Residual effects of composted sewage sludge on nitrogen cycling and plant metabolism in a no-till common bean-palisade grass-soybean rotation.

Introduction and aims: In the context of increasing population and decreasing soil fertility, food security is one of humanity's greatest challenges. Large amounts of waste, such as sewage sludge, are produced annually, with their final disposal causing environmental pollution and hazards to human health. Sludge has high amounts of nitrogen (N), and, when safely recycled by applying it into the soil as composted sewage sludge (CSS), its residual effect may provide gradual N release to crops. A field study was conducted in the Brazilian Cerrado. The aims were to investigate the residual effect of successive applications of CSS as a source of N in the common bean (Phaseolus vulgaris L. cv. BRS Estilo)-palisade grass (Urochloa brizantha (A.Rich.) R.D. Webster)-soybean (Glycine max L.) rotation under no-tillage. Additionally, N cycling was monitored through changes in N metabolism; the efficiency of biological N2 fixation (BNF) and its implications for plant nutrition, development, and productivity, was also assessed. Methods: The experiment consisted of a randomized complete block design comparing four CSS rates (10, 15, 20, and 25 Mg ha-1, wet basis) to a control treatment (without adding mineral or organic fertilizer) over two crop years. Multiple plant and soil analyses (plant development and crop yield, Falker chlorophyll index (FCI), enzymatic, biochemical, 15N natural abundance, was evaluated, root and shoot N accumulation, etc.) were evaluated. Results and discussion: Results showed that CSS: i) maintained adequate N levels for all crops, increasing their productivity; ii) promoted efficient BNF, due to the stability of ureide metabolism in plants and increased protein content; iii) increased the nitrate content and the nitrate reductase activity in soybean; iv) affected urease activity and ammonium content due to changes in the plant's urea metabolism; v) increased N accumulation in the aerial part of palisade grass. Composted sewage sludge can be used as an alternative source to meet crops' N requirements, promoting productivity gains and N cycling through forage and improving N metabolism.

Soil quality index as a tool to assess biochars soil quality improvement in a heavy metal-contaminated soil.

The assessment of soil quality improvement provided by biochars is complex and rarely examined. In this work, soil quality indices (SQIs) were produced to evaluate coffee industry feedstock biochars improvement on soil quality samples of a heavy metal-multicontaminated soil. Therefore, a 90-day incubation experiment was carried out with the following treatments: contaminated soil (CT), contaminated soil with pH raised to 7.0 (CaCO3), contaminated soil + 5% (m/m) coffee ground biochar, and contaminated soil + 5% (m/m) coffee parchment biochar (PCM). After incubation, chemical and biological attributes were analyzed, and the data were subjected to principal component analysis and Pearson correlation to obtain a minimum dataset (MDS), which explain the majority of the variance of the data. The MDS-selected attributes were dehydrogenase and protease activity, exchangeable Ca content, phytoavailable content of Cu, and organic carbon, which composed the SQI. The resulting SQI ranged from 0.50 to 0.56, with the highest SQI obtained for the PCM treatment and the lowest for the CT. The phytoavailable content Cu was the determining factor for differentiating PCM from the other treatments, which was a biochar original attribute and helped to improve soil quality based on the SQI evaluation, further than heavy metal immobilization due to the soil sample pH increase. Longer-term experiments may illustrate clearer advantages of using biochar to improve heavy metal-contaminated soil quality, as physical attributes may also respond, and more significant contributions to biological attributes could be obtained as biochar ages.

Physicochemical and bacterial changes during composting of vegetable and animal-derived agro-industrial wastes.

This study investigates the impact of different agro-industrial organic wastes (i.e., sugarcane filter cake, poultry litter, and chicken manure) on the bacterial community and their relationship with physicochemical attributes during composting. Integrative analysis was performed by combining high-throughput sequencing and environmental data to decipher changes in the waste microbiome. The results revealed that animal-derived compost stabilized more carbon and mineralized a more organic nitrogen than vegetable-derived compost. Composting enhanced bacterial diversity and turned the bacterial community structure similar among all wastes, reducing Firmicutes abundance in animal-derived wastes. Potential biomarkers indicating compost maturation were Proteobacteria and Bacteroidota phyla, Chryseolinea genus and Rhizobiales order. The waste source influenced the final physicochemical attributes, whereas composting enhanced the complexity of the microbial community in the order of poultry litter > filter cake > chicken manure. Therefore, composted wastes, mainly the animal-derived ones, seem to present more sustainable attributes for agricultural use, despite their losses of C, N, and S.

