TY - JOUR
AU - Bartkevics,, Vadims
AB - Abstract Multiple food research studies have shown that the polycyclic aromatic hydrocarbon (PAHs) are frequently found in processed cocoa products and chocolate. In a present study a method based on dopant-assisted atmospheric pressure photoionisation (DA-APPI) combined with a liquid chromatography/high-resolution mass spectrometer (HPLC–HRMS) for high-sensitivity analysis of four EU marker PAHs in dark chocolate samples was developed and fully validated according to the performance criteria set in EU guidelines. PAHs detection was achieved by HRMS in positive electrospray ionization mode with toluene used as a dopant to enhance the ionization efficiency of non-polar PAHs. The on-column instrument detection limits ranged from 0.8 to 1.2 pg for all four marker compounds. The method detection limits ranged from 0.016 to 0.024 μg kg−1 expressed on fat basis. The elaborated method was successfully applied to the analysis of four EU marker PAHs in dark chocolate samples. The presence of benzo[a]anthracene, benzo[b]fluoranthene and chrysene revealed at detectable levels in 100% of the samples, while benzo[a]pyrene was revealed in 77% of the samples, with its content ranging from 0.08 to 2.90 μg kg−1 fat. Introduction Polycyclic aromatic hydrocarbons (PAHs) constitute a large class of organic compounds (comprising ~10,000 substances) characterized by a structure composed of carbon and hydrogen atoms arranged in two or more fused aromatic rings without any heteroatoms or substituents (1). PAHs can be classified according to the number of condensed aromatic rings as light (2–3 rings) or heavy (4–6 rings) PAHs, the latter being more stable and toxic than the light ones (2). A number of PAHs are considered as genotoxic carcinogens with pronounced mutagenic effects. Other PAHs that are not defined as carcinogens may act as synergists of carcinogenesis (3). Food consumption was shown to be the main source of PAH intake for non-smokers, and this fact highlights the importance of research about PAHs in food and the development of mitigation strategies to reduce such contamination (4). PAHs occurring in foods are not present individually, but always exist as complex mixtures, so the occurrence of a whole range of PAHs in food and environment represents a cause for concern. PAHs that are found in foods may be formed during industrial food processing or domestic food preparation, such as smoking, drying, roasting, baking, frying or grilling. Food can be also contaminated with PAHs present in the environment, i.e., PAHs can accumulate on the waxy surfaces of many vegetables and fruits. Indeed, the presence of PAHs in uncooked food, such as vegetables, seeds, and grains has also been demonstrated. For example, Fismes et al. (5) have experimentally demonstrated the uptake of PAHs by fruit and vegetables grown in contaminated soils. Another example of possible PAH contamination in foods is due to traffic exaust, i.e., crops or livestock close to busy roads could be exposed to PAHs and nitro-PAHs (derivatives from PAHs), which often show higher mutagenic, carcinogenic and toxic activity in comparison to their corresponding PAHs (6). Cocoa is an important commercial crop—the raw material from which chocolate is manufactured. A number of manufacturing steps are necessary for the production of a homogenous chocolate of high quality with respect to flavor, consistency and homogeneity. The manufacturing process includes some critical steps during which cocoa products including chocolate may be contaminated with PAHs. According to literature data (7), PAH contamination in chocolate mainly can be affected by drying, roasting, winnowing, blending and fermenting of the cocoa beans, typically in their country of origin (7, 8). Cocoa butter is a major constituent of raw cocoa products (e.g., cocoa beans, cocoa mass or cocoa nibs) that is eventually present in chocolate and other processed cocoa products. It has been confirmed by many researchers that cocoa butter might contain even higher levels of PAH than other oils and fats and it cannot be refined by processes applied to other vegetable oils and fats (4, 9, 10). Therefore, the maximum permissible levels for PAHs in cocoa beans and derived products were established on a fat basis since PAHs tend to concentrate in the fat fraction, which is the cocoa butter (Commission Regulation (EC) No 835/2011) (11). It should be mentioned that cocoa beans and derived products are the only food categories for which the maximum permissible levels of PAHs are based on the fat fraction. EU has established the maximum level for benzo[a]pyrene (BaP) and for the sum of the four marker PAHs (benzo[a]anthracene (BaA), benzo[b]fluoranthene (BbF), chrysene (Chr) and BaP) as 5.0 and 30.0 μg kg−1 fat, respectively. The second maximum level for the sum of four marker PAHs came into force on 1 April 2015 (Commission Regulation (EU) No. 2015/1933) (12). For the purpose of supporting the implementation of the regulated limits of PAHs in cocoa products, the EU Reference Laboratory for Polycyclic Aromatic Hydrocarbons (EURL PAHs) had organized two inter-laboratory comparisons (ILC) for the determination of the four marker PAHs in cocoa products—EURL ILC 2012 (dark chocolate and cocoa butter) (13) and EURL ILC 2015 (cocoa powder and milk chocolate) (14). The overall performance of most participants was good, but both of the ILC results pointed to several difficulties nevertheless. For example, a severe decline in performance was noticed in 2012 for results expressed on fat basis. The determination of the analytes in cocoa powder caused more problems in 2015 than their determination in milk chocolate. The Z-scores outside the satisfactory range were 28 on product base and 31 on fat base for the chocolate test sample, while for cocoa powder they were 47 and 55, respectively. The overall evaluation of the ILC results in 2015 showed that only 58% of the zeta-scores assigned to the four individual analytes and to the sum of four PAHs were within the satisfactory performance range, and only 20 labs out of 41 had no Z-scores outside the satisfactory range. This might be partially explained by the higher degree of difficulty related to low analyte contents, a low fat content and the complexity of the cocoa powder matrix. Thus, the results of EURL ILCs as well as recently published research papers indicated that a more comprehensive method for the determination of PAHs in such complex matrices as chocolate is needed. The analytical determination of PAHs can be carried out by both liquid chromatography (LC), including ultra-high-performance LC (UPLC) and gas chromatography (GC) with various detectors, or by comprehensive techniques (GCxGC and LCxLC) (2). The LC determination of PAHs usually is carried out by LC coupled to fluorescence (LC-FLD) or ultraviolet–visible detection (LC–UV) techniques, which are also described in some official methods according to the International Standardization Organization and the United States Environmental Protection Agency (US EPA). However, it is well known that UV detection shows a number of disadvantages, such as selectivity problems and sensitivity limitations, and it cannot discriminate matrix interferences, especially in complex matrices. On the contrary, FLD is more selective and sensitive than UV detection, and it is currently the detection system of choice in LC analysis of PAHs. LC-FLD has been extensively applied for the determination of PAHs in very different matrices, including foodstuffs and beverages, since it is simple and affordable compared to other detection systems (1). Despite the advantages of FLD compared to UV detection, FLD can still show a lack of selectivity. Moreover, some authors describe certain selectivity problems due to the