## 3 Results and Discussion
### Environmental Impact Assessment  
The environmental aspect of the studied power plants at the various locations are estimated in this section. The avoided CO2 emissions from electricity generation due to the use of the STPP for electricity generation can be computed using Equation (10) [61]. \[Mit_{CO2}=E_{g}\times\ F_{e} \tag{10}\]  
where the mitigating CO2 emissions is represented by \(Mit_{CO2}\), \(E_{g}\) denotes the annual produced electricity from the RES, and \(F_{e}\) is the emission factor, taken as 0.8274 kgCO2/kWh [62] for India in the current study. The outcome of the estimations are presented in Table 4. Based on the calculations, it appears that the integration of the STPP into the Indian energy mix could lead to a significant cut in the country's GHG emissions. Bhopal would record the highest reduction in  
Figure 11: Effect of solar multiple on NCC on both models, (**a**) dry-cooled and (**b**) wet-cooled, at 6 h TES. Figure 10: Effect of up-front fee on LCOE of both models, (**a**) dry-cooled and (**b**) wet-cooled, at 6 h TES for SM of 2.  
emissions for both the dry and wet-cooled systems. Avoided emissions of 31,132.50 metric tons and 33,984.63 metric tons of CO\({}_{2}\)e are expected to be recorded per year at the Bhopal region. In total, if a system with a dry-cooled condenser were to be implemented at all six locations with similar capacities, as presented in this study, then India could reduce the country's emissions by some 169,219.62 metric tons of CO\({}_{2}\)e per year. Similarly, if the wet-cold power plants were to be deployed across all six areas, then the avoided emissions for all six locations could be as much as 185,469.90 metric tons of CO\({}_{2}\)e per year. Considering the government's recent commitment to reduce the emission intensity of the country's gross domestic product by 45% by 2030, and its long-term goal of reaching net zero by 2070 [63], the deployment of STPP in the country would significantly help the country to achieve its targets. Finally, in Table 5, the results of the proposed STPP modelled system are compared with those of previous studies according to different CSP technologies/parameters/configurations/economic criterion, i.e., Simulation software, TES, and LCOE. The results as presented in the current work fall within the range of values obtained in other studies, as demonstrated in Table 5. The slight variations in economic output in the results obtained in this study could be attributed to the differences in weather characteristics, type of CSP technology, and the economic parameters used as inputs for the simulations. A higher DNI value for a study area could affect the technical and economic output of the power plant in a more positive way. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**City Name**} & \multicolumn{2}{c}{**Dry-Cooled**} & \multicolumn{2}{c}{**Wet-Cooled**} \\ \cline{2-5}  & **Annual Energy (kWh)** & \
\begin{tabular}{c} **Carbon Footprint,** \\ **(Metric Tons of CO\({}_{2}\)e)** \\ \end{tabular} & **Annual Energy (kWh)** &
\begin{tabular}{c} **Carbon Footprint,** \\ **(Metric Tons of CO\({}_{2}\)e)** \\ \end{tabular} \\ \hline Bhopal & 376,269,000 & 31,132.50 & 410,740,000 & 33,984.63 \\ \hline Jhansi & 364,845,000 & 30,187.28 & 401,175,000 & 33,193.22 \\ \hline Jalandhar & 300,678,000 & 24,878.10 & 330,133,000 & 27,315.20 \\ \hline Srikakulam & 353,159,000 & 29,220.38 & 382,817,000 & 31,674.28 \\ \hline West Medinipur & 301,156,000 & 24,917.65 & 329,713,000 & 27,280.45 \\ \hline Erode & 349,090,000 & 28,883.71 & 387,021,000 & 32,022.12 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Avoided emissions due to the use of the CSP technology.