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Record W4309277394 · doi:10.5194/acp-22-14631-2022

Long-term declines in atmospheric nitrogen and sulfur deposition reduce critical loads exceedances at multiple Canadian rural sites, 2000–2018

2022· article· en· W4309277394 on OpenAlexafffundabout
Irene Cheng, Leiming Zhang, Zhuanshi He, Hazel Cathcart, Daniel Houle, Amanda Cole, Jian Feng, Jason O’Brien, A. M. Macdonald, Julian Aherne, Jeffrey R. Brook

Bibliographic record

VenueAtmospheric chemistry and physics · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsTrent UniversityPublic Health OntarioUniversity of TorontoEnvironment and Climate Change Canada
FundersEnvironment and Climate Change Canada
KeywordsDeposition (geology)NitrogenPrecipitationEnvironmental chemistryEnvironmental scienceSulfurParticulatesEcosystemChemistryHydrology (agriculture)Atmospheric sciencesMeteorologyEcologyGeographySedimentGeology

Abstract

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Daily air concentrations of inorganic nitrogen (N) species, including gaseous HNO 3 and particulate-bound (p)NH4+ and pNO3-, and sulfur (S) species, including SO 2 and pSO42-, and precipitation concentrations of NO3-, NH4+, and SO42-, have been routinely monitored by the Canadian Air and Precipitation Monitoring Network (CAPMoN) since 1983. Data at 15 rural sites from 2000–2018 were used to estimate dry and wet N and S deposition fluxes, which were then used to explore their spatiotemporal trends and assess ecosystem damage through a retrospective analysis of critical loads (CLs) exceedances. Total (dry + wet) N deposition ranged from 1.7–9.5 kgNha-1yr-1 among the 15 sites, though dry deposition of NH 3 and some oxidized N species were not included due to lack of monitoring data. Based on additional N measurements in 2010 at one of the sites, annual total N deposition may be underestimated by up to 32 %. Total N deposition was dominated by wet NO3- and wet NH4+ deposition, which together comprised 71 %–95 %. Contributions to dry N deposition were 40 %–74 % by HNO 3 , 11 %–40 % by pNH4+, and 5 %–25 % by pNO3-. Total S deposition ranged from 1.3–8.5 kgSha-1yr-1 and was dominated by wet deposition of SO42- and dry deposition of SO 2 . Relative percentages of wet and dry S deposition were 45 %–89 % and 11 %–55 %, respectively. Acidic ion fluxes were greatest in southeastern Canada and were comparable among the west coast, prairie, remote, and eastern Canadian sites. Oxidized N (dry HNO 3 , dry pNO3-, wet NO3-) deposition was greater than that of reduced N (dry pNH4+, wet NH4+) in the early 2000s. In 2014–2018, reduced N deposition surpassed that of oxidized N in southeastern Canada. Total N and S deposition decreased significantly at a rate of −0.03 to −0.25 kgNha-1yr-1 (−1.1 % yr −1 to −3.3 % yr −1 ) and −0.08 to −0.66 kgSha-1yr-1 (−3.5 % yr −1 to −6.6 % yr −1 ), respectively, among the sites. The weak declining trend in total N deposition at the west coast site was consistent with the slower decline in NO x emissions in western Canada. Reductions in total N deposition were driven by its oxidized form as trends in reduced N were non-significant. As a result, reduced N contributions to total N deposition increased on average from 42 % in 2000–2004 to 53 % in 2014–2018. Anthropogenic NO x and SO 2 emissions reductions in both eastern Canada and eastern US were highly effective in reducing total oxidized N and total S deposition, respectively, in eastern Canada. Acidic deposition exceeded terrestrial CL at 5 of the 14 sites and aquatic CL at 2 of the 5 sites in the early 2000s. However, exceedances have been trending downwards and acidic deposition fluxes were mostly near or below CL after 2012 for the subset of sites assessed, which support recovery from historical acidification. Further assessments of CL exceedances are required in other Canadian regions susceptible to acidification and affected by elevated or increasing N and S emissions.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.217
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations31
Published2022
Admission routes3
Has abstractyes

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