Explore the vast range of titles available.

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km2) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures.

A wide range of Marginal Abatement Cost Curve (MACC) methods for reducing greenhouse gas (GHG) emissions has been introduced in various academic literature in the last decade to address various issues, to use different calculable logic, producing different results and implications. A detailed review has not been carried out on the application of MACC in terms of types of emissions, country/sector, and methodology used. This study is aimed at identifying, interpreting, and clarifying currently available literature on MACCs development from 2010-2020 by reviewing the previous applicability of three analytic dimensions including Greenhouse Gas (GHG) emission type, research objects, and modeling methodologies from top-down and bottom-up methods, providing researchers with information of past developments and future trends in this area. The result shows that CO2 is one of the most studied GHG emissions in calculating marginal abatement costs and some countries/regions have not received much attention from researchers in assessing emission reductions. Finally, the MACC bottom-up methodology focuses on the application of the engineering model method and the distance function method is a favorite in the application of the top-down method. Furthermore, this study also highlights possible research opportunities, which may lead to more successful and impactful results in future MACC studies.

The master plan of energy management for Thailand iron and steel industry has been proposed by Iron and Steel Institute of Thailand (ISIT). Three plausible scenarios in the master plan were S1: without integrated steel plant (baseline scenario), S2: with a traditional integrated BF–BOF and S3: with an alternative integrated DR-EAF. This study investigated the potential of energy reduction and CO 2 emission reduction in 2030 under two reduction target scenarios which were scenario A: to achieve ISIT'S plan and scenario B: maximum energy reduction. Moreover, the CO 2 abatement cost curve and the sensitivity analysis of the abatement cost with different interest rates were studied. By following the baseline scenario (S1), the potential of energy reduction and CO 2 reduction was 12.74 million GJ and 1.28 million tCO eq . The traditional integrated BF–BOF route (S2) exhibited the highest energy saving and CO 2 reduction potential, followed by S3 (DR-EAF) and S1 (baseline). The maximum energy reduction and CO 2 reduction could be increased 11.8% and 17.9% from the ISIT’s plan. The sensitivity analysis indicated that the change of interest rates (3.27, 4.27 and 5.27%) affected the abatement cost ranged from − 21 to + 24% when compared with the long-term interest rate of 4.27%.

We provide a graphical illustration of how standard consumer and producer theory can be used to quantify the welfare loss associated with inefficient pricing in insurance markets with selection. We then show how this welfare loss can be estimated empirically using identifying variation in the price of insurance. Such variation, together with quantity data, allows us to estimate the demand for insurance. The same variation, together with cost data, allows us to estimate how insurers' costs vary as market participants endogenously respond to price. The slope of this estimated cost curve provides a direct test for both the existence and the nature of selection, and the combination of demand and cost curves can be used to estimate welfare.We illustrate our approach by applying it to data on employer-provided health insurance from one specific company. We detect adverse selection but estimate that the quantitative welfare implications associated with inefficient pricing in our particular application are small, in both absolute and relative terms.

Methane is the second most important greenhouse gas after carbon dioxide contributing to human-made global warming. Keeping to the Paris Agreement of staying well below two degrees warming will require a concerted effort to curb methane emissions in addition to necessary decarbonization of the energy systems. The fastest way to achieve emission reductions in the 2050 timeframe is likely through implementation of various technical options. The focus of this study is to explore the technical abatement and cost pathways for reducing global methane emissions, breaking reductions down to regional and sector levels using the most recent version of IIASA's Greenhouse gas and Air pollution Interactions and Synergies (GAINS) model. The diverse human activities that contribute to methane emissions make detailed information on potential global impacts of actions at the regional and sectoral levels particularly valuable for policy-makers. With a global annual inventory for 1990-2015 as starting point for projections, we produce a baseline emission scenario to 2050 against which future technical abatement potentials and costs are assessed at a country and sector/technology level. We find it technically feasible in year 2050 to remove 54 percent of global methane emissions below baseline, however, due to locked in capital in the short run, the cumulative removal potential over the period 2020-2050 is estimated at 38 percent below baseline. This leaves 7.7 Pg methane released globally between today and 2050 that will likely be difficult to remove through technical solutions. There are extensive technical opportunities at low costs to control emissions from waste and wastewater handling and from fossil fuel production and use. A considerably more limited technical abatement potential is found for agricultural emissions, in particular from extensive livestock rearing in developing countries. This calls for widespread implementation in the 2050 timeframe of institutional and behavioural options in addition to technical solutions.

We use exogenous variation in tax benefit functions to estimate firm-specific cost of debt functions that are conditional on company characteristics such as collateral, size, and book-to-market. By integrating the area between the benefit and cost functions, we estimate that the equilibrium net benefit of debt is 3.5% of asset value, resulting from an estimated gross benefit (cost) of debt equal to 10.4% (6.9%) of asset value. We find that the cost of being overlevered is asymmetrically higher than the cost of being underlevered and that expected default costs constitute only half of the total ex ante costs of debt.

