Infrastructure autopoiesis: requisite variety to engage complexity

Infrastructure systems must change to match the growing complexity of the environments they operate in. Yet the models of governance and the core technologies they rely on are structured around models of relative long-term stability that appear increasingly insufficient and even problematic. As the environments in which infrastructure function become more complex, infrastructure systems must adapt to develop a repertoire of responses sufficient to respond to the increasing variety of conditions and challenges. Whereas in the past infrastructure leadership and system design has emphasized organization strategies that primarily focus on exploitation (e.g., efficiency and production, amenable to conditions of stability), in the future they must create space for exploration, the innovation of what the organization is and does. They will need to create the abilities to maintain themselves in the face of growing complexity by creating the knowledge, processes, and technologies necessary to engage environment complexity. We refer to this capacity as infrastructure autopoiesis. In doing so infrastructure organizations should focus on four key tenets. First, a shift to sustained adaptation – perpetual change in the face of destabilizing conditions often marked by uncertainty – and away from rigid processes and technologies is necessary. Second, infrastructure organizations should pursue restructuring their bureaucracies to distribute more resources and decisionmaking capacity horizontally, across the organization’s hierarchy. Third, they should build capacity for horizon scanning, the process of systematically searching the environment for opportunities and threats. Fourth, they should emphasize loose fit design, the flexibility of assets to pivot function as the environment changes. The inability to engage with complexity can be expected to result in a decoupling between what our infrastructure systems can do and what we need them to do, and autopoietic capabilities may help close this gap by creating the conditions for a sufficient repertoire to emerge.

Factors influencing household-level positive and negative solid waste management practices in rapidly urbanizing cities: insights from Santa Cruz de la Sierra, Bolivia

Household solid waste management (HSWM) practices are a critical aspect of municipal solid waste management (MSWM) systems. Despite efforts to implement source separation and recycling at the household level in developing countries, negative practices such as illegal dumping and backyard burning remain ubiquitous, particularly in rapidly urbanizing cities. Source separation and recycling behaviors have been rarely studied in such cities. Moreover, studies on illegal dumping and backyard burning using robust tools and frameworks are practically non-existent. This study aims to (a) estimate the prevalence of “negative” and “positive” behaviors for different HSWM practices, and (b) identify their observable and non-observable influencing factors. The focus is Santa Cruz, a rapidly urbanizing city of Bolivia. Household surveys (n=305) are used to establish the connections between latent constructs (e.g. awareness, satisfaction), and observable variables (e.g. location, socio-demographic characteristics) with each behavior. This is achieved through the combination of exploratory factor analysis to validate the constructs to be included in the analysis, and structural equation modeling to identify the most influential factors. Two causal models are developed, one for the positive behaviors (i.e. source separation, recyclables donation, recyclables selling, and use of drop-off facilities), and the other for the negative behaviors (i.e. illegal dumping and backyard burning). Results indicate that, satisfaction with the MSWM service has a negative and significant influence on the prevalence of illegal dumping and backyard burning behaviors, while the remoteness of the household (i.e. distance to the city center) has a positive significant effect on the prevalence of these behaviors. Source separation and recyclable donation are influenced positively by latent constructs such as attitudes, knowledge, and awareness. For recyclables selling and use of drop-off stations, income and location are the most relevant factors, although with smaller effects.

‘What is infrastructure? What does it do?’: Anthropological perspectives on the workings of infrastructure(s)

Infrastructure is often thought of in big material terms: dams, buildings, roads, and so on. This study, instead, draws on literatures in anthropology and the social sciences to analyse infrastructures in relation to society and environment, and so cast current conceptions of infrastructure in a new light. Situating the analysis in context of President Biden’s recent infrastructure bill, the paper expands what is meant by and included in discussions of infrastructure. The study examines what it means for different kinds of material infrastructures to function (and for whom) or not, and also consider how the immaterial infrastructure of human relations are manifested in, for example, labour, as well as how infrastructures may create intended or unintended consequences in enabling or disabling social processes. Further, in this study, we examine concepts embedded in thinking about infrastructure such as often presumed distinctions between the technical and the social, nature and culture, the human and the non-human, and the urban and the rural, and how all of these are actually implicated in thinking about infrastructure. Our analysis, thus, draws from a growing body of work on infrastructure in anthropology and the social sciences, enriches it with ethnographic insights from our own field research, and so extends what it means to study ‘infrastructures’ in the 21st century.

