Under the background of energy shortage and emerging climate change caused by fossil energy,forest residues were encouraged to be used as an energy resource.The mitigation benefits from using forest residues received growing attention in recent decades.However,it is challenging to quantify the forest residue at the fine spatial scale due to the data stabilizability and suitable research methods.In this study,we established a model to estimate the forest residues in 2018 in China through the top-down method,and the remote sensing data were used to further down scale of provincial forest remaining reserves to the county level,providing more detailed data support for the energy utilization of forest residues.At the same time,based on the decomposition process of forest residues,we use the dynamic soil carbon model(YASSO 15)to quantify the carbon emissions caused by the decomposition of forest residues,and establish an indicator to clarify its contribution to climate change(CCC).The main conclusions are as follows:(1)In 2018,the availability of forest residu(2)es in China reached 152.13 million t.Among various types of residues,forest tending and thinning residues were the most extensive(87.46%),followed by forest harvest residues(7.58%),and energy forests were the least(4.96%).Among the various subcategories of forest tending and thinning residues,the reserve of shrub stumping residues was the highest(62.05 million t),accounting for 40.79%of the total forest residue in the country.There are also economic forest tending management residues(34.72 million t,22.83%)and wood forest tending and thinning residues(23.03 million t,15.15%),accounting for more than 10%of the forest residue.(3)The distribution of forest residues has significant spatial heterogeneity,with 13provinces in the southern region providing 60.47%forest residues,8 provinces in the plain and hilly region accounting for 17.87%,and 10 provinces in the northern region accounting for 21.66%.The three provinces with the largest forest residues were Yunnan(14.38 million t),Guangxi(12.09 million t),and Sichuan(10.5 million t).There were a total of five provinces with forest residue reserves below 1 million t in the country.The highest areal-specific forest residues were found in Hainan(0.72 t/ha),while the lowest occurred in Qinghai(0.01 t/ha).(4)From the county level,there were 2805 counties with forest residue distribution,of which 3 counties had forest residues exceeding 1 million t:Shenmu,Shaanxi(1.35 million t),Dongzhi,Anhui(1.12 million t),Jiangning,Jiangsu(1.05 million t),152 counties had forest residue exceeding 0.20 million t,and 1634 counties have forest residue reserves exceeding10000 t.(5)The decomposition rate of forest residues was relatively fast in the first decade,and then gradually decreased.The decomposition rate of forest residues nationwide reached a peak in the second year.The cumulative carbon emissions of forest residues in a century reached 59.11 million t.In the first 14 years,more than 50%of forest residues were decomposed.(6)The CCC accumulated by the natural decomposition of forest residues over one-hundred-year had reached 49.27 million t CO2 eq,with forest tending and thinning residues contributing the most to climate change(86.86%).The CCC in various provinces ranges from0.48 million t CO2 eq in Yunnan to 75000 t CO2 eq in Ningxia.According to the areal-specific CCC of each province,3 provinces exceed 200 kg CO2 eq/ha,the areal-specific forest residue CCC of 13 provinces was between 100-200 kg CO2 eq/ha,and 15 provinces were below 100kg CO2 eq/ha.The highest annual CCC value across the country occurs in the second year,and the annual differences between provinces were significant.The highest level of CCC in the county was in the Lancang Lahu Autonomous County of Yunnan(0.67 million t of CO2eq).The benefit from avoidance of decomposition cannot be ignored in future bioenergy research.The energy utilization of forest residues is of great significance to the management of forest resources and the realization of the goal of carbon neutrality. |