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Record W3088695491 · doi:10.3390/w12102709

Nitrate Contamination in Brazilian Urban Aquifers: A Tenacious Problem

2020· article· en· W3088695491 on OpenAlexafffund
Ricardo Hirata, Fabiana Alves Cagnon, Aline Michelle Bernice, Carlos Maldaner, Paulo Galvão, Carlos Henrique Gil Marques, Rafael Terada, Cláudia Varnier, M. Cathryn Ryan, Reginaldo Antônio Bertolo

Bibliographic record

VenueWater · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of CalgaryUniversity of Guelph
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoUniversidade de São PauloUniversity of WaterlooFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsNitrateAquiferEnvironmental scienceContaminationPlumeHydrology (agriculture)MODFLOWEnvironmental engineeringWastewaterGroundwaterInfiltration (HVAC)Environmental chemistryGeologyGroundwater flowChemistryGeotechnical engineeringGeographyEcology

Abstract

fetched live from OpenAlex

This study follows the geochemistry of nitrogen in a Cretaceous and unconfined sedimentary aquifer in the city of Urânia (Brazil) over 20 years. Although the sewer network was built in the 1970s, the nitrate contamination problem (>45 mg/L-NO3−) persists to this day. The oldest urbanization areas located in the north of the city initially used cesspits for wastewater and currently present the highest nitrate concentrations (>120 mg/L-NO3−), with the plume reaching the deeper aquifer portions (up to 100 m). The contamination is not as dramatic in the south part of the city, where urbanization including installation of the sewage network with PVC pipes that are more resistant to leak than the old ceramic networks occurred after 1985. Based on the constructive well profiles, three hydrogeochemical zones were established: shallow (<20 m deep), with average nitrate of 63 mg/L-NO3−; intermediate (20–60 m), with 30 mg/L-NO3−; and deep (>60 m), with 17 mg/L-NO3−. The current total nitrate mass in the aquifer exceeds 731 kg-NO3−. Numerical flow (Modflow) and transport (MT3D) model scenarios support the hypothesis that the nitrate contamination is caused by substantial infiltration of nitrogen through the cesspits until the 1970s, but after the 1990s, leaks from the sewer network should be responsible for the maintenance of the recently observed high concentrations of nitrate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.177
Teacher spread0.168 · 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; both teacher heads agree on what is shown here.

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

Citations44
Published2020
Admission routes2
Has abstractyes

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