Transitioning to green growth in Kenya: The Horticulture Productivity, Fuel Consumption and Short-Lived Climate Pollutants nexus

Abstract

The need to transform Kenya’s horticultural sector to adopt low carbon, resource-efficient initiatives require a shift to sustainable consumption and production practices that underpin low carbon green economy regimes. Short-lived climate pollutants (SLCPs), including black carbon, methane, tropospheric ozone, have harmful effects on agricultural productivity, ecosystems, and people, consequently impinging on green economic growth. This paper evaluates the influence of horticultural productivity in Kenya on National Fuel Consumption and SLCPs. National data from the Kenya Bureau of Statistics (KNBS) on horticultural commodity prices (HCPs), as a proxy to horticultural productivity, are compared with fuel consumption and satellite-borne national average black carbon measurements. The KNBS data were collected for the period 2002 to 2018. National monthly area average time-series of the SLCPs were obtained from satellite data from the National Aeronautics and Space Administration Giovanni website for the same period. Consumption of eight fuel types was correlated with HCPs. Correlation and regression analyses employed on the data revealed a statistically significant relationship between monthly black carbon and annual horticultural commodity prices, with dry months of February and June reporting inverse relationship, with a correlation of determination (r2) ranging from 0.36 to0.38. On the other hand, the wet month of October registered a positive correlation with black carbon (r2 = 0.54). The statistically significant inverse relationship between Annual horticultural commodity prices and annual surface black carbon concentrations is evident for fruits. The vehicular emissions connected to the horticulture value chain need to be mitigated as Kenya transitions to a green economy. Total monthly fuel consumption is positively and moderately correlated with horticultural commodity prices, with January recording the highest r2 (0.85). The months of October to December record the lowest variance explained. This alludes to the need to adopt green energy in the horticulture sector to be in tandem with the transition