Approximately 40% of the global population relies on traditional bioenergy, accounting for 9% of global energy use and 55% of global wood harvest. However, knowledge about the environmental impacts of traditional bioenergy is fragmented. This review addresses several persistent questions and summarizes recent research on land cover change (LCC) and pollution emissions resulting from traditional bioenergy use. We also review recent studies analyzing transitions from traditional bioenergy to cleaner stoves and fuels.Between 27 and 34% of the wood fuel harvest in 2009 was unsustainable, with large geographical variations. Almost 300 million rural people live in wood fuel “hotspots,” concentrated in South Asia and East Africa, creating risks of wood-fuel-driven degradation. Different fuels and stoves show variation in climate-forcing emissions. Many, but not all, nontraditional stoves result in lower emissions than traditional models. Traditional bioenergy makes substantial contributions to anthropogenic black carbon (BC) emissions (18–30%) and small contributions to total anthropogenic climate impacts (2–8%). Transitions from traditional fuels and devices have proven difficult. Stacking, i.e., the use of multiple devices and fuels to satisfy household energy needs, is common, showing the need to shift stove interventions from the common approach that promotes one fuel and one device to integrated approaches that incorporate deep understanding of local needs and practices, and multiple fuels and devices, while monitoring residual use of traditional technologies.

Over the last 20 years, the Kirk R. Smith research group at the University of California Berkeley—in collaboration with Electronically Monitored Ecosystems, Berkeley Air Monitoring Group, and other academic institutions—has developed a suite of relatively inexpensive, rugged, battery-operated, microchip-based devices to quantify parameters related to household air pollution. These devices include two generations of particle monitors; data-logging temperature sensors to assess time of use of household energy devices; a time-activity monitoring system using ultrasound; and a CO₂-based tracer-decay system to assess ventilation rates. Development of each system involved numerous iterations of custom hardware, software, and data processing and visualization routines along with both lab and field validation. The devices have been used in hundreds of studies globally and have greatly enhanced our understanding of heterogeneous household air pollution (HAP) concentrations and exposures and factors influencing them.