## 3 Results and Discussion
### DPV Analytical Curve and Standard Additions Method in River Water Sample  
From the results obtained in our previous work, the composite sensor exhibited an excellent response for detecting HCQ in H\({}_{2}\)SO\({}_{4}\)/ultrapure water solution. However, the use of ultrapure water with a single target pollutant could mask the applicability of the experimental data to actual uses [20] with real water matrices (which are composed by several inorganic and organic compounds that can affect the electrochemical sensor response to quantify HCQ). Then, this composite sensor was used to construct an analytical curve with a non-polluted river water matrix (see Table 1). As can be observed in Figure 1, the sensor presented excellent performances, in terms of the electrochemical response (current vs. (HCQ)) as a function of HCQ concentration, when a non-polluted river water sample was used. This behavior demonstrated that non-significant matrix effect was attained at surface sensor during the analytical curve construction. In other words, it was possible to confirm that real water composition did not affect the detection of HCQ. The analytical curve was represented considering the current-peak (I\({}_{\text{p}}\)) responses as a function of the linear increase of the HCQ concentration (Figure 1a), in the range from 2.5 to 40 mg L\({}^{-1}\) (5.72\(-\)92.17 uM). The linear regression equation (I\({}_{\text{p}}\) vs. (HCQ)) was determined as, I\({}_{\text{p}}\)(I) = 3.7 \(\times\) 10\({}^{-3}\)\(\times\) [HCQ] \(-\) 1.3 \(\times\) 10\({}^{-2}\) (R\({}^{2}\) = 0.990). The limit of detection (LOD) and limit of quantification (LOQ) were found to be 1.46 mg L\({}^{-1}\) (\(\approx\)3.36 uM) and 4.42 mg L\({}^{-1}\) (\(\approx\)10.19 uM), according to Equations (3) and (4). \[\text{LOD}=3.3\times\text{S}_{\text{y/x}}/\text{b} \tag{3}\]  
\[\text{LQ}=10\times\text{S}_{\text{y/x}}/\text{b} \tag{4}\]  
Figure 1: (**a**) DPV curves for electrochemical cork-graphite sensor in acidified sample of river water sample by adding well-known volumes (HCQ solution (10 mM)) to obtain: (a) 2.5 (b) 5, (c) 10, (d) 15, (e) 20, (f) 25, (g) 30, (h) 40 mg L\({}^{-1}\). Blank is the red dashed line. Inset: Plot of electrochemical responses, in terms of current, as a function of HCQ concentration. (**b**) Graphic representation of the residual’s behavior, which confirms the linearity of the calibration curve. where S\({}_{\rm{y/x}}\) is the residual standard deviation and b is the slope of the calibration plot [28; 29]. The non-linearity was also evaluated from the residuals of regression curve, as can be observed in Figure 1b. Thus, the absence of significant non-linearity was confirmed, guaranteeing the reliability in real water matrices, as recommended by IUPAC [28; 30] and the literature [31]. It is important to highlight that all analyses were performed in triplicate, consequently it was possible to obtain the confidence intervals and standard deviations within 95% (red dotted lines in analytical curve). Thus, this information was used in order to identify false positives and false negatives (\(\alpha=\beta=0.05\)), as already reported by experts in the field [31]. Later, to evaluate the reliability of directly using the composite sensor in real water matrices, the sensor was used to electroanalytically quantify the HCQ concentration by standard addition method in the polluted river water sample. As can be observed in Figure 2, the HCQ signal was confirmed by intensification of the peaks associated with the addition of different volumes of standard HCQ solution to polluted sample [32]. The HCQ concentration electroanalytically determined by DPV approach was about 26.87 \(\pm\) 0.34 mg L\({}^{-1}\) (61.92 \(\pm\) 0.04 mM), which was similar to the spectrophotometric measurement reported in Table 1. It is important to highlight that the results were obtained with acceptable standard deviations and confidence intervals, within 95% [31].