Renewable Energy in Europe = Wood = Killing Trees

As of 2016 you can see from this graph that renewable energy for a lot of Europe really just means wood.

The red bar is woods percentage of renewables.

The green bar is wood share of total energy.

For example, Estonia gets 90% of its renewable energy from wood.

Green energy means killing trees.

Estonia is killing trees.

In April 2018, representatives from the international forest movement gathered in Estonia to discuss the protection of forests and peoples’ rights. While there, they learned about the serious threats to Estonia’s forests.  

One significant threat to forests is a planned biorefinery close to Tartu, in the east of the country. The biorefinery would use a quarter of Estonia’s annual wood production (approximately 3.3 million m3 of wood), and the impact on the environment is immense: between 2001 and 2015, 285,000 hectares of the country’s forests were lost, despite warnings from the Estonian Academy of Sciences that the logging was compromising healthy and resilient ecosystems. For example, habitat for several birds and the flying squirrel, a species protected by the EU Habitats Directive, decreased significantly.  

While the national government continues to ignore local resistance against the biorefinery project, the international forest movement published a statement supporting the people of Tartu in their fight to have it stopped. 

The expansion of the biorefinery and other ongoing projects in Estonia are a perfect example of how the EU’s renewable energy directive (RED) can backfire. The EU allows its Member States to subsidise the production of energy from wood, and Estonia has taken this seriously: between 2009 (introduction of the RED) and 2016, renewable energy production from wood grew by more than 65 per cent, accompanied by an ominous increase in logging. This has also negatively affected Estonian forests’ role in mitigating climate change: between 2005 and 2030, it is projected that the country’s forests will turn from a sink into a source of emissions. Currently, Estonia already harvests 90 per cent of its annual forest growth.  

Estonia plans to ‘trade’ a surplus of its renewable energy with other EU countries. But the EU should be warned that this comes at the expense of a considerable forest and climate deficit. 

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Electricity pricing in California will cause old people to not use life saving air conditioning in heat waves

The electrical pricing is setting old people up to not use the air conditioning that they may truly need at some point to save their life.

Steeply tiered electricity costs can nail people with electricity bills of $200-500 or more in months where they use several hours of air conditioning in one day in California and South Korea and many other countries.

 

https://www.nextbigfuture.com/2018/08/affordable-electricity-and-air-conditioning-is-needed-during-heat-waves-in-california-and-south-korea.html

 

 

Evolving at Unprecedented Speed

Wait! I thought Animals Were Fixed In Stone and Couldn’t Change or Adapt?

Sprawling cities are forcing animals to evolve at ‘unprecedented speeds’ in an effort to survive their urban environments

  • Comments were made by Professor Menno Schilthuizen at Leiden University
  • ‘I think Darwin underestimated the speed [that evolution] can happen,’ he said
  • Cities have forced great tits to learn to open caps off milk bottles and lizards have  developed stickier feet to climb up buildings

Our cities are ‘powerhouses of evolution’ where animals are adapting to their environment at ‘unprecedented speeds’.

That’s according to evolutionary biologist Menno Schilthuizen who claims that, far from being desolate wastelands, cities are helping create new species.

Professor Schilthuizen, who is author of ‘Darwin Comes to Town’, claims humans are helping speed up this process, with some surprising results.

Our cities are ‘powerhouses of evolution’ where animals are adapting to their environment at 'unprecedented speeds'. For instance, bobcats in Hollywood have evolved to be genetically different from those living north of the 101 freeway

Our cities are ‘powerhouses of evolution’ where animals are adapting to their environment at ‘unprecedented speeds’. For instance, bobcats in Hollywood have evolved to be genetically different from those living north of the 101 freeway

In an in-depth interview with National Geographic’s Simon Worrall, Processor Schilthuizen explains how cities are creating a new breed of ‘London Underground Mosquito’.

Despite its name, the London Underground Mosquito can be found all over the world living in underground environments such as basements and subway systems.

The London Underground mosquito can no longer interbreed with its above ground counterpart and is effectively thought to be a new species.

‘I think Darwin underestimated the speed [that evolution] can happen, particularly with species that have numerous generations in a short space of time,’  Professor Schilthuizen, who is also a professor in biodiversity at Leiden University in The Netherlands, told National Geographic.

‘Generation time is the evolutionary clock speed, so if you have multiple generations per year you can accumulate evolutionary changes much more quickly than humans can, for example, which have one generation every 20 years.’

In another example, Professor Schilthuizen highlights the fact that bobcats in Hollywood are now different from those living north of the 101 freeway.

‘Fragmentation in cities is a common theme. In urban ecology humans create all kinds of barriers, like roads and highways,’ said Professor Schilthuizen.

The London Underground mosquito can no longer interbreed with its above ground counterpart and is effectively thought to be a new species

The London Underground mosquito can no longer interbreed with its above ground counterpart and is effectively thought to be a new species

‘North of Los Angeles, the bobcat population is divided by two very large highways, which bisect the area where they live.

‘These barriers cause something similar to what happens to mosquitoes in the London subway lines, whereby evolution is restricted to the areas cut off from other populations.’

Read more: http://www.dailymail.co.uk/sciencetech/article-5698733/Cities-forcing-animals-evolve-unprecedented-speeds.html

 

German Electricity March 26 2018

Lets say its March 26th 2018 8pm in Germany and there is about 59GW of demand to keep the country functioning and you are a greenie looking forward to a day when there is no more nuclear or CO2 producing power plants..

Ooops.

0.00GW from solar.

1.13GW from wind.

9.27GW from nuclear. 

45.5GW from CO2 producing power plants (gas, coal, biomass, oil)

 

Alberta Hot Old Data Purged?

In my previous post I looked at July averages by decade for Alberta. Go back and read the intro.

In this post I change the selection criteria to allow stations without data in 2017. But kept the other criteria.

I can’t help but think they purged the “hot old” stations to make Albertans think it is getting hotter as of now.

Look at the stations with the 1930s as the hottest decade Tmax July (even with some 2010s data)

 

Station Station No Records Min Year Max Year pct of data 2010s 2000s 1990s 1980s 1970s 1960s 1950s 1940s 1930s 1920s 1910s 1900s 1890s 1880s
LETHBRIDGE CDA 3033890 104 1908 2015 96.3 33.4 35.1 31.8 33 33.4 32.7 32.8 33.5 35.1 32.9 33.5 33
CAMPSIE 3061200 100 1913 2013 99 29.8 31.8 28.8 29.9 28.6 30.4 29.9 30.8 30.7 32.1 29.3
OLDS 3024920 97 1914 2013 97 29.5 30.6 27.6 29.2 30.2 30.4 30.1 31.3 31.8 30.6 31.4
RED DEER A 3025480 76 1938 2013 100 29.6 31.2 28.6 30.1 30.6 31.3 30.2 31.3 31.7
CALGARY INT’L A 3031093 129 1884 2012 100 29.6 31.8 29.8 31.2 31.6 31.2 30.5 31.6 33.8 33 31.7 30 32.4 30.5
BEAVER MINES 3050600 76 1935 2011 98.7 30 31.8 29.1 30.9 30.4 29.7 30.3 31.1 33.1
WHITECOURT LO 3067392 63 1939 2011 86.3 24.8 26.6 24.5 25.9 24.6 25.8 26 27.1 28.3
CARROT CREEK LO 3061360 62 1939 2011 84.9 26.5 29.7 27.1 27.8 27.6 27.2 27.2 29.4 30
CARWAY 3031400 87 1915 2010 90.6 30 32.4 29.1 30.8 30.3 29.6 30.2 31.2 33.9 32 31.1
MEDICINE HAT A 3034480 125 1884 2008 100 36.4 33.8 34.8 35.2 34.9 36.1 36.7 38.9 36.9 36.6 35.3 36.2 34.7
LETHBRIDGE A 3033880 71 1938 2008 100 35.6 32 33.4 34.3 33.9 33.8 34.9 38
CALMAR 3011120 89 1916 2007 96.7 30.4 27.8 29.5 29.4 30.7 30.4 31.4 31.8 31.1 29.6
LAKE LOUISE 3053760 88 1915 2007 94.6 29.5 27.8 27.7 28.5 28.7 28.5 29.6 30.5 29.5 29.2
GLEICHEN 3032800 101 1903 2005 98.1 34.4 31.1 33.1 33.2 32.2 31.7 32.9 35.5 32.9 32.8 31.9
HIGH RIVER 3033240 95 1903 2005 92.2 32.5 29.1 31.2 31 30.6 30.4 31.3 34.9 31.7 33.1 31
BEAVERLODGE CDA 3070560 91 1913 2005 97.8 28.3 28.4 29.8 28.1 30.1 29.6 30.5 29.9 30.3 29
ENTRANCE 3062440 82 1918 2005 93.2 30.2 29.8 31.3 30.1 30.2 30.4 32.3 32.7 32.2 33.2
SION 3015960 88 1911 2004 93.6 30.9 28.7 29.8 28.6 30.3 30.7 32 31.7 31 30.3
CARDSTON 3031320 82 1919 2004 95.3 34.7 30.5 32.1 32.2 31.5 32.3 32.4 35.3 32.8 36.1
FOREMOST 3032640 82 1919 2004 95.3 36.5 33 34.1 34.1 34 35.7 36.3 38.7 35.7 39.4
EDMONTON CITY CENTRE A 3012208 67 1938 2004 100 31.9 29.1 30.7 30.5 30.9 31 31.2 31.4
VIKING 3016840 66 1923 1997 88 30.1 31.6 31.6 31.7 32.1 32.7 32.9 33
