Annual greenhouse gas (GHG) emissions by source.
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Official data on GHG emissions is compiled by the Ministry of Natural Resources and Environmental Sustainbility (NRES), following the Intergovernmental Panel on Climate Change (IPCC) guidelines for national greenhouse gas inventories. The GHG emissions data is derived from multiple sectors including energy, industrial processes, agriculture, waste, as well as land use, land-use change, and forestry (LULUCF). LULUCF data reflects both emissions and removals based on land management practices, contributing to the net emissions calculations.
Data for 2020 and 2021 is provisional and subject to revision. Furthermore, no breakdown is provided for those years, i.e. only values for total emissions are provided.
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Annual greenhouse gas (GHG) emissions by source.
Name in Dataset | Variable | Definition |
---|---|---|
date (Date) | Date | The date in YYYY-MM-DD format, with MM-DD set to 01-01 since the data is at annual frequency |
source (Categorical) | Source | Either total emissions excluding LULUCF ('total'), net emissions including LULUCF ('net'), or the source of emissions ('industrial_processes', 'agriculture', 'waste', 'lulucf'). It should be noted that although LULUCF values can, in principle, be positive (representing emissions) or negative (representing removals), the values for Malaysia are all negative. |
emissions (Float) | Emissions | The amount of GHG emissions in gigagrams (Gg) of COβ equivalent (COβe). |
01 Sept 2024, 00:00
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This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A copy of the license is available Here.
Full Dataset (CSV)
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Full Dataset (Parquet)
Recommended for data scientists seeking to work with data via code.
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Connect directly to the data with Python.
# If not already installed, do: pip install pandas fastparquet
import pandas as pd
URL_DATA = 'https://storage.data.gov.my/environment/ghg_emissions.parquet'
df = pd.read_parquet(URL_DATA)
if 'date' in df.columns: df['date'] = pd.to_datetime(df['date'])
print(df)
The following code is an example of how to make an API query to retrieve the data catalogue mentioned above. You can use different programming languages by switching the code accordingly. For a complete guide on possible query parameters and syntax, please refer to the official Open API Documentation.
import requests
import pprint
url = "https://api.data.gov.my/data-catalogue?id=ghg_emissions&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
Department of Statistics Malaysia
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