DECC’s Dumb Global Calculator Model

On the 28th January 2015, the DECC launched a new policy emissions tool, so everyone can design policies to save the world from dangerous climate change. I thought I would try it out. By simply changing the parameters one-by-one, I found that the model is both massively over-sensitive to small changes in input parameters and is based on British data. From the model, it is possible to entirely eliminate CO2 emissions by 2100 by a combination of three things – reducing the percentage travel in urban areas by car from 43% to 29%; reducing the average size of homes to 95m2 from 110m2 today; and for everyone to go vegetarian.

The DECC website says

Cutting carbon emissions to limit global temperatures to a 2°C rise can be achieved while improving living standards, a new online tool shows.

The world can eat well, travel more, live in more comfortable homes, and meet international carbon reduction commitments according to the Global Calculator tool, a project led by the UK’s Department of Energy and Climate Change and co-funded by Climate-KIC.

Built in collaboration with a number of international organisations from US, China, India and Europe, the calculator is an interactive tool for businesses, NGOs and governments to consider the options for cutting carbon emissions and the trade-offs for energy and land use to 2050.

Energy and Climate Change Secretary Edward Davey said:

“For the first time this Global Calculator shows that everyone in the world can prosper while limiting global temperature rises to 2°C, preventing the most serious impacts of climate change.

“Yet the calculator is also very clear that we must act now to change how we use and generate energy and how we use our land if we are going to achieve this green growth.

“The UK is leading on climate change both at home and abroad. Britain’s global calculator can help the world’s crucial climate debate this year. Along with the many country-based 2050 calculators we pioneered, we are working hard to demonstrate to the global family that climate action benefits people.”

Upon entering the calculator I was presented with some default settings. Starting from a baseline emissions in 2011 of 49.9 GT/CO2e, this would give predicted emissions of 48.5 GT/CO2e in 2050 and 47.9 GT/CO2e in 2100 – virtually unchanged. Cumulative emissions to 2100 would be 5248 GT/CO2e, compared with 3010 GT/CO2e target to give a 50% chance of limiting warming to a 2°C rise. So the game is on to save the world.

I only dealt with the TRAVEL, HOMES and DIET sections on the left.

I went through each of the parameters, noting the results and then resetting back to the baseline.

The TRAVEL section seems to be based on British data, and concentrated on urban people. Extrapolating for the rest of the world seems a bit of a stretch, particularly when over 80% of the world is poorer. I was struck first by changing the mode of travel. If car usage in urban areas fell from 43% to 29%, global emissions from all sources in 2050 would be 13% lower. If car usage in urban areas increased from 43% to 65%, global emissions from all sources in 2050 would be 7% higher. The proportions are wrong (-14% gives -13%, but +22% gives +7%) along with urban travel being too high a proportion of global emissions.

The HOMES section has similar anomalies. Reducing the average home area by 2050 to 95m2 from 110m2 today reduces total global emissions in 2050 by 20%. Independently decreasing average urban house temperature in 2050 from 17oC in Winter & 27oC in Summer, instead of 20oC & 24oC reduces total global emissions in 2050 by 7%. Both seem to be based on British-based data, and highly implausible in a global context.

In the DIET section things get really silly. Cutting the average calorie consumption globally by 10% reduces total global emissions in 2050 by 7%. I never realised that saving the planet required some literal belt tightening. Then we move onto meat consumption. The baseline for 2050 is 220 Kcal per person per day, against the current European average of 281 Kcal. Reducing that to 14 Kcal reduces global emissions from all sources in 2050 by 73%. Alternatively, plugging in the “worst case” 281 Kcal, increases global emissions from all sources in 2050 by 71%. That is, if the world becomes as carnivorous in 2050 as the average European in 2011, global emissions from all sources at 82.7 GT/CO2e will be over six times higher the 13.0 GT/CO2e. For comparison, OECD and Chinese emissions from fossil fuels in 2013 were respectively 10.7 and 10.0 GT/CO2e. It seems it will be nut cutlets all round at the climate talks in Paris later this year. No need for China, India and Germany to scrap all their shiny new coal-fired power stations.

Below is the before and after of the increase in meat consumption.

Things get really interesting if I take the three most sensitive, yet independent, scenarios together. That is, reducing urban car use from 43% to 29% of journeys in 2050; reducing the average home area by 2050 to 95m2 from 110m2; and effectively making a sirloin steak (medium rare) and venison in redcurrant sauce things of the past. Adding them together gives global emissions of -2.8 GT/CO2e in 2050 and -7.1 GT/CO2e in 2100, with cumulative emissions to 2100 of 2111 GT/CO2e. The model does have some combination effect. It gives global emissions of 3.2 GT/CO2e in 2050 and -0.2 GT/CO2e in 2100, with cumulative emissions to 2100 of 2453 GT/CO2e. Below is the screenshot of the combined elements, along with a full table of my results.

It might be great to laugh at the DECC for not sense-checking the outputs of its glitzy bit of software. But it concerns me that it is more than likely the same people who are responsible for this nonsense are also responsible for the glossy plans to cut Britain’s emissions by 80% by 2050 without destroying hundreds of thousands of jobs; eviscerating the countryside; and reducing living standards, especially of the poor. Independent and critical review and audit of DECC output is long overdue.

Kevin Marshall


A spreadsheet model is also available, but I used the online tool, with its’ excellent graphics. The calculator is built by a number of organisations.

Global Emissions Reductions Targets for COP21 Paris 2015

There is a huge build-up underway for the COP21 climate conference to be staged in Paris in November. Many countries and NGOs are pushing for an agreement that will constrain warming to just 2oC, but there are no publicly available figures of what this means for all the countries of the world. This is the gap I seek close with a series of posts. The first post is concerned with getting a perspective on global emissions and the UNIPCC targets.

In what follows, all the actual figures are obtained from three primary sources.

  • Emissions data comes from the Carbon Dioxide Information Analysis Centre or CDIAC.
  • Population data comes from the World Bank, though a few countries are missing. These are mostly from Wikipedia.
  • The Emissions targets can be found in the Presentation for the UNIPCC AR5 Synthesis Report.

All categorizations and forecast estimates are my own.

The 1990 Emissions Position

A starting point for emissions reductions is to stabilize emissions to 1990 levels, around the time that climate mitigation was first proposed. To illustrate the composition emissions I have divided the countries of the world into the major groups meaningful at that time – roughly into First World developed nations, the Second World developed communist countries and the Third World developing economies. The First World is represented by the OECD. I have only included members in 1990, with the USA split off. The Second World is the Ex-Warsaw pact countries, with the countries of the former Yugoslavia included as well. The rest are of the world is divided into five groups. I have charted the emissions per capita against the populations of these groups to come up with the following graph.

In rough terms, one quarter of the global population accounted for two-thirds of global emissions. A major reduction on total emissions could therefore be achieved by these rich countries taking on the burden of emissions reductions, and the other countries not increasing their emissions, or keeping growth to a minimum.

The 2020 emissions forecast

I have created a forecast of both emissions and population for 2020 using the data up to 2013 for both emissions and population. Mostly these are assuming the same change in the next seven years as the last. For emissions in the rapidly-growing countries this might be an understatement. For China and India I have done separate forecasts based on their emissions commitments. This gives the following graph.

The picture has changed dramatically. Population has increased by 2.4 billion or 45% and emissions by over 80%. Global average emissions per capita have increased from 4.1 to 5.2t/CO2 per capita. Due to the population increase, to return global emissions to 1990 levels would mean reducing average emissions per capita to 2.85t/CO2.

The composition of emissions has been even more dramatic. The former First and Second World countries will see a slight fall in emissions from 14.9 to 14.0 billion tonnes of CO2 and the global share will have reduced from 68% to 36%. Although total population will have increased on 1990, the slower growth than elsewhere means the share of global population has shrunk to just 19%. China will have a similar population and with forecast emissions of 13.1 billion tonnes of CO2, 33% of the global total.

