Operationalizing the net-negative carbon economy.

The remaining carbon budget for limiting global warming to 1.5 degrees Celsius will probably be exhausted within this decade1,2. Carbon debt3 generated thereafter will need to be compensated by net-negative emissions4. However, economic policy instruments to guarantee potentially very costly net carbon dioxide removal (CDR) have not yet been devised. Here we propose intertemporal instruments to provide the basis for widely applied carbon taxes and emission trading systems to finance a net-negative carbon economy5. We investigate an idealized market approach to incentivize the repayment of previously accrued carbon debt by establishing the responsibility of emitters for the net removal of carbon dioxide through 'carbon removal obligations' (CROs). Inherent risks, such as the risk of default by carbon debtors, are addressed by pricing atmospheric CO2 storage through interest on carbon debt. In contrast to the prevailing literature on emission pathways, we find that interest payments for CROs induce substantially more-ambitious near-term decarbonization that is complemented by earlier and less-aggressive deployment of CDR. We conclude that CROs will need to become an integral part of the global climate policy mix if we are to ensure the viability of ambitious climate targets and an equitable distribution of mitigation efforts across generations.

Subcortical tau is linked to hypoperfusion in connected cortical regions in 4-repeat tauopathies.

Four-repeat (4R) tauopathies are neurodegenerative diseases characterized by cerebral accumulation of 4R tau pathology. The most prominent 4R tauopathies are progressive supranuclear palsy (PSP) and corticobasal degeneration characterized by subcortical tau accumulation and cortical neuronal dysfunction, as shown by PET-assessed hypoperfusion and glucose hypometabolism. Yet, there is a spatial mismatch between subcortical tau deposition patterns and cortical neuronal dysfunction, and it is unclear how these two pathological brain changes are interrelated. Here, we hypothesized that subcortical tau pathology induces remote neuronal dysfunction in functionally connected cortical regions to test a pathophysiological model that mechanistically links subcortical tau accumulation to cortical neuronal dysfunction in 4R tauopathies. We included 51 Aß-negative patients with clinically diagnosed PSP variants (n = 26) or corticobasal syndrome (n = 25) who underwent structural MRI and 18F-PI-2620 tau-PET. 18F-PI-2620 tau-PET was recorded using a dynamic one-stop-shop acquisition protocol to determine an early 0.5-2.5 min post tracer-injection perfusion window for assessing cortical neuronal dysfunction, as well as a 20-40 min post tracer-injection window to determine 4R-tau load. Perfusion-PET (i.e. early window) was assessed in 200 cortical regions, and tau-PET was assessed in 32 subcortical regions of established functional brain atlases. We determined tau epicentres as subcortical regions with the highest 18F-PI-2620 tau-PET signal and assessed the connectivity of tau epicentres to cortical regions of interest using a resting-state functional MRI-based functional connectivity template derived from 69 healthy elderly controls from the ADNI cohort. Using linear regression, we assessed whether: (i) higher subcortical tau-PET was associated with reduced cortical perfusion; and (ii) cortical perfusion reductions were observed preferentially in regions closely connected to subcortical tau epicentres. As hypothesized, higher subcortical tau-PET was associated with overall lower cortical perfusion, which remained consistent when controlling for cortical tau-PET. Using group-average and subject-level PET data, we found that the seed-based connectivity pattern of subcortical tau epicentres aligned with cortical perfusion patterns, where cortical regions that were more closely connected to the tau epicentre showed lower perfusion. Together, subcortical tau-accumulation is associated with remote perfusion reductions indicative of neuronal dysfunction in functionally connected cortical regions in 4R-tauopathies. This suggests that subcortical tau pathology may induce cortical dysfunction, which may contribute to clinical disease manifestation and clinical heterogeneity.

Air Quality and Health Implications of Coal Power Retirements Attributed to Industrial Electricity Savings in China.

The coal-dominated electricity system, alongside increasing industrial electricity demand, places China into a dilemma between industrialization and environmental impacts. A practical solution is to exploit air quality and health cobenefits of industrial energy efficiency measures, which has not yet been integrated into China's energy transition strategy. This research examines the pivotal role of industrial electricity savings in accelerating coal plant retirements and assesses the nexus of energy-pollution-health by modeling nationwide coal-fired plants at individual unit level. It shows that minimizing electricity needs by implementing more efficient technologies leads to the phaseout of 1279 hyper-polluting units (subcritical, <300 MW) by 2040, advancing the retirement of these units by an average of 7 years (3-16 years). The retirements at different locations yield varying levels of air quality improvements (9-17%), across six power grids. Reduced exposure to PM2.5 could avoid 123,100 pollution-related cumulative deaths over the next 20 years from 2020, of which ∼75% occur in the Central, East, and North grids, particularly coal-intensive and populous provinces (e.g., Shandong and Jiangsu). These findings provide key indicators to support geographically specific policymaking and lay out a rationale for decision-makers to incorporate multiple benefits into early coal phaseout strategies to avoid lock-in risk.

Calibration by differentiation - Self-supervised calibration for X-ray microscopy using a differentiable cone-beam reconstruction operator.

High-resolution X-ray microscopy (XRM) is gaining interest for biological investigations of extremely small-scale structures. XRM imaging of bones in living mice could provide new insights into the emergence and treatment of osteoporosis by observing osteocyte lacunae, which are holes in the bone of few micrometres in size. Imaging living animals at that resolution, however, is extremely challenging and requires very sophisticated data processing converting the raw XRM detector output into reconstructed images. This paper presents an open-source, differentiable reconstruction pipeline for XRM data which analytically computes the final image from the raw measurements. In contrast to most proprietary reconstruction software, it offers the user full control over each processing step and, additionally, makes the entire pipeline deep learning compatible by ensuring differentiability. This allows fitting trainable modules both before and after the actual reconstruction step in a purely data-driven way using the gradient-based optimizers of common deep learning frameworks. The value of such differentiability is demonstrated by calibrating the parameters of a simple cupping correction module operating on the raw projection images using only a self-supervisory quality metric based on the reconstructed volume and no further calibration measurements. The retrospective calibration directly improves image quality as it avoids cupping artefacts and decreases the difference in grey values between outer and inner bone by 68-94%. Furthermore, it makes the reconstruction process entirely independent of the XRM manufacturer and paves the way to explore modern deep learning reconstruction methods for arbitrary XRM and, potentially, other flat-panel computed tomography systems. This exemplifies how differentiable reconstruction can be leveraged in the context of XRM and, hence, is an important step towards the goal of reducing the resolution limit of in vivo bone imaging to the single micrometre domain.

Intensity interferometry-based 3D imaging.

The development of single-photon counting detectors and arrays has made tremendous steps in recent years, not the least because of various new applications, e.g., LIDAR devices. In this work, a 3D imaging device based on real thermal light intensity interferometry is presented. By using gated SPAD technology, a basic 3D scene is imaged in reasonable measurement time. Compared to conventional approaches, the proposed synchronized photon counting allows the use of more light modes to enhance 3D ranging performance. Advantages like robustness to atmospheric scattering or autonomy by exploiting external light sources can make this ranging approach interesting for future applications.

The Critical Role of Policy Enforcement in Achieving Health, Air Quality, and Climate Benefits from India's Clean Electricity Transition.

The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India's electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14 200 to 59 000 more PM2.5-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM2.5-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO2 in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.

Reducing global air pollution: the scope for further policy interventions.

Over the last decades, energy and pollution control policies combined with structural changes in the economy decoupled emission trends from economic growth, increasingly also in the developing world. It is found that effective implementation of the presently decided national pollution control regulations should allow further economic growth without major deterioration of ambient air quality, but will not be enough to reduce pollution levels in many world regions. A combination of ambitious policies focusing on pollution controls, energy and climate, agricultural production systems and addressing human consumption habits could drastically improve air quality throughout the world. By 2040, mean population exposure to PM2.5 from anthropogenic sources could be reduced by about 75% relative to 2015 and brought well below the WHO guideline in large areas of the world. While the implementation of the proposed technical measures is likely to be technically feasible in the future, the transformative changes of current practices will require strong political will, supported by a full appreciation of the multiple benefits. Improved air quality would avoid a large share of the current 3-9 million cases of premature deaths annually. At the same time, the measures that deliver clean air would also significantly reduce emissions of greenhouse gases and contribute to multiple UN sustainable development goals. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Reduction of solar photovoltaic resources due to air pollution in China.