presence of alkylated PAHs, which are considered to be the main impurities of PAH fractions (15). These compounds show fluorescence responses similar to the unsubstituted PAHs. Another disadvantage is the impossibility of using certain isotopically labeled compounds that cannot be distinguished by FLD from the native PAHs (1, 2). Mass spectrometric detection methods have become popular because of the high selectivity that enables reliable confirmation of analyte identity and the possibility to use stable isotope labeled PAHs as internal standards (4). The most commonly used ion sources in LC–mass spectrometry (MS) analysis are electrospray ionization (ESI) and atmospheric-pressure chemical ionization sources (APCI). However, such ion sources provide insufficient efficiency for the ionization of non-polar PAHs. APPI appears to be a good alternative to ESI and APCI for the coupling of low flow rate separation techniques (<50 μL min−1) and capillary LC, due to the lower concentration of the solvent vapor in the ion source. Furthermore, APPI is generally considered to be a compatible ionization technique for non-polar compounds. In fact, APPI was found by various authors to be more complementary to ESI than APCI, due to its ability to ionize less polar molecules than those that can be ionized in APCI, and this type of interface also shows less ion suppression than APCI and ESI (2, 16). Most of the LC-APPI studies describe the usage of single quadrupole (MS) and triple quadrupole (MS/MS) analyzers, whereas other types of analyzers such as high-resolution MS (e.g., time-of-flight, Orbitrap) are rarely used. In order to surmount the aforementioned difficulties, the present study is focussed on the development and optimization of a novel LC–APPI-Orbitrap-MS analytical method for sensitive and selective determination of four EU marker PAHs in samples of a complex matrix—dark chocolate. Experimental Chemicals and standards The solvents used (acetonitrile, cyclohexane, n-hexane, dichloromethane and ethyl acetate) were of pesticide purity grade and were purchased from Sigma-Aldrich (Steinheim, Germany). Anhydrous sodium sulfate and Strata SI-1 Silica solid-phase extraction (SPE) tubes (6 mL (500 mg)) were obtained from Supelco (Bellefonte, PA, USA) and Phenomenex (Torrance, CA, USA), respectively. Four individual PAH standards (BaA, BbF, BaP and Chr) (50 mg L−1 each in acetonitrile) and isotopically labeled deuterated standards (BaP-d12, BbF-d12, Chr-d12 and BaA-d12) (1 mg L−1 each in toluene) were purchased from Dr Ehrenstorfer and were stored at 4°C. The spiking solutions and calibration standards were prepared by serial dilution of stock standards in toluene and were stored in UV-protected glassware at 4°C. Samples Overall, 26 randomly selected dark chocolate samples with cocoa content in a range of 41–77% from different countries were analyzed during this study. All the samples were obtained from local supermarkets. To avoid potential chemical composition changes, all samples were immediately prepared upon arrival to the laboratory and the final extracts were stored at −20°C before performing the instrumental analysis. Sample preparation and clean-up Samples were ground and homogenized. A 2.75 g portion of each homogenized chocolate sample was thoroughly mixed with 10 g of anhydrous sodium sulfate to absorb moisture. A 27.5 μL aliquot of toluene solution of internal standards including BaP-d12, Chr-d12, BbF-d12 and BaA-d12 with 1.0 μg mL−1 concentration was added. The PAHs were extracted from chocolate samples by adding 25 mL of dichlormethane/n-hexane (1:1, v/v) mixture and performing sonication for 20 min. After sonication, the supernatant was decanted to pre-weighed round-bottom flask and 15 mL of fresh solvent was added to the sample for another 20 min of sonication. To avoid the presence of solid particles, all the extracts were filtered. The combined extracts (~40 mL) were rotary evaporated (30°C, 500–100 mbar) to dryness to eliminate the solvents, and fatty residue was then weighed to determine the fat content. Further, fatty residue was reconstituted in 5.5 mL of cyclohexane/ethyl acetate (1:1, v/v) mixture and elimination of high-molecular compounds by the means of gel permeation chromatography (GPC) was performed. The extracts were centrifuged at 3,000 rpm for 10 min and the solution was transferred into a glass GPC vial. The extracts were injected into LC Tech Freestyle™ GPC system (Dorfen, Germany) consisting of an HPLC pump, autosampler, and a fraction collector. High-molecular substances were removed on a glass column (500 × 40 mm, 25 mm ID) filled with 50 g of Bio-Beads SX3 (Bio-Rad, Philadelphia, PA, USA) stationary phase with cyclohexane/ethyl acetate (1:1, v/v) mobile phase at a flow rate of 5 mL min−1. The automated GPC program was as follows: dump time 0–21 min, collection time 21–45 min. The collected fractions were transferred to round-bottom flasks and then evaporated to dryness on a rotary evaporator (30°C, 130 mbar). The dry residue was dissolved in cyclohexane (3 mL). Further clean-up was performed by using SPE Silica cartridges. The sorbent of the SPE cartridges was first conditioned with cyclohexane (5 mL) and the extracts were loaded onto the cartridges. The analytes of interest were eluted from the cartridges with cyclohexane (3 × 3 mL), the obtained fractions were evaporated under a slow stream of nitrogen at 40°C, dissolved in acetonitrile (100 μL), and transferred into autosampler vials for the further HPLC-Orbitrap-MS analysis of PAHs. HPLC parameters A Thermo Scientific Dionex Ultimate 3000 Series RS pump coupled to a Thermo Scientific Dionex Ultimate 3000 Series TCC-3000RS column compartments and a Thermo Fisher Scientific Ultimate 3000 Series WPS-3000RS autosampler controlled by Chromeleon 7.2 software (Thermo Fisher Scientific, Waltham, MA and Dionex Softron GmbH, Part of Thermo Fisher Scientific, Germany) were used for the analysis. A Pinnacle DB PAH 50 mm × 2.1 mm, ID 1.9 μm (Restek, Bellefonte, PA, USA) column was used for the chromatographic separation of target compounds at 30°C. Mobile phase A consisted of 100% water, and mobile phase B consisted of 100% acetonitrile. The gradient was started from 50% B, then the phase B was increased to 90% from 0 to 1 min, after that the phase B was increased to 95% (1–2 min) and, finally, to 100% (2–5 min), and was held constant for 1 min. Finally, the mobile phase was brought back to the initial conditions and maintained for 1 min. The selected flow rate was 0.4 mL min−1 and the injection volume was 5 μL. HRMS parameters The determination of target analytes was performed using an HPLC-Orbitrap-MS system consisting of Thermo Accela HPLC instrument (Zwingen, Switzerland) coupled to an Orbitrap Q-Exactive mass spectrometer (Bremen, Germany) equipped with a Thermo Scientific Ion Max APCI/APPI interface (Thermo Fisher Scientific). The Ion Max source housing was equipped with a Syagen Photo-Mate vacuum UV light source (krypton discharge lamp, 10.0 eV) (Syagen Technology Inc., Tustin, CA, USA). The APCI probe was used as a nebulizer-desolvation device without applying corona discharge. The mass spectra were recorded in the positive ion mode. During the tuning procedure, the signals of target analytes were preliminarily optimized for the highest response of the corresponding ions. Introduction of the target compounds (native analytes and deuterated internal standards, 1 ng mL−1 in toluene) into the APPI interface of MS system was performed using a Chemyx Fusion 100 T (Stafford, TX, USA) infusion pump at the flow rate of 50 μL min−1 through a T-piece connected to the capillary, which delivered the mobile phase to the ion source with a flow rate of 400 μL min−1. Orbitrap-MS detection in targeted-MS2 (tMS2) mode that provides the possibility of MS/MS experiments, was applied for the quantitative determination of selected compounds using the two most abundant ions of the respective molecular ion cluster for both the native components and the deuterated internal standards. The width of the ion-extraction window was 5 × 10−6 amu (5 ppm). External calibration of the Orbitrap-MS system was performed before each batch of samples over the m/z range of 50–2,000 according to the guidelines provided by the instrument supplier. The details of the optimized instrumental parameters in tMS2 mode are summarized in Table I. Table I. The Optimized DA-APPI-Orbitrap-MS Parameters for tMS2 Mode APPI parameters  Sheath gas flow 40 a.u.  Auxiliary gas flow 30 a.u.  Sweep gas flow 0 a.u.  Capillary temperature 300°C  Source heater temperature 350°C  S-lens radio frequency 35 a.u.  Dopant Toluene  Dopant flow rate 50 μL min−1 Orbitrap-MS parameters  Detection mode tMS2  Maximum injection time 100 ms  Automatic gain control (AGC target) 2 × 105  MS resolving power 17,500 FWHM APPI parameters  Sheath gas flow 40 a.u.  Auxiliary gas flow 30 a.u.  Sweep gas flow 0 a.u.  Capillary temperature 300°C  Source heater temperature 350°C  S-lens radio frequency 35 a.u.  Dopant Toluene  Dopant flow rate 50 μL min−1 Orbitrap-MS parameters  Detection mode tMS2  Maximum injection time 100 ms  Automatic gain control (AGC target) 2 × 105  MS resolving power 17,500 FWHM a.u. = arbitrary unit. Table I. The Optimized DA-APPI-Orbitrap-MS Parameters for tMS2 Mode APPI parameters  Sheath gas flow 40 a.u.  Auxiliary gas flow 30 a.u.  Sweep gas flow 0 a.u.  Capillary temperature 300°C  Source heater temperature 350°C  S-lens radio frequency 35 a.u.  Dopant Toluene  Dopant flow rate 50 μL min−1 Orbitrap-MS parameters  Detection mode tMS2  Maximum injection time 100 ms  Automatic gain control (AGC target) 2 × 105  MS resolving power 17,500 FWHM APPI parameters  Sheath gas flow 40 a.u.  Auxiliary gas flow 30 a.u.  Sweep gas flow 0 a.u.  Capillary temperature 300°C  Source heater temperature 350°C  S-lens radio frequency 35 a.u.  Dopant Toluene  Dopant flow rate 50 μL min−1 Orbitrap-MS parameters  Detection mode tMS2  Maximum injection time 100 ms  Automatic gain control (AGC target) 2 × 105  MS resolving power 17,500 FWHM a.u. = arbitrary unit. The general requirements for quantification and confirmation of an analyte by the means of Q-Orbitrap systems are to monitor the retention time of an analyte, to record chromatographic peaks by detecting the mass signal of precursor ion and at least one product ion. In order to obtain a precursor and a product ion, the predefined experiment templates—full scan (FS), targeted-SIM (tSIM) and tMS2 were used. The average experimental mass of precursor ion as well as the ion masses used for the quantification and confirmation of all four marker PAHs are shown in Table II. Table II. HRMS Scan Parameters of the Detection of Selected PAHs PAH Chemical formula RT (min) Calculated exact mass [M]+ (m/z) Experimental mass [M]+ (m/z) Mass accuracy (ppm) NCE, % Quantification iona mass (m/z) Experimental quantification iona mass (m/z) Mass accuracy (ppm) Confirmation ionb mass (m/z) Experimental confirmation ionb mass (m/z) Mass accuracy (ppm) BaA C18H12 3.77 228.0939 228.0943 1.62 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 Chr C18H12 3.91 228.0939 228.0945 2.72 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 BbF C20H12 4.40 252.0939 252.0936 −1.15 100 250.07825 250.07844 0.76 226.07825 226.07885 2.65 BaP C20H12 4.88 252.0939 252.0937 −0.67 100 250.07825 250.07846 0.84 226.07825 226.07884 2.61 BaA-d12 C18D12 3.68 240.1692 240.1697 2.08 110 236.14100 236.14190 3.81 212.14100 212.14170 3.30 Chr-d12 C18D12 3.81 240.1692 240.1703 4.58 100 236.14100 236.14190 3.81 212.14100 212.14170 3.30 BbF-d12 C20D12 4.29 264.1692 264.1683 −3.41 110 260.14100 260.14040 −2.31 236.14100 236.14090 −0.42 BaP-d12 C20D12 4.73 264.1692 264.1682 −3.79 120 260.14100 260.14050 −1.92 236.14100 236.14120 0.85 PAH Chemical formula RT (min) Calculated exact mass [M]+ (m/z) Experimental mass [M]+ (m/z) Mass accuracy (ppm) NCE, % Quantification iona mass (m/z) Experimental quantification iona mass (m/z) Mass accuracy (ppm) Confirmation ionb mass (m/z) Experimental confirmation ionb mass (m/z) Mass accuracy (ppm) BaA C18H12 3.77 228.0939 228.0943 1.62 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 Chr C18H12 3.91 228.0939 228.0945 2.72 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 BbF C20H12 4.40 252.0939 252.0936 −1.15 100 250.07825 250.07844 0.76 226.07825 226.07885 2.65 BaP C20H12 4.88 252.0939 252.0937 −0.67 100 250.07825 250.07846 0.84 226.07825 226.07884 2.61 BaA-d12 C18D12 3.68 240.1692 240.1697 2.08 110 236.14100 236.14190 3.81 212.14100 212.14170 3.30 Chr-d12 C18D12 3.81 240.1692 240.1703 4.58 100 236.14100 236.14190 3.81 212.14100 212.14170 3.30 BbF-d12 C20D12 4.29 264.1692 264.1683 −3.41 110 260.14100 260.14040 −2.31 236.14100 236.14090 −0.42 BaP-d12 C20D12 4.73 264.1692 264.1682 −3.79 120 260.14100 260.14050 −1.92 236.14100 236.14120 0.85 a[M–H2]+ or [M–D2]+. b[M–C2H2]+ or [M–C2D2]+. Table II. HRMS Scan Parameters of the Detection of Selected PAHs PAH Chemical formula RT (min) Calculated exact mass [M]+ (m/z) Experimental mass [M]+ (m/z) Mass accuracy (ppm) NCE, % Quantification iona mass (m/z) Experimental quantification iona mass (m/z) Mass accuracy (ppm) Confirmation ionb mass (m/z) Experimental confirmation ionb mass (m/z) Mass accuracy (ppm) BaA C18H12 3.77 228.0939 228.0943 1.62 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 Chr C18H12 3.91 228.0939 228.0945 2.72 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 BbF C20H12 4.40 252.0939 252.0936 −1.15 100 250.07825 250.07844 0.76 226.07825 226.07885 2.65 BaP C20H12 4.88 252.0939 252.0937 −0.67 100 250.07825 250.07846 0.84 226.07825 226.07884 2.61 BaA-d12 C18D12 3.68 240.1692 240.1697 2.08 110 236.14100 236.14190 3.81 212.14100 212.14170 3.30 Chr-d12 C18D12 3.81 240.1692 240.1703 4.58 100 236.14100 236.14190 3.81 212.14100 212.14170 3.30 BbF-d12 C20D12 4.29 264.1692 264.1683 −3.41 110 260.14100 260.14040 −2.31 236.14100 236.14090 −0.42 BaP-d12 C20D12 4.73 264.1692 264.1682 −3.79 120 260.14100 260.14050 −1.92 236.14100 236.14120 0.85 PAH Chemical formula RT (min) Calculated exact mass [M]+ (m/z) Experimental mass [M]+ (m/z) Mass accuracy (ppm) NCE, % Quantification iona mass (m/z) Experimental quantification iona mass (m/z) Mass accuracy (ppm) Confirmation ionb mass (m/z) Experimental confirmation ionb mass (m/z) Mass accuracy (ppm) BaA C18H12 3.77 228.0939 228.0943 1.62 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 Chr C18H12 3.91 228.0939 228.0945 2.72 100 226.07825 226.07916 4.03 202.07825 202.07916 4.50 BbF C20H12 4.40 252.0939 252.0936 −1.15 100 250.07825 250.07844 0.76 226.07825 226.07885 2.65 BaP C20H12 4.88 252.0939 252.0937 −0.67 100 250.07825 250.07846 0.84 226.07825 226.07884 2.61 BaA-d12 C18D12 3.68 240.1692 240.1697 2.08 110 236.14100 236.14190 3.81 212.14100 212.14170 3.30 Chr-d12 C18D12 3.81 240.1692 240.1703 4.58 100 236.14100 236.14190 3.81 212.14100 212.14170 3.30 BbF-d12 C20D12 4.29 264.1692 264.1683 −3.41 110 260.14100 260.14040 −2.31 236.14100 236.14090 −0.42 BaP-d12 C20D12 4.73 264.1692 264.1682 −3.79 120 260.14100 260.14050 −1.92 236.14100 236.14120 0.85 a[M–H2]+ or [M–D2]+. b[M–C2H2]+ or [M–C2D2]+. The validation of analytical method The proposed dopant-assisted atmospheric pressure photoionisation (DA-APPI)–HPLC-Orbitrap-MS method was validated according to the Commission Regulations (EU) No. 836/2011, 2015/1933 and 2016/582 (12, 17, 18). LOD, LOQ, as well as the recovery and precision of the analytical procedure were estimated within the study. Recovery experiments were performed by spiking chocolate samples with standard solutions containing PAHs at three different concentrations: 0.1, 1.0 and 5.0 μg kg−1 expressed on fat basis. Each spiking level was repeated, resulting in 3 × 5 individual sample analyses. Internal standard calibration was used for each compound. A linear calibration function was utilized, including a forced intercept at zero and 1/x weighting. The correlation coefficient (r2) values were calculated for nine spiking levels (0.10, 0.15, 0.20, 0.25, 0.30, 0.50, 1.0, 2.0 and 5.0 μg kg−1). Recoveries were calculated as differences in the PAHs content in spiked and non-spiked samples relative to the spiking level. For these recovery analyses, the repeatability of the method was expressed as the relative standard deviation (RSD) in %, and therefore as the coefficient of variation (CV). In accordance with Commission Regulation (EU) No. 836/2011 (17), the HORRATR values are regarded as a measurement of the method precision. The HORRATR values were calculated for all four marker PAHs analyzed at each of the three different concentrations. Results Optimisation of the sample clean-up and HPLC conditions Since the concentrations of PAHs in food are very low, generally in the range of parts per billion, the sample clean-up procedures usually consist of several extraction and purification steps (4). The analytical procedure for the present study was based on a previously published GC–MS-MS analytical method and included extraction of PAHs with dichlormethane/n-hexane mixture, GPC and solid phase extraction (19). The sample clean-up procedure used in the aforementioned reference was suitable for sensitive analysis of bread samples and in the current study it was concluded that it could be used for PAHs analysis in chocolate samples without any significant modifications. During the optimization of the sample clean-up procedure, we attempted to analyze the chocolate samples without the final purification step (solid phase extraction), and it was found that a sample clean-up apart from GPC was not strictly necessary for the APPI. However, for routine applications, the SPE clean-up step is very beneficial in order to avoid contamination of the ion source. In order to achieve the highest possible instrumental selectivity for specific PAHs, the parameters of HPLC analysis were optimized. Based on previous studies regarding the analysis of PAHs using LC–MS (1, 2, 20), two different LC columns were tested—LiChrospher PAH 250 mm × 3 mm, ID 5 μm (Merck Millipore, Darmstadt, Germany) and Pinnacle DB PAH 50 mm × 2.1 mm, ID 1.9 μm (Restek, Bellefonte, PA, USA). The initial experiments were based on the manufacturer’s recommendations and then optimized to achieve better separation of the analytes. Both columns demonstrated acceptable results even for the critical compounds—BbF and Chr. The main difference between the two tested columns was the total run time of the sample analysis. Sufficient separation of PAHs was achieved within a 6 min run on the Pinnacle DB PAH column, whereas LiChrospher PAH 250-3 showed acceptable results only after a 25 min run. Therefore, the selection of Pinnacle DB PAH analytical column was more reasonable. The optimal column flow rate of 0.4 mL/min was used, and was proved to be well suited for direct coupling with the APPI interface. Chromatographic separation of the analytes was achieved using water/acetonitrile as a binary mobile phase system and no column re-equilibration time between injections was needed. Despite the fact that acetonitrile is not recommended as mobile phase solvent for APPI source due to its relatively low protonating efficiency, it was used successfully under our experimental conditions. The limitations for the use of acetonitrile are based on the low yield of acetonitrile ions responsible for the ionization of PAHs, which is not sufficient for achieving sufficient ionization of the analytes (21). In our case, the ionizing efficiency was greatly improved by adding a post-column doping agent to the mobile phase. Several studies were performed during the last decade that compared the benefits of either single dopants or mixtures of dopants (22–24). In our study, a screening aimed at the selection of several dopants and their combinations with the ionization potential of <10 eV was performed, and these were (1) toluene; (2) anisole; (3) chlorobenzene; (4) toluene/acetone (50:50, v/v); (5) toluene/anisole (99.5:0.5, v/v); (6) toluene/chlorobenzene (99:1, v/v); and (7) ethanol/chlorobenzene/bromobenzene/anisole (98.975:0.1:0.9:0.025, v/v). All selected dopants and dopant mixtures were evaluated in terms of obtained sensitivity, linear range, precision and reproducibility of the target compounds. Pure organic dopants such as toluene, anisole and chlorobenzene showed the highest signal intensities, whereas, only pure toluene and anisole showed high peak shape stability and reproducibility in the presence of a complex sample matrix. In order to introduce a dopant that is less toxic and more compatible with the LC phase solvents, the introduction of acetone and ethanol was also evaluated. The obtained results showed that these mixtures were not able to generate the target compound peaks comparable to those produced using chlorobenzene as a dopant, and thus resulted in lower ionization efficiency. The mixtures of toluene/anisole and toluene/chlorobenzene were also less efficient compared to pure organic solvents in terms of higher background noise, that was attributed to higher gas-phase ion molecular reactions. To sum up, under our experimental conditions, pure toluene and pure anisole showed better performance in terms of providing higher ion intensity for most of the selected PAHs. Similar results were obtained by Moriwaki et al. (25) when toluene gave the highest peak areas for 12 EPA-PAHs and by Itoh et al. (22) who reported that a mixture of toluene and anisole in the volume ratio of 99.5:0.5 provided the most suitable ionization for the analysis of 16 PAHs. Due to the fact that most of our analytical standards were prepared in pure toluene, and to avoid the introduction of different solvents, toluene was finally selected in preference over other dopants as the most effective and convenient agent. The maximum sensitivity for the analytes was obtained by post-column introduction of toluene to the mobile phase at the flow rate of 50 μL min−1. Optimization of the Orbitrap-MS method The use of APPI ionization mode in PAH analysis was previously described by several authors (22, 23, 26–28), however, limited selectivity, sensitivity, as well as strong interference might be occasionally encountered when using quadrupole MS instruments (29, 30). The performance of Q-Exactive mass spectrometer functioning as a part of innovative hybrid high-resolution mass spectrometers (HRMS) combined the high resolving power (RP) performance of the Orbitrap with the high selectivity of the quadrupole. Hereby, in order to overcome the aforementioned limitations, we propose the use of HPLC-Orbitrap-MS as a promising technology for the routine analysis of PAHs. In order to adjust the HRMS parameters and to optimize the method for determination of PAHs, systematic experiments were carried out for each of the Q-Exactive scan modes (FS, tSIM and tMS2). The effect of MS parameters, such as automatic gain control (AGC target), maximum injection time (IT), RP, normalized collision energy (NCE) and number of scans per chromatographic peak were examined. During the optimization of Q-Exactive scan modes, one of the essential criteria responsible for the sensitivity of method is finding the optimal values of two related parameters—AGC and IT. In the FS mode (m/z range of 100–500) with a complex matrix, the optimal AGC was configured to 1 × 106, while the IT was set to 200 ms. As a consequence, the detection of all species in the operating mass range was enhanced. The