The picture is not yet complete. On slide 30 of their Synthesis Report presentation the UNIPCC state

Measures exist to achieve the substantial emissions reductions required to limit likely warming to 2oC (40-70% emissions reduction in GHGs globally by 2050 and near zero GHGs in 2100)

The baseline is 2011, when global emissions were 29.74 billion t/CO2. In 2050 global population will be nearly nine billion. This gives an upper limit of 2.2 t/CO2 per capita and lower limit of 1.1 t/CO2 per capita.

To put this in another perspective, consider the proportions of people living in countries that need emissions targets based on greater than 2.2t/CO2 emissions per capita.

In 1990, it was just a third of the global population. In 2020 it will be three quarters. No longer can an agreement on constraining global CO2 emissions be limited to a few countries. It needs to be truly global. The only area that meets the target is Africa, but even here the countries of Algeria, Egypt, Libya, Tunisia and South Africa would need to have emission reduction targets.

Further Questions

  1. What permutations are possible if other moral considerations are taken into account, like the developed countries bear the burden of emission cuts?
  2. What targets should be set for non-fossil fuel emissions, such as from Agriculture? Are these easier or harder to achieve than for fossil fuels?
  3. What does meeting emission targets mean for different types of economies? For instance are emission reductions more burdensome for the fast-growing emerging economies that for the developed economies?
  4. What are the measures that IPCC claims exist to reduce emissions? Are they more onerous than the consequences of climate change?
  5. Are there in place measures to support the states dependent on the production of fossil fuels? In particular, the loss of income to the Gulf States from leaving oil in the ground may further destabilize the area.
  6. What sanctions if some countries refuse to sign up to an agreement, or are politically unable to implement an agreement?
  7. What penalties will be imposed if countries fail to abide by the agreements made?

Kevin Marshall

Why no country should sign up to Climate Mitigation at Paris 2015

The blog “the eco experts“, has produced a map of the countries most likely to survive climate change.

The most populous country with a high risk is India. In fact it has more people than the 50+ nations of Africa, or nearly twice the population of the OECD – the rich nations club. It is determined not to constrain the rapid growth in emissions if it means sacrificing the rapid economic growth that is pulling people out of poverty. Is this sensible when rapidly increasing its emissions create the prospect of dangerous climate change?

Look at the pattern of vulnerability.

Why is Mongolia more vulnerable than Russia or China?

Why is Haiti more vulnerable than Guatemala & El Salvador, which in turn are more vulnerable than Mexico, which in turn is more vulnerable than the USA?

Why are Syria and Iraq more vulnerable than Iran, which in turn is more vulnerable than Saudi Arabia, which is in turn more vulnerable than the UAE?

Why is Madagascar more vulnerable than Tanzania, which in turn is more vulnerable than South Africa, which is in turn more vulnerable than Botswana?

The answer does not lie in the local climate system but in the level of economic development. As with natural extreme weather events, any adverse consequences of climate change will impact on the poorest disproportionately.

In the light of this, should India

  1. Agree to sacrifice economic growth to constrain emissions, having a significant impact on global emissions and maybe encouraging others to do likewise?


  2. Continue with the high economic growth (and hence emission growth) strategy knowing that if catastrophic climate change is real the population will be better able to cope with it, and if inconsequential they will have sacrificed future generations to a trivial problem?


  3. Continue with the high economic growth (and hence emission growth) strategy and invest in more accurately identifying the nature and extent of climate change?

Now consider that any Government should be first and foremost responsible for the people of that country. If that can be best progressed by international agreements (such as in trade and keeping global peace) then it is the interests of that country to enter those agreements, and encourage other nations to do likewise. Global peace and globalisation are win-win strategies. But climate change is fundamentally different. It is a prospective future problem, the prospective harms from which are here clearly linked to stage of economic development. Combating the future problem means incurring costs, the biggest of which is economic growth. Technologically, there low-cost solutions are in place, and there is no example of any country aggressively weeding out ineffectual policies. Even if there were effective policies in in theory, for costs to exceed benefits would mean every major country either drastically cutting emissions (e.g. the OECD, China, Russia, Saudi Arabia, South Africa) or drastically constraining future emissions growth (India, Brazil, Indonesia, Vietnam, Thailand, plus dozens of other countries). If some countries fail to sign up then policy countries will be burdened with the certain actual costs of policy AND any residual possible costs of policy. Responsible countries will duck the issue, and, behind the scenes, help scupper the climate talks in Paris 2015.

