metadata: authors: 0: author: Mani,Muthukumara S.
1: author: Markandya,Anil
2: author: Sagar,Aarsi
3: author: Golub,Elena Strukova
count: India
docna: 0: docna: An analysis of physical and monetary losses
            of environmental health and natural resources in India
docty: Policy Research Working Paper
subtopic: Health Care Services Industry,Pollution Management & Control,Air Quality & Clean Air,Hydrology,Brown Issues and Health,Law and Justice Institutions,Global Environment
teratopic: Environment,Health, Nutrition and Population
abstracts: cdata!: This study provides estimates of social
            and financial costs of environmental damage in India from
            three pollution damage categories: (i) urban air pollution;
            (ii) inadequate water supply, poor sanitation, and hygiene;
            and (iii) indoor air pollution. It also provides estimates
            based on three natural resource damage categories: (i)
            agricultural damage from soil salinity, water logging, and
            soil erosion; (ii) rangeland degradation; and (iii)
            deforestation. The estimates are based on a combination of
            Indian data from secondary sources and on the transfer of
            unit costs of pollution from a range of national and
            international studies. The study estimates the total cost of
            environmental degradation in India at about 3.75 trillion
            rupees (US$80 billion) annually, equivalent to 5.7 percent
            of gross domestic product in 2009, which is the reference
            year for most of the damage estimates.  Of this total,
            outdoor air pollution accounts for 1.1 trillion rupees,
            followed by the cost of indoor air pollution at 0.9 trillion
            rupees, croplands degradation cost at 0.7 trillion rupees,
            inadequate water supply and sanitation cost at around at 0.5
            trillion rupees, pasture degradation cost at 0.4 trillion
            rupees, and forest degradation cost at 0.1 trillion rupees.
geo_reg_key: 517198,517212,517191
repnme: repnme: An analysis of physical and monetary losses
            of environmental health and natural resources in India
display_title: An analysis of physical and monetary
            losses of environmental health and natural resources in India
listing_relative_url: /research/2012/10/16812484/analysis-physical-monetary-losses-environmental-health-natural-resources-india
topicv3: Water m1326522 137,Air Pollution m1327122 1791,Environment, Natural Resources and Blue
            Economy m1327391 566,Mortality m1504365 3661,Health m1504661 3480
publishtoextweb_dt: 2012-10-01T00:00:00Z
historic_topic: Environment,Health, Nutrition and Population
no_of_pages: 41
author_keys: 0: author_key: 96748
1: author_key: 321136
2: author_key: 1038641
3: author_key: 427979
model_extractions: WPS6219 Policy Research Working Paper 6219 An Analysis of Physical and Monetary Losses of Environmental Health and Natural Resources in India _Muthukumara Mani Anil Markandya Aarsi Sagar Elena Strukova_ The World Bank South Asia Region Disaster Risk Management and Climate Change October 2012
Policy Research Working Paper 6219

# **Abstract**

This study provides estimates of social and financial costs of environmental damage in India from three pollution damage categories: (i) urban air pollution; (ii) inadequate water supply, poor sanitation, and hygiene; and (iii) indoor air pollution. It also provides estimates based on three natural resource damage categories: (i) agricultural damage from soil salinity, water logging, and soil erosion; (ii) rangeland degradation; and (iii) deforestation. The estimates are based on a combination of Indian data from secondary sources and on the transfer of unit costs of pollution from a range of national and international studies. The study estimates the total cost of environmental degradation in India at about 3.75 trillion rupees (US$80 billion) annually, equivalent to 5.7 percent of gross domestic product in 2009, which is the reference year for most of the damage estimates. Of this total, outdoor air pollution accounts for 1.1 trillion rupees, followed by the cost of indoor air pollution at 0.9 trillion rupees, croplands degradation cost at 0.7 trillion rupees, inadequate water supply and sanitation cost at around at 0.5 trillion rupees, pasture degradation cost at 0.4 trillion rupees, and forest degradation cost at 0.1 trillion rupees.

This paper is a product of the Disaster Risk Management and Climate Change, South Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mmani@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# An Analysis of Physical and Monetary Losses of Environmental Health and Natural Resources in India

Muthukumara Mani Anil Markandya Aarsi Sagar Elena Strukova<sup>12</sup> JEL codes: C68, O44, O53, Q43, Q52 Key words: India, Environmental Degradation, Pollution Control, Environment and Health **,** Economic Growth and Environment Sector Board: Environment 1 This paper is part of a collaborative effort between the World Bank and the Ministry of Environment and Forests (MoEF). Authors extend special gratitude to Mr. Hem Pande (Joint Secretary, MoEF), and his team for support and guidance throughout the study. The team gratefully acknowledges the contribution of Gaurav Joshi for his excellent help and support on the data front. The team also acknowledges Dan Biller, Charles Cormier, Giovanna Prennushi, and Michael Toman for carefully reviewing and providing expert guidance to the team at crucial stages. The financial support of UK’s Department for International Development (DFID) is gratefully acknowledged.

2 The authors can be contacted at mmani@worldbank.org, World Bank-SASDC, anil.markandya@bc3research.org, BC3 Basque Center for Climate Change, asagar@post.harvard.edu, World Bank-SASDI; <u>estrukova@worldbank.org, World Bank-SASDC.</u>
# **I  Introduction**

Economic growth is universally recognized as a prerequisite for development. A strong momentum in investment reflecting rising productivity, healthy corporate profits, and robust exports has fueled a buoyant economic growth exceeding 7% a year in India for almost a decade. Economic growth has increased employment opportunities and allowed millions to emerge from poverty.<sup>3</sup> Economic expansion is also often accompanied by rising demands on the already scarce and often degraded natural resources (soils, fossil fuels, water and forests) and the increasing pollution footprint will negatively impact human health and growth prospects. In India’s case, a remarkable growth record has been clouded by a degrading environment and growing scarcity of natural resources. Mirroring the size and diversity of its economy, environmental risks are wide ranging and are driven by both poverty and prosperity. Environmental sustainability could become the next major economic challenge as India surges along its growth trajectory.

This study provides estimates of social and financial costs of environmental damage in India from three pollution damage categories: (i) urban air pollution, (ii) inadequate water supply, poor sanitation and hygiene, (iii) indoor air pollution; and three natural resource damage categories: (i) agricultural damage from soil salinity, water logging and soil erosion, (ii) rangeland degradation, and (iii) deforestation. The estimates are based on a combination of Indian data from secondary sources and on the transfer of unit costs of pollution from a range of national and international studies (a process known as benefit transfer). Data limitations have prevented estimation of degradation costs at the national level for coastal zones, municipal waste disposal and inadequate industrial and hospital waste management. Furthermore the estimates provided do not account for loss of non-use values (i.e. values people have for natural resources even when they do not use them).

## _Methodology for Valuation of Environmental Damage_

The quantification and monetary valuation of environmental damage involves many scientific disciplines including environmental, physical, biological and health sciences, epidemiology, and environmental economics. Environmental economics relies heavily on other fields within economics, such as econometrics, welfare economics, public economics, and project economics. New techniques and methodologies have been developed in recent decades to better understand and quantify preferences and values of individuals and communities in the context of environmental quality, conservation of natural resources, and environmental health risks. The results from these techniques and methodologies can then be, and often are, utilized by policy makers and stakeholders in the process of setting environmental objectives and priorities. And, because preferences and values are expressed in monetary terms, the results provide some guidance for the allocation of public and private resources across diverse sectors in the course of socio-economic development.

