Exploratory modeling to estimate major elements contents of woody biomass ash from stokers, fluidized beds and gasification reactors

• The contents of major elements in 98 woody biomass ashes (WBA) were analyzed. • Fly ash contains more carbon, Mg, P, S, Cl, and Ca than bottom ash does. • Cluster analysis first separated the gasification residues, bottom ash and fly ash. • Elemental compositions of WBA were influenced by soil characteristics too. • The regression models estimated TC, Mg, Al, Si, P, S, Ca, and Fe with R 2 > 0.5. The recycling of woody biomass ash (WBA) from biomass power generation has become a target for attaining a circular economy. To increase the efficiency of WBA utilization, getting information of elemental composition before chemical analyses is definitely useful. This is the first study to propose estimation formulas of elemental composition of WBA by the production parameters. Additionally, unburned carbon of WBA should be discussed more for its cement and biochar use. 98 WBA were collected and their major elements. The potential of WBA for fertilizer, cement material, and biochar was evaluated by its elemental contents data. The cluster analysis implied that bottom ash (BA) from circulating fluidized beds (CFB) contained higher amount of Si and less carbon. Fly ash (FA) from fluidized beds contained more P and Ca. The regression analysis showed that the elemental contents of WBA are substantially influenced by fuel type and the soil too. Elements in FA were more dependent on waste wood firing. Elements like Al and Si of BA from CFB were influenced by soil distribution of Japan, that implies the importance of local WBA application. BA from CFB contained less S and Cl, considered to be suitable for cement material. FA from bubbling fluidized beds would contain reasonable concentration of P as well as enough K for fertilizer material. The regression models estimated the elements with 0.18–0.85 of coefficient of determination. Some elements might be also influenced by combustion temperatures and other parameters, further information of which can improve the accuracy of estimation.