Stoichiometric interpretations of C:N:P ratios in organic waste materials
Maria Lourdes San Diego-McGlone1, Stephen V. Smith2, Vivian F. Nicolas1
1Marine Science Institute, University of the Philippines, Diliman, Quezon City 1101, Philippines
2Department of Oceanography, University of Hawaii, 1000 Pope Road, Honolulu, Hawaii 96822, USA
Stoichiometric proportionalities were derived that can be used to convert reported BOD values of organic wastes to C, N, and P estimates. Ratios to approximate the dissolved inorganic fractions of N and P from reported TN and TP values were also obtained. Stoichiometric ratios were determined for various kinds of organic waste load.
(This page is taken from:San Diego-McGlone, M.L., S.V. Smith and V. Nicolas. 1999.)
In pollution monitoring activities for water bodies, BOD is a commonly determined variable and is an important water quality indicator and descriptor of effluent content. Thus, many reports contain BOD values. Rapid assessment techniques such as provided by Economopoulos (1993), engineering tables to design or evaluate waste treatment facilities (e.g., Tchobanoglous and Burton, 1991), and most waste-stream monitoring programs are based on BOD as the main, often the sole, calibration variable for waste loading. Many such monitoring studies do not include other variables that may also be of environmental importance, e.g., N, P, TOC, and COD. Definitions of all the variables used in the study are given in Table 1.
The present exercise has been an attempt to determine generalized stoichiometric C:N:P ratios in organic waste materials from studies in which multiple variables have been measured. If general trends can indeed be found, then one can convert frequently available BOD data into estimates for N, P, or C. For ecosystems that are affected by anthropogenic activities, this information is important for assessing impacts of wastes on inventory and C, N, P balance and for inferring assimilative capacities of the environment for waste inputs. We have encountered the need for such general loading indices in the construction of mass balance budgets for coastal ecosystems for which sparse data on material loading are available (following the budgeting guidelines laid out for the LOICZ project, by Gordon et al., 1996).
A study by Strain et al. (1995) of nutrient loading and oxygen demand associated with multiple uses of a tidal inlet in Nova Scotia underscores the potential utility of such information. That inlet receives wastes from aquaculture, fish processing, a pulp mill, and a municipal sewage treatment plant. The authors made the assumption that oxygen demand and the C, N, and P content of these wastes could be related to the familiar Redfield Ratio, which characterizes the composition of phytoplankton. It would be useful to know how reliable the Redfield Ratio or some alternative general ratio is in the evaluation of organic waste loading to the environment.
Materials and Methods
Data on organic wastes were derived from 72 references in the primary literature (see References marked with *). Waste was classified into categories adapted from Economopoulos (1993). These are: Category 1, for animal agriculture and livestock production; Category 2, for food, tanneries, leather, wood and paper manufacturing; Category 3, for industrial chemicals; and Category 4, for sanitary services. Since stoichiometric proportionalities are most readily visualized on a molar basis, reported estimates of BOD, COD, TN, TP, TOC, TKN, NH4-N, NO3+NO2-N, and PO4-P from organic wastes were converted to molar units prior to the statistical analysis. To download an excel spreadsheet containing these data, click here. To download an excel spreadsheet that will allow you to estimate the nutrient load to coastal ecosytems associated with effluent, click here.
We make the assumption that any two variables X and Y, representing chemical entities of interest, are proportional to one another. This may be called the "stoichiometric assumption." It is implicit that there is neither curvature in a scatter diagram of X versus Y nor residual amounts of either X or Y as the other value (Y or X) approaches 0. That is,
Y = k2X (1)
The value k2 can be calculated as the simple ratio of the mean of Y divided by the mean of X. This is equivalent to a regression equation in which the intercept (k1) is forced through the origin. The slope (k2) is simply the ratio of the mean value of Y to the mean value of X.
