Bridging and breaking silos: Transformational governance of the migration-sustainability nexus.

Sustainability and migration are typically treated as discrete policy spheres in international, national, and local fora, separated in governance structures and institutions. This results in policy incoherence that hinders just transitions toward more sustainable societies cognizant of mobile realities. This explorative effort identifies the (dis)connections between policy domains using data collected on how the sustainability-migration nexus is governed in four countries with a special emphasis on urban areas: Belgium, the Netherlands, Sweden, and the United States. Results of 73 interviews show that migration and sustainability actors find it challenging to see how they could be working together and that migrants are rarely conceived of as sustainability actors and/or targeted populations of sustainability policy. Despite the cross-sectoral nature of sustainability, it appears that migration and sustainability are sequestered into silos that hinder collaborative actions. Lamenting the existence of silos is not enough to encourage new lines of thinking or practice in how sustainability is governed; therefore, we examine the evidence to ascertain current barriers blocking synergetic governance and the opportunities for change perceived by respondents via three critical elements of transformations toward sustainability: structural, systemic, and enabling conditions. We argue that for sustainability transitions to happen, a wider set of societal actors needs to be included from policy intention to action, but that this transformation may require more than policy integration via horizontal coordination. It demands reflexivity and pluralistic pathways that close vertical gaps between national and municipal levels and diminish structural inequalities as they intersect with migration type and status.

Migration, Embeddedness, and Vulnerability During the COVID-19 Pandemic.

The COVID-19 pandemic and concomitant policy measures have disproportionally affected the lives of migrants worldwide. Focusing on inequalities between social groups, studies have tended to neglect the role of local embeddedness as a factor influencing the extent to which individuals are affected by COVID-19. In this paper, we study the vulnerabilities of people with different migration experiences in an urban setting in the early stages of the pandemic, focusing on three key livelihood assets: economic, social, and human capital (health). Our analyses are based on online survey data (n = 1381) collected among international migrants, second-generation residents (those with at least one parent born abroad), and non-migrants residing in Amsterdam in July 2020. We find that international migrants, and particularly those who arrived in the city more recently, reported larger shocks to their economic and social capital than other city residents. This finding illustrates the vulnerabilities of "newcomers" to the city and their limited resilience to shocks. Second-generation residents were particularly vulnerable in terms of health, but this relationship was strongly mediated by education and neighborhood effects. In all three groups, those with poor relative wealth and those who were self-employed were more vulnerable to economic shocks. Our findings illustrate how the COVID-19 pandemic has exacerbated inequalities in vulnerabilities across migrant and non-migrant groups, and how those who were locally embedded, including migrants and non-migrants, were less likely to be negatively affected by the pandemic.

COVID-19 responses restricted abilities and aspirations for mobility and migration: insights from diverse cities in four continents.

Research on the impacts of COVID-19 on mobility has focused primarily on the increased health vulnerabilities of involuntary migrant and displaced populations. But virtually all migration flows have been truncated and altered because of reduced economic and mobility opportunities of migrants. Here we use a well-established framework of migration decision-making, whereby individual decisions combine the aspiration and ability to migrate, to explain how public responses to the COVID-19 pandemic alter migration patterns among urban populations across the world. The principal responses to COVID-19 pandemic that affected migration are: 1) through travel restrictions and border closures, 2) by affecting abilities to move through economic and other means, and 3) by affecting aspirations to move. Using in-depth qualitative data collected in six cities in four continents (Accra, Amsterdam, Brussels, Dhaka, Maputo, and Worcester), we explore how populations with diverse levels of education and occupations were affected in their current and future mobility decisions. We use data from interviews with sample of internal and international migrants and non-migrants during the 2020 COVID-19 pandemic outbreak to identify the mechanisms through which the pandemic affected their mobility decisions. The results show common processes across the different geographical contexts: individuals perceived increased risks associated with further migration, which affected their migration aspirations, and had reduced abilities to migrate, all of which affected their migration decision-making processes. The results also reveal stark differences in perceived and experienced migration decision-making across precarious migrant groups compared to high-skilled and formally employed international migrants in all settings. This precarity of place is particularly evident in low-income marginalised populations.

Evaluation of the NASA OBPG MERIS ocean surface PAR product in clear sky conditions.

The operational MEdium Resolution Imaging Spectrometer (MERIS) daily mean photosynthetically available radiation (PAR) product generated by the NASA Ocean Biology Processing Group (OBPG) was evaluated in clear sky conditions against in-situ measurements at various sites in the northwestern Mediterranean Sea (BOUSSOLE buoy), the northwestern Pacific (CCE-1 and -2 moorings), and the northeastern Atlantic (COVE platform). The measurements were first checked and corrected for calibration errors and uncertainties in data processing by comparing daily means for clear days (i.e., no clouds from sunrise to sunset and low aerosol abundance) with theoretical values from an accurate Monte Carlo radiative transfer code. The OBPG algorithm performed well when sky was completely cloudless during daytime, with a bias of 0.26 E/m2/d (0.6%) and a RMS difference of 1.7 E/m2/d (4.0%). Using satellite-derived aerosol optical thickness (AOT) and Angström coefficient instead of climatology slightly degraded the results, which was likely due to uncertainties in the aerosol retrievals. A sensitivity study to aerosol properties indicated that climatology may not work in some situations (e.g., episodic dust, pollution, or biomass burning events), suggesting that it is best to use actual aerosol estimates in clear sky conditions. The analysis also revealed that specifying aerosol properties, therefore atmospheric transmittance, from AOT and Angström coefficient, even retrieved from the satellite imagery, may not be sufficient in the presence of absorbing aerosols, especially when loadings are important. Performance was degraded when including situations of clear sky at the time of the MERIS observation but cloudy sky before and/or after overpass, resulting in a bias (overestimation) of 2.8 E/m2/d (7.3%) and a RMS difference of 6.0 E/m2/d (15.8%). The relatively large overestimation was due to the inability of the OBPG PAR algorithm to detect cloudiness at times other than the time of satellite overpass. The key to improving the daily mean PAR estimates in such situations does not reside so much in improving the radiative transfer treatment or specifying more accurately aerosol properties, but rather in accounting properly for the diurnal variability of cloudiness. To this end, a methodology that utilized Modern Era Retrospective Reanalysis for Research and Applications, Version 2 (MERRA-2) hourly cloud data (fractional coverage, optical thickness) was proposed and tested, reducing the bias to 1.6 E/m2/d (4.2%). Improvement was not sufficient in some situations, due to the coarse resolution and uncertainties of the MERRA-2 products, which could not describe properly the cloud properties at the local scale (MERIS pixel). The treatment is applicable to any cloud situation and should be considered in a future version of the of OBPG PAR algorithm. This would require, however, refreshing the standard OBPG PAR products generated as part of the ocean-color processing line according to MERRA-2 data availability.