Understanding the systemic nature of cities to improve health and climate change mitigation

Definition and characteristics of climate-adaptive cities: a systematic review

BACKGROUND

Cities, as frontline responders to climate change, necessitate a precise understanding of climate-adaptive features. This systematic review aims to define and outline the characteristics of climate-adaptive cities, contributing vital insights for resilient urban planning.

METHODS

This systematic review, initiated on March 6, 2018, and concluded on August 26, 2021, involved reviewing multiple electronic databases based on the study's objectives. The Critical Appraisal Skills Program (CASP) tool was used for quality assessment and critical evaluation of articles retrieved through a comprehensive and systematic text search. Descriptive and thematic analyses were conducted to extract definitions, features, and characteristics of climate-adaptive cities.

RESULTS

Out of 6104 identified articles, 38 articles met the inclusion criteria. In total, 20 definitions and 55 features for climate-adaptive cities were identified in this review. Codes were categorized into two categories and ten subcategories. The categories included definitions and features or characteristics of climate-adaptive cities.

CONCLUSION

A climate-adaptive city, as derived from the findings of this study, is a city that, through effective resource management, future-oriented planning, education, knowledge utilization, innovation in governance and industry, decentralized management, and low-carbon economy, leads to the adaptability, resilience, sustainability, and flexibility of the capacity of individuals, communities, institutions, businesses, and systems within a city against all climate change impacts and reduces their negative consequences.

Determinant factors hinder urban structure plan implementation: The case of Nekemte Town, Ethiopia

Urban structure plan is widely used plan in the process of urbanization and rapid urban spatial expansion. However, rapidly growing urban centers of Ethiopia are facing challenges to implement their structure plan within the time horizon. Thus, this study aims to investigate the determinant factors that hinder structure plan implementation in Nekemte town. Questionnaire survey, interview, observation and land use survey were used to collect data. Descriptive data analysis and regression model were used to analyze the data. The main findings of the study show that all identified factors: lack of active participation, lack commitment, political instability and lack of sufficient budget significantly contribute for the failure of structure plan implementation at P-value of 0.05. The regression analysis further indicated that, lack of community participation; - 0.0499 coefficients is the most determining factors and followed by customary land tenure and lack of awareness -0.0489 and -0.0468 coefficients respectively. Hence, future structure plan implementation endeavors of Nekemte city must be underpinned by inculcating community participation and awareness of structure plan that is required to implement the plan to the expected level. Furthermore, use of modern technology like GIS and appropriate man power are also equally recommended to enhance structure plan implementation of Nekemte city.

A synthetic water-heat-vegetation biodiversity nexus approach to assess coastal vulnerability in eastern China

Climate change pressure and biodiversity degradation in coastal regions have caused an increase in urban vulnerability. Current coastal vulnerability studies fail to consider the interactions among the perturbations. Increases in such interactions contribute to the indeterminate changes in the ecosystem productivity and impact on human well-being. Therefore, by integrating water, heat, and vegetation biodiversity (WHB) indicators using catastrophe theory in the study, the interaction among subsystems was explored to expound on the multi-effect of the urban. The results showed that (1) the overall vulnerability of China's coastal cities has increased, and high-value areas were mainly distributed in the three southern provinces; (2) the spatial-temporal pattern of vulnerability was highly heterogeneous. As low-low clusters, Shanghai and its surrounding cities exhibited spatial aggregation characteristics; (3) social, physical and financial capitals were the first three main adaptive capacity factors. The distance-based linear model (DistLM) evidenced that per capita GDP, and road density explained about 30 % and 10 % of the difference in vulnerability variation. The proposed framework could help decision-makers detect how vulnerable coastal areas exposed to WHB impacts are, with crucial implications for future sustainable management.

Impacts of new cycle infrastructure on cycling levels in two French cities: an interrupted time series analysis

BACKGROUND

Cities globally have started to make substantial investment in more sustainable forms of transportation. We aimed to evaluate whether the construction of new cycling infrastructure in Paris and Lyon, France, affected population cycling activity along new or improved routes.

