This is part of the labels / documentation for <a href='http://jcm.chooseclimate.org'>Java Climate Model</a><hr/>

#people		§This module stores population, GDP, and secondary energy data, for the 12 regions (see @aboutregions). 
  £§iobinfo  ££peopleintro ££peoplefuture

#peopleintro		§

Currently this module simply stores data, fixed for each scenario (see @aboutsres.  The socioeconomic data helps to reveal some of the driving forces behind the scenarios.

°adju You can view the socioeconomic data using the @varq menu on @distribplot , and also use it as a divisor to show quantites 'per capita', 'per dollar' etc., using the @perq menus on @distribplot, @attributeplot, @costsplot .

The socioeconomic data is also used for distributing regional CO2 emissions. -see @distribution

#regshares		§This module calculates regional shares of future CO2 emissions according to various @distribution formulae.
  Each region's quota is the product of its share, multiplied by the global emissions from the @mitigation module
  This module also calculates regional emissions abatement, compared to SRES.
  £§iobinfo
  <hr>See also  @aboutregions, @distribution, @convergence, @effectofkyoto, @peoplefuture

#kyoto		§This module calculates the CO2 emissions (regional and total) during the period 2000-2013, if Kyoto option is enabled
  £§iobinfo ££kyotohowwork ££kyotofuture

#distribmenu		§Choose distribution of future emissions between regions, see also @distribution

#percapita		§Emissions allocations converge to reach equal per-capita levels in a target year. If you make a plot of emissions per capita, you can experiment with various adjustable paramaters, and see how the formula works.  <li>@convergence

#grandfather		§Equal percentage reductions from a baseline year:
  The more you polluted in the past, the more emissions quota you get in the  future! This is clearly inequitable, but was the starting point for "burden sharing" negotiations in the Kyoto process.

#sresdist		§This option combines the SRES regional emissions distribution with total emissions fixed by mitigation scenarios.

Note, this option is provided only for <i>comparison</i> with other proposals. As you can see from changing between SRES scenarios, there is no single  "business as usual" projection. With such a variety of possible scenarios, it would be difficult to agree an emissions allocation formula based on deviation from a "baseline". Nevertheless, there is some convergence between richer and poorer countries in all scenarios.  <li>@aboutsres

#unspecified		§Since the future distribution is a controversial policy issue, the default option is "unspecified" (grey colour).You must choose another option to see meaningful curves for emissions and abatement.

#convpergdp		§This option uses the same @convergence formula as @percapita.
  °adju To see adjustable parameters for convergence year (and other expert options), make a @distribplot with @perq set to @gdp.

This is not a serious policy proposal, however it may be illustrative of proposals based on economic efficiency. It's interesting to compare it also with  @reduceintensity, which is effectively grandfathering of emissions per GDP.

#brazil		§Allocation of emissions reductions based on attribution of responsibility for climate change.

JCM is now participating in the UNFCCC assessment of the scientific aspects of this proposal. For more about this see:   <li>@attribution, @attributeplot, and @responsibility
  ²Note: this distribution option is not working in the latest version, because the @responsibility module has been adapted to use the 4 SRES regions, as specified for the UNFCCC exercise, rather than than the 12 JCM regions shown in the distribution plot. Extension to JCM regions will be developed later -see @aboutregions²

#kyotoopt		§see @kyoto

#incusaopt		§see @kyoto

#convyear		§see @convergence

#convfac		§see @convfac

#popcoy		§see @convpopcoy

#expconvopt		§see @convfac

#popcoyopt		§see @convpopcoy

#regiondatasource		§Historical emissions data comes from CDIAC (@dataref)  <li>See also @histemitobserv  <li>²°cogs Note the individual country data were summed for JCM regions (CDIACs regions are slightly different). ²  <li>² °cogs Historical emissions of other gases used in @responsibility module for @attributeplot are derived from RIVM Edgar-Hyde (link to be added) ²



Regional socioeconomic data (population, GDP, energy) and future SRES emissions data is derived from RIVM's implementation of the SRES scenarios using the IMAGE model (@dataref)  <li>see @people module  <li>²(Note SRES itself only reported data for 4 regions, whilst JCM has 12 and IMAGE has 17). These data are normalised to ensure consistency with totals tabulated in SRES. ²  <li>²°cogs The original data is compressed to one byte per number -see @loaddata²

#histemitobserv		§If you make a plot of Emissions ("what" menu) / Population ("per" menu), you can observe some well known historical events as sudden changes in the curves:   <li>Economic depressions in 1929 (Wall street crash) and 1979 (related to OPEC oil price rise)   <li>rapid economic growth in 1960s   <li>'great leap forward' in China 1950s   <li>burning oil wells in Middle East during 1991 Gulf war   <li>collapse of the USSR leading to closure of heavy industry (also in east europe)   <li>effect of weather variation on renewable energy supply (wind and hydro) in Denmark.

