ROOTS - Circular policies for changing the biowaste system.

The circular economy has a huge potential to make our societies more sustainable and decarbonised, with a reduced impact on the planet's resources. The deployment of innovative solutions in the field of urban biowaste valorisation and reuse is still hindered by numerous bottlenecks, such as technological readiness, funding and financing tools availability, quality and quantity of biowaste and regulatory barriers. The European Green Deal and associated legislative initiatives provide the opportunity to overcome the last ones. To promote innovative solutions for the European circular bioeconomy and help to overcome the barriers for the deployment of a circular bioeconomy, five Horizon 2020 projects working on biowaste valorisation have teamed up. This joint initiative is named ROOTS - circulaR pOlicies for changing the biOwasTe System. The projects HOOP, VALUEWASTE, SCALIBUR, WaysTUP! and CITYLOOPS are piloting new solutions to transform urban biowaste (food waste and green waste) and wastewater into valuable products like feed, fertilisers, bioplastics, biopesticides, proteins and bioethanol. They use different processes and technologies, but they all rely on high levels of recycling/upcycling and propose valorisation solutions relevant to the uptake of a truly circular bioeconomy. As a result of the work performed and experience acquired, a number of bottlenecks have been identified, on the following topics: biowaste prevention, recycling targets and treatment plants, waste and by-products, biopesticides, insects for animal feed, single cell protein, citizen behaviour, investment needs. For each identified bottleneck, this open letter proposes specifically 1) policy recommendations for each level of governance, and 2) information about solutions, good practices and concrete experiences from the participating projects.

The use of mid-infrared diffuse reflectance spectroscopy for acid sulfate soil analysis.

Good management of sulfide minerals and sulfuric acid in Acid Sulfate Soils (ASS) requires cost-effective rapid analytical data for their characterisation. However, the determination of properties in ASS samples using traditional laboratory techniques is expensive and time consuming. Excessive delays in analysis risks sample changes from oxidation. Mid-infrared (MIR) spectroscopy with multivariate regression offers a quicker and cheaper surrogate. This manuscript reports the prediction of some of the following key soil parameters in ASS characterisation using benchtop (Perkin Elmer) and handheld (ExoScan) diffuse reflectance MIR Fourier transform (DRIFT) spectrometers: Total Organic Carbon (TOC), Titratable Actual Acidity (TAA), Extractable Sulfate Sulfur (ESS), Reduced Inorganic Sulfur (RIS), Retained Acidity (RA), Acid Neutralising Capacity (ANC), and Lime Calculation (LC). Three sets of representative ASS soil profiles, comprising 132 samples from hyposulfidic, hypersulfidic and sulfuric materials, and covering a wide range of environments in South Australia were scanned under laboratory conditions. These were combined with reference laboratory data in partial least squares regression (PLSR) calibration models. The calibrations were validated by leave-one-out cross validation, with a further test set available for validation. Predictions with coefficient of determination (R2) > 0.75, were obtained for TOC (0.95), TAA (0.88), RIS (0.86), LC (0.76) and ANC (0.76), but models for ESS (0.66) and RA (0.41) were less satisfactory. The handheld spectrometer performed similarly to the benchtop spectrometer in terms of PLSR prediction accuracies with the potential for in-field sampling. Results thus confirmed the possibility of using MIR spectroscopy for the rapid and cost-effective characterisation of ASS.

Evaluation of strategies for mitigating risks associated with metals in pyrite ash.

The main objective was to evaluate and optimise strategies for the immobilisation or mobilisation of Cd, Cu, Cr, Ni, Pb, and Zn from pyrite ash. Alkaline amendments were used for the immobilisation test: cement, sandstone, marl, marble waste and calcareous crust. The amendments were mixed with pyrite ash at a 1:2 rate, incubated for 28 days, and leachates analysed at the beginning of the experiment (day 0) and after 2, 7, 14 and 28 days. The mobilisation experiment tested metal release from pyrite ash by four concentrations of H2SO4 (0.25 M, 0.5 M, 1 M and 2 M) and contact times (60, 120, 180 and 240 min). Results for the immobilisation/mobilisation tests for Cr and Ni are not presented due to the low concentration in pyrite ash. In the immobilisation test, optimum results across metals and amendments were obtained after two days with percentages of retention being about 90% compared to leachates from pyrite ash only. The release success (in % of total content) using sulphuric acid followed the order: Cd (75%) > Zn (62%) > Cu (37%) > Pb (7%). The concentration of acid was more important than contact time (release enhanced at higher concentrations) except for Zn. The two strategies tested were successful to reduce the risk posed by metals. In terms of optimization, all alkaline materials showed high efficiency for metal retention after a short contact time; for mobilisation, treatment with sulphuric acid at high concentration (up to 2 M tested) resulted to be the optimum with contact time having limited influence.

