Global deposition of total reactive nitrogen oxides from 1996 to 2014 constrained with satellite observations of NO <sub>2</sub> columns
Bibliographic record
Abstract
Abstract. Reactive nitrogen oxides (NOy) are a major constituent of the nitrogen deposited from the atmosphere, but observational constraints on their deposition are limited by poor or nonexistent measurement coverage in many parts of the world. Here we apply NO2 observations from multiple satellite instruments (GOME, SCIAMACHY, and GOME-2) to constrain the global deposition of NOy over the last 2 decades. We accomplish this by producing top-down estimates of NOx emissions from inverse modeling of satellite NO2 columns over 1996–2014, and including these emissions in the GEOS-Chem chemical transport model to simulate chemistry, transport, and deposition of NOy. Our estimates of long-term mean wet nitrate (NO3−) deposition are highly consistent with available measurements in North America, Europe, and East Asia combined (r = 0.83, normalized mean bias = −7 %, N = 136). Likewise, our calculated trends in wet NO3− deposition are largely consistent with the measurements, with 129 of the 136 gridded model–data pairs sharing overlapping 95 % confidence intervals. We find that global mean NOy deposition over 1996–2014 is 56.0 Tg N yr−1, with a minimum in 2006 of 50.5 Tg N and a maximum in 2012 of 60.8 Tg N. Regional trends are large, with opposing signs in different parts of the world. Over 1996 to 2014, NOy deposition decreased by up to 60 % in eastern North America, doubled in regions of East Asia, and declined by 20 % in parts of western Europe. About 40 % of the global NOy deposition occurs over oceans, with deposition to the North Atlantic Ocean declining and deposition to the northwestern Pacific Ocean increasing. Using the residual between NOx emissions and NOy deposition over specific land regions, we investigate how NOx export via atmospheric transport has changed over the last 2 decades. Net export from the continental United States decreased substantially, from 2.9 Tg N yr−1 in 1996 to 1.5 Tg N yr−1 in 2014. Export from China more than tripled between 1996 and 2011 (from 1.0 to 3.5 Tg N yr−1), before a striking decline to 2.5 Tg N yr−1 by 2014. We find that declines in NOx export from some western European countries have counteracted increases in emissions from neighboring countries to the east. A sensitivity study indicates that simulated NOy deposition is robust to uncertainties in NH3 emissions with a few exceptions. Our novel long-term study provides timely context on the rapid redistribution of atmospheric nitrogen transport and subsequent deposition to ecosystems around the world.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".