Environmental damage means physical damages that have an origin in the physical environment. Thus, damages to health from air or water pollution are included as well as damages from

> 3 Source:Indiastat

2
deforestation. The term cost means the opportunity cost to society, i.e., what is given up or lost, by taking a course of action. When goods traded in markets are damaged, prices and knowledge of consumer preferences for the damaged goods (embodied in the demand function) and production information (embodied in the supply function) provide the necessary information for computing social costs. Estimating social costs from reduced productivity of agricultural land due to erosion, salinity or other forms of land degradation is a good example. However, many damages from environmental causes are to “goods,” such as health, that are not traded in markets. In these cases, economists have devised a number of methods for estimating social costs based on derived preferences from observable or hypothetical behavior and choices.

One example is the value of time lost to illness or provision of care for ill family members. If the person who is ill or who is providing care for someone who is ill does not otherwise has a job the financial cost of time losses is zero. However, even in such a case the person is normally engaged in activities that are valuable for the family and time losses reduce the amount of time available for these activities. Thus, there is a social cost of time losses to the family. In an economic costing exercise this is normally valued at the opportunity cost of time, i.e. the salary, or a fraction of the salary that the individual could earn if he or she chose to work for income. In summary, social costs are preferred over financial costs because social costs capture the cost and reduced welfare to society as a whole. All costs are estimated as flow values (annual losses).

Unfortunately, information needed to estimate social costs for some categories is often lacking, particularly in developing countries, such as India. In such cases one has the option of relying on financial costs, which generally do not capture all the social costs. In this study, financial costs have been used for a significant part of the analysis, but with social costs being reported wherever these could be obtained or estimated. In general these financial costs are likely to underestimate social costs.

# **II    Cost of Environmental Degradation**

This section provides a summary of estimated social and financial costs of environmental damage. A discussion of each environmental category is provided in the following sections.

Environmental pollution, degradation of natural resources, natural disasters and inadequate environmental services, such as improved water supply and sanitation, impose costs to society in the form of ill health, lost income, and increased poverty and vulnerability. This section provides overall estimates of social and economic costs of such damages, referring, as much as possible, to damages for 2009. In some cases, however, the figures may be based on damages in an earlier year if that was the latest information available (see later sections for details).

The results are summarized in Figures 2.1 and 2.2 and in Table 2.1. Total damages amount to about Rs. 3.75 trillion (US$80 billion) equivalent to 5.7 percent of GDP. Of this total, outdoor air pollution accounts for the highest share at 1.7 percent (figure 2.1) followed by the cost of indoor air pollution at 1.3 percent; croplands degradation cost at just over one percent; inadequate water supply, sanitation and hygiene (WSH) cost at around at 0.8 percent; pastures degradation cost at 0.6 percent, and forest degradation cost at 0.2 percent. The individual damages are shown as shares of the total in Figure 2.2. Outdoor air pollution accounts for 29 3
percent, followed by indoor air pollution (23 percent), cropland degradation (19 percent), water supply and sanitation (14 percent), pasture (11 percent), and forest degradation (about 4 percent).

In addition India has experienced some damages from natural disasters (floods, landslides, tropical cyclones, and storms). These are, however, not included in the above figures as they are not the result of anthropogenic factors, although such factors can exacerbate their impacts. Over the period 1953-2009 damages from natural disasters were estimated at Rs. 150 billion a year on average (in constant 2009 prices) and took the form of loss of life and injury, losses to livestock and crops and losses to property and infrastructure.

Similarly, while India has been phasing out lead in gasoline since 2001 there are a number of other sources that are not controlled. This is probably due to the fact that some gasoline is still produced with lead due the presence of lead in pipes, drinking water, soils, food, paints, and other products. Lead exposure could result in substantial mortality from diseases associated with high blood pressure among adults and IQ reduction and Mild Mental Retardation. While some studies have suggested high levels of lead among urban population (both children and adults) in there is great uncertainty about current BLL in the urban population as a whole (and the rural population). It is therefore necessary to undertake new studies of BLL in children and adults to provide a more accurate estimate of health effects and their costs taking into account the gradual lead phase-out in India.

**Figure 2.1: Annual Cost of Environmental Damage (Billion Rs.)**

<!-- Start of picture text --> 1,200<br>1,000<br>800<br>600<br>400<br>200<br>0<br>Outdoor air Indoor air Crop lands Water supply, Pastures Forest<br>pollution pollution degradation sanitation and degradation degradation<br>hygiene<br>Billion Rs .<br><!-- End of picture text --> _Source:_ Staff estimates.

4
<!-- Start of picture text --> S\y<br>—<br><!-- End of picture text -->
|Indoor air pollution|305|**870**|1,425|23%|
|---|---|---|---|---|
|Crop lands degradation|480|**703**|910|19%|
|Water supply, sanitation and hygiene|475|**540**|610|14%|
|Pastures degradation|210|**405**|600|11%|
|Forest degradation|70|**133**|196|4%|
|TOTAL ANNUAL COST (billion<br>R’s/yr.)|1,710|**3,751**|5,821|1|
|Total as percent of GDP in 2009|2.60%|**5.70%**|8.84%||

_Note:_ Staff estimates are rounded to the nearest ten.

# **_Health Related Damages among selected populations in India_**

The damages associated with environmental health are estimated for different groups of the population. This mainly reflects differences in terms of who is affected by the different pollutants but also the availability of data. The outdoor air pollution losses were estimated for the inhabitants of cities with a population of over 100 thousand (due to data limitations); inadequate water supply, sanitation and hygiene costs were estimated for the whole population of India; and indoor air pollution costs were estimated for the households that use solid fuel for cooking (about 75 percent of all households). These differences in coverage should be borne in mind when comparing across the different environmental burdens. In particular coverage for outdoor air pollution is less complete than the others and thus the figures for that category are underestimated.

The higher costs for outdoor/indoor air pollution (other than lead exposure) are primarily driven by an elevated exposure of the urban and rural population to particulate matter pollution that results in a substantial cardiopulmonary and COPD mortality load among adults. As noted the rural population has only been assessed for indoor air pollution.

Figure 2.3 gives estimates of damage per person within the different exposed populations used to construct the figures in Table 2.1. We note that a significant part of the health burden, especially from water supply, sanitation and hygiene is borne by children under 5 (Figure 2.4). These figures would suggest that about 23 percent of all under-5 mortality can be associated with indoor air pollution and inadequate water supply, sanitation and hygiene, and 2 percent of adult mortality with outdoor air pollution.

6
<!-- Start of picture text --> 5,000<br>4,000<br>w 3,000<br>a<br>CT]<br>a<br>=<br>= 2,000<br>1,000<br>a)<br>Water supply, Indoor air pollution Outdoor air pollution<br>sanitation and hygiene<br><!-- End of picture text -->
**Figure 2.4:  Estimated Share of Annual Mortality from Different Sources in India**

<!-- Start of picture text --> 12.60%<br>9.80%<br>0.40%<br>2%<br>0.40%<br>Outdoor air pollution Indoor air pollution Water Supply, Sanitation and<br>Hygiene<br>Adult Children<br><!-- End of picture text --> _Source:_ Staff estimates.

# **_Other Categories of Damages_**

Cropland damages arise from the decline the value of crops due to soil erosion, water logging, salinity and overgrazing. We derive a range of estimates due to uncertainty of crop and pasture profitability as well as the uncertainty of the level of degradation.

Forest degradation has arisen in India from unsustainable logging practices in some regions, and general over-exploitation of forest resources. Although the country has gained about 7 percent in overall forest cover between 1990 and 2010 there has also been a notable degradation in some forests. It is this that results in losses of ecosystem services including carbon sequestration, provision of timber and non-timber forest products, recreational and cultural use of forests and prevention of soil erosion. The losses are valued using a range of techniques, which are subject to considerable uncertainty arising from the estimates of forest productivity and methods of obtaining values for the non-marketed services.

Finally impacts of changes in fisheries were examined but it was not possible to value these in monetary terms due to gaps in the data.

