Introduction

Air pollution represents one of the most critical environmental issues, with adverse impacts on human health, ecosystems and climate. Understanding the chemical and physical processes at stake in the atmosphere and assessing and mitigating their impacts requires a reliable estimate of the pollutant anthropogenic and natural emissions.

Methods

I will show here how to include poster elements that may be useful, such as an equation using mathjax:

\[ E = mc^2 \]

To reference a citation you can add your .bib file to the working directory and name it in the YAML metadata or generate an automated one as done here, then you only need to reference the label value in the .bib file. For example this package is built on top of the wonderful {pagedown} package and I will cite it at the end of this sentance using this in the rmd [@R-pagedown] (Xie et al. 2022).

To get a better understanding of how to include features like these please refer to the {posterdown} wiki.

Now on to the results!

Results

Here you may have some figures to show off, bellow I have made a scatterplot with the infamous Iris dataset and I can even reference to the figure automatically like this, Figure \@ref(fig:irisfigure), Figure 1.

Figure 1: Here is a caption for the figure. This can be added by using the “fig.cap” option in the r code chunk options, see this link from the legend himself, Yihui Xie.

Maybe you want to show off some of that fancy code you spent so much time on to make that figure, well you can do that too! Just use the echo=TRUE option in the r code chunk options, Figure 2!

#trim whitespace
par(mar=c(2,2,0,0))
#plot boxplots
boxplot(iris$Sepal.Width~iris$Species,
        col = "#008080", 
        border = "#0b4545",
        ylab = "Sepal Width (cm)",
        xlab = "Species")

Figure 2: Boxplots, so hot right now!

How about a neat table of data? See, Table 1: