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SELECTED NUTRIENTS AND HEAVY METALS IN SEWAGE SLUDGE FROM NEW JERSEY POTWs 1
Author(s) -
Krogmann Uta,
Chiang HaiNing C.
Publication year - 2002
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2002.tb00989.x
Subject(s) - sewage sludge , sewage , kjeldahl method , environmental science , nutrient , pollutant , pollution , environmental chemistry , environmental engineering , chemistry , nitrogen , ecology , organic chemistry , biology
In order to determine appropriate application rates and to ensure low pollutant levels in sewage sludge, knowing the chemical composition of sewage sludge is of great importance in a land application program. The objective of this study is to evaluate the variability of selected chemical characteristics of sewage sludge from New Jersey publicly owned treatment works (POTWs). Measurements of total Kjeldahl nitrogen (TKN), NH 4 + ‐N, P, K + , Cd, Cu, Pb, and Zn reported by 98 facilities in the 1996 and 1997 New Jersey Sludge Quality Assurance Regulations (SQAR) reports were statistically analyzed. Sewage sludge from Category 5 POTWs (greater than 10 percent industrial input) showed higher Cd, Cu, and Pb concentrations than Category 3 and Category 4 facilities (less than 10 percent industrial input). Even though only two years of data were analyzed, there was an indication that Cd and Pb concentrations in sewage sludge are decreasing with time. The yearly mean of only a few facilities exceeded the federal pollution concentration limits (40 CFR Part 503, Table 3). Phosphorus and Cd values showed the highest variability within facilities based on the coefficient of variation. Due to the variability of sewage sludge constituents, the use of the yearly rolling mean of nutrient concentrations to determine application rates was considered inadequate. An actual analysis of the sewage sludge to be applied is more appropriate to determine application rates than historical data.