Assessment of cyanide contamination in soils with a handheld mid-infrared spectrometer.

We examined the feasibility of using handheld mid-infrared (MIR) Fourier-Transform infrared (FT-IR) instrumentation for detecting and analysing cyanide (CN) contamination in field contaminated soils. Cyanide spiking experiments were first carried out, in the laboratory, to test the sensitivity of infrared Fourier transform (DRIFT) spectrometry to ferro- and ferricyanide compounds across a range of reference soils and minerals. Both benchtop and handheld diffuse reflectance infrared spectrometers were tested. Excellent results were obtained for the reference soils and minerals, with the MIR outperforming the near-infrared (NIR) range. Spectral peaks characteristic of the -C≡N group were observed near 2062 and 2118cm-1 in the MIR region for the ferro- and ferricyanide compounds spiked into soils/minerals, respectively. In the NIR region such peaks were observed near 4134 and 4220cm-1. Cyanide-contaminated samples were then collected in the field and analyzed with the two spectrometers to further test the applicability of the DRIFT technique for soils containing aged CN residues. The prediction of total CN in dry and ground contaminated soils using the handheld MIR instrument resulted in a coefficient of determination (R2) of 0.88-0.98 and root mean square error of the cross-validation (RMSE) of 21-49mgkg-1 for a CN range of 0-611mgkg-1. A major peak was observed in the MIR at about 2092cm-1 which was attributed to "Prussian Blue" (Fe4[Fe(CN)6]3·xH2O). These results demonstrate the potential of handheld DRIFT instrumentation as a promising alternative to the standard laboratory method to predict CN concentrations in contaminated field soils.

Rapid prediction of total petroleum hydrocarbons in soil using a hand-held mid-infrared field instrument.

This manuscript reports on the performance of a hand-held diffuse reflectance (mid)-infrared Fourier transform (DRIFT) spectrometer for the prediction of total petroleum hydrocarbons (TPH) in three different diesel-contaminated soils. These soils include: a carbonate dominated clay, a kaolinite dominated clay and a loam from Padova Italy, north Western Australia and southern Nigeria, respectively. Soils were analysed for TPH concentration using a standard laboratory methods and scanned in DRIFT mode with the hand-held spectrometer to determine TPH calibration models. Successful partial least square regression (PLSR) predictions, with coefficient of determination (R(2)) ~0.99 and root mean square error (RMSE) <200mg/kg, were obtained for the low range TPH concentrations of 0 to ~3,000mg/kg. These predictions were carried out using a set of independent samples for each soil type. Prediction models were also tested for the full concentration range (0-60,000mg/kg) for each soil type model with R(2) and RMSE values of ~0.99 and <1,255mg/kg, respectively. Furthermore, a number of intermediate concentration range models were also generated for each soil type with similar R(2) values of ~0.99 and RMSE values <800mg/kg. This study shows the capability of using a portable mid-infrared (MIR) DRIFT spectrometer for predicting TPH in a variety of soil types and the potential for being a rapid in-field screening method for TPH concentration levels at common regulatory thresholds. A novel hand-held mid-infrared instrument can accurately detect TPH across different soil types and concentrations, which paves the way for a variety of applications in the field.

GEMAS: prediction of solid-solution partitioning coefficients (Kd) for cationic metals in soils using mid-infrared diffuse reflectance spectroscopy.

Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra, were used to predict distribution coefficient (Kd) values for selected added soluble metal cations (Ag(+), Co(2+), Cu(2+), Mn(2+), Ni(2+), Pb(2+), Sn(4+), and Zn(2+)) in 4813 soils of the Geochemical Mapping of Agricultural Soils (GEMAS) program. For the development of the PLSR models, approximately 500 representative soils were selected based on the spectra, and Kd values were determined using a single-point soluble metal or radioactive isotope spike. The optimum models, using a combination of MIR-DRIFT spectra and soil pH, resulted in good predictions for log Kd+1 for Co, Mn, Ni, Pb, and Zn (R(2) ≥ 0.83) but poor predictions for Ag, Cu, and Sn (R(2) < 0.50). These models were applied to the prediction of log Kd+1 values in the remaining 4313 unknown soils. The PLSR models provide a rapid and inexpensive tool to assess the mobility and potential availability of selected metallic cations in European soils. Further model development and validation will be needed to enable the prediction of log K(d+1) values in soils worldwide with different soil types and properties not covered in the existing model.

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2) = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2) = 0.62-0.79), compared with those from PSLR-DRIFT (R(2) = 0.61-0.72) and MLR (R(2) = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration.