G3W and Capacity Building
The successful implementation of G3W necessitates a robust and all-encompassing capacity building programme. This must cater to diverse roles within the organizational structure, spanning managerial levels, operators, data managers, modellers, and infrastructure support professionals. It is imperative that training occurs before, during, and after the roll-out, ensuring the acquisition, maintenance, and expansion of competencies. For an in-depth exploration of capacity building details, the complete information is available in the 9. Capacity Building section of the G3W Implementation Plan, published on the WMO INFCOM-3 mini-site.
Survey on National Capacities for G3W Implementation
To assess the requirements for capacity development, a comprehensive survey of Member countries was conducted. Commencing on October 13, 2023, the data collection phase garnered responses from 60 61 out of the 193 member nations. The primary objective was to ascertain the capabilities of member countries in implementing G3W.
Our sincere gratitude extends to the 60 61 nations that participated, providing invaluable insights into G3W capacity building efforts. These countries include: Algeria, Angola, Argentina, Australia, Austria, Barbados, Bosnia and Herzegovina, Burundi, Cabo Verde, Canada, China, Costa Rica, Côte d'Ivoire, Croatia, Cuba, Cyprus, Czech Republic, Denmark, Egypt, Estonia, Fiji, Finland, Ghana, Germany, Hong Kong-China, Hungary, Indonesia, Ireland, Italy, Japan, Kenya, Latvia, Madagascar, Malawi, Mauritius, Monaco, Mongolia, Morocco, New Zealand, Nigeria, Norway, Pakistan, Peru, Poland, Republic of Armenia, Republic of Benin, Republic of Korea, Russia, Singapore, Slovakia, Seychelles, South Africa, Spain, Sweden, Switzerland, Tajikistan, Tunisia, Türkiye, United Kingdom, United States of America, Vietnam. |
Overview
Please note that this analysis includes responses from 43 countries received before December 12th. Updates for responses collected after this date will be provided shortly on this page.
You can navigate the full pdf. version here:
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Survey Introduction & Respondents
Data collection took place from October 13th to December 12th, encompassing responses from a total of 43 countries. The objective is to grasp the member countries’ capabilities for Implementation of G3W.
<Chart 1. Response rate by region>
RA X | Total members | Survey Respondents | Response rate |
|---|---|---|---|
RA I | 53 | 11 | 20.8% |
RA II | 34 | 6 | 17.6% |
RA III | 12 | 2 | 16.7% |
RA IV | 22 | 1 | 4.5% |
RA V | 22 | 4 | 18.2% |
RA VI | 50 | 19 | 38.0% |
<Table 1. Response rate by region>
The response rates are highest in Region VI: Europe, with 38%, followed by Region I: Africa at 20.8%. Meanwhile, in terms of RA III and IV, two or fewer countries responded, RAIII: Peru, Argentina; RA IV: Costa Rica. Consequently, meaningful analysis for those regions is challenging.
Responses were primarily collected on a country basis, and in cases where multiple agencies within a single country provided responses, the data was aggregated for statistical analysis.
Survey Questions and Results
1) Is your agency responsible for the compilation of national GHG inventory?
<Chart 2. Q1>
46% of Countries responded “No”. The most popular response was that many countries do not have capabilities for the compilation of national GHG inventory (assuming that 46%, No, was significantly higher than 25%, Yes).
When examining the regional averages for "Yes", RA I (Africa) shows a lower average at 9%, below the grand average of 25%. Conversely, RA VI (Europe) has a surpassing average of 44%. From RA II and RA V, no countries responded with "Yes.“
2) For what type of decision-making GHG data are needed or used in your country?
<Table 3. Sum of Q2>
Responses were collected with the option for multiple selections. The most frequent responses included Climate Policy Formulation and Evaluation, followed by Climate Impact Assessment and Contribution to emission inventory development.
Additional responses under the "Other" category, beyond the provided options, included Academic Research, Monitoring, and Verification of Inventories.
3-1) Number of staff(s) involved in your agency in a GHG observation.
3-2) Number of staff(s) involved in your agency in a GHG modelling.
Staff(s) in modelling | Staff(s) in observation | |
|---|---|---|
Grand Mean | 4.1 | 8.2 |
<Chart 3. Regional average of Q3>
The statistic is on a country basis as the data was consolidated in cases where a single country provided responses from multiple agencies. For Region IV, only one case was available, Costa Rica: responded with 2, 2, so no statistical analysis was conducted.
Upon examining the grand means, it is evident that there is a shortage of personnel in modelling compared to observation.
The countries that answered "0" for both questions, indicating a pressing need for capacity building, are as follows:
- RA I: Mauritius; Brundi
- RA II: Bosnia and Herzegovina
- RA III: Pakistan
- RA V: Fiji
- RA VI: Republic of Armenia; Slovakia; Latvia
4-1) How many measurement stations are operated in your country for in situ atmospheric concentration measurements of CO2/ CH4/ N2O/ Other GHGs?
4-2) How many measurement stations are operated in your country for direct flux measurement of CO2 / CH4/ N2O/ Other GHGs?
Staff(s) in modelling | Staff(s) in observation | |
|---|---|---|
Grand Mean | 4.1 | 8.2 |
<Table 4. Grand Mean of In Situ Measurements>
CO2 | CH4 | N2O | Other GHG | |
|---|---|---|---|---|
Grand Mean | 5.3 | 1.5 | 0.5 | o.4 |
<Table 5. Grand Mean of Direct Flux Measurements>
Upon, comparing the grand mean, it is observed that the Grand average of measurement stations in both measurements decreases in the order of CO2, CH4, and N2O.
CO2 | CH4 | N2O | Other GHG | |
|---|---|---|---|---|
Non-response | 0 | 2 | 2 | 3 |
“0” | 11 | 14 | 18 | 12 |
<Table 6. In Situ: Sum of Countries with non-response/ no measurement>
CO2 | CH4 | N2O | Other GHG | |
|---|---|---|---|---|
Non-response | 3 | 6 | 6 | 7 |
“0” | 20 | 24 | 29 | 30 |
<Table 7. Direct Flux: Sum of Countries with non-response/ no measurement>
Referring the tables above, Q4 is the one with a particularly high number of non-responses or "0“(no measurement) responses. Especially regarding the non-responses, it can be inferred that there is a significant number of countries with limited knowledge about their current situation. For a detailed list of countries, please refer to Sheet 3 in the appendix.
5) To what extent is the national greenhouse gas observational network in your country/territory supported operationally (funding and staffing)?
<Chart 4. Sum of Q5>
The most prevalent responses were for Purely on research grants, followed by Full support from the government for > 5 years.
There are cases where single country chose multiple options when they represent multiple agencies. For example, in Germany: "Fully funded: DWD, UBA, ICOS Central Facilities; Research grants (TCCON, COCCON, in-kind contributions for ICOS Ecosystem stations)."
Under the "Other" category, the following responses were provided:
- Mongolia: Cooperation between IRIMHE and GMD, NOAA, USA
- Spain: Each institution uses its funds to support the operation of the station
- Monaco: Operational for more than 5 years but only on inventory
6) What other GHG atmospheric measurements are performed in or by your country?
<Chart 5. Sum of Q6>
The responses were highest for ground-based remote sensing, followed by ship and aircraft. However, it's worth noting that non-response and no measurement were also relatively high, with 10 and 9 responses each.
Under the "Other" category, the following responses were provided:
- Germany: drone based, aircores; aircraft/ship remote sensing
- Norway: Development of remote sensing platforms and drones ongoing
- Australia: by RV Investigator, a GAW mobile platform
Countries that fall under "Start from 2024" include South Africa and Italy.
<Chart 6. The Other Countries’ Sum of Q6 >
To examine whether there is a significant difference based on national income, the responding countries were analyzed, divided into "WB Top Developed Countries" and "The Other Countries". For the list of countries corresponding to this analysis, please refer to Sheet 4 in the appendix.
In WB Top Developed Countries, a similar trend to Chart 5 was observed, with responses being highest for ground-based remote sensing, followed by ship and aircraft.
On the other hand, in The Other Countries, responses were highest for no measurement, ground-based remote sensing, non-response, aircraft, and ship, in that order. This suggests a meaningful difference in Implementation Capabilities between developed countries and others.
