From 413ef7721269fc39e892f7a4dd96e930cbe50451 Mon Sep 17 00:00:00 2001 From: RFlx Date: Mon, 27 Nov 2023 17:55:15 +0000 Subject: [PATCH] replace tables paper --- paper/PaperCEUS/PaperCEUS.Rmd | 87 +++++++++++++++++++++++----------- paper/PaperCEUS/PaperCEUS.pdf | Bin 1266141 -> 1266800 bytes paper/PaperCEUS/PaperCEUS.tex | 44 +++++++++++------ 3 files changed, 89 insertions(+), 42 deletions(-) diff --git a/paper/PaperCEUS/PaperCEUS.Rmd b/paper/PaperCEUS/PaperCEUS.Rmd index c2a1b28..ff5b77d 100644 --- a/paper/PaperCEUS/PaperCEUS.Rmd +++ b/paper/PaperCEUS/PaperCEUS.Rmd @@ -189,7 +189,7 @@ knitr::include_graphics("img/map2.png", error = FALSE) -For the cycling legs of the journey (first and last legs), socio-environmental impacts were estimated, using the HEAT for Cycling tool v5.0 [@HEAT] from the World Health Organization, and the [`HEATaaS` R package](https://github.com/HEAT-WHO/HEAT_heatr_api)[^5]. +For the cycling legs of the journey (first and last legs), socio-environmental impacts were estimated, using the HEAT for Cycling tool v5.2 [@HEAT] from the World Health Organization, and the [`HEATaaS` R package](https://github.com/HEAT-WHO/HEAT_heatr_api)[^5]. The HEAT tool provided estimates on the shifting from car to cycling for a short term time horizon (i.e., one year) and the long term (i.e., ten years). We considered two dimensions: *social* — including the physical activity of cyclists, air pollution exposure, and road casualties; *environmental* — including CO~2~eq emissions and other pollutants. @@ -223,28 +223,57 @@ We updated all the monetary reference values of the literature based on the annu # Results and Discussion Table \ref{tab:summary1} presents the LMA total daily trips that can be made with cycling + TP combination (with the aforementioned restrictions), the trips in the baseline scenario and corresponding new trips to achieve the national strategy targets (4% and 10%), for different route profiles. -For the cycling legs of the journey (first and last legs), the environmental avoided emissions and monetized socio-environment (SE) benefits are also presented, resulting from replacing car trips with cycling. +For the cycling legs of the journey (first and last legs), the environmental avoided emissions and monetized socio-environment (SE) benefits are presented in \ref{tab:summary1b}, resulting from replacing car trips with cycling. -```{r summary1} -summary1 = readRDS("load/summary1.Rds") -summary1 = summary1 %>% - mutate(LTS = recode(LTS, `3` = "safe", `4` = "direct")) |> - mutate(Estrategia = paste0(Estrategia*100,"%")) |> - mutate(TotalTrips = TotalTrips/2, - Bikebase = Bikebase/2, - Bikepotential = Bikepotential/2) #this is a quick correction while we donr run biclar entirely again. The error was found and it was adding up the 2 bike legs, instead of making the mean. The SE estimates remain the same because they are from the bikeshare and carshare percentages, that did not change. +```{r summary0} +summary0 = readRDS(url("https://github.com/U-Shift/biclar/releases/download/0.0.1/HEAT_AML_intermodal_ppp_NEW.Rds")) +# see code/test-code/heat-prep.R#intermodality + +summary0 = summary0 |> + mutate(Target = paste0(ENMAC*100,"%"), + Routing = c("safe", "safe", "direct", "direct"), + TotalTrips = Total, + Bikebase = Bike, + Bikepotential = Bike_new, + Social = Economic - Environmenal_only, + Social10 = Economic10 - Environmenal10_only) +``` + +```{r summary1} +summary1 = summary0 |> + select(Target, Routing, TotalTrips, Bikebase, Bikepotential) |> + arrange(desc(Target)) knitr::kable(summary1, digits = 0, format.args = list(big.mark = " "), col.names = c("Target", "Routing", "Total trips", - "Baseline Cycling + PT", "Potencial Cycling + PT", - "Avoided CO2eq (ton/yr)", "SE Benefits for 10 years (thousand €)"), - caption = "\\label{summary1}Summary of the cycling potencial of intermodality scenario and its socio-environmental benefits for the cycling legs.", + "Baseline Cycling + PT", "Potencial Cycling + PT"), + caption = "\\label{summary1}Summary of the cycling potencial of the intermodality scenario.", format="latex", booktabs = TRUE) |> - kableExtra::column_spec(column = c(4:7), width = "6em") + kableExtra::column_spec(column = c(4:5), width = "7em") + +``` + +```{r summary1b} +summary1b = summary0 |> + select(Target, Routing, Mortality, Social, CO2eq, Environmenal_only) |> + mutate(Social = Social/1000, + Environmenal_only = Environmenal_only/1000) |> + arrange(desc(Target)) + +knitr::kable(summary1b, + digits = c(0,0,1,0,0,0), + format.args = list(big.mark = " "), + col.names = c("Target", "Routing", + "Avoided Mortality (deaths/yr)", "Social benefits (k€/yr)", + "Avoided CO2eq (ton/yr)", "Environmental benefits (k€/yr)"), + caption = "\\label{summary1b}Summary of the cycling potencial of intermodality scenario and its socio-environmental benefits for the cycling legs.", + format="latex", + booktabs = TRUE) |> + kableExtra::column_spec(column = c(3:6), width = "6em") ``` @@ -286,10 +315,11 @@ Regarding the PT segment, the shift from private car would lead to the mitigatio ```{r summary22} summary22 = readRDS("load/TPtable_aml.Rds") summary22 = summary22 %>% - mutate(LTS = recode(Percursos, "seguro" = "safe", "direto" = "direct")) |> - mutate(Value = money_emissions_eur/1000) |> - select(Meta_ENMAC, LTS, CO2eq_TP, CO_PT, PM10_PT, NOx_PT, VOC_PT, Value) |> - arrange(Meta_ENMAC) + mutate(Routing = recode(Percursos, "seguro" = "safe", "direto" = "direct")) |> + mutate(Value = money_emissions_eur/1000, + Target = Meta_ENMAC) |> + select(Target, Routing, CO2eq_TP, CO_PT, PM10_PT, NOx_PT, VOC_PT, Value) |> + arrange(Target) knitr::kable(summary22, digits = c(0,0,0,0,1,0,1,0), @@ -305,19 +335,20 @@ knitr::kable(summary22, The sum of CO~2~eq avoided emissions from the potential car trips shifted to bike (first-and-last legs) in combination with PT (second leg) in the LMA is presented on Table \ref{tab:summaryall}, for both national cycling strategy targets and routing profiles, and the socio-environmental benefits monetized in €, for a 1-year and 10-year time periods. ```{r summaryall, message=FALSE, warning=FALSE} -summary0 = readRDS("load/HEAT_aml_results.Rds") |> slice_tail(n = 4) + rate = ((1+0.03)^10)/((1+0.05)^10) # inflation rate 3% discount rate 5% -summaryall = summary1 |> - mutate(Meta_ENMAC = Estrategia) |> +summaryall = summary0 |> left_join(summary22) |> - mutate(Code = c(3304, 3404, 3310, 3410)) |> - left_join(summary0 |> select(Code, Economic), by = "Code") |> - select(Estrategia, LTS, co2, CO2eq_TP, monet, Value, Economic) |> - mutate(CO2eq = co2 + CO2eq_TP, - value1 = Economic/1000 + Value, # this is CORRECT - value10 = monet + Value*10*rate) |> # this is CORRECT - select(Estrategia, LTS, CO2eq, value1, value10) + select(Target, Routing, CO2eq, CO2eq_TP, Environmenal_only, Environmenal10_only, Social, Social10, Value) |> + mutate(Social = Social/1000, + Social10 = Social10/1000, + Environmenal_only = Environmenal_only/1000, + Environmenal10_only = Environmenal10_only/1000) |> + mutate(CO2eqT = CO2eq + CO2eq_TP, + value1 = Environmenal_only + Value + Social, # this is CORRECT + value10 = Environmenal10_only + Value*10*rate + Social10) |> # this is CORRECT + select(Target, Routing, CO2eqT, value1, value10) knitr::kable(summaryall, digits = 0, diff --git a/paper/PaperCEUS/PaperCEUS.pdf b/paper/PaperCEUS/PaperCEUS.pdf index 0c20aa74515dd55fa07e5abbc8f8d906cd1ed2c9..0d38b77d3b291e353fdb684c07b1d7f6439e4889 100644 GIT binary patch delta 45070 zcmZs?Q*b6+w5=W6wr!go+qP||lf1Ewj%{~r+fF)qW7|&tZ&&>n`_wrXPpw(C*5$gG zV~#PmixqAw6cTwrSsQpm5YXg20th1U^ZldmK6bvrI=q;lLuL>nW)MLC1MEM*{{!Mb zApZmEKcN2u=09Nn1MWZI|Koq&BmM`{e<1${%737?%^;u|!2=R4hCr0%D|n@CG}aaF z6IkTt2aK%cN?;NjGK1xD?PFWO`*l2T$llr0Fe0i%_U>Xq4~SZ|O#<>}Z88rVLQ^i> 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zh^e7`H>8+dc*em5Hw1-U{EUEdkibRns~ha$4*%a!>=q1`U9XA(88>u75M)+Awj12i zj!1{E#ufj@U}Xy&?k?Zo!160N=3c&zaPZO3Klx;_^ zQ2Q%%!QtVjuh}~sUVhbAR9y#p$OS@M->I|iB;P73$?Dw+)1NoE7z}Iz^znSpXM)Zf zOTBiyYRijw)w^B)>R+@ltb-KtO(sc(S3QQ`H@~4$^Aa=16SZ48?ZrFCav|%_t%J{* zlbX82qlD*bT~cIVt(^{&oc+06zsrPJ{4-!