Published in IIPS Mumbai, ENVIS center, Volume 2, No. 4, December 2005

 

ON LINKAGES BETWEEN POPULATION AND ENVIRONMENT:  SOME EVIDENCES FROM INDIA

by 
Gopal K Kadekodi  Director,ISEC,Bangalore



Introduction

 

The link between environmental situation in any particular site, location, region, state or nation (even global) is a complex one (Boulding: 1966; Markandya, 1998, Grossman and Krueger: 1995, 1996; Arrow et aI., 1995; Seldon and Song: 1994; Shafik and Bandyopadhyay: 1992; Beckennan: 1992). The issue is not only a static one but one of the dynamics of the linkages. Apart from population and its concomitants (age, sex composition, health status etc.), other socioeconomic components that are necessary to be linked and analyzed are: income level and its degree of inequality, human devc1opoment and poverty, and property rights on resources (Kadekodi and Venkatachalam,2005). A clear understanding of the complexity is possible only with long time series of data and well designed econometric models (Kadekodi, 200 I; Duraiappah, 19(8). Duraiappah et al (2000) formulate such a dynamic model, which in brief they term as PASIR (Pressure-Activity-State-Impact-Response) model.

 

As far as environment and natural resources are concerned, both the stock of them and the flow of income, welfare and environmental services from them are to be evaluated to understand the links between human and environmental development. India is endowed with 675,540 sq kms of forest cover (i.e. 20.55% of the total geographical area of 3,287,263 sq kms), of which about 416,809 sq kms arc under dense forest cover. The country is also rich with about 7,515 kms of coastal length, rich in fishery and marine resources. About 84, I 48 sq kms of the geographical area of the country is under various rivers and streams, with an additional area of about 21,960 sq kms under lakes, reservoirs and canals. However, with the growth of industrialization and population, a large number of environmental problems have cropped up, among which the air and water pollutions dominate. Against this background, the amount of wastelands has been estimated to be 638,) 18 sq kms (or about 19% of the geographical area of the country). According to the estimates made by the Planning Commission, between 1987 and 1997, states like Andhra Pradesh have witnessed highest deforestation of over 14%, the least loss being in Kerala. Apart from traditionally known rivers such as Saraswati having vanished, both the groundwater tables and catchments of the river basins have lost their capacities as 'catchments'. As documented by Agarwal and Narain (1997), traditional water harvesting structures such as tanks have significantly vanished in many parts of the country. As a source of irrigation, between 1970-71 and 1997-98 the area under tank irrigation has come down from 4.1 to 3.1 million hectares (Kadekodi, 2004). Because or their concentration in the industrial and heavy transport intensive areas, the emission loads from these sectors can not be ignored, though, on a per capita or per geographical area basis they may sound too small. As of 1990, about 2.18() million tones of carbon monoxide is being emitted annually from various industrial and transport sectors. Likewise, in 1990, about 156 million tonnes of carbon emission took place from Indian continent, which rose  to 251 million tonnes by 2001 (www.eia.doe.gov/emeu/cabs/indiaenv.htm). Such massive emissions of pollutants arc acting against the health and quality of life. The forest degradation, depletion of water bodies, and degradation of ground and surface water qualities, deterioration of soil qualities due to excessive use of chemical fertilizers and pesticides, non-disposal or nonrecycling of urban and other solid wastes, climate change etc., are all increasing. They are resulting in incidences of adverse effects on human and animal lives. The deterioration or health status, increasing incidences and reemergence of diseases such as malaria, and other parasitic attacks due to climate change etc., are coming in the way of human development. According to WHO, about one million people die of malaria annually in the world today. Increased incidences of respiratory diseases and heart disorders are attributed to urban and industrial air pollution. According to the estimates made by the World Health Organization (WHO) about 3.3 million people die every year from diarrheal diseases globally and at anyone time there are 1.5 million with parasitic worm infections stemming from human excreta and solid waste in the environment (Bojo et al: 2001 ).

 

This brief note is to highlight the complexities in establishing or testing the linkages or adversaries between environment, population and human development, in any specific situation, more so, at the state levels in India. 

 

 

 

 

 

Status at the National Level

 

It may be useful to take a look at the recently estimated Environmental Sustainability Indices (ESI) for India (and likewise for 145 other countries in the world) by the Yale Centre for Environmental Law and Policy (2004), based on 76 variables. As can be seen from a comparable scenario among the neighbouring countries (Table 1), Indian status of environmental sustainability is better than China, but worse than Malaysia, Bhutan, Indonesia, or Sri Lanka. Globally speaking, the highest ESI rank is observed for Finland with a score of 75.1 and lowest being North Korea with 146th rank and a score of 29.2. India ranks hundred and one in the global ordering. Furthermore, among 21 countries with high population density, India ranks seventh, Japan as number one (with ESJ score of 57.3) and North Korea as twenty first (with ESI score of 29.2). 

