Integration of microalgal cultivation with industrial flue gas will ultimately introduce heavy metals and other inorganic compounds into the growth media. This study presents a procedure used to determine the end fate and impact of heavy metals and inorganic contaminants on the growth of Nannochloropsis salina grown in photobioreactors.
Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages include high potential yield, use of non-arable land and integration with waste streams. The nutrient requirements of a large-scale microalgae production system will require the coupling of cultivation systems with industrial waste resources, such as carbon dioxide from flue gas and nutrients from wastewater. Inorganic contaminants present in these wastes can potentially lead to bioaccumulation in microalgal biomass negatively impact productivity and limiting end use. This study focuses on the experimental evaluation of the impact and the fate of 14 inorganic contaminants (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn) on Nannochloropsis salina growth. Microalgae were cultivated in photobioreactors illuminated at 984 µmol m-2 sec-1 and maintained at pH 7 in a growth media polluted with inorganic contaminants at levels expected based on the composition found in commercial coal flue gas systems. Contaminants present in the biomass and the medium at the end of a 7 day growth period were analytically quantified through cold vapor atomic absorption spectrometry for Hg and through inductively coupled plasma mass spectrometry for As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, Se, Sn, V and Zn. Results show N. salina is a sensitive strain to the multi-metal environment with a statistical decrease in biomass yieldwith the introduction of these contaminants. The techniques presented here are adequate for quantifying algal growth and determining the fate of inorganic contaminants.
Compared to traditional terrestrial crops microalgae have been shown to achieve higher biomass and lipid yields due to inherent higher solar conversion efficiencies1,2. Cultivation of microalgae at high productivity rates requires the supply of various nutrients including an external carbon source. It is expected that large-scale growth facilities will be integrated with industrial waste streams such as industrial flue gas in order to minimize production costs and at the same time provide environmental remediation. Industrial waste carbon is typically in the form of gaseous carbon dioxide and can contain contaminants that have the potential to negatively impact microalgae production. Specifically, flue gas derived from coal will have a variety of contaminants including but not limited to combustion products water and carbon dioxide, as well as oxides of sulphur and nitrogen, fine dust, organic contaminants such as dioxins and furans, and inorganic contaminants such as heavy metals. The impact of the majority of these contaminants including inorganics with some of them known as heavy metals on microalgae productivity have not been explored. Some of these elements can be nutrients at appropriate concentrations, however at higher concentrations they can produce cell dysfunction and even death3.
The integration of microalgae with industrial flue gas has the potential to directly introduce inorganic contaminants into growth media. Coal based flue gas has a variety of inorganic elements (e.g., As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn) at various concentrations some of which, in low concentration, represent nutrients for microalgae growth. Inorganic contaminants have a high affinity to bind to microalgae and further be sorbed internally through nutrient transporters. Some inorganic contaminants (i.e., Co, Cu, Zn and Mn) are nutrients that form part of enzymes involved in photosynthesis, respiration and other functions3,4. However, in excess metals and metalloids can be toxic. Other elements, such as Pb, Cd, Sn, Sb, Se, As and Hg, are not known to support cell function in any concentration and represent non-nutrient metals which could negatively impact culture growth3,5,6. The presence of any of these contaminants has the potential to produce negative effects on microalgae cell function. Furthermore, the interaction of multiple metals with microalgae complicates growth dynamics and has the potential to impact growth.
Large-scale economics have been directly linked to the productivity of the cultivation system7-19. Moreover, medium recycle in the microalgae growth system for either open raceway ponds (ORP) or photobioreactors (PBR) is critical as it represents 99.9 and 99.4% of the mass, respectively20. The presence of inorganic contaminants in the media could ultimately limit microalgae productivity and the recycling of media due to contaminant build up. This study experimentally determined the impact of 14 inorganic contaminants (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn), at concentrations expected from the integration of microalgae cultivation systems with coal derived flue gas, on the productivity of N. salina grown in airlift PBRs. The contaminants used in this study have been shown to not only be present in coal-based flue gas but municipal waste-based flue gas, biosolids-based flue gas, municipal wastewater, produced water, impaired groundwater and seawater21-23. The concentrations used in this study are based on what would be expected if microalgae growth systems were integrated with a coal based CO2 source with an uptake efficiency demonstrated in commercial PBR systems20. Detailed calculations supporting the concentrations of the heavy metals and inorganic contaminants are presented in Napan et al.24 Analytical techniques were used to understand the distribution of the majority of the metals in the biomass, media and environment. The methods presented enabled the assessment of productivity potential of microalgae under inorganic contaminant stress and quantification of their end fate.