Kevin Marshall

Veritasium Misinforms on Global Warming

Bishop Hill posts on a You-tube video “13 Misconceptions About Global Warming” from Veritasium (Dr Derek Muller), inviting readers to play a sort of bingo to “spot all the strawmen arguments, cherrypicking, out of date data, and plain old mistakes”. Here is my attempt, restricted to just 13 points.

  1. “Global warming” / “climate change” naming. It might be true that people can deny global warming by pointing to a localized cold weather snap. But it is also true that using the term “climate change” can result in any unusual weather event or short-term trend being blamed on anthropogenic global warming, along with natural global fluctuations. The term “global warming” reminds us that the adverse effects on climate are as a result of rising greenhouse gas levels warming the atmosphere. More importantly the use of the term “global” reminds us those changes in climate due to changes in greenhouse gases is a global issue requiring global solutions. Any mitigation policy that excludes 80% of the global population and two-thirds of global carbon emissions, will not work.


  2. Veritasium claims climate change is also about more extreme weather and ocean acidification, not just the average surface temperature is warming. But there is nothing in the greenhouse gas hypothesis that says a rise in temperatures will result in more extreme weather, nor does Veritasium provide the evidence of this happening. At Wattupwiththat there is a page that demonstrates weather is not getting more extreme from a number of different measures.


  3. Claim that it has not stopped warming as 13 of the 14 hottest years are in this century. This is a strawman, as there was significant warming in the last quarter of the twentieth century. We would only fail to have hottest years if global average temperatures had taken a sharp step decrease.


  4. Claims that taking the satellite data of global temperature anomalies into account shows that warming has not stopped. From Kevin Cowtan’s page (copied by Skeptical Science) we can calculate linear trends. It is the RSS satellite data that shows the longest period of no warming – 18 years from 1997-2014 based on the linear trend. It is just 13 years for GISTEMP and 14 years for HADCRUT4. The other satellite data is UAH, where there is just 6 years of no warming.



  5. What he is doing is comparing UAH satellite data that only shows the pause from 2009. There is now 35 years of satellite data, with the total recorded trend of 0.48oC. The RSS data shows 0.51oC of warming. The surface thermometer measures vary between 0.59 and 0.63 oC of warming. This is data cherry-picking.


  6. There is a claim that climate sensitivity is lower than thought in the 1980s. Not according to Nicholas Lewis, who found that the range of sensitivities is unchanged from the Charney Report 1979 through to AR5 WG1 of Sept-13


  7. Claims the central estimate for warming from a doubling of CO2 is 3.0oC of warming. Based on this from 2001 from HADCRUT4 shows no warming there would be 0.30oC of warming, when the trend from HADCRUT4 is zero. In a longer period from 1979 for which we have satellite data, an increase in CO2 from 336.8 to 398.5 ppm (Mauna Loa data) implies an increase in temperatures of 0.72oC – between 1.14 on 1.5 times greater than that measured by the temperature series. Even this is misleading, as there was no warming from 1944 to the late 1970s. In 1944 I estimate that CO2 levels were 308ppm, indicating a total warming in the last 70 years of 1.1oC, respectively 1.7 and 2.1 times greater than the trend in GISTEMP and HADCRUT4.


  8. This would appear to contradict this graph, which has no proper labelling showing have 3.0oC of doubling affects temperatures.

    Specifically from 1958 to 1980 CO2 rose from 315 to 339ppm, indicating warming of about 0.31 oC, but there was no warming in the IPCC projections. A rise in CO2 of 315 to 398.5 ppm from 1958 to 2014 would predict 1.0 oC in warming, almost double the actual data and the IPCC projections. Another point is with the “observed temperature”. It is not identified (probably GISTEMP) and ends on the high of 2010.


