Research Papers

Which Financial Stressors are Linked to Food Insecurity Among Adults in the United Kingdom, Germany and the Netherlands? An Exploratory Study

By Wändi Bruine de Bruin

Food Security

2022

Food insecurity among adults age 65 and older is a growing public policy concern in European countries, but the extent of the problem and the related financial stressors are unclear. The purpose of this paper is to measure the percent of food insecure individuals in a targeted sample of financially fragile older adults, and to identify associated financial stressors and socio-economic characteristics. This exploratory study is based on an online survey of 1,059 older adults experiencing financial hardship. Participants were recruited through commercial consumer panels in the United Kingdom, Germany, and the Netherlands. The proportion of financially fragile older adults reporting food insecurity ranged from 24% in the British sample, 29% in the German sample, and 35% in the Dutch sample. We identified financial stressors that contributed to food insecurity in each country sample. Having more financial stressors increased the risk of food insecurity, which was similar in each country. Within and across country samples, food insecurity is associated with financial stressors. Insights for policy makers, consumer advocates, and social services point to the value of integrating financial and food-related support services, the potential for cross-country collaboration, and efforts that take into account the particular financial circumstances of older adults.


Ten Questions Concerning Human-Building Interaction Research for Improving the Quality of Life

By Burçin Becerik-Gerber et al.

Building and Environment

2022

This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence. The field of HBI builds on several existing efforts in historically separate research fields/communities and aims to understand how buildings affect human outcomes and experiences, as well as how humans interact with, adapt to, and affect the built environment and its systems, to support buildings that can learn, enable adaptation, and evolve at different scales to improve the quality-of-life of its users while optimizing resource usage and service availability. Questions were developed by a diverse group of researchers with backgrounds in design, engineering, computer science, social science, and health science. Answers to these questions draw conclusions from what has been achieved to date as reported in the available literature and establish a foundation for future HBI research. This paper aims to encourage interdisciplinary collaborations in HBI research to change the way people interact with and perceive technology within the context of buildings and inform the design, construction, and operation of next-generation, intelligent built environments. In doing so, HBI research can realize a myriad of benefits for human users, including improved productivity, health, cognition, convenience, and comfort, all of which are essential to societal well-being.


A Model to Characterize Soil Moisture and Organic Matter Profiles in the Permafrost Active Layer in Support of Radar Remote Sensing in Alaska Artic Tundra

By Mahta Moghaddam et al.

Environmental Research

2022

Organic matter (OM) content and a shallow water table are two key variables that govern the physical properties of the subsurface within the active layer of arctic soils underlain by permafrost, where the majority of biogeochemical activities take place. A detailed understanding of the soil moisture and OM profile behavior over short vertical distances through the active layer is needed to adequately model the subsurface physical processes. To observe and characterize the profiles of soil properties in the active layer, we conducted detailed soil sampling at five sites along Dalton Highway on Alaska’s North Slope. These data were used to derive a generalized logistics function to characterize the total OM and water saturation fraction behavior through the profile. Furthermore, a new pedotransfer function was developed to estimate the soil bulk density and porosity—information that is largely missing from existing soil datasets—within each layer, solely from the soil texture (organic and mineral properties). Given the currently sparse soil database of the Alaskan Arctic, these profile models can be highly beneficial for radar remote sensing models to study active layer dynamics.


Embedded Temporal Convolutional Networks for Essential Climate Variables Forecasting

By Mahta Moghaddam et al.

Sensors

2022

Forecasting the values of essential climate variables like land surface temperature and soil moisture can play a paramount role in understanding and predicting the impact of climate change. This work concerns the development of a deep learning model for analyzing and predicting spatial time series, considering both satellite derived and model-based data assimilation processes. To that end, we propose the Embedded Temporal Convolutional Network (E-TCN) architecture, which integrates three different networks, namely an encoder network, a temporal convolutional network, and a decoder network. The model accepts as input satellite or assimilation model derived values, such as land surface temperature and soil moisture, with monthly periodicity, going back more than fifteen years. We use our model and compare its results with the state-of-the-art model for spatiotemporal data, the ConvLSTM model. To quantify performance, we explore different cases of spatial resolution, spatial region extension, number of training examples and prediction windows, among others. The proposed approach achieves better performance in terms of prediction accuracy, while using a smaller number of parameters compared to the ConvLSTM model. Although we focus on two specific environmental variables, the method can be readily applied to other variables of interest.


