Processing tools to create emissions for use in numerical air 
  quality models. Emissions can be calculated both using emission factors 
  and activity data (Schuch et al 2018) <doi:10.21105/joss.00662> or using 
  pollutant inventories (Schuch et al., 2018) <doi:10.30564/jasr.v1i1.347>. 
  Functions to process individual point emissions, line emissions and 
  area emissions of pollutants are available as well as methods to 
  incorporate alternative data for Spatial distribution of emissions 
  such as satellite images (Gavidia Calderon et. al, 2018) 
  <doi:10.1016/j.atmosenv.2018.09.026> or openstreetmap data 
  (Andrade et al, 2015) <doi:10.3389/fenvs.2015.00009>.

Provides a fast and parallelised calculator to estimate combined wastewater emissions. 
    It supports the planning and design of urban drainage systems, without the requirement of 
    extensive simulation tools. The 'EmiStatR' package implements modular R methods. This enables 
    to add new functionalities through the R framework.

Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) <doi:10.1214/18-BA1141>, Hubin, A., Storvik, G., & Frommlet, F. (2021) <doi:10.1613/jair.1.13047>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>, and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>, which allow for estimating posterior model probabilities and Bayesian model averaging across a wide set of Bayesian models including linear, generalized linear, generalized linear mixed, generalized nonlinear, generalized nonlinear mixed, and logic regression models.

Work with Ecological Metadata Language ('EML') files. 
    'EML' is a widely used metadata standard in the ecological and
    environmental sciences, described in Jones et al. (2006),
    <doi:10.1146/annurev.ecolsys.37.091305.110031>.