  9. Completely ignores the other greenhouse gases that contribute to warming, such as methane and halocarbons.


  10. Claims that sea level rise is another indication of global warming, through thermal expansion. This is not necessarily the case. The average temperature of the ocean is 3.9oC. A rise of to 4.0 oC will have zero expansion. If the rise in sea temperatures is confined to the Arctic or in the deep oceans where temperatures are below 4.0 oC, a rise in temperatures would mean a fall in sea levels. Below I have compiled a graph to show the expansion of a 100metre column of water by 0.1 oC from various starting temperatures.


  11. On Arctic Sea ice, is correct in saying that the 40% uptick in the last two years ignores the longer period of data. But in turn, Veritasium ignores evidence pre-satellites that were fluctuations in sea ice. Further, the uptick occurred at precisely the year when previous experts had predicted that summer sea ice cover would disappear. As a consequence, contraction of the sea ice is both less severe and less likely to be linked to human-caused warming than previously thought.


  12. Correctly points out that water vapour is the major greenhouse gas, but incorrectly claims to have evidence that water vapour is increasing in the atmosphere. The evidence is from a graphic from a 2007 PNAS paper.

    The evidence from 1900 is the average of 12 models. The confidence intervals are utter rubbish, appearing to be related to the magnitude of the average modelled anomaly. The actual (estimated) data in black does not have a confidence interval. It would appear that this estimated data has a step increase at roughly the time, or slightly before, when the warming stopped in the surface temperature records.


  13. Policy justification is totally wrong.

Veritasium says at 5.35

I’m not claiming it’s going to be some sort of crazy catastrophe, but we are going to get more intense storms, more droughts and floods, the oceans will become more acidic, sea levels will rise and my point is it would be better for all species on this planet and probably cheaper for us if we just started reducing emissions now than if we wait and pay the consequences later.

Every economic justification of policy projects “some sort of crazy catastrophe” that human being and other species will not be able to adapt to. Further they project that global emissions reductions will be both effective and relatively costless, which is contradicted by the evidence. But most of all, there is no political proposal in the climate talks that will reduce global emissions in the next twenty years. The proposals may only constrain the rate of increase.

Kevin Marshall

The Truth About Davey’s Energy Savings


Ed Davey’s claim that the DECC published “a complete picture of everything that affects final energy bills” is refuted by Paul Homewood below.
This is far from an exhaustive list. For instance there are also the costs of upgrading the National Grid to transport the generated the electricity generated in remote wind turbines to the centers of population; the impact on jobs and growth of increasing energy costs relative to other nations;and the more esoteric costs to democracy of having a dogmatic group of people with dogmatic beliefs in a specialist applied subject claiming that this gives them superior insights into public policy-making, policy implementation and economic theory.

Originally posted on NOT A LOT OF PEOPLE KNOW THAT:

By Paul Homewood


Ed Davey has been stung into defending his disastrous energy policies, following revelations that his department had disgracefully attempted to hide data, showing that electricity prices would soon be 40% higher, as a result of climate policies.

The above letter was published in last week’s Sunday Telegraph. Unfortunately, he is being rather economical with the truth.

First, let’s recap on the energy savings which Davey says will make us so much better off. The table below is from the data that DECC tried to hide.


The so-called savings are listed under 2).

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Ed Hoskins: Capital Cost and Production Effectiveness of Renewable Energy in Europe – the Data


Ed Hoskins provides a very wide-ranging analysis on the capital costs of renewables in Europe, with information about all the major countries. Despite total investment of $500bn so far, renewables provide just 2.9% of actual power generated. Hoskins also provides some graphical data on “Intermittency and Non-dipatchability” of energy output, helping highlight that renewables are not just expensive, they are also pretty useless at providing power when required.
The one weakness in the analysis is in the costs per unit of output – something outside the main purpose of the post. The source of that data is the U.S. Energy Information Administration. This uses (Table 2-5 on page 44 of the pdf file) “Overnight Capital Cost” which measures capital and maintenance costs per unit of capacity. So, for instance, “Onshore Wind” appears to have only 2.2 times the capital cost of “Natural Gas Advanced Combined Cycle”. But assuming the former operates at 25% of capacity and the latter at 85%, the capital costs of wind power becomes 7.5 times that of gas. Similarly, assuming offshore wind operates at 35% of capacity, relative capital costs rise from 6.2 to 14.8 times that of gas.

