Just Accepted

The “Just Accepted” manuscripts have gone through the peer-review processes and been accepted for publication. The “Just Accepted” manuscripts are uploaded to the JUSTC website after being polished in a timely fashion, prior to technical editing and formatting as well as author proofing. “Just Accepted” is a free service that allows authors to make their results immediately available to the research community upon the acceptance of their manuscripts. Once the manuscripts have been technically edited and formatted, they will be transferred to the “ASAP Articles” website from the “Just Accepted” website. Please be advised that technical editing and formatting may introduce minor changes to the manuscripts which may affect their contents, and all legal disclaimers that apply to JUSTC pertain. In no event shall JUSTC be held responsible for errors or consequences arising from the use of any information contained in the “Just Accepted” manuscripts. To cite the “Just Accepted” manuscripts, please use their Digital Object Identifiers (e.g., doi: 10.52396/JUSTC-202x-0xxx), which remain identical for all formats of their publication.
Display Method:
Impact of modified SWAT plant growth module on modeling green and blue water resources in subtropics
Tianming Ma, Tianxiao Ma
, Available online  , doi: 10.52396/JUSTC-2023-0023
The dynamics of water availability within a region can be quantitatively analyzed by partitioning the water into blue and green water resources. It is widely recognized that vegetation is one of the key factors that affect the assessment and modeling of blue and green water in hydrological models. However, SWAT-EPIC has limitations in simulating vegetation growth cycles in subtropics because it was originally designed for temperate regions and naturally based on temperature. To perform a correct and realistic assessment of changing vegetation impacts on modeling blue and water resources in the SWAT model, an approach was proposed in this study to modify the SWAT plant growth module with the remotely sensed leaf area index (LAI) to finally solve problems in simulating subtropical vegetation growth, such as controlling factors and dormancy. Comparisons between the original and modified model were performed on the model outputs to summarize the spatiotemporal changes in hydrological processes (including rainfall, runoff, evapotranspiration and soil water content) under six different plant types in a representative subtropical watershed of the Meichuan Basin, Jiangxi Province. Meanwhile, detailed analysis was conducted to discuss the effectiveness of the modified SWAT model and the impacts of vegetation changes on blue and green water modeling. The results showed that (1) the modified SWAT produced more reasonable seasonal curves of plants than the original model. ENS (Nash-Sutcliffe efficiency) and R2 increased by 0.02 during the calibration period and accounted for an increase of 0.09 and 0.03, respectively, during the validation period. (2) The comparison of model outputs between the original and modified SWAT suggested that evapotranspiration was more sensitive to vegetation changes than other components of green water. In addition, vegetation presented conservation capability in the blue water. (3) The variation in blue and green water resources with different plant types after modifying the SWAT model showed that seasonal changes in vegetation led to a significant difference between forest and non-forest areas.
Estimation of peer pressure in dynamic homogeneous social networks
Jie Liu, Pengyi Wang, Jiayang Zhao, Yu Dong
, Available online  , doi: 10.52396/JUSTC-2023-0035
Social interaction with peer pressure is widely studied in social network analysis. Game theory can be utilized to model dynamic social interaction and one class of game network models assumes that peopleos decision payoff functions hinge on individual covariates and the choices of their friends. However, peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model. For this reason, we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks. The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios. To estimate peer pressure in the model, we first present two algorithms based on the initialize expand merge method and the polynomial-time two-stage method to estimate homogeneity parameters. Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure. Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error. We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.
Asymmetric connectedness between China’s carbon and energy markets based on TVP-VAR model
Yu Dong, Xue Yuan, Yuting Wei
, Available online  , doi: 10.52396/JUSTC-2022-0144
An intuitive portrayal of the correlation between the carbon and energy markets is essential for risk control and green financial investment management. In this paper, we examine the asymmetric propagation of return spillovers between carbon and energy markets at the sector level. To achieve that, we improve the Diebold-Yilmaz index by a time-varying vector autoregressive (TVP-VAR) model. In a unified network, our daily dataset includes the closing prices of the Hubei carbon market, Shenzhen carbon market, coal futures, and energy stock index. The findings reveal that both the Hubei and Shenzhen pilots typically generate net information spillovers on energy futures. In connection with energy stocks, the Hubei carbon market acts as a net receiver, while the Shenzhen carbon market is a net transmitter. Compared with the Hubei pilot, the Shenzhen pilot is more tightly connected to the energy markets. Furthermore, the spillovers of the carbon markets exhibit significant asymmetry. In most cases, they have more substantial impacts on the energy markets when the prices of emission allowances rise. The direction and magnitude of asymmetric spillovers across markets vary over time and can be influenced by certain economic or political events.
A hybrid trade-old-for-new and trade-old-for-remanufactured supply chain with carbon tax
Yu Dong, Wuqing Liao
, Available online  
Facing serious environmental problems, governments and manufacturers are taking action to reduce carbon emissions. Among these endeavors, carbon tax policy are widely adopted by governments, trade-old-for-new (TON) and trade-old-for- remanufactured (TOR) are offered by manufacturers and subsidized by governments. To explore the effects of remanufacturer competition and carbon tax on the manufacturer’s TON and TOR decisions and the environment, we formulate three profit maximization models and present some theoretical and numerical analyses. The results show that, under the remanufacturer competition and carbon tax, the manufacturer’s optimal price and production decisions mainly depend on consumer willingness and carbon tax rate. A higher consumer willingness to manufacturer’s remanufactured products will decrease the demand for the manufacturer’s TON, but it always increases the demand foe the manufacturer’s TOR. A higher consumer willingness to remanufacturer’s products will not affect the demand for the manufacturer’s TON; however, it will reduce the demand for manufacturer’s TOR. In addition, we find that a higher carbon tax rate always reduces total carbon emission reduction, and it may increase the manufacturer’s profit due to the increase in TOR demand.
Investigating the mechanisms driving the seasonal variations in surface PM2.5 concentrations over East Africa with the WRF-Chem model
Nkurunziza Fabien Idrissa, Chun Zhao, Qiuyan Du, Shengfu Lin, Kagabo Safari Abdou, Weichen Liu, Xiaodong Wang
, Available online  , doi: 10.52396/JUSTC-2022-0142
Most previous studies on surface PM2.5 concentrations over East Africa focused on short-term in situ observations. In this study, the WRF-Chem model combined with in situ observations is used to investigate the seasonal variation in surface PM2.5 concentrations over East Africa. WRF-Chem simulations are conducted from April to September 2017. Generally, the simulated AOD is consistent with satellite retrieval throughout the period, and the simulations depicted the seasonal variation in PM2.5 concentrations from April to September but underestimated the concentrations throughout the period due to the uncertainties in local and regional emissions over the region. The composition analysis of surface PM2.5 concentrations revealed that the dominant components were OIN and OC, accounting for 80% and 15% of the total concentrations, respectively, and drove the seasonal variation. The analysis of contributions from multiple physical and chemical processes indicated that the seasonal variation in surface PM2.5 concentrations was controlled by the variation in transport processes, PBL mixing, and dry and wet deposition. The variation in PM2.5 concentrations from May to July is due to wind direction changes that control the transported biomass burning aerosols from southern Africa, enhanced turbulent mixing of transported aerosols at the upper level to the surface and decreased wet deposition from decreased rainfall from May to July.