Urban River Interventions in São Paulo Municipality (Brazil): The Challenge of Ensuring Justice in Sociotechnical Transitions

The paper aims to discuss the sociotechnical transitions regarding urban rivers policy in São Paulo Municipality by focusing on programs and projects conducted since 2000. Accordingly, we use a theoretical reflection on sociotechnical transitions and just transitions in interventions related to water and cities. Our work is based on a documental analysis of programs and projects for urban rivers in the municipality conducted via theoretical discussion. The primary focus is on the current sociotechnical regime, the channeling of streams and construction of road systems on its banks, and disputes and pressures brought by the technological landscape and niches, which lead to the construction of linear parks and leisure areas along with the bodies of water. It also shows how the issue of justice has been losing ground in this transition, which although is “in the making,” already presents many factors of injustice. This is due to the low presence of the theme of precarious settlements, in innovative speeches and practices, and the different treatment given by the programs and projects for rivers in the consolidated middle- and upper-class regions and for those located on the peripheries.

Monitoring and Understanding Urban Transformation: A Mixed Method Approach

Cities must address many challenges including air quality, climate change and the health and wellbeing of communities. Public authorities and developers increasingly look to improve these through the implementation of interventions and innovations, such as low traffic neighbourhoods, deep housing retrofits and green infrastructure. Monitoring the impacts of interventions is essential to determine the success of such projects and to build evidence for broader urban transformation. In this paper we present a mixed-method cross-disciplinary approach that brings together cutting edge atmospheric and data science, measurements of activity in public spaces and novel methods to assess wellbeing-promoting behaviours. The Manchester Urban Observatory focuses on living areas that have a high density of inter-related systems, which require observation, understanding and intervention at multiple levels. This must be completed in line with urban planning goals as well as a clear and succinct data solution that allows robust scientific conclusions to be made and viewed in real time. Delivery of such a monitoring strategy is not trivial and is time, resource and expertise heavy. This paper discusses the methods employed by the Manchester Urban Observatory to monitor the effectiveness off interventions implemented within cities and effective communication strategies with local communities.

Tracking a Circular Economy Transition Through Jobs: Method Development and Application in Two Cities

The methodology presented in this paper produces a circular economy jobs (CE jobs) measure. Using jobs as a proxy indicator, these measure gives cities a robust number to indicate progress toward the circular economy and is designed to serve as a first step in developing a circular economy strategy. The CE jobs measure tracks the inputs and outputs of goods in a city's “boundaries” through the material import dependency of the city's economic sectors. At the same time, tracking and assessing the circularity of the local jobs in these economic sectors will also provide city leaders with an indication of which sectors circularity is happening and could potentially happen. This paper also concludes that the process of coming to the CE jobs has two parts, the first more relevant to the local government and the second better influenced by the national government. Both need to come together for a truly circular local economy to happen.

A Social-Ecological Approach to Studying Variation in Urban Trees and Ecosystem Services in the National Municipal District of Santo Domingo, Dominican Republic

Maintaining a diverse urban forest that provides ecosystem services can promote urban sustainability and resilience to environmental change. Around the world, cities have taken to inventorying their urban trees and quantifying their ecosystem services but more so in industrialized counties than in Latin America. Here we describe the results of an i-Tree inventory that established 206 survey plots in the National Municipal District of Santo Domingo (NMDSD). We used social-ecological theory to evaluate potential factors that may influence urban forest structure, composition, and ecosystem services diversity across three wards with distinct social and urban characteristics. Rarefaction curves showed a diverse urban forest dominated by non-native trees that have ornamental and medicinal uses. Wards differed in species composition with palms being particularly dominant in Wards 1 and 2 where the proportion of low-income houses is smaller. Ward 1 supports high-income residential areas and Ward 3 is the area with higher population and housing densities and lower income residents. On average, we found no significant differences among wards in tree species richness, average dbh, leaf area, and percent tree cover per plot. Trees in Ward 2 were taller, on average, than those in Ward 1 but were comparable to those in Ward 3. Likewise, tree density per plot was highest in Ward 2, followed by Ward 1 and Ward 3. Despite these significant differences in stem densities, average values in four ecosystem services involving measures of carbon, rainfall, and contaminants (C-sequestration, C-storage, avoided runoff, and removal of air pollutants) were non-significant across wards. We found disproportionately more street trees in Ward 1 relative to Wards 2 and 3 and more trees in public spaces in Wards 1 and 2 relative to Ward 3. Evidence for the luxury effect on tree distribution in the NMDSD was subtle and manifested mostly through differences in species composition and tree distribution across public and private domains as well as the amount of planting space. Overall results point to inequalities in the potential of reforestation among NMDS wards and an overabundance of non-native species, which should guide urban forest management with ecosystem services and conservation goals.

