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Analysis: Average change over time #34
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FanWangEcon
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- Part 1 of #34, all hours day and night - output csv file across thresholds - parallel scripts to generate threshold-specific and aggregate files
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- Part 2 of #34, day time hours only - output csv file across thresholds - parallel scripts to generate threshold-specific and aggregate files
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- Generate output files for mean child tab and figures - Generate mean child table, table A done - Change folder name 6 to 22 #34
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- Core function outputs file without the word pm10 in variable string #11 - Core function outputs categorical variable labeling group-specific and cross-group and overall-results #11 - New local run support parallel node, temperature array helper func - New Run scripts file - Updated 24 hour and day time scripts to use new local run support - Updated CSV outputs for 24 hour and day time results with no pm10 in variable names and categorical label #34
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Average change over time
We compute change overtime in the exposure (units = share of time during the course of the year) of the average child to temperature over different thresholds. We consider a range of temperature from -40 to 40 at 1 degree intervals. We compare between 1990 and 2020. Our share of time is approximated by hourly ERA5 temperature meaures.
Part 1 Implementation with day and night time hours
Call
PrjCEC::ffp_cec_inequality_func()
and[PrjCEC::ffp_demo_loc_thres_dist()](https://github.com/ClimateInequality/PrjCEC/blob/main/R/ffp_cec_thres_combine.R)
, with:Control parameters:
stv_grp_demo <- "age_group_m3"
st_demo_subgroup <- "0_14"
stv_grp_loc <- "all_locations"
st_time_stats <- "share"
ar_temp_bound <- seq(-40, 40, length.out = 81)
bl_greater <- TRUE
Input files:
df_china_census_county_1990.csv
anddf_china_census_county_2020.csv
df_era5_utci_china_1990_hour.csv
anddf_era5_utci_china_2020_hour.csv
st_file_key_popgrp <- "df_key_demo_china_census_1990.csv"
st_file_key_loc <- "df_key_loc_china_coord2county_1990.csv"
st_file_key_loc_agg <- "df_key_loc_china_county2province_1990.csv"
Output files:
data-res/dm_90h24_share_gr_age_group_m3is0_14_all_locations.csv
data-res/dm_20h24_share_gr_age_group_m3is0_14_all_locations.csv
Part 2 Implementation with only daytime hours
All same as in part 2, but first run #35 to generate day time hours only, and then use different temperature files.
Code files:
Input files:
df_era5_utci_china_1990_hour6t22.csv
anddf_era5_utci_china_2020_hour6t22.csv.
Output files:
data-res/dm_90h6t22_share_gr_age_group_m3is0_14_all_locations.csv
data-res/dm_20h6t22_share_gr_age_group_m3is0_14_all_locations.csv
Part 3 Implementation with non-summer only time
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