raw MS spectra for all four priority PAHs are shown in Supplementary Figure S1. The AGC value for the tSIM mode was established at the same level as was found optimal for the FS mode, whereas the IT value was decreased. As a result, we observed a slightly improved sensitivity and much higher intensities of the analyte signals in the spectra (Supplementary Figure S2). The optimal AGC and IT values used for this detection mode were 1 × 106 and 120 ms, respectively. In the case of the tMS2 mode, the target ions were filtered from the total ion flux and a large portion of interfering ions were removed by applying a selective isolation window of narrow mass range (m/z 1) by the quadrupole. Thus, the ions were selectively accumulated in high collision dissociation (HCD) cell and subsequently fragmented. In order to avoid disrupting the analyte ions in the Orbitrap and to prevent distortions, the AGC was set to 2 × 105, to limit the amount of ions in the Orbitrap. At the same time, IT was set to 100 ms, still providing a sufficient number of scans per second. As a result, the proportion of target ions among the total ion population was greater, favouring lower detection limits compared to the FS and tSIM modes. The raw MS spectra for each PAH in tMS2 mode are shown in Supplementary Figure S3. Another important parameter to consider in relation to the selectivity of HRMS analysis is the RP. Analysis at higher RP enables a better mass accuracy, thus a higher selectivity. Yet, high RP decreases the number of acquisitions during an analysis due to longer duty cycles (31). For quantitative measurements with acceptable RSDs, it is generally agreed that a minimum of about 20 data points per peak is required (32). The number of data points in relation to RP was studied in order to identify the best compromise between selectivity and quantitative parameters of the method. With these criteria, the selected RP for FS and tSIM was 35 000 Full Width Half Maximum (FWHM), and 17 500 FWHM for tMS2. Supplementary Figure S4 presents the optimal RP with the corresponding optimum acquisition points for tSIM and tMS2 modes. As described above, the efficiency of different scan modes was examined during the study. The FS and tSIM modes showed poorer performance in terms of selectivity compared to tMS2, and many interfering peaks were observed for chocolate matrix when operating at low detection levels, especially near the BaA and BbF peaks (Supplementary Figure S5). Comparing the different scan modes in terms of sensitivity and amount of data points per peaks against the tMS2 mode showed better performance (Supplementary Figure S2). Consequently, the tMS2 mode resulted in a more accurate determination of PAHs and should be preferred when using complex matrices. Based on these observations, only the tMS2 method was validated in the present study and used for the further analysis of chocolate samples. Validation of the method The validation of the method was performed using dark chocolate homogenate (pseudo-blank) previously analyzed for the PAHs content and found to contain quantifiable traces of selected substances. The mean concentrations of PAHs in the pseudo-blank sample were: BaA—0.205 μg kg−1 fat; Chr—0.306 μg kg−1 fat; BbF—0.162 μg kg−1 fat; BaP—0.071 μg kg−1 fat. In order to evaluate the analytical performance of the developed method, essential parameters such as sensitivity, selectivity, linearity, accuracy and precision were investigated. The overview of validation parameters such as linearity (r2), linearity range, instrumental and method LODs and LOQs for the elaborated method are given in Table III. Table III. Main Validation Parameters of the Elaborated PAH Determination Method PAH Linearity range, μg kg−1 fat Linearity, r2 i-LOD, pg on-column i-LOQ, pg on-column m-LOD, μg kg−1 fat m-LOQ, μg kg−1 fat BaA 0.1–5.0 0.995 1.2 3.7 0.024 0.081 Chr 0.1–5.0 0.993 0.8 2.4 0.016 0.054 BbF 0.1–5.0 0.989 1.0 3.1 0.021 0.069 BaP 0.1–5.0 0.997 1.0 2.9 0.019 0.064 PAH Linearity range, μg kg−1 fat Linearity, r2 i-LOD, pg on-column i-LOQ, pg on-column m-LOD, μg kg−1 fat m-LOQ, μg kg−1 fat BaA 0.1–5.0 0.995 1.2 3.7 0.024 0.081 Chr 0.1–5.0 0.993 0.8 2.4 0.016 0.054 BbF 0.1–5.0 0.989 1.0 3.1 0.021 0.069 BaP 0.1–5.0 0.997 1.0 2.9 0.019 0.064 Table III. Main Validation Parameters of the Elaborated PAH Determination Method PAH Linearity range, μg kg−1 fat Linearity, r2 i-LOD, pg on-column i-LOQ, pg on-column m-LOD, μg kg−1 fat m-LOQ, μg kg−1 fat BaA 0.1–5.0 0.995 1.2 3.7 0.024 0.081 Chr 0.1–5.0 0.993 0.8 2.4 0.016 0.054 BbF 0.1–5.0 0.989 1.0 3.1 0.021 0.069 BaP 0.1–5.0 0.997 1.0 2.9 0.019 0.064 PAH Linearity range, μg kg−1 fat Linearity, r2 i-LOD, pg on-column i-LOQ, pg on-column m-LOD, μg kg−1 fat m-LOQ, μg kg−1 fat BaA 0.1–5.0 0.995 1.2 3.7 0.024 0.081 Chr 0.1–5.0 0.993 0.8 2.4 0.016 0.054 BbF 0.1–5.0 0.989 1.0 3.1 0.021 0.069 BaP 0.1–5.0 0.997 1.0 2.9 0.019 0.064 As the analytical method had to be fit for the generation of reliable data at low concentration levels, an emphasis was given to the assessment of the lower limits at which analytes can be detected. Nine calibration levels, as described in “The validation of analytical method” section, covered the concentration range between 0.1 and 5.0 μg kg−1 expressed on fat basis. To avoid heteroscedasticity, the calibration range was split into two parts. The lower part, which was applicable for LOD calculation, covered the range from 0.10 to 0.30 μg kg−1 fat, whereas the second calibration curve was set up for the range between 0.2 and 5.0 μg kg−1 fat and was used for the analysis of chocolate samples. The linearity of instrument responses was evaluated for each section based on visual inspection of the residuals of the linear regression curves. The obtained correlation coefficients were >0.989 for all of the investigated compounds. The calculation of method LOD (m-LOD) was performed according to Equation 1 under the conditions of performing a single analysis on the test sample, 10 independent analyses of the pseudo-blank, and equal probabilities (α = ß = 0.05) for false positive and false negative detections (33). The pseudo-blank samples were processed by applying the whole analytical procedure. Homoscedasticity was assumed for the content range between m-LOD and the spiking level, and the probabilities of type I and type II errors (α and ß errors) were set to 0.05. The m-LOD and m-LOQ of each analyte were calculated based on the Guidance Document on the Estimation of LOD and LOQ for Measurements in the Field of Contaminants in Feed and Food (33), according to Eqs. (1) and (2), respectively. The factor 3.86 takes into account the number of experiments and the chosen error probabilities. Equation (1) was used for the estimation of m-LOD: xLOD=3.86⋅Sy,bb (1) xLOD ⁠: limit of detection for the method; Sy,b ⁠: standard deviation of the pseudo-blank signals; and b ⁠: slope of the calibration curve close to LOD. whereas, Equation (2) was applied for the estimation of m-LOQ: xLOQ=3.3⋅xLOD (2) xLOQ ⁠: limit of quantification for the method. Due to the fact that in the case of Orbitrap-MS the extraction of exact masses within 5 ppm of the theoretical m/z from the FS raw data for most of the target compounds provided for absence of background noise, the evaluation of the instrumental sensitivity via S/N ratio was not applicable and could result in overestimated results (34). Thus, the instrumental LOD (i-LOD) and instrumental LOQ (i-LOQ) values were assessed from the analyses of pure standard solutions with analyte concentrations from 0.1 to 0.5 pg μL−1 (0.5–2.5 pg injected on-column). For the reliable detection taking into account the dynamic range of the detector, only signals with the intensities above 1 × 104 were used. The assessed i-LOD values for the analyzed PAHs were in the range of 0.8–1.2 