METHODS

Routinely collected cycle count data from January 2014 to March 2020 were acquired for the cities of Paris and Lyon. Improvements were identified at 15 locations with 6 months of pre- and post-intervention data. Comparison streets were chosen within Paris or Lyon for which pre-intervention trends in cycling were similar to those at intervention sites. Controlled interrupted time series analyses and autocorrelation were performed adjusting for seasonality. Random-effects meta-analysis combined results across streets within each city and overall.

RESULTS

On average, cycling counts/day increased on both intervention and control streets in Paris and Lyon. In general, results of the ITS analysis indicated no significant change in the level or trend as a result of the improvements in either city. Meta-analysis suggested that intervention streets in Paris had a larger positive pooled effect size for level change (218 cycle counts, 95% CI -189, 626, I² = 0%) compared to Lyon (34, 95% CI -65, 133, I² = 14%); however, confidence intervals for both cities were wide and included no effect.

CONCLUSIONS

The findings suggest that improving or constructing new cycle lanes may be necessary but not sufficient to induce significant changes in cycling levels. There is a need to understand how context, intervention design and other complementary interventions can improve the effectiveness of new cycling infrastructure.

Transformative low-carbon urban innovations: Operationalizing transformative capacity for urban planning

Cities can set in motion sustainability transitions through experimentation and innovation. To invest in and mainstream solutions that contribute to urban transformation agendas, urban planners needs to understand which innovations have transformational potential as well as how these innovations can accelerate sustainability transitions. In order to explore this, existing frameworks of transformative capacity provide the guidance, but they are generic, abstract, and challenging to apply for urban planning. As part of our effort to develop a more operational version of the transformative capacity framework by Wolfram (2016), we conducted a systematic scoping review of the academic literature to determine the characteristics of people-based and nature-based low-carbon innovations that constitutes their transformative capacity. After reviewing 65 records, we identified dimensions indicating each of the transformative capacity components through analysis and synthesis. Besides contributing to the science-policy interface through a knowledge synthesis on low-carbon people-based and nature-based innovations, this paper examines bridging frameworks to inform urban planners in developing practical solutions and actionable elements for low-carbon urban futures.

Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution

Nighttime light remote sensing has aroused great popularity because of its advantage in estimating socioeconomic indicators and quantifying human activities in response to the changing world. Despite many advances that have been made in method development and implementation of nighttime light remote sensing over the past decades, limited studies have dived into answering the question: Where does nighttime light come from? This hinders our capability of identifying specific sources of nighttime light in urbanized regions. Addressing this shortcoming, here we proposed a parcel-oriented temporal linear unmixing method (POTLUM) to identify specific nighttime light sources with the integration of land use data. Ratio of root mean square error was used as the measure to assess the unmixing accuracy, and parcel purity index and source sufficiency index were proposed to attribute unmixing errors. Using the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light dataset from the Suomi National Polar-Orbiting Partnership (NPP) satellite and the newly released Essential Urban Land Use Categories in China (EULUC-China) product, we applied the proposed method and conducted experiments in two China cities with different sizes, Shanghai and Quzhou. Results of the POTLUM showed its relatively robust applicability of detecting specific nighttime light sources, achieving an rRMSE of 3.38% and 1.04% in Shanghai and Quzhou, respectively. The major unmixing errors resulted from using impure land parcels as endmembers (i.e., parcel purity index for Shanghai and Quzhou: 54.48%, 64.09%, respectively), but it also showed that predefined light sources are sufficient (i.e., source sufficiency index for Shanghai and Quzhou: 96.53%, 99.55%, respectively). The method presented in this study makes it possible to identify specific sources of nighttime light and is expected to enrich the estimation of structural socioeconomic indicators, as well as better support various applications in urban planning and management.

Evaluating natural experiments to measure the co-benefits of urban policy interventions to reduce carbon emissions in New Zealand

