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--- the_regionalised_data_base_capreg [2020/02/11 09:21] – [Methodology applied in the regional data consolidation] matsz
+++ the_regionalised_data_base_capreg [2022/11/07 10:23] (current) – external edit 127.0.0.1
@@ Line 105: / Line 105: @@
 \begin{split}
 CORR_{GROF,o} &= \sum_{j,r}{Levl_{j,r}O_{j,r}}/GROF_{o,n}\\
-O_{j,r}^*&=O_{j,r}*CORR_{GROF,o}
+O_{j,r}^*&=O_{j,r} \cdot CORR_{GROF,o}
 \end{split}
 \end{align}
@@ Line 121: / Line 121: @@
 where y covers all output coefficients in the data base. The Hodrick-Prescott filter is applied both at the national and regional level after any gaps in the time series had been closed.
-===Final steps of regional data completion===
+====Final steps of regional data completion====
 The regional database modules also cover some aspects which are discussed in other parts of this documentation.
-  * For policy data at the regional level (mostly premium related data) see Section 3.6. These policy related assignments require a good part of the CAPREG module
+  * For policy data at the regional level (mostly premium related data) see Section [[Policy data]]. These policy related assignments require a good part of the CAPREG module
-  * For the fertiliser and feed allocations and environmental indicators, also important elements of the regional database, see the next Section 3.4
+  * For the fertiliser and feed allocations and environmental indicators, also important elements of the regional database, see the next Section [[Input Allocation]]
-  * Towards the end of the regional data base consolidation supply side PMP parameters are calibrated as a final test of consistency and sometimes to serve as starting values for the subsequent baseline calibration (in gams\capreg\pmp.gms)
+  * Towards the end of the regional data base consolidation supply side PMP parameters are calibrated as a final test of consistency and sometimes to serve as starting values for the subsequent baseline calibration (in //gams\capreg\pmp.gms//)
-===Build and compare time series of GHG inventories===
+====Build and compare time series of GHG inventories====
 The regionalised data base module CAPREG runs in two steps:
@@ Line 134: / Line 134: @@
   * The second step involves more time consuming processing steps which are therefore only executed for the selected base year: feed allocation, computation of GHG results, and the final calibration test
-To assess the reliability of the CAPRI database in terms of GHG results against official UNFCCC notifications, results from the first step (time series) were insufficient, as the GHG accounting also requires information on the feed allocation. This problem was addressed within the scope of the IDEAg (Improving the quantification of GHG emissions and flows of reactive nitrogen) project , where an option has been introduced to allow for a consistent accounting of GHG emissions over time. This is able to combine input information from CAPREG time series runs as well as (short run, nowcasting-style) CAPMOD simulation results. Furthermore, an R-based tool was introduced to the CAPRI GUI that maps GHG emissions data from CAPRI to the GHG emission balances contained in the National Inventory Reports (NIRs) that are submitted annually by countries in compliance with UNFCCC GHG reporting obligations.
+To assess the reliability of the CAPRI database in terms of GHG results against official UNFCCC notifications, results from the first step (time series) were insufficient, as the GHG accounting also requires information on the feed allocation. This problem was addressed within the scope of the IDEAg (Improving the quantification of GHG emissions and flows of reactive nitrogen) project((The IDEAg project was commissioned by the JRC-IES in Ispra in 2015 and was carried out by the Thünen Institute in cooperation with the JRC-IES (August 2015 – August 2016). A more detailed explanation of the CAPRI task “Build GHG inventories” and its use has been prepared by the Thünen contributors at the time, Sandra Marquardt and Alexander Gocht, see capri\doc\GHG_inventory_module.docx. )), where an option has been introduced to allow for a consistent accounting of GHG emissions over time. This is able to combine input information from CAPREG time series runs as well as (short run, nowcasting-style) CAPMOD simulation results. Furthermore, an R-based tool was introduced to the CAPRI GUI that maps GHG emissions data from CAPRI to the GHG emission balances contained in the National Inventory Reports (NIRs) that are submitted annually by countries in compliance with UNFCCC GHG reporting obligations.