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Record W2968603026 · doi:10.5194/acp-20-3107-2020

Air quality in the eastern United States and Eastern Canada for 1990–2015: 25 years of change in response to emission reductions of SO <sub>2</sub> and NO <sub> <i>x</i> </sub> in the region

2020· article· en· W2968603026 on OpenAlexafffundabout
Jianying Feng, Elton Chan, Robert Vet

Bibliographic record

VenueAtmospheric chemistry and physics · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersEnvironment and Climate Change Canada
KeywordsNOxAir quality indexNitrateAtmospheric sciencesSulfateEnvironmental sciencePrecipitationTroposphereAerosolAmmoniumEnvironmental chemistryChemistryMeteorologyGeographyCombustion

Abstract

fetched live from OpenAlex

SO 2 and NO x are precursors to form sulfate, nitrate, and ammonium particles in the air, which account for more than 50 % of PM 2.5 mass in the eastern US (Bell et al., 2007) and are dominant components of PM 2.5 during many smog events (Dabek-Zlotorzynska et al., 2011). H 2 SO 4 and HNO 3 , formed from the oxidation of SO 2 and NO x , respectively, are the main sources of acid deposition through wet and dry depositions. NO x is also a precursor to the formation of tropospheric O 3 , which is an important atmospheric oxidant and is also essential for the formation of other atmospheric oxidants, such as OH and H 2 O 2 . In the past 26 years from 1990 to 2015, emissions of SO 2 and NO x in the US were significantly reduced from 23.1 and 25.2 million t yr −1 in 1990 to 3.7 and 11.5 million t yr −1 in 2015, respectively. In Canada, SO 2 and NO x were reduced by 63 % and 33 % from 1990 to 2014. In response to the significant reductions of SO 2 and NO x emissions, air quality in the eastern US and Eastern Canada improved tremendously during 1990–2015. In this study, we analyzed surface air concentrations of SO42-, NO3-, NH4+, HNO 3 , and SO 2 measured weekly by the Clean Air Status and Trends Network (CASTNET) in the US and measured daily from the Canadian Air and Precipitation Monitoring Network (CAPMoN) in Canada to reveal the temporal and spatial changes in each species during the 25-year period. For the whole eastern US and Eastern Canada, the annual mean concentrations of SO42-, NO3-, NH4+, HNO 3 , SO 2 , and TNO 3 (NO3- + HNO 3 , expressed as the mass of equivalent NO3-) were reduced by 73.3 %, 29.1 %, 67.4 %, 65.8 %, 87.6 %, and 52.6 %, respectively, from 1990 to 2015. In terms of percentage, the reductions of all species except NO3- were spatially uniform. The reductions of SO 2 and HNO 3 were similar in the warm season (May–October) and the cold season (November–April), and the reductions of SO42-, NO3-, and NH4+ were more significant in the warm season than in the cold season. The reductions of SO42- and SO 2 mainly occurred in 1990–1995 and 2007–2015 during the warm season and in 1990–1995 and 2005–2015 during the cold season. The reduction of NO3- mainly occurred in the Midwest after 2000. Other than in the Midwest, NO3- exhibited very little change during the cold season for the period. The reduction of NH4+ generally followed the reduction trend of SO42-; especially after 2000, the temporal trend of NH4+ was almost identical to that of SO42-. The ratio of S in SO42- to total S in SO42- plus SO 2 , as well as the ratio of NO3- to TNO 3 increased by more than 50 % during the period. This indicates that a notable change in regional chemistry took place from the beginning to the end of the period, with a higher percentage of SO 2 being oxidized to SO42- and a higher percentage of HNO 3 being neutralized to NH 4 NO 3 near the end of the period.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 score0.015
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.233
Teacher spread0.210 · 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

Citations64
Published2020
Admission routes3
Has abstractyes

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