Modelling Global Fossil CO2 Emissions with a Lognormal Distribution: A Climate Policy Tool
Carbon dioxide (CO2) emissions have emerged as a critical issue with profound impacts on the environment, human health, and the global economy. The steady increase in atmospheric CO2 levels, largely due to human activities such as burning fossil fuels and deforestation, has become a major contributor to climate change and its associated catastrophic effects. To tackle this pressing challenge, a coordinated global effort is needed, which necessitates a deep understanding of emissions patterns and trends. In this paper, we explore the use of statistical modelling, specifically the lognormal distribution, as a framework for comprehending and predicting CO2 emissions. We build on prior research that suggests a complex distribution of emissions and seek to test the hypothesis that a simpler distribution can still offer meaningful insights for policy-makers. We utilize data from three comprehensive databases and analyse six candidate distributions (exponential, Fisk, gamma, lognormal, Lomax, Weibull) to identify a suitable model for global fossil CO2 emissions. Our findings highlight the adequacy of the lognormal distribution in characterizing emissions across all countries and years studied. Furthermore, to provide additional support for this distribution, we provide statistical evidence supporting the applicability of Gibrat's law to those CO2 emissions. Finally, we employ the lognormal model to predict emission parameters for the coming years and propose two policies for reducing total fossil CO2 emissions. Our research aims to provide policy-makers with accurate and detailed information to support effective climate change mitigation strategies.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Empirical Analysis of Zipf's Law, Power Law, and Lognormal Distributions in Medical Discharge Reports
Bayesian modelling and statistical text analysis rely on informed probability priors to encourage good solutions. This paper empirically analyses whether text in medical discharge reports follow Zipf's law, a commonly as…
A Logarithmic Mean Divisia Index Decomposition of CO$_2$ Emissions from Energy Use in Romania
Carbon emissions have become a specific alarming indicators and intricate challenges that lead an extended argue about climate change. The growing trend in the utilization of fossil fuels for the economic progress and si…
Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models
The forecasting of large ramps in wind power output known as ramp events is crucial for the incorporation of large volumes of wind energy into national electricity grids. Large variations in wind power supply must be com…
PredictionThe energy return on investment of whole energy systems: application to Belgium
Planning the defossilization of energy systems by facilitating high penetration of renewables and maintaining access to abundant and affordable primary energy resources is a nontrivial multi-objective problem. However, s…
COVID-19 causes record decline in global CO2 emissions
The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2…