Work-related heat stress concerns in automotive industries: a case study from Chennai, India

Abstract

Background: Work-related heat stress assessments, the quantification of thermal loads and their physiological consequences have mostly been performed in non-tropical developed country settings. In many developing countries (many of which are also tropical), limited attempts have been made to create detailed job-exposure profiles for various sectors. We present here a case study from Chennai in southern India that illustrates the prevalence of work-related heat stress in multiple processes of automotive industries and the efficacy of relatively simple controls in reducing prevalence of the risk through longitudinal assessments.

Methods: We conducted workplace heat stress assessments in automotive and automotive parts manufacturing units according to the protocols recommended by NIOSH, USA. Sites for measurements included indoor locations with process-generated heat exposure, indoor locations without direct process-generated heat exposure and outdoor locations. Nearly 400 measurements of heat stress were made over a four-year period at more than 100 locations within eight units involved with automotive or automotive parts manufacturing in greater Chennai metropolitan area. In addition, cross-sectional measurements were made in select processes of glass manufacturing and textiles to estimate relative prevalence of heat stress.

Results: Results indicate that many processes even in organised large-scale industries have yet to control heat stress-related hazards adequately. Upwards of 28% of workers employed in multiple processes were at risk of heat stress-related health impairment in the sectors assessed. Implications of longitudinal baseline data for assessing efficacy of interventions as well as modelling potential future impacts from climate change (through contributions from worker health and productivity impairments consequent to increases in ambient temperature) are described.

Conclusions: The study re-emphasises the need for recognising heat stress as an important occupational health risk in both formal and informal sectors in India. Making available good baseline data is critical for estimating future impacts.

• work-related heat stress
• WBGT
• climate change
• automotive industry

Background

The prevalence of heat-related health risks in any strenuous job performed in hot and humid environments is well known and has been the basis for development of work-related heat stress standards 12. While the prevalence of exposures to heat stress is common in many occupations throughout the world, the quantification of thermal loads and their physiological consequences have mostly been performed in non-tropical settings. In developing countries (many of which including India are also tropical), limited attempts have been made to create detailed job-exposure profiles for various sectors. For the large workforce employed in these settings, especially in small and medium enterprises and non-industrial settings (including farming), the contributions from environmental exposures, varying workloads and physiological differences remain poorly characterised. Against this backdrop of a well-known occupational risk factor, there now looms an additional health threat from potential heat stress contributions related to global climate change 3. Climate change impacts related to heat stress are often examined in relation to heat wave-mediated effects on the general population but the recognition that climate change may exacerbate occupational heat-related risks is yet to develop. With the majority of workplace settings in developing countries being heavily influenced by outdoor temperatures (in the absence of mechanical cooling), it can be expected that both indoor and outdoor workers may experience heat stress. Even relatively modest increases in ambient temperatures could be expected to tip large worker populations exposed to ‘near limit values’ of heat stress over the threshold into the realm of experiencing heat stress-related health risks.

The Indian automotive industry is a major economic sector and has undergone rapid expansion since 1991 with Governmental deregulation of the sector. For instance, production of vehicles has increased nearly five-fold from about 2 million in 1991 to 9.7 million in 2006. Chennai, formerly Madras, is the fourth largest metropolis in India and is the capital of the southern coastal state of Tamil Nadu. Chennai accounts for 60% of the country's automotive exports and is sometimes referred to as ‘the Detroit of India’. The sector employs nearly 250,000 workers. Although most manufacturing plants in this sector are large units that are well regulated for most occupational health and safety hazards, heat stress exposure remains quite prevalent in many processes. Chennai temperatures also range from around 21°C (between December and February) to around 37°C (between March and September). Some months record temperatures as high as 42°C. Although most processes in the automotive sector are performed indoors, lack of controls within the work environment and outdoor jobs make workers prone to heat stress from both ambient temperatures as well as process-generated heat.

We present here a case study from Chennai in southern India that illustrates the prevalence of work-related heat stress within multiple processes of automotive industries and the efficacy of relatively simple controls in reducing prevalence of risks through longitudinal assessments. We also made limited assessments in two other sectors to estimate the likely percentages of workers at risk from heat stress in various processes. Since newly established plants have routine monitoring facilities, the choice of newly established automotive plants to conduct this pilot in a rapidly expanding sector allowed us to identify opportunities to create longitudinal baseline data for assessing efficacy of interventions as well as modelling future impacts from climate change.