Finding effective policy interventions for addressing the Sustainable Development Goals, such as reducing carbon emissions (SDG 13), which can also enhance good health and wellbeing (SDG 3), is urgent. Many promising interactions occur between sustainable cities and communities (SDG 11), clean water and sanitation (SDG 6) and affordable and clean energy (SDG 7), which sit at the centre of integrated urban planning and regeneration. In this paper, we consider the framing and findings of four policies we have evaluated as natural experiments, all of which have important co-benefits, which were not always the focus of the initial policies. These policies are: the installation of cycleways and walkways in existing suburbs; a central government measure to recentralise employment after the 2011 Christchurch earthquakes; the streamlining of housing developments by reducing land-use regulation; and ongoing changes of policy about public housing investment. We show that having a clear understanding of the benefits of increased physical activity for health, for example, could accelerate the reduction of carbon emissions. Also, decisions about infrastructure, housing and job locations can generate health and environmental gains if supported by broader public transport investments. Cycling and walking are also more likely to substitute for short habitual car trips. Similarly, measuring the co-benefits of differential residential models, relating to land-use and renewable energy, provides a framework that can facilitate learning from policy interventions, enabling wider and potentially more rapid generalisation of policies, including those for climate change mitigation.

Urban Sprawl Sustainability of Mountainous Cities in the Context of Climate Change Adaptability Using a Coupled Coordination Model: A Case Study of Chongqing, China

In recent years, a noticeable contradiction has emerged between the disorderly sprawl and fragile climate environment of many cities, especially in mountainous cities. Therefore, this paper respectively constructed evaluation indicators for urban sprawl sustainability (USS) and climate change adaptability (CCA). Next, a coupling coordination degree model was used to measure the coordinated development of USS and CCA. Finally, this paper analyzed the coordinated development type of USS and CCA in the Chongqing metropolitan area from 2007 to 2017. The results of this paper show that USS and CCA have gradually shifted to coordinated development in the Chongqing metropolitan area during the study period. However, there were obvious regional differences in the type of coordinated development in the Chongqing metropolitan area. The coordinated development degree of USS and CCA in nine districts ranged from 0.635 to 0.721 in 2017. It can be divided into three types: slightly coordinated development with lagging CCA; slightly coordinated development with lagging USS; and moderately coordinated development with lagging CCA. Those districts should give priority to the use of Nature-Based Solutions (NBS), and multi-center and multi-group approaches to enhance the coordinated development between USS and CCA, which is also helpful for mountainous cities in China and other countries.

Mapping interactions between the sustainable development goals: lessons learned and ways forward

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones ("trade-offs") and positive ones ("co-benefits"). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

Identifying the key catastrophic variables of urban social-environmental resilience and early warning signal

Pursuit of sustainability requires a systematic approach to understand a system's specific dynamics to adapt and enhance from disturbances in social-environmental systems. We developed a systematic resilience assessment of social-environmental systems by connecting catastrophe theory and probability distribution equilibrium. Catastrophe models were used to calculate resilience shifts between slow and fast variables; afterwards, two resilience transition modes ("Less resilient" or "More resilient") were addressed by using probability distribution equilibrium analysis. A tipping point that occurs in "Less resilient" system suggests that the critical resilience transition can be an early warning signal of approaching threshold. Catastrophic shifts were explored between the interacting social-environmental sub-systems of land use and energy (fast variables) and environmental pollution (slow variables), which also identifies the critical factors in maintaining the integrated social-environmental resilience. Furthermore, the early warning signals enable the adaptability of urban systems and their resilience to perturbations, and provide guidelines for urban social-environmental management.

How Economic Analysis Can Contribute to Understanding the Links between Housing and Health

An economic analysis of housing's linkages to health can assist policy makers and researchers to make better decisions about which housing interventions and policies are the most cost-beneficial. The challenge is to include cobenefits. The adoption in 2015 of the UN Sustainable Development Goals underscores the importance of understanding how policies interact, and the merit of comprehensively evaluating cobenefits. We explain our approach to the empirical assessment of such cobenefits in the housing and health context, and consider lessons from empirical economic appraisals of the impact of housing on health outcomes. Critical assumptions relating to cobenefits are explicitly examined. A key finding is that when wider policy outcome measures are included, such as mental health impacts and carbon emission reductions, it is important that effects of assumptions on outcomes are considered. Another is that differing values underlie appraisal, for example, the weight given to future generations through the discount rate. Cost-benefit analyses (CBAs) can better facilitate meaningful debate when they are based on explicit assumptions about values. In short, the insights drawn from an economic framework for housing-and-health studies are valuable, but nonetheless contingent. Given that housing interventions typically have both health and other cobenefits, and incorporate social value judgements, it is important to take a broad view but be explicit about how such interventions are assessed.