1. Growth system
Figure 1. Microalgae growth system. (A) air rotometer, (B) CO2 rotometer, (C) pH controller with solenoid, (D) data logger, (E) in-line air filters, (F) air distribution header, (G) fluorescent light bank, (H) pH meters, (I) cooling system, (J) water bath, (K) thermocouple wire, (L) air lift photobioreactor, (M) heater, (N) walk-in fume hood, (O) vent, (P) air delivery capillary tube, (Q) air filters, (R) sampling tube, (S) PBR silicone lid, and (T) pH well in silicone lid. Please click here to view a larger version of this figure.
2. Lab Ware Preparation
3. N. salina Medium Preparation
Component | Amount to add (g) | Final concentration (g/L) |
H3BO3 | 0.900 | 0.900 |
Na2MoO4·2H2O | 0.012 | 0.012 |
MnCl2·4H2O | 0.300 | 0.300 |
ZnSO4·7H2O | 0.060 | 0.060 |
CuSO4·5H2O | 0.020 | 0.020 |
Table 1: Solution A recipe. Quantities are amounts needed in the preparation of 1 L of concentrated solution.
Vitamins | Amount (mg) | Final volume (mL) | Final vitamin concentration (mg/L) |
Biotin | 12.22 | 500 | 24.43 |
Vitamin B12 | 13.50 | 100 | 135.00 |
Thiamine hydrochloride | 977.63 | 500 | 1,955.27 |
Table 2: Vitamin solution recipe. Quantities are amounts needed for the preparation of concentrated solution.
Component | Amount to add to medium | Unit |
NaCl | 350.00 | g |
CaCl2·2H2O | 3.00 | g |
KCl | 9.60 | g |
Na2SiO3·9H2O | 1.14 | g |
MgSO4·7H2O | 29.60 | g |
KNO3 | 20.40 | g |
KH2PO4 | 1.36 | g |
Ammonium ferric citrate | 0.10 | g |
Solution A | 20.00 | ml |
Biotin solution* | 818.00 | µl |
Vitamin B12 solution* | 296.20 | µl |
Thiamine hydrochloride solution* | 521.60 | µl |
* Add to cooled autoclaved media |
Table 3: N. salina medium recipe. Quantities are amounts needed in the preparation of 20 L of nutrient-rich medium.
4. Inorganic contaminants stock preparation
Analyte | Salt source | Volume of stock to prepare (L) | Salt to add to the flask (mg salt) | Analyte concentration added to the culture (mg analyte/L) |
As | NaAsO2 | 0.1 | 14.8 | 7.74E-02 |
Cd | CdCl2 | 0.5 | 13.5 | 1.50E-02 |
Co | CoCl2.6H2O | 0.5 | 34.7 | 1.56E-02 |
Cr | Na2Cr2O7·2H2O | 0.1 | 40.6 | 1.29E-01 |
Cu | CuCl2.2H2O | 0.1 | 38.3 | 1.30E-01 |
Hg | HgCl2 | 1.0 | 14.6 | 9.80E-03 |
Mn | MnCl2.4H2O | 0.1 | 58.8 | 1.49E-01 |
Ni | NiCl2.6H2O | 0.1 | 112.0 | 2.51E-01 |
Pb | PbCl2 | 0.5 | 39.9 | 5.41E-02 |
Sb | Sb2O3 | 0.5 | 26.7 | 4.06E-02 |
Se | Na2SeO3 | 0.5 | 11.8 | 9.80E-03 |
Sn | SnCl2.2H2O | 0.5 | 3.9 | 3.76E-03 |
V | V2O5 | 0.1 | 22.2 | 1.13E-01 |
Zn | ZnCl2 | 0.1 | 99.9 | 4.36E-01 |
Table 4: Concentrated inorganic contaminants stock preparation. Addition of 1 ml of this concentrated stock to the 1.1 L PBR medium produces the final concentration shown in the last column.
5. N. salina Inoculum Production
6. Experimental Reactors
7. Microwave Assisted Digestion of Samples
The digestion of the biomass samples is required as a pre-processing step for ICP-MS analysis.
Note: These steps use a closed vessel microwave digestion system with controlled pressure relief. (CAUTION: High pressures develop during acid digestion, inspect the physical integrity of the digestion vessels and shields, and reshape the microwave digestion vessel lids before every use).
Step | Vials rinsing | Sample digestion | ||||
Temperature (°C) | Time (min) | Max. power (W) | Temperature (°C) | Time (min) | Max. power (W) | |
1 | RT to 190 | 25 | 1,000 | RT to 180 | 15 | 1,000 |
2 | 190 | 10 | 1,000 | 180 | 15 | 1,000 |
Exhaust | – | 20 | – | – | 20 | – |
Table 5: Parameters used in the microwave digestion program.
8. Quality Control (QC) Samples
Note: Analyze QC samples in order to assure reliability of the results from experimental samples.
9. Quantification by Inductively Coupled Plasma Mass Spectrometry (ICPMS)
Parameter | Level 1 | Level 2 | Level 3 | Level 4 | Level 5 | Level 6 | Level 7 |
Purchased standard to be added (ml) | – | – | – | – | – | – | 10.0 |
Level 7 to be added (ml) | 0.0 | 1.0 | 2.5 | 5.0 | 20.0 | 25.0 | – |
Final volume* (ml) | – | 50.0 | 50.0 | 50.0 | 100.0 | 50.0 | 100.0 |
Final concentration (µg/L) | |||||||
75As | 0.0 | 2.0 | 5.0 | 10.0 | 20.0 | 50.0 | 100.0 |
111Cd | 0.0 | 1.0 | 2.5 | 5.0 | 10.0 | 25.0 | 50.0 |
59Co | 0.0 | 10.0 | 25.0 | 50.0 | 100.0 | 250.0 | 500.0 |
52Cr | 0.0 | 2.0 | 5.0 | 10.0 | 20.0 | 50.0 | 100.0 |
63Cu | 0.0 | 5.0 | 12.5 | 25.0 | 50.0 | 125.0 | 250.0 |
55Mn | 0.0 | 3.0 | 7.5 | 15.0 | 30.0 | 75.0 | 150.0 |
60Ni | 0.0 | 8.0 | 20.0 | 40.0 | 80.0 | 200.0 | 400.0 |
208Pb | 0.0 | 1.0 | 2.5 | 5.0 | 10.0 | 25.0 | 50.0 |
121Sb | 0.0 | 12.0 | 30.0 | 60.0 | 120.0 | 300.0 | 600.0 |
51V | 0.0 | 10.0 | 25.0 | 50.0 | 100.0 | 250.0 | 500.0 |
66Zn | 0.0 | 4.0 | 10.0 | 20.0 | 40.0 | 100.0 | 200.0 |
* Achieve this volume by adding the solution prepared in step 8.1 |
Table 6: Concentration of calibration standards. Levels 1 to 7.
Parameters | Values |
Internal standards | 72Ge, 115In |
Rf power | 1,500 W |
Plasma gas flow rate | 14.98 |
Nebulizer gas flow rate | 1.1 L/min (carrier and dilution gas combined – 0.6 + 0.5 L/min) |
Sampling cone | Nickel for x lens |
Skimmer cone | Nickel |
Sample uptake rate | 0.3 rps |
Nebulizer pump | 0.1 rps |
S/C temperature | 2 °C |
Scanning condition | Dwell time 1 sec, number of replicate 3 |
H2 gas flow | N/A |
He gas flow | 4.3 ml/min |
Table 7: ICPMS operating conditions.
