><mml:math id="M141" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> VCDs were reduced from
14 <inline-formula><mml:math id="M142" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M143" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M144" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (2008) to
4 <inline-formula><mml:math id="M145" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M146" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M147" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (2016), showing a percent
reduction of nearly 70 %. Especially during 2012–2016, the decreases in
<inline-formula><mml:math id="M148" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions and VCDs accelerated owing to the implementation of
the Action Plan for Air Pollution Prevention and Control by the Chinese
government (Zheng et al., 2018). The ground measurements in a typical urban
station in the North China Plain indicated that the annual average
<inline-formula><mml:math id="M149" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> concentration in PM<inline-formula><mml:math id="M150" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> decreased by 35 %
(2013–2016) along with rapid <inline-formula><mml:math id="M151" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> reductions, which was accompanied
by a 33 % decrease in particulate <inline-formula><mml:math id="M152" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (Fig. 1b).
Seasonally, the decrease in ground-level <inline-formula><mml:math id="M153" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> reached 60 %
during summertime (JJA), which was much higher than in other seasons.</p>
</sec>
<sec id="Ch1.S3.SS2">
  <?xmltex \opttitle{Simulations of increasing trend in NH${}_{{3}}$ columns}?><title>Simulations of increasing trend in NH<inline-formula><mml:math id="M154" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns</title>
      <p id="d1e1968">We performed numerical simulations with WRF-Chem to interpret the cause of
the <inline-formula><mml:math id="M155" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> increase. We first evaluated model results against
measurements of surface <inline-formula><mml:math id="M156" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations available in the North China
Plain as well as the satellite-retrieved <inline-formula><mml:math id="M157" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns. The simulated
monthly averaged surface <inline-formula><mml:math id="M158" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations at 11 stations (mean
<inline-formula><mml:math id="M159" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> standard deviation: 13.5 <inline-formula><mml:math id="M160" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.8 <inline-formula><mml:math id="M161" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M162" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) generally
agreed with corresponding observations
(13.4 <inline-formula><mml:math id="M163" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 9.7 <inline-formula><mml:math id="M164" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M165" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) with a correlation coefficient of
0.57. More than 70 % of the comparisons differed within a factor of 2
(Fig. 2). Both simulations and observations show high <inline-formula><mml:math id="M166" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
concentrations of about 30 <inline-formula><mml:math id="M167" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M168" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in warm seasons
(March–October) due to enhanced <inline-formula><mml:math id="M169" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> volatilization and frequent
fertilization activities, as well as lower values (mostly
&lt; 15 <inline-formula><mml:math id="M170" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M171" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) in other months (Fig. 3). Spatially,
the hotspot of <inline-formula><mml:math id="M172" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> was mainly concentrated in Hebei, Shandong, and
Henan provinces, which have the most intensive agricultural production in
China and thus emit considerable gas-phase <inline-formula><mml:math id="M173" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> into the atmosphere.
We note that the simulated monthly <inline-formula><mml:math id="M174" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations were
underestimated by 25 %–70 % in several stations in wintertime (January,
February, and December). Recently, <inline-formula><mml:math id="M175" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions from the
residential coal and biomass combustion for heating are considered to be a
potentially important source of <inline-formula><mml:math id="M176" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in suburban and rural areas
during wintertime (Li et al., 2016), but it has not been fully included in
our bottom-up inventory, which was partially responsible for such deviation
between the model and observations.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><caption><p id="d1e2194">Comparison of modeled gaseous <inline-formula><mml:math id="M177" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations with
corresponding monthly measurements of <inline-formula><mml:math id="M178" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> from September 2015 to
August 2016. The <inline-formula><mml:math id="M179" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>:</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M180" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>:</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> dashed lines are shown for reference and the
Pearson correlation coefficient (<inline-formula><mml:math id="M181" display="inline"><mml:mi>r</mml:mi></mml:math></inline-formula>) is shown inset.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/17933/2018/acp-18-17933-2018-f02.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p id="d1e2258">Spatial distribution of modeled ground <inline-formula><mml:math id="M182" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations
(<inline-formula><mml:math id="M183" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M184" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and monthly measurements over the North China Plain from
September 2015 (201509) to August 2016 (201608).</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/17933/2018/acp-18-17933-2018-f03.jpg"/>

        </fig>

      <p id="d1e2298">We calculated the <inline-formula><mml:math id="M185" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> VCDs from the simulations by integrating
<inline-formula><mml:math id="M186" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> molecular concentrations from the surface level to the top of
the troposphere. The results agreed well with the observed <inline-formula><mml:math id="M187" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns
of 2016 on the magnitude and spatiotemporal patterns (Fig. S2 in the
Supplement). Both IASI measurements and the WRF-Chem simulation showed high
annual mean <inline-formula><mml:math id="M188" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations in Hebei, Shandong, and Henan
provinces, reaching above 30 <inline-formula><mml:math id="M189" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M190" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M191" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>.
Moreover, we evaluated the modeled SNA concentrations using the filter-based
PM<inline-formula><mml:math id="M192" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> samples at an urban atmospheric monitoring station in the North China
Plain during 2014–2016 (Fig. S3 in the Supplement). The model generally
reproduced the observed SNA concentrations, with a small annual mean bias for
sulfate (<inline-formula><mml:math id="M193" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>2 %) and ammonium (<inline-formula><mml:math id="M194" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>13 %) and a relatively large bias
for nitrate (<inline-formula><mml:math id="M195" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>24 %). Overall, the model performed well in modeling the
concentrations in tropospheric <inline-formula><mml:math id="M196" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> as well as secondary inorganic
aerosols, which provides high confidence for the following interpretation of
the <inline-formula><mml:math id="M197" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> increases.</p>
      <?pagebreak page17938?><p id="d1e2427">The model successfully reproduced the observed increasing trend in
<inline-formula><mml:math id="M198" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns over the North China Plain during 2008–2016 (Fig. 4).
The modeled <inline-formula><mml:math id="M199" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns were systemically lower than the
measurements because the relative error weighting mean method always biased a
high result due to the smaller relative error in a larger column (Van Damme
et al., 2014; Whitburn et al., 2016). An overall increase of 39 % in
<inline-formula><mml:math id="M200" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns with an average annual increase of
0.8 <inline-formula><mml:math id="M201" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M202" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M203" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yr<inline-formula><mml:math id="M204" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> was found in the
simulations between 2008 and 2016, and meanwhile the <inline-formula><mml:math id="M205" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns
averaged over the North China Plain decreased by approximately 50 % in
this period. These results were close to the measurements.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><caption><p id="d1e2517">Trends in the annual averages of observed and simulated
<inline-formula><mml:math id="M206" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns over the North China Plain. The red stars denote the
simulated <inline-formula><mml:math id="M207" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns under the 2008 <inline-formula><mml:math id="M208" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions levels
(i.e., Run_10_S08 to Run_16_S08).</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/17933/2018/acp-18-17933-2018-f04.png"/>

        </fig>

      <p id="d1e2559">To verify our hypothesis, we replaced <inline-formula><mml:math id="M209" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions during
2010–2016 by those in 2008 and repeated the simulations (referred to as
Run_10_S08 to Run_16_S08). It was noticeable that, under these conditions,
the increasing trend of <inline-formula><mml:math id="M210" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations was not observed,
and even a decrease of 13 % took place (Fig. 4). The largest differences
were found in 2015 and 2016, when the annual <inline-formula><mml:math id="M211" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns in these
sensitivity simulations were about 40 %
(8–10 <inline-formula><mml:math id="M212" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M213" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M214" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) lower than those in the
baseline cases, corresponding to the 60 % reduction in <inline-formula><mml:math id="M215" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
emissions between 2008 and 2016. By comparing the results among Run_08,
Run_16, and Run_16_S08, we found that the reduction in <inline-formula><mml:math id="M216" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
emissions increased the <inline-formula><mml:math id="M217" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations by 52 %
during 2008–2016, which was even higher than the overall increase (39 %)
in the baseline cases. Therefore, we deduce that the rapid <inline-formula><mml:math id="M218" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
emission reductions are responsible for the increased <inline-formula><mml:math id="M219" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> levels
during 2008–2016, while other mechanisms may be negative contributors. More
details on these effects are shown in the following.</p>
</sec>
<sec id="Ch1.S3.SS3">
  <?xmltex \opttitle{Influence of SO${}_{{2}}$ emission reductions on tropospheric
NH${}_{{3}}$ concentrations}?><title>Influence of SO<inline-formula><mml:math id="M220" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> emission reductions on tropospheric
NH<inline-formula><mml:math id="M221" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> concentrations</title>
      <p id="d1e2704">As we indicated above, <inline-formula><mml:math id="M222" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> was observed to be decreasing over
recent years in response to the reductions of <inline-formula><mml:math id="M223" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions. This
was also reproduced by our simulations, which showed that the annual average
sulfate concentrations decreased by almost 50 % in the lower troposphere.
This decreasing trend was especially pronounced after 2013 owing to the very
effective <inline-formula><mml:math id="M224" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions. Given that the vapor pressure of
<inline-formula><mml:math id="M225" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">H</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>(g) is practically zero over atmospheric particles,
atmospheric <inline-formula><mml:math id="M226" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> is predominately in the particle phase and can
combine with <inline-formula><mml:math id="M227" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> available in air, forming sulfate salts (mostly
ammonium sulfate/bisulfate) (Seinfeld and Pandis, 2006). Since the North China
Plain is typically under rich <inline-formula><mml:math id="M228" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> regimes, <inline-formula><mml:math id="M229" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> is
mainly in the form of ammonium sulfate (Meng et al., 2011; Huang et al.,
2017); and the aforementioned <inline-formula><mml:math id="M230" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> reductions would therefore
increase atmospheric <inline-formula><mml:math id="M231" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations by driving the phase state
of <inline-formula><mml:math id="M232" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> from particulate to gaseous.</p>
      <p id="d1e2854">By assuming that a 1 mol decrease in simulated <inline-formula><mml:math id="M233" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> would lead
to a 2 mol increase in ambient gaseous <inline-formula><mml:math id="M234" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in this region, the
average annual increase in the tropospheric <inline-formula><mml:math id="M235" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns due to the
reductions of <inline-formula><mml:math id="M236" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> was estimated to be approximately
1.5 <inline-formula><mml:math id="M237" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M238" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M239" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yr<inline-formula><mml:math id="M240" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> over the North China
Plain during 2008–2016. This is comparable with or higher than the simulated
results from Run_08 to Run_16, as well as the IASI observations
(0.9 <inline-formula><mml:math id="M241" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M242" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M243" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yr<inline-formula><mml:math id="M244" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). By neglecting
the deposition processes, we found that the rapid <inline-formula><mml:math id="M245" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission
reduction of 50 % from 2012 to 2016 resulted in a 55 % increase in
the <inline-formula><mml:math id="M246" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns, compared to that of 30 % recorded by IASI
observations. Overall, the estimation results confirmed that the increasing
trend of <inline-formula><mml:math id="M247" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> was mainly determined by the <inline-formula><mml:math id="M248" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission
reductions.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p id="d1e3039">The differences between Run_08 and Run_16 <bold>(a, b)</bold>, and
between Run_08 and Run_16_S08 <bold>(c, d)</bold>. A–F in <bold>a</bold> denote the Beijing, Tianjin, Hebei,
Shanxi, Shandong, and Henan Provinces, respectively.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/17933/2018/acp-18-17933-2018-f05.png"/>

        </fig>

      <p id="d1e3058">We compared the spatial patterns of decreased <inline-formula><mml:math id="M249" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> and
increased <inline-formula><mml:math id="M250" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> between 2008 and 2016 (Run_08 vs. Run_16). Large
reductions of 6–10 <inline-formula><mml:math id="M251" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M252" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M253" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in annual
averages of sulfate columns were concentrated in Hebei, Shandong, and Henan
provinces, the area subject to high <inline-formula><mml:math id="M254" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> loadings and stringent
emission controls (Fig. 5a). Meanwhile, the simulated increases in
<inline-formula><mml:math id="M255" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns reached more than
8 <inline-formula><mml:math id="M256" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M257" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M258" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in most parts of the North China
Plain (Fig. 5b) and were comparable with those observed by the IASI
(8–16 <inline-formula><mml:math id="M259" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M260" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M261" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). In addition, we found
that <inline-formula><mml:math id="M262" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations have decreased with a similar magnitude
to the increases in gas-phase <inline-formula><mml:math id="M263" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> levels between Run_08 and
Run_16. The proportion of <inline-formula><mml:math id="M264" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in the total
(<inline-formula><mml:math id="M265" display="inline"><mml:mrow><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow><mml:mo>+</mml:mo><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:mrow></mml:math></inline-formula>) increased on average from 26 % in 2008 to 37 % in
2016 over the North China Plain. Figure 5c and d illustrate that, without the large
<inline-formula><mml:math id="M266" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions between 2008 and 2016 (i.e., replacing
<inline-formula><mml:math id="M267" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in 2016 by those in 2008, Run_08 vs. Run_16_S08),
the sulfate columns partly increased. Correspondingly, the <inline-formula><mml:math id="M268" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
columns remained constant or decreased by about
5 <inline-formula><mml:math id="M269" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M270" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M271" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (<inline-formula><mml:math id="M272" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>13 % relative to the
2008 level) in parts of the North China Plain. Thus, the increase in the
tropospheric <inline-formula><mml:math id="M273" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns was the result of a transition in
<inline-formula><mml:math id="M274" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> phase partitioning, which was strongly associated with the
decreased formation of ammonium sulfate due to <inline-formula><mml:math id="M275" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission
reductions.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p id="d1e3358">Seasonal patterns of simulated <inline-formula><mml:math id="M276" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> <bold>(a)</bold> and
<inline-formula><mml:math id="M277" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> <bold>(b)</bold> columns for Run_08, Run_16, and Run_16_S08
(the simulation for 2016 with <inline-formula><mml:math id="M278" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in 2008) cases. MAM,
JJA, SON, and DJF represent spring (March, April, and May), summer (June,
July, and August), autumn (September, October, and November), and winter (December,
January, and February) months.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/17933/2018/acp-18-17933-2018-f06.png"/>

        </fig>

      <?pagebreak page17940?><p id="d1e3411">The seasonal variations in <inline-formula><mml:math id="M279" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> decreases and <inline-formula><mml:math id="M280" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
increases were consistent (Fig. 6). We can see that the reduction of sulfate
column concentrations between the Run_08 and Run_16 reached
1.3 <inline-formula><mml:math id="M281" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M282" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molecules cm<inline-formula><mml:math id="M283" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in summer (JJA), which was
about 3 times larger than in other seasons. The corresponding percent
reductions ranged from 15 % in DJF to 36 % in JJA. As aforementioned,
the observations of PM<inline-formula><mml:math id="M284" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> in Beijing also showed the highest decrease in
sulfate in summer. Considering that the <inline-formula><mml:math id="M285" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions
were uniform throughout the year, this seasonal pattern was likely attributed
to the conversion efficiency of <inline-formula><mml:math id="M286" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> to <inline-formula><mml:math id="M287" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">H</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M288" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>.