#distribution		§££distribintro
  ££unspecified ££percapita ££grandfather ££sresdist ££unspecified ££convpergdp ££brazil ££distribdeaccat
  <hr>Note also @equity, @aboutregions, @stabilisation, @histemitobserv

#distribintro		§Stabilisation of CO2 concentration, or any "mitigation" scenario, implies a global agreement to limit emissions. Such an agreement is unlikely to be achieved, without including a more equitable distribution of emissions, particularly between industrialised and developing countries (although note, this is only one of several @equity). Therefore, it is important to investigate the implications of various distribution options.
  The distribution of future emissions in stabilisation scenarios is a controversial issue which IPCC did not yet address, however it is often raised within the UNFCCC process (where it may be referred in phrases such as "differentiation of commitments", ?common but differentiated responsibilities", ?reducing per-capita inequity?, etc.).
  <!-- add direct links to unfccc docs?-->
  You can explore some different approaches, by selecting an option from the @distribmenu (in @mitigpanel), and observing the effect on regional emissions in a @distribplot. Note that the distribution options define the shares of CO2 emissions allocated to each region. These shares are multiplied by the total emissions according to your chosen option from the @emitmenu. The calculations are made in @regshares.
  Any of the options below may also be applied following after the Kyoto protocol in 2013 -see @kyoto
  ²Note:  the list of distribution options in JCM is not intended to be comprehensive, other options will be added later -please suggest ideas²

#effectofkyoto		§Essentially the answer depends on   <li>what you compare it with (SRES or stabilisation or scenarios)   <li>what you think Kyoto might lead to later (in the UNFCCC process)
  See also  @kyotohowwork

You can experiment for yourself, by pressing the "Kyoto" button in the CO2 emissions plot. This will set the fossil fuel CO2 emissions according to the Kyoto targets for AnnexB countries, and according to the SRES scenarios for the other countries (change using the SRES menu).

As you can see, Kyoto reduces the emissions in 2012 compared with any of the SRES "no-policy" baseline scenarios. However it increases the emissions compared to most pathways leading to stabilisation   <li> @sres (where are we going?)  <li> @stabilisation  (where do we need to go?)

For example, for stabilisation of CO2 concentration at 450ppm, the emissions curve must drop more rapidly if starting after Kyoto 2013.
  Note, however, that Kyoto also reduces emissions compared to the WRE scenarios (see @pathways)  which initially follow a IS92A business-as-usual.

In all cases the immediate impact on the climate is very small, simply because the timescale of the Kyoto protocol is very short in the context of the slow, cumulative process of climate change<li>See @inertia

So the effectiveness of Kyoto really depends on whether it lays a good foundation for the climate convention process, which might lead to greater reductions later. Are the targets a step in the right direction? Can it help to build trust between diverse regional groups? Does it set good precedents in the rules for flexible mechanisms and accounting? Such questions require consideration of diplomacy as well as science.

The USA announced in spring 2001 that it does not intend to ratify the protocol. You can see what effect this might have by pressing the "US" button on the CO2 emissions plot (if "KP" button is enabled). This sets the US emissions according to the SRES scenario (choose from menu), as for the developing countries. In this case, only about 30% of the total emissions in 2012 would be limited by Kyoto quotas. Moreover, lack of US participation in the first step might discourage participation by other countries later.
  ³Per-capita emissions³
  The effect of the Kyoto protocol on the distribution of emissions may be illustrated by the a plot of emissions per capita<li> see @distribplot

You can see that the per-capita emissions targets for USA are about twice those of Europe and Japan, which are still about twice the world average. However the most obvious effect of Kyoto is the very large increase for Russia and Ukraine (brown colour), whose per-capita target is similar to that of USA (taking into account population changes). As it is unlikely that they will actually need to burn so much fossil fuel during this period, this surplus "hot air" quota will probably be sold to other countries.

#kyotohowwork		§Emissions targets for the six JCM regions corresponding to Annex B were calculated (externally), by summing the target emissions for each country, calculated using emissions data from CDIAC.

Note that Kyoto targets applied to a basket of six gases, and also included some emissions from land use change. Here the same percentage reduction targets are applied to fossil CO2 only.
  (i.e. for each country it has been assumed that ratio fossil CO2 emissions as a fraction of total greenhouse gas emissions will be the same during 2008-12 as it was in the baseline year 1990)
  One consequence of this, is that the total CO2 reduction for the six "Annex B" regions is slightly less than the 5.2% reduction in AnnexB total ghg emissions. Note also that EE region (orange) includes former Yugoslavia and Albania without targets, whose emissions are assumed to grow.
  The Kyoto targets for Annex B countries apply to the budget period 2008-2012, so a linear transition is shown between 2000 and 2007.
  For the non-AnnexB countries and also for USA, if not included (an adjustable option), emissions are set according to an SRES baseline, which varies according the chosen scenario (SRES menu at top). This data is derived from RIVM's IMAGE model (See @aboutregions)
  It should be noted, that these SRES projections seem rather high compared to current trends.
  <hr>for a general discussion see @effectofkyoto

#kyotofuture		§<li>Targets should apply to all gases   <li>The effect of emissions trading and CDM could be shown   <li>Land-use change emissions should be included, limited as specified at COP7   <li>This approach should be extended to further commitment periods

