Bottom-up Research Articles

Carbon and Greenhouse Gas Budgets of Europe: Trends, Interannual and Spatial Variability, and Their Drivers

AbstractIn the framework of the RECCAP2 initiative, we present the greenhouse gas (GHG) and carbon (C) budget of Europe. For the decade of the 2010s, we present a bottom‐up (BU) estimate of GHG net‐emissions of 3.9 Pg CO2‐eq. yr−1 (using a global warming potential on a 100 years horizon), which are largely dominated by fossil fuel emissions. In this decade, terrestrial ecosystems acted as a net GHG sink of 0.9 Pg CO2‐eq. yr−1, dominated by a CO2 sink that was partially counterbalanced by net emissions of CH4 and N2O. For CH4 and N2O, we find good agreement between BU and top‐down (TD) estimates from atmospheric inversions. However, our BU land CO2 sink is significantly higher than the TD estimates. We further show that decadal averages of GHG net‐emissions have declined by 1.2 Pg CO2‐eq. yr−1 since the 1990s, mainly due to a reduction in fossil fuel emissions. In addition, based on both data driven BU and TD estimates, we also find that the land CO2 sink has weakened over the past two decades. A large part of the European CO2 and C sinks is located in Northern Europe. At the same time, we find a decreasing trend in sink strength in Scandinavia, which can be attributed to an increase in forest management intensity. These are partly offset by increasing CO2 sinks in parts of Eastern Europe and Northern Spain, attributed in part to land use change. Extensive regions of high CH4 and N2O emissions are mainly attributed to agricultural activities and are found in Belgium, the Netherlands and the southern UK. We further analyzed interannual variability in the GHG budgets. The drought year of 2003 shows the highest net‐emissions of CO2 and of all GHGs combined.

Revisiting the Global Methane Cycle Through Expert Opinion

AbstractAn accurate quantification of global methane sources and sinks is imperative for assessing realistic pathways to mitigate climate change. A key challenge of quantifying the Global Methane Budget (Saunois et al., 2020, https://doi.org/10.5194/essd‐12‐1561‐2020) is the lack of consistency in uncertainties between sectors. Here we provide a new perspective on bottom‐up (BU) and top‐down (TD) methane uncertainties by using an expert opinion analysis based on a questionnaire conducted in 2021. Expectedly, experts rank highest uncertainty and lowest confidence levels in the Global Methane Budget related to natural sources in BU budgets. Here, we further reveal specific uncertainty types and introduce a ranking system for uncertainties in each sector. We find that natural source uncertainty is related particularly to driver data uncertainty in freshwater, vegetation, and coastal/ocean sources, as well as parameter uncertainty in wetland models. Reducing uncertainties, most notably in aquatic and wetland sources will help balance future BU and TD global methane budgets. We suggest a new methane source partitioning over gradients of human disturbance and demonstrate that 76.3% (75.8%–79.4%) or 561 (443–700) Tg CH4 yr−1 of global emissions can be attributed to moderately impacted, man‐made, artificial, or fully anthropogenic sources and 23.7% (20.6%–24.2%) or 174 (115–223) Tg CH4 yr−1 to natural and low impacted methane sources. Finally, we identify current research gaps and provide a plan of action to reduce current uncertainties in the Global Methane Budget.

Synthesis of C-Dots Based on Bitter Melon Peel using the Bottom UP Method

There is an increasing demand for creative ways to turn garbage into useful resources as environmental sustainability becomes more and more of a global concern. Carbon dots can be synthesized using organic materials, one of which is bitter melon skin. The goal of this research is to create an economical and environmentally friendly process for creating carbon dots from organic waste. The bitter melon peel synthesis process uses a bottom-up method with microwave techniques. Furthermore, c-dots were characterized using a UV-Vis spectrophotometer to determine the absorbance value and wavelength and FTIR (Fourier Transform Infra-Red) to determine the functional groups contained in the sample. The UV-Vis spectrophotometer characterization results obtained an absorbance value of 3.311 and a wavelength of 206 nm. FTIR results show the presence of O-H and C=C functional group bonds indicating that this synthesis process has been successfully carried out.Keyword: Carbon Dots, Bitter Melon Peel, Bottom-up

Greenhouse gas emissions and their trends over the last 3 decades across Africa

Abstract. A key goal of the Paris Agreement (PA) is to reach net-zero greenhouse gas (GHG) emissions by 2050 globally, which requires mitigation efforts from all countries. Africa's rapidly growing population and gross domestic product (GDP) make this continent important for GHG emission trends. In this paper, we study the emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in Africa over 3 decades (1990–2018). We compare bottom-up (BU) approaches, including United Nations Convention Framework on Climate Change (UNFCCC) national inventories, FAO, PRIMAP-hist, process-based ecosystem models for CO2 fluxes in the land use, land use change and forestry (LULUCF) sector and global atmospheric inversions. For inversions, we applied different methods to separate anthropogenic CH4 emissions. The BU inventories show that, over the decade 2010–2018, fewer than 10 countries represented more than 75 % of African fossil CO2 emissions. With a mean of 1373 Mt CO2 yr−1, total African fossil CO2 emissions over 2010–2018 represent only 4 % of global fossil emissions. However, these emissions grew by +34 % from 1990–1999 to 2000–2009 and by +31 % from 2000–2009 to 2010–2018, which represents more than a doubling in 30 years. This growth rate is more than 2 times faster than the global growth rate of fossil CO2 emissions. The anthropogenic emissions of CH4 grew by 5 % from 1990–1999 to 2000–2009 and by 14.8 % from 2000–2009 to 2010–2018. The N2O emissions grew by 19.5 % from 1990–1999 to 2000–2009 and by 20.8 % from 2000–2009 to 2010–2018. When using the mean of the estimates from UNFCCC reports (including the land use sector) with corrections from outliers, Africa was a mean source of greenhouse gases of 262221863239 Mt CO2 eq. yr−1 from all BU estimates (the subscript and superscript indicate min–max range uncertainties) and of +263717615873 Mt CO2 eq. yr−1 from top-down (TD) methods during their overlap period from 2001 to 2017. Although the mean values are consistent, the range of TD estimates is larger than the one of the BU estimates, indicating that sparse atmospheric observations and transport model errors do not allow us to use inversions to reduce the uncertainty in BU estimates. The main source of uncertainty comes from CO2 fluxes in the LULUCF sector, for which the spread across inversions is larger than 50 %, especially in central Africa. Moreover, estimates from national UNFCCC communications differ widely depending on whether the large sinks in a few countries are corrected to more plausible values using more recent national sources following the methodology of Grassi et al. (2022). The medians of CH4 emissions from inversions based on satellite retrievals and surface station networks are consistent with each other within 2 % at the continental scale. The inversion ensemble also provides consistent estimates of anthropogenic CH4 emissions with BU inventories such as PRIMAP-hist. For N2O, inversions systematically show higher emissions than inventories, on average about 4.5 times more than PRIMAP-hist, either because natural N2O sources cannot be separated accurately from anthropogenic ones in inversions or because BU estimates ignore indirect emissions and underestimate emission factors. Future improvements can be expected thanks to a denser network of monitoring atmospheric concentrations. This study helps to introduce methods to enhance the scope of use of various published datasets and allows us to compute budgets thanks to recombinations of those data products. Our results allow us to understand uncertainty and trends in emissions and removals in a region of the world where few observations exist and where most inventories are based on default IPCC guideline values. The results can therefore serve as a support tool for the Global Stocktake (GST) of the Paris Agreement. The referenced datasets related to the figures are available at https://doi.org/10.5281/zenodo.7347077 (Mostefaoui et al., 2022).

Interaction between top-down decision-driven congruency effect and bottom-up input-driven congruency effect is correlated with conscious awareness.

In a conventional (Stroop) priming paradigm, it was well documented that objective prime-target incongruency delays response time (RT) to target compared to prime-target congruent condition. Recent evidence suggests that incongruency between the target and subjectively reported prime identity also delays RT over and above the classic congruency effect. When the prime is rendered invisible, the former effect is fundamentally a bottom-up (BU) stimulus-driven congruency effect and the latter a top-down (TD) guess-driven congruency effect. An influential theory of consciousness, global neuronal workspace theory, postulates that the long-lasting simultaneous and reciprocal interaction between TD decision network and BU input network is preserved during conscious processing and disabled during unconscious processing. Current study is focused on testing this theoretical postulation using two behavioral experiments. Our results showed that indeed TD-congruency and BU-congruency produced additive RT effects on prime-invisible trials, which implies that TD and BU prime representations are activated in independent neuronal populations. Meanwhile, an underadditive interaction effect was observed as prime visibility rose, which is a signature that TD and BU prime representations recruited overlapping neuronal populations during conscious perception. In addition, we suggest that current behavioral paradigm might be a financially friendly alternative to detect the presence of representational overlap in the brain between a wide range of mental representations, such as expectation, prediction, conscious/unconscious perception, and conscious/unconscious working memory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Informing Methane Emissions Inventories Using Facility Aerial Measurements at Midstream Natural Gas Facilities.

Increased interest in greenhouse gas (GHG) emissions, including recent legislative action and voluntary programs, has increased attention on quantifying and ultimately reducing methane emissions from the natural gas supply chain. While inventories used for public or corporate GHG policies have traditionally utilized bottom-up (BU) methods to estimate emissions, the validity of such inventories has been questioned. Therefore, there is attention on utilizing full-facility measurements using airborne, satellite, or drone (top-down (TD)) techniques to inform, improve, or validate inventories. This study utilized full-facility estimates from two independent TD methods at 15 midstream natural gas facilities in the U.S.A., which were compared with a contemporaneous daily inventory assembled by the facility operator, employing comprehensive inventory methods. Estimates from the two TD methods statistically agreed in 2 of 28 paired measurements. Operator inventories, which included extensions to capture sources beyond regular inventory requirements and integration of local measurements, estimated significantly lower emissions than the TD estimates for 40 of 43 paired comparisons. Significant disagreement was observed at most facilities, both between the two TD methods and between the TD estimates and operator inventory. These findings have two implications. First, improving inventory estimates will require additional on-site or ground-based diagnostic screening and measurement of all sources. Second, the TD full-facility measurement methods need to undergo further testing, characterization, and potential improvement specifically tailored for complex midstream facilities.

A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations

Achieving climate neutrality by 2050 requires ground-breaking technological and methodological advancements in climate change mitigation planning and actions from local to regional scales. Monitoring the cities' CO2 emissions with sufficient detail and accuracy is crucial for guiding sustainable urban transformation. Current methodologies for CO2 emission inventories rely on bottom-up (BU) approaches which do not usually offer information on the spatial or temporal variability of the emissions and present substantial uncertainties. This study develops a novel approach which assimilates direct CO2 flux observations from urban eddy covariance (EC) towers with very high spatiotemporal resolution information from an advanced urban BU surface flux model (Part 1 of this study, Stagakis et al., 2023) within a Bayesian inversion framework. The methodology is applied to the city centre of Basel, Switzerland (3 × 3 km domain), taking advantage of two long-term urban EC sites located 1.6 km apart. The data assimilation provides optimised gridded CO2 flux information individually for each urban surface flux component (i.e. building heating emissions, commercial/industrial emissions, traffic emissions, human respiration emissions, biogenic net exchange) at 20 m resolution and weekly time-step. The results demonstrate that urban EC observations can be consistently used to improve high-resolution BU surface CO2 flux model estimations, providing realistic seasonal variabilities of each flux component. Traffic emissions are determined with the greatest confidence among the five flux components during the inversions. The optimised annual anthropogenic emissions are 14.7 % lower than the prior estimate, the human respiration emissions have decreased by 12.1 %, while the biogenic components transformed from a weak sink to a weak source. The root-mean-square errors (RMSEs) of the weekly comparisons between EC observations and model outputs are consistently reduced. However, a slight underestimation of the total flux, especially in locations with complex CO2 source/sink mixture, is still evident in the optimised fluxes.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking systemto examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Posttranslational-modifications of human-serum-albumin analysis by a top-down approach validated by a comprehensive bottom-up analysis

The posttranslational modifications (PTM) of human serum albumin (HSA) can result in the development of isoforms that have been identified as potential biomarkers for advanced hepatic diseases. However, previous approaches using top-down (TD) analysis to identify isoforms based on molecular weight may have resulted in misidentifications. The nature of the identified isoforms has never been confirmed in previous works. Here, we aimed to critically evaluate TD for the characterization and determination of HSA isoforms in patients and make an inventory of HSA-PTM.Serum samples from control subjects and patients with liver dysfunctions were analyzed using both top-down (TD) and bottom-up (BU) approaches. TD analysis involved using a LC-TOF-MS system to obtain a multicharged spectrum of HSA, which was deconvoluted to identify isoforms. Spectra were then used for relative quantitation analysis of albumin isoform abundances based on trapezoidal integration. For BU analysis, serums were reduced +/- alkylated, digested with trypsin and analyzed in the Q-TOF, data-dependent acquisition (DDA) mode to generate a SWATH-MS high-resolution mass spectral library of all HSA peptides. Tryptic digests of another set of serum samples were then analyzed using data-independent acquisition (DIA) mode to confirm the presence of HSA isoforms and their modification sites.TD detected 15 isoforms corresponding to various modifications, including glycation, cysteinylation, nitrosylation, and oxidation (di- and tri-). In BU, the spectral library containing 127 peptides allowed for the characterization of the important isoforms with their modified sites, including some modifications that were only characterized in BU (carbamylation, deamidation, and amino-acid substitution). The method used for determining isoforms offered acceptable reproducibility (intra-/inter-assay CVs < 15%) for all isoforms present at relative abundances higher than 2%.Overall, the study found that several isoforms could be missed or misidentified by TD. However, all HSA isoforms identified by TD and reported to be relevant in liver dysfunctions were confirmed by BU. This critical evaluation of TD approach helped design an adequate and reliable method for the characterization of HSA isoforms in patients and offers the possibility to estimate isoform abundances within 3 min. These findings have significant implications for the diagnosis and treatment of liver dysfunctions.

The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019

Abstract. Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).

Efficiency of TB service provision in the public and private health sectors in Ethiopia.

BACKGROUND: The Ethiopian Government has identified efficiency of TB services as a key priority in planning and budgeting. Understanding the magnitude and sources of inefficiencies is key to ensuring value for money and improved service provision, and a requirement from donors to justify resource needs. This study identifies the cost of providing a wide range of TB services in public and private facilities in Ethiopia.METHODS: Financial and economic unit costs were estimated from a health provider´s perspective, and collected retrospectively in 26 health facilities using both top-down (TD) and bottom-up (BU) costing approaches for each TB service output. Capacity inefficiency was assessed by investigating the variation between TD and BU unit costs where the factor was 2.0 or more.RESULTS: Overall, TD unit costs were two times higher than BU unit costs. There was some variation across facility ownership and level of care. Unit costs in urban facilities were on average 3.8 times higher than in rural facilities.CONCLUSION: We identified some substantial inefficiencies in staff, consumable and capital inputs. Addressing these inefficiencies and rearranging the TB service delivery modality would be important in ensuring the achievement of the country´s End TB strategy.

A high-resolution monitoring approach of urban CO2 fluxes. Part 1 - bottom-up model development

Monitoring carbon dioxide (CO2) emissions of urban areas is increasingly important to assess the progress towards the Paris Agreement goals for climate neutrality. Cities are currently voluntarily developing their local inventories, however, the approaches used across different cities are not systematically assessed, present consistency issues, neglect the biogenic fluxes and have restricted spatial and temporal resolution. In order to assess the accuracy of the urban emission inventories and provide information which is useful for planning local climate change mitigation actions, high resolution modelling approaches combined or evaluated with atmospheric observations are needed. This study presents a new high-resolution bottom-up (BU) model which provides hourly maps of all major components contributing to the local urban surface CO2 flux (i.e. building emissions, traffic emissions, human respiration, soil respiration, plant respiration, plant photosynthetic uptake) and can therefore be used for direct comparison with in-situ atmospheric observations and development of local scale atmospheric inversion methodologies. The model design aims to be simple and flexible using inputs that are available in most cities, facilitating transferability to different locations. The inputs are primarily based on open geospatial datasets, census information, road traffic monitoring and basic meteorological parameters. The model is applied on the city centre of Basel, Switzerland, for the year 2018 and the results are compared to a local inventory. It is demonstrated that the model captures the highly dynamic spatiotemporal variability of the urban CO2 fluxes according to main environmental drivers, population activity dynamics and geospatial information proxies. The annual modelled emissions from buildings and traffic are estimated 14.8 % and 9 % lower than the respective information derived by the local inventory. The differences are mainly attributed to the emissions from the industrial areas and the highways which are beyond the geographical coverage of the model.

Temporal Hierarchical Reconciliation for Consistent Water Resources Forecasting Across Multiple Timescales: An Application to Precipitation Forecasting

AbstractObtaining consistent forecasts at different timescales is important for reliable decision‐making. This study introduces and evaluates the benefits of utilizing temporal hierarchical reconciliation methods for water resources forecasting, with an application to precipitation. Original (precipitation) Forecasts (ORFs) were produced using “automatic” Exponential Time‐Series Smoothing (ETS), Artificial Neural Network (ANN), and Seasonal Auto‐Regressive Integrated Moving Average (SARIMA) models at six timescales, namely, monthly, 2‐monthly, quarterly, 4‐monthly, bi‐annual, and annual, for 84 basins extracted from the Canadian model parameter experiment. Temporal hierarchical reconciliation methods, including structural scaling‐based Weighted Least Squares (WLS), series variance scaling‐based WLS, and Ordinary Least Squares, along with the simple Bottom‐Up (BU) method, were applied to reconcile the forecasts. In general, ETS (direct forecasting) demonstrated better performance compared to ANN and SARIMA (recursive forecasting). The results confirmed that improvements in accuracy due to reconciliation is dependent on the basin, timescale, and the ORFs' accuracy. For different forecast models, the reconciliation methods showed different levels of performance. For ETS, BU was able to improve forecast accuracy to a greater extent than the temporal hierarchical reconciliation methods, while for ANN and SARIMA, forecast accuracy was improved through all temporal hierarchical reconciliation methods but not BU. The reconciled forecasts' accuracy was affected more by the ORFs' accuracy than by the reconciliation method. Different timescales showed dissimilar sensitivity to reconciliation. The presented results are anticipated to serve as a valuable benchmark for evaluating future developments in the promising area of temporal hierarchical reconciliation for water resources forecasting.

Cost of TB prevention and treatment in the Philippines in 2017.

SUMMARYBACKGROUND :The Philippines aims to accelerate TB reduction through the provision of universally accessible and affordable services. The objectives of this paper are to estimate the costs of TB services and interventions using a health systems’ perspective, and to explore cost differences in service delivery via primary care facilities or hospitals.METHODS :Data were collected from a multi-stage stratified random sampling of 28 facilities in accordance with Global Health Cost Consortium costing standards and analysis tools. Unit costs (in US$) estimated using top-down (TD) and bottom-up (BU) approaches, are summarised following Value TB reporting standards and by broad facility type.RESULTS :Cost of delivering 32 TB services and eight interventions varied by costing method and delivery platform. Average BU costs ranged from US$0.38 for treatment support visits, US$2.5 for BCG vaccination, US$19.48 for the Xpert® MTB/RIF test to US$3,677 for MDR-TB treatment using the long regimen. Delivering TB care in hospitals was generally more costly than in primary care facilities, except for TB prevention in children and MDR-TB treatment using the long regimen.CONCLUSION :Comprehensive costing data for TB care in the Philippines are now available to aid in the design, planning, and prioritisation of delivery models to End TB.

Predicting fatigue service life reductions of asphalt pavements due to deficiency in design-level values of effective binder content

The focus of this study is the evaluation of the effects of deficiencies in design-level values of effective binder content (Δ Vbe) on the top-down (TD) and bottom-up (BU) fatigue cracking performance of hot-mix asphalt (HMA) mixtures using AASHTOWare Pavement ME Design structural simulation program. Using an analytical–mathematical-based methodology, this study also aims to predict the reduction in fatigue service life (i.e., TD, and BU fatigue cracking) of asphalt pavements that are most sensitive to the variation (Δ Vbe). Two types of mixes with varying levels of Vbe are used to simulate the fatigue cracking performance of a full-depth (FD) pavement structure. For each of the three studied cases, one asphalt course has a variable value of Vbe, while the two other courses have a fixed value of Vbe. Results indicate that the Δ Vbe of 3% reduced 50%–70% of fatigue cracking service life. Additionally, Pavement ME shows a limitation to account for the effect of Vbe in the intermediate course on the BU fatigue cracking.

Cost of TB services in healthcare facilities in Kenya (No 3).

