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Simple Summary: Crop switching is an important climate change adaptation strategy. New crops may need to be cultivated to provide food security as traditional staple crops become less suited to the changing climate in the bread baskets of many countries. For example, potato farming in the Philippines is being scaled up to supplement the cultivation of rice to meet the needs of a growing population. Since new crops introduced for this purpose can also be vulnerable to invasive pests, it is necessary to develop methods for planning pest management strategies that consider the complex interactions that can occur in farm ecosystems. In this paper, we develop a graph theoretic model for assessing pest management options for the prospective case of the entry of the Colorado potato beetle in potato farms in the Philippines. Two biological control agents and use of chemical pesticides are considered as alternative strategies. The model results indicate that the biological control strategies outperform the use of chemical pesticides. The concurrent use of both biological control agents could be less effective due to competition between the two species. Crop shifting is considered as an important strategy to secure future food supply in the face of climate change. However, use of this adaptation strategy needs to consider the risk posed by changes in the geographic range of pests that feed on selected crops. Failure to account for this threat can lead to disastrous results. Models can be used to give insights on how best to manage these risks. In this paper, the socioecological process graph technique is used to develop a network model of interactions among crops, invasive pests, and biological control agents. The model is applied to a prospective analysis of the potential entry of the Colorado potato beetle into the Philippines just as efforts are being made to scale up potato cultivation as a food security measure. The modeling scenarios indicate the existence of alternative viable pest control strategies based on the use of biological control agents. Insights drawn from the model can be used as the basis to ecologically engineer agricultural systems that are resistant to pests. [ABSTRACT FROM AUTHOR]

Critical infrastructure systems are essential in sustaining people's livelihoods and the operation of economic sectors. In this paper, we extend the dynamic inoperability IO model (DIIM), we evaluate the resilience of economic sectors given the initial functionality loss and recovery time of an infrastructure. The resulting model is applied in a case study of the 2020 eruption of Taal Volcano in the Philippines. The initial inoperability and recovery period parameters are used in the 14-sector DIIM. The dynamic recovery behaviors of the sectors are plotted over the disaster timeline based on two metrics: (1) economic loss, which is the monetary value of the damage; and (2) inoperability, which is the dimensionless loss relative to the total production output of each sector. The DIIM template and case study results from this paper can provide policy insights to enhance disaster resilience planning for future disasters. [ABSTRACT FROM AUTHOR]

Centralised wastewater systems are considered as conventional means for wastewater treatment, however, the implementation of large-scale systems and expansion of sewerage networks in developing countries prove to be challenging due to political, social, financial, technical, and environmental factors. Several studies identified decentralised wastewater management (DWM) systems as a promising solution due to its benefits including resource recovery for energy and agricultural applications. The successful implementation of DWM systems in developing countries contributes to the main objective of Sustainable Development Goal (SDG) No. 6 which is to provide basic sanitation access to all. A low carbon society can also be promoted through energy recovery from wastes and reducing energy requirement in the transport and handling of wastewater and sludge. The paper provides an overview of the barriers and potential resource recovery and reuse applications to implement decentralised wastewater management systems in developing countries. The initial review showed that there are existing technologies already used for resource recovery such as anaerobic systems for biogas production, nature-based systems for crop cultivation and water reuse, and mechanised systems like moving bed bioreactors for wastewater treatment and reuse. However, developing countries are faced with several barriers in the planning and implementation of sustainable wastewater management systems. The information from the literature review is used as a guide to determine interventions for key barriers and to draft a policy guidance manual on technology selection for decision-makers in the Philippines. [ABSTRACT FROM AUTHOR]

In this study, we utilize an input–output (I–O) model to perform an ex-post analysis of the COVID-19 pandemic workforce disruptions in the Philippines. Unlike most disasters that debilitate physical infrastructure systems, the impact of disease pandemics like COVID-19 is mostly concentrated on the workforce. Workforce availability was adversely affected by lockdowns as well as by actual illness. The approach in this paper is to use Philippine I–O data for multiple years and generate Dirichlet probability distributions for the Leontief requirements matrix (i.e., the normalized sectoral transactions matrix) to address uncertainties in the parameters. Then, we estimated the workforce dependency ratio based on a literature survey and then computed the resilience index in each economic sector. For example, sectors that depend heavily on the physical presence of their workforce (e.g., construction, agriculture, manufacturing) incur more opportunity losses compared to sectors where workforce can telework (e.g., online retail, education, business process outsourcing). Our study estimated the 50th percentile economic losses in the range of PhP 3.3 trillion (with telework) to PhP 4.8 trillion (without telework), which is consistent with independently published reports. The study provides insights into the direct and indirect economic impacts of workforce disruptions in emerging economies and will contribute to the general domain of disaster risk management. [ABSTRACT FROM AUTHOR]