Another point is that the EIA does not consider conventional coal-fired power stations, possibly inflating the price by some measure of “The Social cost of Carbon”. Using the average price in AR4 of $12 per tonne of CO2 (Synthesis Report Page 69) and that a coal-fired power station produces about 500kg per megawatt, this $6 per megawatt is trivial compared with the much higher cost of renewables.

Originally posted on Tallbloke's Talkshop:

Guest post from Ed Hoskins
A comparison of both the Capital Cost and Energy Production Effectiveness of the Renewable Energy in Europe.

The diagrams and table below collate the cost and capacity factors of Renewable Energy power sources, Onshore and Off-shore Wind Farms and Large scale Photovoltaic Solar generation, compared to the cost and output capacity of conventional Gas Fired Electricity generation.

Screen Shot 2014-12-16 at 08.16.07

The associated base data is shown below:

View original 2,794 more words

Nissan Leaf Fails The Test


Paul Homewood has a very useful comparison between the cost of the electric Nissan Leaf car and a couple of super-efficient Ford Focuses. The electric car turns out to be a much worse buy. But looking at the costs of motoring to the consumer, and the tax costs can be complex, so there are a couple of points that I would amend.
First is that the £5000 rebate on an electric car is relevant to the buying decision. Otherwise it would not be in place. The purchaser of the car ends up paying £5000 less, so that is a reduction in both the depreciation and the borrowing they will face. As a result the annual cost differential on your figures reduces from £3200 to £1350. However, due to the differential in maintenance this figure is more like £1700.
Second is the difference in tax revenue. New cars attract 20% VAT. For the Leaf this is £4750. After the rebate, the exchequer gives out £250. VAT on the focus Focus Diesel is about £3300. In 3 years, the net tax revenue on the Leaf (purchase price, 5% VAT on electricity, 20% VAT in maintenance) is £50. On both Fords it is £5100.
The figures, by chance, fall out the same. Buy a Nissan Leaf instead of a Ford Focus and both you and the Exchequer will be about £5000 worse off over three years.
The differences do not stop there. As AC Osborn rightly points out there is a problem with range. The Leaf is limited to about 100 miles before a recharge of over four hours. As such, for families, it becomes a second car, whereas the a Focus with a range of at least 400 miles and a five minute refill can both serve for the school run / daily commute and for longer trips as well. An electric car becomes more of a lifestyle car, so on cost the Leaf is competing with an Audi A3 or similar.
Kevin Marshall

Originally posted on NOT A LOT OF PEOPLE KNOW THAT:

By Paul Homewood

With oil prices falling through the floor, and confirmation of just how much electricity prices are going to rise in the next few years, it is time to look again at the comparative costs of electric and conventional cars.

The Nissan Leaf seems to be the most popular electric car in the UK, and is comparable, from a specification point of view, to the Ford Focus. The Leaf Acenta is the mid range version, and can be compared with the Focus Zetec, which I have shown for both the 1.6 TDCi diesel and Eco 1.0 petrol options.

So first, some basic costs and specifications.

View original 653 more words

Has NASA distorted the data on global warming?

The Daily Mail has published some nice graphics from NASA on how the Earth’s climate has changed in recent years. The Mail says

Twenty years ago world leaders met for the first ever climate change summit but new figures show that since then the globe has become hotter and weather has become more weird.

Numbers show that carbon dioxide emissions are up, the global temperature has increased, sea levels are rising along with the earth’s population.

The statistics come as more than 190 nations opened talks on Monday at a United Nations global warming conference in Lima, Peru.

Read more:

Follow us: @MailOnline on Twitter | DailyMail on Facebook

See if anyone can find a reason for the following.

  1. A nice graphic compares the minimum sea ice extent in 1980 with 2012 – nearly three month after the 2014 minimum. Why not use the latest data?

