Human radio frequency exposure limits: An update of reference levels in Europe, USA, Canada, China, Japan and Korea
Bibliographic record
Abstract
Compliance with human exposure limits for electromagnetic fields (EMFs) is a significant health and safety issue to regulators, service providers and wireless equipment suppliers. The recent exposure limits are reported. The Specific Absorption Rate (SAR) and the power-density (PD) reference levels in European countries, USA, Canada, China, Japan and Korea are compared and contrasted. The allowed SAR cellular handsets' exposure limits for localized heating are more restrictive in the USA, Canada and Korea (1.6 W/kg), relative to others (2 W/kg). Even the averaging is more restrictive: averaged over 1 g in N. America and Korea, versus 10 g tissue in ICNIRP 1998 and ANSI/IEEE C95.1-2006. Europe in general follows the ICNIRP 1998 PD levels from base stations. Despite the (non-mandatory) EU Council Recommendation 1999/519/EC, some EU countries adopt more restrictive thresholds. USA and Japan are the most liberal countries, adopting in 300-1,500 MHz power-density 4/3 of the ICNIRP1998 and IEEE 2006 levels. On 13 March 2015, Health Canada revised the 2009 PD limits (that were identical to the USA), and published more restrictive reference levels. There is no scientific reason to use different exposure limits in different countries. Some explanations of the different limits are provided.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
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".