#convergence		§The convergence formula defines a gradual transition from the current distribution of emissions, to an equal per-capita distribution in the "convergence year".
  Note this is not meant to be a prediction, but a possible framework for allocating tradeable emissions quotas under a global climate agreement. See @distribution
  ££convadju ££convmath
  ³Expert Convergence Options³ §²°adju Only available, if you choose expert version from the top menu²
  ££convfac ££convpopcoy

#convadju		§Select "convergence to equal-per-capita from the distribution menu. You can then adjust the convergence year by dragging the blue arrow on the per-capita emissions plot. You should see point where the lines converge move to the left or right accordingly. See also @distribplot

#convmath		§The allocation for each country (or region) is simply calculated by

(allocation for country "c" in year "y") =

 (global emissions budget in year "y") x  (share for country "c" in year "y").

The "share" for each country (i.e. the fraction of the global emissions budget)
  is calculated every year as follows:

For country "c" in year "y" the share "s" is given by:

s<sub>c, y+1</sub> = s<sub>c, y</sub> + f<sub>y</sub>. ( p<sub>c, y</sub> / p<sub>w, y</sub> -  s<sub>c,y</sub> )

where "p<sub>c, y</sub>" is the population of that country, "p<sub>w, y</sub>" is the world population <i>in that year</i>.

f<sub>y</sub> is a factor determining the rate of convergence.

A simple linear formula gives

f<sub>y</sub>  = 1 / ( y<sub>conv</sub> - y )

where "y<sub>conv</sub>" is the convergence year (which must be agreed in advance).

Alternatively, if you choose the "expert" version, you can experiment with  an exponential formula:

f<sub>y</sub> = e <sup>{q ( t -1 ) }</sup>

where t = ( y - y<sub>start</sub> ) / ( y<sub>conv</sub> - y<sub>start</sub> )

and q is an arbitrary "convergence factor"

Some key features of this convergence formula (with either definition of f<sub>y</sub>) are:  <li>The sum of the shares in any year must always be equal to one.
  To stay within a fixed global emissions budget, you can only increase the share of one country, by decreasing the share of another.   <li>In the convergence year f=1, so shares are then exactly proportional to populations  <li>The formula for allocating shares between countries is independent of the formula for defining the global emissions budget  <li>The share in any year is only dependent on the population in the previous year, and on the share in the start year.
  A policy agreement based on this formula, would not need to specify any projections of future population changes.  <li>The same formula applies to all countries.

Other options for convergence criteria may also be considered, for example "energy demand" perhaps mixing population, economic activity, natural resources, local climate (feedback?), etc.

#convfac		§The linear convergence formula is used by default. This is simpler, but results in a sharp kink for some countries in the start year. So the exponential formula allows a smoother transition, although the penalty for higher emissions in earlier years, is a more rapid drop later.

°adju To choose the exponential convergence formula, click the button labelled "EC" at the top right of the plot. You should now see that the lines become more curved, and a new double-arrow (cyan) control appears. Dragging this control to the left or right changes the "convergence factor" as defined above. You can see the exact value of this factor in the pop-up info, the default value is 6.0.

#convpopcoy		§It may be argued that the convergence @convmath provides no incentive for countries to restrain future population growth.
  Therefore the option is provided the option to freeze the population used for calculating convergence, in a certain year which we call the "population cutoff year". Specifically,  p<sub>c, y</sub> and p<sub>w, y</sub> in the formula above are fixed in and after the cutoff year (but not before that).

This cutoff year would have to be agreed in advance. On the plot it is shown by the position of the green upward-pointing arrow, which appears if you click the button labelled PC at the top right of the plot.

You may have observed that, when the population cutoff option is enabled, the per-capita emissions do not converge exactly in the convergence year, or appear to <i>diverge</i> thereafter. This is to be expected, since after the cutoff year, countries with growing populations have to divide their share among more people, and so get less for each person, whereas those with falling populations will have more for each person. Note that the per-capita emissions shown on the plot are calculated by taking the shares calculated using the "cutoff year" population as defined above, multiplying these by the global emissions budget, and then dividing by the actual (projected) population (<i>not by the "cutoff" population</i>).

#distribdeaccat		§Another option which may be implemented later, is to reduce Annex-B emissions in steps (as Kyoto), and others follow with equivalent reductions compared to the  baseline after a fixed delay period.

#peoplefuture	¨fut		§<li>Later it is anticipated to develop a simple dynamic socioeconomic model, including some feedbacks to/from the climate system.   <li>This should be tuneable to fit SRES, and thus extend/interpolate the scenarios.   <li>This will also require consideration of basic economic sectors, including energy, transport, agriculture etc, and must also capture the inherent inertia in changing infrastructure, technology, lifestyle and population patterns.  <li>We also need abatement costs for each gas, to find the most effective ways to reduce warming.  <li>These may be considered alongside climate change impacts  -see @costs, @impacts, @optimisation  <li>More regions are needed, to capture the diversity of socioeconomic, political and climatic patterns.  <li>A basic emissions trading module is important to show the effect of the Kyoto protocol and longer-term distribution options