Materials and methods

We conducted workplace heat stress assessments in automotive and automotive parts manufacturing units according to the protocols recommended by NIOSH, USA. Locations for measurements were selected based on the initial survey results; these included indoor locations with process-generated heat exposure, indoor locations without direct process-generated heat exposure and outdoor locations. Nearly 400 measurements of heat stress were made over a four-year period at more than 100 locations within eight units involved with automotive or automotive parts manufacturing in the greater Chennai metropolitan area. Since most workplace locations were not air-conditioned and therefore likely to be influenced by outside temperature and time of day/season, measurements were always made during the hottest part (11:00–14:30) of the day in the months of May or June, with repeated annual assessments. Measurements were used to recommend interventions at selected locations in the automotive units and multiple longitudinal measurements were made at locations where controls were implemented in order to assess their efficacy.

In addition, cross-sectional assessments were made in multiple processes in glass manufacturing and textile industries. We then collected information on workforce strengths in all three sectors to estimate likely percentages in each sector that were likely to be at risk from work-related heat stress.

The measurements were carried out using an area heat stress monitor (Model Questemp° 34, manufactured by Quest Technologies, USA) that calculates the wet bulb globe temperature (WBGT) to assess heat stress. The instruments used for the measurements comply with the standards set out by American Conference of Governmental Industrial Hygienists (ACGIH). The necessary information on workload, clothing worn, worker's time-activity pattern and acclimatisation was collected on-site, to make appropriate adjustments to the measured WBGT value. The threshold limit value (TLV) was computed by taking spot readings throughout the work-shift and on the basis of worker description of workload, using a ‘clo’ factor of 0.6 for summer work uniforms. This ‘clo’ factor contributes to a WBGT correction factor of 0°C. For light workloads and full acclimatisation of the workers, a TLV of 29.5°C was used and in case workstations did not require workers to stay permanently, a TLV of 29.5°C was used assuming light work (e.g. inspection work) and full acclimatisation. The adjusted values were compared to the prescribed TLVs recommended by the ACGIH.

Descriptive statistical analysis was done using the software ‘R’.

Results

Heat stress exposure in various processes of automotive and automotive parts manufacturing

Fig. 1 shows the distribution of measured heat stress indices across locations. Many indoor locations were found to be close to or exceeded the recommended TLVs. Further, indoor WBGT indices were observed to be largely driven by outdoor temperatures as they were uniformly high even in locations with no process-generated heat components.

Figure 1.  Box plots illustrating the distribution of measured WBGT values at various indoor locations in automotive or automotive parts manufacturing units (dashed lines indicate the range of outdoor WBGT values across locations; dark boxes indicate locations with process-generated heat contributions and light boxes indicate locations without process heat contributions (i.e. only ambient temperature contributions), respectively, to heat stress.

Work locations key: With process heat contributions – A: PTCS (varnishing oven), B: cab furnace, C: paint shop, D: fuel injection manufacturing, E: tube manufacturing, F: canteen (boiler area). Without process heat contributions – G: body shop (general shop floor), H: fuel injection manufacturing (general shop floor), I: paint shop (general shop floor), J: stamping, K: wheel alignment and engine deck, L: material storage and stores, M: PTCS (starter, armature and shaft areas), N: team meeting areas, O: plastic moulding area, P: utility areas, Q: canteen (general), R: brazing, S: trim and chassis.

Workloads prevalent at each of the locations shown in Fig. 1 (that were used to compute the corresponding WBGT index) are illustrated in Fig. 2.

Figure 2.  Workloads at various locations in relation to WBGT indices (dark boxes indicate locations with process-generated heat contributions and light boxes indicate locations without process heat contributions (i.e. only ambient temperature contributions), respectively, to heat stress; dashed lines indicate TLV for fully acclimatised light work and dotted-dashed lines indicate TLV for fully acclimatised moderate work).

Work locations key: With process heat contributions – A: PTCS (varnishing oven), B: cab furnace, C: paint shop, D: fuel injection manufacturing, E: tube manufacturing, F: canteen (boiler area). Without process heat contributions – G: body shop (general shop floor), H: fuel injection manufacturing (general shop floor), I: paint shop (general shop floor), J: stamping, K: wheel alignment and engine deck, L: material storage and stores, M: PTCS (starter, armature and shaft areas), N: team meeting areas, O: plastic moulding area, P: utility areas, Q: canteen (general), R: brazing, S: trim and chassis.

Many locations with light workloads were still in excess of TLVs (indicating the need for engineering controls). Other locations with moderate workloads were close to or exceeded the TLVs (indicating opportunities for both administrative and engineering controls).

Qualitative assessment of work practices and implementation of controls

In order to make specific recommendations to the units for heat stress exposure reduction, we undertook an observational qualitative assessment for existing work practices and existing controls. A number of recommendations ranging from provision of hydration breaks to improved natural ventilation and installation of air cooling devices were made. Based on longitudinal measurements at the same facilities, some of the key post-intervention improvements are shown in Table 1.

