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Record W2942507904 · doi:10.25358/openscience-3850

Investigation of atmospheric transport and chemistry of semivolatile organic pollutants using earth system models

2018· article· en· W2942507904 on OpenAlexaboutno aff
Mega Octaviani

Bibliographic record

VenueGutenberg Open Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPollutantEarth (classical element)Atmospheric chemistryEnvironmental chemistryEnvironmental scienceChemistryAstrobiologyEarth system scienceAtmospheric sciencesGeologyOzoneOceanography

Abstract

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The global atmospheric cycling of persistent organic pollutants is complex because of partitioning among phases of the aerosol and revolatilization. Many of the substances are detrimental to human health and the environment. Global dynamical multicompartmental chemistry and transport models are needed to investigate their fate and distributions. The first study investigates climate change influences on the meridional transports of dichlorodiphenyltrichloroethane (DDT) and polychlorinated biphenyls (PCBs) to and from the Arctic by application of the MPI-MCTM model. The objectives are to determine major transport gates along the Arctic Circle, the trends in import and export fluxes, and the relationships between transports and two selected patterns of climate variability, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO), under present-day (1970−1999) and future (2070−2099) climate. The pollutants enter the Arctic by passing through the Alaska−Northwest Territories regions, Greenland, the Norwegian Sea−Northwestern Russia, and the Urals−Siberian; whereas they leave the Arctic via the Canadian Arctic and Eastern Russia. DDT import fluxes to the Arctic show a decreasing trend during the present climate, but the trend is expected to change to increasing import fluxes. In contrast, PCB153 export from the Arctic is expected to be increasing in the future climate. The zonal mean meridional fluxes across the Arctic Circle are positively correlated with AO/NAO in winter, corresponding to high net imports when the frequency of positive AO/NAO increases. Under the future climate, there will be an increasing significance of the correlations for DDT while the correlations for PCB153 are expected to weaken. It is concluded that the long-term accumulation trends of other persistent pollutants in the Arctic need to be studied specifically. In the second study, the new module SVOC was developed and coupled to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model to facilitate a continuous development of modeling semivolatile organic compounds through a modular framework. Parameterizations of air−surface mass exchange in the EMAC-SVOC model are similar to those in MPI-MCTM. Other physics parameterizations were improved in the following ways: The gas−particle partitioning is described using poly-parameter linear free energy relationships; and aerosol particle size is discretized into a series of log-normally distributed modes. Through a sensitivity analysis with factor separation technique, the study examined the effects of four factors. These include the aforementioned parameterizations, as well as volatilization and temporal resolution of emissions. The focus here is set on four polycyclic aromatic hydrocarbons (PAHs), i.e., phenanthrene (PHE), pyrene (PYR), fluoranthene (FLT), and benzo(a)pyrene (BaP). The results indicate that seasonal emissions show dominant effects on PHE concentrations, notwithstanding the non-negligible effects from revolatilization. Other species are more sensitive to the change of internal model features. For all PAHs, the degree of model response is more determined by the interactions among factors with their contributions overall being stronger than individual factor contributions. Predicted near-surface concentrations using optimum model configuration were compared against observations. The model underestimates PHE concentrations in the Arctic and tropics but overestimates in the mid-latitudes. FLT and PYR tend to be overestimated over the Arctic and mid-latitudes, and underestimated over the tropics. There is a consistent underestimation of BaP in all regions, with bias increasing from mid-latitudes to the Arctic. The systematic underestimation of BaP concentrations is related to a too fast particulate-phase oxidation by ozone. This issue is addressed in the third study through a better description of BaP multiphase degradation. A new kinetic scheme was developed by considering the dependence of BaP reaction rate on two environmental parameters, that is, temperature (T) and relative humidity (RH). These parameters influence not only the phase state and diffusivity of organic aerosol coating but also the chemical reactivity of BaP. The significance of the new scheme (ROI-T) for distributions and fate was quantitatively assessed by regional (WRF-Chem-BaP) and global scale (EMAC-SVOC) modeling. In comparison to laboratory-based degradation schemes, the ROI-T scheme consistently shows better predictions and improved bias against observations at near-source sites, mid-latitude sites and most substantially at Arctic sites. The new scheme reasonably simulates the effect of low T and RH conditions to increase BaP atmospheric lifetime, leading to a more efficient transport at high altitudes or in a cold season/regions. The scheme can be adopted for modeling the multiphase degradation of other semivolatile organics.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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 designSimulation or modeling
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

Citations0
Published2018
Admission routes1
Has abstractyes

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