Another way of looking at the role of environmental resources is in terms of the “GDP of the poor”<sup>5</sup> . Natural resources degradation is more significant when compared with their income. One measure of the growth potential for the poor is in the share of GDP generated in agriculture, forestry and fishery, which made up about 17 percent of GDP in 2010. To be sure not all the GDP in these sectors goes to the poor but a more significant part of it does than for some other sectors. Figure 2.5 summarizes potential impact of natural resource degradation losses on the

> 5 Gundimeda & Sukhdev (2008) introduced a concept GDP of the poor that includes GDP only from agriculture, forestry and fishery, since these sectors reflect growth potential for most of the rural, predominantly poor Indian making up 72 percent of the total. The importance of these sectors for the poor is also discussed in World Bank (2006).

8
<!-- Start of picture text --> 8%<br>7%<br>6%<br>5%<br>4% @ %GDP from agriculture,<br>forestry and fishery<br>3% mTM% GDP<br>2%<br>1%<br>0%<br>Crop lands Pastures Forest<br>degradation degradation degradation<br><!-- End of picture text -->
<!-- Start of picture text --> BPHD@ DS @ SF @ BBLK SL HP© MHK& KL HMHN PHO O WB GSWEP OgWK BD _ HaMAS 0SL<br>PP HBP HP LH PF PP OS<br>A® g oe s Nanos or o*®<br><!-- End of picture text --> <!-- Start of picture text --> op 5000<br>bi<br>4900<br>2 2% .<br>2 3000 =<br>ox<br>#<br>1% 2000 2E<br>1000 8<br>=<br>0% 0 oaa<br>China Iran India Pakistan =<br>SOAP cost = GOP per capita<br><!-- End of picture text -->
# **III    Urban Air Pollution**

# **_3.1 Particulate Matter_**

There is substantial research evidence from around the world that outdoor urban air pollution has significant negative impacts on public health and results in premature deaths, chronic bronchitis, and respiratory disorders. A comprehensive review of such studies is provided in Ostro (1994), Ostro et al. (2004). The air pollutant that has shown the strongest association with these health endpoints is particulate matter and other secondary particles with similar characteristics of less than 10 microns in diameter (PM10)<sup>7</sup> . Research in the United States in the 1990s and most recently by Pope et al (2002) provides strong evidence that it is particulates of less than 2.5 microns (PM2.5) that have the largest health effects. Other gaseous pollutants (SO2, NOx, CO, and ozone) are generally not thought to be as damaging as fine particulates. However, SO2 and NOx may have important health consequences because they can react with other substances in the atmosphere to form secondary particulates. In particular, the evidence implicates sulfates formed from SO2, but is much less certain about nitrates, formed from NOx.

The focus of this study therefore is the health effects of all fine particulates (PM10 and PM2.5). This requires data on who is exposed, the health impacts of that exposure and the value attached to those impacts.

Given data limitations we can only estimate impacts for the urban populations and in fact only for a part of that population. Only major cities have TSP and PM10 monitoring data. In this study we focus on cities with a population of 100,000 and above only. Since the baseline population is from the 2001 census there are many cities that have achieved a population of 100,000 since 2001 and have not been included in the study. This can be updated in the future. .

Pollution data for all cities, where available, was taken from the Central Pollution Control Board’s (CPCB) Environmental Data Bank website for the year 2008. Health damage estimates for PM10 were calculated based on observations for the year 2008. The study included 96 cities with monitoring stations and 223 cities with no monitoring stations (254 million people in total). The population for 96 cities with monitoring stations amounts to 186 million, or about 16% of the country’s population. In addition there are about 225 cities with an average population of 69 million for which there are no data on PM concentrations. Since excluding them from the estimation of health impacts would be a serious omission, annual average PM10 levels were assigned to these cities based on scaling up of the World Bank modeling PM10 concentrations (taken from the World Bank Internal Research Database), using an average factor for the major cities.

The age distribution of the urban population was estimated using urban population parameters from the 2001 India Census. PM10 were transformed into PM2.5 to obtain values for the latter using a ratio of 0.5 based on evidence from India (CPCB, 2011). This ratio reflects the mean of the PM2.5/PM10 ratio for large Indian cities reported in this paper

> 7 Also called total suspended particulates or TSP.

11
Based on the current status of worldwide research, the risk ratios, or concentration-response coefficients from Pope et al (2002) were considered likely to be the best available evidence of the mortality effects of ambient particulate pollution (PM 2.5).

Damages due to anthropogenic factors are measured from a baseline PM2.5 concentration, which we set equal to 7.5 ug/m3 (as in WHO (2002). This is considered to be the level one would find in the natural environment. A log-linear function for estimating cardiopulmonary mortality associated with outdoor air pollution was applied.

The morbidity effects assessed in most worldwide studies are based on PM10. Concentrationresponse coefficients from Ostro (1994, 1998) and Abbey et al (1995) have been applied to estimate these effects. Ostro (1994) reviews worldwide studies and based on that Ostro (1998) estimates concentration-response coefficient for restricted activity days, and Abbey et al (1995) provides estimates of chronic bronchitis associated with particulates (PM10). A linear function for estimating morbidity end-points associated with outdoor air pollution was applied. The mortality and morbidity coefficients are presented in Table 3.1 based on these estimates.

|**Table 3.1Urban Air Pollution Concentration-Response Coefficients**|
|---|

|Annual Health Effect|Concentration-<br>response<br>Coefficient|Per 1 ug/m<sup>~~3~~</sup><br>annual average<br>ambient<br>concentration of:|
|---|---|---|
|Long term mortality (% change in cardiopulmonary and lung<br>cancer mortality)|0.8% *|PM 2.5|
|Acute mortality children under five (% change in ARI<br>deaths)|0.166%|PM10|
|Chronic bronchitis(% change in annual incidence)|0.9%|PM10|
|Respiratoryhospital admissions(per 100,000population)|1.2|PM10|
|Emergencyroom visits(per 100,000population)|24|PM10|
|Restricted activitydays(% change in annual incidence)|0.475%|PM10|
|Lower respiratoryillness in children(per 100,000 children)|169|PM10|
|Respiratory symptoms (per 100,000 adults)|18,300|PM10|

*Mid-range coefficient from Pope et al (2002) reflecting a linear function of relative risk.  In the analysis however, we used a log-linear

_Source:_ Pope et al (2002), Ostro (2004) for the mortality coefficients. Ostro (1994, 1998) and Abbey et al (1995) for the morbidity coefficients.

The health effects of air pollution can be converted to disability adjusted life years (DALYs) to facilitate a comparison with health effects from other environmental risk factors. DALYs per 10 thousand cases of various health end-points are presented in Table 3.2.

12
# **<u>Table 3.2: DALYs for Different Health Endpoints</u>**

|**Health Effect**|**DALYs lost per**<br>**10,000 cases**|
|---|---|
|Mortalityadults|75,000|
|Mortalitychildren under 5|340,000|
|Chronic Bronchitis(adults)|22,000|
|Respiratoryhospital admissions|160|
|EmergencyRoom visits|45|
|Restricted activitydays(adults)|3|
|Lower respiratoryillness in children|65|
|Respiratorysymptoms(adults)|0.75|

Note: DALYs are calculated using a discount rate of 3% and full age weighting based on WHO tables.

Urban air particulate pollution is estimated to cause around 109,000 premature deaths among adults and 7,500 deaths among children under 5 annually. Adult mortality estimated above is consistent with Cropper et al’s (2012) estimate of the annual mortality associated with coal electricity generation in India (about 60,000 people calculated as about 650 deaths per year with 92 coal burning power plants in India). Electricity generation is responsible for a fraction of PM pollution analyzed in this study<sup>8</sup> . Estimated new cases of chronic bronchitis are about 48,000 per year. Annual hospitalizations due to pollution are estimated at close to 370 thousand and emergency room visits/outpatient hospitalizations at 7,300 thousand per year. Cases of less severe health impacts are also presented in the Table. In terms of annual DALYs lost mortality accounts for an estimated 60 percent, chronic bronchitis around 5 percent, restricted activity days (RADs) for 7 percent, and respiratory symptoms for 25 percent.

