Assessment and driving factor of housing vacancies in Shandong Peninsula urban agglomeration based on multi-source remote sensing data.

As the urbanization rate in the world has increased rapidly, the housing vacancy problem has become serious and attracting more attention. Calculating and analyzing vacant housing can help reduce the wasteful use of resources. This paper measures the housing vacancy rate and housing vacancy stock in the Shandong Peninsula urban agglomeration using night-time lighting and land use data. The results show that the average housing vacancy rate in the Shandong Peninsula urban agglomeration rose rapidly from 14.68% in 2000 to 29.71% in 2015 before declining slowly to 29.49% in 2020. Since urban population growth is lower than the housing construction rate, the average annual growth of housing vacancy stock between 2000 and 2020 exceeds 3 million square meters in megacities and is around 1-2 million square meters in large and medium-sized cities. The vacant housing has caused considerable waste of housing resources. The driving factors of the housing vacancy were further analyzed using the LMDI decomposition method. Results indicate that the economic development level is the most significant driving factor of the vacant housing stock. In addition, the value effect of unit floor areas is the major driving factor inhibiting the growth of vacant housing stock, while the decline of unit floor area value is conducive to the reduction of this stock.

Changes in water use and wastewater generation influenced by the COVID-19 pandemic: A case study of China.

This paper examines and projects the water use and wastewater generation during and after the SARS-CoV-2 (COVID-19) in China, and discussed the water use/wastewater generation pattern changes among different sectors. Existing studies on the impact of pandemic spread-prevention measures on water consumption and wastewater treatment during the pandemic are reviewed. The water use and wastewater discharge in China through the COVID-19 period are then projected and analyzed using Multivariate Linear Regression. The projection is carried out for years 2019-2023 and covers an (estimated) full process of pre-pandemic, pandemic outbreak, and recovery phase and provides essential information for determining the complete phase impact of the COVID-19. Two scenarios, i.e. the recovery scenario and the business as usual scenario, are set to investigate the water use and wastewater generation characteristics after the pandemic. The results imply that in both scenarios, the water use in China shows a V-shaped trend from 2019 to 2023 and reached a low point in 2020 of 5,813✕108 m3. The wastewater discharge shows an increasing trend throughout the COVID period in both scenarios. The results are also compared with the water consumption and wastewater generation during the SARS-CoV-1 period. The implication for policymakers is the possible increase of water use and wastewater discharge in the post COVID period and the necessity to ensure the water supply and control of water pollution and wastewater discharge.

Industrial water network vulnerability analysis using dynamic inoperability input-output model.

Industrial parks provide opportunities for Process Integration among different enterprises. Inter-Plant Water Network Integration is an effective strategy for water conservation. However, increased interplant linkages can make the entire system vulnerable to cascading failures in case of loss of water flow in some plants. The potential indirect impact of water shortages on such integrated systems may not be evident without the use of appropriate models. This work defines inoperability as the fractional loss of water flow relative to normal operations. A comparison between the applicability of demand-driven versus supply-driven Inoperability Input-output Model (IIM) is conducted. Then, a Vulnerability Assessment Framework which integrates vulnerability indicators into the Dynamic Input-Output Model (DIIM) is developed to analyse failure propagation in water networks in an industrial park. The DIIM is then applied to simulate the cascading effects of disturbances. From a time perspective, the vulnerabilities of the industrial parks With Integrated Optimal Water Network (WWN) and Without Integrated Optimal Water Network (WOWN) are assessed considering robustness, adaptability, and recoverability as the indicators. The results indicate that supply-driven IIM is more suitable for cascading failure analysis of water networks. The average inoperability at 16% from supply-driven IIM is higher than that from demand-driven IIM. In the freshwater disturbance scenario, the dependence of the plant on freshwater is proportional to the rate of inoperability change, the time to reach a new equilibrium. In this study, the robustness of WWN is about fivefold that of WOWN, but the recovery rate is only one-sixth of the latter. This work can help identify system vulnerabilities and provide a scientific insight for the development of park-wide water management strategies.

Agent-based model for simulation of the sustainability revolution in eco-industrial parks.

Eco-industrial parks (EIPs) are of increasing importance for implementing industrial ecology strategies and are facing increasing challenges in terms of environmental pollution and resource scarcity. As a complex adaptive system, an EIP involves multiple sectors and faces various disturbances that influence its evolutionary trajectories. This study adopts an agent-based model to simulate the material flows and industrial symbiosis process in the EIP, considering the initiative of each company and the ever-changing environment. The proposed EIP model emphasises the heterogeneity of companies and attempts to reflect multiple and dynamic factors that have received less attention in previous studies. This model contains two types of agents, companies and the external environment. A company agent makes decisions and interacts with other agents following its own behaviour rules, while the external environment agent functions to coordinate the material flows and exert influence on the companies. The model has been verified and validated by simulating a 20-year-period development of an empirical EIP in China. The simulation results are assessed by three indicators: eco-connectance, eco-efficiency, and industrial symbiosis indicator. Results showed that during the growing phase, the eco-connectance increased from 0.02 to 0.1 for the non-disturbance situation. The eco-efficiency and industrial symbiosis indicator also realised 78.5% and 74.8% of their total increments. The outcome of this research provides insights for the design of the strategies to improve the industrial symbiosis performance and is of high potential to facilitate EIPs in promoting eco-transformation and sustainable development.

Process assessment, integration and optimisation: The path towards cleaner production.

This contribution starts from the broad perspective of the global material cycles, analysing the main resource and pollution issues world-wide from the viewpoint of the disturbances to these cycles caused by human activities. The issues are analysed in the light of the currently developing COVID-19 pandemic with the resulting behavioural and business pattern changes. It has been revealed in the analysis of previous reviews that there is a need for a more comprehensive analysis of the resource and environmental impact contributions by industrial and urban processes, as well as product supply chains. The review discusses the recent key developments in the areas of Process Integration and Optimisation, the assessment and reduction of process environmental impacts, waste management and integration, green technologies. That is accompanied by a review of the papers in the current Virtual Special Issue of the Journal of Cleaner Production which is dedicated to the extended articles developed on the basis of the papers presented at the 22nd Conference on Process Integration for Energy Saving and Pollution Reduction. The follow-up analysis reveals significant advances in the efficiency and emission cleaning effects of key processes, as well as water/wastewater management and energy storage. The further analysis of the developments identifies several key areas for further research and development - including increases of the safety and robustness of supply networks for products and services, increase of the resources use efficiency of core production and resource conversion processes, as well as the emphasis on improved product and process design for minimising product wastage.