 

A comparison between the ESI and HDI ranks indicates that among the neighbouring south Asian countries, as compared to the status of HDIs, the variation in environmental status is much less. Secondly, countries like Bhutan and Indonesia with very high ESI seem to be low in their HDI rankings. Likewise, highly populated countries like China seem to be much better in HDI, but very low in ESI ratings. The low level of correlation coefficient (i.e. 0.102) between ESI score and HDI score for these countries suggests that improvement in human development alone is not sufficient to ensure environmental sustainability and vice versa.

 

Table 1: Environmental Sustainability Index and Human Development Index for India and other Asian Countries

Country

 Envir onme ntal Susta inabili ty Index (ESI)

ESI Rankin g On A Global Scale

HDI (2004)

HDI Ranks

Malaysia

54.0

23

0.793

59

Bhutan

53.5

43

0.536

134

Indonesia

48.8

53

0.692

111

Sri Lanka

48.5

79

0.740

96

Nepal

47.7

85

0.504

140

Phillippines

42.5

97

0.753

83

India

45.2

101

0.595

127

Bangladesh

44.1

114

0.509

138

Pakistan

39.9

131

0.497

142

China

38.6

133

0.745

94

 

Source: Yale Center for Environmental Law and Policy (2005) and www.undp.org.

 

If one looks closely at the performance of India on ESI (see Table 2), the following major observations can be made:

  • Out of the 21 major indicators included in ESI, twelve of them are negative (some very high, and some marginal), leaving the remaining nine to be positive; 

  • All the major indicators of air, water, biodiversity and land related indicators are negative;

  •  In terms of policy interventions, attempts to reduce environment related natural disaster vulnerability is very poor (with a high negative score). 

  • More than population dynamics, other factors influence the environment directly and significantly.

All these are, summarily, some glimpses of macro-level linkages between human and environmental developments for India in the most recent periods. Do they have any message for understanding the linkages between these two, as suggested by Brundtland Commission report? That is not easy to answer. The better answer lies in analyzing them more and more at the disaggregated level, at the state, district and even village levels. 

 

In brief, three different types of links between environmental matters and their changes are affecting the quality of life. They are the increasing blue environmental matters (such as pollution and degradation of air and water quality), second, depletion and deterioration of resources such as forest, land and water bodies, and third, loss of links between livelihood supports to population and natural resources. 

 

Table 2: Scores for different components of ESI for India

 

AIR QUALITY

 

-0.98

Biodiversity

 

-0.62

Land

 

-0.36

Water Quality

 

-0.96

Water Quantity

 

-0.75

 

 

 

Reducing Air Pollution

 

-0.28

Reducing Ecosystem Stress

 

0.32

Reducing Population Stress

 

0.12

Reducing Waste &

 

0.35

Consumption Pressures

 

 

Reducing Water Stress

 

-0.27

Natural Resource

 

-0.25

Management

 

 

 

 

 

Environmental Health

 

0.08

Basic Human Sustenance

 

-0.04

Reducting ENV. Related

 

-0.37

Natural Disaster

 

 

 

 

 

Environmental goverence

 

0.04

Eco-effciency

 

 

Private Sector

 

0.50

Responsiveness

 

 

Science and Technology

 

-0.28

International Collaborative

 

0.67

Efforts

 

 

Greenhouse Gas Emissions

 

-0.37

Reducing Transboundary

 

0.92

Environmental Pressures

 

 

Source: Yale Center for Environmental Law and Policy (2005) 
Note: These scores are expected to be between -1.0 (worse negative situation) to + 1.0 (most favourable situation).

 

 

 

 

 

 

Towards Empirical Testing at Disaggregated Levels 

On a global basis there is some evidence by now to say that environmental degradation affects the quality life, as much as changing quality of life in turn affects (or interferes with) environmental quality and status (Duraiappah et al., 2(00). Essentially, there is an increasing realization that the process of growth is making increasing demands on natural and environmental resources. This in turn is making adverse impacts on environment, which in turn is affecting the human development itself. Figure 1 makes such a representation for the understanding of this feed back process of pressures and impacts. The context being highly populated country like India, the debatable issues is whether population pressure alone drives the environmental degradation and hence in turn the down turn of human development or, is it development which drives environmental degradation in the early phases of development as an inevitable consequence, a hypothesis referred as inverted U curve on environmental degradation (or popularly stated as Environmental Kuznets hypothesis). 

