# data[].attributes.headline
While mitigation assessments are conducted to assess whether the GHG emissions reduction targets are being met, and to track the progress of national climate action and overall transparency to stabilizing GHG concentrations in the atmosphere, which can only be achieved through substantive mitigation actions that limited by sources and to preserve or enhance sinks and reservoirs of GHGs, it must be supported and coordinated with quantifiable metrics and indicators, by a variety of stakeholders on its various mitigation actions, policies and measures undertaken in a given timeframe and their mutual interactions. The impacts and outcomes of mitigation actions in developing countries hinges on the availability of accurate and credible data of sectoral categories (Energy, Transport, Land Use Change and Forestry, Agriculture, Waste, and Industrial Process) for baselines and projections by databases of National GHG Inventories which depends on the data requirements, methodologies, assumptions, and the viability of these approaches. Even though the methodological differences between the national (top-down) and more individual (bottom-up) assessments with the different data types: Measured, Modelled, Calculated, and Proxy data, are used, but poor data yields poor results.Common barriers in assessing progress of mitigation initiatives: 1-	Complexity of formats,2-	Lack of clarity on requirements,3-	Lack of commitment to the supply of data,4-	Lack of robust MRV systems - data not to be fluently transferred along the system,5-	Data provided in different formats,6-	Different degrees of description, level of depth among mitigations actions.Common barriers in reporting mitigation information: 1-	Different format of results of the mitigation potential calculations,2-	Different time frames and frequency of reporting,3-	Differences in baseline considerations,4-	Differences in measurement and units. Ex-ante and ex-post determination of achieved mitigation effects can be overcome in various ways by institutional arrangements. Beside a good cycle of data management (Prioritize data collection efforts, Select data, Collect data, Fill data gaps, Improve data quality over time), gaps can be addressed by:1-	Simplify the process of progress reporting,2-	Design a multi-stage process of data provision depending upon the source of reporting,3-	Define and maintain channels for the reporting flows,4-	Differentiate between data more and less readily available to avoid blocking the reporting and collection process,5-	Design feasible and compatible MRV systems and tools that can be easily employed, given the level of information available, 6-	Developing common training for the Government staff in charge of the preparation of information to conduct the mitigation assessments, and encouraging homogeneity in the use of technical language,7-	Definition of a set of national templates to distribute to the different ministries, 8-	Use of compatible or even the same computing tools as far as possible. 

# data[].attributes.subject
While mitigation assessments are conducted to assess whether the GHG emissions reduction targets are being met, and to track the progress of national climate action and overall transparency to stabilizing GHG concentrations in the atmosphere, which can only be achieved through substantive mitigation actions that limited by sources and to preserve or enhance sinks and reservoirs of GHGs, it must be supported and coordinated with quantifiable metrics and indicators, by a variety of stakeholders on its various mitigation actions, policies and measures undertaken in a given timeframe and their mutual interactions. The impacts and outcomes of mitigation actions in developing countries hinges on the availability of accurate and credible data of sectoral categories (Energy, Transport, Land Use Change and Forestry, Agriculture, Waste, and Industrial Process) for baselines and projections by databases of National GHG Inventories which depends on the data requirements, methodologies, assumptions, and the viability of these approaches. Even though the methodological differences between the national (top-down) and more individual (bottom-up) assessments with the different data types: Measured, Modelled, Calculated, and Proxy data, are used, but poor data yields poor results.Common barriers in assessing progress of mitigation initiatives: 1-	Complexity of formats,2-	Lack of clarity on requirements,3-	Lack of commitment to the supply of data,4-	Lack of robust MRV systems - data not to be fluently transferred along the system,5-	Data provided in different formats,6-	Different degrees of description, level of depth among mitigations actions.Common barriers in reporting mitigation information: 1-	Different format of results of the mitigation potential calculations,2-	Different time frames and frequency of reporting,3-	Differences in baseline considerations,4-	Differences in measurement and units. Ex-ante and ex-post determination of achieved mitigation effects can be overcome in various ways by institutional arrangements. Beside a good cycle of data management (Prioritize data collection efforts, Select data, Collect data, Fill data gaps, Improve data quality over time), gaps can be addressed by:1-	Simplify the process of progress reporting,2-	Design a multi-stage process of data provision depending upon the source of reporting,3-	Define and maintain channels for the reporting flows,4-	Differentiate between data more and less readily available to avoid blocking the reporting and collection process,5-	Design feasible and compatible MRV systems and tools that can be easily employed, given the level of information available, 6-	Developing common training for the Government staff in charge of the preparation of information to conduct the mitigation assessments, and encouraging homogeneity in the use of technical language,7-	Definition of a set of national templates to distribute to the different ministries, 8-	Use of compatible or even the same computing tools as far as possible. 

# data[].attributes.body
Yes , I agree about the common barries which are common to our country as well. Other than the lack of data sharing mechanism is major barrier for the assesing of progress of mitigation actions.

# data[].attributes.body
Most of the barriers outlined truly represent Pakistan. Besides hesitation in providing the data these organizations dont have the date on the parameters required for mitigation assessments. Data collection at the sub-national level for a particular sector an dthe pooling in national level is another key concern.