pg injected on-column, while the i-LOQs were in the range of 2.4–3.6 pg on-column, respectively. The obtained m-LODs and m-LOQs were far below the levels set in Commission Regulation (EU) No. 836/2011 (17) and 2015/1933 (12), with the levels ranging from 0.016 to 0.024 μg kg−1 fat and from 0.054 to 0.081 μg kg−1 fat (Table III), respectively. According to the Commission Regulation No. 836/2011 (17) amending the performance criteria for methods of analysis for PAHs, validated method recoveries for every single PAH4 compound should be in the range from 50 to 120%, and HORRATR values should be <2. The mean recoveries for the elaborated method were within the recommended range—from 86 to 102%. All the obtained HORRATR values were significantly lower than required (Table IV). Table IV. Recoveries and RSD of the Method for Determination of PAHs at Different Spiking Levels, as Well as HORRATR and Uncertainty Values for Both Inter-day and Intra-day Validations PAH Recovery, % Precision, RSD% HORRATR Uncertainty, % a b c Mean a b c Mean Inter-day validation  BaA 86 88 84 86 14 7 11 10 0.71 18  Chr 95 85 86 89 10 3 9 7 0.49 14  BbF 94 92 91 92 12 9 7 9 0.63 12  BaP 111 102 95 102 16 8 8 11 0.72 11 Intra-day validation  BaA 86 87 84 86 12 7 10 10 0.67 17  Chr 92 85 85 87 17 4 10 10 0.71 16  BbF 94 92 91 92 16 8 6 10 0.69 13  BaP 109 101 95 102 14 10 7 10 0.71 10 PAH Recovery, % Precision, RSD% HORRATR Uncertainty, % a b c Mean a b c Mean Inter-day validation  BaA 86 88 84 86 14 7 11 10 0.71 18  Chr 95 85 86 89 10 3 9 7 0.49 14  BbF 94 92 91 92 12 9 7 9 0.63 12  BaP 111 102 95 102 16 8 8 11 0.72 11 Intra-day validation  BaA 86 87 84 86 12 7 10 10 0.67 17  Chr 92 85 85 87 17 4 10 10 0.71 16  BbF 94 92 91 92 16 8 6 10 0.69 13  BaP 109 101 95 102 14 10 7 10 0.71 10 a = 0.1 μg kg−1 fat; b = 1 μg kg−1 fat; c = 5 μg kg−1 fat. Table IV. Recoveries and RSD of the Method for Determination of PAHs at Different Spiking Levels, as Well as HORRATR and Uncertainty Values for Both Inter-day and Intra-day Validations PAH Recovery, % Precision, RSD% HORRATR Uncertainty, % a b c Mean a b c Mean Inter-day validation  BaA 86 88 84 86 14 7 11 10 0.71 18  Chr 95 85 86 89 10 3 9 7 0.49 14  BbF 94 92 91 92 12 9 7 9 0.63 12  BaP 111 102 95 102 16 8 8 11 0.72 11 Intra-day validation  BaA 86 87 84 86 12 7 10 10 0.67 17  Chr 92 85 85 87 17 4 10 10 0.71 16  BbF 94 92 91 92 16 8 6 10 0.69 13  BaP 109 101 95 102 14 10 7 10 0.71 10 PAH Recovery, % Precision, RSD% HORRATR Uncertainty, % a b c Mean a b c Mean Inter-day validation  BaA 86 88 84 86 14 7 11 10 0.71 18  Chr 95 85 86 89 10 3 9 7 0.49 14  BbF 94 92 91 92 12 9 7 9 0.63 12  BaP 111 102 95 102 16 8 8 11 0.72 11 Intra-day validation  BaA 86 87 84 86 12 7 10 10 0.67 17  Chr 92 85 85 87 17 4 10 10 0.71 16  BbF 94 92 91 92 16 8 6 10 0.69 13  BaP 109 101 95 102 14 10 7 10 0.71 10 a = 0.1 μg kg−1 fat; b = 1 μg kg−1 fat; c = 5 μg kg−1 fat. The obtained mean RSD values for the inter-day validation ranged from 7 to 11%, while the mean RSD values for the intra-day validation were 10% for all the individual compounds. The recoveries, as well as the RSD values for all the three different spiking levels during the inter-day and intra-day validation experiments are presented in Table IV. The trueness of the method was estimated by analysis of an inter-laboratory comparison test material (EUPT-2015—four marker PAHs in cocoa products). In general, the determined concentrations for the analytes included in the inter-laboratory comparison test were in good agreement with the provided assigned values for both samples (Table V). Table V. Results Obtained for the ILC 2015—Four Marker PAHs in Cocoa Products XILC, μg kg−1 fat uILC, μg kg−1 fat Xm, μg kg−1 fat um, μg kg−1 fat |Y| Acceptance Milk chocolate  BaA 4.66 0.27 4.17 0.42 −1.0 Yes  Chr 5.79 0.34 5.28 0.53 −0.8 Yes  BbF 3.85 0.24 3.76 0.38 −0.2 Yes  BaP 3.91 0.20 3.52 0.35 −1.0 Yes  ∑PAH4 18.20 0.54 16.73 3.35 −0.4 Yes Cocoa powder  BaA 4.40 0.32 4.66 0.47 0.5 Yes  Chr 6.16 0.39 5.87 0.59 −0.4 Yes  BbF 2.32 0.21 2.70 0.27 1.1 Yes  BaP 2.19 0.17 2.06 0.21 −0.5 Yes  ∑PAH4 15.07 0.57 15.29 3.06 0.1 Yes XILC, μg kg−1 fat uILC, μg kg−1 fat Xm, μg kg−1 fat um, μg kg−1 fat |Y| Acceptance Milk chocolate  BaA 4.66 0.27 4.17 0.42 −1.0 Yes  Chr 5.79 0.34 5.28 0.53 −0.8 Yes  BbF 3.85 0.24 3.76 0.38 −0.2 Yes  BaP 3.91 0.20 3.52 0.35 −1.0 Yes  ∑PAH4 18.20 0.54 16.73 3.35 −0.4 Yes Cocoa powder  BaA 4.40 0.32 4.66 0.47 0.5 Yes  Chr 6.16 0.39 5.87 0.59 −0.4 Yes  BbF 2.32 0.21 2.70 0.27 1.1 Yes  BaP 2.19 0.17 2.06 0.21 −0.5 Yes  ∑PAH4 15.07 0.57 15.29 3.06 0.1 Yes Table V. Results Obtained for the ILC 2015—Four Marker PAHs in Cocoa Products XILC, μg kg−1 fat uILC, μg kg−1 fat Xm, μg kg−1 fat um, μg kg−1 fat |Y| Acceptance Milk chocolate  BaA 4.66 0.27 4.17 0.42 −1.0 Yes  Chr 5.79 0.34 5.28 0.53 −0.8 Yes  BbF 3.85 0.24 3.76 0.38 −0.2 Yes  BaP 3.91 0.20 3.52 0.35 −1.0 Yes  ∑PAH4 18.20 0.54 16.73 3.35 −0.4 Yes Cocoa powder  BaA 4.40 0.32 4.66 0.47 0.5 Yes  Chr 6.16 0.39 5.87 0.59 −0.4 Yes  BbF 2.32 0.21 2.70 0.27 1.1 Yes  BaP 2.19 0.17 2.06 0.21 −0.5 Yes  ∑PAH4 15.07 0.57 15.29 3.06 0.1 Yes XILC, μg kg−1 fat uILC, μg kg−1 fat Xm, μg kg−1 fat um, μg kg−1 fat |Y| Acceptance Milk chocolate  BaA 4.66 0.27 4.17 0.42 −1.0 Yes  Chr 5.79 0.34 5.28 0.53 −0.8 Yes  BbF 3.85 0.24 3.76 0.38 −0.2 Yes  BaP 3.91 0.20 3.52 0.35 −1.0 Yes  ∑PAH4 18.20 0.54 16.73 3.35 −0.4 Yes Cocoa powder  BaA 4.40 0.32 4.66 0.47 0.5 Yes  Chr 6.16 0.39 5.87 0.59 −0.4 Yes  BbF 2.32 0.21 2.70 0.27 1.1 Yes  BaP 2.19 0.17 2.06 0.21 −0.5 Yes  ∑PAH4 15.07 0.57 15.29 3.06 0.1 Yes Equation (3) was applied for evaluation of the obtained results (14). The measurement uncertainty was estimated as a first approximation from the determined intermediate precision. A statistically significant difference of the measurement result and certified value cannot be postulated at the 95% confidence level if Equation (3) is fulfilled. Statistical evaluation of the measurement results did not indicate any bias. The details are given in Table V. 2≥|Y|=Xm−XILCum2+uILC2 (3) Xm ⁠: the average measured value; XILC ⁠: the values assigned for inter-laboratory comparison; um ⁠: standard uncertainty of the measurement; and uILC ⁠: standard uncertainty of the assigned value. The overall quality assessment of validation data shows that our elaborated methodology provided acceptable performance for sensitive, selective and accurate analysis of selected PAHs in chocolate samples. Evaluation of the method applicability (analysis of chocolate samples) Most of the studies based on the application of APPI in the analysis of PAHs were carried out using pure PAH standards (21–24, 26, 27, 35, 36). Only a few published studies describe the determination of PAHs in complex food matrices—LC–DA-APPI–MS-MS method for the determination of 15 + 1 EU priority PAHs in edible oil (28); LC–DA-APPI–MS-MS method for the determination of 16 US EPA priority PAHs in shrimp samples (37), and LC–APPI–MS method for 16 US EPA priority PAHs analysis in oysters (30). The LODs of the reported methods were the following: 0.19–0.36 μg kg−1 for the oil, 0.02–0.51 μg kg−1 for the shrimp and 0.013–0.129 μg kg−1 for the oysters. The m-LODs observed in the present study were 0.016–0.024 μg kg−1 of the fat fraction, which was ~10 times lower than those obtained by Hollosi et al. (28), and comparable to the lowest LODs reported by Smoker et al. (37) and Cai et al. (30). With regard to the i-LOD values, the most sensitive among the aforementioned methods was reported by Smoker et al. (37), with the lowest established i-LOD at the level of 0.4 pg of BaP on-column. However, the determination of LODs for the reported method was based on S/N ratio that is often associated with overestimated results. The i-LOD values reported by other authors were 6.3 pg of BaP on-column for edible oil matrix