`OIZiZWi~wD>+xx&Z$i&K;NBZ_Ift(! z&*?SnuX$v1w(C41FQ}{LIv1^T7xp(`zbf+S=zy4y9c=F(6Nn96)0_j}_q@-F|EW!A f?@2<%m!JMWfH_4?6%!qSjfWS3ib`BT0^$DwottxS diff --git a/paper/PaperCEUS/PaperCEUS.tex b/paper/PaperCEUS/PaperCEUS.tex index 682dd12..ca1602f 100644 --- a/paper/PaperCEUS/PaperCEUS.tex +++ b/paper/PaperCEUS/PaperCEUS.tex @@ -347,7 +347,7 @@ \subsection{Assessing socio-environmental For the cycling legs of the journey (first and last legs), socio-environmental impacts were estimated, using the HEAT for Cycling -tool v5.0 (Kahlmeier et al., 2017) from the World Health Organization, +tool v5.2 (Kahlmeier et al., 2017) from the World Health Organization, and the \href{https://github.com/HEAT-WHO/HEAT_heatr_api}{\texttt{HEATaaS} R package}\footnote{\texttt{HEATaaS} is under development. For more @@ -412,21 +412,37 @@ \section{Results and Discussion}\label{results-and-discussion}} trips to achieve the national strategy targets (4\% and 10\%), for different route profiles. For the cycling legs of the journey (first and last legs), the environmental avoided emissions and monetized -socio-environment (SE) benefits are also presented, resulting from -replacing car trips with cycling. +socio-environment (SE) benefits are presented in \ref{tab:summary1b}, +resulting from replacing car trips with cycling. \begin{table} -\caption{\label{tab:summary1}\label{summary1}Summary of the cycling potencial of intermodality scenario and its socio-environmental benefits for the cycling legs.} +\caption{\label{tab:summary1}\label{summary1}Summary of the cycling potencial of the intermodality scenario.} \centering -\begin{tabular}[t]{llr>{\raggedleft\arraybackslash}p{6em}>{\raggedleft\arraybackslash}p{6em}>{\raggedleft\arraybackslash}p{6em}>{\raggedleft\arraybackslash}p{6em}} +\begin{tabular}[t]{llr>{\raggedleft\arraybackslash}p{7em}>{\raggedleft\arraybackslash}p{7em}} \toprule -Target & Routing & Total trips & Baseline Cycling + PT & Potencial Cycling + PT & Avoided CO2eq (ton/yr) & SE Benefits for 10 years (thousand €)\\ +Target & Routing & Total trips & Baseline Cycling + PT & Potencial Cycling + PT\\ \midrule -4\% & safe & 538 514 & 2 312 & 20 385 & 5 920 & 230 270\\ -4\% & direct & 500 880 & 2 274 & 18 944 & 6 011 & 223 720\\ -10\% & safe & 538 514 & 2 312 & 52 324 & 15 192 & 591 790\\ -10\% & direct & 500 880 & 2 274 & 48 609 & 15 414 & 574 200\\ +4\% & safe & 538 514 & 2 312 & 20 385\\ +4\% & direct & 500 880 & 2 274 & 18 944\\ +10\% & safe & 538 514 & 2 312 & 52 323\\ +10\% & direct & 500 880 & 2 274 & 48 609\\ +\bottomrule +\end{tabular} +\end{table} + +\begin{table} + +\caption{\label{tab:summary1b}\label{summary1b}Summary of the cycling potencial of intermodality scenario and its socio-environmental benefits for the cycling legs.} +\centering +\begin{tabular}[t]{ll>{\raggedleft\arraybackslash}p{6em}>{\raggedleft\arraybackslash}p{6em}>{\raggedleft\arraybackslash}p{6em}>{\raggedleft\arraybackslash}p{6em}} +\toprule +Target & Routing & Avoided Mortality (deaths/yr) & Social benefits (k€/yr) & Avoided CO2eq (ton/yr) & Environmental benefits (k€/yr)\\ +\midrule +4\% & safe & 4.1 & 12 717 & 2 958 & 238\\ +4\% & direct & 4.0 & 12 441 & 3 004 & 241\\ +10\% & safe & 10.0 & 32 820 & 7 590 & 610\\ +10\% & direct & 10.0 & 31 800 & 7 694 & 618\\ \bottomrule \end{tabular} \end{table} @@ -502,10 +518,10 @@ \section{Results and Discussion}\label{results-and-discussion}} \toprule Target & Routing & Avoided CO2eq (tons) & SE Benefits 1yr (k€) & SE Benefits 10yrs (k€)\\ \midrule -4\% & safe & 14 513 & 27 299 & 242 024\\ -4\% & direct & 14 713 & 26 572 & 235 706\\ -10\% & safe & 35 819 & 69 938 & 620 094\\ -10\% & direct & 36 207 & 67 956 & 602 972\\ +4\% & safe & 11 551 & 14 380 & 127 534\\ +10\% & safe & 28 217 & 36 861 & 325 814\\ +4\% & direct & 11 706 & 14 135 & 125 016\\ +10\% & direct & 28 487 & 35 905 & 318 062\\ \bottomrule \end{tabular} \end{table}