Table 1. Improvements in heat stress-related exposures at select locations

Location	Work-load	Mean WBGT (in °C) 2005	Mean WBGT (in °C) 2006	Mean WBGT (in °C) 2007	Mean WBGT (in °C) 2008	TLV (in °C)	Recommendation implemented
Stamping (n=24)	Moderate	30.5	29.6	29.2	27.1	27.5	Improvement of cross-ventilation by installing more windows on the wall
Body shop (n=48)	Moderate	29.9	30.7	–	28.9	27.5	Improvement of cross-ventilation by installing more windows on the wall
							Provision of lime juice and milk during the hot season
Paint shop (loading/unloading) (n=54)	Light to moderate	32.2	–	31.2	29.1	27.5	Installation and maintenance of air cooling ducts
Paint shop (oven operations) (n=24)	Light	34.2	–	–	29.2	29.5	Thermoinsulation of the oven
Engine/chassis/wheel alignment (n=34)	Light	32.0	–	33.8	31.4	29.5	Increasing the number of breaks during summer
Batch and hold yard shed (n=38)	Light	33.4	33.3	32.2	31.7	29.5	Installation and maintenance of air cooler

Note: WBGT measurements were made during the hottest part of the day.

Estimating potential for work-related heat stress across select sectors

As an attempt to understand the potential scale of impacts related to work-related heat stress, in order to understand possible ramifications for climate change-related exacerbation, an estimate of the proportion of workers at risk are provided for selected sectors. This is based on measurements that were made and information collected as part of the routine occupational hygiene monitoring services provided by the investigators’ University department. While the case study summarised above had the single largest set of longitudinal measurements, the other sectors had a smaller number of cross-sectional measurements. The exposure implications for select processes in three such sectors, namely automotive parts manufacturing, glass manufacturing and textiles are detailed in Table 2.

Table 2. Exposure profiles for heat stress in select processes of automotive, glass and textile manufacturing sectors in southern India

Industrial sector	Location	Name of the process	Physical workload	Number of workers	Average WBGT (in °C)	TLV for WBGT (in °C)	Exceeding TLV	Estimated % of population at risk
Automobile/automotive parts manufacturing	Indoor with process heat	Paint shop	Moderate	178	30.4	27.5	Yes	100
	Indoor without process heat	Stamping	Moderate	90	29.1	27.5	Yes	51.3
		Body shop	Moderate	340	28.9	27.5	Yes
		TCF	Moderate	312	31.3	27.5	Yes
		Engine plant	Moderate	172	30.6	27.5	Yes
		Launch	Moderate	15	30.2	27.5	Yes
		MP & L	Light	45	29.4	29.5	No
			Moderate	100	29.3	27.5	Yes
		P & D	Light	100	28.2	29.5	No
			Moderate	26	28.3	27.5	Yes
		Admin	Light	1,000	25.6	29.5	No
		Maintenance	Moderate	150	29.7	27.5	Yes
	Outdoor	Maintenance	Moderate	50	30.9	27.5	Yes	100
		Gardening	Moderate	25	30.9	27.5	Yes
			Heavy	50	30.9	26	Yes
Glass manufacturing	Indoor with process heat	Furnace area	Light	25	31.9	29.5	Yes	100
		Port 3	Light	14	37.8	29.5	Yes
		Bay 1	Light	12	38	29.5	Yes
		Bay 2	Light	25	40.9	29.5	Yes
		Bay 17	Light	48	34.9	29.5	Yes
		Annealing area 1	Light	7	35.6	29.5	Yes
		Annealing area 2	Light	6	38	29.5	Yes
		Cold end	Light	9	32.4	29.5	Yes
		Mirror plant – hot	Light	7	29.8	29.5	Yes
	Indoor without process heat	Mirror plant – wet	Light	12	28.5	29.5	No	31.2
		Bay loading area	Moderate	76	29.3	27.5	Yes
		Admin	Light	200	26	29.5	No
		Maintenance	Moderate	20	29.8	27.5	Yes
	Outdoor	Maintenance	Moderate	10	31	27.5	Yes	100
		Gardening	Moderate	18	31.2	27.5	Yes
			Heavy	10	31.1	26	Yes
Textile manufacturing	Indoor without process heat	Blowing	Moderate	19	26.8	27.5	No	28.1
		Carding/drawing/roving	Moderate	15	28.8	27.5	Yes
		Combing	Moderate	22	26.5	27.5	No
		Spinning	Moderate	46	30.3	27.5	Yes
		Winding/reeling/doubling	Moderate	31	27.2	27.5	No
		Weaving	Moderate	47	27	27.5	No
		Admin	Light	50	26.8	29.5	No
		Maintenance	Moderate	5	29.6	27.5	Yes
	Outdoor	Maintenance	Moderate	5	29.7	27.5	Yes	100
		Gardening	Moderate	2	29.6	27.5	Yes
			Heavy	3	29.6	26	Yes

Discussion

Results from over 400 measurements across multiple locations and industries clearly indicate that many processes even in organised large-scale industries have yet to control heat stress-related hazards adequately. Although a systematic review is not available, studies conducted in many other sectors in India reveal a high prevalence of heat-related exposures in both the formal and informal sectors, including farming, glass manufacturing, stone quarrying and crushing, mining, etc. 456.