We are Boiling: Management Scholars Speaking out on COVID-19 and Social Justice

By Paul S. Adler et al.

Journal of Management Inquiry

2022

COVID-19 is the most immediate of several crises we face as human beings: crises that expose deeply-rooted matters of social injustice in our societies. Management scholars have not been encouraged to address the role that business, as we conduct it and consider it as scholars, has played in creating the crises and fostering the injustices our crises are laying bare. Contributors to this article draw attention to the way that the pandemic has highlighted long-standing examples of injustice, from inequality to racism, gender, and social discrimination through environmental injustice to migratory workers and modern slaves. They consider the fact that few management scholars have raised their voices in protest, at least partly because of the ideological underpinnings of the discipline, and the fact these need to be challenged.


The NASA Cyclone Global Navigation Satellite System SmallSat Constellation

By Mahta Moghaddam et al.

Small Satellite Conference

2022

The NASA Cyclone Global Navigation Satellite System (CYGNSS) mission consists of a constellation of eight microsatellites launched on 15 December 2016 into a common circular orbit at ~525 km altitude and 35 deg inclination. Each observatory carries a four channel bistatic radar receiver to measure GPS signals scattered by the Earth surface. Over ocean, near-surface wind speed, air-sea latent and sensible heat flux, and ocean microplastic concentration are derived from the measurements. Over land, near-surface soil moisture and inland water bodies extent are derived. The measurements penetrate through all levels of precipitation and most vegetation due to the 19 cm wavelength of GPS L1 signals. The sampling produced by the constellation makes possible the reliable detection of short time scale weather events such as flood inundation dynamics immediately after a tropical cyclone landfall and rapid soil moisture dry down immediately after major precipitation events. The sun-asynchronous nature of the CYGNSS orbit also supports full sampling of the diurnal cycle of hydrological dynamics within a short period of time. Summaries are presented of engineering and science highlights of the CYGNSS mission, with particular emphasis on those aspects most directly enabled by the use of a constellation of SmallSats.


Educational and Developmental Psychologists Take Action in Response to the Climate Crisis

By Gale M. Sinatra

Educational and Developmental Psychologist

2022

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.


Contribution of tailpipe and non-tailpipe traffic sources to quasi-ultrafine, fine and coarse particulate matter in southern California

By Rob McConnell et al.

Journal of the Air & Waste Management Association

2021

Exposure to traffic-related air pollution (TRAP) in the near-roadway environment is associated with multiple adverse health effects. To characterize the relative contribution of tailpipe and non-tailpipe TRAP sources to particulate matter (PM) in the quasi-ultrafine (PM0.2), fine (PM2.5) and coarse (PM2.5–10) size fractions and identify their spatial determinants in southern California (CA). Month-long integrated PM0.2, PM2.5 and PM2.5–10 samples (n = 461, 265 and 298, respectively) were collected across cool and warm seasons in 8 southern CA communities (2008–9). Concentrations of PM mass, elements, carbons and major ions were obtained. Enrichment ratios (ER) in PM0.2 and PM10 relative to PM2.5 were calculated for each element. The Positive Matrix Factorization model was used to resolve and estimate the relative contribution of TRAP sources to PM in three size fractions. Generalized additive models (GAMs) with bivariate loess smooths were used to understand the geographic variation of TRAP sources and identify their spatial determinants. EC, OC, and B had the highest median ER in PM0.2 relative to PM2.5. Six, seven and five sources (with characteristic species) were resolved in PM0.2, PM2.5 and PM2.5–10, respectively. Combined tailpipe and non-tailpipe traffic sources contributed 66%, 32% and 18% of PM0.2, PM2.5 and PM2.5–10 mass, respectively. Tailpipe traffic emissions (EC, OC, B) were the largest contributor to PM0.2 mass (58%). Distinct gasoline and diesel tailpipe traffic sources were resolved in PM2.5. Others included fuel oil, biomass burning, secondary inorganic aerosol, sea salt, and crustal/soil. CALINE4 dispersion model nitrogen oxides, trucks and intersections were most correlated with TRAP sources. The influence of smaller roadways and intersections became more apparent once Long Beach was excluded. Non-tailpipe emissions constituted ~8%, 11% and 18% of PM0.2, PM2.5 and PM2.5–10, respectively, with important exposure and health implications. Future efforts should consider non-linear relationships amongst predictors when modeling exposures.


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