Fiji's Sources of CO2 Emissions
Key Insights
Colonial Era and Land Use Changes
Fiji's history of CO2 emissions is deeply intertwined with its colonial past. The cession to the British Empire in 1874 marked a significant shift in land use, with the introduction of large-scale sugarcane plantations. This led to increased CO2 emissions due to deforestation and land conversion. The use of fossil fuels for transportation and machinery in these plantations further contributed to emissions, setting a precedent for future industrial activities.
Industrial Expansion and Emission Growth
The 1960s saw a notable expansion of Fiji's sugar industry, driven by global demand. This expansion involved clearing more land for cultivation, contributing to CO2 emissions from deforestation. The increased use of fertilizers and machinery also likely boosted emissions. During this period, emissions from oil became the dominant source, reflecting the growing energy needs of the industry.
Political Instability and Emission Fluctuations
Fiji's political landscape has significantly influenced its emission trends. The military coups in 1987 and 2000 led to economic downturns, reducing industrial activity and energy consumption, which likely resulted in temporary decreases in CO2 emissions. However, these periods also saw increased reliance on subsistence agriculture, potentially affecting land-use emissions. The 2006 coup had similar effects, with reduced industrial output but possible changes in land-use emissions.
Natural Disasters and Recovery Efforts
In 2016, Cyclone Winston caused widespread destruction, impacting infrastructure and agricultural lands. The recovery efforts involved significant construction activities, potentially increasing CO2 emissions from fossil fuels and construction materials. The cyclone's impact on vegetation and land use may have also affected emissions, highlighting the complex interplay between natural disasters and emission trends in Fiji.
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.