Governments restricted mobility and effectively shuttered much of the global economy in response to the COVID‐19 pandemic. Six San Francisco Bay Area counties were the first region in the United ...States to issue a “shelter‐in‐place” order asking non‐essential workers to stay home. Here we use CO2 observations from 35 Berkeley Environment, Air‐quality and CO2 Network (BEACO2N) nodes and an atmospheric transport model to quantify changes in urban CO2 emissions due to the order. We infer hourly emissions at 900‐m spatial resolution for 6 weeks before and 6 weeks during the order. We observe a 30% decrease in anthropogenic CO2 emissions during the order and show that this decrease is primarily due to changes in traffic (–48%) with pronounced changes to daily and weekly cycles; non‐traffic emissions show small changes (–8%). These findings provide a glimpse into a future with reduced CO2 emissions through electrification of vehicles.
Plain Language Summary
This work uses atmospheric observations to quantify the changes in urban CO2 emissions from different sectors in response to COVID‐19 mobility regulations.
Key Points
A 30% decrease in urban CO2 emissions was observed from the San Francisco Bay Area in response to COVID‐19 mobility restrictions
Changes are primarily driven by a decrease in CO2 emissions from traffic (–48%)
There is a large change to the weekly and diurnal cycle of emissions with reductions in morning rush hour emissions
Abstract
Governments restricted mobility and effectively shuttered much of the global economy in response to the COVID‐19 pandemic. Six San Francisco Bay Area counties were the first region in the ...United States to issue a “shelter‐in‐place” order asking non‐essential workers to stay home. Here we use CO
2
observations from 35 Berkeley Environment, Air‐quality and CO
2
Network (BEACO
2
N) nodes and an atmospheric transport model to quantify changes in urban CO
2
emissions due to the order. We infer hourly emissions at 900‐m spatial resolution for 6 weeks before and 6 weeks during the order. We observe a 30% decrease in anthropogenic CO
2
emissions during the order and show that this decrease is primarily due to changes in traffic (–48%) with pronounced changes to daily and weekly cycles; non‐traffic emissions show small changes (–8%). These findings provide a glimpse into a future with reduced CO
2
emissions through electrification of vehicles.
Plain Language Summary
This work uses atmospheric observations to quantify the changes in urban CO
2
emissions from different sectors in response to COVID‐19 mobility regulations.
Key Points
A 30% decrease in urban CO
2
emissions was observed from the San Francisco Bay Area in response to COVID‐19 mobility restrictions
Changes are primarily driven by a decrease in CO
2
emissions from traffic (–48%)
There is a large change to the weekly and diurnal cycle of emissions with reductions in morning rush hour emissions
The majority of global anthropogenic CO.sub.2 emissions originate in cities. We have proposed that dense networks are a strategy for tracking changes to the processes contributing to urban CO.sub.2 ...emissions and suggested that a network with â¼ 2 km measurement spacing and â¼ 1 ppm node-to-node precision would be effective at constraining point, line, and area sources within cities. Here, we report on an assessment of the accuracy of the Berkeley Environmental Air-quality and CO.sub.2 Network (BEACO.sub.2 N) CO.sub.2 measurements over several years of deployment. We describe a new procedure for improving network accuracy that accounts for and corrects the temperature-dependent zero offset of the Vaisala CarboCap GMP343 CO.sub.2 sensors used. With this correction we show that a total error of 1.6 ppm or less can be achieved for networks that have a calibrated reference location and 3.6 ppm for networks without a calibrated reference.
The majority of global anthropogenic CO2 emissions originate in cities. We have proposed that dense networks are a strategy for tracking changes to the processes contributing to urban CO2 emissions ...and suggested that a network with ∼ 2 km measurement spacing and ∼ 1 ppm node-to-node precision would be effective at constraining point, line, and area sources within cities. Here, we report on an assessment of the accuracy of the Berkeley Environmental Air-quality and CO2 Network (BEACO2N) CO2 measurements over several years of deployment. We describe a new procedure for improving network accuracy that accounts for and corrects the temperature-dependent zero offset of the Vaisala CarboCap GMP343 CO2 sensors used. With this correction we show that a total error of 1.6 ppm or less can be achieved for networks that have a calibrated reference location and 3.6 ppm for networks without a calibrated reference.