BACKGROUND:The reduction of Kenya’s TB burden requires improving resource allocation both to and within the National TB, Leprosy and Lung Disease Program (NTLD-P). We aimed to estimate the unit costs of TB services for budgeting by NTLD-P, and allocative efficiency analyses for future National Strategic Plan (NSP) costing.METHODS:We estimated costs of all TB interventions in a sample of 20 public and private health facilities from eight counties. We calculated national-level unit costs from a health provider’s perspective using bottom-up (BU) and top-down (TD) approaches for the financial year 2017–2018 using Microsoft Excel and STATA v16.RESULTS:The mean unit cost for passive case-finding (PCF) was respectively US$38 and US$60 using the BU and TD approaches. The unit BU and TD costs of a 6-month first-line treatment (FLT) course, including monitoring tests, was respectively US$135 and US$160, while those for adult drug-resistant TB (DR-TB) treatment was respectively US$3,230.28 and US$3,926.52 for the 9-month short regimen. Intervention costs highlighted variations between BU and TD approaches. Overall, TD costs were higher than BU, as these are able to capture more costs due to inefficiency (breaks/downtime/leave).CONCLUSION:The activity-based TB unit costs form a comprehensive cost database, and the costing process has built-in capacity within the NTLD-P and international TB research networks, which will inform future TB budgeting processes.

Costs of TB services in India (No 1).

BACKGROUND:There is a dearth of economic analysis required to support increased investment in TB in India. This study estimates the costs of TB services from a health systems’ perspective to facilitate the efficient allocation of resources by India’s National Tuberculosis Elimination Programme.METHODS:Data were collected from a multi-stage, stratified random sample of 20 facilities delivering TB services in two purposively selected states in India as per Global Health Cost Consortium standards and using Value TB Data Collection Tool. Unit costs were estimated using the top-down (TD) and bottom-up (BU) methodology and are reported in 2018 US dollars.RESULTS:Cost of delivering 50 types of TB services and four interventions varied according to costing method. Key services included sputum smear microscopy, Xpert® MTB/RIF and X-ray with an average BU costs of respectively US$2.45, US$17.36 and US$2.85. Average BU cost for bacille Calmette-Guérin vaccination, passive case-finding, TB prevention in children under 5 years using isoniazid and first-line drug treatment in new pulmonary and extrapulmonary TB cases was respectively US$0.76, US$1.62, US$2.41, US$103 and US$98.CONCLUSION:The unit cost of TB services and outputs are now available to support investment decisions, as diagnosis algorithms are reviewed and prevention or treatment for TB are expanded or updated in India.

Cost of TB services in the public and private sectors in Georgia (No 2).

BACKGROUND:Patient-centred care along with optimal financing of inpatient and outpatient services are the main priorities of the Georgia National TB Programme (NTP). This paper presents TB diagnostics and treatment unit cost, their comparison with NTP tariffs and how the study findings informed TB financing policy.METHODS:Top-down (TD) and bottom-up (BU) mean unit costs for TB interventions by episode of care were calculated. TD costs were compared with NTP tariffs, and variations in these and the unit costs cost composition between public and private facilities was assessed.RESULTS:Outpatient interventions costs exceeded NTP tariffs. Unit costs in private facilities were higher compared with public providers. There was very little difference between per-day costs for drug-susceptible treatment and NTP tariffs in case of inpatient services. Treatment day financing exceeded actual costs in the capital (public facility) for drug-resistant TB, and this was lower in the regions.CONCLUSION:Use of reliable unit costs for TB services at policy discussions led to a shift from per-day payment to a diagnosis-related group model in TB inpatient financing in 2020. A next step will be informing policy decisions on outpatient TB care financing to reduce the existing gap between funding and costs.

Magnitude and Uncertainty of Nitrous Oxide Emissions From North America Based on Bottom‐Up and Top‐Down Approaches: Informing Future Research and National Inventories

AbstractWe synthesized N2O emissions over North America using 17 bottom‐up (BU) estimates from 1980–2016 and five top‐down (TD) estimates from 1998 to 2016. The BU‐based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007–2016, North American N2O emissions are estimated at 1.7 (1.0–3.0) Tg N yr−1 (BU) and 1.3 (0.9–1.5) Tg N yr−1 (TD). Anthropogenic emissions were twice as large as natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process‐based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories.

Regional trends and drivers of the global methane budget.

The ongoing development of the Global Carbon Project (GCP) global methane (CH4) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000–2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top‐down (TD) (atmospheric and transport model‐based) and bottom‐up (BU) (inventory‐ and process model‐based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions—China, Southeast Asia, USA, South Asia, and Brazil—account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH4 yr−1 in 2008–2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.