ELK POINT 3012280 79 1912 1996 92.9 30.1 30.6 29.2 31.2 31.6 31.8 32.4 31.6 32
JASPER 3053520 64 1927 1995 92.8 29.1 30.2 31.2 31.3 31.3 32.4 31.1 32.2
BANFF 3050520 102 1890 1994 97.1 29.4 29.9 30.2 29.6 29.9 29.9 31.6 31.4 30.4 29.2 29.3
LACOMBE CDA 3023720 86 1908 1993 100 27.6 30.1 30.1 31.6 30.7 33.3 33.7 33.3 29.8 29.1
PEKISKO 3055120 83 1905 1992 94.3 26.7 29.7 29.1 28.3 28.8 29.3 31.9 29.7 29.6 32.2
RANFURLY 3015400 86 1905 1991 98.9 32 30.6 29.2 30.8 30.9 32.9 32.9 35.5 30.4 28.3
FAIRVIEW 3072520 60 1932 1991 100 31.5 29.1 27.4 29.9 29.3 30.5 29
MANYBERRIES CDA 3044200 62 1929 1990 100 36 34.8 34.5 33.9 35.1 35.6 37.8 34.8
CALDWELL 3031000 56 1932 1990 94.9 29 31.1 30.7 29.4 30.6 32.9 33.7
FORT MACLEOD 3032680 94 1876 1987 83.9 33.4 33.2 32.9 33.8 34.8 36.9 34.6 34.7 33.4 35.5
FORT VERMILION CDA 3072720 78 1908 1985 100 30.7 29.3 30.7 30.2 32 31.1 31.6 30.7 30.5
HANNA 3023000 54 1921 1984 84.4 37 31.4 32.8 33.2 33.5 35.1 33.4
KEG RIVER 3073640 43 1935 1979 95.6 29.4 30 30.8 31.5 30.1
THREE HILLS 3026480 56 1921 1977 98.2 33.5 33.3 32.5 33.8 35.4 35
WASTINA HEMARUKA 3016960 60 1913 1976 93.8 32.4 32.6 32.2 35.3 37.2 34.7 31.3
STETTLER 3016120 57 1919 1976 98.3 29.7 32.2 32 33.2 34.7 30.2 32.2
HIGH PRAIRIE 3063160 47 1927 1976 94 26.6 30.3 29.2 31.9 30.8 29.5
IRON RIVER 3083480 49 1925 1975 96.1 28.8 30.7 30.6 30.7 30.7 31.1
WETASKIWIN 3017280 69 1903 1974 95.8 29.3 31.4 31.1 32.2 33 31.8 30.6 28.7
HUGHENDEN 3013360 35 1935 1971 94.6 30 32.4 33.8 34.4 35
LLOYDMINSTER 3013960 51 1913 1970 87.9 30 31.8 32.9 32.5 33.3 34.1 30.4
BROOKS 1 3030840 56 1912 1968 98.2 33.3 33.2 35.2 36 34.2 33.1
DRUMHELLER 3022120 36 1923 1967 80 34.5 35 35.6 37.2 34.7
ATHABASCA 3060320 42 1918 1965 87.5 31.6 31.7 32.5 30.7 32.2 35
NACO 3014760 35 1930 1965 97.2 32.7 32.9 35.2 36.5
PINCHER CREEK TOWN 3035220 64 1894 1962 92.8 32.8 31.9 32.3 33.7 30.7 30.5 31.2 30.7
STRATHMORE 3036200 49 1912 1962 96.1 31.9 30.4 32.1 34.2 32.9 30.6
SLAVE LAKE 3066000 36 1925 1962 94.7 29.8 29.8 30.2 30.6 28.7
ANTHRACITE 3050240 33 1929 1961 100 31.9 29.1 30.4 32 31.7
HILLSDOWN 3023280 56 1904 1960 98.2 33.9 29.8 30 32.1 32.7 29.4 29.1
EDSON 3062240 43 1916 1959 97.7 29.6 30.4 32 32.6 31.8
BUFFALO HEAD PRAIRIE 3070960 27 1933 1959 100 30.6 31.2 30.2
LUNDBRECK 3054080 39 1913 1958 84.8 29.4 30.9 33.9 30.1 30.1
THORSBY 3016440 26 1932 1958 96.3 29.7 31.7 31.8
SPRINGDALE 3026080 42 1913 1956 95.5 30.5 30.1 30.3 30.2 29
VAUXHALL 3036680 42 1914 1956 97.7 35 34.3 36.7 34.7 35.9
NORDEGG 3054840 36 1916 1954 92.3 30.2 28.9 28.8 29.4 28.6
ELMWORTH 3072320 26 1927 1952 100 31.5 31.4 30.1 29.3
RADWAY 3015345 27 1923 1951 93.1 34.2 32.6 31.3 30.8
ALIX 3020120 43 1906 1949 97.7 34.7 36.4 34.4 31.1 28.1
FT MCMURRAY 3062695 31 1910 1944 88.6 34.2 32.1 32.7 32.6 34.4
GROUARD 3062965 30 1914 1944 96.8 31.7 30.2 31.1 31
EDMONTON 3012195 61 1880 1942 96.8 31.1 32.4 31.8 29.4 29.2 30.6 30.1
HARMATTAN 3023055 30 1908 1938 96.8 31.9 30.4 29.1 26.7
PERBECK 3025170 25 1913 1938 96.2 35.7 33.6 32.4