Congo's Sources of CO2 Emissions
✨ Key Insights
Independence and Economic Transition
The Republic of the Congo's journey through the 20th century was marked by significant political and economic changes, notably its independence from Belgium in 1960. This period of transition likely influenced CO₂ emissions, as shifts in land use and agricultural practices were implemented to modernize the economy. Although specific emission figures are not documented, the data suggests that land-use changes contributed to fluctuations in emissions during this time.
Oil Industry and Emission Growth
The nationalization of the oil industry in 1973 marked a pivotal moment for the Republic of the Congo, leading to increased oil production and export. This expansion likely resulted in higher CO₂ emissions from fossil fuel extraction and combustion. The data reflects a notable increase in emissions from oil during this period, aligning with the country's growing oil infrastructure and activities.
Civil War and Reconstruction
The civil war in 1997 brought economic disruption and changes in land use, potentially increasing CO₂ emissions due to deforestation and abandoned agricultural lands. Post-war reconstruction efforts further contributed to emissions as infrastructure development and agricultural expansion took place. These activities likely led to increased emissions, although precise figures remain undocumented.
Recent Trends and Challenges
In recent years, the Republic of the Congo has faced challenges such as increased logging activities and the impact of the COVID-19 pandemic. Logging has contributed to deforestation, releasing stored carbon into the atmosphere. The pandemic temporarily reduced economic activities, potentially decreasing emissions, but also disrupted conservation efforts, possibly leading to increased deforestation. These factors highlight the complex interplay between economic activities and CO₂ emissions in the country.
Background
The chart shows a national breakdown by source of the yearly CO2 emissions from human activities and processes expressed in megatonnes. It is critical to know and track the sources of national CO2 emissions in order to understand their individual impacts on climate change.
The sources of human CO2 emissions are
- CO2 From Fossil Fuels and Industry: coal, oil, gas combustion, other fossil processes
- CO2 From Land-Use, Land-Use Change, and Forestry
Coal, oil and gas combustion
Fossil fuel CO2 emissions from the combustion of coal, oil and gas are emitted by processes in electricity generation, transport, industry, and the building sector. All processes can be linked to human activities. Examples include driving cars with combustion engines burning diesel or gas, or electric cars charged by electricity from a power plant that burns coal.
Other fossil processes
Fossil CO2 emissions from other processes include sources like cement manufacturing and production of chemicals and fertilizers. Cement also has an absorption factor highlighted in the absorption breakdown chart.
Land-use change
Human civilization emits CO2 by changing and managing its land. Those emissions come, for example, from deforestation, logging, forest degradation, harvest activities and shifting agriculture cultivation. Land-use change also absorbs considerable amounts of CO2, which is shown in the absorption breakdown chart. Land-use change emits more than it absorbs, so the net effect is still emissions, but less than for coal, oil and gas.
Wikipedia: Greenhouse Gas EmissionsEarth System Science Data: GCP 2020 paper: Section 2.2 Land-use change; Section 2.1 Fossil fuel emissions
IPCC: Annual Report 6, 5.2.1.1 Anthropogenic CO2 emissions
Units and Measures
CO2 emissions are expressed in the total weight in megatonnes per year. 1 Megatonne is equal to 1 million tonnes.
Wikipedia: MegatonneWikipedia: Global warming potential
About the Data
The last available year is 2023. CO2 emissions data is from the Global Carbon Project. It contains national CO2 emissions from fossil sources and land-use change.
The Key Insights paragraph was generated using a large language model (LLM) using a structured approach to improve the accuracy. This included separating the context generation from the interpretation and narrative.
Data Sources
Global Carbon Budget 2024 Global Carbon Budget
Update cycle: yearlyDelay: ~ 10 months after the end of the year. Current year values are estimated and published in November.Credits: Friedlingstein et al., 2024, ESSD. Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Hauck, J., Landschützer, P., Le Quéré, C., Li, H., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Arneth, A., Arora, V., Bates, N. R., Becker, M., Bellouin, N., Berghoff, C. F., Bittig, H. C., Bopp, L., Cadule, P., Campbell, K., Chamberlain, M. A., Chandra, N., Chevallier, F., Chini, L. P., Colligan, T., Decayeux, J., Djeutchouang, L., Dou, X., Duran Rojas, C., Enyo, K., Evans, W., Fay, A., Feely, R. A., Ford, D. J., Foster, A., Gasser, T., Gehlen, M., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Kato, E., Keeling, R. F., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Lauvset, S. K., Lefèvre, N., Liu, Z., Liu, J., Ma, L., Maksyutov, S., Marland, G., Mayot, N., McGuire, P., Metzl, N., Monacci, N. M., Morgan, E. J., Nakaoka, S.-I., Neill, C., Niwa, Y., Nützel, T., Olivier, L., Ono, T., Palmer, P. I., Pierrot, D., Qin, Z., Resplandy, L., Roobaert, A., Rosan, T. M., Rödenbeck, C., Schwinger, J., Smallman, T. L., Smith, S., Sospedra-Alfonso, R., Steinhoff, T., Sun, Q., Sutton, A. J., Séférian, R., Takao, S., Tatebe, H., Tian, H., Tilbrook, B., Torres, O., Tourigny, E., Tsujino, H., Tubiello, F., van der Werf, G., Wanninkhof, R., Wang, X., Yang, D., Yang, X., Yu, Z., Yuan, W., Yue, X., Zaehle, S., Zeng, N., and Zeng, J.: Global Carbon Budget 2024, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-519, in review, 2024.