Our simulations showed that a 1 mol decrease in <inline-formula><mml:math id="M289" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> corresponded
to an approximately 0.7 mol decrease in particulate sulfate in summer over
the North China Plain, but the values dropped to below 0.4 in other seasons. It
is known that the photochemical oxidation of <inline-formula><mml:math id="M290" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> by OH radical is
most active in summertime due to high atmospheric oxidizing capacity, and it
dominates the formation of <inline-formula><mml:math id="M291" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, which makes the response of
<inline-formula><mml:math id="M292" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations to <inline-formula><mml:math id="M293" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions more
sensitive (Paulot et al., 2017; Huang et al., 2014). The comparison of
modeled <inline-formula><mml:math id="M294" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> columns also showed a markedly higher increase in
summer months than during other seasons, driven by the variations in
<inline-formula><mml:math id="M295" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>. Furthermore, by comparing the model results between the
Run_16 and Run_16_S08 cases, we found that, without considering the
<inline-formula><mml:math id="M296" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions, the seasonal increases in <inline-formula><mml:math id="M297" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
columns and decreases in <inline-formula><mml:math id="M298" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations were not observed.</p>
      <p id="d1e3654">Since the chemical formation of particulate ammonium nitrate also affects the
gas–particle partitioning of <inline-formula><mml:math id="M299" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, the role of
<inline-formula><mml:math id="M300" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions should be discussed. We noted that, unlike
the trend of particulate sulfate in PM<inline-formula><mml:math id="M301" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula>, the simulated concentrations
of particulate nitrate in PM<inline-formula><mml:math id="M302" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> increased on average by 28 % over
the North China Plain between 2008 and 2016, despite a 16 % reduction in
<inline-formula><mml:math id="M303" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions (Fig. S4 in the Supplement). This trend can
be partially explained by the increased <inline-formula><mml:math id="M304" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in the atmosphere that
would facilitate the formation of ammonium nitrate. To quantitatively
understand the effect of <inline-formula><mml:math id="M305" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emission on the trend of
<inline-formula><mml:math id="M306" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, we performed a sensitivity experiment by repeating the
simulation of 2016 with the <inline-formula><mml:math id="M307" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions in 2008
(Run_16_08N). By comparing the results among Run_16, Run_16_08N, and
Run_08, we found that the reduction in <inline-formula><mml:math id="M308" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions
(16 % from 2008 to 2016) decreased the gaseous <inline-formula><mml:math id="M309" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
concentrations by about 3 % (Fig. S5 in the Supplement). Specifically,
because the reduced <inline-formula><mml:math id="M310" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> in this period promoted the
transition of ozone (O<inline-formula><mml:math id="M311" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) photochemistry from a volatile organic compound (VOC)-limited to a transitional
regime with high O<inline-formula><mml:math id="M312" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> production efficiency (Jin and Holloway, 2015), the
simulated annual mean O<inline-formula><mml:math id="M313" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> concentrations were elevated by 3.7 ppb over
the North China Plain between the Run_16_08N and Run_16 cases. The
resultant enhancement in atmospheric oxidizing capacity would favor the
conversion of NO<inline-formula><mml:math id="M314" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> to <inline-formula><mml:math id="M315" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and therefore derive more
<inline-formula><mml:math id="M316" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> partitioning from gaseous to particulate phases via aerosol
thermodynamic equilibrium. Moreover, the measurements at an urban station of
Beijing indicated a fluctuating trend of the annual mean <inline-formula><mml:math id="M317" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>
concentrations during 2013–2016 (Fig. 1). Overall, the limited reduction in
<inline-formula><mml:math id="M318" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions cannot be responsible for the increased
<inline-formula><mml:math id="M319" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, because the concentrations of particulate nitrate has remained high
over the North China Plain during recent years.</p>
      <p id="d1e3883">Besides, meteorological conditions are known to have an influence on
<inline-formula><mml:math id="M320" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations. Both Warner et al. (2017) and Fu et al. (2017)
found that elevated annual surface temperature has partially contributed to
the increase in <inline-formula><mml:math id="M321" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in eastern China over the past decade. In this
work, we tested the effects of meteorological conditions on <inline-formula><mml:math id="M322" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
variations by a simulation with meteorological fields in 2016 and
anthropogenic emissions in 2012 (Run_12_M16). We selected these 2 years
because <inline-formula><mml:math id="M323" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations experienced a rapid increase during the
period. This change in meteorological fields for the Run_12_M16 resulted in
a decrease of about 3 % in annual mean <inline-formula><mml:math id="M324" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations
relative to the Run_12 (Fig. S6 in the Supplement). Therefore, the
inter-annual variability in meteorological conditions cannot explain the
observed significant increase over the North China Plain.</p>
      <p id="d1e3942">Interestingly, increasing trends of gas-phase <inline-formula><mml:math id="M325" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in the atmosphere
have also been observed in the last 20 years in the Midwest of the United
States and Western Europe by satellite retrievals and ground measurements
(Saylor et al., 2015; Warner et al., 2017; Ferm and Hellsten, 2012). The
marked decreases in <inline-formula><mml:math id="M326" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M327" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emissions were
largely responsible for these increases, as confirmed by the corresponding
trends of particulate sulfate and nitrate concentrations. Warner et
al. (2017) infer that <inline-formula><mml:math id="M328" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reduction in China may be a
leading cause of the increased <inline-formula><mml:math id="M329" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. More recently, Yu et al. (2018)
quantified the contributions of the acid gases on the trends of
<inline-formula><mml:math id="M330" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and found that emissions of <inline-formula><mml:math id="M331" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> contributed to
two-thirds and <inline-formula><mml:math id="M332" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> to one-third of the change in <inline-formula><mml:math id="M333" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> over the
United States from 2001 to 2016. In this work, we demonstrate that the rapid
reduction in <inline-formula><mml:math id="M334" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions was responsible for the increase in
<inline-formula><mml:math id="M335" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> over the North China Plain during 2008–2016, while other
potential pathways (<inline-formula><mml:math id="M336" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions, <inline-formula><mml:math id="M337" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>
emissions, and meteorological conditions) decreased its concentrations by
approximately 13 % for this period.</p>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <title>Conclusion</title>
      <?pagebreak page17941?><p id="d1e4098">By integrating chemical model simulations and ground and satellite
observations, this study investigates an increase (<inline-formula><mml:math id="M338" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 30 %) in
tropospheric <inline-formula><mml:math id="M339" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column concentrations that was observed from
the space over the North China Plain during 2008–2016. First, the long-term
<inline-formula><mml:math id="M340" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission inventory presents a decreasing tendency of <inline-formula><mml:math id="M341" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>7 %
in the emission, and therefore it cannot explain the <inline-formula><mml:math id="M342" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> increase.
The meteorological variations and the change in <inline-formula><mml:math id="M343" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>
emissions in the study period decreased the <inline-formula><mml:math id="M344" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column
concentrations both by about 3 %. Our work strongly indicates that the
rapid <inline-formula><mml:math id="M345" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions (60 %) from 2008 to 2016 were
responsible for the <inline-formula><mml:math id="M346" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> increase. The multi-year WRF-Chem
simulations capture the increasing trend of <inline-formula><mml:math id="M347" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and decreasing
trend of particulate sulfate well. Simulation results demonstrate that the
<inline-formula><mml:math id="M348" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission reductions decreased the regional mean
<inline-formula><mml:math id="M349" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations by about 50 % in the lower troposphere,
which reduced the formation of ammonium sulfate particles and consequently
increased the average proportions of gas-phase <inline-formula><mml:math id="M350" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> from
26 % (2008) to 37 % (2016) within the total <inline-formula><mml:math id="M351" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> column
concentrations. The sensitivity simulations by fixing <inline-formula><mml:math id="M352" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions
of 2008 show that, without the reductions in <inline-formula><mml:math id="M353" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions, the
increase in <inline-formula><mml:math id="M354" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> is not observed during 2008–2016, and even a
decrease of 13 % takes place, which is associated with the effects of
other mechanisms (<inline-formula><mml:math id="M355" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions, <inline-formula><mml:math id="M356" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emission,
and meteorology). Seasonally, both simulation and observations show the
highest decrease in sulfate concentrations, making the increasing trend of
<inline-formula><mml:math id="M357" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> more pronounced in this season. This is likely due to a more
sensitive response of sulfate concentrations to <inline-formula><mml:math id="M358" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission
reductions in summer than in other seasons.</p>
      <p id="d1e4332">Given the ongoing stringent controls on <inline-formula><mml:math id="M359" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in China, a
continued increase in <inline-formula><mml:math id="M360" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations is anticipated if
<inline-formula><mml:math id="M361" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions are not regulated. The increased tropospheric
<inline-formula><mml:math id="M362" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> levels may have a significant impact on air pollution and
nitrogen deposition in China. For instance, the elevated <inline-formula><mml:math id="M363" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> would
facilitate ammonium nitrate formation based on the aerosol thermodynamic
equilibrium and negatively impact PM<inline-formula><mml:math id="M364" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> control. That is supported by
the fact that <inline-formula><mml:math id="M365" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations remain high in northern China
and have become increasingly important in contributing to PM<inline-formula><mml:math id="M366" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula>
pollution (Wen et al., 2018; Li et al., 2018), despite a moderate
<inline-formula><mml:math id="M367" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> emission reduction. The increased proportion of
gas-phase <inline-formula><mml:math id="M368" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> within the total can increase ammonium–nitrogen
deposition since gas-phase ammonia deposits more rapidly than particle
ammonium. This may alter the spatial pattern of regional nitrogen deposition
with higher levels of <inline-formula><mml:math id="M369" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> deposited near emission sources. These
effects are important for human and ecosystem health and need to be
investigated in future studies.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability">

      <p id="d1e4459"><inline-formula><mml:math id="M370" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> vertical column density data are freely
available through the AERIS database: <uri>http://iasi.aeris-data.fr/NH_3/</uri>
(last access: 13 September 2017) (Whitburn et al., 2017). The <inline-formula><mml:math id="M371" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
vertical column density retrieved from the Ozone Monitoring Instrument is
available from the Level-3 Aura/OMI Global <inline-formula><mml:math id="M372" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> Data Products
(OMSO2e) released by the NASA Goddard Earth Sciences Data and Information
Service Center (<uri>https://disc.sci.gsfc.nasa.gov/</uri> (last access: 1 March
2018) (Krotkov et al., 2015). Anthropogenic emissions in industry, power
plants, transportation, and residential sectors are obtained from the
Multi-resolution Emission Inventory for China (MEIC,
<uri>http://www.meicmodel.org/</uri>, last access: 15 May 2018) (Zheng et al.,
2018). The PKU-<inline-formula><mml:math id="M373" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission inventory is freely available from the
corresponding author Yu Song (songyu@pku.edu.cn) upon reasonable request.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e4515">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-18-17933-2018-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-18-17933-2018-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution">

      <p id="d1e4524">YS, MH, and TZ designed the study. ZW and MH
conducted measurements of aerosol chemical compositions. YP conducted
measurements of gas-phase ammonia concentrations. QZ developed the MEIC
emission database. ML, XH, and XL contributed to the development of the ammonia
emission inventory. ML, XH, YS, TX, SW, LZ, and TZ analyzed the data. ML led the
writing with input from all co-authors.</p>
  </notes><notes notes-type="competinginterests">

      <p id="d1e4530">The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e4536">This study was funded by the National Key R&amp;D
Program of China (2016YFC0201505), National Natural Science Foundation of
China (NSFC) (91644212 and 41675142), and National Research Program for Key
Issues in Air Pollution Control (DQGG0208).<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited by:
Marc von Hobe <?xmltex \hack{\newline}?>
Reviewed by: two anonymous referees</p></ack><ref-list>
    <title>References</title>

      <ref id="bib1.bib1"><label>1</label><mixed-citation>Asman, W. A. H.: Modelling the atmospheric transport and deposition of
ammonia and ammonium: an overview with special reference to Denmark, Atmos.
