Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements

Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements

<p>Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (N<span class="inline-formula"><sub>r</sub></span>) species, especially of reduced N (gaseou...

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Autores principales: Y. Ge, M. R. Heal, D. S. Stevenson, P. Wind, M. Vieno
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Publicado: Copernicus Publications 2021
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Geology
QE1-996.5
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collection DOAJ
language EN
topic Geology
QE1-996.5
spellingShingle Geology
QE1-996.5
Y. Ge
Y. Ge
M. R. Heal
D. S. Stevenson
P. Wind
M. Vieno
Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
description <p>Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (N<span class="inline-formula"><sub>r</sub></span>) species, especially of reduced N (gaseous <span class="inline-formula">NH<sub>3</sub></span>, particulate <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="47abf32743cd28df9573e01430c76658"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00001.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00001.png"/></svg:svg></span></span>). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of N<span class="inline-formula"><sub>r</sub></span> chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="d308210e38ed1a4940972a050836d54c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00002.svg" width="34pt" height="11pt" src="gmd-14-7021-2021-ie00002.png"/></svg:svg></span></span> resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric N<span class="inline-formula"><sub>r</sub></span> and secondary inorganic aerosol (SIA). The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSE<span class="inline-formula"><sub>E</sub></span> (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSE<span class="inline-formula"><sub>E</sub></span> only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China) but are much less sensitive for secondary components. For example, the difference in modelled global annual mean surface <span class="inline-formula">NH<sub>3</sub></span> concentration using the two 2010 inventories is 18 % (HTAP: 0.26 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.31 <span class="inline-formula">µg m<sup>−3</sup></span>) but is only 3.5 % for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="88e3051c9abcd7cd53c8b0640d7b1dd6"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00003.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00003.png"/></svg:svg></span></span> (HTAP: 0.316 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.305 <span class="inline-formula">µg m<sup>−3</sup></span>). Comparisons of 2010 and 2015 surface concentrations between the model and measurements demonstrate that the model captures the overall spatial and seasonal variations well for the major inorganic pollutants <span class="inline-formula">NH<sub>3</sub></span>, <span class="inline-formula">NO<sub>2</sub></span>, <span class="inline-formula">SO<sub>2</sub></span>, <span class="inline-formula">HNO<sub>3</sub></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M21" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="df1f0fc1093d7c213f3735ccc009a4e7"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00004.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00004.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="2c946b389efef41f68452a1514b13f0e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00005.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00005.png"/></svg:svg></span></span>, and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M23" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn></msub><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="c0d51741a4f5a075e6988150e0bd7e57"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00006.svg" width="34pt" height="16pt" src="gmd-14-7021-2021-ie00006.png"/></svg:svg></span></span> and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (mean <span class="inline-formula"><i>R</i></span> for seven species: <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M25" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.73</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="dc695532dd84c8181ba41d7a34a02423"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00007.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00007.png"/></svg:svg></span></span>), Europe (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M26" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.67</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="4c3b7d90722f2e047301bb0417113f08"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00008.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00008.png"/></svg:svg></span></span>), and North America (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M27" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.63</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="82b6aa70b269c6e8689752f48f0be24d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00009.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00009.png"/></svg:svg></span></span>) than in East Asia (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M28" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">5</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.35</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="588f544eb0d3af9f76e5d57317b7c8ea"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00010.svg" width="48pt" height="16pt" src="gmd-14-7021-2021-ie00010.png"/></svg:svg></span></span>) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurements agree on higher <span class="inline-formula">NH<sub>3</sub></span> concentrations in spring and summer and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13 %–45 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.94 <span class="inline-formula"><i>R</i></span> range). High correlations between measured and modelled <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M31" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3a32c345e2253b43267a7413deb4349c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00011.