  2. There is a nice graphic showing the rise in global carbon emissions from 1960 to the present. Notice gradient is quite steep until the mid-70s; there is much shallower gradient to around 2000 when the gradient increases. Why do NASA not produce their temperature anomaly graph to show us all how these emissions are heating up the world?

    Data from


  3. There is a simple graphic on sea level rise, derived from the satellite data. Why does the NASA graph start in 1997, when the University of Colorado data, that is available free to download, starts in 1993?



Some Clues

Sea Ice extent

COI | Centre for Ocean and Ice | Danmarks Meteorologiske Institut

Warming trends – GISTEMP & HADCRUT4

The black lines are an approximate fit of the warming trends.

Sea Level Rise

Graph can be obtained from the University of Colorado.


NB. This is in response to a post by Steve Goddard on Arctic Sea Ice.

Kevin Marshall

Proximity to Natural Gas Wells and Reported Health Status Study

A new study has been publisheda tentatively suggesting that there are significant health effects for those living in close proximity to gas fracking sites. The study may make headlines despite the authors expressly stating that the results should be viewed as ‘hypothesis generating’. There are a number of problems with the survey which could indicate small sample size and biases in adjusting for other factors account for the difference. Alternatively there is also the possibility that reported health effects of living near the fracking sites is due to stress from the false perceptions of the risks of living near to a fracking site. Anti-fracking environmentalists may be damaging people’s health and happiness through misinformation.

The study is

Proximity to Natural Gas Wells and Reported Health Status: Results of a Household Survey in Washington County, Pennsylvania (Environ Health Perspect; DOI:10.1289/ehp.1307732)

Peter M. Rabinowitz, Ilya B. Slizovskiy, Vanessa Lamers, Sally J. Trufan, Theodore R. Holford, James D. Dziura, Peter N. Peduzzi, Michael J. Kane, John S. Reif, Theresa R. Weiss, and Meredith H. Stowe


The households were split into three groups based on distance from a gas well. <1km (62 households), 1-2km (57) & >2km (61). The major result was

The number of reported health symptoms per person was higher among residents living <1 km (mean 3.27 ± 3.72) compared with >2 km from the nearest gas well (mean 1.60 ± 2.14, p=0.02).

The study also found significantly higher incidences in two out of five health symptoms in the <1km group than in >2km group.

There are multiple reasons for expecting these tentative results will not be replicated.

  • The small sample size for a very complex set of data.
  • Perceived water quality is not related to fracking.
  • Failure to control properly for obesity and smoking
  • Failure to repeat the sampling process with the same model.
  • Failure to corroborate the results by checks for actual contamination.
  • Biases in answering the questions.


  1. Small sample size

There is an obvious problem with the health status study. The sample size was reported as the sample size of 180 households with 472 people, too small to generate meaningful results when there are a number of inter-related factors involved.

Consider how this sample was selected. To select these households the researchers randomly selected 20 points on a map in each of 38 townships. On a map they located the nearest house to the spot. The researchers were concerned with the possible impact of fracking on ground fed water supplies, which only applied to a minority of households. This was the main reason for reducing the sample From 760 data points to 227 households. 47 refusals reduced this to down to the 180 households for which questionnaires were received. They then put the data through a model “that adjusted for age, gender, household education, smoking, awareness of environmental risk, work type, and animals in house.”

The results were based on comparing two sample groups – one with 62 households and 150 people, the other with 61 households with 192 people. The >2km households were 30% larger than the <1km group, and the average age was 7 years lower. Not only were the numbers small, but there were material differences in the sample groups. It was necessary to adjust for

  1. Perceived water quality is not related to fracking.

Sixty-six percent reported using their ground-fed water (well or natural spring) for drinking water and 84% reported using it for other activities such as bathing.

If there were health effects from contaminated water due to fracking, then there should be a difference in distance between those who drank the water and those who did not. But although there were more households who said the water has an unnatural appearance near the in the <1km group, (13/62 for <1km v 6/61 for >2km), the position was reversed when for those who said taste/odour prevented water use (14/62 for <1km v 19/61 for >2km). If people believed there was a problem with the water due to fracking, then those living near the wells might be more likely to avoid drinking the water than those further away. It was not the case. The proportions drinking the water were the same. It would appear that water quality is generally considered poor in the area. This point can be demonstrated by water sampling.