Infrastructure and SDG localization: the 21st century mandate

The United Nations Sustainable Development Goals (SDGs) propose a vision for policymaking at all scales and an institutional platform for producing knowledge and sharing experiences. National governments have the prerogative to determine their SDG planning and implementation strategies, with 169 targets and 232 indicators guiding efforts to achieve the 17 goals. At the same time, pursuing the SDGs is often a ground-level endeavor, highlighting the local and urban scale for policy concerns like infrastructure. In this way, cities are at the front lines of SDG implementation. This article considers how the global political economy of the SDGs – that is, the power and resource dynamics shaping sustainability narratives – imprints itself on relationships among cities and across levels of government in the planning of sustainable infrastructure.

Energy price modelling in Sub-Saharan Africa: a systematic literature review

The energy market in Sub-Saharan Africa (SSA) is not meeting the demands of the region’s growing population. Energy access remains a significant challenge, with most people on the continent still reliant on biomass and other traditional forms of energy. Paradoxically, research has found that the African continent has the highest potential for renewable energy generation. For this energy to be commercialized effectively, there is a need to understand energy price modelling in the SSA context. Our initial review of Literature showed that energy price modelling has received little attention in SSA. This paper, therefore, fills this gap by using a systematic literature review to consolidate knowledge on how energy price modelling has been applied in the SSA context. The systematic literature review results reveal four commonly used models: time series, Artificial Neural Network, Hybrid Iterative Reactive Adaptive (HIRA), and Hybrid models. Across the 46 SSA countries, governments have applied these models to price electricity and petroleum at the national level. However, these models have not been applied to renewable energy markets. Neither have they been applied at the household level. In the discussion, we hypothesize that price modelling can be used at the household level to improve energy decision-making. For this to work, price modelling should be simplified, user-friendly, and accessible to households. In conclusion, we recommend that SSA governments develop a more holistic view of energy price modelling to better harness the potential of renewables. They can do this through effective stakeholder engagement that includes the needs of small businesses and households. The main lessons drawn from this review include the possibility of using energy price modelling technology as a pathway to encouraging energy transitions to renewable energy in informal settlements in Africa. Using technology to bring the price modelling closer to the people is also an important element in facilitating effective transition to renewable energy. Finally, including the members of the community in pricing through creation of awareness on the models used and popularizing technology that can help in predictive pricing will help in creating better and faster energy transitions.

Diversity in the observed functionality of dams and reservoirs

Knowledge and modeling of the observed functionality of dams and reservoirs are desirable for better water resources management. In this study, we examine the functionality of dams and reservoirs over much of the globe through a hydroclimate assessment over 990 Global Runoff Data Center stations that have at least one dam/reservoir over the corresponding drainage areas and available streamflow records of at least 25 years. To quantify the potential capacity of human disturbance/alteration, annual cumulative maximum storage (CMS) of the dams are computed and then annual potential changes in the residence time of water (PRT; CMS divided by annual mean monthly flow) are assessed. In addition, the Man-Kendall tests for annual maximum, mean, and minimum monthly streamflow, and drainage area-averaged precipitation are conducted. Results show that the size of CMS and the main purpose have an explanatory power of the designed hydrologic response (i.e., flattening of the seasonality) while 6% of dam-affected stations experienced the opposite hydrologic response (intensifying of the seasonality) due to the overwhelming impact of anthropogenic climate change. This study finds that the magnitude of PRT is a potential indicator to identify a considerable impact of dams and reservoirs for the regional hydrologic regime. The findings of this study suggest diversity in the observed functionality of dams and reservoirs, which is still a challenge in global hydrological modeling.

A Colorado-specific life cycle assessment model to support evaluation of low-carbon transportation fuels and policy