Environ., 35, 1969–1983, <ext-link xlink:href="https://doi.org/10.1016/S1352-2310(00)00548-3" ext-link-type="DOI">10.1016/S1352-2310(00)00548-3</ext-link>, 2001.</mixed-citation></ref>
      <ref id="bib1.bib2"><label>2</label><mixed-citation>Asman, W. A. H., Sutton, M. A., and Schjørring, J. K.: Ammonia: emission,
atmospheric transport and deposition, New Phytol., 139, 27–48,
<ext-link xlink:href="https://doi.org/10.1046/j.1469-8137.1998.00180.x" ext-link-type="DOI">10.1046/j.1469-8137.1998.00180.x</ext-link>, 1998.</mixed-citation></ref>
      <ref id="bib1.bib3"><label>3</label><mixed-citation>Behera, S. N., Sharma, M., Aneja, V. P., and Balasubramanian, R.: Ammonia in
the atmosphere: a review on emission sources, atmospheric chemistry and
deposition on terrestrial bodies, Environ. Sci. Pollut. Res. Int., 20,
8092–8131, <ext-link xlink:href="https://doi.org/10.1007/s11356-013-2051-9" ext-link-type="DOI">10.1007/s11356-013-2051-9</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib4"><label>4</label><mixed-citation>Bouwman, A. F., Lee, D. S., Asman, W. A. H., Dentener, F. J., Van Der Hoek,
K. W., and Olivier, J. G. J.: A global high-resolution emission inventory
for ammonia, Global Biogeochem. Cy., 11, 561–587, <ext-link xlink:href="https://doi.org/10.1029/97gb02266" ext-link-type="DOI">10.1029/97gb02266</ext-link>, 1997.</mixed-citation></ref>
      <ref id="bib1.bib5"><label>5</label><mixed-citation>Clarisse, L., Clerbaux, C., Dentener, F., Hurtmans, D., and Coheur, P.-F.:
Global ammonia distribution derived from infrared satellite observations,
Nat. Geosci., 2, 479–483, <ext-link xlink:href="https://doi.org/10.1038/ngeo551" ext-link-type="DOI">10.1038/ngeo551</ext-link>, 2009.</mixed-citation></ref>
      <?pagebreak page17942?><ref id="bib1.bib6"><label>6</label><mixed-citation>Ferm, M. and Hellsten, S.: Trends in atmospheric ammonia and particulate
ammonium concentrations in Sweden and its causes, Atmos. Environ., 61,
30–39, <ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2012.07.010" ext-link-type="DOI">10.1016/j.atmosenv.2012.07.010</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib7"><label>7</label><mixed-citation>Fu, X., Wang, S., Xing, J., Zhang, X., Wang, T., and Hao, J.: Increasing
Ammonia Concentrations Reduce the Effectiveness of Particle Pollution
Control Achieved via <inline-formula><mml:math id="M374" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and NOX Emissions Reduction in East China, Environ. Sci. Tech. Lett., 4, 221–227, <ext-link xlink:href="https://doi.org/10.1021/acs.estlett.7b00143" ext-link-type="DOI">10.1021/acs.estlett.7b00143</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib8"><label>8</label><mixed-citation>Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G.,
Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within
the WRF model, Atmos. Environ., 39, 6957–6975,
<ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2005.04.027" ext-link-type="DOI">10.1016/j.atmosenv.2005.04.027</ext-link>, 2005.</mixed-citation></ref>
      <ref id="bib1.bib9"><label>9</label><mixed-citation>Huang, X., Song, Y., Li, M., Li, J., Huo, Q., Cai, X., Zhu, T., Hu, M., and
Zhang, H.: A high-resolution ammonia emission inventory in China, Global
Biogeochem. Cy., 26, GB1030, <ext-link xlink:href="https://doi.org/10.1029/2011GB004161" ext-link-type="DOI">10.1029/2011GB004161</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib10"><label>10</label><mixed-citation>Huang, X., Song, Y., Zhao, C., Li, M., Zhu, T., Zhang, Q., and Zhang, X.:
Pathways of sulfate enhancement by natural and anthropogenic mineral
aerosols in China, J. Geophys. Res.-Atmos., 119, 14165–14179,
<ext-link xlink:href="https://doi.org/10.1002/2014JD022301" ext-link-type="DOI">10.1002/2014JD022301</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib11"><label>11</label><mixed-citation>Huang, X., Song, Y., Zhao, C., Cai, X., Zhang, H., and Zhu, T.: Direct
Radiative Effect by Multicomponent Aerosol over China, J. Climate, 28,
3472–3495, <ext-link xlink:href="https://doi.org/10.1175/JCLI-D-14-00365.1" ext-link-type="DOI">10.1175/JCLI-D-14-00365.1</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib12"><label>12</label><mixed-citation>Huang, X., Liu, Z., Liu, J., Hu, B., Wen, T., Tang, G., Zhang, J., Wu, F.,
Ji, D., Wang, L., and Wang, Y.: Chemical characterization and source
identification of PM<inline-formula><mml:math id="M375" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> at multiple sites in the Beijing–Tianjin–Hebei
region, China, Atmos. Chem. Phys., 17, 12941–12962,
10.5194/acp-17-12941-2017, 2017.</mixed-citation></ref>
      <ref id="bib1.bib13"><label>13</label><mixed-citation>Huo, Q., Cai, X., Kang, L., Zhang, H., Song, Y., and Zhu, T.: Estimating
ammonia emissions from a winter wheat cropland in North China Plain with
field experiments and inverse dispersion modeling, Atmos. Environ., 104,
1–10, <ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2015.01.003" ext-link-type="DOI">10.1016/j.atmosenv.2015.01.003</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib14"><label>14</label><mixed-citation>Jin, X. and Holloway, T.: Spatial and temporal variability of ozone
sensitivity over China observed from the Ozone Monitoring Instrument, J.
Geophys. Res.-Atmos., 120, 7229–7246, <ext-link xlink:href="https://doi.org/10.1002/2015JD023250" ext-link-type="DOI">10.1002/2015JD023250</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib15"><label>15</label><mixed-citation>Kang, Y., Liu, M., Song, Y., Huang, X., Yao, H., Cai, X., Zhang, H., Kang,
L., Liu, X., Yan, X., He, H., Zhang, Q., Shao, M., and Zhu, T.:
High-resolution ammonia emissions inventories in China from 1980 to 2012,
Atmos. Chem. Phys., 16, 2043–2058, <ext-link xlink:href="https://doi.org/10.5194/acp-16-2043-2016" ext-link-type="DOI">10.5194/acp-16-2043-2016</ext-link>,
2016.</mixed-citation></ref>
      <ref id="bib1.bib16"><label>16</label><mixed-citation>Krotkov, N. A., Li, C., and Leonard, P.: OMI/Aura Sulfur Dioxide
(<inline-formula><mml:math id="M376" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) Total Column L3 1 day Best Pixel in 0.25 degree <inline-formula><mml:math id="M377" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.25
degree V3, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information
Services Center (GES DISC), available at:
<uri>https://disc.sci.gsfc.nasa.gov/</uri> (last access: 1 March 2018),
<ext-link xlink:href="https://doi.org/10.5067/Aura/OMI/DATA3008" ext-link-type="DOI">10.5067/Aura/OMI/DATA3008</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib17"><label>17</label><mixed-citation>Li, C., Zhang, Q., Krotkov, N. A., Streets, D. G., He, K., Tsay, S.-C., and
Gleason, J. F.: Recent large reduction in sulfur dioxide emissions from
Chinese power plants observed by the Ozone Monitoring Instrument, Geophys.
Res. Lett., 37, L08807, <ext-link xlink:href="https://doi.org/10.1029/2010gl042594" ext-link-type="DOI">10.1029/2010gl042594</ext-link>, 2010.</mixed-citation></ref>
      <ref id="bib1.bib18"><label>18</label><mixed-citation>Li, C., McLinden, C., Fioletov, V., Krotkov, N., Carn, S., Joiner, J.,
Streets, D., He, H., Ren, X., Li, Z., and Dickerson, R. R.: India Is
Overtaking China as the World's Largest Emitter of Anthropogenic Sulfur
Dioxide, Sci. Rep., 7, 14304, <ext-link xlink:href="https://doi.org/10.1038/s41598-017-14639-8" ext-link-type="DOI">10.1038/s41598-017-14639-8</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib19"><label>19</label><mixed-citation>Li, H., Zhang, Q., Zheng, B., Chen, C., Wu, N., Guo, H., Zhang, Y., Zheng,
Y., Li, X., and He, K.: Nitrate-driven urban haze pollution during summertime
over the North China Plain, Atmos. Chem. Phys., 18, 5293–5306,
<ext-link xlink:href="https://doi.org/10.5194/acp-18-5293-2018" ext-link-type="DOI">10.5194/acp-18-5293-2018</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib20"><label>20</label><mixed-citation>Li, Q., Jiang, J., Cai, S., Zhou, W., Wang, S., Duan, L., and Hao, J.:
Gaseous Ammonia Emissions from Coal and Biomass Combustion in Household
Stoves with Different Combustion Efficiencies, Environ. Sci. Tech. Lett.,
3, 98–103, <ext-link xlink:href="https://doi.org/10.1021/acs.estlett.6b00013" ext-link-type="DOI">10.1021/acs.estlett.6b00013</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib21"><label>21</label><mixed-citation>Liu, F., Zhang, Q., van der A, R. J., Zheng, B., Tong, D., Yan, L., Zheng,
Y., and He, K.: Recent reduction in NOx emissions over China: synthesis of
satellite observations and emission inventories, Environ. Res. Lett., 11,
114002, <ext-link xlink:href="https://doi.org/10.1088/1748-9326/11/11/114002" ext-link-type="DOI">10.1088/1748-9326/11/11/114002</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib22"><label>22</label><mixed-citation>Lu, Z., Zhang, Q., and Streets, D. G.: Sulfur dioxide and primary
carbonaceous aerosol emissions in China and India, 1996–2010, Atmos. Chem.
Phys., 11, 9839–9864, <ext-link xlink:href="https://doi.org/10.5194/acp-11-9839-2011" ext-link-type="DOI">10.5194/acp-11-9839-2011</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib23"><label>23</label><mixed-citation>Meng, Z. Y., Lin, W. L., Jiang, X. M., Yan, P., Wang, Y., Zhang, Y. M., Jia,
X. F., and Yu, X. L.: Characteristics of atmospheric ammonia over Beijing,
China, Atmos. Chem. Phys., 11, 6139–6151,
<ext-link xlink:href="https://doi.org/10.5194/acp-11-6139-2011" ext-link-type="DOI">10.5194/acp-11-6139-2011</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib24"><label>24</label><mixed-citation>Pan, Y., Tian, S., Zhao, Y., Zhang, L., Zhu, X., Gao, J., Huang, W., Zhou,
Y., Song, Y., Zhang, Q., and Wang, Y.: Identifying Ammonia Hotspots in China
Using a National Observation Network, Environ. Sci. Technol., 52, 3926–3934,
<ext-link xlink:href="https://doi.org/10.1021/acs.est.7b05235" ext-link-type="DOI">10.1021/acs.est.7b05235</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib25"><label>25</label><mixed-citation>Paulot, F., Jacob, D. J., Pinder, R. W., Bash, J. O., Travis, K., and Henze,
D. K.: Ammonia emissions in the United States, European Union, and China
derived by high-resolution inversion of ammonium wet deposition data:
Interpretation with a new agricultural emissions inventory (MASAGE_<inline-formula><mml:math id="M378" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>), J.
Geophys. Res.-Atmos., 119, 4343–4364, <ext-link xlink:href="https://doi.org/10.1002/2013jd021130" ext-link-type="DOI">10.1002/2013jd021130</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib26"><label>26</label><mixed-citation>Paulot, F., Ginoux, P., Cooke, W. F., Donner, L. J., Fan, S., Lin, M.-Y.,
Mao, J., Naik, V., and Horowitz, L. W.: Sensitivity of nitrate aerosols to
ammonia emissions and to nitrate chemistry: implications for present and
future nitrate optical depth, Atmos. Chem. Phys., 16, 1459–1477,
<ext-link xlink:href="https://doi.org/10.5194/acp-16-1459-2016" ext-link-type="DOI">10.5194/acp-16-1459-2016</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib27"><label>27</label><mixed-citation>Paulot, F., Fan, S., and Horowitz, L. W.: Contrasting seasonal responses of
sulfate aerosols to declining <inline-formula><mml:math id="M379" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions in the Eastern U.S.: Implications
for the efficacy of <inline-formula><mml:math id="M380" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission controls, Geophys. Res. Lett., 44, 455–464,
<ext-link xlink:href="https://doi.org/10.1002/2016gl070695" ext-link-type="DOI">10.1002/2016gl070695</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib28"><label>28</label><mixed-citation>Pope, C. A. I., Ezzati, M., and Dockery , D. W.: Fine-Particulate Air
Pollution and Life Expectancy in the United States, N. Engl. J. Med., 360,
376–386, <ext-link xlink:href="https://doi.org/10.1056/NEJMsa0805646" ext-link-type="DOI">10.1056/NEJMsa0805646</ext-link>, 2009.</mixed-citation></ref>
      <ref id="bib1.bib29"><label>29</label><mixed-citation>Pozzer, A., Tsimpidi, A. P., Karydis, V. A., de Meij, A., and Lelieveld, J.:
Impact of agricultural emission reductions on fine-particulate matter and
public health, Atmos. Chem. Phys., 17, 12813–12826,
<ext-link xlink:href="https://doi.org/10.5194/acp-17-12813-2017" ext-link-type="DOI">10.5194/acp-17-12813-2017</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib30"><label>30</label><mixed-citation>Saylor, R., Myles, L., Sibble, D., Caldwell, J., and Xing, J.: Recent trends
in gas-phase ammonia and PM<inline-formula><mml:math id="M381" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> ammonium in the Southeast United States, J.
Air Waste Manag. Assoc., 65, 347–357, <ext-link xlink:href="https://doi.org/10.1080/10962247.2014.992554" ext-link-type="DOI">10.1080/10962247.2014.992554</ext-link>,
2015.</mixed-citation></ref>
      <?pagebreak page17943?><ref id="bib1.bib31"><label>31</label><mixed-citation>
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From
Air Pollution to Climate Change, 2nd ed., John Wiley &amp; Sons, Hoboken, New
Jersey, USA, 2006.</mixed-citation></ref>
      <ref id="bib1.bib32"><label>32</label><mixed-citation>Van Damme, M., Clarisse, L., Heald, C. L., Hurtmans, D., Ngadi, Y., Clerbaux,
C., Dolman, A. J., Erisman, J. W., and Coheur, P. F.: Global distributions,
time series and error characterization of atmospheric ammonia (<inline-formula><mml:math id="M382" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>)
from IASI satellite observations, Atmos. Chem. Phys., 14, 2905–2922,
<ext-link xlink:href="https://doi.org/10.5194/acp-14-2905-2014" ext-link-type="DOI">10.5194/acp-14-2905-2014</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib33"><label>33</label><mixed-citation>Van Damme, M., Clarisse, L., Dammers, E., Liu, X., Nowak, J. B., Clerbaux,
C., Flechard, C. R., Galy-Lacaux, C., Xu, W., Neuman, J. A., Tang, Y. S.,
Sutton, M. A., Erisman, J. W., and Coheur, P. F.: Towards validation of
ammonia (<inline-formula><mml:math id="M383" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) measurements from the IASI satellite, Atmos. Meas.
Tech., 8, 1575–1591, <ext-link xlink:href="https://doi.org/10.5194/amt-8-1575-2015" ext-link-type="DOI">10.5194/amt-8-1575-2015</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib34"><label>34</label><mixed-citation>Van Damme, M., Whitburn, S., Clarisse, L., Clerbaux, C., Hurtmans, D., and
Coheur, P.-F.: Version 2 of the IASI <inline-formula><mml:math id="M384" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> neural network retrieval algorithm:
near-real-time and reanalysed datasets, Atmos. Meas. Tech., 10, 4905–4914,
<ext-link xlink:href="https://doi.org/10.5194/amt-10-4905-2017" ext-link-type="DOI">10.5194/amt-10-4905-2017</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib35"><label>35</label><mixed-citation>Warner, J. X., Dickerson, R. R., Wei, Z., Strow, L. L., Wang, Y., and Liang,
Q.: Increased atmospheric ammonia over the world's major agricultural areas
detected from space, Geophys. Res. Lett., 44, 2875–2884,
<ext-link xlink:href="https://doi.org/10.1002/2016gl072305" ext-link-type="DOI">10.1002/2016gl072305</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib36"><label>36</label><mixed-citation>Wen, L., Xue, L., Wang, X., Xu, C., Chen, T., Yang, L., Wang, T., Zhang, Q.,
and Wang, W.: Summertime fine particulate nitrate pollution in the North
China Plain: increasing trends, formation mechanisms and implications for
control policy, Atmos. Chem. Phys., 18, 11261–11275,
<ext-link xlink:href="https://doi.org/10.5194/acp-18-11261-2018" ext-link-type="DOI">10.5194/acp-18-11261-2018</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib37"><label>37</label><mixed-citation>Whitburn, S., Van Damme, M., Clarisse, L., Bauduin, S., Heald, C. L.,
Hadji-Lazaro, J., Hurtmans, D., Zondlo, M. A., Clerbaux, C., and Coheur, P.
F.: A flexible and robust neural network IASI-<inline-formula><mml:math id="M385" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> retrieval
algorithm, J. Geophys. Res.-Atmos., 121, 6581-6599, <ext-link xlink:href="https://doi.org/10.1002/2016jd024828" ext-link-type="DOI">10.1002/2016jd024828</ext-link>,
2016.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib38"><label>38</label><mixed-citation>Whitburn, S., Clarisse, L., Van Damme, M., and Coheur, P.-F.: Ammonia total
columns retrieved from IASI measurements, Greenbelt, Universite Libre de
Bruxelles (ULB)/Laboratoire atmosphères, milieux et observations spatiales
(LATMOS), available at: <uri>https://iasi.aeris-data.fr/nh3/</uri> (last access:
13 September 2017), 2017.</mixed-citation></ref>
      <ref id="bib1.bib39"><label>39</label><mixed-citation>Yu, F., Nair, A. A., and Luo, G.: Long-term trend of gaseous ammonia over the
United States: Modeling and comparison with observations, J. Geophys.
Res.-Atmos., 123, 8315–8325, <ext-link xlink:href="https://doi.org/10.1029/2018JD028412" ext-link-type="DOI">10.1029/2018JD028412</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib40"><label>40</label><mixed-citation>Zhang, L., Chen, Y., Zhao, Y., Henze, D. K., Zhu, L., Song, Y., Paulot, F.,
Liu, X., Pan, Y., Lin, Y., and Huang, B.: Agricultural ammonia emissions in
China: reconciling bottom-up and top-down estimates, Atmos. Chem. Phys., 18,
339–355, <ext-link xlink:href="https://doi.org/10.5194/acp-18-339-2018" ext-link-type="DOI">10.5194/acp-18-339-2018</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib41"><label>41</label><mixed-citation>Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X.,
Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang,
Q.: Trends in China's anthropogenic emissions since 2010 as the consequence
of clean air actions, Atmos. Chem. Phys., 18, 14095–14111,
<ext-link xlink:href="https://doi.org/10.5194/acp-18-14095-2018" ext-link-type="DOI">10.5194/acp-18-14095-2018</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib42"><label>42</label><mixed-citation>Zhu, L., Henze, D., Bash, J., Jeong, G.-R., Cady-Pereira, K., Shephard, M.,
Luo, M., Paulot, F., and Capps, S.: Global evaluation of ammonia
bidirectional exchange and livestock diurnal variation schemes, Atmos. Chem.
Phys., 15, 12823–12843, <ext-link xlink:href="https://doi.org/10.5194/acp-15-12823-2015" ext-link-type="DOI">10.5194/acp-15-12823-2015</ext-link>, 2015.</mixed-citation></ref>

  </ref-list></back>
    <!--<article-title-html>Rapid SO<sub>2</sub> emission reductions significantly increase tropospheric ammonia concentrations over the North China Plain</article-title-html>
<abstract-html><p>The North China Plain has been identified as a significant hotspot of ammonia
(NH<sub>3</sub>) due to extensive agricultural activities. Satellite
observations suggest a significant increase of about 30&thinsp;% in tropospheric
gas-phase NH<sub>3</sub> concentrations in this area during 2008–2016.
However, the estimated NH<sub>3</sub> emissions decreased slightly by 7&thinsp;%
because of changes in Chinese agricultural practices, i.e., the transition in
fertilizer types from ammonium carbonate fertilizer to urea, and in the
livestock rearing system from free-range to intensive farming. We note that
the emissions of sulfur dioxide (SO<sub>2</sub>) have rapidly declined by
about 60&thinsp;% over the recent few years. By integrating measurements from
ground and satellite, a long-term anthropogenic NH<sub>3</sub> emission
inventory, and chemical transport model simulations, we find that this large
SO<sub>2</sub> emission reduction is responsible for the NH<sub>3</sub>
increase over the North China Plain. The simulations for the period
2008–2016 demonstrate that the annual average sulfate concentrations
decreased by about 50&thinsp;%, which significantly weakens the formation of
ammonium sulfate and increases the average proportions of gas-phase
NH<sub>3</sub> within the total NH<sub>3</sub> column concentrations from
26&thinsp;% (2008) to 37&thinsp;% (2016). By fixing SO<sub>2</sub> emissions of 2008
in those multi-year simulations, the increasing trend of the tropospheric
NH<sub>3</sub> concentrations is not observed. Both the decreases in sulfate
and increases in NH<sub>3</sub> concentrations show highest values in summer,
possibly because the formation of sulfate aerosols is more sensitive to
SO<sub>2</sub> emission reductions in summer than in other seasons. Besides,
the changes in NO<sub><i>x</i></sub> emissions and meteorological conditions
both decreased the NH<sub>3</sub> column concentrations by about 3&thinsp;% in
the study period. Our simulations suggest that the moderate reduction in
NO<sub><i>x</i></sub> emissions (16&thinsp;%) favors the formation of
particulate nitrate by elevating ozone concentrations in the lower
troposphere.</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Asman, W. A. H.: Modelling the atmospheric transport and deposition of
ammonia and ammonium: an overview with special reference to Denmark, Atmos.
