Data review is a crucial part of water quality analysis quality assurance and the final effective quality control measure in the entire quality assurance system. Besides meeting the requirements of the quality control analysis indicators, the key aspects of data review include the recording, calculation, and reporting of significant figures, as well as the reasonable relationships between data. The following theoretical study examines these two aspects to provide a reference for data review. 1. Recording Significant Figures: Significant figures consist of all definite figures and one uncertain figure. Depending on the measuring instruments used, accurate recording of measurement data is essential, retaining only one uncertain figure. Precision is typically expressed using only one significant figure; when the number of measurements is high, two significant figures can be used, but at most two. The number of significant figures achievable by the measurement results must not be lower than the number of significant figures achievable by the method detection limit. The correlation coefficient of the regression equation is retained to only four decimal places, rounding off the remainder. Significant figure calculations must conform to the calculation rules. The number of decimal places retained in addition and subtraction calculations should be the same as the number of decimal places retained in the calculated data. For multiplication and division calculations, the number of significant figures retained should be the same as the number of significant figures retained in the calculated data. For other data, rounding should be performed first, and the significant figures of the result should be the same as the number of significant figures retained in the calculated data. The number of significant figures retained in the result of exponentiation or root extraction should be the same as the number of significant figures retained in the original number. In logarithmic calculations, the number of decimal places (excluding the first digit) of the logarithm should be the same as the number of significant figures retained in the original number. 2. Review of the reasonable relationship between data 2.1 Relationship between filterable evaporation residue and total filterable ions For clean water samples, the filterable evaporation residue (dried to constant weight at 105℃) is roughly equal to the sum of filterable ions (mainly the eight major ions in water: Na+, K+, Ca+, Mg2+, SO42-, Cl-, HCO3-, SiO32-). For contaminated water samples, due to the potential presence of high concentrations of Fe3+, Mn2+, Zn2+, Cu2+, F-, NO3- ions, the concentration of the filterable evaporation residue may be greater than the sum of the concentrations of these eight ions. If the water sample contains a significant amount of acidic components, the concentration of the filterable evaporation residue may be less than the sum of the concentrations of these eight ions, as the acid is lost through volatilization during drying. 2.2 Relationship between Total Dissolved Solids and Conductivity Conductivity is the reciprocal of the resistance of an aqueous solution. The more soluble ions in a water sample, the lower the resistance and the higher the conductivity. Therefore, there is a certain correlation between the conductivity and total dissolved solids in a water sample. In natural water, the ratio of total dissolved solids to conductivity is approximately 0.55–0.70, which is only a rough estimate. If the water sample contains a significant amount of free acid or caustic alkali, the ratio will be lower than 0.55; if the water sample contains a large amount of salt, the ratio may be higher than 0.70. 2.3 Relationship between Total Dissolved Solids and Total Hardness Since there are eight main ions in water, including Ca2+ and Mg2+, the total hardness of a water sample is less than the total dissolved solids, with a ratio of approximately 0.50–0.80. This is only a rough estimate. If the Ca+ and Mg2+ content in the water is very high, the ratio will be greater than 0.80, while if the Ca+ and Mg2+ content is very low, the ratio will be less than 0.50. 2.4 Relationship between Total Hardness and Total Calcium and Magnesium Content Total hardness is actually the total molar concentration of calcium and magnesium. However, since other ions also complex with EDTA, when the concentration of other ions is high, the measured total hardness should be greater than the sum of the molar concentrations of calcium and magnesium. When the concentration of other ions is low, the measured total hardness is approximately equal to the sum of the molar concentrations of calcium and magnesium. 