The Taihang Mountains are an important ecological barrier in China, and their ecosystems have good carbon sink capacity. Studying the spatial-temporal variation characteristics and driving factors of carbon storage in the Taihang Mountains ecosystem provides decision-making for the construction of “dual carbon” projects and the improvement of ecological environment quality in this region. This paper takes the area in the Taihang Mountains as the research area, based on the land use and carbon density data of 2005, 2010, 2015, and 2019 of the Taihang Mountains, calculates the carbon storage in the region with the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, explores the main factors affecting the spatial differentiation of carbon storage in this region, and analyzes their driving mechanisms by Geodetector. The results show that: (1) From 2005 to 2019, the land use of the Taihang Mountains changed somewhat. The area of forest and construction land increased slightly, while the area of farmland and grassland decreased. (2) The current carbon storage in the Taihang Mountains ranges from 1472.91 × 10⁶ t to 1478.17 × 10⁶ t (t is the abbreviation of ton), and shows a decreasing trend, which is due to the decrease in forest and the increase in construction land. (3) Slope and Normalized Difference Vegetation Index (NDVI) are the main driving factors affecting the spatial variation of carbon storage in the Taihang Mountains ecosystem. Temperature, precipitation, and population density are the secondary factors affecting the spatial variation of carbon storage. (4) The synergy between the driving factors is more potent than the individual factor, which is the most evident between NDVI and slope. This means some areas may have more abundant carbon storage under the combined effect of slope and NDVI.

A series of anilido–imine chromium complexes have been used as precursors to catalyze homo- and copolymerization of ethylene and norbornene. The chromium complexes activated with methylalumoxane (MAO) exhibit good activities for homopolymerization of ethylene (E) to produce linear polyethylene and moderate activities for norbornene (N) polymerization to afford vinyl-type polynorbornene. Ethylene–norbornene copolymers with high incorporation of norbornene can be also produced by these catalysts. ¹³C NMR and differential scanning calorimetry (DSC) analyses show that the copolymers are random products, and –NNN– and –EEE– units can be observed in the microstructure of the copolymers.

In this paper, the sensitivity factors of CO₂ huff-n-puff for multifractured horizontal wells (MFHWs) in tight oil reservoirs were investigated through an experimental test and numerical simulation. The pressure-volume-temperature (PVT) experiment and the slim tube experiment are used to understand the interaction mechanism between CO₂ and crude oil, and the minimum miscibility pressure (MMP) of the CO₂-crude oil system is 17MPa. The single-well model was firstly established to analyze the sensitivity factors on production performance of MFHWs by using CO₂ huff-n-puff. The controlling factors of CO₂ huff-n-puff for MFHWs in tight oil reservoirs were divided into three categories (i.e., reservoir parameters, well parameters, and injection-production parameters), and the impact of individual parameter on well performance was discussed in detail. The range of reservoir parameters suitable for CO₂ huff-n-puff of MFHWs is obtained. The reservoir permeability is from 0.1mD to 1mD, the reservoir thickness changes from 10m to 30m, and the reservoir porosity is from 7 to 12. Based on the reservoir parameters of the target reservoir, the reasonable well and fracture parameters are obtained. The sensitivity intensity was followed by the horizontal well length, fracture conductivity, fracture spacing, and fracture half-length. CO₂ injection-production parameters are further optimized, and the sensitivity intensity was followed by the single-cycle cumulative CO₂ injection rate, the soaking time, the injection rates, and the production rates. It provides a reference for parameter optimization of CO₂ huff-n-puff for MFHWs in tight oil reservoirs.