In the available data, the units for X and Y are mixed (e.g., concentration, flux). Moreover, the dilution factors for the materials vary by orders of magnitude. The result of these two characteristics is that the data are very non-normally distributed. This implies that solving the regression equation (whether or not k1 is forced through the origin) will greatly bias the estimated proportionality constant towardss large numbers. The problem of data that are not normally distributed can be overcome by use of log-transformed data. This latter situation suggests an equation of the following form might be appropriate:
Y = aXb (2)
In order to preserve the simple proportionality of the "stoichiometric assumption," b is set equal to 1, and the equation is log-transformed:
log(Y) = log(a) + log(X) (3)
Equations (1) and (2) demonstrate that k2 and a are algebraically equivalent, if b = 1. The statistical derivation of k2 and a will give quite different results, however. Because the desire is not to weight the proportionality constant excessively by large numbers, equation (3) is the preferred equation to derive the proportionality constant. For n data points, the proportionality constant can therefore be simply estimated from the following relationship, which follows from a least-squares-fit of the parameter a:
This is equivalent to:
i= aest xI (4b)
The next requirement is evaluating the goodness of fit of the data to equation (4). This is the equivalent of r2, except that the simple calculation of r2 is not directly applicable. The desired statistic (that is, the coefficient of determination, CD) is the ratio of the explained sum of squares to the total sum of squares of the log transformed Y values. The total sum of squares for log(Y) (SSTO) can be evaluated:
SSTO can be broken into the components SSR (the sum of squares explained by the proportionality constant) and SSE (the error sum of squares):
SSE is calculated as the deviation of the log(Y) values from the proportionality constant, where log() is the estimated value. Thus
It follows from equations (7) and (8) that
The proportion of the variance in log(Y) that is explained by the regression equation is given by the ratio SSR/SSTO. This value (CD) is analogous to r2.
Tables 2 and 3 present a summary of the stoichiometric ratios of various variables scaled to BOD, TN, and TP, respectively that passed the 95% confidence criteria. Figures 1 - 4 show stoichiometric ratios scaled to BOD, COD, TN & TP and TOC. Stoichiometric ratios for the various categories of organic wastes, as well as for combined categories, are reported. The underlying advantages of working with combined categories are a lessened need to "assign" a particular kind of waste load to a specific category when estimating pollutant loading, and a greater number of samples within each grouped category (hence, more robust statistics for the stoichiometric calculations). Close agreement was seen for some of the ratios derived from different and combined categories indicating similarity in the C, N, and P components of organic wastes from various sources.
The data in Tables 2 and 3 lead to the
following generalities. The COD:BOD molar ratio for most materials can be well
approximated by the value of 2.6 (n = 53). There is more scatter for the other
scalings relative to BOD, but the following general overall COD:TOC:TN:TP:BOD ratio is
reconstructed: 2.6:1.7:0.5:0.042:1. This ratio can be used in general to scale from BOD
loading to the other variables. The Redfield (O2:C:N:P) ratio as applied by
Strain et al. (1995) was based on the composition of plankton (Redfield, 1934) and is
-138:106:16:1. The waste load ratio we have derived, expressed in equivalent units, is -62:40:12:1. Waste load is therefore rich in the nutrients N and P, relative to the C content of plankton.
It also appears from the data that about 50% of the P in waste loads is PO4 albeit with considerable scatter in the data; the remainder is assumed to be organic, although polyphosphate may be important in some instances. Typically about 40% of the N is NH4, with NO3 usually being very minor; the remainder of the N is organic.
Moreover, the organic matter (as represented by C) has a higher oxygen demand (COD:TOC = 62/40 = 1.55) than either the classical Redfield ratio based on plankton and seawater composition (Redfield, 1934; Redfield et al., 1963) (O2:C:N:P = -138:106:16:1; COD:TOC = 138:106 = 1.30) or more recent formulations by Takahashi et al. (1985) (O2:C:N:P = -175:122:16:1; COD:TOC = 175:122 = 1.43). While BOD is traditionally treated as an index of the organic matter which is readily oxidized on time scales of days, it is likely that most or all of the COD represents oxygen loading on the receiving systems over longer time scales. Terrestrial plant-derived organic matter in general tends to have a relatively high carbon content (e.g., Vitousek et al., 1988), so we assume that the relatively low TOC content and high inorganic nutrient content of waste material represent partial (up to 50%) oxidation of organic matter in the waste production process.
The study by Strain et al. (1995), cited in the Introduction, used the Redfield Ratio to approximate the composition of various forms of waste discharge into a tidal inlet. That approximation seems likely to overestimate oxygen utilization relative to nutrient loading and to underestimate oxygen utilization relative to organic carbon loading. The more important point to the present analysis is not to take issue in any substantive way with that study, but rather to recognize a need for conversion factors and to present a generic ratio that can be more rationally related to waste load composition than the Redfield Ratio. Moreover, the analysis here provides basis to partition the nutrient loading in untreated effluent between organic and inorganic nutrients. The effects of these two forms of N and P delivery would be very different to subsequent reactions within the ecosystem.
It needs to be stressed that this analysis is based on untreated effluents. Waste treatment to secondary levels will have an elevated ratio of TN and TP relative to BOD, COD, and TOC and a higher ratio of inorganic nutrients relative to total nutrients. These changes will represent organic oxidation of a portion of the waste load, without nutrient removal. The TN:TP ratio of waste streams not subjected to tertiary treatment should tend to be relatively constant. Tertiary treatment will obviously remove some N or P, or both. Because much waste produced by human activities enters the environment with little or no treatment, the waste composition ratios constructed here should have relatively wide applicability.
The results of this exercise are stoichiometric interpretations of O2:C:N:P ratios associated with organic wastes from various categories. The relatively small differences among categories suggest that for many purposes a single ratio can be used. While any assessment of mass loading to an environment will obviously be more robust if direct measurements of the waste composition are available, it appears that quite a bit can be inferred about the composition of mass loading from BOD alone.
Dennis Swaney is gratefully acknowledged for his critical evaluation and suggested modifications of the statistical analysis employed here. We also thank WOTRO for providing the funds for this exercise. This analysis has been undertaken as part of the biogeochemical modelling being undertaken by the IGBP core project element, Land-Ocean Interactions in the Coastal Zone (LOICZ).
*Abdelmonem, N. & Abou-Elela, S.I. (1994). In-plant control in oil and soap industry. Wat. Sci. Tech. 29(9), 143-149.
*Alexiou, I.E., Anderson, G.K. & Evison, L.M. (1994). Design of pre-acidification reactors for the anaerobic treatment of industrial wastewaters. Wat. Sci. Tech. 29(9), 199-204.
*Appan, A. & Kean, C.K. (1979). A computer solution for determination of unit pollution loads. Prog. Water Tech. 11, 521-530.
*Arueste, G., Farchill, D., Goldstein, M. & Gruber, Y. (1989). Operation of the Soreq wastewater treatment plant with a single-stage nitrification-denitrification activate sludge system. Wat. Sci. Tech. 21, 1359-1372.
*Bahre, G., Firk, W. & Gassen, M. (1990). Development of a two-stage treatment plant for extensive nitrogen and phosphorus elimination. Wat. Sci. Tech. 22(7/8), 171-179.
*Ball, R., Kayser, R., Peter, A. & Sarfert, F. (1989). Full-scale experiences with biological phosphorus removal at the wastewater treatment plants of West Berlin. Wat. Sci. Tech. 21, 1373-1387.
*Barnard, J.L. (1975). Biological nutrient removal without the addition of chemicals. Water Res. 9, 485-490.
*Barnard, J.L. (1984). Design and operation of Bardenpho plants in an African country. Water Pollut. Control 83, 443-449.
*Barnard, J.L., Stevens, G.M. & Leslie, P.J. (1985) Design strategies for nutrient removal plant. Wat. Sci. Tech. 17, 233-242.
*Barker, J.C., Humenik, F.J., Overcash, M.R., Phillips, R. & Wetherill, G.D. (1980). Performance of aerated lagoon-land treatment systems for swine manure and chick hatchery wastes. In Livestock Waste: A Renewable Resource. Proceedings of the 4th International Symposium on Livestock Wastes - 1980, Amarillo, Texas. pp. 217-220.
*Battistoni, P. & Fava, G. (1994). Fish processing wastewater treatment requirements by line production changes. Wat. Sci. Tech. 29(9), 111-119.
*Bland, R.R., Martin Jr., J.H. & Loehr, R.C. (1980). Treatment of milking center wastewater in facultative ponds. In Livestock Waste: A Renewable Resource. Proceedings of the 4th International Symposium on Livestock Wastes - 1980, Amarillo, Texas. pp. 221-234.
*Bongards, M., Hengstermann, T. & Kdhne, M. (1993). Principles of operation and experimental results for a small wastewater treatment plant of 300 population equivalents. Wat. Sci. Tech. 28(10), 387-392.
*Brond, S., Sund, C. (1994). Biological removal of nitrogen in toxic industrial effluents, high in ammonia. Wat. Sci. Tech. 29(9), 231-240.
*Buelna, G., Bhattarai, K., de la None, J. & Taiganides, E.P. (1990). Evaluation of various flocculants for the recover of algal biomass grown on pig-waste. Biological Wastes 31, 211-222.
*Burdick, C.R., Refling, D.R. & Stensel, H.D. (1982). Advanced biological treatment to achieve nutrient removal. J. Water Pollut. Control Fed. 54(7), 1078-1086.
*Cimino, G. & Caristi, C. (1990). Acute toxicity of heavy metals to aerobic digestion of waste cheese whey. Biological Wastes 33, 201-210.
*Cooper, R.N., Heddle, J.F. & Russell, J.M. (1979) Characteristics and treatment of slaughterhouse effluents in New Zealand. Prog. Water Tech. 11(6), 55-68.
*Croce, F., Poulsom, S. & Hendricks, D.W. (1994). Combined treatment of olive mill effluent and municipal wastewater in a small tourist community. Wat. Sci. Tech. 29(9), 105-110.
*Crockett, A.B. (1997). Water and wastewater quality monitoring, McMurdo Station, Antarctica. Environmental Monitoring and Assessment 47, 39-57.
*Curi, K., Velioglu, S.G. & Sur, M.H. (1985). Anaerobic treatment of olive oil wastewater. In Appropriate Waste Management for Developing Countries (K. Kuri, ed.), pp. 291-310. Plenum, New York.
*Dakers, A.J. (1979). Management of livestock wastes in New Zealand--problems and practice. Prog. Water Tech. 11(6), 397-404.
*Deakyne, C.W., Patel, M.A. & Krichten, D.J. (1984). Pilot plant demonstration of biological phosphorus removal. J. Water Pollut. Control Fed. 56, 867-873.
*Dilek, F.B. & Gokcay, C.F. (1994). Treatment of effluents from hemp-based pulp and paper industry. I. Waste characterization and physico-chemical treatability. Wat. Sci. Tech. 29(9), 161-163.
Economopoulos, A.P. (1993). Rapid Inventory Techniques in Environmental Pollution. In Assessment of Sources of Air, Water, and Land Pollution. World Health Organization, Geneva.
*Farran, I.G. (1979). A closed piggery waste management system using solid separation. Prog. Water Tech. 11(6), 133-146.
*Fiestas, J. A., Martin, A. & Borja, R. (1990). Influence of immobilization supports on the kinetic constants of anaerobic purification of olive mill wastewater. Biological Wastes 33, 131-142.
*Forster, C.F. & Wase, D.A.J. (1983). Anaerobic treatment of dilute wastewater using an upflow sludge blanket reactor. Environ. Pollut. (Ser. A) 31, 57-61.
*Fukase, T., Shibata, M. & Miyaji, Y. (1985). Factors affecting biological removal of phosphorus. Wat. Sci. Tech. 17, 187-198.
*Fulhage, C.D. (1980). Performance of anaerobic lagoons as swine waste and treatment facilities in Missouri. In Livestock Waste: A Renewable Resource. Proceedings of the 4th International Symposium on Livestock Wastes - 1980, Amarillo, Texas. pp. 225-227.
*Gao, Z., Sun, T. & Qu, X. (1991). Studies on the land treatment irrigation system of municipal wastewater in Shengyang. Wat. Sci. Tech. 24(5), 47-53.
*Ghobrial, F.H. (1993). Performance assessment of three wastewater treatment plants providing effluents for irrigation. Wat. Sci. Tech. 27(9), 139-146.
Gordon, D.C., Jr., Boudreau, P.R., Mann, K.H., Ong, J.-E., Silvert, W.L., Smith, S.V., Wattayakom, G., Wulff, F., & Yanagi, T. (1996). LOICZ Biogeochemical Modelling Guidelines. LOICZ/R&S/95-5, vi +96pp. LOICZ, Texel, The Netherlands.
*Guillard, J.F., Aminot, A. & Menesguen, A. (1992). Urban wastewater disposal and eutrophication risk assessment in the coastal zone. Wat. Sci. Tech. 25(12), 77-86.
*Hamza, A. (1985). Treatment of wastewater from the canning industry in Egypt. In Appropriate Waste Management for Developing Countries, (K. Kuri, ed.) pp. 349-362, Plenum, New York.
*Herbert, J.C., Fries, M.K. & Archer, A.B. (1992). The feasibility studies and design of a public sewage collection, treatment, and outfall scheme for the south coast of Barbados. Wat. Sci. Tech. 25(12), 3-12.
*Hong, S., Krichten, D., Best, A. & Rachwal, A. (1984). Biological phosphorus and nitrogen removal via the A/O process: recent experience in the United States and United Kingdom. Wat. Sci. Tech. 16, 151-172.
*Imine, R.L., Ketchum Jr., L.H., Arora, M.L. & Barth, E.F. (1985). An organic loading study of full-scale sequencing batch reactor. J. Water Pollut. Control Fed. 57, 847-853.
*Kang, S.J., Bailey, W.F. & Jenkins, D. (1992). Biological nutrient removal and the Blue Plains wastewater treatment plant in Washington, D.C. Wat. Sci. Tech. 26(9-11), 2233-2236.
*Kasapgil, B., Anderson, G.K. & Ince, O. (1994). An investigation into the pre-treatment of dairy wastewater prior to aerobic biological treatment. Wat. Sci. Tech. 29(9), 205-212.
*Keeley, G.M. & Quin, B.F. (1979). The effects of irrigation with meatworks-fellmongery effluent on water quality in the unsaturated zone and shallow aquifer. Prog. Water Tech. 11(6), 369-386.
*Leach, L.E., Duan, Z.B., Wang, S.T. & Bledsoe, B.E. (1991). Bilateral wastewater land treatment research by China and the U.S. EPA. Wat. Sci. Tech. 24(5), 33-40.
*Li, J., Wang, J. & Zang, J. (1991). Removal of nutrient salts in relation with algae in ponds. Wat. Sci. Tech. 24(5), 75-83.
*Lin, C.Y. (1990). Aerobic treatment of pesticide-plant wastewater. Biological Wastes 34, 301-311.
*Lockyer, D.R. & Pain, B.F. and Klarenbeek, J.V. (1989). Ammonia emissions from cattle, pig and poultry wastes applied to pasture. Environ. Pollut. 56, 19-30.
*Loehr, R.C. (1979). Potential pollutants from agriculturean assessment of the problem and possible control approaches. Prog. Wat. Tech. 11(6), 169-193.
*Londong, J. & Zander, S. (1990). Steps in planning the expansion of the large sewage treatment plant at Buchenhoffen, operated by the Wupper Watershed Management Association. Wat. Sci. Tech. 22(7/8), 123-129.
*Macgregor, A.N., Stout, J.D. & Jackson, R.J. (1979). Quality of drainage water from pasture treated with dairy shed effluent. Prog. Water Tech. 11(6), 11-17.
*Malnou, D., Meganek M., Faup, G.M. & du Rostu, M. (1984). Biological phosphorus removal: study of the main parameters. Wat. Sci. Tech. 16, 173-185.
*Mathur, S.P., Patni N.K. & Levesque, M.P. (1990). Static pile, passive aeration composting of manure slurries using peat as a bulking agent. Biological Wastes 34, 323-333.
*Milbury, W.F., McCauley, D. & Hawthome, C.H. (1971). Operation of conventional activated sludge for maximum phosphorus removal. J. Water Pollut. Control Fed. 43, 1890-1901.
*Nakasone, H. & Ozaki, M. (1993). Study on the denitrification ability of the contact aeration process. Wat. Sci. Tech. 28(10), 369-376.
*Nemerow, N.L. (1971). Liquid waste of industry: theories, practices and treatment. 584 pp. Addison-Wesley, Massachusetts.
*Nodar, R., Acea, M.J. & Carballas, T. (1990). Microbial composition of poultry excreta. Biological Wastes 33, 95-105.
*Odegaard, H. (1992). Norwegian experiences with chemical treatment of raw wastewater. Wat. Sci. Tech. 25(12), 255-264.
*Ozturk, I., Zambal, T., Samsunlu, A. & Gdknel, E. (1992). Environmental impact evaluation of Istanbul wastewater treatment and marine disposal systems. Wat. Sci. Tech. 9, 85-92.
*Pavlostathis, S.G. & Jungee, S.A. (1994). Biological treatment of photoprocessing wastewaters. Wat. Sci. Tech. 29(9), 89-98.
*Payne Jr., V.W.E., Shipp Jr., J.W. & Miller III, F.A. (1980). Supernatant characteristics of three animal waste lagoons in North Alabama. In Livestock Waste: A Renewable Resource. Proceedings of the 4th International Symposium on Livestock Wastes - 1980, Amarillo, Texas. pp. 240-243.
*Pitman, A.R., Venter, S.L.V. & Nicholls, H.A. (1983). Practical experience with biological phosphorus removal plants in Johannesburg. Wat. Sci. Tech. 15, 233-259.
Redfield, A. C. (1934). On the proportions of organic derivatives in seawater and their relation to the composition of plankton. pp. 176-192 James Johnston Memorial Volume. (R. J. Daniel, ed.) University Press of Liverpool, Liverpool, England.
Redfield, A. C., Ketchum, B. H. & Richards, F. A. (1963). The influence of organisms on the composition of seawater. pp 26-87 In The Sea, vol. 2. (M. N. Hill, ed.) Interscience, New York.
*Roberts, F., Guarino, C. & Arias M. (1994). The impact of industrial waste on Venezuela marine water. Wat. Sci. Tech. 29(8), 51-60.
*Rusten, B. & Eliassen, H. (1993). Sequencing batch reactors for nutrient removal at small wastewater treatment plants. Wat. Sci. Tech. 28(10), 233-242.
*Rusten, B. & Storhaug, R. (1991). Strategies for upgrading from primary treatment to nutrient removal at the Sandefjord sewage treatment plant. Wat. Sci. Tech. 24(10),187-194.
*Schierup, H.H. & Brix, H. (1990). Danish experience with emergent hydrophytic treatment systems (EHTS) and prospects in the light of future requirements on outlet water quality. Wat. Sci. Tech. 22(3/4), 65-72.
*Spatzierer, G., Ludwig, C. & Matsche, N. (1985). Biological phosphorus removal in combination with simultaneous precipitation. Wat. Sci. Tech. 17, 163-176.
Strain, P.M., Wildish, D.J., & Yeats, P.A. (1995). The application of simple models of nutrient loading and oxygen demand to the management of a marine tidal inlet. Mar. Pollut. Bull. 30, 253-261.
*Strotmann, U.J. & Weisbrodt, W. (1994). Wastewater treatment and integrated environmental protection at the BASF AG in Ludwigshafen, Germany. Wat. Sci. Tech. 29(8), 185-192.
*Sutton, A.L., Mayrose, V.B., Moeller, N.J., Underwood, L.B., Brown, C.M. & Kelly, D.T. (1980). Nutrient and biological changes in single-stage dairy and swine lagoons-two case studies. In Livestock Waste: A Renewable Resource. Proceedings of the 4th International Symposium on Livestock Wastes - 1980, Amarillo, Texas. pp. 252-256.
Takahashi, T., Broecker, W. S. & Langer, S. (1985). Redfield ratio based on chemical data from isopycnal surfaces. J. Geophys. Res. 90, 6907-6924.
*Talini, I. (1994). Pre-treatment of tannery wastewaters. Wat. Sci. Tech. 29(9), 175-178.
*Thomson, N.R., McBean, E.A., Snodgrass, W. & Monstrenko, I.B. (1997). Highway stormwater runoff quality: development of surrogate parameter relationships. Water, Air, Soil Pollut. 94, 307-347.
*Tunay, O., Orhon, D. & Kabdasli I. (1994). Pretreatment requirements for leather tanning industry wastewater. Wat. Sci. Tech. 29(9), 121-128.
Tchobanoglous, G. & Burton, F. L. (1991). Waste-water Engineering: Treatment, Disposal, and Reuse, 3rd edition, New York. McGraw Hill.
*Veliglu, S.G., Curi, K., Baban, A. & Alpaslan, N. (1985). Improvement of biodegradability in anaerobic digestion of dairy cow manure. In Appropriate Waste Management for Developing Countries (K. Kuri, ed.), pp. 247-264, Plenum, New York.