Application of Deep Neural Networks to Distribution System State Estimation and Forecasting

Classical neural networks such as feedforward multi-layer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks (LSTMs) to mitigate the aforementioned challenges in power distribution systems. The ability of MLPs to perform regression to perform power system state estimation will be investigated. MLPs are considered based upon their promise to learn complex functional mapping between datasets with many features. CNNs and LSTMs are considered based upon their promise to perform time-series forecasting by learning the correlation of the dataset being predicted. The performance of MLPS, CNNs, and LSTMs to perform state estimation and state forecasting will be presented in terms of average root-mean square error (RMSE) and training execution time. An IEEE standard 34-bus test system is used to illustrate the proposed conventional neural network and deep learning methods and their effectiveness to perform power system state estimation and power system state forecasting.

Self-Reported Effects of the Covid-19 Pandemic on Stewardship Organizations and Their Activities in Southeast New England, USA

In many communities, regions, or landscapes, there are numerous environmental groups working across different sectors and creating stewardship networks that shape the environment and the benefits people derive from it. The make-up of these networks can vary, but generally include organizations of different sizes and capacities. As the Covid-19 pandemic (2020 to the present) shuts down businesses and nonprofits, catalyzes new initiatives, and generally alters the day-to-day professional and personal lives, it is logical to assume that these stewardship networks and their environmental work are impacted; exactly how, is unknown. In this study, we analyze the self-reported effects of the Covid-19 pandemic on stewardship groups working in southeast New England, USA. Stewardship organizations were surveyed from November 2020 to April 2021 and asked, among other questions, “How is Covid-19 affecting your organization?” We analyzed responses using several qualitative coding approaches. Our analysis revealed group-level impacts including changes in group capacity, challenges in managing access to public green spaces, and altered forms of volunteer engagement. These results provide insights into the varied effects of the Covid-19 pandemic and government responses such as stay-at-home orders and social distancing policies on stewardship that can inform the development of programs to reduce negative outcomes and enhance emerging capacities and innovations.

Impact of EDDS Dosage on Lead Phytoextraction in Contaminated Urban Residential Soils

Lead (Pb) contamination in soils of residential properties due to peeling and chipping of Pb-based paint can cause human health problems. Phytoextraction is a green technology that has the potential to remediate soil Pb. The efficiency of phytoextraction is dependent on the geochemical forms of Pb in soil. A biodegradable chelating agent, ethylenediaminedisuccinic acid (EDDS), was previously shown to enhance Pb removal by facilitating phytoextraction. In this study, EDDS was tested at various concentrations for its potential in mobilizing Pb in urban residential soils in Jersey City, New Jersey, and San Antonio, Texas. Results show that the concentrations of plant-available forms of Pb increased with the increasing dosage of EDDS from 2 to 30 mmol/L. The addition of EDDS at 30 mmol/L resulted in the conversion of up to 61.2% and 68.9% of the total Pb to plant-available forms in Jersey City and San Antonio soils, respectively. Further analysis showed that, after EDDS application, carbonate-bound Pb, oxide-bound Pb, organic-bound Pb, and residual silicate-bound Pb were transformed to plant-available forms. Higher doses of EDDS performed better than lower doses in transforming soil Pb forms, especially for the oxide-bound Pb. Strong correlations between Pb concentrations measured on-site using a portable X-ray Fluorescence Analyzer (p-XRF) and those obtained in the laboratory using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) confirmed that p-XRF is a reliable rapid, convenient technology to measure Pb levels in situ.

Data Governance and Regulation for Sustainable Smart Cities

It is increasingly understood that data governance is a key variable in the endeavor to design smart cities in such a way that they effectively contribute to achieving sustainability goals and solving environmental problems. However, the question of how different governance options might affect sustainability goals is still open. This article suggests an approach to answering this question from a regulatory perspective. It draws some preliminary lessons from previous regulatory debates, proposes a prospective evaluation of ideal types of data regulation, and finally seeks to outline normative guidelines for social–ecological data governance.