While indoor work without process-generated heat exposures should be relatively less hazardous, because of the tropical climatic conditions in India, and particularly in the south, and the lack of controlled built environments, ambient temperatures influence work-related heat exposures even in indoor settings. This is further compounded by manual handling and other ergonomic hazards, also widely prevalent and poorly controlled in many industrial processes. Outdoor work is very common in India. Many jobs in the service sector (transport and local trade), construction, municipal administration and small businesses, in addition to specific processes in manufacturing and mining, are performed outdoors and here the impacts of high ambient temperatures can be particularly detrimental.

Exposure information available from selected studies in India is summarised in Table 3 along with estimates of worker populations employed in these sectors. While reliable measurements are not available in many sectors to estimate worker populations at risk, the sectors profiled in this paper serve to illustrate the likely widespread prevalence of such risks. Although the measured values reported in many studies, including this one, have not been able to capture the full range of exposures that may be experienced across seasons and at different times during the day, the observed prevalences of work-related heat stress reported in Table 2 are likely to be at the low end of exposure spectrum as they were limited to large scale and relatively newly established units.

Table 3. Heat stress and worker profiles for selected industry sectors in India

Sector	Range of heat stress values (WBGT) measured (^oC)	Estimated worker population in 1,000s (as per Indian National Sample Survey, 2000)	Reference
Agriculture	34.4–42.2	237,786	Nag et al. 5
Glass manufacturing	30–40	Not available	Srivastava et al. 6
Ceramics	43–54	Not available	Parikh et al. 7
Mining	25–31	2,263	Mukerjee et al. 8
Tanning	28–41	1,081	Conroy et al. 9
Textiles	27–39	10,480	Sankar et al. 10

As illustrated by the efficacy of relatively simple controls in the units included for assessment, there exist several options to install and/or improve existing controls. It is particularly important to recognise that while administrative controls appear more attractive (as they do not require initial large capital investments), the loss in productivity could be substantial if one were not to genuinely implement appropriate controls to ensure health and comfort of workers. The cost–benefit thus should duly address health and quality of work impacts while comparing across control strategies. In developing countries there is also a socio-cultural dimension of ‘risk perception’ that argues against provision of air-conditioned work spaces in the shop floor. The added value of having comfortable work spaces insulated from external climate vagaries for health and productivity thus remain largely uncharacterised.

Given the large propensity of workplaces that expose workers to near or more than permissible levels of heat stress, it could be expected that even modest increases in temperature resulting from climate change could significantly alter the distribution of exposures and related health impacts. Work ability at even the lowest intensities of work may be severely limited if WBGT indices are increased beyond the already high values recorded in workplaces. The effects are also likely to make poorer workers even more vulnerable on account of their poorer health status, limitations in accessing controlled (air-conditioned) workplaces/homes and greater likelihood of engaging in heavy work. Although work-related heat stress information is frequently collected in many workplaces, many variables can influence measured values and accompanying heat stress such as time of day, month, location of measurement, workloads and availability and efficacy of controls. While it could be expected that increase in work-related heat stress may hamper productivity (for example, due to increased frequency of rest breaks, diminished work output and lost work days), the quantitative exposure relationship between heat stress and productivity remains to be characterised across work settings. In order to maintain adequate surveillance on workplaces, modelling approaches are needed that could use routinely collected weather station data in relation to measured WBGT indices at workplaces over a local region to estimate population level impacts on productivity and health. The development of such Population Heat Exposure Profiles (PHEPs) are being explored (Kjellstrom and Lemke, unpublished) and will likely allow monitoring of trends in ambient temperature and related implications for work-related heat stress across space and time as well as across multiple work place configurations in developing country settings, where routine workplace data is not always available and accessible.

Conclusions

The present case study serves to re-emphasise the need for recognition of heat stress as an important occupational health risk in both formal and informal sectors in India. Control of heat stress may have multiple co-benefits in terms of better health, improved productivity, lower rates of accidents, lower rates of morbidity and improved sense of comfort and social well-being. With the threat of climate change-related impacts looming large on developing countries including India, there is an imminent need to include this set of heat-related impacts while modelling health effects related to climate change. Making available good baseline data is critical for estimating future impacts and the case study presented here represents one such pilot effort in southern India.

Conflict of interest and funding

The authors have not received any funding or benefits from industry to conduct this study.

Acknowledgements

We thank Professor Tord Kjellstrom for his technical guidance in presenting the case study in the form of this manuscript. His insights in interpreting the results in context of emerging implications of climate change-mediated impacts on worker productivity were particularly useful for data analysis and the authors are grateful for his patient involvement.