One of the major environmental threat in the world today is the increased production of plastic and its usage. The inept plastic waste management system with regard to its recycling and energy recovery in the developing countries creates a global threat as a major land and water body pollutant. However, its durability, thermal properties, and chemical resistance make plastics an alternate choice as a building material. This study investigates the use of plastic in concrete mixture with an objective to improve the thermal performance of the building. The shredded plastic fibers from plastic bottles (polyethylene terephthalate, PET) were used as a partial weight replacement (2.5%, 5%, and 7.5%) of coarse aggregate in concrete blocks. The cubes were cast using the Indian standards (IS 456) and the essential tests were performed. Additionally, experiments were designed to investigate the change in the thermal conductivity of the concrete block due to the varying amount of plastic. It was found that the use of PETs affected the compressive strength and also decreased the thermal conductivity of the concrete blocks. The experimental results suggest that PETs can be used in the construction of energy-efficient building to handle the environmental concerns because of its abundance.

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<p>Good scientific practice requires good documentation and traceability of every research step in order to ensure reproducibility and repeatability of our research. However, with increasing data availability and ability to record big data, experiments and data analysis become more complex. This complexity often requires many pre- and post-processing steps that all need to be documented for reproducibility of final results. This poses very different challenges for numerical experiments, laboratory work and field-data analysis. The platform Renku (https://renkulab.io/), developed by the Swiss Data Science Center, aims at facilitating reproducibility and repeatability of all these scientific workflows. Renku stores all data, code and scripts in an online repository, and records in their history how these files are generated, interlinked and modified. The linkages between files (inputs, code and outputs) lead to the so-called <span>knowledge graph, used to record the provenance of results and connecting those with all other relevant entities in the project.</span></p><p>We will discuss here several use examples, including mathematical analysis, laboratory experiments, data analysis and numerical experiments, all related to scientific projects presented separately. Reproducibility of mathematical analysis is facilitated by clear variable definitions and a computer algebra package that enables reproducible symbolic derivations. We will present the use of the Python package ESSM (https://essm.readthedocs.io) for this purpose, and how it can be integrated into a Renku workflow. Reproducibility of laboratory results is facilitated by tracking of experimental conditions for each data record and instrument re-calibration activities, mainly through Jupyter notebooks. Data analysis based on different data sources requires the preservation of links to external datasets and snapshots of the dataset versions imported into the project, that is facilitated by Renku. Renku also takes care of clear links between input, code and output of large numerical experiments, our last use example, and enables systematic updating if any of the input or code files are changed.</p><p>These different examples demonstrate how Renku can assist in documenting the scientific process from input to output and the final paper. All code and data are directly available online, and the recording of the workflows ensures reproducibility and repeatability.</p>

Land surface temperature (LST) is a preeminent state variable that controls the energy and water exchange between the Earth’s surface and the atmosphere. At the landscape-scale, LST is derived from thermal infrared radiance measured using space-borne radiometers. At the plot-scale, the flux tower recorded longwave radiation components are inverted to retrieve LST. Since the down-welling longwave component was not measured routinely until recently, usually only the up-welling longwave component is used for the plot-scale LST retrieval. However, we found that ignoring reflected down-welling longwave radiation for plot-scale LST estimations can lead to substantial error. This also has important implications for estimating the correct surface emissivity using flux tower measurements, which is needed for plot-scale LST retrievals. The present study proposes a new method for plot-scale emissivity and LST estimation and addresses in detail the consequences of omitting down-welling longwave radiation as frequently done in the literature. Our analysis uses ten eddy covariance sites with different land cover types and found that the LST values obtained using both up-welling and down-welling longwave radiation components are 0.5 to 1.5 K lower than estimates using only up-welling longwave radiation. Furthermore, the proposed method helps identify inconsistencies between plot-scale radiometric and aerodynamic measurements, likely due to footprint mismatch between measurement approaches. We also found that such inconsistencies can be removed by slight corrections to the up-welling longwave component and subsequent energy balance closure, resulting in realistic estimates of surface emissivity and consistent relationships between energy fluxes and surface-air temperature differences. Landscape-scale daytime LST obtained from satellite data (MODIS TERRA) was strongly correlated with our plot-scale estimates for most of the sites, but higher by several Kelvin at two sites. We also quantified the uncertainty in estimated LST and surface emissivity using the different methods and found that the proposed method does not result in increased uncertainty. The results of this work have significant implications for the combined use of aerodynamic and radiometric measurements to understand the interactions and feedbacks between LST and surface-atmosphere exchange processes.

<p>The concept of canopy-scale resistances was developed to investigate and evaluate the transfer of momentum, heat and mass from the leaf surface to the canopy air space and to the atmosphere. Therefore, reliable estimates of resistances are of fundamental importance for studying the ecosystem scale fluxes and land-atmosphere interaction. The canopy-scale resistance has two components: the leaf boundary layer resistance and canopy-air-to-atmosphere resistance. In big-leaf conceptualizations, canopy-scale resistances are represented in a single term called aerodynamic resistance, which refers to the resistance between an idealized ‘big-leaf’ and the atmosphere for the transfer of momentum, heat and mass. A decent amount of literature exists on the estimation of aerodynamic resistances for various ecosystems based on the roughness length parametrizations and atmospheric stability correction. Most of these parametrizations do not include the leaf boundary layer explicitly and therefore rely on a conceptual 'aerodynamic temperature' at some distance above the leaf surface. This gap hampers reliable modelling of canopy gas exchange (transpiration and CO2 assimilation) as these processes happen directly at the leaf surface and strongly rely on accurately capturing the leaf surface temperature. To bridge this gap, an additional resistance based on a ‘kB<sup>-1</sup>' parametrization is commonly added to the classical aerodynamic resistance.</p><p> </p><p>The objective of the present study is to estimate the total resistance to heat transfer from the heat exchanging surfaces to the measurement height and to find the most appropriate mathematical formulation for this resistance. We used radiometric and eddy covariance (EC) measurements from a wide range of land cover types and estimated the total resistance to heat transport using measured fluxes and radiometric surface temperatures by inverting the flux-profile equation. We also performed a comprehensive comparison of total resistance estimates with commonly used stability and roughness-based resistance formulations, including ‘KB<sup>-1</sup>' parametrizations and the momentum flux resistance inverted from EC measurements. We found that total resistances were consistently greater than the roughness length-based resistance parametrizations at most of the study sites. We further found that the difference between the total and aerodynamic resistance can be largely explained by dominant leaf sizes at the individual sites.</p><p> </p><p>Based on these results, we propose a consistent canopy resistance formulation by explicitly considering leaf sizes and leaf boundary layer resistances in combination with an adequate representation of aerodynamic canopy-atmosphere resistance. This approach will enable a consistent coupling of the aerodynamic process with physiological leaf-scale processes such as photosynthesis and stomatal control, which depend on and interact with leaf temperature, and aerodynamic stability.</p><p> </p>