and 8–106 pg of individual PAHs for oysters. In the case of our method, the i-LODs ranged from 0.8 to 1.2 pg on-column for all four investigated PAHs. The DA-APPI–HPLC-Orbitrap-MS method developed within the current study was applied for the analysis of dark chocolate samples. Dark chocolate is more often contaminated with PAHs because of the relatively high cocoa bean and cocoa butter content (8, 14). The fat content in our analyzed samples varied over the range of 30–66%. Twenty six randomly selected dark chocolate samples were tested for the four EU marker PAHs. The total PAH content was found to be in the range from 1.11 to 16.07 μg kg−1 fat, with the mean content of 4.24 μg kg−1 fat. In all of the samples, the 4-ring PAHs (BaA, Chr) were detected at relatively higher concentrations than the 5-ring PAHs (BbF, BaP). Chr was especially prominent in the analyzed samples, at the concentration range from 0.37 to 7.39 μg kg−1 fat. BaP, the most harmful of the indicator substances for the PAHs, had the mean concentration of 0.71 μg kg−1 fat, with 77% of the samples showing detectable concentrations of BaP. The determined concentrations of individual PAHs in the analyzed chocolate samples are shown in Table VI. The concentrations below the LOD were considered as not detected (ND) and the values were set to zero in order to describe the sample set by descriptive statistics methods. No samples exceeding the existing EU ML values were found. Table VI. The Content of PAHs in the Analyzed Dark Chocolate Samples, μg kg−1 Fat (n = 26) No. Country of production Fat content, % BaA, μg kg−1 fat Chr, μg kg−1 fat BbF, μg kg−1 fat BaP, μg kg−1 fat ΣPAH4, μg kg−1 fat 1 Latvia 45.8 0.41 ± 0.07 0.69 ± 0.11 1.14 ± 0.15 0.55 ± 0.06 2.8 ± 0.2 2 Spain 50.2 0.75 ± 0.13 0.76 ± 0.12 0.46 ± 0.06 0.60 ± 0.06 2.6 ± 0.2 3 France 44.7 0.18 ± 0.03 0.81 ± 0.13 0.16 ± 0.02 <0.02 1.1 ± 0.1 4 France 50.5 0.73 ± 0.12 1.08 ± 0.17 0.54 ± 0.07 <0.02 2.4 ± 0.2 5 Germany 48.7 3.61 ± 0.61 5.39 ± 0.86 4.80 ± 0.62 2.27 ± 0.23 16.1 ± 1.3 6 Switzerland 52.7 1.34 ± 0.23 2.30 ± 0.37 1.41 ± 0.18 1.04 ± 0.10 6.1 ± 0.5 7 Lithuania 43.3 0.36 ± 0.06 0.72 ± 0.12 0.99 ± 0.13 0.57 ± 0.06 2.6 ± 0.2 8 Estonia 56.7 0.72 ± 0.12 0.74 ± 0.12 0.32 ± 0.04 <0.02 1.8 ± 0.2 9 Germany 34.2 0.41 ± 0.07 0.79 ± 0.13 0.73 ± 0.09 <0.02 1.9 ± 0.2 10 Latvia 47.3 1.39 ± 0.24 3.13 ± 0.50 3.86 ± 0.50 2.90 ± 0.29 11.3 ± 0.8 11 Germany 42.9 0.29 ± 0.05 0.46 ± 0.07 0.76 ± 0.10 0.52 ± 0.05 2.0 ± 0.1 12 Belgium 58.9 3.49 ± 0.59 7.39 ± 1.18 3.21 ± 0.42 0.87 ± 0.09 15.0 ± 1.4 13 Germany 45.1 1.48 ± 0.25 1.72 ± 0.28 2.75 ± 0.36 0.69 ± 0.07 6.6 ± 0.5 14 Germany 55.6 0.38 ± 0.07 0.71 ± 0.11 0.36 ± 0.05 0.21 ± 0.02 1.7 ± 0.1 15 Germany 66.9 0.41 ± 0.07 0.83 ± 0.13 0.30 ± 0.04 0.56 ± 0.06 2.1 ± 0.2 16 Germany 61.5 0.47 ± 0.08 0.91 ± 0.15 0.48 ± 0.06 0.75 ± 0.07 2.6 ± 0.2 17 Denmark 48.0 0.24 ± 0.04 0.97 ± 0.16 0.14 ± 0.02 <0.02 1.4 ± 0.2 18 France 35.3 0.23 ± 0.04 0.61 ± 0.10 0.96 ± 0.12 0.55 ± 0.06 2.4 ± 0.2 19 Germany 57.8 0.49 ± 0.08 0.37 ± 0.06 0.18 ± 0.02 0.08 ± 0.01 1.1 ± 0.1 20 Switzerland 44.7 2.65 ± 0.45 0.94 ± 0.15 3.02 ± 0.39 0.89 ± 0.09 7.5 ± 0.6 21 Germany 55.3 0.49 ± 0.08 1.03 ± 0.17 0.53 ± 0.07 0.76 ± 0.08 2.8 ± 0.2 22 Switzerland 40.7 0.84 ± 0.14 0.94 ± 0.15 0.97 ± 0.13 0.88 ± 0.09 3.6 ± 0.3 23 Finland 58.2 0.58 ± 0.10 1.01 ± 0.16 0.76 ± 0.10 1.95 ± 0.20 4.3 ± 0.3 24 Russia 30.9 0.34 ± 0.06 0.60 ± 0.10 0.34 ± 0.04 <0.02 1.3 ± 0.1 25 Russia 34.5 0.46 ± 0.08 0.78 ± 0.12 0.45 ± 0.06 0.65 ± 0.06 2.3 ± 0.2 26 Russia 30.2 1.02 ± 0.17 1.88 ± 0.30 0.84 ± 0.11 1.12 ± 0.11 4.9 ± 0.4 No. Country of production Fat content, % BaA, μg kg−1 fat Chr, μg kg−1 fat BbF, μg kg−1 fat BaP, μg kg−1 fat ΣPAH4, μg kg−1 fat 1 Latvia 45.8 0.41 ± 0.07 0.69 ± 0.11 1.14 ± 0.15 0.55 ± 0.06 2.8 ± 0.2 2 Spain 50.2 0.75 ± 0.13 0.76 ± 0.12 0.46 ± 0.06 0.60 ± 0.06 2.6 ± 0.2 3 France 44.7 0.18 ± 0.03 0.81 ± 0.13 0.16 ± 0.02 <0.02 1.1 ± 0.1 4 France 50.5 0.73 ± 0.12 1.08 ± 0.17 0.54 ± 0.07 <0.02 2.4 ± 0.2 5 Germany 48.7 3.61 ± 0.61 5.39 ± 0.86 4.80 ± 0.62 2.27 ± 0.23 16.1 ± 1.3 6 Switzerland 52.7 1.34 ± 0.23 2.30 ± 0.37 1.41 ± 0.18 1.04 ± 0.10 6.1 ± 0.5 7 Lithuania 43.3 0.36 ± 0.06 0.72 ± 0.12 0.99 ± 0.13 0.57 ± 0.06 2.6 ± 0.2 8 Estonia 56.7 0.72 ± 0.12 0.74 ± 0.12 0.32 ± 0.04 <0.02 1.8 ± 0.2 9 Germany 34.2 0.41 ± 0.07 0.79 ± 0.13 0.73 ± 0.09 <0.02 1.9 ± 0.2 10 Latvia 47.3 1.39 ± 0.24 3.13 ± 0.50 3.86 ± 0.50 2.90 ± 0.29 11.3 ± 0.8 11 Germany 42.9 0.29 ± 0.05 0.46 ± 0.07 0.76 ± 0.10 0.52 ± 0.05 2.0 ± 0.1 12 Belgium 58.9 3.49 ± 0.59 7.39 ± 1.18 3.21 ± 0.42 0.87 ± 0.09 15.0 ± 1.4 13 Germany 45.1 1.48 ± 0.25 1.72 ± 0.28 2.75 ± 0.36 0.69 ± 0.07 6.6 ± 0.5 14 Germany 55.6 0.38 ± 0.07 0.71 ± 0.11 0.36 ± 0.05 0.21 ± 0.02 1.7 ± 0.1 15 Germany 66.9 0.41 ± 0.07 0.83 ± 0.13 0.30 ± 0.04 0.56 ± 0.06 2.1 ± 0.2 16 Germany 61.5 0.47 ± 0.08 0.91 ± 0.15 0.48 ± 0.06 0.75 ± 0.07 2.6 ± 0.2 17 Denmark 48.0 0.24 ± 0.04 0.97 ± 0.16 0.14 ± 0.02 <0.02 1.4 ± 0.2 18 France 35.3 0.23 ± 0.04 0.61 ± 0.10 0.96 ± 0.12 0.55 ± 0.06 2.4 ± 0.2 19 Germany 57.8 0.49 ± 0.08 0.37 ± 0.06 0.18 ± 0.02 0.08 ± 0.01 1.1 ± 0.1 20 Switzerland 44.7 2.65 ± 0.45 0.94 ± 0.15 3.02 ± 0.39 0.89 ± 0.09 7.5 ± 0.6 21 Germany 55.3 0.49 ± 0.08 1.03 ± 0.17 0.53 ± 0.07 0.76 ± 0.08 2.8 ± 0.2 22 Switzerland 40.7 0.84 ± 0.14 0.94 ± 0.15 0.97 ± 0.13 0.88 ± 0.09 3.6 ± 0.3 23 Finland 58.2 0.58 ± 0.10 1.01 ± 0.16 0.76 ± 0.10 1.95 ± 0.20 4.3 ± 0.3 24 Russia 30.9 0.34 ± 0.06 0.60 ± 0.10 0.34 ± 0.04 <0.02 1.3 ± 0.1 25 Russia 34.5 0.46 ± 0.08 0.78 ± 0.12 0.45 ± 0.06 0.65 ± 0.06 2.3 ± 0.2 26 Russia 30.2 1.02 ± 0.17 1.88 ± 0.30 0.84 ± 0.11 1.12 ± 0.11 4.9 ± 0.4 Table VI. The Content of PAHs in the Analyzed Dark Chocolate Samples, μg kg−1 Fat (n = 26) No. Country of production Fat content, % BaA, μg kg−1 fat Chr, μg kg−1 fat BbF, μg kg−1 fat BaP, μg kg−1 fat ΣPAH4, μg kg−1 fat 1 Latvia 45.8 0.41 ± 0.07 0.69 ± 0.11 1.14 ± 0.15 0.55 ± 0.06 2.8 ± 0.2 2 Spain 50.2 0.75 ± 0.13 0.76 ± 0.12 0.46 ± 0.06 0.60 ± 0.06 2.6 ± 0.2 3 France 44.7 0.18 ± 0.03 0.81 ± 0.13 0.16 ± 0.02 <0.02 1.1 ± 0.1 4 France 50.5 0.73 ± 0.12 1.08 ± 0.17 0.54 ± 0.07 <0.02 2.4 ± 0.2 5 Germany 48.7 3.61 ± 0.61 5.39 ± 0.86 4.80 ± 0.62 2.27 ± 0.23 16.1 ± 1.3 6 Switzerland 52.7 1.34 ± 0.23 2.30 ± 0.37 1.41 ± 0.18 1.04 ± 0.10 6.1 ± 0.5 7 Lithuania 43.3 0.36 ± 0.06 0.72 ± 0.12 0.99 ± 0.13 0.57 ± 0.06 2.6 ± 0.2 8 Estonia 56.7 0.72 ± 0.12 0.74 ± 0.12 0.32 ± 0.04 <0.02 1.8 ± 0.2 9 Germany 34.2 0.41 ± 0.07 0.79 ± 0.13 0.73 ± 0.09 <0.02 1.9 ± 0.2 10 Latvia 47.3 1.39 ± 0.24 3.13 ± 0.50 3.86 ± 0.50 2.90 ± 0.29 11.3 ± 0.8 11 Germany 42.9 0.29 ± 0.05 0.46 ± 0.07 0.76 ± 0.10 0.52 ± 0.05 2.0 ± 0.1 12 Belgium 58.9 3.49 ± 0.59 7.39 ± 1.18 3.21 ± 0.42 0.87 ± 0.09 15.0 ± 1.4 13 Germany 45.1 1.48 ± 0.25 1.72 ± 0.28 2.75 ± 0.36 0.69 ± 0.07 6.6 ± 0.5 14 Germany 55.6 0.38 ± 0.07 0.71 ± 0.11 0.36 ± 0.05 0.21 ± 0.02 1.7 ± 0.1 15 Germany 66.9 0.41 ± 0.07 0.83 ± 0.13 0.30 ± 0.04 0.56 ± 0.06 2.1 ± 0.2 16 Germany 61.5 0.47 ± 0.08 0.91 ± 0.15 0.48 ± 0.06 0.75 ± 0.07 2.6 ± 0.2 17 Denmark 48.0 0.24 ± 0.04 0.97 ± 0.16 0.14 ± 0.02 <0.02 1.4 ± 0.2 18 France 35.3 0.23 ± 0.04 0.61 ± 0.10 0.96 ± 0.12 0.55 ± 0.06 2.4 ± 0.2 19 Germany 57.8 0.49 ± 0.08 0.37 ± 0.06 0.18 ± 0.02 0.08 ± 0.01 1.1 ± 0.1 20 Switzerland 44.7 2.65 ± 0.45 0.94 ± 0.15 3.02 ± 0.39 0.89 ± 0.09 7.5 ± 0.6 21 Germany 55.3 0.49 ± 0.08 1.03 ± 0.17 0.53 ± 0.07 0.76 ± 0.08 2.8 ± 0.2 22 Switzerland 40.7 0.84 ± 0.14 0.94 ± 0.15 0.97 ± 0.13 0.88 ± 0.09 3.6 ± 0.3 23 Finland 58.2 0.58 ± 0.10 1.01 ± 0.16 0.76 ± 0.10 1.95 ± 0.20 4.3 ± 0.3 24 Russia 30.9 0.34 ± 0.06 0.60 ± 0.10 0.34 ± 0.04 <0.02 1.3 ± 0.1 25 Russia 34.5 0.46 ± 0.08 0.78 ± 0.12 0.45 ± 0.06 0.65 ± 0.06 2.3 ± 0.2 26 Russia 30.2 1.02 ± 0.17 1.88 ± 0.30 0.84 ± 0.11 1.12 ± 0.11 4.9 ± 0.4 No. Country of production Fat content, % BaA, μg kg−1 fat Chr, μg kg−1 fat BbF, μg kg−1 fat BaP, μg kg−1 fat ΣPAH4, μg kg−1 fat 1 Latvia 45.8 0.41 ± 0.07 0.69 ± 0.11 1.14 ± 