Vitousek, P. M., Fahey, T., D. Johnson, D. W. & Swift, M. J. (1988). Element interactions in forest ecosystems: succession allometry, and input-output budgets. Biogeochemistry 5, 7-34.
*Warburton, D.J., Clarke, R.M. & Melcer, H. (1979). An alternative treatment system for dairy shed water. Prog. Water Tech. 11(6), 1-10.
*Wong, S.H., Wu, M.W. & Choi, C.C. (1990). Upgrading an aerated lagoon to a sequencing batch reactor for piggery waste treatment. Biological Wastes 34, 113-122.
*Yeoh, B.G. (1993). Use of water hyacinth (Eichhornia crassipes) in upgrading small agroindustrial wastewater treatment plants. Wat. Sci. Tech. 28(10), 207-213.
*Yeoman, S., Stephenson, T., Lester, J.N. & Perry, R. (1988). The removal of phosphorus during wastewater treatment:a review. Environ. Pollut. 49, 183-233.
* Data from this reference were used in the analysis presented here.
TABLE 1. Definition of variables
|BOD = Biological Oxygen Demand. BOD is a measure of the amount of dissolved oxygen consumed by microbial life while assimilating and oxidizing the organic matter present. Usually measured over 5 days.|
|COD = Chemical Oxygen Demand. COD is the amount of oxygen consumed when organic and oxidizable inorganic substances are oxidized by a strong chemical oxidant.|
|TOC = Total Organic Carbon. Sometimes (although not in this report) TOC is divided into particulate organic carbon (POC) and dissolved organic carbon (TOC).|
|N = Nitrogen. May be divided into various fractions. Most commonly reported forms are total nitrogen (TN), nitrate (NO3), nitrite (NO2), ammonium (NH4), and organic nitrogen (ON). NH4 + NO3 + NO2 is sometimes denoted dissolved inorganic nitrogen (DIN). Total Kjeldahl Nitrogen (TKN), the sum of NH4 and ON, is often reported, because for many years this was the standard method on N analysis in wastewater.|
|P = Phosphorus. Most commonly reported forms are phosphate (PO4), sometimes also denoted as dissolved inorganic phosphorus (DIP), and organic P (OP). Some waste materials also include polyphosphate compounds.|
TABLE 2. Stoichiometric ratio of variables scaled to BOD where the 95% confidence criterion is satisfied.
|Categorya||Nb||Ratioc||CDd (F test)|
|1, 4||38||2.7||0.9707 (1%)|
|1, 2, 3, 4||53||2.6||0.9608 (1%)|
|1, 4||33||0.50||0.9698 (1%)|
|1, 4||48||0.071||0.8764 (1%)|
|1, 2, 3, 4||62||0.042||0.7315 (1%)|
|2, 4||10||1.7||0.9888 (1%)|
|TKN/BOD||1, 4||26||0.35||0.5741 (1%)|
|1, 4||23||0.04||0.7543 (1%)|
1 = Animal Agriculture and Livestock Production; 2 = Food, Tanneries, Leather, Wood mfg.,
Paper mfg.; 3 = Industrial Chemicals; 4 = Sanitary Services
bnumber of data points
cstoichiometric ratio (molar)
dCD = coefficient of determination
TABLE 3. Stoichiometric ratio among different forms of N and P scaled to TN and TP where the 95% confidence criterion is satisfied.
|Category*||nb||Ratioc||CDd (F test)|
|1, 4||16||0.97||0.9983 (1%)|
|(NO3+NO2 )/TN||1||9||0.01||0.8893 (1%)|
|1, 4||33||0.38||0.9101 (1%)|
|1, 4||19||0.50||0.9164 (1%)|
1 = Animal Agriculture and Livestock Production; 2 = Food, Tanneries,
Leather, Wood mfg., Paper mfg.; 3 = Industrial Chemicals; 4 = Sanitary Services
bnumber of data points
cstoichiometric ratio (molar)
dCD = coefficient of determination
Back to [Node Introduction] [Table of Contents] [Nutrient budget][LOICZ]
You are visitor number since January 12, 2000
Last Updated 12 May 2009 by DPS