.

# **<u>Table 3.3: Estimated Health Impact of Urban Air Pollution</u>**

|**Health end-points**|**Total**<br>**Cases**|**Total**<br>**DALYs**|
|---|---|---|
|Prematuremortality adults|109,340|820,049|
|Mortalitychildren under 5|7,513|255,431|
|Chronic bronchitis|48,483|106,663|
|Hospital admissions|372,331|5,957|
|Emergencyroom visits/Outpatient hospital visits|7,303,897|32,868|
|Restricted activitydays|1,231,020,030|369,306|
|Lower respiratoryillness in children|16,255,360|105,660|
|Respiratorysymptoms|3,917,855,052|293,839|
|TOTAL||1,989,773|

_Source:_ Staff estimates.

The estimated annual cost of urban air pollution health effects is presented in Table 3.4. The cost of mortality is based on the human capital approach (HCA) as a lower bound and the value of statistical life (VSL) as an upper bound for adults and HCA for children (see Annex I).

> 8 Cropper et al (2012) analyses direct emissions from coal burning power plants and applied annual average intake PM2.5 fractions. Ambient concentrations of PM2.5 are analyzed in this report.

13
The cost-of-illness (COI) approach (mainly medical cost and value of time losses) was applied to obtain an estimate of the morbidity cost (see cost of morbidity in Table 3.4).

To summarize, the mean estimated annual cost of PM urban air pollution totals 1,103 billion Rs. or 1.7 percent of GDP in 2009. About 90 percent of the cost is associated with mortality, and 10 percent with morbidity (Table 3.4). Measured in terms of Disability Adjusted Life Years (DALYs)<sup>9</sup> about 54 percent of the cost is associated with mortality and 46 percent with morbidity (Table 3.3).

## **Table** **<u>3.4: Estimated Annual Cost of Health Impacts (Billion Rs.)</u>**

|**Health categories**|**Total Annual Cost***|**Percent of Total Cost***|
|---|---|---|
|||**(Mean)**|
|**_Mortality_**|||
|Adults|1,018|92.2%|
|Children under 5|13|1.2%|
|**_Morbidity: _**|||
|Chronic bronchitis|1|0.1%|
|Hospital admissions|3|0.3%|
|Emergency room visits/Outpatient hospital<br>visits|8|0.7%|
|Restricted activitydays(adults)|46|4.2%|
|Lower respiratoryillness in children|14|1.3%|
|Total cost of Morbidity|72|9%|
|TOTAL COST (Mortality and Morbidity)|1,103|100 %|

* Percentages are rounded to nearest percent. _Source:_ Staff estimates.

# **_3.2 Lead Exposure_**

The problem of lead pollution used to be quite serious in India. A number of Indian studies report on a mean level in blood (BLL) at about 10 ug/dL a level that the U.S. Center for Disease Control considers requiring urgent action (see for example <u>http://www.cdc.gov/nceh/lead/faq/about.htm). Health effects are quite uncertain at blood levels</u> of 5-10 ug/dl.

The main pathways for lead exposure in India are the following<sup>10</sup> :

- i. Food traces of lead are found in almost all food. Airborne lead falls onto crops or soil and is absorbed by plants.

> 9 The sum of years of potential life lost due to premature mortality and  the years of productive life lost due to disability (www.who.int).

> 10 Source: Toxics Link Handout on Lead (http://www.toxicslink.org)

14
- ii. Air: lead in environment comes from industrial emissions, smelters and refineries

- iii. Dust and soil: dust and soils can be significant sources of lead exposure, especially for young children. Lead in soil can come from the air or from erosion of lead bearing rocks and may be carried indoors as dust.

- iv. Water: lead can enter the water supply from lead solder in the plumbing or lead pipes in the house.

- v. Paint: most indoor and outdoor paints contain substantial amounts of lead. Most paint companies in large cities have eliminated lead from their products, although lead in paints might still be prevalent in rural areas.

- vi. Inexpensive, horizontal PVC mini blinds.

- vii. Leaded crystal is widely used for serving beverages. When the crystal comes in contact with the beverages, especially acidic beverages such as port, wine and fruit juices, some lead dissolves into the liquid.

- viii. Lead fumes are released when waste oil, colored newsprint, battery casings or wood covered with lead paint are burned.

Thus, while India has been phasing out lead in gasoline since 2001 there are a number of other sources that are not still controlled. Therefore it will be quite some time until the lead phase-out policy brings significant results. Roy et al (2009) in a special study about lead phase out report that measured lead blood levels are still high in the Indian population.

Some of the studies of BLL in India date back to 2003 and the average BLL do not reflect the recent phase-out program of lead in gasoline. While there is great uncertainty about how much BLL will decline due to the on-going lead phase-out program, international experience indicates that a program over a five-year period could lead to a 40 percent reduction in BLL under a complete phase out.

As there is great uncertainty about current BLL in the urban population as a whole (and the rural population), it is necessary to undertake new studies of BLL in children and adults to provide a more accurate estimate of health effects and their costs taking into account the gradual lead phase-out in India.

# **IV    Water Supply, Sanitation and Hygiene**

The main health impacts of unclean water and poor hygiene are diarrheal diseases, typhoid and paratyphoid. In addition there are costs in the form of averting expenditures to reduce health risk. Diarrheal and related illness contributes the dominating share of the health cost. We consider these in turn.

# **_4.1 Diarrheal Diseases, Typhoid and Paratyphoid_**

WHO has proposed a rigorous methodology<sup>11</sup> that links the access to improved water supply, safe sanitation, and hygiene to diarrheal illnesses (mortality and morbidity of children under 5) and other population morbidity based on an extended meta-analysis of peer reviewed

> 11 Fewtrell, L. and J. Colford Jr. (2004).

15
publications,. About 88 % of diarrheal cases globally are attributed to water, sanitation and hygiene (Pruss-Ustun et al, 2004). This is a conservative approach where malnutrition impact on early childhood diseases is omitted. If considered, this additional indirect impact would approximately double the mortality attributed to water supply, sanitation and hygiene (WSH) (World Bank, 2010). However, a major part of these losses are in the form of acute respiratory mortality that was accounted for in the indoor air pollution section. To avoid double counting and be on a conservative side we considered only direct impact of inadequate water supply, sanitation and hygiene (WSH).

Mortality for children under 5 and diarrheal-based child mortality are high in India. Baseline health data for estimating the health impacts of inadequate water supply, sanitation and hygiene are presented in Table 4.1. The Office of the Registrar General (2004) indicates that 14 percent of child mortality was due to intestinal diseases. A baseline diarrheal mortality rate of 14 percent of under-5 child mortality is thus used for diarrheal mortality estimation.

For diarrheal morbidity, however, it is very difficult or practically impossible to identify all cases of diarrhea. The main reason is that substantial numbers of cases are not treated or do not require treatment at health facilities, and are therefore never recorded. A second reason is that cases treated by private doctors or clinics are often not reported to public health authorities. Household surveys therefore provide the most reliable indicator of total cases of diarrheal illness. Most household surveys, however, contain only information on diarrheal illness in children. Moreover, the surveys only reflect diarrheal prevalence at the time of the survey. As there is often high variation in diarrheal prevalence across seasons of the year, extrapolation to an annual average will result in either an over- or underestimate of total annual cases. Correcting this bias is often difficult without knowledge of seasonal variations.

In spite of all these difficulties a reasonable estimate has been made of the number of cases and prevalence of diarrhea in the population, along with the number of DALYs per 100,000 cases of diarrhea. The figures summarized in Table 4.1.