7) Does your country conduct measurements of greenhouse gases (e.g., CO2) dissolved in the ocean? If yes, could you provide the number of observational platforms?
<Chart 7. Sum of Q7>
<Table 8. Sum of Q7 by RA>
A total of 16 countries responded with "Yes," and among them, 63% are from RA VI: Europe. If the response is "Yes," the mean number of measurements is 2.64.
The country that responded with "no measurement" is Bosnia and Herzegovina. Switzerland and Nigeria didn’t respond.
8) What satellite data for greenhouse gases are used in your country and/or by your agency?
<Chart 8. Sum of Q8 >
Duplicates were allowed, and statistics were calculated only for cases where there were at least two or more responses. The most frequent response was Sentinel, showing that 47% of countries use it.
Under the "Other" category, Denmark and Switzerland mentioned CO2-M satellite (planning), Vietnam mentioned VNREDSat-1, and New Zealand mentioned MethaneSAT.
Countries that responded with "No satellite data" include Latvia, Monaco, Slovakia, Fiji, Morocco, and Armenia; and “No Capacity” Pakistan and Australia-CSIRO.
9) Where does your country share greenhouse gas observational data?
<Chart 9. Sum of Q9 >
Duplicates were allowed, and statistics were calculated only for cases where there were at least two or more responses.
Countries with “No Data/ Not shared” include Pakistan; Slovakia; Tunisia; Argentina; Monaco; Fiji; Mauritius; and Costa Rica.
Countries with “Own DB/ for own use” include Cabo Verde; Madagascar; Nigeria; and Czech Republic.
In this question, there were differences in responses between developed countries and others.
In WB Top Developed Countries, the responses were highest for WDCGG, ICOS, FLUXNET, SOCAT, and TCCON, in that order.
In The Other Countries, the responses were highest for WDCGG, No Data/Not shared, Own DB/for own use, ICOS, and NOAA, in that order. The remaining options are0, not chosen.
<Chart 10. The Other Countries’ Sum of Q9 >
10) What modelling tools are used in your country and/or by your agency to calculate greenhouse gas concentrations and fluxes?
<Chart 10. Sum of Q10 >
Duplicates were allowed. The response rate for Emission Inventory models for anthropogenic fluxes was the highest.
Under the "Other" category, the following responses were provided:
- Pakistan: Geographic information systems and remote sensing programs
- Vietnam: AFOLU Carbon Calculator
- Tunisia: Own computer tools calculating the pollutants concentration per station (28 stations in Tunisia) using SENTINEL data;
- Algeria: climatic model
- Morocco: Machine Learning Models for O3
However, 12 countries either did not respond or marked it as N/A. In cases where the response was "No operational model at the moment" or the responding institution does not carry out modelling, the answer was marked as N/A, totaling 5 countries: Indonesia, Peru, Republic of Armenia, Fiji, and Nigeria. Additionally, 7 countries, representing 17% of all countries, did not provide a response.
11) Does your country have a national greenhouse gas monitoring plan?
<Chart 11. Percentage of Q11 >
Many countries indicated that they either do not have a plan or are in the stage of development without a concrete timeline, accounting for 63%.
This suggests that most countries lack a concrete plan for GHG monitoring at the national level.
Specifically for South Korea and Russia, there were multiple responses indicating that "The plan has been developed and is in the stage of implementation" and "The plan is under development, and the implementation will start within 5 years."
12-1) How many stations in the country need to be repaired/ upgraded currently?
12-2) How many stations in the country need to be newly built (for a well-covered designed observation)?
27 countries responded clearly to Q 12. The grand mean indicates that 2.8 stations are in need of repair/upgrade and 10.7 stations are in need of being newly built for well-covered observation, inaverage.
However, it's important to note that these statistical results have limitation. Some responses consider the range at a national level, leading the response values tend to be higher, while others may be specific to a single agency. Also, many responses were provided in approximate terms.
