ABSTRACT
During spring 2020, the COVID-19 pandemic caused massive reductions in emissions from industry and ground and airborne transportation. To explore the resulting atmospheric composition changes, we conducted the BLUESKY campaign with two research aircraft and measured trace gases, aerosols, and cloud properties from the boundary layer to the lower stratosphere. From 16 May to 9 June 2020, we performed 20 flights in the early COVID-19 lockdown phase over Europe and the Atlantic Ocean. We found up to 50% reductions in boundary layer nitrogen dioxide concentrations in urban areas from GOME-2B satellite data, along with carbon monoxide reductions in the pollution hot spots. We measured 20%-70% reductions in total reactive nitrogen, carbon monoxide, and fine mode aerosol concentration in profiles over German cities compared to a 10-yr dataset from passenger aircraft. The total aerosol mass was significantly reduced below 5 km altitude, and the organic aerosol fraction also aloft, indicative of decreased organic precursor gas emissions. The reduced aerosol optical thickness caused a perceptible shift in sky color toward the blue part of the spectrum (hence BLUESKY) and increased shortwave radiation at the surface. We find that the 80% decline in air traffic led to substantial reductions in nitrogen oxides at cruise altitudes, in contrail cover, and in resulting radiative forcing. The light extinction and depolarization by cirrus were also reduced in regions with substantially decreased air traffic. General circulation-chemistry model simulations indicate good agreement with the measurements when applying a reduced emission scenario. The comprehensive BLUESKY dataset documents the major impact of anthropogenic emissions on the atmospheric composition.
ABSTRACT
Aerosols influence the Earth's energy balance directly by modifying the radiation transfer and indirectly by altering the cloud microphysics. Anthropogenic aerosol emissions dropped considerably when the global COVID-19 pandemic resulted in severe restraints on mobility, production, and public life in spring 2020. We assess the effects of these reduced emissions on direct and indirect aerosol radiative forcing over Europe, excluding contributions from contrails. We simulate the atmospheric composition with the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model in a baseline (business-as-usual) and a reduced emission scenario. The model results are compared to aircraft observations from the BLUESKY aircraft campaign performed in May-June 2020 over Europe. The model agrees well with most of the observations, except for sulfur dioxide, particulate sulfate, and nitrate in the upper troposphere, likely due to a biased representation of stratospheric aerosol chemistry and missing information about volcanic eruptions. The comparison with a baseline scenario shows that the largest relative differences for tracers and aerosols are found in the upper troposphere, around the aircraft cruise altitude, due to the reduced aircraft emissions, while the largest absolute changes are present at the surface. We also find an increase in all-sky shortwave radiation of 0.21 +/- 0.05 Wm(-2) at the surface in Europe for May 2020, solely attributable to the direct aerosol effect, which is dominated by decreased aerosol scattering of sunlight, followed by reduced aerosol absorption caused by lower concentrations of inorganic and black carbon aerosols in the troposphere. A further increase in shortwave radiation from aerosol indirect effects was found to be much smaller than its variability. Impacts on ice crystal concentrations, cloud droplet number concentrations, and effective crystal radii are found to be negligible.
ABSTRACT
STATEMENT OF PROBLEM/QUESTION: Health care for individuals experiencing homelessness is typically fragmented and passive, and illequipped to meet the complex needs of this population. DESCRIPTION OF PROGRAM/INTERVENTION: The Mobile, Medical, and Mental Health Care Team (M3 Team) is a mobile, patient-centered, integrated care model for people experiencing chronic homelessness with a chronic medical condition, serious mental illness, and substance use disorders. M3 innovates in three ways: 1) M3 is mobile and patient-centered, meeting people where they are - both geographically and in their readiness for engagement;2) M3 is integrated and holistic, integrating primary care, behavioral health care, and health-related social needs across public medical and mental health systems;3) M3 focuses on racial equity to include provider training, prioritization of Black clients, and data disaggregation by race and ethnicity. MEASURES OF SUCCESS: We conducted quarterly assessments of enrolled patients using two standardized scales: (1) self-reported functioning and mental health symptoms using the Behavior and Symptom Identification Scale (BASIS-24), and (2) substance use using the Addiction Severity Index (ASI) drug and alcohol use scales. To assess changes in the dependent variables over time, we used repeated measures ANOVA with time, gender, race, ethnicity, number of comorbidities, and an indicator of whether the measurement was taken before or after the start of the COVID-19 pandemic as independent variables. We also evaluated emergency department utilization and hospitalizations, 6 and 12 months pre- and post-enrollment on the M3 Team (unadjusted results presented here, adjusted analyses currently ongoing and will be presented if accepted). We also tracked enrollment in social programs. FINDINGS TO DATE: 54 clients were enrolled between August 2019 and December 2022. In the 6 months following the start of M3 enrollment, participants experienced decreases in mean severity of mental health symptoms related to depression and functioning (-0.205, p=0.011) and self-harm (-0.055, p=0.008), as well as alcohol use (-0.120, p=0.007) and drug use (-0.065, p=0.001). In the 18 months following M3 initiation, mean severity of symptoms related to depression and functioning (-0.372, p=0.003), self-harm (-0.073, p=0.019), emotional lability (-0.114, p=0.014), and drug use (-0.080, p=0.005) decreased while other domains were not significantly different from baseline values. On average, ED visits post enrollment were significantly lower than pre-enrollment for the 6-month and 12-month measures by 51% and 43%, respectively. Hospitalizations pre- and post-enrollment were not significantly different. Enrollment in a variety of social service programs increased over the enrollment period. KEY LESSONS FOR DISSEMINATION: Delivery models that integrate primary care, behavioral health care, and social services hold promise for improving behavioral health outcomes, reducing ER utilization, and addressing social needs of individuals with complex health needs who are experiencing homelessness.
ABSTRACT
Large-scale pandemic events have sent scientific communities scrambling to gather and analyze data to provide governments and policy makers with information to inform decisions and policies needed when imperfect information is all that may be available. Historical records from the 1918 influenza pandemic reflect how little improvement has been made in how government and policy responses are formed when large scale threats occur, such as the COVID-19 pandemic. This commentary discusses three examples of how metadata improvements are being, or may be made, to facilitate gathering and assessment of data to better understand complex and dynamic situations. In particular, metadata strategies can be applied in advance, on the fly or even after events to integrate and enrich perspectives that aid in creating balanced actions to minimize impacts with lowered risk of unintended consequences. Metadata can enhance scope, speed and clarity with which scholarly communities can curate their outputs for optimal discovery and reuse. Conclusions are framed within the Metadata 2020 working group activities that lay a foundation for advancement of scholarly communications to better serve all communities. © 2020-IOS Press and the authors. All rights reserved.