10. Hg quantification by Cold Vapor Atomic Absorption Spectrophotometer (CVAAS)
Parameter | Level 1 | Level 2 | Level 3 | Level 4 | Level 5 | Level 6 |
L7 Hg standard to be added (ml) | 0 | 1 | 2.5 | 5 | 20 | 25 |
Final volume* (ml) | – | 50 | 50 | 50 | 100 | 50 |
Final concentration (µg/L) | 0 | 0.5 | 1.25 | 2.5 | 5 | 12.5 |
* Achieve this volume by adding the solution prepared in step 8.1 |
Table 8: Concentration of Hg calibration standard. Levels 1 to 6.
Parameters | Values |
Carrier gas | Argon, 100 ml/min |
Lamp | Hg electrodeless discharge lamp, setup at 185 mA |
Wavelength | 253.7 nm |
Slit | 0.7 nm |
Cell temperature | 100 °C |
Sample volume | 500 µl |
Carrier | 3% HCl, 9.23 ml/min |
Reductant | 10% SnCl2, 5.31 ml/min |
Measurement | Peak height |
Read replicates | 3 |
Table 9: CVAAS operating conditions.
Biomass yields
Production of N. salina in the PBR system used in this study grew from 1 g/L-1 to 8.5 ± 0.19 g/L-1 (N = 12) for control reactors and 4.0 ± 0.3 g/L-1 (N = 12) for the multi-metal contaminated in 7 days. The experiments produced repeatable data across triplicate reactors and multiple batches. Figure 2A shows the average culture density with very small standard error based on sampling from three independent PBRs. To ensure this result was not an isolated result, three more batches were grown with similar results. The combined results for all four batches are shown in Figure 2B. Although biological variability exists, this study shows that there is a consistent negative impact of inorganic contaminants to N. salina production. The biomass yields in the contaminant exposed PBRs were statistically different to the control PBRs from day 2 onwards (ANOVA, p <0.05).
Quality Control assessment of inorganic contaminant quantification
Twelve of the fourteen elements analyzed were fully recoverable after digestion as shown by the LFB%R with %R near 100%, indicating no losses, no gains and no cross-contamination of analytes during digestion (Table 10). During quantitative analysis of samples %D and RPD were monitored through all analysis and the average of the results are shown in Table 10. As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, V and Zn passed the %D and RPD, however %D for Pb and Sb gradually dropped during analysis. The %D for these elements are improved after cone cleaning, however, constant cone cleaning is impractical, and therefore the data quality objectives for Pb and Sb were lowered. CCB for all the analytes were also below the MRL. Matrix effects were assessed by analyzing LFM samples and obtaining the %R. While Co, Hg, V and Sb passed the QC data criteria, it was not passed by As, Cd, Cr, Cu, Mn, Ni, Pb and Zn when digested biomass samples were analyzed, resulting in %R below the QC objectives. Matrix dilution in DW to a ratio of 1:3 (solute:solvent) resulted in %R that passed data quality criteria. Matrix effects were also observed during the analysis of the digested supernatant and were addressed by the same dilution ratio (Table 10) making sure the dilution did not compromise the detection limit of the instrument. Issues with the detection of Se and Sn were observed based on unstable readings and a contamination issue, respectively. The unstable readings for Se are attributed to salts in the matrix 27. The Sn contamination was traced back to an acid used in the digestion step.
Analyte | R | CCV | LFB | LFM for biomass samples | LFM for supernatant samples | ||||
%D | %R | Dilution ratio | %R | RPD | Dilution ratio | %R | RPD | ||
QC limits 25 | 0.9950 | ±10 | 70-130 | – | 75-125 | ±20 | – | 75-125 | ±20 |
As | 0.9998 | 1.8 | 101.0 | 1:3 | 100.4 | 5.2 | 1:3 | 92.5 | -0.5 |
Cd | 1.0000 | 1.4 | 102.6 | 1:3 | 103.5 | 4.6 | None | 92.3 | 0.6 |
Co | 0.9997 | 1.7 | 98.8 | None | 95.2 | -1.4 | None | 96.5 | -1.5 |
Cr | 0.9999 | 1.5 | 99.8 | 1:3 | 96.5 | 1.8 | 1:3 | 90.1 | -0.8 |
Cu | 0.9999 | 2.9 | 98.2 | 1:3 | 101.4 | 4.8 | 1:3 | 94.4 | -0.5 |
Hg | 0.9983 | -1.7 | 103.0 | None | 98.7 | 1.5 | None | 98.0 | 0.3 |
Mn | 0.9998 | 2.9 | 97.6 | 1:3 | 83.2 | 1.8 | 1:3 | 95.4 | -1.7 |
Ni | 0.9999 | 0.5 | 103.5 | 1:3 | 98.5 | 2.1 | None | 93.3 | -0.9 |
V | 0.9998 | 2.5 | 97.2 | None | 95.5 | -1.5 | None | 101.2 | -1.9 |
Pb | 0.9998 | 12.6 | 105.2 | 1:3 | 88.9 | 0.0 | None | 93.5 | -0.5 |
Sb | 0.9998 | 1.1 | 105.7 | None | 101.8 | -9.6 | None | 90.8 | -1.2 |
Zn | 0.9997 | 5.2 | 120.8 | 1:3 | 90.7 | 1.4 | None | 89.2 | -1.9 |
Table 10: Summary of the results of quality control samples. R = correlation coefficient, %D: percent difference, %R: percent recovery, RPD = relative percent difference, dilution ratio refers to solute:solvent ratio.
Inorganic contaminant concentrations
Heavy metal and inorganic contaminants were found in both biomass and supernatant medium. The concentrations found in the biomass for the 12 elements analyzed are shown in Figure 3. Concentrations in the biomass harvested from triplicate PBRs (N = 3) in batch #1 shows a very small standard error (Figure 3A). Combining data from triplicate PBRs from 4 batches consistently shows that inorganic contaminants are present in the biomass (N = 12). The concentrations found in the supernatant medium are shown in Figure 4. Results show triplicate PBRs (N = 3) for batch #1 also have small standard error (Figure 4A) and show that most contaminants preferentially were located in the biomass leading to very low concentrations in the supernatant with several sample concentrations close to the MRL of the instrument. Results from all four batches are presented in Figure 4B.
Figure 2. Culture concentration over the cultivation period for contaminated and control PBRs. (A) Culture density in batch #1, results from N = 3 PBRs. (B) Culture density in 4 batches, results from N = 12 PBRs. Empty circles represent contaminated biomass, filled circles represent the control.
Figure 3. Concentration of inorganic contaminants in biomass. (A) Concentration in batch #1, results from N=1 PBR for Zn and N = 3 PBRs for all the other analytes, (B) Concentration from 4 batches, results from N = 4 PBRs for Zn and N = 12 PBRs for all the other analytes. Mean concentrations are represented by black filled circles, individual data points are represented by grey filled circles. Error bars represent ± one standard error from the mean.
Figure 4. Concentration of inorganic contaminants in supernatant. (A) Concentration in batch #1, results from N = 3 PBRs, (B) Concentration from 4 batches, results from N = 12 PBRs. Mean concentrations are represented by black filled circles, individual data points are represented by grey filled circles. Error bars represent ± one standard error from the mean.
Saline microalgae N. salina can be successfully grown in the designed growth system with repeatable results and high biomass yields. Airlift mixing allowed for a well-mixed suspended culture with minimal settling or biofouling over the 7 day growth periods. The minimal light variability across the fluorescent light bank is also shown to not produce noticeable differences in growth.
The study shows heavy metal contaminated media at concentrations representative of integration with coal flue gas negatively impacts biomass growth. Repeatability in the study highlights the impact the multi-metal system has on productivity. Various steps in the process have the potential to negatively impact growth and contaminate the system requiring diligent experimental preparation. Determination of the pH of the medium before starting the experiment is a QC step that allows for verification that the medium is not acidified (e.g., resulting from improper PBR rinsing after acid soaking). Acidified medium will affect algal growth and change nutrient bioavailability (e.g., changes in inorganic carbon speciation and metals speciation) thus impacting the interactions between algal binding sites, nutrients and metals. The meticulous preparation of the laboratory equipment for these studies was required such that an accurate mass balance of the introduced metals can be performed. Other steps in the process have the potential to introduce unaccounted for metals highlighting the need for the use of proper grade solvents and chemicals. Proper QC through the process can effectively identify the introduction of heavy metal contaminants.