Solar photovoltaic (PV) electricity generation is expanding rapidly in China, with total capacity projected to be 400 GW by 2030. However, severe aerosol pollution over China reduces solar radiation reaching the surface. We estimate the aerosol impact on solar PV electricity generation at the provincial and regional grid levels in China. Our approach is to examine the 12-year (2003-2014) average reduction in point-of-array irradiance (POAI) caused by aerosols in the atmosphere. We apply satellite-derived surface irradiance data from the NASA Clouds and the Earth's Radiant Energy System (CERES) with a PV performance model (PVLIB-Python) to calculate the impact of aerosols and clouds on POAI. Our findings reveal that aerosols over northern and eastern China, the most polluted regions, reduce annual average POAI by up to 1.5 kWh/m2 per day relative to pollution-free conditions, a decrease of up to 35%. Annual average reductions of POAI over both northern and eastern China are about 20-25%. We also evaluate the seasonal variability of the impact and find that aerosols in this region are as important as clouds in winter. Furthermore, we find that aerosols decrease electricity output of tracking PV systems more than those with fixed arrays: over eastern China, POAI is reduced by 21% for fixed systems at optimal angle and 34% for two-axis tracking systems. We conclude that PV system performance in northern and eastern China will benefit from improvements in air quality and will facilitate that improvement by providing emission-free electricity.

Impact of population growth and population ethics on climate change mitigation policy.

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period's discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing-rather than merely cost savings-again depends on the ethical approach to valuing population.

Air quality, health, and climate implications of China's synthetic natural gas development.

Facing severe air pollution and growing dependence on natural gas imports, the Chinese government plans to increase coal-based synthetic natural gas (SNG) production. Although displacement of coal with SNG benefits air quality, it increases CO2 emissions. Due to variations in air pollutant and CO2 emission factors and energy efficiencies across sectors, coal replacement with SNG results in varying degrees of air quality benefits and climate penalties. We estimate air quality, human health, and climate impacts of SNG substitution strategies in 2020. Using all production of SNG in the residential sector results in an annual decrease of ∼32,000 (20,000 to 41,000) outdoor-air-pollution-associated premature deaths, with ranges determined by the low and high estimates of the health risks. If changes in indoor/household air pollution were also included, the decrease would be far larger. SNG deployment in the residential sector results in nearly 10 and 60 times greater reduction in premature mortality than if it is deployed in the industrial or power sectors, respectively. Due to inefficiencies in current household coal use, utilization of SNG in the residential sector results in only 20 to 30% of the carbon penalty compared with using it in the industrial or power sectors. Even if carbon capture and storage is used in SNG production with today's technology, SNG emits 22 to 40% more CO2 than the same amount of conventional gas. Among the SNG deployment strategies we evaluate, allocating currently planned SNG to households provides the largest air quality and health benefits with the smallest carbon penalties.

Optimal Climate Policy and the Future of World Economic Development.

How much should the present generations sacrifice to reduce emissions today, in order to reduce the future harms of climate change? Within climate economics, debate on this question has been focused on so-called "ethical parameters" of social time preference and inequality aversion. We show that optimal climate policy similarly importantly depends on the future of the developing world. In particular, although global poverty is falling and the economic lives of the poor are improving worldwide, leading models of climate economics may be too optimistic about two central predictions: future population growth in poor countries, and future convergence in total factor productivity (TFP). We report results of small modifications to a standard model: under plausible scenarios for high future population growth (especially in sub-Saharan Africa) and for low future TFP convergence, we find that optimal near-term carbon taxes could be substantially larger.

Global methane emissions from pit latrines.

Pit latrines are an important form of decentralized wastewater management, providing hygienic and low-cost sanitation for approximately one-quarter of the global population. Latrines are also major sources of the greenhouse gas methane (CH4) from the anaerobic decomposition of organic matter in pits. In this study, we develop a spatially explicit approach to account for local hydrological control over the anaerobic condition of latrines and use this analysis to derive a set of country-specific emissions factors and to estimate global pit latrine CH4 emissions. Between 2000 and 2015 we project global emissions to fall from 5.2 to 3.8 Tg y(-1), or from ∼ 2% to ∼ 1% of global anthropogenic CH4 emissions, due largely to urbanization in China. Two and a half billion people still lack improved sanitation services, however, and progress toward universal access to improved sanitation will likely drive future growth in pit latrine emissions. We discuss modeling results in the context of sustainable water, sanitation, and hygiene development and consider appropriate technologies to ensure hygienic sanitation while limiting CH4 emissions. We show that low-CH4 on-site alternatives like composting toilets may be price competitive with other CH4 mitigation measures in organic waste sectors, with marginal abatement costs ranging from 57 to 944 $/ton carbon dioxide equivalents (CO2e) in Africa and 46 to 97 $/ton CO2e in Asia.

