Reconciling Assumptions in Bottom-Up and Top-Down Approaches for Estimating Aerosol Emission Rates From Wildland Fires Using Observations From FIREX-AQ

Accurate fire emissions inventories are crucial to predict the impacts of wildland fires on air quality and atmospheric composition. Two traditional approaches are widely used to calculate fire emissions: a satellite-based top-down approach and a fuels-based bottom-up approach. However, these methods often considerably disagree on the amount of particulate mass emitted from fires. Previously available observational datasets tended to be sparse, and lacked the statistics needed to resolve these methodological discrepancies. Here, we leverage the extensive and comprehensive airborne in situ and remote sensing measurements of smoke plumes from the recent Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to statistically assess the skill of the two traditional approaches. We use detailed campaign observations to calculate and compare emission rates at an exceptionally high-resolution using three separate approaches: top-down, bottom-up, and a novel approach based entirely on integrated airborne in situ measurements. We then compute the daily average of these high-resolution estimates and compare with estimates from lower resolution, global top-down and bottom-up inventories. We uncover strong, linear relationships between all of the high-resolution emission rate estimates in aggregate, however no single approach is capable of capturing the emission characteristics of every fire. Global inventory emission rate estimates exhibited weaker correlations with the high-resolution approaches and displayed evidence of systematic bias. The disparity between the low-resolution global inventories and the high-resolution approaches is likely caused by high levels of uncertainty in essential variables used in bottom-up inventories and imperfect assumptions in top-down inventories

Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i.e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates

Paying for community-based health insurance schemes in rural Nigeria: the use of in-king payments

Financing healthcare for the poor is one major challenge facing the world’s poorest populations in developing countries. While over 90% of the global burden of disease is borne by over 80%, only about 11% of global health spending is on the poor. Community-based health insurance schemes (CBHIS) have emerged in Africa for mobilizing community resources. They can also be a stepping stone to a more formal and potentially universal coverage. In parts of Africa where such schemes exist, they have not effectively covered the target population. Nigeria has a few such schemes. This paper uses the contingent valuation to examine the possibility of adopting CBHIS using in-kind payments in rural Nigeria. The study finds that gender, household size, health status, the quality of health care centers, confidence in the proposed scheme, distance to the nearest health care center and income are major determinants of households’ willingness to pay (WTP) for the scheme.Soins de santé de financement pour les pauvres est un défi majeur auquel sont confrontées populations les plus pauvres de la planète dans les pays en développement. Alors que plus de 90% de la charge mondiale de morbidité est supportée par plus de 80%, seulement environ 11% des dépenses de santé mondiale est sur les pauvres. Communauté des régimes d’assurance santé (CBHIS) ont émergé en Afrique pour mobiliser les ressources communautaires. Ils peuvent aussi être un tremplin vers une couverture plus formelle et potentiellement universelle. Dans certaines régions d’Afrique où de tels régimes existent, ils n’ont pas effectivement couvert la population cible. Le Nigeria a quelques programmes tels. Ce document utilise l’évaluation contingente d’examiner la possibilité d’adopter CBHIS utilisant des paiements en nature dans les régions rurales du Nigeria. L’étude constate que le sexe, la taille du ménage, l’état de santé, la qualité des centres de soins de santé, la confiance dans le système proposé, la distance du centre de soins de santé le plus proche et le revenu sont des déterminants majeurs de la volonté des ménages à payer (CAP) pour le régime