Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2

We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx , and SO2. Rather than a static assignment of average emission rates to each unit area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N D 44) in this dynamic emission model (a) vary much less over space and time, (b) allow for a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion set-up for the Dutch Rijnmond area at 1km-1km resolution. We find that the fossil fuel emission model approximates the gridded emissions well (annual mean differences < 2 %, hourly temporal r2 D 0:21-0.95), while reported errors in the underlying parameters allow a full covariance structure to be created readily. Propagating this error structure into atmospheric mole fractions shows a strong dominance of a few large sectors and a few dominant uncertainties, most notably the emission ratios of the various gases considered. If the prior emission ratios are either sufficiently well-known or well constrained from a dense observation network, we find that including observations of co-emitted species improves our ability to estimate emissions per sector relative to using CO2 mole fractions only. Nevertheless, the total CO2 emissions can be well constrained with CO2 as the only tracer in the inversion. Because some sectors are sampled only sparsely over a day, we find that propagating solutions from day-to-day leads to largest uncertainty reduction and smallest CO2 residuals over the 14 consecutive days considered. Although we can technically estimate the temporal distribution of some emission categories like shipping separate from their total magnitude, the controlling parameters are difficult to distinguish. Overall, we conclude that our new system looks promising for application in verification studies, provided that reliable urban atmospheric transport fields and reasonable a priori emission ratios for CO2 and its co-emitted species can be produced

Diurnal variability of atmospheric O-2, CO2, and their exchange ratio above a boreal forest in southern Finland

The exchange ratio (ER) between atmospheric O(2 )and CO2 is a useful tracer for better understanding the carbon budget on global and local scales. The variability of ER (in mol O(2 )per mol CO2) between terrestrial ecosystems is not well known, and there is no consensus on how to derive the ER signal of an ecosystem, as there are different approaches available, either based on concentration (ERatmos) or flux measurements (ERforest). In this study we measured atmospheric O-2 and CO2 concentrations at two heights (23 and 125 m) above the boreal forest in Hyytiala, Finland. Such measurements of O-2 are unique and enable us to potentially identify which forest carbon loss and production mechanisms dominate over various hours of the day. We found that the ERatmos signal at 23 m not only represents the diurnal cycle of the forest exchange but also includes other factors, including entrainment of air masses in the atmospheric boundary layer before midday, with different thermodynamic and atmospheric composition characteristics. To derive ERforest, we infer O(2 )fluxes using multiple theoretical and observation-based micro-meteorological formulations to determine the most suitable approach. Our resulting ERforest shows a distinct difference in behaviour between daytime (0.92 +/- 0.17 mol mol(-1)) and nighttime (1.03 +/- 0.05 mol mol(-1)). These insights demonstrate the diurnal variability of different ER signals above a boreal forest, and we also confirmed that the signals of ERatmos and ERforest cannot be used interchangeably. Therefore, we recommend measurements on multiple vertical levels to derive O-2 and CO2 fluxes for the ERforest signal instead of a single level time series of the concentrations for the ERatmos signal. We show that ERforest can be further split into specific signals for respiration (1.03 +/-; 0.05 mol mol-1) and photosynthesis (0.96 +/- 0.12 molmol(-1)). This estimation allows us to separate the net ecosystem exchange (NEE) into gross primary production (GPP) and total ecosystem respiration (TER), giving comparable results to the more commonly used eddy covariance approach. Our study shows the potential of using atmospheric O-2 as an alternative and complementary method to gain new insights into the different CO2 signals that contribute to the forest carbon budget.Peer reviewe

Global atmospheric CO₂ inverse models converging on neutral tropical land exchange, but disagreeing on fossil fuel and atmospheric growth rate

