A data-driven analysis of HDPE post-consumer recyclate for sustainable bottle packaging

The packaging industry faces mounting demand to integrate post-consumer recyclate (PCR). However, the complex structure-property relationships of PCRs often obscure their performance compared to virgin equivalents, posing challenges in selecting suitable PCRs for applications. Focused on extrusion blow moulding grade high-density polyethylene (HDPE), this study presents the most extensive characterisation of HDPE PCR to date, encompassing 23 resins (3 virgin, 20 PCR). Employing Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), rheology, colour analysis, and mechanical testing, we established a feature-rich dataset with 56 distinctive characteristics. Utilising a data science approach based on principal component analysis, with the virgin samples as a benchmark, we identified that combining FTIR, TGA and mechanical testing provided effective identification of PCRs that closely match the properties of virgin HDPE. The pipeline created can be utilised for new PCRs to determine suitability as a replacement for virgin plastic in a desired application

Assessing Model Predictions of Carbon Dynamics in Global Drylands

Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO$_2$ enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle

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Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites

This is the final version. Available on open access from IOP Publishing via the DOI in this recordData availability statement The data and code that support the findings of this study are openly available at the following URL: (https://github.com/jakobjassmann/qhi_phen_ts).Data across scales are required to monitor ecosystem responses to rapid warming in the Arctic and to interpret tundra greening trends. Here, we tested the correspondence among satellite- and drone-derived seasonal change in tundra greenness to identify optimal spatial scales for vegetation monitoring on Qikiqtaruk - Herschel Island in the Yukon Territory, Canada. We combined time-series of the Normalised Difference Vegetation Index (NDVI) from multispectral drone imagery and satellite data (Sentinel-2, Landsat 8 and MODIS) with ground-based observations for two growing seasons (2016 and 2017). We found high cross-season correspondence in plot mean greenness (drone-satellite Spearman's ρ 0.67-0.87) and pixel-by-pixel greenness (drone-satellite R 2 0.58-0.69) for eight one-hectare plots, with drones capturing lower NDVI values relative to the satellites. We identified a plateau in the spatial variation of tundra greenness at distances of around half a metre in the plots, suggesting that these grain sizes are optimal for monitoring such variation in the two most common vegetation types on the island. We further observed a notable loss of seasonal variation in the spatial heterogeneity of landscape greenness (46.2%-63.9%) when aggregating from ultra-fine-grain drone pixels (approx. 0.05 m) to the size of medium-grain satellite pixels (10-30 m). Finally, seasonal changes in drone-derived greenness were highly correlated with measurements of leaf-growth in the ground-validation plots (mean Spearman's ρ 0.70). These findings indicate that multispectral drone measurements can capture temporal plant growth dynamics across tundra landscapes. Overall, our results demonstrate that novel technologies such as drone platforms and compact multispectral sensors allow us to study ecological systems at previously inaccessible scales and fill gaps in our understanding of tundra ecosystem processes. Capturing fine-scale variation across tundra landscapes will improve predictions of the ecological impacts and climate feedbacks of environmental change in the Arctic.Natural Environment Research Council (NERC)National Geographic SocietyParrot Climate Innovation GrantAarhus University Research FoundationEuropean Union Horizon 202

Durability of CaO–CaZrO₃ Sorbents for High-Temperature CO₂ Capture Prepared by a Wet Chemical Method

Powders of CaO sorbent modified with CaZrO₃ have been synthesized by a wet chemical route. For carbonation and calcination conditions relevant to sorbent-enhanced steam reforming applications, a powder of composition 10 wt % CaZrO₃/90 wt % CaO showed an initial rise in CO₂ uptake capacity in the first 10 carbonation–decarbonation cycles, increasing from 0.31 g of CO₂/g of sorbent in cycle 1 to 0.37 g of CO₂/g of sorbent in cycle 10 and stabilizing at this value for the remainder of the 30 cycles tested, with carbonation at 650 °C in 15% CO₂ and calcination at 800 °C in air. Under more severe conditions of calcination at 950 °C in 100% CO₂, following carbonation at 650 °C in 100% CO₂, the best overall performance was for a sorbent with 30 wt % CaZrO₃/70 wt % CaO (the highest Zr ratio studied), with an initial uptake of 0.36 g of CO₂/g of sorbent, decreasing to 0.31 g of CO₂/g of sorbent at the 30th cycle. Electron microscopy revealed that CaZrO₃ was present in the form of ≤0.5 μm cuboid and 20–80 nm particles dispersed within a porous matrix of CaO/CaCO₃; the nanoparticles are considered to be the principal reason for promoting multicycle durability

