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1.Explain how each of the following is linked to air quality (in no particular order):1)human health, 2) housing segregation, 3) urban land use decisions, 4) socio-economic status, 5) chronic average exposure, 6) acute peak exposure, 7) siting of industrial facilities, 8) environmental impacts, 9) real estate values, 10) recent immigrants, 11) market characteristics, 12) capacity of the air monitoring network, 13) complexity of air emission patterns, 14) enforcement of environmental laws, and 15) political climate. To support your written description, create a conceptual framework (a diagram) that includes all of these factors (though not exclusively).
2. The EPA (2009) and many peer-reviewed articles have concluded that “kriging” is the best technique for interpolating air pollution data. Kriging has been shown to perform better than area average, nearest monitor, toxicity indexes, inverse distance weighting, spline interpolation, and dispersion modeling (Rivera-Gonzalez, et al 2015; Buzzelli, et al 2003; Jerrett, et al 2001). There is no debate on the value of the kriging technique, and for over two decades ArcGIS mapping software has included a kriging button. Researchers on the cutting edge of geo-statistical analysis, however, have identified plenty of drawbacks with ArcGIS kriging. These state-of-the-art scholars prefer approaches based on Poisson or binomial likelihoods or on Bayesian inference methods (Paciorek, 2008). Describe, in full detail, the advantages and disadvantages of using the ArcGIS kriging tool for spatial correlation of air pollution data.
 
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