Air quality in postunification Erfurt, East Germany: associating changes in pollutant concentrations with changes in emissions.
Bibliographic record
Abstract
The unification of East and West Germany in 1990 resulted in sharp decreases in emissions of major air pollutants. This change in air quality has provided an opportunity for a natural experiment to evaluate the health impacts of air pollution. We evaluated airborne particle size distribution and gaseous co-pollutant data collected in Erfurt, Germany, throughout the 1990s and assessed the extent to which the observed changes are associated with changes in the two major emission sources: coal burning for power production and residential heating, and motor vehicles. Continuous data for sulfur dioxide, total suspended particulates (TSP), nitric oxide, carbon monoxide, and meteorologic parameters were available for 1990-1999, and size-selective particle number and mass concentration measurements were made during winters of 1991 and 1998. We used hourly profiles of pollutants and linear regression analyses, stratified by year, weekday/weekend, and hour, using NO and SO(2) as markers of traffic- and heating-related combustion sources, respectively, to study the patterns of various particle size fractions. Supplementary data on traffic and heating-related sources were gathered to support hypotheses linking these sources with observed changes in ambient air pollution levels. Substantially decreased (19-91%) concentrations were observed for all pollutants, with the exception of particles in the 0.01-0.03 microm size range (representing the smallest ultrafine particles that were measured). The number concentration for these particles increased by 115% between 1991 and 1998. The ratio of these ultrafine particles to TSP also increased by more than 500%, indicating a dramatic change in the size distribution of airborne particles. Analysis of hourly concentration patterns indicated that in 1991, concentrations of SO(2) and larger particle sizes were related to residential heating with coal. These peaks were no longer evident in 1998 due to decreases in coal consumption and consequent decreased emissions of SO(2) and larger particles. These decreases in coal combustion and the decreased concentrations of SO(2) and particles of larger size classes may have led to decreased particle scavenging and may be partially responsible for the observed increases in ultrafine particles. Traffic-related changes, such as increased numbers of trucks and increased use of diesel vehicles in Erfurt, were also associated with increased number concentrations of ultrafine particles. Morning particle peaks of all sizes were associated with NO and CO (markers for traffic) in both the 1991 and 1998 periods. There were significant differences in the ultrafine particle levels for morning hours between 1991 and 1998, suggesting that traffic was the cause of this increase.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".