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00011.png"/></svg:svg></span></span> precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (0.75–0.82 <span class="inline-formula"><i>R</i></span> range), followed by Southeast Asia (<span class="inline-formula"><i>R</i>=0.68</span>) and Europe (<span class="inline-formula"><i>R</i>=0.61</span>). Model–measurement bias varies between species in different networks; for example, bias for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M35" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3e19afed06e3ea335bb19dfa58eaff6b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00012.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00012.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M36" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="5bf2f905a09d07a0fbd9e1f354927308"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00013.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00013.png"/></svg:svg></span></span> is largest in Europe and North America and smallest in East Asia and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model–measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this<span id="page7022"/> study support the application of this model framework for global analysis of current and potential future budgets and deposition of N<span class="inline-formula"><sub>r</sub></span> and SIA.</p>
format article
author Y. Ge
Y. Ge
M. R. Heal
D. S. Stevenson
P. Wind
M. Vieno
author_facet Y. Ge
Y. Ge
M. R. Heal
D. S. Stevenson
P. Wind
M. Vieno
author_sort Y. Ge
title Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
title_short Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
title_full Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
title_fullStr Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
title_full_unstemmed Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
title_sort evaluation of global emep msc-w (rv4.34) wrf (v3.9.1.1) model surface concentrations and wet deposition of reactive n and s with measurements
publisher Copernicus Publications
publishDate 2021
url https://doaj.org/article/b518cc613a474f9c99af46f3f0525a20
work_keys_str_mv AT yge evaluationofglobalemepmscwrv434wrfv3911modelsurfaceconcentrationsandwetdepositionofreactivenandswithmeasurements
AT yge evaluationofglobalemepmscwrv434wrfv3911modelsurfaceconcentrationsandwetdepositionofreactivenandswithmeasurements
AT mrheal evaluationofglobalemepmscwrv434wrfv3911modelsurfaceconcentrationsandwetdepositionofreactivenandswithmeasurements
AT dsstevenson evaluationofglobalemepmscwrv434wrfv3911modelsurfaceconcentrationsandwetdepositionofreactivenandswithmeasurements
AT pwind evaluationofglobalemepmscwrv434wrfv3911modelsurfaceconcentrationsandwetdepositionofreactivenandswithmeasurements
AT mvieno evaluationofglobalemepmscwrv434wrfv3911modelsurfaceconcentrationsandwetdepositionofreactivenandswithmeasurements
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spelling oai:doaj.org-article:b518cc613a474f9c99af46f3f0525a202021-11-18T12:32:14ZEvaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements10.5194/gmd-14-7021-20211991-959X1991-9603https://doaj.org/article/b518cc613a474f9c99af46f3f0525a202021-11-01T00:00:00Zhttps://gmd.copernicus.org/articles/14/7021/2021/gmd-14-7021-2021.pdfhttps://doaj.org/toc/1991-959Xhttps://doaj.org/toc/1991-9603<p>Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (N<span class="inline-formula"><sub>r</sub></span>) species, especially of reduced N (gaseous <span class="inline-formula">NH<sub>3</sub></span>, particulate <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="47abf32743cd28df9573e01430c76658"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00001.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00001.png"/></svg:svg></span></span>). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of N<span class="inline-formula"><sub>r</sub></span> chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="d308210e38ed1a4940972a050836d54c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00002.svg" width="34pt" height="11pt" src="gmd-14-7021-2021-ie00002.png"/></svg:svg></span></span> resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric N<span class="inline-formula"><sub>r</sub></span> and secondary inorganic aerosol (SIA). The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSE<span class="inline-formula"><sub>E</sub></span> (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSE<span class="inline-formula"><sub>E</sub></span> only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China) but are much less sensitive for secondary components. For example, the difference in modelled global annual mean surface <span class="inline-formula">NH<sub>3</sub></span> concentration using the two 2010 inventories is 18 % (HTAP: 0.26 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.31 <span class="inline-formula">µg m<sup>−3</sup></span>) but is only 3.5 % for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="88e3051c9abcd7cd53c8b0640d7b1dd6"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00003.