A Quantitative Approach Towards Human-Thermal Vulnerability

Human vulnerability towards extreme heat exposure has generally been expressed as the cumulative expression of social, demographic, agricultural, environmental factors. Besides this, behavioural and physiological characteristics of individual may be responsible for significant differences in thermal perception and health effects towards extreme heat. The present endeavour is towards the identification and derivation of the quantitative scale of human-thermal vulnerability considering the social, human and thermal indicators. The study illustrates district-wise and village-wise human vulnerability considering different conventional indicators from social and environmental domain along with the factors accountable towards human warmth. The vulnerability was assessed, as representative for the state of Punjab, Haryana and West Bengal of India. Principle Component Analysis (PCA) was used as means of aggregating diverse indicators and to develop clusters of different variables as the respective principal components. The analysis indicated the utility of the expression of different types of vulnerability and the reasons to consider various indicators and their relative weightages. Accordingly, a quantitative scale of human-thermal vulnerability is arrived at, considering the social, human and thermal indicators.


Abstract
Human vulnerability towards extreme heat exposure has generally been expressed as the cumulative expression of social, demographic, agricultural, environmental factors.
Besides this, behavioural and physiological characteristics of individual may be responsible for significant differences in thermal perception and health effects towards

Introduction
Worldwide concerns have been raised about the potential impacts of the changing climate, climate variability and the associated weather extremes (Aubrecht and Özceylan, 2013). Evidences reaffirm that extreme climatic condition makes the human being more and more vulnerable ( intensifies the health risk due to elevated physiological responses and inadequacy in the thermoregulatory controls that manifest into a varied forms of heat disorders and injury (Parsons, 2009). Excessive storage of heat in the body due to inappropriate evaporative heat loss (Zhao et al., 2009) in the moist thermal environment significantly decrease labour productivity (Dunne et al., 2013). Several studies (Sahu et Figure 1). Such parameters have been chosen to describe sensitivity and adaptive capacity of the exposed population, with least consideration of individual physiological, psychological (Ford et al., 2006) and behavioural characteristics (Vincent, 2004). Human being exposed towards similar climatic condition may experience different perception and health effects, leading to variations in the vulnerability (Nikolopoulou and Steemers, 2003;Sen and Nag, 2019b). Undoubtedly, the assessment of vulnerability considering the tolerance, sensitivity, and adaptive capacity of the individual in tropical climatic area is scanty (Nag et al., 2013). Needless to mention that establishing the degree of vulnerability of a population towards heat exposure is a complex phenomenon. The challenge remains in defining the potentials of risk due to heat exposure in individual level involving a combination of location-dependent physiological variables, social and environmental factors. This study is a modest endeavour to arrive at the degree of vulnerability integrating different facets of vulnerability. Such an approach may be applied to varied regional and local perspectives.

Methods and materials
In the present contribution, vulnerability assessment was done incorporating multidimensional data. Moreover, individual physiological and behavioural parameters were integrated along with the conventional parameters (as mentioned in Figure 1     -Rural population Overpopulation in rural areas creates pressure over natural resources (Rao et al., 2013). In such areas, more people are directly exposed to extreme climatic events (Gbetibouo et al., 2009  Social data were obtained from Census 2011 for the selected villages to achieve the degree of social vulnerability. 28 variables (Table 2) were treated to assess the social vulnerability of these villages adopting the similar methodology of the PCA technique. The relevance of these social variables in vulnerability study has already been briefly described. For the micro-region vulnerability assessment, some basic amenities and assets parameters were also considered from the census data in correspondence to each village. Percentage of these parameters in the individual villages denotes the living standards.
Observations of over 1000 people were considered in the assessment of the human thermal vulnerability for the selected villages. Subjective and objective measurements, such as, height, weight, body temperature, heart rate of the surveyed population were obtained at the time of field investigation of the mentioned villages.
The objective measurements and the perceived responses recorded after taking ethical consent of the workers for their participation in the study. The environmental parameters included dry-bulb (Ta) and wet bulb temperature (Twb) measured by the dry and wet bulb thermometer, and wind-speed (v) by an anemometer. Other Based on the environmental and biophysical parameters (Table 3)  Metabolic heat production in the body is significantly related with the working load. Increasing workload exacerbate heat load in the body and therefore decrease productivity (Nag and Nag, 1992).

Results
The social indicators (Table 1) Figure 4b) and represented as same. The analysis shows differences in the village wise social and thermal vulnerability and supports that socially vulnerable regions might not indicate climatic vulnerable and vice versa.   However, in the context of climatic exposure, physical characteristics cannot alone manifest vulnerability (Wolf and McGregor, 2013). Gaps remain in the micro-level vulnerability assessment (Vincent, 2004) and creating a model for future projection of vulnerability over varied climatic regions. Also, there is an obvious need to identify such indicators which can be used globally and may apply to propose a modelling approach (Kelly and Adger, 2000) towards the assessment of human vulnerability. The present analysis is affirmative that the interaction between biophysical and social processes may be suitable for micro to macro-regional (e.g., village and district level) vulnerability assessment. In this analysis, indicators were used to assess different types of vulnerability (such as social, human, climatic and thermal vulnerability).
Further stated that any single parameter might not be adequate to determine the degree of vulnerability (Adger et al., 2004;Vincent, 2004).