Magnitudes of Households’ Carbon Footprint in Iskandar Malaysia: A Policy Implications for Sustainable Development
Bibliographic record
Abstract
The carbon footprint of households is a significant contribution to global greenhouse gas emissions, accounting for 24% of total emissions. As a result, it is critical to quantify a household's carbon footprint in order to reduce it over time. One of the best ways to measure carbon emitted from various sectors of the economy, including household daily activities, is to calculate a country's carbon footprint (CF). This study statistically examined the magnitude of households’ carbon footprints and their relationships with household daily activities and certain socio-economic demographic variables in Malaysia. Results revealed that the average household carbon footprint amounted to 11.76 t-CO2. The average also showed that the primary carbon footprint, 7.02 t-CO2 or 59.69% was higher compared to the secondary carbon footprint which was 4.73 t- CO2 or 40.22% and assessment revealed significant differences among household types. The largest carbon footprint was evident in a medium-high cost urban area, estimated at 20.14 t-CO2, while the carbon footprint found in a rural area was 9.58 t-CO2. In the latter, the primary carbon footprint was almost double the figure of 5.84 t-CO2 (61%) than the secondary carbon footprint of 3.73 t-CO2 (39%). The study reveals a higher carbon footprint in urban areas compared to rural ones depicting the effects of urbanisation and urban sprawl on household lifestyles and carbon footprints. Despite some limitations, the findings of this study will help policymakers design and implement stronger policies that enforce low-carbon activities and energy-saving goods and services in order to reduce urban Malaysia's carbon footprint dramatically.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".