Thermophysical Properties of Plant Leaves and Their Influence on the Environment Temperature

Jayalakshmy, M. S.; Philip, J.

doi:10.1007/s10765-010-0877-7

Cited by 86 publications

(43 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The thermal time constant (τ, s) was defined following Michaletz et al () as

τ = φ \cdot italicLMA \cdot ((), \frac{c_{italicpw}}{italicLDMC \cdot H} + \frac{c_{pd} - c_{pw}}{H}),

where φ , the ratio of projected to total leaf area, is 0.5 for flat leaves; LMA is in kilograms per square metre; c pw is the specific heat capacity of water (4,181 J·kg −1 ·K −1 ); and c pd is the specific heat capacity of dry leaf matter (J·kg −1 ·K −1 ). c pd varies by species and, here, we use 2,814 J·kg −1 ·K −1 , the mean of seven tropical tree species from Jayalakshmy and Philip (). H is a heat transfer coefficient (W·m −2 ·K −1 ) accounting for convection, radiation, and transpiration (Michaletz et al, ).…”

Section: Methodsmentioning

confidence: 99%

Differences in leaf thermoregulation and water use strategies between three co‐occurring Atlantic forest tree species

Fauset

Freitas

Galbraith

et al. 2018

Plant Cell & Environment

100

View full text Add to dashboard Cite

In the first study of leaf energy balance in tropical montane forests, we observed current leaf temperature patterns in the Atlantic forest, Brazil, and assessed whether and why patterns may vary among species. We found large leaf‐to‐air temperature differences that were influenced strongly by radiation and differences in leaf temperature between 2 species due to variation in leaf width and stomatal conductance. We highlight the importance of leaf functional traits for leaf thermoregulation and also note that the high radiation levels that occur in montane forests may exacerbate the threat from increasing air temperatures.

show abstract

“…The thermal time constant (τ, s) was defined following Michaletz et al () as

τ = φ \cdot italicLMA \cdot ((), \frac{c_{italicpw}}{italicLDMC \cdot H} + \frac{c_{pd} - c_{pw}}{H}),

Section: Methodsmentioning

confidence: 99%

Differences in leaf thermoregulation and water use strategies between three co‐occurring Atlantic forest tree species

Fauset

Freitas

Galbraith

et al. 2018

Plant Cell & Environment

100

View full text Add to dashboard Cite

show abstract

“…Similarly, higher thermal capacity and specific heat capacity of vegetation as compared to impervious surface indicate that a higher heat energy is needed to raise the temperature of UGSs. Briefly, higher thermal capacity, higher specific heat capacity, and lower thermal effusivity make UGSs a potential heat sink to keep the surrounding area cooler, and the higher thermal conductivity and higher specific heat capacity of water as compared to impervious surfaces makes it an effective heat sink [76].…”

Section: Gci Indicators and Lst Impact Factorsmentioning

confidence: 99%

Studying the Association between Green Space Characteristics and Land Surface Temperature for Sustainable Urban Environments: An Analysis of Beijing and Islamabad

Naeem

Cao

Qazi

et al. 2018

IJGI

View full text Add to dashboard Cite

Increasing trends of urbanization lead to vegetation degradation in big cities and affect the urban thermal environment. This study investigated (1) the cooling effect of urban green space spatial patterns on Land Surface Temperature (LST); (2) how the surrounding environment influences the green space cool islands (GCI), and vice versa. The study was conducted in two Asian capitals: Beijing, China and Islamabad, Pakistan by utilizing Gaofen-1 (GF-1) and Landsat-8 satellite imagery. Pearson's correlation and normalized mutual information (NMI) were applied to investigate the relationship between green space characteristics and LST. Landscape metrics of green spaces including Percentage of Landscape (PLAND), Patch Density (PD), Edge Density (ED), and Landscape Shape Index (LSI) were selected to calculate the spatial patterns of green spaces, whereas GCI indicators were defined by Green Space Range (GR), Temperature Difference (TD), and Temperature Gradient (TG). The results indicate that both vegetation composition and configuration influence LST distributions; however, vegetation composition appeared to have a slightly greater effect. The cooling effect can be produced more effectively by increasing green space percentage, planting trees in large patches with equal distribution, and avoiding complex-shaped green spaces. The GCI principle indicates that LST can be decreased by increasing the green space area, increasing the water body fraction, or by decreasing the fraction of impervious surfaces. GCI can also be strengthened by decreasing the fraction of impervious surfaces and increasing the fraction of water body or vegetation in the surrounding environment. The cooling effect of vegetation and water could be explained based on their thermal properties. Beijing has already enacted the green-wedge initiative to increase the vegetation canopy. While designing the future urban layout of Islamabad, the construction of artificial lakes within the urban green spaces would also be beneficial, as is the case with Beijing.

show abstract

“…The value was first defined in the ISBA LSM as 3 × 10 À3 K m 2 J À1 [Noilhan and Planton, 1989] and later revised to 2 × 10 À5 K m 2 J À1 [Manzi and Planton, 1994]. In the new version of the PX LSM in WRF v3.7, C v is computed from equation (5) using the high end of the ranges of the density, specific heat, and thermal conductivity for leaf mass reported by Jayalakshmy and Philip [2010] resulting in a value of C v = 1.2 × 10 À5 K m 2 J À1 .…”

Section: 1002/2015jd024406mentioning

confidence: 99%

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

et al. 2016

View full text Add to dashboard Cite

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) that employs the Pleim‐Xiu land surface model (PX LSM). Recently, PX LSM WRF/CMAQ has been updated in vegetation, soil, and boundary layer processes resulting in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the domain compared to the previous version for a period around August 2006. Yearlong meteorology simulations with the updated system demonstrate that MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green‐up in the southeast from April and move toward the west and north through August. From October to March, MODIS input does not have much influence on the system because vegetation is not as active. The greatest effects of MODIS input include more accurate phenology, better representation of leaf area index (LAI) for various forest ecosystems and agricultural areas, and realistically sparse vegetation coverage in the western drylands. Despite the improved meteorology, MODIS input causes higher bias for the surface O3 simulation in April, August, and October in areas where MODIS LAI is much less than the base LAI. Thus, improvements may be needed in the CMAQ dry deposition model for low LAI areas where deposition on the soil surface becomes important.

show abstract

Thermophysical Properties of Plant Leaves and Their Influence on the Environment Temperature

Cited by 86 publications

References 10 publications

Differences in leaf thermoregulation and water use strategies between three co‐occurring Atlantic forest tree species

Differences in leaf thermoregulation and water use strategies between three co‐occurring Atlantic forest tree species

Studying the Association between Green Space Characteristics and Land Surface Temperature for Sustainable Urban Environments: An Analysis of Beijing and Islamabad

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

Contact Info

Product

Resources

About