Simulation-driven training of vision transformers enables metal artifact reduction of highly truncated CBCT scans.

BACKGROUND: Due to the high attenuation of metals, severe artifacts occur in cone beam computed tomography (CBCT). The metal segmentation in CBCT projections usually serves as a prerequisite for metal artifact reduction (MAR) algorithms. PURPOSE: The occurrence of truncation caused by the limited detector size leads to the incomplete acquisition of metal masks from the threshold-based method in CBCT volume. Therefore, segmenting metal directly in CBCT projections is pursued in this work. METHODS: Since the generation of high quality clinical training data is a constant challenge, this study proposes to generate simulated digital radiographs (data I) based on real CT data combined with self-designed computer aided design (CAD) implants. In addition to the simulated projections generated from 3D volumes, 2D x-ray images combined with projections of implants serve as the complementary data set (data II) to improve the network performance. In this work, SwinConvUNet consisting of shift window (Swin) vision transformers (ViTs) with patch merging as encoder is proposed for metal segmentation. RESULTS: The model's performance is evaluated on accurately labeled test datasets obtained from cadaver scans as well as the unlabeled clinical projections. When trained on the data I only, the convolutional neural network (CNN) encoder-based networks UNet and TransUNet achieve only limited performance on the cadaver test data, with an average dice score of 0.821 and 0.850. After using both data II and data I during training, the average dice scores for the two models increase to 0.906 and 0.919, respectively. By replacing the CNN encoder with Swin transformer, the proposed SwinConvUNet reaches an average dice score of 0.933 for cadaver projections when only trained on the data I. Furthermore, SwinConvUNet has the largest average dice score of 0.953 for cadaver projections when trained on the combined data set. CONCLUSIONS: Our experiments quantitatively demonstrate the effectiveness of the combination of the projections simulated under two pathways for network training. Besides, the proposed SwinConvUNet trained on the simulated projections performs state-of-the-art, robust metal segmentation as demonstrated on experiments on cadaver and clinical data sets. With the accurate segmentations from the proposed model, MAR can be conducted even for highly truncated CBCT scans.

Elevated CSF GAP-43 is associated with accelerated tau accumulation and spread in Alzheimer's disease.

In Alzheimer's disease, amyloid-beta (Aß) triggers the trans-synaptic spread of tau pathology, and aberrant synaptic activity has been shown to promote tau spreading. Aß induces aberrant synaptic activity, manifesting in increases in the presynaptic growth-associated protein 43 (GAP-43), which is closely involved in synaptic activity and plasticity. We therefore tested whether Aß-related GAP-43 increases, as a marker of synaptic changes, drive tau spreading in 93 patients across the aging and Alzheimer's spectrum with available CSF GAP-43, amyloid-PET and longitudinal tau-PET assessments. We found that (1) higher GAP-43 was associated with faster Aß-related tau accumulation, specifically in brain regions connected closest to subject-specific tau epicenters and (2) that higher GAP-43 strengthened the association between Aß and connectivity-associated tau spread. This suggests that GAP-43-related synaptic changes are linked to faster Aß-related tau spread across connected regions and that synapses could be key targets for preventing tau spreading in Alzheimer's disease.

Body weight telemetry is useful to reduce interdialytic weight gain in patients with end-stage renal failure on hemodialysis.

