Data...

As in all projects that rely on data for further analysis, the task of collecting, sorting and grouping the data was a challenge for the project in terms of time and effort. Not all the data that can be collected is available for use, either because it does not fulfill all the requirements or because after handled the results are not of good quality.

USA data:

The data for USA was taken from the EPA web site quoted in the references
page. The following results can be emphasized:

• 2364 different landfills

• Only 139 had all the data we needed in order to calculate efficiency

• Depending on the standard used, some data was removed (curve shape, efficiency above 100%)

• 79 gave credible results when efficiency was calculated using CAA standard

• 45 when efficiency was calculated using AP-42 standard

• 125 if using EPA document formula

In the case of the EU, there were several sites containing bits of information that was used for the project, this is, no unique site had all the data we required. The next table shows how the data fitted into the project:

EU data:

• 55 different landfills, all with the required data

• Same as with the USA data, some data was removed depending on the standard used (curve shape, efficiency above 100%)

• Using CAA standard, a total of 39 gave good results.

• 21 when efficiency was calculated using AP-42 standard. No good statistical results could be obtained from these data.

• 45 data points were used when calculating efficiency using EPA document formula

From the data collected and sorted as explained above, no good correlation was found when plotting the amount of Methane reported as used against the Waste in Place. It was expected that as the size of the site becomes bigger and the amount of Methane generated grows, the amount of Methane reported as used should had increased accordingly

The above is the numerator of the efficiency formula. The same handling was used to determine the correlation between the maximum amount of gas (calculated as per CAA) against the amount of Waste in Place, this is, the denominator of the efficiency formula. The charts are shown next:

As it can be seen, a much better correlation is obtained from the calculated numbers. However, as the efficiency formula makes use of both reported and calculated values, it was not possible to discard the scatter and hence the initial efficiency reference charts were difficult to judge

Therefore, a statistical analysis was needed in order to sort and analyze the results. The data was sorted in bins, aiming to have 10 bins per standard with a minimum of 5 data points in each bin. When any particular bin did not satisfy the number of data points required, then it was grouped with the following bin. Only the particular case of Europe data using the AP-42 standard did not satisfy all the considerations due to the limited number of data points. On the resulting numbers the standard deviation was also calculated