Across the world, cities are spending billions of dollars to manage urban runoff through decentralized green infrastructure (GI). This research uses an agent‐based model to explore some of the physical, social, and economic consequences of one such urban GI programs. Using the Bronx, NY, as a case study, two alternative approaches to GI application are compared. The first (Model 1) mimics NYC's current GI program by opportunistically selecting sites for GI within the city's priority combined sewer watersheds; the second (Model 2) features a more spatially flexible approach to GI siting, in which the city attempts to maximize opportunities for co‐benefits within the geographic areas considered in Model 1. The effects of both approaches, measured in terms of stormwater captured and co‐benefits (e.g., carbon sequestered) provided, are tracked over 20‐year simulations. While both models suggest it will be difficult to meet the citywide stormwater capture goals (managing the first 2.5 cm of rainfall from 10% of impervious surfaces) in the Bronx solely through public investment in GI, Model 2 shows that by integrating GI with other city initiatives (e.g., sustainability goals and resilience planning), synergistic outcomes are possible. Specifically, Model 2 produces stormwater capture rates comparable to those obtained under Model 1, but these rates are accompanied by elevated co‐benefits for Bronx communities. The results are discussed in the context of future GI policy development in NYC.
- NSF-PAR ID:
- Date Published:
- Journal Name:
- Journal of Environmental Policy & Planning
- Page Range / eLocation ID:
- 1 to 18
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
Over the past several decades, urban planning has considered a variety of advanced analysis methods with greater and lesser degrees of adoption. Geographic Information Systems (GIS) is probably the most notable, with others such as database management systems (DBMS), decision support systems (DSS), planning support systems (PSS), and expert systems (ES), having mixed levels of recognition and acceptance (Kontokosta, C. E. (2021). Urban informatics in the science and practice of planning. Journal of Planning Education and Research, 41(4), 382–395. doi:10.1177/0739456X18793716; Yigitcanlar, T., Desouza, K. C., Butler, L., & Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13(6), 1473). Advances in information technologies have moved very slowly in the field of urban planning, more recently concerning ‘smart city’ technologies while revolutionizing other domains, such as consumer goods and services. Baidu, Amazon, Netflix, Google, and many others are using these technologies to gain insights into consumer behaviour and characteristics and improve supply chains and logistics. This is an opportune time for urban planners to consider the application of AI-related techniques given vast increases in data availability, increased processing speeds, and increased popularity and development of planning related applications. Research on these topics by urban planning scholars has increased over the past few years, but there is little evidence to suggest that the results are making it into the hands of professional planners (Batty, M. (2018). Artificial intelligence and smart cities. Environment and Planning B: Urban Analytics and City Science, 45(1), 3–6; Batty, M. (2021). Planning education in the digital age. Environment and Planning B: Urban Analytics and City Science, 48(2), 207–211). Others encourage planners to leverage the ubiquity of data and advances in computing to enhance redistributive justice in information resources and procedural justice in decision-making among marginalized communities (Boeing, G., Besbris, M., Schachter, A., & Kuk, J. (2020). Housing search in the Age of Big data: Smarter cities or the same Old blind spots? Housing Policy Debate, 31(1), 112–126; Goodspeed, R. (2015). Smart cities: Moving beyond urban cybernetics to tackle wicked problems. Cambridge journal of regions, Economy and Society, 8(1), 79–92). This article highlights findings from a recent literature review on AI in planning and discusses the results of a national survey of urban planners about their perspectives on AI adoption and concerns they have expressed about its broader use in the profession. Currently, the outlook is mixed, matching how urban planners initially viewed the early stages of computer adoption within the profession. And yet today, personal computers are essential to any job.more » « less
Green infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.
McBroom-Fitterer, Cameron (Ed.)Problem, Approach, and Findings Extreme heat is one of the most concerning natural hazards facing cities today, forecasted to increase in frequency, duration, and intensity in the future. With close to 3.5 billion people projected to be impacted worldwide by extreme heat by 2070, it is critical that efforts focus on planning and adapting our built urban environment to reduce the risks that people will face from heat waves. A lack of data and monitoring has left uncertainty surrounding the full impact to people’s health from extreme heat. Currently, planners are undertaking important work to understand how extreme heat disproportionately affects communities historically discriminated against in planning practices. Implications This article looks at how local planners and municipalities, primarily in urban communities, can best address extreme heat within the lens of equitable resilience. Planners must go beyond unenforceable comprehensive plans to zoning regulations and unified development ordinances to change and adapt to threats posed by hazards. Equitable stakeholder engagement and environmental justice must be incorporated into the process, centering those with power and those most impacted, as these people will have the most at stake.more » « less
null (Ed.)Livability, resilience, and justice in cities are challenged by climate change and the historical legacies that together create disproportionate impacts on human communities. Urban green infrastructure has emerged as an important tool for climate change adaptation and resilience given their capacity to provide ecosystem services such as local temperature regulation, stormwater mitigation, and air purification. However, realizing the benefits of ecosystem services for climate adaptation depend on where they are locally supplied. Few studies have examined the potential spatial mismatches in supply and demand of urban ecosystem services, and even fewer have examined supply–demand mismatches as a potential environmental justice issue, such as when supply–demand mismatches disproportionately overlap with certain socio-demographic groups. We spatially analyzed demand for ecosystem services relevant for climate change adaptation and combined results with recent analysis of the supply of ecosystem services in New York City (NYC). By quantifying the relative mismatch between supply and demand of ecosystem services across the city we were able to identify spatial hot- and coldspots of supply–demand mismatch. Hotspots are spatial clusters of census blocks with a higher mismatch and coldspots are clusters with lower mismatch values than their surrounding blocks. The distribution of mismatch hot- and coldspots was then compared to the spatial distribution of socio-demographic groups. Results reveal distributional environmental injustice of access to the climate-regulating benefits of ecosystem services provided by urban green infrastructure in NYC. Analyses show that areas with lower supply–demand mismatch tend to be populated by a larger proportion of white residents with higher median incomes, and areas with high mismatch values have lower incomes and a higher proportion of people of color. We suggest that urban policy and planning should ensure that investments in “nature-based” solutions such as through urban green infrastructure for climate change adaptation do not reinforce or exacerbate potentially existing environmental injustices.more » « less