By Lawrence A. Palinkas, Marleen Wong
Social Work and Sustainability in Asia
Maintaining social sustainability in the context of global climate change is among the most pressing challenges facing contemporary societies in the Asia-Pacific Rim. These societies are increasingly being confronted with a host of changes in the physical environment, ranging from natural disasters, rising air and water temperatures, rising sea levels and ocean acidification, prolonged droughts and scarcity of fresh water in some regions, and extensive flooding in other regions. All of these changes are contributing to the wholesale destruction of natural ecosystems on land and sea. They also have profound social implications, threatening human health and well-being, destabilizing assets, coping capacities, and response infrastructures, and substantially increasing the number of socially, economically, and psychologically vulnerable individuals and communities. Moreover, these impacts will not affect everyone equally, leading to new social inequities with significant social justice implications. In this chapter, we summarize the human impacts of global climate change with a focus on the sustainability of individuals, families, and communities. We then address strategies for promoting sustainability in the face of two specific impacts: population displacement and disaster response and recovery. These strategies adhere to a three-tier model of climate change impact and response, and include microlevel interventions designed to prevent and mitigate behavioral and mental health impacts; mezzo-level interventions to prevent and mitigate social conflict within families and communities; and macro-level policies and programs designed to build and support individual, families, and community resilience, assets, and action.
By Douglas Houston, Marlon Boarnet, Gavin Ferguson, Steven Spears
Directing growth towards compact rail corridors has become a key strategy for redirecting auto-oriented regions towards denser, mixed-use communities that support sustainable travel. Few have examined how travel of near-rail residents varies within corridors or whether corridor land use–travel interactions diverge from regional averages. The Los Angeles region has made substantial investments in transit-oriented development, and our survey analysis indicates that although rail corridor residents drove less and rode public transit more than the county average, households in an older subway corridor with more near-transit development had about 11 fewer daily miles driven and higher transit ridership than households along a newer light rail line, a difference likely associated with development patterns and the composition and preferences of residents. Rail transit corridors are not created equally, and transit providers and community planners should consider the social and development context of corridors in efforts to improve transit access and maximise development.
By Andrea Martinez, Joon-Ho Choi
Reducing the energy consumption in existing buildings became one of the critical challenges at the beginning of the 21st century. Several types and levels of retrofits are now being implemented in the building stock. To obtain a better understanding of the actual impact of these actions, evidence-based research has been playing an increasingly important role. This paper describes the collection of data on measured pre- and post-retrofit energy consumption of a group of buildings in the U.S., in order to distinguish the impacts of different levels of retrofits. In particular, the goal has been to distinguish how retrofits including facade improvements compare to those centered exclusively on internal systems. Additionally, energy data was collected for a subset of non-retrofitted buildings and used as the control group. The regression model revealed greater energy savings from retrofits including the facade as compared to those that excluded it. However, those savings are modest considering the energy reductions that are anticipated from deep-energy retrofits. Other relevant factors, such as occupants and their behavior, are vital for determining the value of retrofits and need to be incorporated in the next phases of this study.
By Eric Heikkila
Planning Theory & Practice
Human settlements have long been located on rivers, and the relationship of the place to the river functions as a deep reflection of its historical, cultural, and socio-economic traditions. This paper explores urban river revitalization in contemporary China, focusing particularly on ongoing efforts to clean up Foshan’s polluted Fenjiang River. The research shows that the traditional cultural status of the waterway, which is known as the “Mother River” of Foshan, plays a paradoxically pivotal role in the project to modernize it. Interacting in complex ways with domestic and international political concerns, and popular media and internet technologies, the cultural status of the river has helped to determine both the type of environmental movement that has emerged in its defence, and the community of interests that serves as a proxy for civil society in that movement. Ultimately, this paper argues that the unique configuration of institutions and actors engaged in the Fenjiang River restoration project are emblematic of a new type of “environmentalism with Chinese characteristics.”
By Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining
Discovering latent structures in spatial data is of critical importance to understanding the user behavior of location based services. In this paper, we study the problem of geographic segmentation of spatial data, which involves dividing a collection of observations into distinct geo-spatial regions and uncovering abstract correlation structures in the data. We introduce a novel, Latent Poisson Factor (LPF) model to describe spatial count data. The model describes the spatial counts as a Poisson distribution with a mean that factors over a joint item-location latent space. The latent factors are constrained with weak labels to help uncover interesting spatial dependencies. We study the LPF model on a mobile app usage data set and a news article readership data set. We empirically demonstrate its effectiveness on a variety of prediction tasks on these two data sets.
By Gale M. Sinatra
Educational and Developmental Psychologist
The climate crisis is the defining issue of our time. Educational and developmental psychologists can make clear and important contributions to addressing this existential threat. The articles in the Climate Crisis Special Issue take on the issue of climate change from multiple angles, with varied populations, using different research methods and theoretical frameworks. The special issue makes clear the important role psychologists have to play in addressing the climate crisis.
By Feng Zhu, Julien Emile-Geay, Nicholas P. McKay, Gregory J. Hakim, Deborah Khider, Toby R. Ault, Eric J. Steig, Sylvia Dee, James W. Kirchner
Proceedings of the National Academy of Sciences of the United States of America
Measures of climate are known to exhibit scaling behavior with large exponents, resulting in larger ﬂuctuations at longer timescales. It has been suggested that climate models underestimate these ﬂuctuations [1-4], casting doubt on their ability to predict the amplitude of climate variability over coming decades and centuries. Using the latest simulations and data syntheses, as well as spectral methods tailored to scaling estimation, we ﬁnd agreement for spectra derived from observations and models on timescales ranging from interannual to multi-millennial. Our results conﬁrm the existence of a regime transition between orbital and annual peaks , occurring around millennial periodicities. That both simple and comprehensive ocean-atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. The result implies that decadal to millennial variability over the Holocene is partly a consequence of the climate system’s integrated memory of orbital forcing. While climate models imperfectly depict some aspects of spatiotemporal variability, we find that they appear contain the essential physics to correctly simulate the temperature continuum. We hypothesize that the deep ocean plays a key role in integrating forcings, keeping a long memory of past events, and having the ability to strongly influence climate states. We therefore suggest that a critical element of successful simulations at sub-orbital scales are initial conditions of the deep ocean state that are consistent with observations of the recent past. Failing to provide such initial conditions sets the models up for failure.
By Rob McConnell
Unlike air pollution, traffic-related noise remains unregulated and has been under-studied despite evidence of its deleterious health impacts. To characterize population exposure to traffic noise, both acoustic-based numerical models and data-driven statistical approaches can generate estimates over large urban areas. The aim of this work is to formally compare the performances of the most common traffic noise models by evaluating their estimates for different categories of roads and validating them against a unique dataset of measured noise in Long Beach, California. Specifically, a statistical land use regression model, an extreme gradient boosting machine learning model (XGB), and three numerical/acoustic traffic noise models: the US Noise Model (FHWA-TNM2.5), a commercial noise model (CadnaA), and an open-source European model (Harmonoise) were optimized and compared. The results demonstrate that XGB and CadnaA were the most effective models for estimating traffic noise, and they are particularly adept at differentiating noise levels on different categories of road.