ETC/ATNI Report 2020/4: Costs of air pollution from European industrial facilities 2008–2017.
Bibliographic record
Abstract
This report assesses in monetary terms the cost of damage to health and the environment caused by air pollutant emissions from industrial facilities officially reported to the European Pollutant Release and Transfer Register (E-PRTR). It represents an update of two earlier EEA reports. Marginal damage costs (damage cost per tonne of pollutant emitted) are calculated for selected air pollutants (PM2.5, PM10, SO2, NH3, NOX, NMVOCs, As, Cd, CrVI, Pb, Hg, Ni, 1,3 butadiene, benzene, formaldehyde, benzo(a)pyrene, dioxins and furans) and greenhouse gases (CO2, CH4 and N2O), for the countries EEA38+UK. They are then applied to emissions reported by industrial facilities to the E-PRTR, thus calculating the costs of air pollution from industrial facilities in Europe. Such externalities are calculated for the period 2008-2017. The updated set of marginal damage costs covering impacts on health, crops and forests, building materials and ecosystems varies from earlier ones owing to changes in source receptor matrices, the price base used, updates of the monetary unit values for mortality and the inclusion of additional health impacts. For the first time, a complete set of sectoral adjustment factors was calculated for exposure to PM2.5 and NO2 for each country and sector, permitting to account for differences in emission dispersion and distance from population between different emission sources. The aggregated cost of damage caused by emissions reported by E-PRTR industrial facilities is estimated to have decreased between 2008 and 2017, with reductions over the period by 54% for the main air pollutants, 19% for greenhouse gases, 43% for heavy metals and 60% organic pollutants. A limited number of facilities accounts for the major part of the damage. For example, in 2017, 1.8% of facilities having reported emissions accounted for 50% of estimated damage from main air pollutants and greenhouse gases. Damage estimated in this report remains below total damage caused by total emissions from the studied countries as not all facilities are required to report to E-PRTR. Damage costs of industrial facilities are also presented by individual pollutant, by country, and by sector. The ranking of countries by absolute damage differs from a ranking where damage costs are weighted by gross domestic product (GDP), thus accounting for the respective level of services generated by the national economies.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".