 

Figure 1: Links between HDI, GDP, Population, Poverty and Environment 

 

Observational1y, there are a number of studies to show that wherever peoples' dependency is very high on environmental resources and welfare losses due to environmental degradation is quite high (Jodha: 1986; Kadekodi: 2004). Essentially, the views go on the lines of complementarity’s between environmental and natural resources with development.

 

Some data from selected states for a select set of relevant variables are presented in Table 3, followed by their intercorrelations in Table 4. Some observations can be made based on this data across the states . 

•     Consider four states with high percentage of poor, as reflected in Sen's poverty index. They are Orissa, Bihar, West Bengal, Uttar Pradesh and Table 3: Environment and Rajasthan (all with over 0.20 measure of Sen's poverty index). Compare their status or environment in terms of deforestation and total wastelands. While deforestation was observed in Bihar, West Bengal and Orissa, it was a situation of improved forestation in Uttar Pradesh and Rajasthan. But extent of waste lands is quite significant in Uttar Pradesh and Rajasthan, which is not so in Bihar, West Bengal and Orissa. Hence the performance picture is quite conflicting and mixed among the poor states. 

 

•     On the otherhand, consider the states with lowest incidence of poverty such asKerala, Maharashtra and Haryana. While deforestation isobserved in Kerala and  Haryana, it is not the case in Maharashtra. In any case, all the three states show high incidence of wastelands. 

 

•    At the national level, there are some evidences (purely based on correlations) to say that in general, the states with higher poverty incidence are having higher degree of deforestation and wastelands. 

 

•    On comparison of per capita income and the environmental status across the states, it can be said that with increasing per capita income while forest degradation is observable, the extent of wastelands seem to be coming down.

 

Table 3: Environment and Economy Linkages in India 

 

1

2

3

4

5

6

7

8

9

Orissa

3028

1319

0.42

0.3

-11.70

13.31

55

203

Bihar

3691

1587

0.39

0.21

-7.36

14.85

42

497

WB

3157

1745

0.35

0.24

-5.24

5.69

51

767

MP

4166

1605

0.41

0.15

2.69

20.71

40

149

Maharashtra

5525

1595

0.45

0.13

4.77

25.78

34

257

TN

5122

1591

0.43

0.16

-7.16

17.67

34

429

Assam

5070

1976

0.34

0.12

-9.71

20.29

33

286

Karnataka

4769

1357

0.49

0.18

0.43

14.14

33

235

UP

4185

1535

0.42

0.22

8.11

22.27

40

473

Kerala

5778

1999

0.4

0.13

-0.65

4.25

30

749

Gujarat

5288

1495

0.49

0.19

-7.31

23.36

39

211

Rajasthan

4229

1672

0.41

0.2

7.01

32.19

40

129

AP

5046

1396

0.42

0.08

-13.75

21.63

21

242

Haryana

6368

1922

0.37

0.11

-6.21

8.46

27

373

Punjab

6380

1771

0.39

0.15

81.07

7.51

32

403

 

Notes: Definitions of the variables 

1. State

2. Per capita income, 1993-94 (Rs) 

3. Mean income of the poor. 1993-94 (Rs. per year) 

4. Gini Ratio per capita income

5. Sen poverty index

6. Deforestation between 1987 ancl 1997 (percentage) 

7. Total wasteland as percentage of area in 1988-90

8. Head count ratio as percentage, NCI\ER, 1994 

9. Population density (1991)  Sources for the data: Variable 2-5 and 8: India Human Development Report-NCAER, 1999;

Variable 6: 8th Five Year Plan-1992-97, Vol. II, Planning Commission; Variable 7: Kadekodi: 2004a; Variable 9: Population Census of India .

 

Table 4: Correlation Coefficients among Economic and Environmental Variables

 

1 

2

3

4

5

6

7

8

9

 2

1

0.4669*

0.0778

-0.7814*

0.4120*

-0.1359

-0.8199*

-0.017

 3

 

1

-0.6999*

-0.4250*

0.1878

-0.3718

-0.2789

0.4844

 4

 

 

1

0.0917

-0.0705

0.3844

-0.0710

-0.4488*

 5

 

 

 

1

-0.0784

-0.0525

0.9339*

0.0817

 6

 

 

 

 

1

-0.2069

-0.1252

0.0471

 7

 

 

 

 

 

1

-0.0339

-

 

 

 

 

 

 

 

 

0.7088*

 8

 

 

 

 

 

 

1

0.08338

 9

 

 

 

 

 

 

 

1

* stands for statistically significant values at 5 percent level based on a t-test