An Analytical Model for Spatially Varying Clear-Sky CO2 Forcing

Clear-sky CO2 forcing is known to vary significantly over the globe, but the state dependence which controls this is not well understood. Here we extend the formalism of Wilson and Gea-Banacloche (2012) to obtain a quantitatively accurate analytical model for spatially-varying instantaneous CO2 forcing, which depends only on surface temperature Ts, stratospheric temperature, and column relative humidity RH. This model shows that CO2 forcing can be considered a swap of surface emission for stratospheric emission, and thus depends primarily on surface-stratosphere temperature contrast. The strong meridional gradient in CO2 forcing is thus largely due to the strong meridional gradient in Ts. In the tropics and mid-latitudes, however, the presence of H2O modulates the forcing by replacing surface emission with RH-dependent atmospheric emission. This substantially reduces the forcing in the tropics, introduces forcing variations due to spatially-varying RH, and sets an upper limit (with respect to Ts variations) on CO2 forcing which is reached in the present-day tropics.In addition, we extend our analytical model to the instantaneous tropopause forcing, and find that this forcing depends on Ts only, with no dependence on stratospheric temperature. We also analyze the ‘τ = 1’ approximation for the emission level, and derive an exact formula for the emission level which yields values closer to τ = 1/2 than to τ = 1.

Will Port Integration Help Reduce Carbon Emissions and Improve Social Welfare?

In the context of competition between two ports in Cournot, we studied optimal decision-making processes for the government and the port in four different situations before and after the integration of the port based on the subsidy and carbon tax mechanism. We analyzed the impacts of the carbon tax rate and emission reduction subsidy rate on social welfare and determined the optimal carbon tax rate, the optimal emission reduction subsidy rate, the optimal carbon emission level, and the optimal social welfare level in different situations. We also compared the optimal social welfare level and the optimal carbon emission level of the four situations before and after the integration. This research can be used as a policy reference for the government for the formation of environmental policies based on the goal of maximizing social welfare, and it could also be used for the port’s internal decision-making when the environmental policy has been set.

Solving Multi-Objective Energy Management of a DC Microgrid using Multi-Objective Multiverse Optimization

This paper deals with the multi-objective optimization dispatch (MOOD) problem in a DC microgrid. The aim is to formulate the MOOD to simultaneously minimize the operating cost, pollutant emission level of (NOx, SO2 and CO2) and the power loss of conversion devices. Taking into account the equality and inequality constraints of the system. Two approaches have been adopted to solve the MOOD issue. The scalarization approach is first introduced, which combines the weighted sum method with price penalty factor to aggregate objective functions and obtain Pareto optimal solutions. Whilst, the Pareto approach is based on the implementation of evolutionary multi-objective optimization solution. Single and multi-objective versions of multi-verse optimizer algorithm are, respectively, employed in both approaches to handle the MOOD. For each time step, a fuzzy set theory is selected to find the best compromise solution in the Pareto optimal set. The simulation results reveal that the Pareto approach achieves the best performances with a considerable decrease of 28.96 $/day in the daily operating cost, a slight reduction in the power loss of conversion devices from 419.79 kWh to 419.29 kWh, and in less computational time. While, it is noticing a small increment in the pollutant emission level from 11.54 kg/day to 12.21 kg/day, for the daily microgrid operation. This deviation can be fully covered when comparing the cost related to the treatment of these pollutants, which is only 5.55 $/day, to the significant reduction in the operating cost obtained using the Pareto approach.

Electromagnetic Field Exposure in Kindergarten Children: Responsive Health Risk Concern

Long-term exposure to physical agents can be detrimental to children due to their vulnerability. This study aimed to assess and compare the electromagnetic field (EMF) exposure level around the kindergartens from the underground transmission line (UGTL). We investigated randomly selected 24 kindergartens based on the location of the UGTL. The EMF emission levels were measured using an EMDEX II (Electric and Magnetic Digital Exposure Meter). The maximum mean value of the EMF emission level was 13.5 mG around the kindergartens and 17.7 mG from the point of UGTL to kindergartens. EMF emission level around the kindergartens was significantly associated with the location of the UGTL (t = −7.35, P < 0.001). These estimates are not trivial, as long-term exposure to EMF among kindergarten children can lead to different health problems. Routine monitoring of EMF emission levels is recommended including the awareness of EMF exposure to public citizens.

Incentive Contract Design for Supply Chain Enterprise’s Pollution Abatement with Carbon Tax

This paper applies mechanism design to the supply chain enterprise’s pollution abatement problem with carbon tax. To maximize the government’s expected utility, an uncertain contract model is presented in the framework of principal-agent theory, where the government’s assessment of the supply chain enterprise’s carbon emission level is described as an uncertain variable. Afterwards, the equivalent model is provided to obtain the optimal contract for the uncertain pollution abatement problem. The results demonstrate that the supply chain enterprise’s optimal output decreases with the carbon emission level. Furthermore, the government’s optimal transfer payment decreases with the carbon emission level if the carbon tax is low. In contrast, if the carbon tax is high, the optimal transfer payment increases with the carbon emission level. In addition, an increase in the carbon emission level decreases the optimal utilities of both the government and the supply chain enterprise and also leads to the supply chain enterprise’s incremental marginal utility. Finally, we provide a numerical example, which illustrates the effectiveness and practicability of the proposed model.

Multi-Objective Economic Environmental Dispatch of Variable Hydro-Wind-Thermal Power System

This article presents a multi-objective economic environmental/emission dispatch (EED) of variable head hydro-wind-thermal power system. The combination of NOx emission, SO2 emission, and fuel cost are minimized for non-smooth hydrothermal plants while satisfying various operational constraints like non-smooth fuel cost, penalty coefficient, and wind power uncertainty. The objectives—cost, NOx emission, and SO2 emission—are optimized at the same time. In this research, the non-dominated sorting genetic algorithm-II (NSGA-II) has been employed for solving the given problem where the total cost, NOx emission level, and SO2 emission level are optimized at the same time while satisfying all the operational constraints. The simulation results that are obtained by applying the two test systems on the proposed scheme have been evaluated against strength pareto evolutionary algorithm 2 (SPEA 2).