Wednesday, May 27, 2015

Six times more expensive to travel in Copenhagen by car than by bicycle | Lund University

It is six times more expensive for society – and for you individually - if you travel by car instead of cycling....according to a study by Stefan Gössling from Lund University and Andy S. Choi from the University of Queensland.
Watch: Bikes cheaper alternative to cars

The study considers how much cars and bicycles cost society in terms of air pollution, climate change, travel route, noise, road wear, health and congestion in Copenhagen.

If the costs to society and the costs to private individuals are added together, the impact of the car is EUR 0.50 per kilometre and the impact of the bicycle is EUR 0.08 per kilometre.  If we only look at costs/benefits for society, one kilometre by car costs EUR 0.15, whereas society earns EUR 0.16 on every kilometre cycled.

“The cost-benefit analysis in Copenhagen shows that investments in cycling infrastructure and bike-friendly policies are economically sustainable and give high returns”, says Stefan Gössling.
Photo: Lasse Strandberg

Publication: ‘Transport transitions in Copenhagen: Comparing the cost of cars and bicycles’
Press release dated May 12,

Contact: Professor Stefan Gössling, Department of Service Management and Service Studies, Lund University +46 704 922634

Does Information Provision Shrink the Energy Efficiency Gap? A Cross-City Comparison of Commercial Building Benchmarking and Disclosure Laws
Information failures may help explain the so-called “energy efficiency gap” in commercial buildings, which account for approximately 20 percent of annual US energy consumption and CO2 emissions. Building owners may not fully comprehend what influences energy use in their buildings and may have difficulty credibly communicating building energy performance to prospective tenants and buyers. Ten US cities and one county have addressed this problem by passing energy benchmarking and disclosure laws. The laws require commercial buildings to report their annual energy use to the government. We evaluate whether the laws have had an effect on utility expenditures in office buildings covered by the laws in four of the early adopting cities—Austin, New York, San Francisco, and Seattle—and find that they have reduced utility expenditures by about 3 percent. Our view is that these estimated effects in the early days of the programs are largely attributable to increased attentiveness to energy use.
Table 7 [below] shows the calculated percentage change in utility expenditures per square foot, along with the estimated coefficients from Table 6, and the average utility expenditures per square foot for all four cities. While the coefficients for New York, San Francisco and Seattle are close to one another in size, the estimated percentage effects differ, with the most pronounced difference being between Seattle and the other two cities. [The authors] calculate a 3.3 and 3.5 percent drop in utility expenditures per square foot from disclosure laws in New York and San Francisco, respectively, and a 5.2 percent drop in Seattle. This result is attributable to the relatively low utility expenditures per square foot in Seattle, which in turn is attributable in large part to low electricity prices. During the treatment period, the average electricity price in Seattle was $50.75/MWh, in San Francisco $114.84/MWh, and in New York $148.51/MWh. This highlights a potentially interesting result—that the laws may have a larger percentage impact on utility bills in cities with relatively low average electricity prices and thus low average bills. It also highlights an important aspect of our analysis—that we are focused on the effects of disclosure laws on utility expenditures and not energy use. Ultimately, we are interested in the effects of the policy on energy use and CO2 emissions, but data on energy use are not available from our data source. The translation from energy savings to CO2 emissions reductions will also vary by region, but an analysis of these effects is beyond the scope of this paper.
Image result for Electric Meter benchmarking

Benefits of invasion prevention are constrained by lags and timing of invasion impacts
Quantifying economic damages caused by invasive species is crucial for cost-benefit analyses of control measures. Most studies focus on short-term damage estimates, but evaluating exclusion or prevention measures requires estimates of total anticipated damages from the time of establishment onward. The magnitude of such damages critically depends on the timing of damages relative to a species’ arrival because costs are discounted back to the time of establishment. Using theoretical simulations, we illustrate how (ceteris paribus) total long-term damages, and hence the benefits of prevention efforts, are greater for species that a) have short lags between introduction and spread or between arrival at a location and initiation of damages, b) cause larger, short-lived damages (as opposed to smaller, persistent damages), and c) spread faster or earlier. We empirically estimate total long-term discounted impacts for three forest pests currently invading North America - gypsy moth (Lymantria dispar), hemlock woolly adelgid (Adelges tsugae), and emerald ash borer (Agrilus planipennis) - and discuss how damage persistence, lags between introduction and spread, and spread rates affect damages. Many temporal characteristics can be predicted for new invaders and should be considered in species risk analyses and economic evaluations of quarantine and eradication programs.
As the table below shows  the total present value of residential damages from the gypsy moth ranges from $32 million with a discount rate of 5% to $6.415 billion at a discount rate of 1%, and $0.7 million to $20 million for the hemlock wooily adegid and from $9.2 billion to 26.4 billion for the emerald ash borer invasion

Table 1. Estimated total present value (millions 2011 USD) of residential damages from gypsy moth and hemlock woolly adelgid and of ash tree removal and replacement costs from emerald ash borer invasion. Present values are calculated from the time of both introduction and initiation of damages (1869 and 1880 for gypsy moth, 1911 and 1971 for hemlock woolly adelgid, and 1990 and 2002 for emerald ash borer).
Fig. 1. Panels show the (a) radial extent, (b) invaded area, (c,e) nondiscounted annual damages, and (d,f) present value of annual damages for the first 100 years of invasion for spread models A, B, and C (lines) with the baseline parameterizations. The second row (c,d) shows damages when persistence P is 1 year, and the third row (e,f) shows damages when persistence P is 100 years.

Quantification of gypsy moth spread and damages.
[The authors] used historical invasion records to characterize past invasion spread from the time of its initial introduction in Medford, Massachusetts, in 1868 through 2012. Past spread of gypsy moth from 1868 to 1912 is summarized in Liebhold et al. and Liebhold and Tobin from a variety of historical records. Spread from 1912 to the present is recorded in county-level quarantine records published by the US Department of Agriculture (US Code of Federal Regulations, Title 7, Chapter III, Section 301.45). Future spread of the gypsy moth was projected based on an assumption of constant radial spread, using a rate of 5 km/yr (the average spread rate estimated for 1999–2012 along the expanding population front in the United States; ... Year of establishment was predicted for each county in 39 eastern states . [They] excluded spread into counties whose climates are unsuitable for gypsy moth development.