The majority of global anthropogenic CO2 emissions originate in cities. We have proposed that dense networks are a strategy for tracking changes to the processes contributing to urban CO2 emissions ...and suggested that a network with ∼ 2 km measurement spacing and ∼ 1 ppm node-to-node precision would be effective at constraining point, line, and area sources within cities. Here, we report on an assessment of the accuracy of the Berkeley Environmental Air-quality and CO2 Network (BEACO2N) CO2 measurements over several years of deployment. We describe a new procedure for improving network accuracy that accounts for and corrects the temperature-dependent zero offset of the Vaisala CarboCap GMP343 CO2 sensors used. With this correction we show that a total error of 1.6 ppm or less can be achieved for networks that have a calibrated reference location and 3.6 ppm for networks without a calibrated reference.
Understanding urban change in particular for larger regions has been a great demur in both regional planning and geography. One of the main challenges has been linked to the potential of modelling ...urban change. The absence of spatial data and size of areas of study limit the traditional urban monitoring approaches, which also do not take into account visualization techniques that share information with the community. This is the case of the Golden Horseshoe in southern Ontario in Canada, one of the fastest growing regions in North America. An unprecedented change on the urban environment has been witnessed, leading to an increased importance of awareness for future planning in the region. With a population greater than 8 million, the Golden Horseshoe is steadily showing symptoms of becoming a mega-urban region, joining surrounding cities into a single and diversified urban landscape. However, little effort has been done to understand these changes, nor to share information with policy makers, stakeholders and investors. These players are in need of the most diverse information on urban land use, which is seldom available from a single source. The spatio-temporal effect of the growth of this urban region could very well be the birth of yet another North American megacity. Therefore, from a spatial perspective there is demand for joint collaboration and adoption of a regional science perspective including land cover and spatio-temporal configurations. This calls forth a novel technique that allows for assessment of urban and regional change, and supports decision-making without having the usual concerns of locational data availability. It is this sense, that we present a spatial-retrofitting model, with the objective of (i) retrofitting spatial land use based on current land use and land cover, and assessing proportional change in the past, leading to four spatial timestamps of the Golden Horseshoe’s land use, while (ii) integrating this in a multi-user open source web environment to facilitate synergies for decision-making. This combined approach is referred to as a regional-spatial-retrofitting approach (RSRA), where the conclusions permit accurate assessment of land use in past time frames based on Landsat imagery. The RSRA also allows for a collective vision of regional urban growth supporting local governance through a decision-making process adhering to Volunteered Geographic Information Systems. Urban land use change can be refined by means of contribution from end-users through a web environment, leading to a constant understanding and monitoring of urban land use and urban land use change.
Mantle shear velocity (Vs) structure beneath the Transportable Array (TA) in Alaska and northwestern Canada is imaged by joint inversion of Rayleigh wave dispersion and teleseismic S wave travel ...times. The study connects previously unsampled parts of northern and western Alaska with portions of southern Alaska imaged with earlier seismic arrays. The new Vs tomography shows contrasting lithospheric structure in the plate interior with lower Vs shallow upper mantle indicative of thinner thermal lithosphere south of the Brooks Range and along the transform margin. Higher Vs down to ~200 km beneath the Brooks Range and northern coast is consistent with the presence of a cold stable lithospheric root that may help guide intraplate deformation to the south. In the subduction‐to‐transform transition, a potential slab fragment is imaged beneath the Wrangell volcanic field where modern subduction has slowed due to the thick buoyant crust of the Yakutat terrane.
Plain Language Summary
We use a groundbreaking seismic data set from the EarthScope project to investigate the structure of the upper mantle beneath Alaska and northwestern Canada to better understand the effects of ongoing subduction and distinctive blocks within the continental lithosphere. Measurements of seismic body and surface waves are used to construct seismic images from the surface down to 800‐km depth. The images reveal cold thick blocks beneath northern Alaska and the Yukon Territory adjacent to warmer thinner blocks beneath younger geologic provinces to the south, suggesting that cold strong lithosphere in the north helps guide the extent of intraplate deformation driven by the southern plate boundary. The model also identifies a potential slab fragment beneath the Wrangell volcanic field, suggesting slab contributions to volcanic activity and a growing slab tear.
