Predicting Future Carbon Sequestration Trends Using a Regression Modelling in Awka, Anambra State, Nigeria

Abstract

Background: The land use and land cover change (LULCC) reduces carbon storage by degrading vegetation and soils, worsening climate change. In Awka, rapid urbanization is turning carbon sinks into sources, highlighting the need for predictive modelling. Aims: The purpose of the study was to use mathematical models to estimate the future effect of the LULCC on carbon sequestration in the Awka Capital Territory (ACT), Nigeria. Study Design: It would be a quantitative research design that combines remote sensing and Laboratory soil analysis. Place and Duration of Study: Six communities in the Awka Capital Territory, Anambra State, Nigeria, in a 30-year study (1993-2023). Methodology: Walkley-Black took place whereby soil organic carbon (SOC) was established in depths of 0-60 cm in the four-land use cover: forest, shrubs, farmlands, and built-up land. To develop the relationship between area changes and carbon stock, Multiple Linear Regression (MLR) were carried out along with Pearson correlation analysis to predictive model. Results: Statistical confirmation rejected the null hypothesis, H 0 2, which provided significant correlations LULCC and carbon stock (0.62 to 0.99). The carbon stock became a near-perfect negative forecast of urbanization (-0.93 to -0.99). Predictive models of the individual communities indicate that the growth of urbanization causes a linear decline in the carbon sinks in the region. Conclusion: The acquired regression models are also a critical instrument that will enable the local policymakers to forecast the environmental effects of urban planning choices and emphasize the necessity of adopting adaptive land management to alleviate climate change in the ACT.