Environ., 35, 1969–1983, <a href="https://doi.org/10.1016/S1352-2310(00)00548-3" target="_blank">https://doi.org/10.1016/S1352-2310(00)00548-3</a>, 2001.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Asman, W. A. H., Sutton, M. A., and Schjørring, J. K.: Ammonia: emission,
atmospheric transport and deposition, New Phytol., 139, 27–48,
<a href="https://doi.org/10.1046/j.1469-8137.1998.00180.x" target="_blank">https://doi.org/10.1046/j.1469-8137.1998.00180.x</a>, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Behera, S. N., Sharma, M., Aneja, V. P., and Balasubramanian, R.: Ammonia in
the atmosphere: a review on emission sources, atmospheric chemistry and
deposition on terrestrial bodies, Environ. Sci. Pollut. Res. Int., 20,
8092–8131, <a href="https://doi.org/10.1007/s11356-013-2051-9" target="_blank">https://doi.org/10.1007/s11356-013-2051-9</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
Bouwman, A. F., Lee, D. S., Asman, W. A. H., Dentener, F. J., Van Der Hoek,
K. W., and Olivier, J. G. J.: A global high-resolution emission inventory
for ammonia, Global Biogeochem. Cy., 11, 561–587, <a href="https://doi.org/10.1029/97gb02266" target="_blank">https://doi.org/10.1029/97gb02266</a>, 1997.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Clarisse, L., Clerbaux, C., Dentener, F., Hurtmans, D., and Coheur, P.-F.:
Global ammonia distribution derived from infrared satellite observations,
Nat. Geosci., 2, 479–483, <a href="https://doi.org/10.1038/ngeo551" target="_blank">https://doi.org/10.1038/ngeo551</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
Ferm, M. and Hellsten, S.: Trends in atmospheric ammonia and particulate
ammonium concentrations in Sweden and its causes, Atmos. Environ., 61,
30–39, <a href="https://doi.org/10.1016/j.atmosenv.2012.07.010" target="_blank">https://doi.org/10.1016/j.atmosenv.2012.07.010</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
Fu, X., Wang, S., Xing, J., Zhang, X., Wang, T., and Hao, J.: Increasing
Ammonia Concentrations Reduce the Effectiveness of Particle Pollution
Control Achieved via SO<sub>2</sub> and NOX Emissions Reduction in East China, Environ. Sci. Tech. Lett., 4, 221–227, <a href="https://doi.org/10.1021/acs.estlett.7b00143" target="_blank">https://doi.org/10.1021/acs.estlett.7b00143</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G.,
Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within
the WRF model, Atmos. Environ., 39, 6957–6975,
<a href="https://doi.org/10.1016/j.atmosenv.2005.04.027" target="_blank">https://doi.org/10.1016/j.atmosenv.2005.04.027</a>, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
Huang, X., Song, Y., Li, M., Li, J., Huo, Q., Cai, X., Zhu, T., Hu, M., and
Zhang, H.: A high-resolution ammonia emission inventory in China, Global
Biogeochem. Cy., 26, GB1030, <a href="https://doi.org/10.1029/2011GB004161" target="_blank">https://doi.org/10.1029/2011GB004161</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
Huang, X., Song, Y., Zhao, C., Li, M., Zhu, T., Zhang, Q., and Zhang, X.:
Pathways of sulfate enhancement by natural and anthropogenic mineral
aerosols in China, J. Geophys. Res.-Atmos., 119, 14165–14179,
<a href="https://doi.org/10.1002/2014JD022301" target="_blank">https://doi.org/10.1002/2014JD022301</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
Huang, X., Song, Y., Zhao, C., Cai, X., Zhang, H., and Zhu, T.: Direct
Radiative Effect by Multicomponent Aerosol over China, J. Climate, 28,
3472–3495, <a href="https://doi.org/10.1175/JCLI-D-14-00365.1" target="_blank">https://doi.org/10.1175/JCLI-D-14-00365.1</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
Huang, X., Liu, Z., Liu, J., Hu, B., Wen, T., Tang, G., Zhang, J., Wu, F.,
Ji, D., Wang, L., and Wang, Y.: Chemical characterization and source
identification of PM<sub>2.5</sub> at multiple sites in the Beijing–Tianjin–Hebei
region, China, Atmos. Chem. Phys., 17, 12941–12962,
10.5194/acp-17-12941-2017, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
Huo, Q., Cai, X., Kang, L., Zhang, H., Song, Y., and Zhu, T.: Estimating
ammonia emissions from a winter wheat cropland in North China Plain with
field experiments and inverse dispersion modeling, Atmos. Environ., 104,
1–10, <a href="https://doi.org/10.1016/j.atmosenv.2015.01.003" target="_blank">https://doi.org/10.1016/j.atmosenv.2015.01.003</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
Jin, X. and Holloway, T.: Spatial and temporal variability of ozone
sensitivity over China observed from the Ozone Monitoring Instrument, J.
Geophys. Res.-Atmos., 120, 7229–7246, <a href="https://doi.org/10.1002/2015JD023250" target="_blank">https://doi.org/10.1002/2015JD023250</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>15</label><mixed-citation>
Kang, Y., Liu, M., Song, Y., Huang, X., Yao, H., Cai, X., Zhang, H., Kang,
L., Liu, X., Yan, X., He, H., Zhang, Q., Shao, M., and Zhu, T.:
High-resolution ammonia emissions inventories in China from 1980 to 2012,
Atmos. Chem. Phys., 16, 2043–2058, <a href="https://doi.org/10.5194/acp-16-2043-2016" target="_blank">https://doi.org/10.5194/acp-16-2043-2016</a>,
2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>16</label><mixed-citation>
Krotkov, N. A., Li, C., and Leonard, P.: OMI/Aura Sulfur Dioxide
(SO<sub>2</sub>) Total Column L3 1 day Best Pixel in 0.25 degree  ×  0.25
degree V3, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information
Services Center (GES DISC), available at:
<a href="https://disc.sci.gsfc.nasa.gov/" target="_blank">https://disc.sci.gsfc.nasa.gov/</a> (last access: 1 March 2018),
<a href="https://doi.org/10.5067/Aura/OMI/DATA3008" target="_blank">https://doi.org/10.5067/Aura/OMI/DATA3008</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>17</label><mixed-citation>
Li, C., Zhang, Q., Krotkov, N. A., Streets, D. G., He, K., Tsay, S.-C., and
Gleason, J. F.: Recent large reduction in sulfur dioxide emissions from
Chinese power plants observed by the Ozone Monitoring Instrument, Geophys.
Res. Lett., 37, L08807, <a href="https://doi.org/10.1029/2010gl042594" target="_blank">https://doi.org/10.1029/2010gl042594</a>, 2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>18</label><mixed-citation>
Li, C., McLinden, C., Fioletov, V., Krotkov, N., Carn, S., Joiner, J.,
Streets, D., He, H., Ren, X., Li, Z., and Dickerson, R. R.: India Is
Overtaking China as the World's Largest Emitter of Anthropogenic Sulfur
Dioxide, Sci. Rep., 7, 14304, <a href="https://doi.org/10.1038/s41598-017-14639-8" target="_blank">https://doi.org/10.1038/s41598-017-14639-8</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>19</label><mixed-citation>
Li, H., Zhang, Q., Zheng, B., Chen, C., Wu, N., Guo, H., Zhang, Y., Zheng,
Y., Li, X., and He, K.: Nitrate-driven urban haze pollution during summertime
over the North China Plain, Atmos. Chem. Phys., 18, 5293–5306,
<a href="https://doi.org/10.5194/acp-18-5293-2018" target="_blank">https://doi.org/10.5194/acp-18-5293-2018</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>20</label><mixed-citation>
Li, Q., Jiang, J., Cai, S., Zhou, W., Wang, S., Duan, L., and Hao, J.:
Gaseous Ammonia Emissions from Coal and Biomass Combustion in Household
Stoves with Different Combustion Efficiencies, Environ. Sci. Tech. Lett.,
3, 98–103, <a href="https://doi.org/10.1021/acs.estlett.6b00013" target="_blank">https://doi.org/10.1021/acs.estlett.6b00013</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>21</label><mixed-citation>
Liu, F., Zhang, Q., van der A, R. J., Zheng, B., Tong, D., Yan, L., Zheng,
Y., and He, K.: Recent reduction in NOx emissions over China: synthesis of
satellite observations and emission inventories, Environ. Res. Lett., 11,
114002, <a href="https://doi.org/10.1088/1748-9326/11/11/114002" target="_blank">https://doi.org/10.1088/1748-9326/11/11/114002</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>22</label><mixed-citation>
Lu, Z., Zhang, Q., and Streets, D. G.: Sulfur dioxide and primary
carbonaceous aerosol emissions in China and India, 1996–2010, Atmos. Chem.
Phys., 11, 9839–9864, <a href="https://doi.org/10.5194/acp-11-9839-2011" target="_blank">https://doi.org/10.5194/acp-11-9839-2011</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>23</label><mixed-citation>
Meng, Z. Y., Lin, W. L., Jiang, X. M., Yan, P., Wang, Y., Zhang, Y. M., Jia,
X. F., and Yu, X. L.: Characteristics of atmospheric ammonia over Beijing,
China, Atmos. Chem. Phys., 11, 6139–6151,
<a href="https://doi.org/10.5194/acp-11-6139-2011" target="_blank">https://doi.org/10.5194/acp-11-6139-2011</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>24</label><mixed-citation>
Pan, Y., Tian, S., Zhao, Y., Zhang, L., Zhu, X., Gao, J., Huang, W., Zhou,
Y., Song, Y., Zhang, Q., and Wang, Y.: Identifying Ammonia Hotspots in China
Using a National Observation Network, Environ. Sci. Technol., 52, 3926–3934,
<a href="https://doi.org/10.1021/acs.est.7b05235" target="_blank">https://doi.org/10.1021/acs.est.7b05235</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>25</label><mixed-citation>
Paulot, F., Jacob, D. J., Pinder, R. W., Bash, J. O., Travis, K., and Henze,
D. K.: Ammonia emissions in the United States, European Union, and China
derived by high-resolution inversion of ammonium wet deposition data:
Interpretation with a new agricultural emissions inventory (MASAGE_NH<sub>3</sub>), J.
