# Analysis of Influencing Characteristics of Biochars for Ammonium Adsorption
## 3 Results and Discussion
The results for the purity of solution had a \(p\) value < 0.0001 and washing had a value of 0.0335. These results indicate that washing the biochar after pyrolysis  
Figure 1: Adsorption capacities of different materials. (thus removing ash from the surface) and using a pure solution versus a mixed solution (competition with other ions) can be significant to the adsorption capacity of the biochar. As previously mentioned, the covariance estimates for all collected data produced by EM did not strongly depend on the initial covariance estimate. The converged correlation matrix (using Pearson correlation) with \(\Sigma^{(0)}=I\) is shown below in Figure 2 for \(n=210\). The number of available observations of each variable of interest is shown in Table 2.  
The correlation matrix shown in Figure 3 suggested a positive correlation between adsorption capacity and BET surface area, CEC, and ammonium concentration, and to a lesser extent pyrolysis temperature and solution pH. The magnitude of the correlation coefficients suggests there was a small negative correlation between adsorption capacity and particle size, and adsorption capacity and residence time. The correlation between adsorption capacity and biochar dosage was small and considered negligible for this analysis. From the magnitude of the coefficients, the strongest conclusions to be drawn from this analysis are the positive relationships between adsorption capacity and BET surface area, CEC and NH4+ concentration. These relationships make sense theoretically as well. As the BET surface area increases, there should be more adsorption sites available for ammonium to adhere to. Likewise, with an increase in ammonium concentration in solution, the number of collisions between ammonium ions and the biochar surface would increase, leading to an increase in adsorption. CEC indicates the ability of a material to bind positively charged ions, so an increase in CEC should also correspond with an increase in ammonium adsorption. However, in the case of CEC, the strength of this conclusion should perhaps be tempered--of the 210 reported measurements, only 57 reported CEC. \begin{table}
\begin{tabular}{c c} \hline
**Influencing Factor** & **Available Observations (Out of 210)** \\ \hline Dosage of biochar & 210 \\ pH value of solution & 138 \\ Biochar particle size & 192 \\ Ammonium concentration in solution & 210 \\ Residence time & 198 \\ Surface Area (BET) & 163 \\ Pyrolysis temperature & 205 \\ Cation exchange capacity (CEC) & 57 \\ \hline \end{tabular}
\end{table} 
Table 2: Data availability for influencing factors. Figure 2: Adsorption capacities of different materials. This analysis also showed a strong positive relationship between BET surface area and pyrolysis temperature, which has been proven experimentally in literature [60]. CEC and contact time showed a strong negative relationship, implying that biochar with larger cation exchange capacity should require a shorter contact time to reach equilibrium. This also makes sense as a higher CEC should indicate better and therefore potentially faster adsorption of positive ions like ammonium. Surprisingly, there was no correlation between pyrolysis temperature and CEC. This could be attributed to the fact that the CEC data were limited, but also could point to a stronger role of feedstock in determining CEC than pyrolysis temperature. A meta-analysis performed by [PERSON] et al. showed that average CEC varied much more with feedstock source than pyrolysis temperature or pyrolysis type (fast versus slow), with manure/biosolids having the highest CEC and wood-based materials the lowest (on average) [60]. Interestingly, the surface areas of wood-based materials were much higher on average, and the surface area of manure/biosolid biochars was lowest, with crop waste in between on both parameters.