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This research proposes a new methodology for U.S. Air Force weather forecast metrics. Military weather forecasters are essentially statistical classifiers. They categorize future conditions into an operationally relevant category based on current data, much like an Artificial Neural Net or Logistic Regression model. There is extensive literature on statistically-based metrics for these types of classifiers. Additionally, in the U.S. Air Force, forecast errors (errors in classification) have quantifiable operational costs and benefits associated with incorrect or correct classification decisions. There is a methodology in the literature, Bayes Cost, which provides a structure for creating statistically rigorous metrics for classification decisions that have such costs and benefits. Applying these types of metrics to Air Force weather yields more informative metrics that account for random chance while remaining simple to calculate. This research conducts an analysis using notional values from an unnamed subject matter expert. Bayes Cost-based verification on Terminal Aerodrome Forecasts and Watches/Warnings/Advisories compared to surface observations from a selection of military installations in the continental United States during the period 01 May 2019 to 30 June 2019. The case study illustrates the added utility of the new metric paradigm.

This article explores and analyses several factors that are interconnected and affect the cost of alternative sources of energy, such as wind, solar PV, hydro and kinetic energy, and compares them to current fossil fuels such as nuclear, coal and natural gas that provide 85% of the total residential and industrial energy consumption worldwide. In addition, we provide a forecast of the levelized energy cost (LEC) until parity of alternative sources of energy that is directly correlated to the multiple factors seen and analyze such as: government tax breaks and subsidies, weather conditions, market conditions, technological advancements, fuel prices and economic conditions between other with their defining role and their related impact in the price of energy. Moreover, we analyzed the consumers' role and the possibilities of creating mini-grids and smart home systems that will increase savings in the short and long run and how will they co-exist with currently utility energy providers.

Small-scale renewable electricity generation projects have the potential to address not just the need to reduce greenhouse gas emissions to combat climate change, but also to provide local, sustainable economic and community revitalization. In this paper, we have proposed a small hydroelectric generation project with citizen participation which includes cooperation in some activities such as cleaning and patrols, and have evaluated the project economically by using the regional input-output (I-O) analysis in which the willingness to work (WTW) is incorporated. The WTW for the project have been estimated by using the conjoint analysis as a function of its various attributes, namely revenue from the project's electricity sales, profits earned for the local community, and rewards given to contributors. The results show that the amount of WTW provided by resident volunteers will increase with increasing unit value of reward, but the amount of reward paid to volunteers will also increase. On the other hand, the operating income of the establishment that has contracted maintenance of the small hydroelectric supply sector will decrease, and its influence will spread through the inter-industry relations. Then, we have analyzed such economic ripple effect by using the regional I-O table for analysis of small hydroelectric generation project. By considering the range of the "unit value of reward" and the "substitution rate of resident volunteers", even if the project is deficit, we have found a good countermeasure which can be expected positive effects. As a result, it is possible to reduce the subsidies of regional governments with respect to the project, and it is possible to devote that amount of budget to improvement of other administrative services. Although introduction of volunteer activities is finished when the amount of WTW exceeds the consignment work load in this case study, more volunteer activities may be introduced if external economic benefits of volunteers are expected. For example, if the bond of community are strengthened by that residents participate in volunteer activities, the bond strengthened can compensate for the lack of government services such as disaster prevention and welfare, and improvement of resident satisfaction may be expected. By evaluating such external economic benefits and practicing social cost benefit analysis, it is possible to discuss that more volunteer activities should be introduced or not. Such external economic benefits can be measured by the opportunity cost of volunteer activities or the time value of WTW, but this matter will be discussed at the next stage. When this type of small hydroelectric generation project utilizing resident volunteers is introduced, household utility levels increase. Understanding the dynamism between these factors can allow regional governments to adapt the scheme to best fit the needs of individual regions.

This paper evaluates changes in electricity generation costs caused by the introduction of market mechanisms to determine production in the United States. I use the staggered transition to markets from 1999 to 2012 to estimate the causal impact of liberalization using a differences-in-difference design on a comprehensive hourly panel of electricity demand, generators' costs, capacities, and output. I find that markets reduce production costs by 5 percent by reallocating production: gains from trade across service areas increase by 55 percent based on a 25 percent increase in traded electricity, and costs from using uneconomical units fall 16 percent. (JEL L51, L94, L98, Q41, Q48)

Implementation of strict policies for mitigating climate change has a direct impact on public health as far as the external health costs of electricity generation can be reduced, thanks to the reduction of emission of typical pollutants by switching to cleaner low carbon fuels and achieving energy efficiency improvements. Renewables have lower external health costs due to the lower life cycle emission of typical air pollutants linked to electricity generation, such as SO(2), NOx, particulate matter, NH(3), or NMVOC (Non-methane volatile organic compounds), which all appear to have serious negative effects on human health. Our case study performed in the Baltic States analyzed the dynamics of external health costs in parallel with the dynamics of the main health indicators in these countries: life expectancy at birth, mortality rates, healthy life years, self-perceived health, and illness indicators. We employed the data for external health costs retrieved from the CASES database, as well as the health statistics data compiled from the EUROSTAT database. The time range of the study was 2010–2018 due to the availability of consistent health indicators for the EU Member States. Our results show that the decrease of external health costs had a positive impact on the increase of the self-perceived good health and reduction of long-standing illness as well as the decrease of infant death rate. Our conclusions might be useful for other countries as well as for understanding the additional benefits of climate change mitigation policies and tracking their positive health impacts. The cooperation initiatives on clean energy and climate change mitigation between countries like One Belt One Road initiative by the Chinese government can also yield additional benefits linked to the public health improvements.