Abstract
The Qinling-Daba Mountain area is a transitional zone between north and south China and not much is known about its carbon storage, particularly its pool of soil organic carbon (SOC). Given this shortcoming, more reliable information regarding its SOC is needed. In light of this, we quantified above and below-ground carbon sinks using both the Carnegie-Ames-Stanford approach (CASA) model and an improved carbon cycle process model. We also assessed the net present value (NPV) for carbon budgets under different carbon price and discount rate scenarios using the NPV model. Our results indicated that the net primary productivity (NPP) was lower in places with low density forests that were situated at high elevation. The spatial distribution of carbon storage depended on NPP production and litter decompositon, which reflected specific vegetation as well as temperature and moisture gradients. The lowest amounts of carbon storage were in the center of the Qinling Mountains and also partly in the Daba area, which is a location associated with sparse grassland. Contrastingly, the broad-leaved forested area showed the highest amount of carbon storage. NPV was positively correlated with discount rate and carbon prices, thus resulting in the highest values in the forests and grassland. The net present value of total soil carbon sequestration in the six scenarios in 2015 was 3.555 b yuan, 3.621 b yuan, 5.421 b yuan, 5.579 b yuan, 7.530 b yuan, 7.929 b yuan; The net present value of total soil carbon sequestration in 6 scenarios in 2017 is 2.816 b yuan, 2.845 b yuan, 4.361 b yuan, 4.468 b yuan, 6.144 b yuan, 6.338 b yuan (billion = 109; b; RMB is the legal currency of the China, and its unit is yuan, 1 euro = 7.7949 yuan, and 1 pound = 9.2590 yuan). Levying a carbon tax would be a notable option for decision makers as they develop carbon emission reduction policies. Given this, incorporating discount rates and carbon pricing would allow for more realistic value estimations of soil organic carbon. This approach would also provide a theoretical basis and underscore the practical significance for the government to set a reasonable carbon price.
Highlights
Increasing economic development coupled with accelerated urbanization has led to a rapid increase in anthropogenic carbon dioxide emissions
The Net Present Value (NPV) method is an economic method combined with carbon tax and discount rate, while the soil organic carbon estimation method combined with ecosystem carbon cycle process model and net primary productivity estimation model is a more accurate evaluation method, combined with the economic method and remote sensing method, this is a new attempt to evaluate the value of soil organic carbon
The high value area of soil organic carbon density is mainly distributed in the middle area of the Qinling Mountain and in the high forest coverage areas like the Daba Mountain; this is followed by the southwest area, which is covered by grasses and shrubs, and includes the Kunlun and Minshan Mountain, and areas with cultivated land distribution have low soil carbon density
Summary
Increasing economic development coupled with accelerated urbanization has led to a rapid increase in anthropogenic carbon dioxide emissions. In the field of soil monitoring, the strict geostatistical requirements for sampling and subsequent laboratory analysis limit its practicability; to this end, remote-sensing technology has obvious advantages [11] The application of this method in China has primarily focused on the estimation and spatial distribution of SOC pools at a national scale [12], the impact of wind erosion on soil carbon pools [13], and the impact mechanism of SOC pools at a regional scale [14,15] as well as SOC changes across a time series [16]. The NPV method is an economic method combined with carbon tax and discount rate, while the soil organic carbon estimation method combined with ecosystem carbon cycle process model and net primary productivity estimation model is a more accurate evaluation method, combined with the economic method and remote sensing method, this is a new attempt to evaluate the value of soil organic carbon. This study regarding carbon value according to a scenario mode will provide a useful reference for the future developments in the government’s macro-control of carbon prices
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