Geophys. Res.-Atmos., 119, 4343–4364, <a href="https://doi.org/10.1002/2013jd021130" target="_blank">https://doi.org/10.1002/2013jd021130</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>26</label><mixed-citation>
Paulot, F., Ginoux, P., Cooke, W. F., Donner, L. J., Fan, S., Lin, M.-Y.,
Mao, J., Naik, V., and Horowitz, L. W.: Sensitivity of nitrate aerosols to
ammonia emissions and to nitrate chemistry: implications for present and
future nitrate optical depth, Atmos. Chem. Phys., 16, 1459–1477,
<a href="https://doi.org/10.5194/acp-16-1459-2016" target="_blank">https://doi.org/10.5194/acp-16-1459-2016</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>27</label><mixed-citation>
Paulot, F., Fan, S., and Horowitz, L. W.: Contrasting seasonal responses of
sulfate aerosols to declining SO<sub>2</sub> emissions in the Eastern U.S.: Implications
for the efficacy of SO<sub>2</sub> emission controls, Geophys. Res. Lett., 44, 455–464,
<a href="https://doi.org/10.1002/2016gl070695" target="_blank">https://doi.org/10.1002/2016gl070695</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>28</label><mixed-citation>
Pope, C. A. I., Ezzati, M., and Dockery , D. W.: Fine-Particulate Air
Pollution and Life Expectancy in the United States, N. Engl. J. Med., 360,
376–386, <a href="https://doi.org/10.1056/NEJMsa0805646" target="_blank">https://doi.org/10.1056/NEJMsa0805646</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>29</label><mixed-citation>
Pozzer, A., Tsimpidi, A. P., Karydis, V. A., de Meij, A., and Lelieveld, J.:
Impact of agricultural emission reductions on fine-particulate matter and
public health, Atmos. Chem. Phys., 17, 12813–12826,
<a href="https://doi.org/10.5194/acp-17-12813-2017" target="_blank">https://doi.org/10.5194/acp-17-12813-2017</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>30</label><mixed-citation>
Saylor, R., Myles, L., Sibble, D., Caldwell, J., and Xing, J.: Recent trends
in gas-phase ammonia and PM<sub>2.5</sub> ammonium in the Southeast United States, J.
Air Waste Manag. Assoc., 65, 347–357, <a href="https://doi.org/10.1080/10962247.2014.992554" target="_blank">https://doi.org/10.1080/10962247.2014.992554</a>,
2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>31</label><mixed-citation>
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From
Air Pollution to Climate Change, 2nd ed., John Wiley &amp; Sons, Hoboken, New
Jersey, USA, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>32</label><mixed-citation>
Van Damme, M., Clarisse, L., Heald, C. L., Hurtmans, D., Ngadi, Y., Clerbaux,
C., Dolman, A. J., Erisman, J. W., and Coheur, P. F.: Global distributions,
time series and error characterization of atmospheric ammonia (NH<sub>3</sub>)
from IASI satellite observations, Atmos. Chem. Phys., 14, 2905–2922,
<a href="https://doi.org/10.5194/acp-14-2905-2014" target="_blank">https://doi.org/10.5194/acp-14-2905-2014</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>33</label><mixed-citation>
Van Damme, M., Clarisse, L., Dammers, E., Liu, X., Nowak, J. B., Clerbaux,
C., Flechard, C. R., Galy-Lacaux, C., Xu, W., Neuman, J. A., Tang, Y. S.,
Sutton, M. A., Erisman, J. W., and Coheur, P. F.: Towards validation of
ammonia (NH<sub>3</sub>) measurements from the IASI satellite, Atmos. Meas.
Tech., 8, 1575–1591, <a href="https://doi.org/10.5194/amt-8-1575-2015" target="_blank">https://doi.org/10.5194/amt-8-1575-2015</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib34"><label>34</label><mixed-citation>
Van Damme, M., Whitburn, S., Clarisse, L., Clerbaux, C., Hurtmans, D., and
Coheur, P.-F.: Version 2 of the IASI NH<sub>3</sub> neural network retrieval algorithm:
near-real-time and reanalysed datasets, Atmos. Meas. Tech., 10, 4905–4914,
<a href="https://doi.org/10.5194/amt-10-4905-2017" target="_blank">https://doi.org/10.5194/amt-10-4905-2017</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>35</label><mixed-citation>
Warner, J. X., Dickerson, R. R., Wei, Z., Strow, L. L., Wang, Y., and Liang,
Q.: Increased atmospheric ammonia over the world's major agricultural areas
detected from space, Geophys. Res. Lett., 44, 2875–2884,
<a href="https://doi.org/10.1002/2016gl072305" target="_blank">https://doi.org/10.1002/2016gl072305</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>36</label><mixed-citation>
Wen, L., Xue, L., Wang, X., Xu, C., Chen, T., Yang, L., Wang, T., Zhang, Q.,
and Wang, W.: Summertime fine particulate nitrate pollution in the North
China Plain: increasing trends, formation mechanisms and implications for
control policy, Atmos. Chem. Phys., 18, 11261–11275,
<a href="https://doi.org/10.5194/acp-18-11261-2018" target="_blank">https://doi.org/10.5194/acp-18-11261-2018</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>37</label><mixed-citation>
Whitburn, S., Van Damme, M., Clarisse, L., Bauduin, S., Heald, C. L.,
Hadji-Lazaro, J., Hurtmans, D., Zondlo, M. A., Clerbaux, C., and Coheur, P.
F.: A flexible and robust neural network IASI-NH<sub>3</sub> retrieval
algorithm, J. Geophys. Res.-Atmos., 121, 6581-6599, <a href="https://doi.org/10.1002/2016jd024828" target="_blank">https://doi.org/10.1002/2016jd024828</a>,
2016.

</mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>38</label><mixed-citation>
Whitburn, S., Clarisse, L., Van Damme, M., and Coheur, P.-F.: Ammonia total
columns retrieved from IASI measurements, Greenbelt, Universite Libre de
Bruxelles (ULB)/Laboratoire atmosphères, milieux et observations spatiales
(LATMOS), available at: <a href="https://iasi.aeris-data.fr/nh3/" target="_blank">https://iasi.aeris-data.fr/nh3/</a> (last access:
13 September 2017), 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>39</label><mixed-citation>
Yu, F., Nair, A. A., and Luo, G.: Long-term trend of gaseous ammonia over the
United States: Modeling and comparison with observations, J. Geophys.
Res.-Atmos., 123, 8315–8325, <a href="https://doi.org/10.1029/2018JD028412" target="_blank">https://doi.org/10.1029/2018JD028412</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>40</label><mixed-citation>
Zhang, L., Chen, Y., Zhao, Y., Henze, D. K., Zhu, L., Song, Y., Paulot, F.,
Liu, X., Pan, Y., Lin, Y., and Huang, B.: Agricultural ammonia emissions in
China: reconciling bottom-up and top-down estimates, Atmos. Chem. Phys., 18,
339–355, <a href="https://doi.org/10.5194/acp-18-339-2018" target="_blank">https://doi.org/10.5194/acp-18-339-2018</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib41"><label>41</label><mixed-citation>
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X.,
Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang,
Q.: Trends in China's anthropogenic emissions since 2010 as the consequence
of clean air actions, Atmos. Chem. Phys., 18, 14095–14111,
<a href="https://doi.org/10.5194/acp-18-14095-2018" target="_blank">https://doi.org/10.5194/acp-18-14095-2018</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib42"><label>42</label><mixed-citation>
Zhu, L., Henze, D., Bash, J., Jeong, G.-R., Cady-Pereira, K., Shephard, M.,
Luo, M., Paulot, F., and Capps, S.: Global evaluation of ammonia
bidirectional exchange and livestock diurnal variation schemes, Atmos. Chem.
Phys., 15, 12823–12843, <a href="https://doi.org/10.5194/acp-15-12823-2015" target="_blank">https://doi.org/10.5194/acp-15-12823-2015</a>, 2015.
</mixed-citation></ref-html>--></article>
