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Despite the large quantities of secondary materials flowing within the built environment, their actual volume and respective waste management processes are not accurately known and recorded. Consequently, various sustainability and material efficiency policies are not supported by accurate data and information-reporting associated with secondary materials’ availability and sourcing. Many recent studies have shown that the integration of digital technologies such as city information management (CIM), building information modeling (BIM), and blockchain have the potential to enhance construction waste management (CWM) by classifying recycled materials and creating value from waste. However, there is insufficient guidance to address the challenges during the process of CWM. Therefore, the research reported in this paper aims to develop a blockchain-enhanced construction waste information management conceptual framework (BeCW). This paper is the first attempt to apply the strengths of integrated information-management modeling with blockchain to optimize the process of CWM, which includes a WasteChain for providing a unified and trustworthy credit system for evaluating construction-waste-recyclability to stakeholders. This is enabled through the use of blockchain and self-executing smart contracts to clarify the responsibility and ownership of the relevant stakeholders. As a result, this study provides a unified and explicit framework for referencing which quantifies the value-contribution of stakeholders to waste-recovery and the optimization of secondary construction materials for reuse and recycling. It also addresses the issue of sustainable CWM through information exchange at four levels: user, application, service, and infrastructure data levels.

A variety of pipelines are distributed under urban roads. The upgrading of pipelines is bound to occupy certain road resources, compress the driving space of motor vehicles for a long time, aggravate the traffic congestion in the construction section, and then affect the traffic operation of the whole region. A reasonable layout of traffic signs for inducement to guide the traffic flow in the area where the construction section is located is conducive to promoting a balanced distribution of traffic flow in the regional road network, so as to achieve the reduction of automobile exhaust emissions and the sustainable development of traffic. In this paper, the layout optimization method of regional traffic signs for inducement is proposed. Taking the maximum amount of guidance information that the regional traffic signs can provide as the objective function, and taking the traffic volume, the characteristics of intersection nodes and the standard deviation of road saturation as the independent variables, the layout optimization model of guidance facilities is constructed, which can optimize the layout of traffic guidance signs in the area affected by the construction section, and achieve the goal that the minimum number of facilities can provide the maximum amount of guidance information. The results of the case study show that among the 64 alternative locations where traffic guidance signs can be set in the study area, eight optimal locations are finally determined as the setting points of guidance facilities through this model, and the effective increment of guidance information is the largest at this time. The model proposed in this paper can be used for reference to promote the sustainable development of traffic in the area where the construction section is located.

Global mitigation pathways play a critical role in informing climate policies and targets that are in line with international climate goals. However, it is not possible to directly compare modelled results with national inventories used to assess progress under the UNFCCC due to differences in how land-based fluxes are accounted for.National inventories consider carbon flux on managed land using an area-based approach with managed land-areas determined by nations. Emissions scenarios consider a different managed land area and are calibrated against data from detailed global carbon cycle models that account for natural (indirect) and anthropogenic (direct) fluxes separately by design. To disentangle the direct and indirect components of land-based carbon fluxes, we use a reduced complexity climate model with explicit treatment of the land-use sector, OSCAR, one of the models used by the Global Carbon Project. We find the discrepancy between model and NGHGI-based accounting methods globally to be 4.4 ± 1.0 Gt CO2 yr-1 averaged over the 2000-2020 time period, which is in line with existing estimates. We then apply OSCAR to the set of pathways assessed by the IPCC to quantify how this gap evolves over time and estimate how key mitigation benchmarks change.Across both 1.5°C and 2°C scenarios, LULUCF emissions pathways aligned with NGHGI accounting practices show a strong increase in the total land sink until around mid-century. However, the ‘NGHGI alignment gap’  decreases over this period, converging in the 2050-2060s for 1.5°C scenarios and 2070s-2080s for 2°C scenarios. The convergence is primarily a result of the simulated stabilization and then decrease of the CO2-fertilization effect as well as background climate warming reducing the overall effectiveness of the land sink, which in turn reduces the indirect removals considered by NGHGIs. These dynamics lead to land-based emissions reversing their downward trend in most NGHGI-aligned scenarios by mid-century, and result in the LULUCF sector becoming a net-source of emissions by 2100 in about 25% of both 1.5°C and 2°C scenarios.Assessing emission pathways using LULUCF definitions from national inventory accounting results in downward revisions to emissions benchmarks derived from scenarios. NGHGI-aligned pathways result in earlier net-zero CO2 emissions by around 2-5 years for both 1.5°C and 2°C scenarios, and 2030 emission reductions relative to 2020 are enhanced by about 5 percentage points for both pathway categories. When incorporating the additional land removals considered by NGHGIs, the assessed cumulative net CO2 emissions to global net-zero CO2 also decreases systematically by 15-18% for both 1.5°C and 2°C scenarios.We find that increasing removals from direct fluxes in 1.5C scenarios overtake estimated removals using NGHGI conventions in the near term. However, by midcentury, the strengthening of direct removals is balanced by weakening of indirect removals, meaning that, on average, carbon removal on land accounted for using NGHGI conventions in 1.5C scenarios results in about half of the LULUCF removals in current policy scenarios. We discuss the implications of our results for future Global Stocktakes and market mechanisms under the Paris Agreement.