Key Points
Upper mantle Rayleigh and S wave tomography using the full Transportable Array in Alaska
Thick high Vs lithosphere is found beneath the western Brooks Range and Arctic coast
A high Vs potential slab fragment is identified beneath the Wrangell volcanic field
Hope has been conceptualized as agency and pathways to achieve goals. However, this goal-directed conceptualization does not encapsulate all situations in which hope may be beneficial. To address the ...dispositional motivation to endure when a desired goal seems unattainable, unlikely, or even impossible (i.e., goal-transcendent hope), we provide initial psychometric evidence for the new Persevering Hope Scale (PHS). We developed and refined the PHS with undergraduates at a public college (Study 1) and replicated our findings in a community adult sample (Study 2). We replicated and extended these findings using longitudinal data with undergraduates at a faith-based college (Study 3) and a community sample of chronically ill adults (Study 4), and examined measurement invariance (Study 5). Scores on the PHS demonstrated robust evidence of estimated internal consistency and of criterion-related, convergent/discriminant, and incremental validity. Estimated temporal stability was modest. Partial scalar invariance was evidenced across samples, and full scalar invariance was evidenced across gender, race/ethnicity, and time. These preliminary findings suggest that the PHS is a psychometrically sound measure of persevering hope. Its use can broaden the current body of literature on trait hope to include goal-transcendent hope and advance research on the nature and benefits of this important construct.
Objective
This study tested three conceptual explanatory models that have been theorized to account for the linkages between religious/spiritual (R/S) struggles and psychological distress: the ...primary model (i.e., R/S struggles lead to psychological distress), the secondary model (i.e., psychological distress leads to R/S struggles), and the complex model (i.e., R/S struggles and psychological distress reciprocally exacerbate each other).
Methods
Using prospective data from a sample of US adults living with chronic health conditions (n = 302), we performed a cross‐lagged panel analysis with three timepoints to test for evidence of potential causal relations between R/S struggles and psychological distress.
Results
Consistent with the complex conceptual model of R/S struggles, we found evidence of positive reciprocal associations between R/S struggles and psychological distress.
Conclusion
The findings highlight the importance of attending to the dynamic interplay between R/S struggles and psychological distress when working with adults who have chronic health conditions.
•We estimated causal effects of suffering on indices of psychological health.•Suffering was associated with worse mental health and psychological well-being.•Practitioners should consider and attend ...to subjective experiences of suffering.
Suffering has been a topic of considerable discussion in the fields of medicine and palliative care, yet few studies have reported causal evidence linking the experience of suffering to health and well-being. In this three-wave prospective cohort study, we explore the potential psychological implications of suffering during the COVID-19 pandemic by examining relations among suffering, mental health, and psychological well-being in a sample of U.S. adults living with chronic health conditions. We analyzed data from n = 184 participants who completed assessments one month before the SARS-CoV-2 outbreak was declared a pandemic by the World Health Organization (February 2020) and then two months (April 2020) and four months later (May/June 2020). Analyses controlled for a range of factors, including sociodemographic characteristics, physical health, religious/spiritual factors, psychological characteristics, and prior values of the predictor and each of the outcomes assessed one month before the COVID-19 pandemic. Results of the primary analysis indicated that greater overall suffering assessed one month into the COVID-19 pandemic was associated with lower psychological well-being (β = -.17, 95% CI: -.29, -.05) and higher levels of anxiety (β = .27, 95% CI: .13, .41) and depression (β = .16, 95% CI: .03, .29) two months later. In a secondary analysis that explored anxiety, depression, and psychological well-being as candidate antecedents of suffering, depression assessed one month into the COVID-19 pandemic was most strongly associated with worse overall suffering two months later. We highlight the implications of the findings for high-risk populations who are suffering amidst the challenges of the COVID-19 pandemic. Potential benefits of both integrating assessments of suffering into screening procedures and addressing experiences of suffering in mental health service settings are discussed.
PDF
