## 4 Discussion
### Some Issues Related to the Empirical Models of GPP, Re and NEP  
Briefly, PAR absorption and indirect use by atmospheric components through chemical and photochemical reactions mainly associated with excited NO\({}_{2}\) (NO\({}_{2}\)*), H\({}_{2}\)O, OH radicals [88] and BVOCs + OH + O\({}_{3}\). Thus, the photochemical term expressed the total PAR used by GLPs. In Equations (1) and (2), the multiple interactions between PAR and the terms (photochemical, scattering, Re term in this study instead of BVOC terms) are explained in EMBE development in more detail [55, 89].  
The EMGPP showed that the GPP increases with the decrease in S/Q (i.e., the increase in the scattered PAR by GLPs, including aerosols and clouds) [45], which were also in good agreement with model studies and observations (the enhanced diffuse radiation caused by the aerosols results in the enhancement of GPP) [90, 91, 92, 93, 94, 95, 96, 97]. Considering similar phenomena for respiration (Section 3.1.1) together, the diffuse radiation associated with the atmospheric GLP substances, i.e., light use efficiency, how much direct and diffuse PAR is absorbed by plants, play significant roles in plant growth and model simulations.  
To better evaluate the empirical model performance, it is beneficial to understand the uncertainties in the measurements and popular model predications. A relative uncertainty of 20-50% for the CO\({}_{2}\) eddy covariance measurements is reported in [29]. The annual sums of NEE are 600 \(\pm\) 130 gC m\({}^{-2}\) year\({}^{-1}\), 300 \(\pm\) 180 gC m\({}^{-2}\) year\({}^{-1}\) at different forests [26]. Uncertainty for the annual NEE estimation is 12-32% [27]. A range of \(\pm\)32% for the annual NEE, GPP, and ecosystem respiration values was used [98]. The annual NEP estimates using traditional ecological models agree with the flux measurements in 5%, 30%, and 100% [24, 25, 26]. The relative error of the PAR sensor is better than \(\pm\)5% [78]. The yearly non-stability is <2% for global solar radiation sensor and <1% for solar direct radiation sensor [86]. The averaged relative bias of water vapor is less than 18% [99]. The uncertainties/responses of GPP to its driving factors (PAR, water vapor, and S/Q) using EMGPP is fully reported in [45] and can be used as a reference for the Re and NEP simulations.  
Using the PAR energy balance method in this coniferous forest, we made applications of EMBE to GPP, then the Re and NEP simulations. Generally, the reasonable estimates of Re and NEP were obtained. The GPP, Re, and NEP empirical models are simple, timesaving, and the input parameters are easily obtained from the weather and solar radiation stations. They also revealed some basic mechanisms, which agreed with model studies, e.g., GPP, Re, NEP, and NEE increased with the increases in the diffuse PAR [82, 83]. It is an important application that the Re (DR) model can also be used to calibrate the longwave radiation sensor (Section 4.2). In all, the empirical models in simulations of BVOCs, GPP, Re, and NEP are useful and suggested to be investigated at other flux stations for a more thorough estimation of the total carbon balance [70, 100].