CCRG “corona ions” paper

The "CCRG" (or "Draper") study has been looking at childhood-cancer rates close to overhead power lines in the UK.

Previous studies found that childhood leukaemia seemed to be higher within about 600 m of high-voltage power lines - but then that this elevation seemed to be strongest in the 1960s and to diminish over the subsequent decades.

The group have now tested whether this pattern of cancer rates fits the predictions of the "corona ion hypothesis".

What is the corona ion hypothesis?

We have a whole section of this website detailing the corona ion hypothesis.

In brief:

  • the high electric fields on the surfaces of the conductors of high-voltage power lines can ionise the air, forming "corona ions";
  • Most of these recombine in the immediate vicinity of the conductors, but some escape;
  • When they escape, they can be blown away by the wind;
  • They can attach themselves to existing airborne pollutants, giving those pollutants a charge;
  • When those pollutants are breathed in, if they are charged, they are more likely to be retained in the lungs or airways and hence to cause disease.

This hypothesis has been challenged, mainly on quantitative grounds - each of these steps happens, but are they big enough to be significant?  We discuss this further on a separate page.

 

Why did the CCRG test this hypothesis?

The original CCRG results from 2005 found an excess of childhood leukaemia near power lines, that unexpectedly extended to 600 m:

graph of CCRG leukaemia results

That is too far to be caused by magnetic fields from the power lines - but it is more or less the distance predicted by the corona ion hypothesis.

Then, in 2014, the "follow on" paper from CCRG showed that this excess of childhood leukaemia had declined over the decades:

graph of CCRG follow on results

The CCRG authors had already realised that some airborne pollution had declined over this same period, and Alasdair Philips of Powerwatch pointed out that atmospheric radionuclide concentrations had also declined over the same period.  This is a colour version of the graph showing this for two different sizes of particulate matter and for radionuclides in the CCRG paper:

graph of trends over the deacdes

Neither the fact that the distance scale matches, nor that there are some atmospheric pollutants for which the time variation matches, proves that the corona ion hypothesis is causing the excess leukaemia rates.  But they justify a proper investigation.

How did CCRG test the theory?

CCRG constructed a model where the "exposure" of a person resulting from the corona ion hypothesis is given by the product of four terms:

  • a distance term, where exposure is a maximum between 50 m and 400 m and drops away to zero after 600 m
  • a source strength term, taking account of which designs of power line are more prone to producing corona
  • a wind direction term, which uses data from 8 meteorological stations around the country to calculate how many hours per year the wind blew in the relevant direction from the power line to each subjects address
  • a wind speed term using the same wind data

The paper says:

The model for calculating corona-ion exposure we have used here is undoubtedly an improvement on the previous quadrant model, but it still has considerable limitations. These include:

  • use of wind data from just eight meteorological stations, applied, in extreme cases, to subjects over a hundred km distant, with no allowance for the effect on the wind direction of local topography or proximity to coasts;
  • modelling of the source strength of each line only in terms of the voltage and conductor bundle, without taking into account the other factors which, whilst not yet identified or understood, must affect corona production; and
  • applying one representative and simplified distance variation to all points.

Nonetheless, we regard our model, despite its limitations, as the best that is likely to be achievable on present understanding and data, and we consider, by taking account of key factors such as voltage and conductor bundle, and wind direction, it provides a valid discrimination between high exposures and low exposures.

And what were the results?

The paper says:

Because the model assigns zero exposure outside 600 m and non-zero exposure inside 600 m, and because we already know that there are raised risks for leukaemia within 600 m in the earlier decades, we expect leukaemia risk to be associated with calculated exposure. The key question is: does the calculated exposure predict risk better than distance on its own?

It then presents two ways of assessing this question, a table:

 

Distance analysis

 

Corona-ion analysis

0-199 m

 

200-599 m

 

Trend across categories

 

Top quartile

RR

95% CI

 

RR

95% CI

 

RR

95% CI

 

RR

95% CI

1960s

4.50

0.97-20.83

 

1.33

0.76-2.35

 

1.32

1.08-1.61

 

14.00

1.84-106.46

1970s

2.46

1.29-4.69

 

0.94

0.72-1.23

 

1.07

0.98-1.16

 

1.41

0.86-2.30

1980s

1.54

0.92-2.58

 

1.13

0.88-1.44

 

1.08

0.99-1.17

 

1.35

0.87-2.11

1990s

0.99

0.66-1.49

 

0.86

0.70-1.05

 

0.97

0.91-1.04

 

1.04

0.73-1.49

2000s

0.71

0.49-1.03

 

1.03

0.86-1.23

 

0.99

0.93-1.05

 

0.77

0.54-1.11

and a graph:

ccrg-corona-result-compare

In both cases the evidence seems to show that the corona ion hypothesis explains the results less well than distance alone.

The paper concludes:

Thus, we conclude that the simple corona-ion hypothesis that we test here explains the observed pattern of leukaemia rates around power lines less well than straightforward distance. Our findings therefore do not support this corona-ion hypothesis as the explanation of these results.

Is this the definitive answer?