Results show introduced contaminants are distributed between the biomass (Figure 3), media (Figure 4) and environment. Inorganic contaminants found in harvested N. salina suggests that this microalgae will incorporate several of the inorganic contaminants present in flue gas. This assimilation can be a result of adsorption onto cell walls due to charged binding sites, absorption inside the cell due to metabolic activity, and precipitation of complexes formed with elements present in the medium28. Visually the reactors with inorganic contaminants after a couple of days appeared yellow in color compared to the dark green of the control reactors. Contaminated harvested biomass was not visually different from the contaminant-free biomass after pellet formation after harvesting by centrifugation. The visual color difference before harvest is attributed to a lower density biomass and stressed microalgae. Contaminants not removed in the biomass have the potential to accumulate in the media as illustrated in Figure 4. Accumulation in the media represents a potential to limit scale as media recycling represents a necessity for economic viability. The limitation would be dictated by the tolerance to heavy metal contaminants which will be species specific. The results of this study highlight the need to better understand the potential negative impacts on integrating microalgae growth systems with waste carbon sources, specifically coal based flue gas. The results from this study highlight the needs to understand the productivity implications of other contaminants expected to be present in flue gas such as oxides of sulphur and nitrogen, fine dust, and organic contaminants such as polychlorinated dibenzo dioxins and dibenzo furans. Previous TEA and LCA assessments have assumed a seamless integration without considering the impacts of contaminants such as heavy metals and inorganic contaminants on productivity. In general the results from this work highlight the impact of a multi-metal system on productivity and can be used to understand the potentials of microalgae to bioremediate contaminants.
The methodology presented allowed for the study of inorganic contaminants with repeatable results for microalgae. Some inorganic contaminants used in this experiment are traditionally found in growth systems at low concentrations, but the others do not have a known function in the cell. As a result the multi-element mixture of As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn at the concentration shown in Table 4 inhibited growth. Quantifying the amount of contaminants in the biomass can prove challenging in multi-metal systems. Often, samples with high contents of organics and salts can produce matrix interferences, polyatomic interferences, physical interferences and salt build up in cones that eventually leads to inaccurate readings and loss of analytical accuracy29,30. Quality control samples run together with the experimental samples helped to determine the accuracy and precision of the readings. Measurement of the analytes using the protocols developed for this study has shown to be accurate and precise producing acceptable recoveries that are within the acceptable performance for this type of study25,29. Digestion of samples by microwave oven was showed to be effective for N. salina as digested samples were clear with no presence of cell debris or immiscible portions. The matrix used in this experiments (algal biomass and artificial seawater) produced matrix interferences that were overcome by matrix dilution. However, higher biomass sample sizes than the ones used in this experiment could lead to matrix interferences, and therefore QC should be analyzed for each specific scenario.
The authors have nothing to disclose.
The authors would like to acknowledge funding from the National Science Foundation (award # 1335550), Utah Water Research Laboratory, Professor Joan McLean and Tessa Guy for their help during the metal/metalloids analysis. The authors also thank Laura Birkhold for her support with the data collection and Danna Olbright.
Chemicals | |||
Sodium chloride | Fisher Scientific | S271-3 | |
Calcium chloride dihydrate | Fisher Scientific | C79-500 | |
Potassium chloride | Fisher Scientific | P217-500 | |
Sodium meta silicate nonahydrate | Fisher Scientific | S408-500 | |
Magnesium sulfate heptahydrate | Fisher Scientific | M63-500 | |
Potassium nitrate | EMD Chemical | PX1520-5 | |
Potassium phosphate monobasic | Fisher Scientific | P285-500 | |
Ammonium ferric citrate | Fisher Scientific | I72-500 | |
Boric acid | Fisher Scientific | A73-500 | |
Sodium molybdate, dihydrate | EMD Chemical | SX0650-2 | |
Manganese chloride tetrahydrate | Fisher Scientific | M87-500 | |
Zinc sulfate heptahydrate | Fisher Scientific | Z68-500 | |
Cupric sulfate pentahydrate | Fisher Scientific | C489-500 | |
Biotin | Acros Organics | 230090010 | |
Thiamine | Acros Organics | 148990100 | |
Vitamin B12 | Acros Organics | 405920010 | |
Copper (II) chloride dihydrate | Sigma-Aldrich | 221783-100G | Irritant, Dangerous to the Environment |
Lead (II) chloride | Sigma-Aldrich | 268690-250G | Toxic, Dangerous to the Environment |
Sodium dichromate dihydrate | Sigma-Aldrich | 398063-100G | Oxidizing, Highly Toxic, Dangerous to the Environment |
Cobalt (II) chloride hexahydrate | Sigma-Aldrich | 255599-100G | Toxic, Dangerous to the Environment |
Nickel (II) chloride hexahydrate | Sigma-Aldrich | 223387-500G | Toxic, Dangerous to the Environment |
Sodium (meta) arsenite | Sigma-Aldrich | 71287 | Toxic, Dangerous to the Environment |
Cadmium chloride | Sigma-Aldrich | 202908-10G | Highly Toxic, Dangerous to the Environment |
Mercury (II) chloride | Sigma-Aldrich | 215465-100G | Toxic, Dangerous to the Environment |
Tin (II) chloride dihydrate | Fisher Scientific | T142-500 | Corrosive. Suitable for Hg analysis. Very hazardous. |
Manganese chloride tetrahydrate | Fisher Scientific | M87-500 | |
Vanadium (V) oxide | Acros Organics | 206422500 | Dangerous to the Environment |
Carbon dioxide | Air Liquide | I2301S-1 | Compressed |
Hydrogen peroxide | H325-500 | Fisher Scientific | 30% in water |
ICP-MS standard | ICP-MS-6020 | High Purity Standards | |
Mercury standard | CGHG1-1 | Inorganic Ventures | 1000±6 µg/mL in 5% nitric acid |
Argon | Air Liquide | Compressed | |
Helium | Air Liquide | Compressed, ultra high purity | |
Hydrogen | Air Liquide | Compressed, ultra high purity | |
Nitric acid | Fisher Scientific | A509-P212 | 67-70% nitric acid, trace metal grade. Caution: manipulate under fume hood. |
Hydrochloric acid | Fisher Scientific | A508-P212 | 35% hydrochloric acid, trace metal grade. Caution: manipulate under fume hood. |
Equipment | |||
Scientific prevacuum sterilizer | Steris | 31626A | SV-120 |
Centrifuge | Thermo Fisher | 46910 | RC-6 Plus |
Spectrophotometer | Shimadzu | 1867 | UV-1800 |
pH controller | Hanna | BL981411 | X4 |
Rotometer, X5 | Dwyer | RMA-151-SSV | T31Y |
Rotometer, X5 | Dwyer | RMA-26-SSV | T35Y |
Water bath circulator | Fisher Scientific | 13-873-45A | |
Compact chiller | VWR | 13270-120 | |
Freeze dryer | Labconco | 7752020 | |
Stir plate | Fisher Scientific | 11-100-49S | |
pH lab electrode | Phidgets Inc | 3550 | |
Inductively coupled plasma mass spectrometer | Agilent Technologies | 7700 Series ICP-MS | Attached to autosampler CETAC ASX-520 |
FIAS 100 | Perkin Elmer Instruments | B0506520 | |
Atomic absorption spectrometer | Perkin Elmer Instruments | AAnalyst 800 | |
Cell heater (quartz) | Perkin Elmer Instruments | B3120397 | |
Microwave | Milestone | Programmable, maximum power 1200 W | |
Microwave rotor | Milestone | Rotor with 24 75 mL Teflon vessels for closed-vessel microwave assisted digestion. | |
Materials | |||
0.2 micron syringe filter | Whatman | 6713-0425 | |
0.2 micron syringe filter | Whatman | 6713-1650 | |
0.45 micron syringe filter | Thermo Fisher | F2500-3 | |
Polystyrene tubes | Evergreen | 222-2094-050 | 17×100 mm w/cap, 16 mL, polysteryne |
Octogonal magnetic stir bars | Fisher scientific | 14-513-60 | Magnets encased in PTFE fluoropolymer |