0.15 0.55 ± 0.06 2.8 ± 0.2 2 Spain 50.2 0.75 ± 0.13 0.76 ± 0.12 0.46 ± 0.06 0.60 ± 0.06 2.6 ± 0.2 3 France 44.7 0.18 ± 0.03 0.81 ± 0.13 0.16 ± 0.02 <0.02 1.1 ± 0.1 4 France 50.5 0.73 ± 0.12 1.08 ± 0.17 0.54 ± 0.07 <0.02 2.4 ± 0.2 5 Germany 48.7 3.61 ± 0.61 5.39 ± 0.86 4.80 ± 0.62 2.27 ± 0.23 16.1 ± 1.3 6 Switzerland 52.7 1.34 ± 0.23 2.30 ± 0.37 1.41 ± 0.18 1.04 ± 0.10 6.1 ± 0.5 7 Lithuania 43.3 0.36 ± 0.06 0.72 ± 0.12 0.99 ± 0.13 0.57 ± 0.06 2.6 ± 0.2 8 Estonia 56.7 0.72 ± 0.12 0.74 ± 0.12 0.32 ± 0.04 <0.02 1.8 ± 0.2 9 Germany 34.2 0.41 ± 0.07 0.79 ± 0.13 0.73 ± 0.09 <0.02 1.9 ± 0.2 10 Latvia 47.3 1.39 ± 0.24 3.13 ± 0.50 3.86 ± 0.50 2.90 ± 0.29 11.3 ± 0.8 11 Germany 42.9 0.29 ± 0.05 0.46 ± 0.07 0.76 ± 0.10 0.52 ± 0.05 2.0 ± 0.1 12 Belgium 58.9 3.49 ± 0.59 7.39 ± 1.18 3.21 ± 0.42 0.87 ± 0.09 15.0 ± 1.4 13 Germany 45.1 1.48 ± 0.25 1.72 ± 0.28 2.75 ± 0.36 0.69 ± 0.07 6.6 ± 0.5 14 Germany 55.6 0.38 ± 0.07 0.71 ± 0.11 0.36 ± 0.05 0.21 ± 0.02 1.7 ± 0.1 15 Germany 66.9 0.41 ± 0.07 0.83 ± 0.13 0.30 ± 0.04 0.56 ± 0.06 2.1 ± 0.2 16 Germany 61.5 0.47 ± 0.08 0.91 ± 0.15 0.48 ± 0.06 0.75 ± 0.07 2.6 ± 0.2 17 Denmark 48.0 0.24 ± 0.04 0.97 ± 0.16 0.14 ± 0.02 <0.02 1.4 ± 0.2 18 France 35.3 0.23 ± 0.04 0.61 ± 0.10 0.96 ± 0.12 0.55 ± 0.06 2.4 ± 0.2 19 Germany 57.8 0.49 ± 0.08 0.37 ± 0.06 0.18 ± 0.02 0.08 ± 0.01 1.1 ± 0.1 20 Switzerland 44.7 2.65 ± 0.45 0.94 ± 0.15 3.02 ± 0.39 0.89 ± 0.09 7.5 ± 0.6 21 Germany 55.3 0.49 ± 0.08 1.03 ± 0.17 0.53 ± 0.07 0.76 ± 0.08 2.8 ± 0.2 22 Switzerland 40.7 0.84 ± 0.14 0.94 ± 0.15 0.97 ± 0.13 0.88 ± 0.09 3.6 ± 0.3 23 Finland 58.2 0.58 ± 0.10 1.01 ± 0.16 0.76 ± 0.10 1.95 ± 0.20 4.3 ± 0.3 24 Russia 30.9 0.34 ± 0.06 0.60 ± 0.10 0.34 ± 0.04 <0.02 1.3 ± 0.1 25 Russia 34.5 0.46 ± 0.08 0.78 ± 0.12 0.45 ± 0.06 0.65 ± 0.06 2.3 ± 0.2 26 Russia 30.2 1.02 ± 0.17 1.88 ± 0.30 0.84 ± 0.11 1.12 ± 0.11 4.9 ± 0.4 The results obtained in the present study correlate well with the previously published survey results about the presence of PAHs in chocolate on the German market (38, 39), where the highest PAH content was found for Chr+triphenylene (0.83–2.09 μg kg−1), while the content of BaP ranged between 0.07 and 0.63 μg kg−1 (median: 0.22 μg kg−1). Recalculating our results on a product mass basis as it was expressed in a study by Ziegenhals et al. (38), the content of BaP ranged from ND (<0.02 μg kg−1) to 0.98 μg kg−1 with the median value of 0.24 μg kg−1, and the content of Chr was in the range of 0.06–2.07 μg kg−1. Meanwhile in a study of Raters and Matissek (39), mean BaP and PAH4 content of 0.57 μg kg−1 fat and 5.88 μg kg−1 fat in dark chocolate samples was specified39. As well no chocolate samples exceeding EU maximum levels were observed—maximum BaP content was specified at the level of 1.56 μg kg−1 fat, and PAH4 at the level of 17.42 μg kg−1 fat. Another study concerning the content of PAHs in chocolate candies (40) indicated the median BaP content of 0.66 μg kg−1, which was almost three times higher than our observed value of 0.24 μg kg−1, whereas the mean BaP content of 1.49 μg kg−1 observed by Indian researchers was more than five times higher than our observed value of 0.27 μg kg−1. This observation could be explained by the fact that some additional chocolate processing steps are included in the manufacturing of chocolate candies, which could act as additional sources for the formation and introduction of PAHs. Commission Regulation (EU) No. 2015/1933 (12) specifies a maximum level of 5.0 μg kg−1 fat for BaP in cocoa beans and derived products (excluding cocoa beans and derived products intended for use as an ingredient in food). All of the analyzed samples conformed to the aforementioned maximum limit. BaP levels over the detection limit were found in 77% of the samples tested. The 95th percentile concentration was 0.29 μg kg−1 fat. An overview of the obtained results from this study is presented in Table VII. Table VII. The Concentration of PAHs in Chocolate and the Percentage of Samples Exceeding the LOD, 1, 2, 5 or 30 μg kg−1 Fat PAH Number of samples (%) above limits (μg kg−1 fat) Concentration in μg kg−1 fat >LOD >1 >2 >5 >30 Median Mean P95 Max BaA 100 27 12 0 0 0.49 0.91 0.38 3.61 Chr 100 35 15 8 0 0.87 1.44 0.65 7.39 BbF 100 27 19 0 0 0.74 1.17 0.51 4.80 BaP 77 19 8 0 0 0.59 0.71 0.29 2.90 ΣPAH4 100 100 73 23 0 2.59 4.24 1.64 16.07 PAH Number of samples (%) above limits (μg kg−1 fat) Concentration in μg kg−1 fat >LOD >1 >2 >5 >30 Median Mean P95 Max BaA 100 27 12 0 0 0.49 0.91 0.38 3.61 Chr 100 35 15 8 0 0.87 1.44 0.65 7.39 BbF 100 27 19 0 0 0.74 1.17 0.51 4.80 BaP 77 19 8 0 0 0.59 0.71 0.29 2.90 ΣPAH4 100 100 73 23 0 2.59 4.24 1.64 16.07 Table VII. The Concentration of PAHs in Chocolate and the Percentage of Samples Exceeding the LOD, 1, 2, 5 or 30 μg kg−1 Fat PAH Number of samples (%) above limits (μg kg−1 fat) Concentration in μg kg−1 fat >LOD >1 >2 >5 >30 Median Mean P95 Max BaA 100 27 12 0 0 0.49 0.91 0.38 3.61 Chr 100 35 15 8 0 0.87 1.44 0.65 7.39 BbF 100 27 19 0 0 0.74 1.17 0.51 4.80 BaP 77 19 8 0 0 0.59 0.71 0.29 2.90 ΣPAH4 100 100 73 23 0 2.59 4.24 1.64 16.07 PAH Number of samples (%) above limits (μg kg−1 fat) Concentration in μg kg−1 fat >LOD >1 >2 >5 >30 Median Mean P95 Max BaA 100 27 12 0 0 0.49 0.91 0.38 3.61 Chr 100 35 15 8 0 0.87 1.44 0.65 7.39 BbF 100 27 19 0 0 0.74 1.17 0.51 4.80 BaP 77 19 8 0 0 0.59 0.71 0.29 2.90 ΣPAH4 100 100 73 23 0 2.59 4.24 1.64 16.07 The limits of 1 and 2 μg kg−1 fat for the individual PAHs concentrations were also applied for better characterization of chocolate samples. Thus, 19% of the samples had BaP levels exceeding 1 μg kg−1 fat, and only 8% exceeded 2 μg kg−1 fat. As for ∑PAH4, the specified maximum level of 30.0 μg kg−1 fat was set in Commission Regulation (EU) No. 2015/1933 (12), and no sample exceeding this level was found. The 95th percentile concentration for the ∑PAH4 was established at the level of 1.64 μg kg−1 fat. Judging from the results obtained in our study, chocolate seems to be consistently contaminated with a range of PAHs. In most of the cases this contamination is characterized by relatively low levels of PAHs, indicating that highly sensitive instrumentation with high trueness and efficiency level without any false positive/negative findings is preferable for reliable, precise and accurate quantification. Conclusions A DA-APPI–HPLC-Orbitrap-MS method for the determination of four EU marker PAHs in dark chocolate was developed and optimized. Toluene as a dopant showed better ionization efficiency of non-polar PAHs. Three scan modes (FS, tSIM and tMS2) were explored to determine the best detection method for selective, sensitive and quantitative analysis. The obtained results indicate that for the quantification of the tested PAHs in a matrix as complex as chocolate, the tMS2 mode should be preferred. This set-up allows for tandem MS, which is more selective with the use of high-performance quadrupole selection, which filters a part of the interfering ions. In addition, product ions were also measured with accurate masses and high-resolution Orbitrap detection to avoid false positives. The elaborated HPLC-Orbitrap-MS method operated in tMS2 mode was successfully validated. The validation results underline good reliability and practicability of the described method, enabling its routine use even for difficult samples at low contamination levels. 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TI - Application of Dopant-Assisted Atmospheric Pressure Photoionisation HPLC–MS Method for the Sensitive Determination of Polycyclic Aromatic Hydrocarbons in Dark Chocolate
JF - Journal of Chromatographic Science
DO - 10.1093/chromsci/bmy103
DA - 2019-03-01
UR - https://www.deepdyve.com/lp/oxford-university-press/application-of-dopant-assisted-atmospheric-pressure-photoionisation-08OG3vGmTn
SP - 220
VL - 57
IS - 3
DP - DeepDyve
ER -