**<u>Table 4.1: Baseline Data for Estimating Health Impacts</u>**

||**Baseline**|**Source:**|
|---|---|---|
|Under-5 child mortalityrate in 2006|52-82|NFHS-3|
|Diarrheal mortality in children under 5 years (% of child<br>mortality)|14 %|Office of Registrar General<br>(2004)|
|Diarrheal 2-week Prevalence in Children under 5years|8.9-9%|NFHS-3|
|Estimated annual diarrheal casesper child under 5years|1.85-1.87|Estimated from NFHS-3|
|Estimated annual diarrheal cases per person (> 5 years)|0.37-0.56|International experience<br>(Krupnick et al,2006)|
|Hospitalization rate (% of all diarrheal cases) –children<br>under 5years|0.15%|NSS (2004)|
|Hospitalization rate (% of all diarrheal cases) –children<br>under 5years|0.3-0.6 %||
|Percent of diarrheal cases attributable to inadequate water<br>supply,sanitation and hygiene|90 %|WHO (2002b)|
|DALYs per 100 thousand cases of diarrhea in children<br>under 5|70|Estimated from WHO tables|
|DALYs per 100 thousand cases of diarrhea in persons >5<br>years|100-130||

16
|DALYs per 100 thousand cases of typhoid in persons<br>under 5 and over 5|190-820|
|---|---|
|DALYs per case of diarrheal and typhoid mortality in|32-34|
|children over 5 and under 5||

Table 4.2 presents the estimated health impacts from inadequate water, sanitation and hygiene, based on the parameters given in Table 4.1, including the assumption (from WHO) that 88 percent of diarrheal illness is attributable to water, sanitation and hygiene. The table also provides estimates of DALYs lost to waterborne diseases. About 60 percent of the DALYs are from diarrheal child mortality. Typhoid/paratyphoid deaths add another 20 percent of DALY.

**Table 4.2: Estimated Annual Health Impacts from Water,** **<u>Sanitation, Hygiene</u>**

||Ca|ses|Estimated Annual DALYS|% of Total<br>|
|---|---|---|---|---|
||||<br>|DALYS|
||Urban|Rural|Urban<br>Rural||
|Children (under the age of<br>5 years) – increased<br>mortality (Thousand)|41|198|1,384<br>6,714|87-93|
|Children (under the age of<br>5 years) – increased<br>morbidity (Thousand)|57,831|178,898|20<br>63|1|
|Population over 5 years of<br>age – increased morbidity<br>(Thousand)|149,836|344,183|177<br>406|11-6|
|Typhoid/paratyphoid<br>mortality (Thousand)|0.|57|19|0|
|Typhoid/paratyphoid<br>morbidity (Thousand)|1,1|50|8|0|

_Source:_ Staff estimates.

. The estimated costs associated with the impacts identified above are given in Table 4.3. The hypothetical value from which the estimates are based relies on the WHO methodology which uses conditions in developed countries as the benchmark. The incidence rates for these illnesses are close to zero in those countries (0.3 per person/year as in Fewtrell and Colford, 2004).

The total cost is Rs. 490 billion. The cost of mortality is based on the human capital approach (HCA) for children under 5. The cost of morbidity includes the cost of illness (medical treatment, medicines, and value of lost time) and value of lost DALYs estimated at GDP per capita. We used GDP per capita as a proxy for WTP for one additional year of life, expressed in DALYs.

**<u>Table 4.3 Estimated Health Impacts from Inadequate Water, Sanitation, Hygiene</u>**

||**E**|**stimated Annual**<br>**Rs. Bn.**|**Cost**|
|---|---|---|---|
||**Urban **|**Rural **|**Total **|
|**_Mortality_**||||
|Children under age 5 diarrheal mortality|50|227|277|
|Children under age 5 typhoid|||0.3|
|Persons over 5 typhoid|||0.5|
|**_Morbidity_**||||

17
|Diarrheal morbidity|105|103|208|
|---|---|---|---|
|Typhoid morbidity<sup>~~12~~</sup>|||3.3|
|**TOTAL ANNUAL COST**|155|330|489.1|

_Source:_ Staff estimates.

# **_4.2 Averting Expenditures_**

In the presence of perceived health risks, individuals often take measures to avoid these risks. These are usually considered as a cost of the health risks of environmental burdens. If consumers perceive that the municipal water supply or the other sources of water supply they rely on are unsafe, they are likely to purchase bottled water for drinking purposes, or boil their water, or install water purification filters. The estimated costs of these options are given in Table 4.4. The assumed hypothetical level of expenditure here is zero (i.e. no avertive expenses would be incurred if the water supplied was safe). The total amount of avertive expenditures for India amount to about Rs. 55 Bn. a year.

**Table 4.4: Estimated Total Annual Household** **<u>Cost of Averting Expenditures</u>**

||**Total An**<br>**(Billio**|**nual Cost**<br>**n Rs.)**|
|---|---|---|
||**Urban **|**Rural **|
|Cost of bottled water consumption|20|7|
|Cost of household boilingdrinkingwater|4|3|
|Cost of household filteringdrinkingwater|14|7|
|**Total annual cost**|38|17|

_Source:_ Staff estimates.

In summary the estimated annual cost associated with inadequate water supply, sanitation and hygiene is presented in Figure 4.1, totaling 470-610 billion Rs. per year, with a mean of 540 billion Rs. The cost of health impacts represents an estimated 90 percent of total mean cost, with averting expenditures accounting for about 10 percent. Health impacts include both mortality and morbidity, and averting expenditures include bottled water consumption, and household boiling of drinking water. Annual costs by major category are presented on Figure 4.1.

> 12 About 25 percent of estimated COI is from hospitalization and doctor visits, 70 percent is from time losses for the ill individuals and their caregivers during illness

18
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more time while cooking (with little children at their side), than in comparison with older children and adult males, who spend more time outdoors.

**<u>Table 5.1: Health Risks of Indoor Air Pollution</u>**

||**Odds Ra**|**tios(OR)**|
|---|---|---|
||“Low”|“High”|
|Acute RespiratoryIllness(ARI)|1.9|2.7|
|Chronic obstructive pulmonary disease (COPD)|2.3|4.8|
|_Source:_Desai et al (2004).|||

The NFHS-3 reports that 90 percent of rural and 32 percent of urban households use solid fuels for cooking in India. The national weighted average is about 71 percent.

To estimate the health effects of indoor air pollution from the odds ratios in Table 5.1, baseline data for ARI and COPD need to be established. These data are presented in Table 5.2, along with unit figures for disability adjusted life years (DALYs) lost to illness and mortality. The hypothetical level against which damages are calculates is a situation in which there is no exposure to indoor air pollution and the odds ratio is one.

**Table** **<u>5.2: Baseline Data for Estimating Health Impacts</u>**

||**Baseline**||**Source:**|
|---|---|---|---|
||Urban|Rural||
|Female COPD mortality rate (% of total female<br>deaths)|9.|5%|WHO estimate for India,<br>Shibuya et al (2001)|
|Female COPD incidence rate(per 100 thousand)||79||
|ARI 2-week Prevalence in Children under 5years|22%|22%|NFHS-3,2006|
|Estimated annual cases of ARI per child under 5<br>years|1.0|1.0|Estimated from NFHS-3, 2006|
|Estimated annual cases of ARI per adult female (><br>30 years)|0.4|0.5|Estimated from a combination of<br>NFHS-3, 2006 and Krupnick et al,<br>2006|
|ARI mortality in children under 5 years (% of child<br>mortality)|2|2%|Office of Registrar General (2004)|
|DALYs per 100 thousand cases of ARI in children<br>under 5|165|165||
|DALYs per 100 thousand cases of ARI in female<br>adults(>30)|700|700|Estimated from WHO tables|
|DALYs per case of ARI mortality in children under<br>5|34|34||
|DALYs per case of COPD morbidity in adult<br>females|2.25|2.25||
|DALYs per case of COPD mortality in adult<br>females|6|6||

The results of the estimation of health losses associated with indoor air pollution are presented in Table 5.3. Estimated cases of ARI child mortality and ARI morbidity (children and female adults) from indoor air pollution represent about 38-53 percent of total ARI in India. Similarly, the estimated cases of COPD mortality and morbidity represent about 46-72 percent of total estimated female COPD from all causes.