Multi-region input-output models have been used extensively for describing and analysing the production and trade of goods. However, there have been no prior publications on the use of such models to determine optimal trade benchmarks considering footprint limits. Such benchmarks can provide valuable insights for economic planning, in the same manner that pinch analysis targets provide insights in process integration. In this work, a mixed-integer linear programming input-output model is developed to minimize environmental footprint by adjusting production and trade levels in a cluster of regions or countries with specified final demand constraints. A case study based on a simplified, low-resolution model of the Philippines using land footprint as objective function is solved to illustrate this new approach. [ABSTRACT FROM AUTHOR]

This study deals with the problem of human resources planning due to the additional workforce requirements of research activities. In practice, planning of human resource expansion is seldom done in a systematic manner, thus leading to sub-optimal results. In this work, a P-graph model is developed as a decision support tool to aid in planning expansion of staffing levels for Higher Education Institutions. Many higher education institutions in the developing world are undergoing the transition from being teaching-intensive to becoming increasingly research-oriented. This shift is widely recognized as an important adjustment to the need for universities to play a greater role in creating knowledge capital, which is an essential component to fuel the next phase of growth of developing countries. Research universities are an essential resource for facilitating eco-innovation in industry. New targets that involve increased research output tend to put strain on institutional processes and resources that were previously configured to meet the demands of teaching-intensive organizations. The model formulation is based on an input-output framework that reflects interdependencies among different employee categories. The use of the model is illustrated with a representative case study of a typical Higher Education Institution in the Philippines. • University research fuels eco-innovation in industry. • A P-graph approach to human resource planning in universities is developed. • The model can facilitate increased institutional research intensity. • A representative case study of a typical Philippine university is presented. [ABSTRACT FROM AUTHOR]

Carbon Emissions Pinch Analysis is a variant of Pinch Analysis that was developed for macroscale carbon-constrained energy planning problems. It uses carbon intensity as the measure of quality of energy streams to be allocated within a large-scale system. Since its inception, this method has been applied to various systems at different scales, utilized in different geographic contexts, and also extended to allow different sustainability metrics, such as land and water footprints, to be considered. In this paper, Carbon Emissions Pinch Analysis is further extended by combining it with Input-Output Analysis. This hybrid approach is capable of economy-wide analysis, where the segments of composite curves are comprised of the sectors in an economic system; flow quantities are measures in terms of economic value, while quality is indicated by carbon intensity. After first illustrating this approach to a small pedagogical case study, the methodology is then applied to a case study on the carbon-constrained economic growth of the Philippines. Prospects and limitations of the potential application of this methodology to other cases are also discussed. [ABSTRACT FROM AUTHOR]

The process graph (P-graph) framework was introduced in the early 1990s as a graph theoretic approach to Process Network Synthesis (PNS) problems in chemical engineering. This framework has several advantageous features, such as mathematically rigorous generation of maximal structures (i.e., superstructures), elucidation of combinatorially feasible solution structures, and efficient search of solution space for optimal PNS compared to conventional branch-and-bound algorithms for mixed integer linear programming (MILP) models. In the three decades since its inception, the P-graph framework has proven to be a viable approach to a wide array of PNS and other structurally analogous problems; the methodology has also matured, as evidenced by the development of key software tools (PNS Draw, PNS Studio and P-graph Studio) and its appearance in modern textbooks. Nevertheless, the P-graph framework has yet to achieve broad, mainstream penetration among grassroots chemical engineering users, especially those without a strong mathematical programming background. In this paper, we discuss the implementation of instructional P-graph modules in undergraduate chemical engineering degree programs at the University of Nottingham, Malaysia Campus and De La Salle University, Manila, Philippines. These modules have primarily focused on the design of Green Processes. Results show that the visual nature of the P-graph methodology is an advantage for practical engineering decision-making, and that it complements the learning of mainstream techniques such as mathematical programming. [ABSTRACT FROM AUTHOR]