Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study.

IF 5.2 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
Paul A Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O Bash, Michael D Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E Clifton, Alma Hodzic, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A Lynch, Kester Momoh, Juan L Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark W Shephard, Ranjeet S Sokhi, Stefano Galmarini
{"title":"Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study.","authors":"Paul A Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O Bash, Michael D Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E Clifton, Alma Hodzic, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A Lynch, Kester Momoh, Juan L Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark W Shephard, Ranjeet S Sokhi, Stefano Galmarini","doi":"10.5194/acp-25-3049-2025","DOIUrl":null,"url":null,"abstract":"<p><p>Exceedances of critical loads for deposition of sulfur (S) and nitrogen (N) in different ecosystems were estimated using European and North American ensembles of air quality models, under the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4), to identify where the risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and European 0.125° resolution domains, which were then used to calculate critical load exceedances. Targeted deposition diagnostics implemented in AQMEII4 allowed for an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. Datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were created for this analysis. These were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2% to 6.1 %; aquatic ecosystems: 21.2% to 11.4 %). All models agreed regarding the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both the severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5% to 75.8 %). The exceedances for herbaceous-community richness also decreased between 2010 and 2016, from 13.9% to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in predictions of both total N deposition and the change in N deposition and hence in the predicted eutrophication exceedances between the 2 years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48% to 4.32% from 2009 to 2010), while eutrophication exceedance increased slightly (60.2% to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the 2 years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulfur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to the observed wet deposition of sulfate, nitrate, and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulfate, nitrate, and ammonium deposition fluxes between models was linked to the use of updated particle dry-deposition parameterizations in some models. However, recent literature and the further development of some of the models within the ensemble suggest these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulfur and nitrogen deposition prediction variability was linked to SO<sub>2</sub> and HNO<sub>3</sub> dry-deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying-gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine-mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest- and the smallest-magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH<sub>3</sub> performance may underestimate the extent of NH<sub>3</sub> emission fluxes from forested areas. Model-measurement fusion in the form of a simple bias correction was applied to the 2016 critical loads. This generally reduced variability between models. However, the bias correction exercise illustrated the need for observations which close the sulfur and nitrogen budgets in carrying out model-measurement fusion. Chemical transformations between different forms of sulfur and nitrogen in the atmosphere sometimes result in compensating biases in the resulting total sulfur and nitrogen deposition flux fields. If model-measurement fusion is only applied to some but not all of the fields contributing to the total deposition of sulfur or nitrogen, the corrections may result in greater variability between models or less accurate results for an ensemble of models, for those cases where an unobserved or unused observed component contributes significantly to predicted total deposition. Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH<sub>3</sub> bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH<sub>3</sub> emission sources should be included in regional chemical transport models. The choice of a land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.</p>","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"25 5","pages":"3049-3107"},"PeriodicalIF":5.2000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11980814/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Chemistry and Physics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/acp-25-3049-2025","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Exceedances of critical loads for deposition of sulfur (S) and nitrogen (N) in different ecosystems were estimated using European and North American ensembles of air quality models, under the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4), to identify where the risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and European 0.125° resolution domains, which were then used to calculate critical load exceedances. Targeted deposition diagnostics implemented in AQMEII4 allowed for an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. Datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were created for this analysis. These were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2% to 6.1 %; aquatic ecosystems: 21.2% to 11.4 %). All models agreed regarding the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both the severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5% to 75.8 %). The exceedances for herbaceous-community richness also decreased between 2010 and 2016, from 13.9% to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in predictions of both total N deposition and the change in N deposition and hence in the predicted eutrophication exceedances between the 2 years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48% to 4.32% from 2009 to 2010), while eutrophication exceedance increased slightly (60.2% to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the 2 years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulfur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to the observed wet deposition of sulfate, nitrate, and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulfate, nitrate, and ammonium deposition fluxes between models was linked to the use of updated particle dry-deposition parameterizations in some models. However, recent literature and the further development of some of the models within the ensemble suggest these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulfur and nitrogen deposition prediction variability was linked to SO2 and HNO3 dry-deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying-gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine-mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest- and the smallest-magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH3 performance may underestimate the extent of NH3 emission fluxes from forested areas. Model-measurement fusion in the form of a simple bias correction was applied to the 2016 critical loads. This generally reduced variability between models. However, the bias correction exercise illustrated the need for observations which close the sulfur and nitrogen budgets in carrying out model-measurement fusion. Chemical transformations between different forms of sulfur and nitrogen in the atmosphere sometimes result in compensating biases in the resulting total sulfur and nitrogen deposition flux fields. If model-measurement fusion is only applied to some but not all of the fields contributing to the total deposition of sulfur or nitrogen, the corrections may result in greater variability between models or less accurate results for an ensemble of models, for those cases where an unobserved or unused observed component contributes significantly to predicted total deposition. Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH3 bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH3 emission sources should be included in regional chemical transport models. The choice of a land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.

北美和欧洲的临界负荷超标使用模型集合和环境影响估计变异原因调查:AQMEII4研究。
在空气质量模型评估国际倡议第4阶段(AQMEII4)下,使用欧洲和北美的空气质量模型集合估计了不同生态系统中硫(S)和氮(N)沉积的临界负荷超标情况,以确定基于模型沉积估计的生态系统危害风险发生的地方。系统由共同排放和侧向边界条件输入驱动。模型输出被重新划分到常见的北美和欧洲0.125°分辨率域,然后用于计算临界负荷超标。AQMEII4中实施的有针对性的沉积诊断允许进行前所未有的模拟后分析,并有助于确定临界负荷超出估计中模型与模型差异的具体原因。为此分析创建了北美森林、土壤、水和水生生态系统的临界酸度负荷数据集。将这些与集合沉积预测相结合,显示出在2010年至2016年期间,超标地点的面积和数量大幅减少(森林土壤:13.2%至6.1%;水生生态系统:21.2%至11.4%)。所有模型对2010 - 2016年总超越量变化的方向一致。北美整体还预测,在2010年至2016年期间,美国受富营养化影响的生态系统的严重程度和超过的总面积都有所下降(敏感附生地衣:81.5%至75.8%)。2010年至2016年间,草本群落丰富度的超标率也从13.9%降至3.9%。与北美富营养化结果相关的不确定性很高;各模型对总氮沉降和氮沉降变化的预测存在较大差异,因此对富营养化异常的预测也存在较大差异。利用欧洲集合预测酸化临界负荷的相对静态超标(2009 - 2010年为4.48% ~ 4.32%),而富营养化超标略有增加(60.2% ~ 62.2%)。大部分模型的临界负荷超出值与2年间的总体变化相同,但超出值的空间范围和幅度在不同模型之间存在显著差异。对这种差异的原因进行了详细的研究,首先对不同来源的硫和氮沉积的相对贡献进行了排序,根据沉积质量和沉积质量中模型与模型之间的差异,然后使用AQMEII4诊断进行分析,并对最新文献进行了评估。对于观测到的硫酸盐、硝酸盐和铵的湿沉降,北美和欧洲整体的所有模式每年都有净负偏倚。诊断和最近的文献表明,这种偏差可能源于气溶胶和气体的云清除不足,并且可以通过在建模框架内纳入多相水流星清除来改善。北美模式无法预测湿铵离子沉积季节高峰的时间(观测到最大值在4月,而所有模式都预测最大值在6月)也可能与多相水流星清除的需要有关(这里使用的所有模式都没有雪清除)。颗粒硫酸盐、硝酸盐和铵沉积通量在不同模式之间的相对重要性的高度可变性与在一些模式中使用更新的颗粒干沉积参数化有关。然而,最近的文献和整体中一些模型的进一步发展表明,这些颗粒偏差也可以通过纳入多相水流星清除来改善。SO2和HNO3干沉降参数化与年硫氮沉降预测变异有关,诊断分析表明角质层和土壤沉降途径主导了这些物种的沉降质量通量。进一步改进这些沉积途径参数化的工作将减少酸化-气体沉积模型估计的可变性。在一些模型中,碱阳离子化学的缺失被证明是细模颗粒铵和颗粒硝酸盐浓度正偏差的主要因素。根据所采用的模型和双向通量算法的不同,采用氨双向通量的模型具有最大和最小的偏差。对双向通量模型的仔细分析表明,NH3性能较差的人可能低估了森林地区NH3排放通量的程度。以简单偏置校正的形式将模型-测量融合应用于2016年临界载荷。这通常减少了模型之间的可变性。 然而,偏差校正工作表明,在进行模型测量融合时,需要接近硫和氮收支的观测值。大气中不同形式的硫和氮之间的化学转化有时会导致所产生的总硫和氮沉积通量场的补偿偏差。如果模型-测量融合只应用于导致硫或氮总沉积的某些场,而不是所有场,则校正可能导致模型之间更大的变异性,或者在未观测或未使用的观测分量对预测的总沉积有重大贡献的情况下,对模型集合的结果精度降低。基于这些结果,因此建议增加对以下模型过程的研究重点以及可能有助于模型评估和改进的观测:多相水流星清除与更新的颗粒干沉积、角质和土壤沉积路径算法相结合,用于酸化气体、碱阳离子化学和排放,以及NH3双向通量。与卫星观测的比较表明,海洋NH3排放源应包括在区域化学输送模式中。在某些情况下,在任何给定模型中选择的土地利用数据库对沉积总量有显著影响,建议在今后的工作中采用跨化学运输模型和临界负荷计算的共同土地利用数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics 地学-气象与大气科学
CiteScore
10.70
自引率
20.60%
发文量
702
审稿时长
6 months
期刊介绍: Atmospheric Chemistry and Physics (ACP) is a not-for-profit international scientific journal dedicated to the publication and public discussion of high-quality studies investigating the Earth''s atmosphere and the underlying chemical and physical processes. It covers the altitude range from the land and ocean surface up to the turbopause, including the troposphere, stratosphere, and mesosphere. The main subject areas comprise atmospheric modelling, field measurements, remote sensing, and laboratory studies of gases, aerosols, clouds and precipitation, isotopes, radiation, dynamics, biosphere interactions, and hydrosphere interactions. The journal scope is focused on studies with general implications for atmospheric science rather than investigations that are primarily of local or technical interest.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信