Global bioenergy potentials have been the subject of extensive research and continued controversy. Due to vast uncertainties regarding future yields, diets and other influencing parameters, estimates of future agricultural biomass potentials vary widely. Most scenarios compatible with ambitious climate targets foresee a large expansion of bioenergy, mainly from energy crops that needs to be kept consistent with projections of agriculture and food production. Using the global biomass balance model BioBaM, we here present an assessment of agricultural bioenergy potentials compatible with the Food and Agriculture Organization's (2018) 'Alternative pathways to 2050' projections. Mobilizing biomass at larger scales may be associated with systemic feedbacks causing greenhouse gas (GHG) emissions, e.g. crop residue removal resulting in loss of soil carbon stocks and increased emissions from fertilization. To assess these effects, we derive 'GHG cost supply-curves', i.e. integrated representations of biomass potentials and their systemic GHG costs. Livestock manure is most favourable in terms of GHG costs, as anaerobic digestion yields reductions of GHG emissions from manure management. Global potentials from intensive livestock systems are about 5 EJ/yr. Crop residues can provide up to 20 EJ/yr at moderate GHG costs. For energy crops, we find that the medium range of literature estimates (∼40 to 90 EJ/yr) is only compatible with FAO yield and human diet projections if energy plantations expand into grazing areas (∼4-5 million km2) and grazing land is intensified globally. Direct carbon stock changes associated with perennial energy crops are beneficial for climate mitigation, yet there are-sometimes considerable-'opportunity GHG costs' if one accounts the foregone opportunity of afforestation. Our results indicate that the large potentials of energy crops foreseen in many energy scenarios are not freely and unconditionally available. Disregarding systemic effects in agriculture can result in misjudgement of GHG saving potentials and flawed climate mitigation strategies.

The US Pulp and Paper (P&P) industry heavily relies on fossil sources, with lime kiln operations posing a significant challenge for achieving zero on-site fossil emissions. This study assesses the greenhouse gas (GHG) reduction potential and costs associated with alternative fuels in lime kiln operations for linerboard production. Various options, including bio-based fuels including pulverized biomass, gasification of biomass, crude tall oil, bio-methanol, and traditional fuels such as fuel oil and petcoke, were analyzed through detailed process simulations and Life Cycle Assessment. Results indicate that per ton of product, 2,789 kg of CO2-eq is emitted, with 69% being biogenic CO2 and 31% fossil CO2-eq. Notably, replacing the natural gas boiler with a biomass boiler reduces Global Warming Potential (GWP) by 41%, while switching lime kiln fuel to biofuels achieves a 5.5% reduction. Combining a biomass boiler with pulverized biomass fuel use in the lime kiln yields a substantial 93.1% reduction in Scope 1 and 2 emissions, at a cost of 76/ton of CO2-eq avoided.

In the rapidly growing economies of Southeast Asia, energy consumption and energy costs in buildings continue to increase. Over the past decade, energy consumption from the commercial building sector in Thailand has increased at an average of 4% per annum and currently represents over 30% of total electricity consumption, second only to the industrial sector. Buildings that exist today will continue to represent most of both energy and greenhouse gas (GHG) emissions from the built environment, with newly constructed buildings representing only a small additional portion. This paper analyzes the environmental, technical, and financial characteristics of energy efficiency retrofit activities in commercial buildings in Thailand through detailed case studies of forty-two projects undertaken over the past 8 years. Our findings suggest that retrofits provide significant opportunities to reduce energy use, energy costs, and GHG emissions while also validating the economic feasibility of investments into such retrofit activities. Through this detailed analysis of past retrofit projects in Thailand, we found that the marginal abatement costs (MAC) relating to the key energy conservation measures (ECM) implemented within these retrofit projects all have negative costs. However, although these findings demonstrate positive economics and should be sufficient to instigate widespread adoption, in reality, this is not taking place. It is evident that greater public policy and leadership are needed to stimulate growth in the building retrofit sector to take advantage of the opportunities and benefits that building retrofits offer.

The risk management of rainfall-induced landslides requires reliable rainfall thresholds to issue early warning alerts. The practical application of these thresholds often leads to misclassifications, either false negative or false positive, which induce costs for the society. Since missed-alarm (false negative) and false-alarm (false positive) cost may be significantly different, it is necessary to find an optimal threshold that accounts for and minimises such costs, tuning the false-alarm and missed-alarm rates. In this paper, we propose a new methodology to develop cost-sensitive rainfall thresholds, and we also analyse several factors that produce uncertainty, such as the accuracy of rainfall intensity values at landslide location, the time of occurrence, the minimum rainfall amount to define the non-triggering event, and the variability of cost scenarios. Starting from a detailed mapping of landslides that occurred during five large-scale rainfall events in the Italian Central Alps, we first developed rainfall threshold curves with a ROC-based approach by using both rain gauge and bias-adjusted weather radar data. Then, based on a reference cost scenario in which we quantified several cost items for both missed alarms and false alarms, we developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). Finally, we studied the sensitivity of cost items. The study confirms how important is the information regarding rainfall intensity at the landslide site for the development of rainfall thresholds. Although the use of bias-corrected radar strongly improves these values, a large uncertainty related to the exact time of landslide occurrence still remains, negatively affecting the analysis. Accounting for the different missed-alarm and false-alarm misclassification costs is important because different combinations of these costs make an increase or decrease of the rainfall thresholds convenient. In our reference cost scenario, the most convenient threshold is lower than ROC-based thresholds because it seeks to minimise the number of missed alarms, whereas the missed-alarm costs are almost seven times greater than false-alarm costs. However, for different cost scenarios, threshold may vary significantly, as much as half an order of magnitude.