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This paper presents a typology of ecological injustice hotspots for targeted design of nature-based solutions to guide planning and designing of just cities. The typology demonstrates how the needs and capabilities of nonhuman nature can be embedded within transitions to multi- and interspecies relational futures that regenerate and protect urban social-ecological systems. We synthesise the findings of previous quantitative and qualitative analyses to develop the Ecologically Just Cities Framework that (1) works as a diagnostic tool to characterise four types of urban ecological injustices and (2) identifies nature-based planning actions that can best respond to different types of place-based ecological injustices. 摘要 本文提出了一个生态不公正热点的类型学，用于有针对性地设计基于自然的解决方案，以指导公正城市的规划和设计。该类型学展示了非人类自然的需求和能力如何能够被嵌入到向多物种和跨物种关系的未来过渡中，从而再生和保护城市社会生态系统。我们综合了之前的定量和定性分析结果，制定了生态公正的城市框架，(1) 作为诊断工具来描述四种类型的城市生态不公正；(2) 确定了基于自然的规划行动，可以最好地应对不同类型的地方生态不公正问题。 

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. 

We examine the uneven social and spatial distributions of COVID-19 and their relationships with indicators of social vulnerability in the U.S. epicenter, New York City (NYC). As of July 17th, 2020, NYC, despite having only 2.5% of the U.S. population, has [Formula: see text]6% of all confirmed cases, and [Formula: see text]16% of all deaths, making it a key learning ground for the social dynamics of the disease. Our analysis focuses on the multiple potential social, economic, and demographic drivers of disproportionate impacts in COVID-19 cases and deaths, as well as population rates of testing. Findings show that immediate impacts of COVID-19 largely fall along lines of race and class. Indicators of poverty, race, disability, language isolation, rent burden, unemployment, lack of health insurance, and housing crowding all significantly drive spatial patterns in prevalence of COVID-19 testing, confirmed cases, death rates, and severity. Income in particular has a consistent negative relationship with rates of death and disease severity. The largest differences in social vulnerability indicators are also driven by populations of people of color, poverty, housing crowding, and rates of disability. Results highlight the need for targeted responses to address injustice of COVID-19 cases and deaths, importance of recovery strategies that account for differential vulnerability, and provide an analytical approach for advancing research to examine potential similar injustice of COVID-19 in other U.S. cities. Significance Statement Communities around the world have variable success in mitigating the social impacts of COVID-19, with many urban areas being hit particularly hard. Analysis of social vulnerability to COVID-19 in the NYC, the U.S. national epicenter, shows strongly disproportionate impacts of the pandemic on low income populations and communities of color. Results highlight the class and racial inequities of the coronavirus pandemic in NYC, and the need to unpack the drivers of social vulnerability. To that aim, we provide a replicable framework for examining patterns of uneven social vulnerability to COVID-19- using publicly available data which can be readily applied in other study regions, especially within the U.S.A. This study is important to inform public and policy debate over strategies for short- and long-term responses that address the injustice of disproportionate impacts of COVID-19. Although similar studies examining social vulnerability and equity dimensions of the COVID-19 outbreak in cities across the U.S. have been conducted (Cordes and Castro 2020, Kim and Bostwick 2002, Gaynor and Wilson 2020; Wang et al. 2020; Choi and Unwin 2020), this study provides a more comprehensive analysis in NYC that extends previous contributions to use the highest resolution spatial units for data aggregation (ZCTAs). We also include mortality and severity rates as key indicators and provide a replicable framework that draws from the Centers for Disease Control and Prevention’s Social Vulnerability indicators for communities in NYC.