  1. Failure to control properly for obesity and smoking

Obesity and smoking have long-been accepted as having consequences for health. The questionnaire is in the Supplemental Material. For obesity it asks the respondent their height and weight, but not the height and weight of the other members of the household. For smoking the question is

Does anyone in this household smoke regularly inside the house?

Smoking causes health problems independent of whether someone smokes inside their home or not. Also the numbers of people smoking in a household matters, along with the number of years smoked and the quantity of cigarettes smoked.

  1. Failure to repeat the sampling process with the same model.

The model that filtered out other elements could have had some very large biases within it. For instance, the model could have over-adjusted for smoking. Conducting a completely fresh survey with the same sampling method would have eliminated this possibility.

  1. Failure to corroborate the results by checks for actual contamination.

If there were actual health issues water contamination or air contamination, then there should be some evidence in water and air samples. The authors did not consult any actual monitoring results to show contamination. In the case of water quality In the case of air quality they threw everything at the issue, including ‘operation of diesel equipment and vehicles‘. If there was something in the air and/or in the water that is causing real health problems, then it will be something that cannot be perceived.

  1. Biases in answering the questions.

In the introduction the authors say

A convenience sample survey of 53 community members living near Marcellus Shale development found that respondents attributed a number of health impacts and stressors to the development. Stress was the symptom reported most frequently (Ferrar et al. 2013).

The study said

We found instead that the refusal rate, while less than 25% overall, was higher among households farther from gas wells, suggesting that such households may have been less interested in participating due to lesser awareness of hazards.

If participation was higher in people nearer to wells because of perceived hazards, and the people get stressed by this. It could be that this stress exacerbates the symptoms and/or people on hearing stories of possible health effects notice their own conditions more. That is, the results of reported health effects of living near fracking sites may be to some extent real, but caused by the stress of believing the scare stories. This could be coupled with the fears of resulting in people remembering minor health symptoms, as there might be a cause. This alone could explain why the number of reported symptoms was twice the level for people living near to the gas wells. Conducting a similar, but larger survey with both dwellings where water is mains supplied and from ground-fed wells. If there is “something in the water”, then those who are mains supplied would not suffer from health effects to the same degree.

  1. Thanks to commentator “Entropic Man” at a Bishop-Hill discussion thread for alerting me to this study.

Kevin Marshall

Climategate : The greatest quote is from Kevin Trenberth

As Paul Matthews at IPCC Report and Anthony Watts at Wattsupwiththat are pointing out, 17th November marked the 5th Anniversary of Climategate1. Paul Matthews has his pick of the most significant quotes. But I believe he misses the most important. Kevin Trenberth to Micheal Mann on Mon, 12 Oct 2009 and copied to most of the leading academics2

The fact is that we can’t account for the lack of warming at the moment and it is a travesty that we can’t. The CERES data published in the August BAMS 09 supplement on 2008 shows there should be even more warming: but the data are surely wrong. Our observing system is inadequate. (emphasis mine)

The first sentence is the mostly widely quoted. It is an admission that we, the experts, cannot explain what is happening. The end of the quote is even more important. There is a clear divergence between the predictions from the climate models – the theoretical understanding of the world – and the real world data. Trenberth’s reaction is that the data is wrong, not the theory. His later excuse for continuing belief in the climate models was coined a few months later. The truth is lurking in the murky depths. As with the mythical Loch Ness Monster, the believers in climate catastrophism hold that the evidence will be found, but we are not able to access it yet. This has created a new branch of climatology – the excuses for the pause. At the time of writing there are 65 excuses and new cases are appearing at more than two a week.

Kevin Marshall


  1. The term Climategate was coined by James Delingpole on 20th November 2009.
  2. Cc: Stephen H Schneider , Myles Allen , peter stott , “Philip D. Jones” , Benjamin Santer , Tom Wigley , Thomas R Karl , Gavin Schmidt , James Hansen , Michael Oppenheimer. This was an email between the high priests of the global warming movement.

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