The transportation sector accounts for over 20 percent of greenhouse gas (GHG) emissions in Colorado which without intervention will grow to over 30 million metric tons (MMT) of GHG emissions per year. This study seeks to develop a specific characterization of the Colorado fuel and transportation system using a customized life cycle assessment (LCA) model. The model (CO-GT) was developed as an analytical tool to define Colorado’s 2020 baseline life cycle GHG emissions for the transportation sector, and to examine Colorado-specific pathways for GHG reductions through fuel types and volumes changes that might be associated with a state clean fuel standard (CFS). By developing a life cycle assessment of transportation fuels that is specific to the state of Colorado’s geography, fleet makeup, policies, energy sector and more, these tools can evaluate various proposals for the transition towards a more sustainable state transportation system. The results of this study include a quantification of the Colorado-specific roles of clean fuels, electricity, extant policies, and fleet transition in projections of the state’s 2030 transportation sector GHG emissions. Relative to a 2020 baseline, electrification of the vehicle fleet is found to reduce state-wide lifecycle GHG emissions by 7.7 MMT CO2e by 2030, and a model CFS policy able to achieve similar reductions in the carbon intensity of clean fuels as was achieved by California in the first 10 years of its CFS policies is found to only reduce state-wide lifecycle GHG emissions by 0.2 MMT CO2e by 2030. These results illustrate the insensitivity of Colorado’s transportation fleet GHG emissions reductions to the presence of CFS policies, as proposed to date.

Factors associated with emerging multimodal transportation behavior in the San Francisco Bay Area

This paper identifies the influence of demographic, local transportation environment, and individual preferences for transportation attributes on multimodal transportation behavior in an urban environment with emergent transportation mode availability. Multimodality is the use of more than one mode of transportation during a given timeframe. Multimodality has been considered a key component of sustainable and efficient transportation systems, as this travel behavior can represent a shift away from personal vehicle use to more sustainable transportation modes, especially in urban environments with diverse transportation systems and emergent shared transportation alternatives (e.g., carsharing, ridehailing, bike sharing). However, it is unclear what factors contribute towards people being more likely to exhibit multimodal transportation behavior in modern urban environments. We assessed commuting behavior based on a survey administered in the San Francisco Bay Area according to whether residents commuted (i) exclusively by vehicle, (ii) by a mix of vehicle and non-vehicle modes, or (iii) exclusively by non-vehicle modes. A classification tree approach identified correlations between commuting classes and demographic variables, preferences for transportation attributes, and location-based information. The characterization of commuting styles could inform regional transportation policy and design that aims to reduce vehicle use by identifying the demographic, preference, and location-based considerations correlated with each commuting style.

Humidification-dehumidification desalination process using green hydrogen and heat recovery

We propose the use of green hydrogen as a fuel for a seawater heater in a humidification / dehumidification (HDH) desalination plant to increase its productivity, to allow scaling to large dimensions without negative environmental effects, and to guarantee continuous operation. We develop a mathematical model of the proposed HDH configuration. For operating conditions that guarantee very low NOX production, the fuel consumption is ~0.03 kg of H2 per kg of pure water produced. If the exhaust gases from the seawater heater are used for heat recovery, the GOR of the equipment may increase by up to 39 % in relation to the same equipment operating without heat recovery. The operation cost of freshwater is comparable to the costs obtained by other equipment in the literature. If the water produced in the combustion of hydrogen is condensed during the heat recovery process and then added to the freshwater produced, the production cost is reduced by 20 %. We found that an excess of air in the air+fuel mix beyond the minimum value appropriate for a low NOX generation does not provide significant benefits. The efficiency of the seawater heater has an impact on the production of pure water, but this impact is strongly mitigated by the heat recovery process. Fuel consumption increases proportionally with the decrease in the effectiveness of the heat recovery device, which is a key parameter for optimal performance. A hydrogen heater is also a good alternative as an auxiliary power source to guarantee continuous operation. On sunny hours a H2 heater may be used to increase productivity preheating the seawater, and at night the system could operate 100 % based on H2.

National and regional waste stream in the United States: conformance and disparity

Accurate estimation of municipal solid waste (MSW) composition is critical for efficient waste management. In the United States, site-specific and material flow approaches determine the MSW composition at regional and national levels. The material flow-based national estimates are determined by the U.S. EPA; the U.S. EPA’s estimates are known to differ substantially from the aggregated tonnage of MSW managed by waste handling facilities in the United States. However, the material class-specific discrepancies of the U.S. EPA’s material flow approach resulting in these differences are unknown. To find the basis of these discrepancies, we analyze the discarded MSW stream of 27 U.S. states, which roughly accounts for 73 percent of the U.S. population. Our analysis indicates that the material flow-based national estimates are accurate for the food, plastic, and glass material classes. In contrast, we find that the U.S. EPA’s material flow-based predictions underestimate paper waste disposal by at least 15 million tons annually. These differences likely stem from incorrect assumptions of residence time. These results highlight the material class-specific strengths and drawbacks of the U.S. EPA’s material flow-based MSW estimates.