Lacking compliance with liquid intake restrictions is one of the major problems in patients on hemodialysis and causes an increased mortality. In 120 patients on hemodialysis with an average interdialytic weight gain (IWG) exceeding 1.5 kg on at least 2 days during the 4 weeks preceding the intervention, the effect of telemetric body weight measurement (TBWM) on IWG, ultrafiltration rate, and blood pressure was evaluated over a period of 3 months. Patients of the telemetric group (TG) were supplied with automatic scales, which transferred the weight via telemetry on a daily basis. In the case of IWG of more than 0.75 kg/24 h, a telephonic contact was made as required, and in the case of an IWG of more than 1.5 kg, telephonic contacting was obligatory along with the advice of a liquid intake restriction to 0.5 L/day until the next dialysis. The patients of the control group (CG) received standard treatment without telemetric monitoring. We examined specific data of the second interdialytic interval (IDI2) and the average within 1 week. The average difference of IWG between TG and CG was not significant before the start of the study but 0.2 kg (p=0.027) (IDI2)/0.27kg (p=0.001) (WP) at the end of the study, respectively. The average difference in the ultrafiltration rate within 1 week was 19.0 mL/h (p=0.282) (IDI2)/8.2 mL/h (p=0.409) before the start of the study but 28.4 mL/h (p=0.122) (IDI2)/30.9 mL/h (p=0.004) at the end of the study, respectively. Thus, TBWM is a feasible method for optimizing the IWG and reducing the ultrafiltration rate.

Dealing with fixed emissions ceilings in an uncertain future: Offsetting under environmental integrity.

National emission ceilings are a policy instrument to reduce adverse environmental impacts of transboundary air pollution. Such ceilings for SO2, NOx, NH3 and VOC are established, for example, in the Gothenburg Protocol of the Convention on Long-range Transboundary Air Pollution (UNECE, 1999) and the National Emission Ceilings (NEC) Directive of the European Union (EC, 2001a, b). They prescribe for each pollutant a fixed upper limit on emissions for a specific year. Flexibility in achieving them could lower implementation costs if reality develops differently from what was foreseen during negotiations. In this paper, we explore the conditions under which emission reductions for one pollutant (e.g., SO2) could be offset by additional cuts of another pollutant (e.g., NOx) within the same country, without compromising the environmental improvements that are envisaged from the original set of emission ceilings. We employ the impact module of the GAINS (Greenhouse gas - Air pollution Interactions and Synergies) model to examine possible exchange rates across pollutants for the 2012 negotiations on the revision of the Gothenburg Protocol in Europe. Our analysis shows that exchange rates that satisfy the environmental integrity condition can be established, but that their values vary substantially across countries. Extending the environmental integrity condition to downwind countries will require significantly higher exchange rates. We discuss aspects that decision makers would need to consider before adopting an offsetting schema for future international environmental agreements.

Extended Reality Solutions in Medical Context and Educational Approaches.

The healthcare sector is growing in importance as people continue to age and pandemics complicate the boundary conditions of such systems. The number of innovative approaches to solve singular tasks and problems in this area is only slowly increasing. This is particularly evident when looking at medical technology planning, medical training and process simulation. In this paper a concept for versatile digital improvements to these problems by using state of the art development methods of Virtual Reality (VR) and Augmented Reality (AR) are presented. The programming and design of the software is done with the help of Unity Engine, which provides an open interface for docking with the developed framework for future work. The solutions were tested under domain specific environments and have shown good results and positive feedback.

Immersive Spatial Planning in Healthcare: Developing a Pipeline to Automatically Convert Computer Aided DesignData to Virtual Reality.

Equipping rooms used for medical purposes, like e.g., intensive care units, is an expensive and time-consuming task. In order to avoid extensive subsequent adjustments due to inappropriate layout visualization or geometric conditions difficult to identify in 2D plans, it is of utmost importance to provide an optimal planning environment to future users such as physicians and nurses. In this paper we present the concept of a fully automatized pipeline, which is designed to visualize computer aided design (CAD) data using virtual reality (VR). The immersive VR experience results in improvement of efficiency in the decision-making process during the planning phase due to better spatial imagination. The pipeline was successfully tested with CAD data from existing Intensive Care Units. The results indicate that the pipeline can be a valuable tool in the field of spatial planning in healthcare, due to simple usage and fast conversion of CAD data. The next step will be the development of a plugin for CAD tools to allow for interactions with the CAD models in Virtual Reality, which is not yet possible without manual intervention.

New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment.

BACKGROUND: Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America. OBJECTIVES: We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days. METHODS: We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations. RESULTS: The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited. DISCUSSION: The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to better characterize the causal relationship between exposures to PM2.5 and morbidity outcomes.