<Chart 12. Regional Mean of Q12 >
16 countries did not provide clear answers, and their responses can be broadly categorized into four:
1.Non-response
- Needed but cannot quantify
- Not applicable due to no existing stations/no plan
- Do not know
Specifically, for Q. 12-1, the N/A responses were as follows:
- RA1: Brundi (no station); Tunisia
- RA2: Pakistan (no station); Republic of Korea
- RA3: Hong Kong
- RA4: Costa Rica (no stations)
- RA6: Monaco (no stations); Latvia (no stations); Austria; Czech Republic (do not know)
13) How many people need to be trained in establishing high quality GHG observations/ GHG modelling/ the use of GHG data for decision making?
33 countries responded clearly to Q 13. The grand mean indicates that 16 staffs are need to be trained in establishing high quality GHG observations; 7.1 staffs in GHG modelling; and 18.9 staffs in the use of GHG data for decision making.
However, it's important to note that these statistical results have limitation. Some responses consider the range at a national level, leading the response values tend to be higher, while others may be specific to a single agency. Also, many responses were provided in approximate terms.
<Chart 13. Regional Mean of Q13 >
10 countries did not provide clear answers, and their responses can be broadly categorized into four:
1.Non-response
- Needed but cannot quantify
- Not applicable due to no existing stations/no plan
- Do not know
Among these, a relatively high number of countries responded with "do not know" to the question about the use of GHG data for decision-making. Specifically:
- RA3: Argentina
- RA6: Norway; Republic of Armenia; United Kingdom; Monaco
Summary
Comparing Current Capabilities on staffs in observation with modeling, it was found that there is a relatively greater shortage of modeling staff. However, when examining the Q 13 regarding Future Development on Staff Training, it was observed that the need for establishing high-quality GHG observations was prioritized over the need for GHG modelling.
In the context of comparing no. of current stations for in situ atmospheric concentration measurements and direct flux measurements, it was noted that there is a relatively greater shortage in direct flux measurement stations.
For Q 11. National GHG Monitoring Plan, it was observed that a significant portion of countries, 64%, either had no plan or were in the process of developing a plan without a specific timeline. This suggests that comprehensive national-level plans for systematic monitoring are largely lacking and needed at the same time.
In the analysis of Other GHG Atmospheric Measurements and GHG Observational Data Sharing, a gap analysis between developed countries and others revealed a meaningful difference in Implementation Capabilities.
Concerning future development-related questions, Q12 & 13, responses showed that about 11 stations in average are in need to be newly established. Regarding staff training, approximately 16, 7, and 19 additional staffs are indicated to be needed for establishing high-quality GHG observations, GHG modeling, and the use of GHG data for decision-making, respectively.
Key Findings
This survey is aimed at gathering foundational data for Capacity Development in implementation of the GGGW. Accurate status data is crucial for effective capability development. However, during the analysis of the survey, discrepancies were identified between the responses provided by countries and the actual on-the-ground situations.
In particular, during the analysis of Question 9, "Where does your country share greenhouse gas observational data?“, it was discovered that a total of 4 countries submitted discrepant data . For the Q 9, Cabo Verde responded with "Own DB/for own use," Argentina with "No data/Not shared," Algeria with "WOUDC," and Czech Republic with "Own DB/for own use." However, according to the WDCGG database, all of these countries are part of the GAW networks and are actively observing various gas species.
It can be inferred that these discrepancies are not limited to Question 9, considering the non-responses throughout the entire survey. It is estimated that there are likely more inconsistencies. Therefore, for meaningful analysis, it is essential to encourage more active participation from countries and, above all, to obtain accurate assessments of their own capabilities first.
Limitation
The number of responding countries was indeed limited, with only 43 out of 193 member countries providing responses. When analyzed by region, response rates were below 20% for all regions except RA1 and RA6.
Additionally, the inconsistency in the range of respondents posed a limitation for statistical analysis. In some cases, multiple agencies in the same country provided their response respectively, while other countries submitted a single response aggregating the multiple pertinent agencies’ data together. In most cases, one national agency responded only limited to its working scope, not including data of other agencies in the same country.
For this analysis,the values were aggregated for statistical purposes if there are multiple responses. Therefore, for detailed data, it is recommended to refer to the Appendix for confirmation.