Climatological Human Comfort Using Heat and Humidity Index (Humidex) in Gadingkulon, Malang

Masitoh, Ferryati; Rusydi, Alfi Nur

doi:10.1088/1755-1315/412/1/012026

Cited by 10 publications

(14 citation statements)

References 15 publications

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“…Large scale rapid screening previously has been done for fatty acid profile in groundnut, major wood characteristics in Eucalyptus (15,16). Electromagnetic radiation from 780 to 2,500 nm in the NIR region is covered by this technique (17), and absorption of Abbreviations: NIRS, near infrared reflectance spectroscopy; MPLS, modified partial least square; TDF, total dietary fiber; RSQ, coe cient of determination; RPD, ratio of performance to deviation; SEP, standard error of performance. http://fdc.nal.usda.gov IR light by the substance under examination is the basis for infrared spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm

et al. 2022

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Cowpea (Vigna unguiculata (L.) Walp.) is one such legume that can facilitate achieving sustainable nutrition and climate change goals. Assessing nutritional traits conventionally can be laborious and time-consuming. NIRS is a technique used to rapidly determine biochemical parameters for large germplasm. NIRS prediction models were developed to assess protein, starch, TDF, phenols, and phytic acid based on MPLS regression. Higher RSQexternal values such as 0.903, 0.997, 0.901, 0.706, and 0.955 were obtained for protein, starch, TDF, phenols, and phytic acid respectively. Models for all the traits displayed RPD values of >2.5 except phenols and low SEP indicating the excellent prediction of models. For all the traits worked, p-value ≥ 0.05 implied the accuracy and reliability score >0.8 (except phenol) ensured the applicability of the models. These prediction models will facilitate high throughput screening of large cowpea germplasm in a non-destructive way and the selection of desirable chemotypes in any genetic background with huge application in cowpea crop improvement programs across the world.

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Section: Introductionmentioning

confidence: 99%

Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm

et al. 2022

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“…The effect of humidity depends on air temperature. At high temperatures humid air prevents the body from sweating, which increases the feels-like temperature, while at low temperatures humid air deposits cold moisture on warm skin, increasing its thermal conductivity and thus decreasing the feels-like temperature 54 .…”

Section: The Building-adjusted Internal Temperaturementioning

confidence: 99%

A global model of hourly space heating and cooling demand at multiple spatial scales

Staffell,

Pfenninger,

Johnson

2023

Nat Energy

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Accurate modelling of the weather’s temporal and spatial impacts on building energy demand is critical to decarbonizing energy systems. Here we introduce a customizable model for hourly heating and cooling demand applicable globally at all spatial scales. We validate against demand from ~5,000 buildings and 43 regions across four continents. The model requires limited data inputs and shows better agreement with measured demand than existing models. We use it first to demonstrate that a 1 °C reduction in thermostat settings across all buildings could reduce Europe’s gas consumption by 240 TWh yr−1, approximately one-sixth of historical imports from Russia. Second, we show that service demand for cooling is increasing by up to 5% per year in some regions due to climate change, and 5 billion people experience >100 additional cooling degree days per year when compared with a generation ago. The model and underlying data are freely accessible to promote further research.

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“…Nevertheless, the uncomfortable class still dominates. In contrast to THI (Masitoh & Rusydi, 2020). In contrast to humidity, air temperature conditions will decrease along with increasing elevation (Fu & Shen, 2016).…”

Section: Assessment Of the Comfort Level Of The Cilegon City Communit...mentioning

confidence: 89%

“…On the other hand, sub-districts that have dense vegetation density have a high comfort level. Masitoh and Rusydi (2020) proved comfortable and rather comfortable areas separated into medium and high-density levels, while uncomfortable to very uncomfortable in areas of sparse vegetation.…”

Section: The Impacts Of Vegetation Density On Community Comfort In Ci...mentioning

confidence: 95%

Assessment of the Comfort Level of Cilegon City Communities Based on Surface Temperature, Vegetation Density, and Built-Up Land

Fitriani,

Hadibasyir,

Fikriyah

et al. 2023

Advances in Social Science, Education and Humanities Research

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Cilegon's appeal as an industrial city is heavily influenced by urbanization. The most important impact of urbanization is the increasing need for residential, commercial, and industrial buildings, resulting in the rapid conversion of green land into built-up land. Reduced vegetated areas that function to absorb solar heat causes surface temperatures to increase so that the comfort of city residents decreases. This study aims to analyze the comfort level of the people of Cilegon City based on land surface temperature, vegetation density, and built-up land. The approach used was based on remote sensing based on Landsat-5 TM and Landsat 8 OLI/TIR image data using the Normalized Different Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Enhanced Built-up and Bareness Index (EBBI) index transformations, Land Surface Temperature (LST), and Temperature Humidity Index (THI). The results showed that developments in LST, NDVI, NDBI, and EBBI result in changes in THI. LST experienced an increase in temperature until it reached an average LST of 30.65 °C in 2019. This condition increased in temperature, causing a decrease in the comfort level of Cilegon City, where in 2019, most of the area was uncomfortable with a little comfort. Comfortable conditions were only felt in densely vegetated areas, while discomfort was felt in densely built-up areas. The correlation results showed a positive relationship between LST, NDBI, EBBI, and THI. There was a negative relationship between NDVI and THI. That is, an increase in LST, NDBI, and EBBI caused an increase in THI, while an increase in NDVI caused a decrease in THI and vice versa.

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Climatological Human Comfort Using Heat and Humidity Index (Humidex) in Gadingkulon, Malang

Cited by 10 publications

References 15 publications

Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm

Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm

A global model of hourly space heating and cooling demand at multiple spatial scales

Assessment of the Comfort Level of Cilegon City Communities Based on Surface Temperature, Vegetation Density, and Built-Up Land

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