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Climate change, environmental degradation, and limited resources are motivations for sustainable forest management. Forests, the most abundant renewable resource on earth, used to make a wide variety of forest-based products for human consumption. To provide a scientific measure of a product’s sustainability and environmental performance, the life cycle assessment (LCA) method is used. This article provides a comprehensive review of environmental performances of forest-based products including traditional building products, emerging (mass-timber) building products and nanomaterials using attributional LCA. Across the supply chain, the product manufacturing life-cycle stage tends to have the largest environmental impacts. However, forest management activities and logistics tend to have the greatest economic impact. In addition, environmental trade-offs exist when regulating emissions as indicated by the latest traditional wood building product LCAs. Interpretation of these LCA results can guide new product development using biomaterials, future (mass) building systems and policy-making on mitigating climate change. Key challenges include handling of uncertainties in the supply chain and complex interactions of environment, material conversion, resource use for product production and quantifying the emissions released.

Understanding the system of connections between societal contexts and policy outcomes in municipal governments provides important insights into how community sustainability happens, and why it happens differently in various communities. A growing body of research in recent years has focused on understanding the socio-economic characteristics of communities and cities that are recognized as policy leaders in sustainability. In this paper, we expand the focus beyond the leaders in sustainability as we apply a selection of socio-demographic influences of community sustainability to a large sample of U.S. communities using community classification analytics to identity a range of community types and levels of engagement with sustainability. Our typology presents an integrated and comprehensive perspective on the structure of community sustainability in the United States, highlighting key points of comparison between human capital factors such as population size and density, affluence, home ownership, and adoption of sustainability policy. The analysis provides new insights not only about community leaders in sustainability, but also communities with the civic and social capacity to do more, and the challenges that may inhibit sustainability efforts in others.

The COVID-19 pandemic has tremendously affected the whole of human society worldwide. Travel patterns have greatly changed due to the increased risk perception and the governmental interventions regarding COVID-19. This study aimed to identify contributing factors to the changes in public and private transportation mode choice behavior in China after COVID-19 based on an online questionnaire survey. In the survey, travel behaviors in three periods were studied: before the outbreak (before 27 December 2019), the peak (from 20 January to 17 March 2020), and after the peak (from 18 March to the date of the survey). A series of random-parameter bivariate Probit models was developed to quantify the relationship between individual characteristics and the changes in travel mode choice. The key findings indicated that individual sociodemographic characteristics (e.g., gender, age, ownership, occupation, residence) have significant effects on the changes in mode choice behavior. Other key findings included (1) a higher propensity to use a taxi after the peak compared to urban public transportation (i.e., bus and subway); (2) a significant impact of age on the switch from public transit to private car and two-wheelers; (3) more obvious changes in private car and public transportation modes in more developed cities. The findings from this study are expected to be useful for establishing partial and resilient policies and ensuring sustainable mobility and travel equality in the post-pandemic era.

To effectively address the sustainability crises our planet faces, decision-makers at different levels of government worldwide will have to get a handle on three key challenges: learning from Global North and South initiatives in tandem, taking stock of social innovations alongside technological fixes, and nurturing grassroots sustainable development initiatives next to, or in place of, top-down corporate and government interventions. Current scientific literature and grant-making institutions have often reinforced the compartmentalized fashion in which we learn and draw policy lessons from North/South, social/technical, and bottom-up/top-down sustainability initiatives, including local food system innovations. The strategic levers for global sustainable development lying in-between are thus left out. This paper uses exploratory, multiple case study analysis to address this omission. By concurrently drawing lessons from grassroots innovations in Brazil, New York, and Senegal—three profoundly different socioeconomic and geographic contexts—we identify common pressure points that have enabled local communities to drive system-wide transformations toward climate adaptation, resilience, and sustainability in the agri-food system. The findings of this paper would be of value to scholars, government officials, and community groups engaged in agri-food systems sustainability and interested in the processes of change that have allowed budding innovations to stabilize and scale up.

The objectives of this study are to: estimate African countries’ Government Openness Index (AGOI) to see the updated progress of open government in those countries, examine which areas African countries should further improve for sustainable development, and compare the performance of the Open Government Partnership (OGP) member countries to that of non-OGP countries in forming AGOI. This study developed the AGOI with 32 selected countries and four factors (ACC (accountability), TRA (transparency), CPF (citizen participation and freedom) and ICT (information and communication technology)) for the period of 2006–2019. The results show that African countries have continuously increased the values of AGOI for the period. ACC has barely changed, but TRA has increased slightly. Both CPF and ICT have increased at higher growth rates during the period. The OGP group reached much better scores than their non-OGP counterparts, with positive differences in AGOI, ICT, CPF, and TRA, except ACC. The results of this study suggest that the constantly increasing CPF and ICT levels in countries that have similar conditions as African countries should be further improved to function well enough to build accountability and transparency. It is also recommended that countries join the OGP in order to move towards improving government openness and creating sustainable development.

In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers.

Due to their unique nature, construction projects are considered one of the world’s most hazardous and incident-prone industrial sectors. The present study aimed to analyze health, safety and environmental (HSE) risks relating to construction projects based on the project management body of knowledge (PMBOK) and sustainability approach. This study was conducted with the participation of 30 experts, using the semi-quantitative risk assessment technique, in nine areas of the project management’s body of knowledge, based on the fuzzy analytic hierarchy process. Risk, in this study, was estimated using a two-dimensional matrix of incident probability and severity, each of which has four sub-parameters. The HSE risks pertaining to each of the nine areas of PMBOK were identified. After that, the two dimensions of risk, including incident probability and severity, were measured. Thirty-seven risk sources associated with nine areas of the PMBOK were identified. Risk analysis revealed that 20 sources were at an unacceptable risk level, and 17 risks were at a tolerable risk level. Identifying HSE-related risk sources in accordance with the nine areas of PMBOK, and using FAHP to assess the risk of these hazards in construction projects, can lead to a more realistic estimate of risk in construction projects. The presented method in the current study can create a novel perspective in terms of the construction industry’s risk management and assessment.

This study explores the impact of oil depletion on the energetic efficiency of oil extraction and refining in California. These changes are measured using energy return ratios (such as the energy return on investment, or EROI). I construct a time-varying first-order process model of energy inputs and outputs of oil extraction. The model includes factors such as oil quality, reservoir depth, enhanced recovery techniques, and water cut. This model is populated with historical data for 306 California oil fields over a 50 year period. The model focuses on the effects of resource quality decline, while technical efficiencies are modeled simply. Results indicate that the energy intensity of oil extraction in California increased significantly from 1955 to 2005. This resulted in a decline in the life-cycle EROI from 6.5 to 3.5 (measured as megajoules (MJ) delivered to final consumers per MJ primary energy invested in energy extraction, transport, and refining). Most of this decline in energy returns is due to increasing need for steam-based thermal enhanced oil recovery, with secondary effects due to conventional resource depletion (e.g., increased water cut).