*2.1. Demographic Data*

The main demographic information used to generate the input projection data for the dynamic LCA is the population of the Kisumu County, per capita income in both urban areas and county, the typical household size, number of households in both urban and rural areas, as well as the useful energy demand for cooking and lightning (Table 1).

**Table 1.** Demographic and energy data of Kisumu County for the baseline year 2015 used by Carvalho et al. [26] to generate the LEAP data to the LCA model [26].


a Based on the average annual useful energy demand for cooking; b Based on the average annual useful energy demand for lightning in a mid-income urban household in Kenya.

This study is based on the fact that the population in the Kisumu County will increase by 99% in the period between 2015 and 2035. By 2035, the population income per capita is expected to grow up to 2900 USD per year, whereas the income per capita in the city of Kisumu (urban income), is expected to be 1.5 times higher than in both the urban and rural areas of the Kisumu County.

According to the LEAP modelling results [26] used in the LCA model, in the baseline year, the household energy use was over 9 million Gigajoule (GJ), with wood-logs and charcoal being the main cooking fuels used in the year 2015. In the LCA study, it is also considered that, despite the trends in urbanization, a significant part of the peri-urban population is expected to continue living in informal settings with limited access to electricity and LPG.

Thus, the present study stresses the importance of potential life-cycle based environmental improvements associated with the introduction of alternative biomass cookstove strategies in the region. In line with the previous LEAP study, the present LCA study also explores the fact that, by 2035, bottle biogas and biomass pellet cooking systems might be an a ffordable way for a substantial part of the Kisumu County's population to mitigate environmental impacts related to current traditional cooking practices [26].

## *2.2. Resource and Energy Data*

In line with the previous LEAP study [26], the projected use of natural resources and final energy used for cooking and lightning used to model the LCA inputs is computed considering the household energy use patterns in the historical years between 2010 and 2014 [26]. The calculation of the energy use is performed according to each type of cooking and lightning fuel/technology system, in order to model the household energy demands between 2015 and 2035. In the ICS scenario, all the woody biomass used in 2035 is expected to be produced via agroforestry systems considering the available agricultural land in both the Kisumu County and the nearby county of Siaya. As there is no su fficient amount of agricultural land available today that can be converted to agroforestry land systems, in this

study it is considered that part of the woody biomass produced via agroforestry was sourced by Siaya County. In the PGS, a full replacement of traditional cookstoves by pellet micro-gasifying stoves is expected to occur in the year 2035. In urban areas, the biomass pellets are expected to be produced by a mixture of woody biomass from agroforestry (50%) and sugarcane bagasse (50%), considering that sugarcane bagasse is the most important crop-residue produced in the industrial sugar belt around the city of Kisumu. In rural areas, biomass pellets are assumed to be fully produced via the densification of woody biomass produced in agroforestry systems. Finally, in the BGS scenario, a full replacement of traditional cookstoves by biogas stoves is projected to occur for the year 2035. Here, half of the biogas is expected to be produced through the anaerobic digestion of animal manure and the other half through the digestion of municipal household waste produced in the Kisumu County. The LEAP functions used to compute the energy data that serves as input data to the LCA model are described in the Eq. 1-3 and Appendix A of the previous research published by Carvalho et al. [26].