The deposition of ash - combustion residues - on superheaters and heat exchanger surfaces reduce their efficiency; this phenomenon was investigated for a large-scale waste-to-energy incineration facility. Over a period of six months, ash samples were collected from the plant, which included the bottom ash and deposits from the superheater, as well as flyash from the convective heat exchanger, the economiser and fabric filters. These were analysed for particle size, unburned carbon, elemental composition and surface morphology. Element partitioning was evident in the different combustion residues, as volatile metals, such as cadmium, antimony and arsenic, were found to be depleted in the bottom ash by the high combustion temperatures (1000+°C) and concentrated/enriched in the fabric filter ash (transferred by evaporation). Non-volatile elements by contrast were distributed equally in all locations (transported by particle entrainment). The heat exchanger deposits and fabric filter ash had elevated levels of alkali metals. 82% of flyash particles from the fabric filter were in the submicron range.

This paper analyses the impact of postponing global mitigation action on abatement costs and energy systems changes in China and India. It compares energy-system changes and mitigation costs from a global and two national energy-system models under two global emission pathways with medium likelihood of meeting the 2 °C target: a least-cost pathway and a pathway that postpones ambitious mitigation action, starting from the Copenhagen Accord pledges. Both pathways have similar 2010–2050 cumulative greenhouse gas emissions. The analysis shows that postponing mitigation action increases the lock-in in less energy efficient technologies and results in much higher cumulative mitigation costs. The models agree that carbon capture and storage (CCS) and nuclear energy are important mitigation technologies, while the shares of biofuels and other renewables vary largely over the models. Differences between India and China with respect to the timing of emission reductions and the choice of mitigation measures relate to differences in projections of rapid economic change, capital stock turnover and technological development. Furthermore, depending on the way it is implemented, climate policy could increase indoor air pollution, but it is likely to provide synergies for energy security. These relations should be taken into account when designing national climate policies.

This paper provides an initial analysis of the EU ETS based on the installation-level data for verified emissions and allowance allocations in the first trading year. Those data, released on May 15, 2006, and subsequent updates revealed that CO2 emissions were about 4% lower than the allocated allowances. The main objective of the paper is to shed light on the extent to which over-allocation and abatement have taken place in 2005. We propose a measure by which over-allocation can be judged and provide estimates of abatement based on emissions data and indicators of economic activity as well as trends in energy and carbon intensity. Finally, we discuss the insights and implications that emerge from this tentative assessment.

Resource-use efficiency and crop yield are significant factors in the management of agricultural greenhouse. Appropriate modeling methods effectively improve the control performance and efficiency of the greenhouse system and are conducive to the design of water and energy-saving strategies. Meanwhile, the extreme environment could be forecasted in advance, which reduces pests and diseases as well as provides high-quality food. Accordingly, the interest of the scientific community in greenhouse modeling and optimizing has grown considerably. The objective of this work is to provide guidance and insight into the topic by reviewing 73 representative articles and to further support cleaner and sustainable crop production. Compared to the existing literature review, this work details the approaches to improve the greenhouse model in the aspects of parameter identification, structure and process optimization, and multi-model integration to better model complex greenhouse system. Furthermore, a statistical study has been carried out to summarize popular technology and future trends. It was found that dynamic and neural network techniques are most commonly used to establish the greenhouse model and the heuristic algorithm is popular to improve the accuracy and generalization ability of the model. Notably, deep learning, the combination of “knowledge” and “data”, and coupling between the greenhouse system elements have been considered as future valuable development.

Ambitious international targets are being developed to protect and restore biodiversity under the Convention on Biological Diversity's post-2020 Global Biodiversity Framework and the European Union's Green Deal. Yet, the land system consequences of meeting such targets are unclear, as multiple pathways may be able to deliver on the set targets. This paper introduces a novel scenario approach assessing the plural implementations of these targets. The Nature Futures Framework (NFF) developed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services aims to illustrate the different, positive ways in which society can value nature. It therefore offers a lens through which the spatial implementation of sustainability targets may be envisioned. We used CLUMondo, a spatially explicit model, to simulate plural land system scenarios for Europe for 2050. The model builds on current land system representations of Europe and explores how and where sustainability targets can be implemented under projected population trends and commodity demands. We created three different scenarios in which the sustainability targets are met, each representing an alternative, normative view on nature as represented by the NFF, favoring land systems providing strong climate regulation (Nature for Society), species conservation (Nature for Nature), or agricultural heritage features (Nature as Culture). Our results show that, irrespective of the NFF view, meeting sustainability targets will require European land systems to drastically change, as natural grasslands and forests are forecast to expand while productive areas are projected to undergo a dual intensification and diversification trajectory. Despite each NFF perspective showcasing a similar direction of change, 20% of Europe's land area will differ based on the adopted NFF perspective, with hotspots of disagreement identified in eastern and western Europe. These simulations go beyond existing scenario approaches by not only depicting broad societal developments for Europe, but also by quantifying the land system synergies and trade-offs associated with alternative, archetypal, interpretations and values of how nature may be managed for sustainability. This quantification exemplifies a means towards constructive dialogue, on the one hand by acknowledging areas of contention, and bringing such issues to the fore, and on the other by highlighting points of convergence in a vision for a sustainable Europe.