Carbon stability and mitigation of fertilizer induced N2O emissions in soil amended with biochar.

Biochar is a promising tool for an efficient and low environmental impact agriculture since can offer both soil carbon (C) sequestration and mitigation of nitrous oxide (N2O) emissions. The extent of biochar C stability after soil amendment and efficiency in reducing N2O emissions from an external nitrogen (N) source were accessed through laboratory incubations. A clay loam soil was amended with chicken manure (CM), sewage sludge (SS), eucalyptus sawdust (ES) and filter cake (FC) feedstocks and corresponding slow-pyrolysis (400°C) biochars at 5gCkg-1 soil in combination with two N fertilizer rates (0 and 140mgNkg-1 soil). Carbon dioxide (CO2) and N2O emissions were measured during 60days. Biochars and feedstocks CO2 emissions were described by an exponential first order kinetics model. For C mineralization an interaction effect was observed for feedstock source and organic amendment. Lower values of mineralizable C was found for biochars than corresponding feedstocks, except for ES. Carbon losses in 60days of incubation totaled between 0.8 and 9.4% and 2.4 and 32% for biochars and feedstocks, respectively. Regarding to N2O emissions, only CM-biochar impacted emissions with a two-fold increase in non-fertilized soil. When NH4NO3 was co-applied, biochars reduced fertilizer induced N2O emissions, reaching a seven-fold reduction in SS-biochar treatment. The fertilizer emission factor (EF) decreased with biochar amendments as well, varying between 0.01 and 0.08% of the fertilizer N emitted as N2O, which shows the biochar potential to reduce fertilizer induced N2O emissions, with major reduction by SS-biochar mitigating 87% of the soil-fertilizer emissions. Such potential could be explored by designing biochars based on feedstock chemical and structural properties, including a mixed feedstock source biochar that promotes C sequestration and mitigates N2O emissions.

Sewage Sludge Microbial Structures and Relations to Their Sources, Treatments, and Chemical Attributes.

Sewage sludges generation and their disposal have become one of the greatest challenges of the 21st century. They have great microbial diversity that may impact wastewater treatment plant (WWTP) efficiency and soil quality whether used as fertilizers. Therefore, this research aimed to characterize microbial community diversity and structure of 19 sewage sludges from São Paulo, Brazil, as well as to draw their relations to sludge sources [domestic and mixed (domestic+industrial)], biological treatments (redox conditions and liming), and chemical attributes, using molecular biology as a tool. All sludges revealed high bacterial diversity, but their sources and redox operating conditions as well as liming did not consistently affect bacterial community structures. Proteobacteria was the dominant phylum followed by Bacteroidetes and Firmicutes; whereas Clostridium was the dominant genus followed by Treponema, Propionibacterium, Syntrophus, and Desulfobulbus. The sludge samples could be clustered into six groups (C1 to C6) according their microbial structure similarities. Very high pH (≥11.9) was the main sludge attribute segregating C6, that presented very distinct microbial structure from the others. Its most dominant genera were Propionibacterium > > Comamonas > Brevundimonas > Methylobacterium ∼Stenotrophomonas ∼Cloacibacterium. The other clusters' dominant genera were Clostridium > > Treponema > Desulfobulbus ∼Syntrophus. Moreover, high Fe and S were important modulators of microbial structure in certain sludges undertaking anaerobic treatment and having relatively low N-Kj, B, and P contents (C5). However, high N-Kj, B, P, and low Fe and Al contents were typical of domestic, unlimed, and aerobically treated sludges (C1). In general, heavy metals had little impact on microbial community structure of the sludges. However, our sludges shared a common core of 77 bacteria, mostly Clostridium, Treponema, Syntrophus, and Comamonas. They should dictate microbial functioning within WWTPs, except by SS12 and SS13.

Ion leaching and soil solution acidification in a vadose zone under soil treated with sewage sludge for agriculture.