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**<u>Table 5.3: Estimated Annual Health Impacts of Indoor Air Pollution (Thousands)</u>**

||**Estimat**<br>**Case**|**ed Annual**<br>**s(000)**|**Estimat**<br>**DALY**|**ed Annual**<br>**s(000)**|
|---|---|---|---|---|
||Urban|Rural|Urban|Rural|
|**_Acute Respiratory Illness(ARI): _**|||||
|Children(under the age of 5years)– increased mortality|19.5|166.4|662|5,660|
|Children(under the age of 5years)– increased morbidity|7,570|47,925|12.5|79|
|Females(30years and older)– increased morbidity|9,401|47,384|65.8|331.7|
|**_Chronic obstructive pulmonary disease (COPD):_**|||||
|Adult females – increased mortality|7.5|53.4|74|363|
|Adult females – increased morbidity|39,000|202.5|127.7|455.6|
|Total Disability Adjusted Life Years (DALYs)-mortality<br>and morbidity|||942.4|6,889.3|

_Source:_ Staff estimates.

Table 5.3 also gives the DALYs lost to indoor air pollution. An estimated 8 million DALYs are lost each year. About 70-80 percent are from mortality and 20-30 percent are from morbidity.

The central estimated costs associated with the impacts identified above are given in Table 5.4. Briefly, the cost of mortality is based on the value of statistical life (VSL) estimated for India as a higher bound and HCA as a lower bound for adults and on HCA for children under 5. The cost of morbidity includes the cost of illness (medical treatment, value of lost time, etc) and value of DALYs estimated in GDP per capita.

To summarize, the total annual cost of indoor air pollution is estimated at Rs. 305-1425 billion, with a mean estimate of about Rs.865 billion (Table 5.4) or 1.3 percent of GDP in 2009. About 68 percent of this cost is associated with COPD, and 32 percent with ARI.<sup>14</sup> COPD and ARI mortality represents about 90 percent of the total cost, and morbidity about 10 percent (Figure 5.1).

# **Table** **<u>5.4: Estimated Annual Cost of Indoor Air Pollution</u>**

||**Estimated A**<br>**(Billio**<br>|**nnual Cost**<br>**n Rs)**<br>|
|---|---|---|
||Urban|Rural|
|**_Acute Respiratory Illness(ARI): _**|||
|Children(under the age of 5years)– increased mortality|20|190|
|Children(under the age of 5years)– increased morbidity|5|15|
|Adult females – increased morbidity|10|20|
|**_Chronic obstructivepulmonary disease(COPD): _**|||
|Adult females – increased mortality|99|485|
|Adult females – increased morbidity|6|15|
|**TOTAL**|140|725|

_Source:_ Staff estimate.

> 14 Based on the mean estimated annual cost.

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# **_6.1 Soil Salinity and Water Logging_**

Soil salinity and water logging reduce the productivity of agricultural lands and, if a threshold salinity level is exceeded the land becomes unfit for cultivation. According to the conventional welfare economics, if agricultural markets are competitive, the economic costs of salinity would be measured as the losses in consumer surplus (consumer willingness to pay above market price) and producer surplus (profit) associated with the loss in productivity. These losses include direct losses through reduced yields as the land becomes saline or degraded. In practice, the calculations can be more complex as account needs to be taken of crop substitution to more saline-tolerant but less profitable crops and other indirect losses. Because of a lack of data, the losses here are approximated by the value of “lost” output related to the salinity, with some simple adjustment for changes in cropping patterns.

The estimated losses from saline soils were calculated under the assumption that such land is only used for wheat production (if it is used at all). This reflects the assumption that when soils are saline farmers will tend to plant crops that are more tolerant of this factor and wheat is such a crop, as opposed to pulses and rice. FAO estimates indicate a loss of yield of 5% for wheat per unit salinity (dS/m) for levels of salinity over 6 dS/m. Taking these values and applying them to lands under wheat is the basis of the estimated loss of output.

## **Table** **<u>6.1. Land degradation in India, million hectares (2002)</u>**

|Degradation type|Degree|of Degradation||||
|---|---|---|---|---|---|
||Slight|Moderate|Strong|Extreme|Total|
|Water Erosion|27.3|111.6|5.4|4.6|148.9|
|a. Loss of topsoil|27.3|99.8|5.4|-|132.5|
|b. Terrain Deterioration|-|11.8|-|4.6|16.4|
|Wind Erosion|0.3|10.1|3.1|-|13.5|
|a. Loss of topsoil|0.3|5.5|0.4|-|6.2|
|b. Loss of topsoil/terrain deterioration|-|4.6|-|-|4.6|
|c. Terrain deformation/over blowing|-|-|2.7|-|2.7|
|Chemical Deterioration|6.5|7.3|-|-|13.8|
|a. Loss of nutrient|3.7|-|-|-|3.7|
|b. Salinization|2.8|7.3|-|-|10.1|
|Physical Deterioration|-|-|-|-|116.6|
|Waterlogging|6.4|5.2|-|-|11.6|
|Total (affected area)|36.8|137.9|8.5|4.6|187.8|

_Source:_ indiastat.com The estimates indicate a net income from a hectare of land under wheat in 2009 as being in the range Rs 8,000-18,000 and total losses from salinity based on the above assumptions come out at between Rs. 0-10 billion in scenario 1 and between Rs. 3-13 billion in scenario 2<sup>15</sup> .

> 15 Information of the salinity level (slight, moderate, strong) was not available at the time of the study. 2 scenarios were considered to address this issue.

23
In addition to the losses we also have to account for losses from strongly saline lands that could not be cultivated at all. There are estimated to be about 13 million hectares of agricultural land that cannot be cultivated, either because they are waterlogged or because they are highly saline. If we assume half of this area is saline then annual net losses from land wasted due to salinity are about Rs. 60-135 billion Rs. In total therefore losses due to salinity amount to between Rs. 63 and Rs 148 billion. The middle of that range is 110 billion Rs. (0.17% of GDP in 2010).

The losses due to water logging are estimated in a similar way. Then annual production losses are about 20 billion Rs. or 0.03% of GDP in 2010.

The remaining waterlogged wasteland is estimated by Indiastat.com to be 7.5 million. ha. None of this is deemed to be cultivatable. Given that the loss in annual profits for paddy production on one hectare is in the range 15,000-24,000 Rs/ha The annual net losses from land wasted due to water logging are about 83-143 billion Rs. or 113 billion Rs. on average (0.2% of GDP in 2010).

**_6.2 Soil Erosion_** In addition to soil salinity land degradation caused by wind and water erosion is substantial in India.  Two major impacts of this erosion are sedimentation of dams and loss of nutrients in the soil.

Soil erosion contributes to sedimentation of dams in India. This in turn reduces the capacity of dams and thus irrigation capacity. We do not have reliable data on sedimentation of dams and reduction in the capacity of dams in India. Hence estimates of losses in crop production as a result of sedimentation could not be made.

As far as soil erosion and the loss of soil nutrients are concerned, this can be valued in terms of the costs of replacing the losses.

The estimated cost of soil nutrients (in terms of nitrogen, phosphorus and potassium) substitution is about 320-600 billion Rs. or 460 billion Rs. on average (0.7 % of GDP in 2010). Soil erosion is thus by far the most substantial problem of land degradation in India.