There were already questions about the corona ion hypothesis, principally whether the effects would be big enough to produce any significant changes to disease rates in practice, and whether childhood leukaemia is in fact caused by airborne pollution as is necessary for this theory.  This new test clearly does not give any support to the corona ion hypothesis, at least as far as childhood cancer is concerned.

But it's not definitive.  The paper says:

In view of the many uncertainties and approximations, however, this analysis is not a definitive rebuttal of this hypothesis, and, as discussed above, would not be relevant to any development of the hypothesis which no longer predicted stronger effects downwind compared to upwind, or in which the effects were confounded by other factors. Further, our test relates only to childhood cancers, not to other diseases.

In more detail:

The following gives a more detailed discussion of how good a test the paper presents of the corona ion theory, by means, where possible, of quotes from the paper.  Most readers will probably not be so interested in all the ins and outs!

What's valid about the model:

[W]e regard our model, despite its limitations, as the best that is likely to be achievable on present understanding and data, and we consider, by taking account of key factors such as voltage and conductor bundle, and wind direction, it provides a valid discrimination between high exposures and low exposures.

But there are limitations to the validity and to the test it performs.

Firstly, just within the model itself, there are limitations:

These include:

• use of wind data from just eight meteorological stations, applied, in extreme cases, to subjects over a hundred km distant, with no allowance for the effect on the wind direction of local topography or proximity to coasts;

• modelling of the source strength of each line only in terms of the voltage and conductor bundle, without taking into account the other factors which, whilst not yet identified or understood, must affect corona production; and

• applying one representative and simplified distance variation to all points.

Secondly, there are factors that the model does not even attempt to take into account:

For example, as well as blowing the corona ions, the wind could also carry pollution itself, and the amount or type could be associated with wind direction. The meteorological conditions that affect how far ions are carried could also be associated with wind direction. These factors are not included in our model. If they are local factors, such effects would average out across our study, but if they apply consistently across the whole study area, they could constitute a potential confounding factor that we are not able to adjust for. Further, there are many sources of ions other than corona, such as combustion products, from transport, industry and gas cooking, waterfalls, etc, which will lead to misclassification; and there will be geographical variations of any airborne pollutants with which the corona ions interact.

And thirdly:

Further, our test relates only to childhood cancers, not to other diseases.

So overall, the fact that this test came out negative is significant (at least as far as applying the corona ion theory to childhood cancer is concerned) - but it's not conclusive.

Powerwatch have pointed to many of the limitations listed above but go further:

We claim that the work is badly flawed due to confounders, by mistakes in scientific modelling and lack of adequate knowledge of weather patterns and aerosol science leading to almost meaningless data. It really stood no chance of properly judging the hypothesis....

Overall we conclude that the data and the modelling are both so poor as to render any conclusions fairly worthless, despite the effort that has clearly gone into to the analysis. This paper, which to be fair it admits, fails to prove or disprove Henshaw's corona ion hypothesis. It was clearly incapable of attempting such a feat. We wonder how and why it was published and hope that it is not cited in the future as if it did disprove the hypothesis.

The original authors and Powerwatch seem to be pretty much agreed on what the limitations in the study are.  The difference is that the original authors think that the core of the model does provide valid discrimination between people predicted to have high and low exposure, so it is still OK to draw conclusions despite the limitations; Powerwatch think the limitations are so serious that no conclusions are valid. But neither claim it is definitive.

Declaration: one of the staff at National Grid who maintains this website, John Swanson, is also an author of the paper.

The abstract in full

J. Radiol. Prot. 34 (2014) 873–889

Childhood cancer and exposure to corona ions from power lines: an epidemiological test

J Swanson1 , K J Bunch2 , T J Vincent2 and M F G Murphy2

1 National Grid, 1–3 Strand, London WC2N 5EH, UK

2 formerly Childhood Cancer Research Group, University of Oxford, New Richards Building, Old Road Campus, Headington, Oxford OX3 7LG, UK

Received 12 June 2014, revised 12 September 2014, accepted for publication 1 October 2014

Abstract

We previously reported an association between childhood leukaemia in Britain and proximity of the child’s address at birth to high-voltage power lines that declines from the 1960s to the 2000s. We test here whether a ‘corona-ion hypothesis’ could explain these results. This hypothesis proposes that corona ions, atmospheric ions produced by power lines and blown away from them by the wind, increase the retention of airborne pollutants in the airways when breathed in and hence cause disease. We develop an improved model for calculating exposure to corona ions, using data on winds from meteorological stations and considering the whole length of power line within 600 m of each subject’s address. Corona-ion exposure is highly correlated with proximity to power lines, and hence the results parallel the elevations in leukaemia risk seen with distance analyses. But our model explains the observed pattern of leukaemia rates around power lines less well than straightforward distance measurements, and ecological considerations also argue against the hypothesis. This does not disprove the corona-ion hypothesis as the explanation for our previous results, but nor does it provide support for it, or, by extension, any other hypothesis dependent on wind direction.

 

The paper

downlosd the paper itself from the Journal website (currently - Nov 2014 - a "featured article" and therefore free)