Assessing Model Predictions of Carbon Dynamics in Global Drylands

International audienceevidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle

Simulating the long-term impacts of drainage and restoration on the ecohydrology of peatlands

Drainage alters the carbon storage and accumulation functions of peatlands, but the long-term effects of drainage ditches, and their restoration, on peatland development are poorly understood. Timescales of monitoring studies in ditch-drained and restored peatlands are typically limited to a few years, and occasionally decades. In addition, experimental studies seldom monitor spatial changes in peat structure caused by ditches, despite such changes affecting water flow and water retention in peat. Ecosystem models offer an alternative to experimental studies and can help explain how complex systems such as peatlands may respond to external disturbances. Here we report on a 2D application of a peatland development model (DigiBog) to explore how contour-parallel ditches, and their damming, affect the ecohydrology of peatlands over decades to centuries, using blanket peatlands as a case study. Drainage resulted in the rapid loss of peat due to increased oxic decay. The majority of these losses occurred in the first 100 years after the ditch was created, but water table dynamics were altered even centuries later. Restoration halted the loss of peat and encouraged net peat accumulation, although the amount lost in 100 years of drainage had not been replaced 200 years after the ditch was dammed. Restoration of ditches in sloping peatlands brought about more peat regrowth downslope of the restored ditch than further upslope. Our study demonstrates the potential for spatially-distributed, ecosystem-scale models as tools to explore complex spatiotemporal responses to disturbance, and to support land managers in making decisions about peatland drainage and restoration

Durability of CaO–CaZrO₃ Sorbents for High-Temperature CO₂ Capture Prepared by a Wet Chemical Method

Powders of CaO sorbent modified with CaZrO have been synthesized by a wet chemical route. For carbonation and calcination conditions relevant to sorbent-enhanced steam reforming applications, a powder of composition 10 wt % CaZrO/90 wt % CaO showed an initial rise in CO uptake capacity in the first 10 carbonation-decarbonation cycles, increasing from 0.31 g of CO/g of sorbent in cycle 1 to 0.37 g of CO/g of sorbent in cycle 10 and stabilizing at this value for the remainder of the 30 cycles tested, with carbonation at 650 C in 15% CO and calcination at 800 C in air. Under more severe conditions of calcination at 950 C in 100% CO, following carbonation at 650 C in 100% CO, the best overall performance was for a sorbent with 30 wt % CaZrO/70 wt % CaO (the highest Zr ratio studied), with an initial uptake of 0.36 g of CO/g of sorbent, decreasing to 0.31 g of CO /g of sorbent at the 30th cycle. Electron microscopy revealed that CaZrO was present in the form of ≤0.5 μm cuboid and 20-80 nm particles dispersed within a porous matrix of CaO/CaCO; the nanoparticles are considered to be the principal reason for promoting multicycle durability

Hydrological hotspots in blanket peatlands: Spatial variation in peat permeability around a natural soil pipe

Measurements were made of the hydraulic conductivity (K) of peat around a natural soil pipe in a blanket bog. This is the first investigation of decimeter-scale variability in both vertical K and horizontal K in blanket peats, which were found to be higher than indicated by previous research. This information suggests that it may be appropriate to reconsider (I) the spatial sampling strategies employed to investigate subsurface flow in blanket peatlands, and (II) how field data are used to parameterize flow models. Critically, there was spatial structure in the heterogeneity, with a wedge of high-K peat directly above the pipe forming a hydrological conduit between near-surface peat and the perennially flowing pipe. There was also significantly greater horizontal K parallel to the pipe's orientation compared with horizontal K perpendicular to the pipe. Determinations of the triaxial anisotropy of K, undertaken for the first time in peat soils, revealed substantial directional variations in K. The K around the pipe-peat interface was investigated; however, sample length dependency of K for peat samples precluded the investigation of a hypothesized low-K skin around the pipe