2.5 Relationship between Total Alkalinity and Total Hardness, Carbonate Hardness, and Non-Carbonate Hardness Carbonate hardness and non-carbonate hardness are two components of total hardness, usually expressed as CaCO3 (mg•L-1). Carbonate hardness is equivalent to the hardness formed by the combination of carbonates and bicarbonates with calcium and magnesium in water. When the calcium and magnesium content in water exceeds the content of carbonates and bicarbonates bound to them, the excess calcium and magnesium combine with chlorides, sulfates, and nitrates in the water to form non-carbonate hardness. Total alkalinity refers to the sum of the total amount of carbonates, bicarbonates, and hydroxides in a water body, mainly reflecting the content of CO32+, HCO3-, and OH- in the water body, and is usually expressed as CaCO3 (mg•L-1). From the above concepts, it can be concluded that when total hardness > total alkalinity, total hardness equals the sum of carbonate hardness and non-carbonate hardness, and non-carbonate hardness should be detected; when total hardness < total alkalinity, total hardness equals carbonate hardness, and non-carbonate hardness should not be detected. 2.6 The relationship between solution pH and carbonate, bicarbonate, and free carbon dioxide is given by K = [CO2]/[H2CO3] = 3.8 × 102, Ka1 = [H+][HCO3-]/[H2CO3] = 4.27 × 10-7, and Ka2 = [H+][CO32-]/[HCO3-] = 5.59 × 10-11. Therefore, hydrated CO2 is the main form of carbonic acid solution. [H2CO3] ≈ [CO2]. pH = 6.37 + lg[HCO3-] - lg[CO2] = 10.25 + lg[CO32-] - lg[HCO3-]. When pH < 7, the free CO2 content is highest; when pH > 10, the CO32- content is highest; and when 7 < pH < 10, the HCO3- content is highest. 2.7 Relationship between Molar Concentrations of Anions and Cations in Water The molar concentration relationship referred to here is the relationship between the sum of the equivalent concentrations of anions and cations. Since anions and cations in water are always in a mutually related and mutually restrictive relationship, to maintain the charge balance of anions and cations in the aqueous solution, the sum of their molar concentrations (equivalent concentrations) should be approximately equal. 2.8 Relationship between Ion Product and Solubility Product Many compounds have very low solubility in water, such as CuS, HgS, CaF2, MgF2, SrSO4, BaSO4, AgCl, and HgCl2. Moreover, in near-neutral natural water bodies, most heavy metals hydrolyze into sparingly soluble hydroxide precipitates, which are then adsorbed or transferred to the precipitate phase by suspended matter (e.g., Fe3+). Therefore, the concentration of heavy metal ions in filterable water cannot be high. When the ion product is greater than the solubility product, the compound precipitates; when the ion product is less than the solubility product, the ion can exist in the solution. Therefore, there is a significant negative correlation between F- and Ca2+, Mg2+, SO42- and Ba2+, Sr2+, S2- and Cu2+, Hg2+, and Cl- and Ag+, Hg2+. When the concentration of one is high, the concentration of the other is very low. 2.9 Relationship between CODCr, CODMn, and BOD5 Based on the concepts of these three and their actual measurement process, for the same water sample, the following rule should exist: CODCr > CODMn CODCr > BOD5 2.10 Relationship between nitrogen and dissolved oxygen Because the form of nitrogen in the environment changes with environmental conditions, especially affected by the concentration of dissolved oxygen in the water, nitrate nitrogen and ammonia nitrogen cannot be high at the same time. Generally, in water bodies with high dissolved oxygen, the concentration of nitrate nitrogen is higher than that of ammonia nitrogen, and vice versa. The concentration of nitrite nitrogen has no significant relationship with this. 2.11 Relationship between Total Bacterial Count, Coliforms, and Fecal Coliforms: Since coliforms are only one group of bacteria, the pathways of contamination are limited. Long-term testing results show that samples with detected coliforms also have detectable total bacterial counts, but samples with high total bacterial counts do not necessarily have detectable total coliforms. Because fecal coliforms are part of the total coliforms, and their detection temperature is 44.5℃, higher than the detection temperature of 37℃ for total coliforms, the detected value of fecal coliforms is lower than that of total coliforms; that is, fecal coliform value < total coliform value. 2.12 Relationship between the ratio of fecal coliform and fecal streptococcal values ​​and the source of fecal contamination: Fecal coliforms are common bacteria in the feces of humans or warm-blooded animals, while fecal streptococci are common bacteria in the feces of warm-blooded animals and are more abundant than fecal coliforms. Detecting fecal coliform and fecal streptococcus levels, and based on their ratio, yields the following results: a fecal coliform to fecal streptococcus ratio less than 0.7 indicates predominantly human fecal contamination; a ratio greater than 4.1 indicates predominantly warm-blooded animal fecal contamination; and a ratio greater than 0.7 but less than 4.1 indicates co-contamination by both. In summary, environmental water quality monitoring is not merely a simple laboratory analysis, but a comprehensive process encompassing site selection, sampling, analysis, and data processing. Given the current challenges in implementing comprehensive quality assurance, data verification is particularly crucial. Only by strengthening practical experience and research in this area can we improve data quality and provide high-quality, efficient services for water quality management. References: [1] Editorial Group of "Environmental Water Quality Monitoring Quality Assurance Manual". 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