State Public Nuisance Claims and Climate Change Adaptation

This Article explores the potential for state public nuisance claims to facilitate adaptation, resource protection, and other climate change responses by coastal communities in California. The California public nuisance actions represent just the latest chapter in efforts to spur responses to climate change and attribute responsibility for climate change through the common law. Part II of this Article describes the California public nuisance lawsuits and situates them in the context of common law actions directed against climate change. Part III considers the preliminary defenses that defendants have raised and could raise in the California public nuisance lawsuits, including the existence of state common law in this context, separation of powers and the political question doctrine, displacement and preemption, and standing. Part IV considers the potential merits of the plaintiffs’ public nuisance claims under California law

Green Bay Chronic Nuisance Notification Evaluation, 2006–2010

Green Bay City Ordinance Chapter 28 allows the City of Green Bay, Wisconsin to recover the cost of providing police services for chronic nuisances. Enforcement of Chapter 28 began in October 2006 and continues as of this writing. This report examined calls for service at properties with chronic nuisance enforcement to determine if enforcement was associated with a reduction in calls for service. Enforcing the chronic nuisance ordinance is associated with reduced calls for service but is costly in terms of officer and analyst hours. The best use of the chronic nuisance ordinance may be as a credible threat to entice property owners to partner with the Green Bay Police Department on crime prevention and nuisance abatement efforts

On Modeling and Estimation for the Relative Risk and Risk Difference

A common problem in formulating models for the relative risk and risk difference is the variation dependence between these parameters and the baseline risk, which is a nuisance model. We address this problem by proposing the conditional log odds-product as a preferred nuisance model. This novel nuisance model facilitates maximum-likelihood estimation, but also permits doubly-robust estimation for the parameters of interest. Our approach is illustrated via simulations and a data analysis.Comment: To appear in Journal of the American Statistical Association: Theory and Method

The nuisance due to the noise of automobile traffic: An investigation in the neighborhoods of freeways

An inquiry was held among 400 people living near freeways in an attempt to determine the characteristics of traffic noise nuisance. A nuisance index was compiled, based on the answers to a questionnaire. Nuisance expressed in these terms was then compared with the noise level measured on the most exposed side of each building. Correlation between the nuisance indexes and the average noise levels is quite good for dwellings with facades parallel to the freeway. At equal noise levels on the most exposed side, the nuisance given for these latter dwellings is lower than for others

Efficient propagation of systematic uncertainties from calibration to analysis with the SnowStorm method in IceCube

Efficient treatment of systematic uncertainties that depend on a large number of nuisance parameters is a persistent difficulty in particle physics and astrophysics experiments. Where low-level effects are not amenable to simple parameterization or re-weighting, analyses often rely on discrete simulation sets to quantify the effects of nuisance parameters on key analysis observables. Such methods may become computationally untenable for analyses requiring high statistics Monte Carlo with a large number of nuisance degrees of freedom, especially in cases where these degrees of freedom parameterize the shape of a continuous distribution. In this paper we present a method for treating systematic uncertainties in a computationally efficient and comprehensive manner using a single simulation set with multiple and continuously varied nuisance parameters. This method is demonstrated for the case of the depth-dependent effective dust distribution within the IceCube Neutrino Telescope