Adding up the three categories of losses arising from land degradation in India we get a total of 715 billion Rs. or 1.1 % of GDP in 2010 (Table 6.2). Another way to express the loss is as a percentage of GDP from agriculture, forestry and fishery, which are sources of income predominantly for the poor. Gundimeda and Sukhdev (2008) refer to this as the “GDP of the poor” and as a percent of that the loss is about 6.4%.

24
**<u>Table 6.2.  Estimated Annual Cost of Crop Losses Due to  Land Degradation</u>**

||Total<br>Low|Loss(billion Rs<br>Mean|)<br>High|% of GDP<br>2010|% GDP of<br>thepoor|
|---|---|---|---|---|---|
|Salinitylosses|63|110|148|0.2%|1.1%|
|Waterlogged land losses|103|133|163|0.2%|1.2%|
|Erosion losses|320|460|600|0.7%|4.1%|
|Total CropLand Degradation Losses|480|703|910|1.1%|6.4%|
|<br>_Source:_Staff estimates.||||||

# **_6.3 Rangeland Degradation_**

Land use reported in India suggests that the main causes of rangeland degradation in India are irrational land use management practices leading to denudation of vegetation from rangelands which, exacerbated by intermittent droughts, has resulted in many pockets of desertification. According to land use data from Indiastat.com about 10 million hectares are classified as permanent pastures. At the same time, about 1.5 times more land, including that under miscellaneous tree crops and groves and cultivable waste land, is also used as pastures. There is a substantial share of degraded lands within all these land categories. Forest lands that are used as pastures are estimated in the next section to avoid double-counting. An estimated 60 percent of livestock grazes in the forest area (Kapur et al., 2010).

The loss in yield is valued in two ways. In the first method the reduction in fodder production is valued at the price of fodder. In the second method the loss of fodder is converted into a loss of livestock based on livestock feed requirements and a value is attached to the loss of livestock. In both cases the hypothetical value against which losses are calculated is one in which original productivity prevails.

The estimated annual cost of rangeland degradation for the two methods is summarized in Table 6.3. The mean of two estimates is 405 billion Rs at 0.6% of GDP in 2010 or 3.6% GDP of the poor.

**Table** **<u>6.3. Annual Cost of Rangelands Degradation in India</u>**

||Billion RS.|% of GDP|% of GDP<br>of thepoor|
|---|---|---|---|
|Market value of fodder losses|400-800|0.6-1.2%|3.6-7.2%|
|Foregone livestock income from fodder losses|170-256|0.3-0.4%|1.5-0.2.3%|
|Mean cost|405|0.6%|3.6%|

_Source:_ Staff estimates.

# **VII    Forest Degradation**

The cost of deforestation and degradation of forests is the aggregate social loss associated with degraded or deforested lands. These losses include, in theory, a wide range of local, regional, national, and even global costs. Examples include direct losses of timber, fuel wood and nontimber products, recreation and tourism losses and indirect use losses (such as those associated 25
with damages to ecosystem services, water supply and carbon sequestration), and non-use value loss associated with loss of forests. This section examines each of these categories of losses with the available data.

India’s forest cover is about 21% of total land area (about 69 million hectares). Dense forest constitutes only 12% of total forest cover area (indiastat.com). Although forest cover area increased by 0.1% in 2007 (indiastat.com), the north-eastern mountainous states with the most dense forest, like Nagaland, Arunachal Pradesh, Tripura and Assam, continued to experience deforestation due to the widespread practice of shifting cultivation. This loss is especially damaging for hilly areas where destructive agricultural practices can result in total ecosystem destruction. Total annual deforested land averaged from 2006-2009 is at about 0.6 million hectares annually (indiastat.com).

Many sources reflect a substantial level of land degradation in India. Overexploitation of forest resources has led to the opening up of the canopy and an increase of shrub-covered areas. The degraded area grew from 19.5 to 24.4 million hectares in 2003 (3rd National Report on Implementation of UN Convention to Combat Desertification, 2003). From the figure of 2.4 million hectares and with annual forest deforestation assumed to be at the same level as in 20062009, the total degraded forest area in 2009 would be estimated at 28 million hectares.

The estimated losses from the degraded forests are based on the use values attached to the forest in their non-degraded state. Previous studies have estimated the use values for two categories: direct use value and indirect use value. Under direct use value they have included: (i) Timber, (ii) Non-timber forest products, (iii) Fodder, (iv) Eco-tourism and (v) Carbon sequestration. Under indirect use values they have covered (i) Soil erosion prevention and (ii) Water recharge. No estimate has been made of non-use values from forests, nor has any account been taken of biodiversity values (e.g. from bioprospecting) although these can be significant.

A summary of the values obtained, both in total and normalized in terms of Rs. per hectare are given in Table 7.1. The biggest source is carbon sequestration, followed by fodder and ecotourism.

In order to value the losses we assume that degraded forests provide between 20 and 80 percent for most of the direct use values but none of the indirect values since indirect values are only associated with dense forest functions. In the case of sequestered carbon a more precise figure is available: degraded forests are associated with 20% loss of total accumulated carbon (Gundimeda, 2001), reported in the range of 21-59 tC/hectare in India,<sup>16</sup> valued at a social cost of carbon USD20 per ton of CO2<sup>17</sup> . The losses are applied to 29 million hectares of degraded forest and about 0.6 million hectares of deforested lands.

> 16 We assume that degraded land would continue to sequester carbon up to 80% of what it uptakes on non-degraded forest. Carbon issues are complicated and at the next stage they should be carefully studied in the context of geographical location and other specific factors. This study attempted to provide indicative country-wide estimates.

> 17 The same CO2 price is applied in China 2030 (World Bank, 2012).

26
# **Table 7.1. Estimated annual use values per hectare of forest in India** **<u>(Billion Rs. except where indicated)</u>**

||Low|High|
|---|---|---|
|**Direct**|||
|Timber|17.2|17.2|
|Non timber values|21.0|21.0|
|Fodder|94.4|188.8|
|Ecotourism|51.2|51.2|
|Carbon sequestration|266.8|339.5|
|Total direct|450.6|617.7|
|Per hectare, Rs.|6,471.3|8,871.2|
|**Indirect**|||
|Soil erosion|15.5|15.5|
|Water recharge|6.4|6.4|
|Total indirect|21.9|21.9|
|Per hectare, Rs.|314.5|314.5|
|**Total use values**|472.5|639.6|
|**Total per hectare, Rs.**|6,785.9|9,185.7|

_Source:_ Staff estimates applying secondary data from GAISP (2005-2006), FAO (2009), Gundimeda (2005), Haripriya (2001), Pearce et al (1999), 3rd National Report on Implementation of UN Convention to Combat Desertification (2003), World Bank (2006), World Bank (2012), data from indiastat.org and www.indg.in.

Based on these figures total annual losses from degraded forest land and annual deforestation losses are presented in Table 7.2. The resulting losses are in the range of 0.1-0.3% of GDP. We should note that this is very likely an underestimate of total losses as it excludes non-use values loss. Gundimeda (2005) estimates that the non-use and bioprospecting values of forests could be as much as 6-20 times greater than use values. Due to the high uncertain nature of this estimate we did not use it in this study.

