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Concentrations and Surface Exchange of Air Pollutants at Harvard Forest EMS Tower since 1990

2022· dataset· en· W6958266837 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Data Initiative · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNOxReactive nitrogenDeposition (geology)NitrogenNitrogen oxideSaturation (graph theory)NitratePollutantAir pollution

Abstract

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In North America, anthropogenic activities such as fossil fuel combustion and high-intensity agriculture have increased the inputs of nitrogen oxides in the atmosphere far above natural, biogenic inputs. The effect of this excess N depends on how it is distributed through the environment. If fixed N is deposited as nitrate in forests, it may act as a "fertilizer", stimulating growth and thus enhancing carbon sequestration. But when accumulated deposition exceeds the nutritional needs of the ecosystem, nitrogen saturation may result. Soil fertility declines due to leaching of cations and thus, carbon uptake diminishes. The balance between fertilization and saturation depends on the spatial and temporal extent of nitrogen deposition. Measurements of nitrogen oxide concentrations and fluxes made at Harvard Forest are intended to quantify the deposition of nitrogen oxides and to examine the rates for oxidation and deposition of reactive nitrogen that are critical in controlling how far the influence of nitrogen oxide emission sources extends. Measurements made to date indicate that dry deposition of NOy to the Harvard Forest canopy is controlled by advection from source regions, vertical mixing, and chemical reaction. The input is about equally divided between wet and dry deposition depending on the amount of precipitation. Southwesterly winds bring air from the major urban areas along the mid-Atlantic coast, whereas northwesterly wind bring air from less populated regions of northern New England and Canada. As a result, southwesterly winds transport higher concentrations and fluxes of NOx and NOy than northwesterly winds. In the summer, aerodynamically rough forests intercept NOx and emit reactive hydrocarbons that accelerate the oxidation of NOx to rapidly depositing species. As a result, much of the NOx emitted by North America is retained by the region in the summer. This deposition leads to a summertime decrease in reactive nitrogen concentrations and fluxes relative to spring levels. In addition to their role as a plant nutrient, nitrogen oxides are a major precursor for photochemical production of tropospheric ozone, a pollutant and greenhouse gas. Measurements at Harvard Forest are used to examine the interannual variability and trends in ozone production and background ozone concentrations. The family of nitrogen oxide species is partitioned between active radicals (NOx, NO3), reservoir species (e.g., peroxyacetylnitrate PAN) which can convert back into NO2 and terminal species (HNO3, organic nitrates), which no longer contribute to photochemistry and are efficiently deposited. At low wintertime temperatures, PAN is stable and can be transported to the upper troposphere and remote regions. In the summer, however, the lifetime of PAN is short (few hours) so concentrations may remain low despite abundant photochemical radicals that promote PAN formation. Thus, temperature directly affects the partitioning of nitrogen oxides, which will in turn affect deposition. Further measurements resolving key species are needed to distinguish the contributions due to direct NO2 deposition, HNO3 deposition and organic nitrate deposition. A dual Tunable Diode Laser Absorption Spectrometer (TDLAS) for eddy covariance flux measurements of NO2 and concentrations of HNO3 and NO2 has been operational since 1999 and a new CG/ECD for continuous measurement of PAN was installed in the spring of 2000. The combination of HNO3 and NO2 concentrations with existing measurements of O3, NOy, NO, PAN, hydrocarbons, tracers of anthropogenic emissions, and meteorological parameters at the site, provide important new data on the speciation and removal mechanisms for reactive nitrogen in the troposphere and subsequently the photochemistry of ozone in both urban and rural air masses. Simultaneous NOy, NOx, PAN and CO data will allow us to distinguish PAN deposition (loss of NOy) from PAN decomposition (leads to NOx increase, no change in NOy). Because seasonal cycles of PAN loss and formation remain a major uncertainty in understanding atmospheric transport and N deposition, we plan to continue measurements of NOy speciation over several seasonal cycles and climactic variation. The addition of PAN and HNO3 measurements provides a comprehensive analysis of the reactive nitrogen at this site, allowing us to examine the diel and seasonal trends in concentrations to determine their production, deposition, and loss rates. CO2 concentration profiles are measured by an infra-red gas analyzer (Licor 6251). Inlet sample flow is maintained at a constant pressure by a pressure control valve upstream of a bypass pump that generates high flow volume to minimize residence time in the inlet line. Sample air for the CO2 analyzer is drawn off and passed through diffusion dryer to remove water vapor down to a low and constant value before passing through the analyzer. Pressure control valve on the instrument exhaust maintains constant pressure in the detector cell. The reference cell of the analyzer is purged with a small flow of calibration gas having a concentration comparable to average ambient concentration. At least three times a day the analyzer is calibrated automatically by replacing sample air with the reference gas to determine the zero offset and with a set of three calibration standards that span the expected range of ambient concentration. A second-order polynomial is fit to the instrument response to standards and used to compute mixing ratio in the samples.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.094
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.007
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0960.002

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 head0.045
GPT teacher head0.268
Teacher spread0.223 · 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

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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