aelab

In aelab: Calculation of Greenhouse Gas Flux

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Installation

Install aelab package from Github. devtools need to be install though install.packges("devtools").

library(aelab)

Load other required packages. Install through install.packages("package_name") if not already installed.

library(readxl)
library(tibble)
library(lubridate)
library(stats)
library(dplyr)
library(openxlsx)

Load and process data from LI-COR

Unnecessary rows and columns are removed. NaN values of GHG data are removed.

ghg_data_path <- system.file("extdata", "ch4.xlsx", package = "aelab", mustWork = T)
ch4 <- tidy_licor(ghg_data_path, "ch4")
ch4[c(1:5), ]

Convert LI-COR time

Convert the time in LI-COR to match the time in real life (if there are any differences).

ch4 <- convert_time(ch4, min = -15, sec = 30)
ch4[c(1:5), ]

Calculate the slope based on the measurement start time

Method 1: Load from excel

Type the date and time of GHG flux measurement (start time) in excel, then load the file into R.

ref_data_path <- system.file("extdata", "reference.xlsx", package = "aelab", mustWork = T)
ref <- read_excel(ref_data_path)
ref

Calculation of the slope of methane concentration over time using the date_time value in the ref data. In the results, start_time and end_time are the time range of the data used to perform regression. slope is the slope and R-square is the R^2 of the regression. reference_time is the start time of the measurement from the input.

calculate_regression(ch4, ghg = "CH4", reference_time = ref$date_time)

The default duration of measurement is set to 7 minutes, and the number of rows selected to perform regression is 300. You can modify these values if desired using the input variables duration_minutes and num_rows according to your needs.

calculate_regression(ch4, ghg = "CH4", reference_time = ref$date_time,
                     duration_minutes = 5, num_rows = 300)

Method 2: Type from R

The start time of measurement can also be input directly into the function. Note that as.POSIXct() is necessary.

calculate_regression(ch4, ghg = "CH4", reference_time = as.POSIXct("2023-03-11 07:32:00", tz = "UTC"))

aelab documentation built on Sept. 11, 2024, 7:33 p.m.