**Table 7.2. Estimation of annual forest** **<u>value loss, Rs. per hectare, except where indicated</u>**

|Losses<br>% loss|Low|High|
|---|---|---|
|**Direct va**<br> <br>|**lues**<br>||
|Timber<br>80-<br>100%|198|248|
|Non timber<br>values<br>20-<br>100%|60|301|
|Fodder<br>0%|1,356|2,712|
|Ecotourism<br>100%|51|51|
|Carbon<br>sequestration<br>20%|766|975|
|Total direct|2,432|4,287|
|Average % loss|42%|53%|
|Total direct , Rs Bn.|60.5|106.7|
|**Indirect values**|||

27
|Soil erosion<br>0-100%|0|1,783|
|---|---|---|
|Water recharge<br>0-100%|0|765|
|Total indirect|0|2,548|
|Average % loss|0|100|
|Total indirect , bil Rs|0.0|63.4|
|Total degradation losses,<br>Bill Rs|60.5|170.2|
|Total deforestation losses<br>(20% carbon losses only)<br>Bill Rs|9.14|25.47|
|Total|69.7|195.6|
|%GDP|0.11%|0.30%|
|% GDP for the poor|0.60%|1.68%|

_Source:_ Staff estimates applying secondary data from GAISP (2005-2006), Gundimeda (2005), Gundimeda (2001).

If related to the GDP of the poor that was about 17% of the total GDP in India in 2010, then losses in the forestry sector are at about 0.6-1.7%.

28
# **Annex I.  Valuation of Premature Mortality**

Two distinct methods of valuation of premature mortality are commonly used to estimate the social cost of premature death, i.e., the human capital approach (HCA) and the value of statistical life (VSL). The first method involves estimating income losses from premature death and was dominant in the past. But because this measure is not based on individual preferences and for other conceptual problems, it has been overtaken by both stated and revealed preference approaches to estimating preferences for reducing mortality risks. The monetary value of these preferences, or willingness to pay, when divided by the relevant risk reduction yields the value of statistical life (VSL). Because HCA almost always underestimates the VSL, the HCA has been applied as a low estimate and VSL as a high estimate in estimating the cost of premature mortality.

## **A. Human Capital Approach.**

The HCA is based on the economic contribution of an individual to society over the lifetime of the individual. Death involves an economic loss that is approximated by the loss of all future income of the individual. Future income is discounted to reflect its value at the time of death. The discount rate commonly applied is the rate of time preference. Thus the social cost of mortality, according to the HCA, is the discounted future income of an individual at the time of death. If the risk of death, or mortality risk, is evenly distributed across income groups, average expected future income is applied to calculate the social cost of death. Mathematically, the present value of future income is expressed as follows: where PV0 (I) is present value of income (I) in year 0 (year of death), g is annual growth in real income, and r is the Ramsey discount rate. As can be seen from (1), the equation allows for income to start from year k, and ending in year n. In the case of children, we may have i<sup>∈</sup> {16,...,65}, assuming the lifetime income on average starts at age 16 and ends at retirement at age 65. The annual growth of real income is variable, and set at about 5 percent for the first 30 years and reducing to 2 percent over the next 35 years. The GDP per capita growth rate was computed in the CGE model for India (see World Bank forthcoming report "Economic Growth and Environmental Sustainability”). Since the real growth of GDP per capita is quite high, it should be accounted for in determining the social discount rate. We apply the Ramsey discount rate to real GDP per capita assuming an intertemporal coefficient of consumption equal to 1, as in Summers and Zeckhauser (2008). Then the average effective discount rate is set at about 1percent.

The most important practical issue raised regarding the HCA is the application of this valuation approach to individuals that do not participate in the economy, i.e., to individuals not having an income, such as the elderly, family members taking care of the home, and children. One may think of an extension of the HCA that recognizes the value of non-paid household work at the same rate as the average income earner, or at a rate equal to the cost of hiring a household helper. In this case, the HCA can be applied to non-income earners and children (whether or not children will become income earners or take care of the home during their adult life). In the case of the 29
elderly, the HCA would not assign an economic value to old individuals that have either retired from the workforce or do not make significant contributions to household work. This obviously is a serious shortcoming of the HCA approach.

The estimated cost of mortality in India based on HCA is presented in Table A1.16. Average annual income is approximated by GDP per capita, corresponding to around 57 thousand Rs. per year. The estimates are from equation (1).

# **Table A1:** **<u>Cost of Mortality (per Death) using HCA</u>**

||Average Number of<br>Years Lost|Thousand Rs|
|---|---|---|
|**_Adults:_**|||
|Mortalityfrom Urban Air Pollution|8|430|
|Mortalityfrom Indoor Air Pollution|7|390|
|Mortalityfrom Lead Exposure|8|430|
|**_Children:_**|||
|Mortalityfrom Urban Air Pollution|65|1,148|
|Mortalityfrom Indoor Air Pollution|65|1,148|
|Mortality from Diarrheal Illness, Typhoid , children<br>under 5|65|1,148|
|Mortality from Diarrheal Illness, Typhoid , children<br>under 19|55|1,863|

# **B. Value of Statistical Life.**

While the HCA involves valuation of the death of an individual, VSL is based on preferences for reducing mortality risk by a small amount. Everyone in society is constantly facing a certain risk of dying. Examples of such risks are occupational fatality risks, risks of traffic accident fatality, and environmental mortality risks. It has been observed that individuals adjust their behavior and decisions in relation to such risks. For instance, individuals demand a higher wage (a wage premium) for a job that involves a higher than average occupational risk of fatal accident, individuals may purchase safety equipment to reduce the risk of death, and/or individuals and families may be willing to pay a premium or higher rent for properties (land and buildings) in a cleaner and less polluted neighborhood or city.

Through the observation of individuals’ choices and willingness to pay for reducing mortality risk, it is possible to measure or estimate the value to society of reducing mortality risk, or, equivalently, measure the social cost of a particular mortality risk. For instance, it may be observed that a certain health hazard has a mortality risk of 1/10,000. This means that one individual dies every year (on average) for every 10,000 individuals. If each individual on average is willing to pay 10 Rupees per year for eliminating this mortality risk, then every 10,000 individuals are collectively willing to pay 100 thousand Rupees per year. This amount is the VSL. Mathematically it can be expressed as follows: VSL = WTPAve * 1/ R (2) where WTPAve is the average willingness-to-pay (Rupees per year) per individual for a mortality risk reduction of magnitude R. In the illustration above, R=1/10,000 (or R=0.0001) and 30
WTPAve= 10 Rupees. Thus, if 10 individuals die each year from the health risk illustrated above, the cost to society is 10* VSL = 10*100 thousand Rupees = 1 million Rupees.

A number of VSL studies have been conducted in India. Table A2 presents a summary.

# **Table A2:** **<u>Value of Statistical Life in India</u>**

|**Name of Study**|**Method of**<br>**Estimation**|**Value**|**Adjusted**<br>**Value (2010)**|**Adjusted**<br>**Value in $**<br>**(2010) using**<br>**` 47.5 = $1**<br>**exchange**<br>**rate**|
|---|---|---|---|---|
|Shanmugam K.R. (1997|Compensating-<br>wage differentials|` 12,084,000|` 18,932,020|$398,569|
|Simon et al. (1999)|Compensating-<br>wage differentials|` 6,417,341 - `<br>15,040642|` 16,197,563|$341,001|
|Bussolo and O'Connor<br>(2001).|PPP and income<br>elasticity Brandon<br>(1995) estimate|$ 202,000 -<br>$343,860, use the<br>central value of<br>$273,000|` 19,109,280|$402,301|
|Madheswaran (2007)|Compensating<br>wage differentials|` 15,000,000|` 16,939,353|$356,618|

Source: prepared by A. Sagar.

The average VSL from these comes out at about $375,000 (Rs. 17.8 million) and this figure was applied in the report. From Table 6.2 it can be seen that the ratio of VSL/HCA is about 16 times for children and 44 times for adults.

In this report we used the average of the VSL and HCA values for adults (i.e. $192,000 or Rs. 9.1 million). For children we do not use the VSL value at all as none of the VSL studies are for children. Hence we take only the HCA value of $24,168 or Rs. 1.148 million (Table 6.1). This conservative approach is also consistent with other costs of degradation studies that have been conducted.

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