We have compared a suite of recent global CO₂ atmospheric inversion results to independent airborne observations and to each other, to assess their dependence on differences in northern extratropical (NET) vertical transport and to identify some of the drivers of model spread. We evaluate posterior CO₂ concentration profiles against observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) aircraft campaigns over the mid-Pacific in 2009–2011. Although the models differ in inverse approaches, assimilated observations, prior fluxes, and transport models, their broad latitudinal separation of land fluxes has converged significantly since the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3) and the REgional Carbon Cycle Assessment and Processes (RECCAP) projects, with model spread reduced by 80 % since TransCom 3 and 70 % since RECCAP. Most modeled CO₂ fields agree reasonably well with the HIPPO observations, specifically for the annual mean vertical gradients in the Northern Hemisphere. Northern Hemisphere vertical mixing no longer appears to be a dominant driver of northern versus tropical (T) annual flux differences. Our newer suite of models still gives northern extratropical land uptake that is modest relative to previous estimates (Gurney et al., 2002; Peylin et al., 2013) and near-neutral tropical land uptake for 2009–2011. Given estimates of emissions from deforestation, this implies a continued uptake in intact tropical forests that is strong relative to historical estimates (Gurney et al., 2002; Peylin et al., 2013). The results from these models for other time periods (2004–2014, 2001–2004, 1992–1996) and re-evaluation of the TransCom 3 Level 2 and RECCAP results confirm that tropical land carbon fluxes including deforestation have been near neutral for several decades. However, models still have large disagreements on ocean–land partitioning. The fossil fuel (FF) and the atmospheric growth rate terms have been thought to be the best-known terms in the global carbon budget, but we show that they currently limit our ability to assess regional-scale terrestrial fluxes and ocean–land partitioning from the model ensemble

Facilitators and Barriers in the Implementation and Adoption of Patient-Reported Outcomes Measurements in Daily Practice

Objectives: At the Erasmus Medical Center, patient-reported outcomes measures (PROMs) are implemented on a hospital-wide scale. However, less than half of the patients and healthcare professionals (HCPs) use these PROMs. Therefore, this study aimed to investigate facilitators and barriers for adoption of PROMs to develop guidance around implementation. Methods: A mixed-methods study with a combination of interviews and focus groups and questionnaires was conducted, involving patients, both PROM nonresponders and PROM responders, HCPs, and medicine students and nurse specialists in training (hereafter “students”). Interview transcripts were subjected to thematic content analysis. Subsequently, questionnaires were developed and presented to all stakeholders to validate the findings. Finally, identified themes and implementation recommendations were presented in a final questionnaire to the Value-Based Healthcare Erasmus Medical Center expert group to prioritize findings. Results: Interviews were conducted with 15 patients, 14 HCPs and 4 students, and 2 focus groups with 5 students. The questionnaire was completed by 370 of 999 responders (37.0%), 173 of 1395 nonresponders (12.5%), and 44 of 194 HCPs (22.7%), and 40 students were reached via an open link. The identified facilitators and barriers were grouped into 4 overarching themes: training on PROMs at different levels in the education of (future) HCPs, motivate and reduce the burden for the HCP, implement generic and disease-specific PROMs simultaneously, and motivate, activate, and reduce the patient burden. Conclusions: Providing end users with digital tools, implementation support, and a clear hospital-wide vision is important, yet this does not guarantee successful adoption of PROMs. Successful adoption necessitates ongoing efforts to engage, motivate, and train end users.</p

Global 3-D Simulations of the Triple Oxygen Isotope Signature Δ17O in Atmospheric CO2

The triple oxygen isotope signature Δ¹⁷O in atmospheric CO₂, also known as its “¹⁷O excess,” has been proposed as a tracer for gross primary production (the gross uptake of CO₂ by vegetation through photosynthesis). We present the first global 3-D model simulations for Δ¹⁷O in atmospheric CO₂ together with a detailed model description and sensitivity analyses. In our 3-D model framework we include the stratospheric source of Δ¹⁷O in CO₂ and the surface sinks from vegetation, soils, ocean, biomass burning, and fossil fuel combustion. The effect of oxidation of atmospheric CO on Δ¹⁷O in CO2 is also included in our model. We estimate that the global mean Δ¹⁷O (defined as Δ¹⁷O = ln( ¹⁷O + 1) − RL · ln( ¹⁸O + 1) with RL = 0.5229) of CO₂ in the lowest 500 m of the atmosphere is 39.6 per meg, which is ∼20 per meg lower than estimates from existing box models. We compare our model results with a measured stratospheric Δ¹⁷O in CO₂ profile from Sodankylä (Finland), which shows good agreement. In addition, we compare our model results with tropospheric measurements of Δ¹⁷O in CO₂ from Göttingen (Germany) and Taipei (Taiwan), which shows some agreement but we also find substantial discrepancies that are subsequently discussed. Finally, we show model results for Zotino (Russia), Mauna Loa (United States), Manaus (Brazil), and South Pole, which we propose as possible locations for future measurements of Δ¹⁷O in tropospheric CO₂ that can help to further increase our understanding of the global budget of Δ¹⁷O in atmospheric CO₂

The association between palliative care team consultation and hospital costs for patients with advanced cancer: An observational study in 12 Dutch hospitals

Background: Early palliative care team consultation has been shown to reduce costs of hospital care. The objective of this study was to investigate the association between palliative care team (PCT) consultation and the content and costs of hospital care in patients with advanced cancer. Material and Methods: A prospective, observational study was conducted in 12 Dutch hospitals.

Sex differences in cardiometabolic risk factors, pharmacological treatment and risk factor control in type 2 diabetes:findings from the Dutch Diabetes Pearl cohort

Introduction Sex differences in cardiometabolic risk factors and their management in type 2 diabetes (T2D) have not been fully identified. Therefore, we aimed to examine differences in cardiometabolic risk factor levels, pharmacological treatment and achievement of risk factor control between women and men with T2D. Research design and methods Cross-sectional data from the Dutch Diabetes Pearl cohort were used (n=6637, 40% women). Linear and Poisson regression analyses were used to examine sex differences in cardiometabolic risk factor levels, treatment, and control. Results Compared with men, women had a significantly higher body mass index (BMI) (mean difference 1.79 kg/m 2 (95% CI 1.49 to 2.08)), while no differences were found in hemoglobin A 1c (HbA 1c) and systolic blood pressure (SBP). Women had lower diastolic blood pressure (-1.94 mm Hg (95% CI -2.44 to -1.43)), higher total cholesterol (TC) (0.44 mmol/L (95% CI 0.38 to 0.51)), low-density lipoprotein cholesterol (LDL-c) (0.26 mmol/L (95% CI 0.22 to 0.31)), and high-density lipoprotein cholesterol (HDL-c) sex-standardized (0.02 mmol/L (95% CI 0.00 to 0.04)), and lower TC:HDL ratio (-0.29 (95% CI -0.36 to -0.23)) and triglycerides (geometric mean ratio 0.91 (95% CI 0.85 to 0.98)). Women had a 16% higher probability of being treated with antihypertensive medication in the presence of high cardiovascular disease (CVD) risk and elevated SBP than men (relative risk 0.84 (95% CI 0.73 to 0.98)), whereas no sex differences were found for glucose-lowering medication and lipid-modifying medication. Among those treated, women were less likely to achieve treatment targets of HbA 1c (0.92 (95% CI 0.87 to 0.98)) and LDL-c (0.89 (95% CI 0.85 to 0.92)) than men, while no differences for SBP were found. Conclusions In this Dutch T2D population, women had a slightly different cardiometabolic risk profile compared with men and a substantially higher BMI. Women had a higher probability of being treated with antihypertensive medication in the presence of high CVD risk and elevated SBP than men, and were less likely than men to achieve treatment targets for HbA 1c and LDL levels

Autochthonous heritage languages and social media:writing and bilingual practices in Low German on Facebook

This article analyses how speakers of an autochthonous heritage language (AHL) make use of digital media, through the example of Low German, a regional language used by a decreasing number of speakers mainly in northern Germany. The focus of the analysis is on Web 2.0 and its interactive potential for individual speakers. The study therefore examines linguistic practices on the social network site Facebook, with special emphasis on language choice, bilingual practices and writing in the autochthonous heritage language. The findings suggest that social network sites such as Facebook have the potential to provide new mediatized spaces for speakers of an AHL that can instigate sociolinguistic change

Efficient Capture of Infected Neutrophils by Dendritic Cells in the Skin Inhibits the Early Anti-Leishmania Response

Neutrophils and dendritic cells (DCs) converge at localized sites of acute inflammation in the skin following pathogen deposition by the bites of arthropod vectors or by needle injection. Prior studies in mice have shown that neutrophils are the predominant recruited and infected cells during the earliest stage of Leishmania major infection in the skin, and that neutrophil depletion promotes host resistance to sand fly transmitted infection. How the massive influx of neutrophils aimed at wound repair and sterilization might modulate the function of DCs in the skin has not been previously addressed. The infected neutrophils recovered from the skin expressed elevated apoptotic markers compared to uninfected neutrophils, and were preferentially captured by dermal DCs when injected back into the mouse ear dermis. Following challenge with L. major directly, the majority of the infected DCs recovered from the skin at 24 hr stained positive for neutrophil markers, indicating that they acquired their parasites via uptake of infected neutrophils. When infected, dermal DCs were recovered from neutrophil depleted mice, their expression of activation markers was markedly enhanced, as was their capacity to present Leishmania antigens ex vivo. Neutrophil depletion also enhanced the priming of L. major specific CD4+ T cells in vivo. The findings suggest that following their rapid uptake by neutrophils in the skin, L. major exploits the immunosuppressive effects associated with the apoptotic cell clearance function of DCs to inhibit the development of acquired resistance until the acute neutrophilic response is resolved