scholarly journals Parametric evaluation of emission savings potential based on a mobility demand model

2016 ◽  
Author(s):  
M. Kugler ◽  
M. Lienkamp
Keyword(s):  
Commonwealth ◽  
2017 ◽  
Vol 19 (1) ◽  
Author(s):  
Somayeh Youssefi ◽  
Patrick L. Gurian

Pennsylvania is one of a number of U.S. states that provide incentives for the generation of electricity by solar energy through Solar Renewal Energy Credits (SRECs). This article develops a return on investment model for solar energy generation in the PJM (mid-­Atlantic) region of the United States. Model results indicate that SREC values of roughly $150 are needed for residential scale systems to break even over a 25-­year project period at 3% interest. Market prices for SRECs in Pennsylvania have been well below this range from late 2011 through the first half of 2016, indicating that previous capital investments in solar generation have been stranded as a result of steep declines in the value of SRECs. A simple conceptual supply and demand model is developed to explain the sharp decline in market prices for SRECs. Also discussed is a possible policy remedy that would add unsold SRECs in a given year to the SREC quota for the subsequent year.


2019 ◽  
Vol 1 (1) ◽  
pp. 36-40
Author(s):  
Souad Adnane

The District of Columbia (DC) Office of the Superintendent of Education (OSSE) issued in December 2016 new educational requirements for childcare workers, according to which, all childcare center directors in the District must earn a bachelor’s degree by December 2022 and all lead teachers an associate’s degree by December 2020 (Institute for Justice, 2018). Moreover, DC has one of the lowest staff-child ratios in the country. How are regulations pertaining to childcare workers’ qualifications and staff-child ratio affecting the childcare market in DC? The present paper is an attempt to answer this question first by analyzing the effects of more stringent regulations on the cost and availability of childcare in the U.S based on existing studies. It also uses the basic supply and demand model to examine the possible impact of the new DC policy on the cost, quality and supply of childcare in the District and how it will affect working parents, especially mothers. Next, the paper discusses the impact of deregulation based on simulations and regressions conducted by studies covering the U.S., and implications for quality. It concludes that more stringent childcare regulations, regarding educational requirements and staff-child ratios, are associated with a reduced number of childcare centers and a higher cost, and eventually affects women’s labor force participation.


1965 ◽  
Vol 38 (3) ◽  
pp. 252 ◽  
Author(s):  
Thomas R. Dyckman

1999 ◽  
Vol 75 (4) ◽  
pp. 603 ◽  
Author(s):  
Matthew D. Berman ◽  
Hong Jin Kim

Author(s):  
Gabriel Wilkes ◽  
Roman Engelhardt ◽  
Lars Briem ◽  
Florian Dandl ◽  
Peter Vortisch ◽  
...  

This paper presents the coupling of a state-of-the-art ride-pooling fleet simulation package with the mobiTopp travel demand modeling framework. The coupling of both models enables a detailed agent- and activity-based demand model, in which travelers have the option to use ride-pooling based on real-time offers of an optimized ride-pooling operation. On the one hand, this approach allows the application of detailed mode-choice models based on agent-level attributes coming from mobiTopp functionalities. On the other hand, existing state-of-the-art ride-pooling optimization can be applied to utilize the full potential of ride-pooling. The introduced interface allows mode choice based on real-time fleet information and thereby does not require multiple iterations per simulated day to achieve a balance of ride-pooling demand and supply. The introduced methodology is applied to a case study of an example model where in total approximately 70,000 trips are performed. Simulations with a simplified mode-choice model with varying fleet size (0–150 vehicles), fares, and further fleet operators’ settings show that (i) ride-pooling can be a very attractive alternative to existing modes and (ii) the fare model can affect the mode shifts to ride-pooling. Depending on the scenario, the mode share of ride-pooling is between 7.6% and 16.8% and the average distance-weighed occupancy of the ride-pooling fleet varies between 0.75 and 1.17.


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