In this study, we performed monitoring of the soil solution (SS) over 10 years on a loamy/clayey-textured Dark Red Dystroferric Oxisol that received sewage sludge for agricultural purposes. The SS was obtained by lysimeters installed along the walls of a well at 1 m, 2 m, 3 m, 4 m and 5 m in depth. The major ions found in the SS were NO3-, SO42-, Cl-, Ca2+, Mg2+, Al3+, Pb2+, Cd2+ and Zn2+, and the pH level ranged from 4 to 6.5 along the profile. Throughout the first three years of monitoring, the pH to a 3-m depth became more acidic, and in the last year, this trend reached 5 m. At the 5-m depth, the pH decreased from 6.5 to 4.5 from the first to the last monitoring. The SS acidification was provoked by both nitrite oxidation and ion leaching. The leaching of H+ or the possible ion exchange/desorption of H+ due to the leached cations (Ca2+ and Mg2+) at the 4-m and 5-m depth caused the pH decrease. The ionic strength (IS) of the solution controlled the ion leaching. The sludge application increased the IS to 3 m, increasing the density of the soil charges and its ability to absorb ions. After the sludge application was completed, there was a decrease in IS of the SS as well as a decrease in ion absorption and retention abilities, which promoted leaching to greater depths. During the entire monitoring process, NO3-, Cd and Pb remained above the potability limit.

A Statistical Review of Alternative Zinc and Copper Extraction from Mineral Fertilizers and Industrial By-Products.

Rapid, accurate, and low-cost alternative analytical methods for micronutrient quantification in fertilizers are fundamental in QC. The purpose of this study was to evaluate whether zinc (Zn) and copper (Cu) content in mineral fertilizers and industrial by-products determined by the alternative methods USEPA 3051a, 10% HCl, and 10% H2SO4 are statistically equivalent to the standard method, consisting of hot-plate digestion using concentrated HCl. The commercially marketed Zn and Cu sources in Brazil consisted of oxides, carbonate, and sulfate fertilizers and by-products consisting of galvanizing ash, galvanizing sludge, brass ash, and brass or scrap slag. The contents of sources ranged from 15 to 82% and 10 to 45%, respectively, for Zn and Cu. The Zn and Cu contents refer to the variation of the elements found in the different sources evaluated with the concentrated HCl method as shown in Table 1. A protocol based on the following criteria was used for the statistical analysis assessment of the methods: F-test modified by Graybill, t-test for the mean error, and linear correlation coefficient analysis. In terms of equivalents, 10% HCl extraction was equivalent to the standard method for Zn, and the results of the USEPA 3051a and 10% HCl methods indicated that these methods were equivalents for Cu. Therefore, these methods can be considered viable alternatives to the standard method of determination for Cu and Zn in mineral fertilizers and industrial by-products in future research for their complete validation.

PLS regression using real sample calibration for aluminum and iron determination in plant extracts.

Real samples were used for PLS model calibration and validation steps, showing that this approach can be of value in preventing deviations in the results caused by the matrix effects for the simultaneous spectrophotometric determination of aluminum and iron in plant extracts. One hundred UV-vis spectra, obtained from samples of the 1997 to 2000 International Plant-Analytical Exchange (IPE) program (The Netherlands), were used for model development, with ICP-AES aluminum and iron determinations as reference values for model calculation. The plant extracts were analyzed both by ICP-AES and by the PLS models developed in this work, using calibrations with both aqueous standard solutions and with real sample extracts. In addition, since the use of smaller calibration sets could be of value in reducing both the cost and the time of analysis, sets with fewer calibration samples were also investigated, with the help of the Kennard and Stone algorithm for sample selection. Comparison of the predictability of the best model obtained with each calibration set was made using the ratio of their relative root mean square error (%RMSEV) for samples in the validation set, for aluminum or iron determinations, and were compared against F-test tabulated values. For all the models developed with real samples, the differences in the %RMSEV values for the aluminum or iron determinations were found not to be statistically significant, at a confidence level of 95%. Although it was observed that the aluminum, but not the iron, determinations with the PLS 2 model prepared with aqueous standards tend to be slightly lower than the ICP-AES determinations, this model has a good global prediction ability, as observed through the correlation curves presented, and can be used for screening determinations or for other agricultural purposes.