# data[].attributes.headline
Is reducing data requirements a good solution?

# data[].attributes.subject
Is reducing data requirements a good solution?

# data[].attributes.body
Reading some of the suggested actions to overcome the obstacles in the monitoring of mitigation activities, I have the impression that, in general, the tactic is reducing requirements (e.g. focusing on most relevant sectors, simplifying the formats etc). I think that, whilst this strategy could be a temporal solution, the danger also exist to reduce ambition and make this short-term patch a long-term solution.

# data[].attributes.body
The biggest problem is the negligence of atmospheric CO2 currently and there is no very responsible person for metering and difficulties in collecting reliable, assured data.

The solution is capacity building in the importance, collection, monitoring and evaluation of CO2 for Madagascar.

# data[].attributes.body
Agree with the common barriers list. Most significant in the Maldives include lack of commitment to the supply of data by stakeholders, especially from the private sector. Complexity of formats is another acute challenge due to weak capacity in stakeholders.
In attempts to address this, training programmes have been undertaken for stakeholders.

# data[].attributes.body
With those barriers mention, here in Vanuatu, I believed those barriers mentioned above are also the barriers that we are facing in the country regarding to the ETF and the Tracking progress.

# data[].attributes.body
Yes, many of the barriers highlighted are common for us - The biggest gap is in lack of provision of adequate and good quality data which hinders accurate tracking of progress.

# data[].attributes.body
I believe most barriers have been outlined. An additional barriers in my country is the lack of technical capacity from lead sectorial agencies to deal with statistic and analyze data

# data[].attributes.body
Agree with the aforementioned barriers. A commitment to provide data is a main challenge along with others such as data provided in different formats and lack of robust MRV system.

Kunzang, Bhutan

# data[].attributes.body
Yes, I agree with the common barriers that explained in the lesson 4. Indonesia has some barriers to tracking the mitigation actions progress, mainly related with data compilation from either sectors and sub-national. Complexity of data form that should be filled has caused not only difficulty on filling process but also inconsistency of data. This barrier has domino effect to process of data analysis and reporting. To address the problem, we try to simplify the data gathering process, such as the data reporting uses the information system web-based with the standard form and following by the SOP to fill it.

# data[].attributes.headline
Barriers to tracking the progress  of mitigation actions

# data[].attributes.subject
Barriers to tracking the progress  of mitigation actions

# data[].attributes.body
All the barriers presented in this module 3 are similar for Sri Lankan context. However, when preparing TNC, capacity and technical skills on mitigation assessments related knowledge among the line ministries, departments and agencies have been identified. And also, technical expertise for identifying appropriate mitigation options for potential  sectors as well as identifying co-benefits in mitigation actions and cost analysis of mitigation actions are the constraints among them.
Therefore, continues capacity building and trainings on MRV system and mitigation assessment are required. Further, development of sectoral MRV system for climate change action is suggested.

# data[].attributes.body
I agree with the common barriers. One that stood out to me and I believe evident in my country is the lack of commitment to supply data. It may due to a number of reasons - one to note and i think is common amongst all is that most data collation, analysis is project driven - so once a project expires so does the motivation and commitment to supply data.

# data[].attributes.body
The barriers outlined in above lesson are so comprehensive and I absolutely agree on that. Complexity on what to report, lack of establishment of an effective MRV system, flow of sensible and accurate data and such data flow system are the obstacles in reporting in my country as in many other developing and least developed countries. Well established MRV system with a proper ways of data flow and reporting backed by the policy and legal framework may overcome such issues underlined above.

Milan
Nepal

# data[].attributes.headline
Yes, we do dealing with some obstacles above such on how vary understanding of  mitigations actions matters; gaps on mitigation actions which not monitored and reported at national reporting; and lack of commitment to the supply of data.

# data[].attributes.subject
Yes, we do dealing with some obstacles above such on how vary understanding of  mitigations actions matters; gaps on mitigation actions which not monitored and reported at national reporting; and lack of commitment to the supply of data.

# data[].attributes.body
Endah - Indonesia

# data[].attributes.body
I agree with the suggested obstacles. However, since the circumstances of each country are different, I think, it is important to identify the prioritized obstacles each country has. Then we need to try to solve the problems one by one.

# data[].attributes.headline
Data format, consistency and storage coupled with poor staff management when it comes to archiving have always been the problems. Each government agency or department have different data which results to consolidation incompatibility. Some data format from local government agencies also vary since the directives are inconsistent and oftentimes unclear. The staff managing data also does not have proper record management skills from storage, back-up and data or record classification which sometimes result to duplication and then retrieval problems. There has been inter-governmental coordination and consolidation by key agencies like the Department of Interior of Local Government and from the Office of the President and the Climate Change Commission. But the problem lies in the competencies and consistencies of these management and administration.

# data[].attributes.subject
Data format, consistency and storage coupled with poor staff management when it comes to archiving have always been the problems. Each government agency or department have different data which results to consolidation incompatibility. Some data format from local government agencies also vary since the directives are inconsistent and oftentimes unclear. The staff managing data also does not have proper record management skills from storage, back-up and data or record classification which sometimes result to duplication and then retrieval problems. There has been inter-governmental coordination and consolidation by key agencies like the Department of Interior of Local Government and from the Office of the President and the Climate Change Commission. But the problem lies in the competencies and consistencies of these management and administration.

# data[].attributes.body
The main barriers in Iran are Lack of commitment to the supply of data, and Data provided in different formats. To overcome this barriers, an online platform of data gathering is implemented and responsible users from different sectors will be trained to input the appropriate data.