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00003.png"/></svg:svg></span></span> (HTAP: 0.316 <span class="inline-formula">µg m<sup>−3</sup></span>; ECLIPSE<span class="inline-formula"><sub>E</sub></span>: 0.305 <span class="inline-formula">µg m<sup>−3</sup></span>). Comparisons of 2010 and 2015 surface concentrations between the model and measurements demonstrate that the model captures the overall spatial and seasonal variations well for the major inorganic pollutants <span class="inline-formula">NH<sub>3</sub></span>, <span class="inline-formula">NO<sub>2</sub></span>, <span class="inline-formula">SO<sub>2</sub></span>, <span class="inline-formula">HNO<sub>3</sub></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M21" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="df1f0fc1093d7c213f3735ccc009a4e7"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00004.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00004.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="2c946b389efef41f68452a1514b13f0e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00005.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00005.png"/></svg:svg></span></span>, and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M23" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn></msub><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="c0d51741a4f5a075e6988150e0bd7e57"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00006.svg" width="34pt" height="16pt" src="gmd-14-7021-2021-ie00006.png"/></svg:svg></span></span> and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (mean <span class="inline-formula"><i>R</i></span> for seven species: <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M25" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.73</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="dc695532dd84c8181ba41d7a34a02423"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00007.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00007.png"/></svg:svg></span></span>), Europe (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M26" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.67</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="4c3b7d90722f2e047301bb0417113f08"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00008.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00008.png"/></svg:svg></span></span>), and North America (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M27" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">7</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.63</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="82b6aa70b269c6e8689752f48f0be24d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00009.svg" width="48pt" height="15pt" src="gmd-14-7021-2021-ie00009.png"/></svg:svg></span></span>) than in East Asia (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M28" display="inline" overflow="scroll" dspmath="mathml"><mrow><mover accent="true"><mrow><msub><mi>R</mi><mn mathvariant="normal">5</mn></msub></mrow><mo mathvariant="normal">‾</mo></mover><mo>=</mo><mn mathvariant="normal">0.35</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="588f544eb0d3af9f76e5d57317b7c8ea"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00010.svg" width="48pt" height="16pt" src="gmd-14-7021-2021-ie00010.png"/></svg:svg></span></span>) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurements agree on higher <span class="inline-formula">NH<sub>3</sub></span> concentrations in spring and summer and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13 %–45 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.94 <span class="inline-formula"><i>R</i></span> range). High correlations between measured and modelled <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M31" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3a32c345e2253b43267a7413deb4349c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00011.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00011.png"/></svg:svg></span></span> precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (0.75–0.82 <span class="inline-formula"><i>R</i></span> range), followed by Southeast Asia (<span class="inline-formula"><i>R</i>=0.68</span>) and Europe (<span class="inline-formula"><i>R</i>=0.61</span>). Model–measurement bias varies between species in different networks; for example, bias for <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M35" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn></msub><mo>+</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="3e19afed06e3ea335bb19dfa58eaff6b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00012.svg" width="29pt" height="14pt" src="gmd-14-7021-2021-ie00012.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M36" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msup><msub><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn></msub><mo>-</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="30pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="5bf2f905a09d07a0fbd9e1f354927308"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="gmd-14-7021-2021-ie00013.svg" width="30pt" height="15pt" src="gmd-14-7021-2021-ie00013.png"/></svg:svg></span></span> is largest in Europe and North America and smallest in East Asia and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model–measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this<span id="page7022"/> study support the application of this model framework for global analysis of current and potential future budgets and deposition of N<span class="inline-formula"><sub>r</sub></span> and SIA.</p>Y. GeY. GeM. R. HealD. S. StevensonP. WindM. VienoCopernicus PublicationsarticleGeologyQE1-996.5ENGeoscientific Model Development, Vol 14, Pp 7021-7046 (2021)

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