Final Report
Study of Rohtang Pass
Sponsor
Himachal Pradesh State Pollution Control Board
______
National Environmental Engineering Research Institute
Nehru Marg, Nagpur ‐ 440 020
October, 2012
Final Report
“STUDY OF ROHTANG PASS”
Sponsor
Himachal Pradesh State Pollution Control Board
______
National Environmental Engineering
Research Institute
Nehru Marg, Nagpur - 440 020
October, 2012
CONTENTS
Chapter 1 : Introduction 1.1 Preamble 1.1 1.2 Study Objectives 1.2 1.3 Scope of Work 1.2 1.3.1 Air Environment 1.2 1.3.2 Water Environment 1.4 1.3.3 Land Environment 1.4 1.3.4 Solid Waste 1.5 1.3.5 Biodiversity 1.5 1.4 Past Studies 1.5
Chapter 2 : Air Quality Monitoring 2.1 Winter Air Quality Monitoring 2.1 2.1.1 Description of Sites 2.1 2.1.2 Results of Winter Monitoring 2.5 2.2 Summer Air quality Monitoring 2.8 2.2.1 Results of Summer Monitoring 2.9 2.3 Conclusions 2.14
Chapter 3 : Air QualityModeling 3.1 Preamble 3.1 3.2 Meteorological Data 3.2 3.3 Vehicular Sources 3.3 3.4 Applicable Emission Factors 3.4 3.5 Paved Road Dust 3.4 3.6 Modeling Results 3.5 3.6.1 PM Concentration 3.5 3.6.2 NO2 Concentration 3.6 3.6.3 CO Concentration 3.8 3.7 Conclusions 3.9
Chapter 4 : Water Environment 4.1 Introduction & Objective 4.1 4.2 Methodology 4.1 4.3 Sampling Procedure 4.4 4.4 General Observations 4.5
Chapter 5: Impact of Tourism on Solid Waste Management and Sanitation 5.1 Preamble 5.1 5.2 Geographical Features of the Study Area 5.2 5.3 Wastewater Treatment Plant at Manali 5.3 5.4 Solid Waste Management for Manali 5.3 5.5 Sanitation 5.4
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Chapter 6: Assessment of Soil, Soil Erosion and Conservation Measures for Erosion 6.1 Introduction 6.1 6.2 Geomorphology of the Study Area 6.2 6.3 Site Factors for Erosion 6.3 6.4 Results and Discussions 6.7 6.5 Chemical Properties 6.8
Chapter 7: Biological Environment 7.1 Introduction 7.1 7.2 Methodology 7.1 1. (A) Assessment of Flora at Select Locations in the Study Area 7.1 1. (B) Assessment of Fauna at Select Locations in the Study Area 7.10 2. Impact of Tourism on Biotic Component in the Study Area 7.13
Chapter 8: Assessment of Impacts of Vehicular Pollution on Glacial Environment 8.1 Preamble 8.1 8.2 Selection of Sampling Locations at Rohtang Pass 8.2 8.3 Sampling Procedure 8.5 8.4 Processing of Filters in the Laboratory 8.6 8.5 EC OC Analysis 8.6 8.6 Ion Analysis 8.9 8.7 Analysis of Molecular Marker 8.10
Chapter 9: Remote Sensing Analysis 9.1 Introduction 9.1 9.2 Study Area 9.1 9.3 Methodology 9.1 9.4 Results and Discussion 9.7 9.5 Summary of Remote Sensing Analysis 9.17
Chapter 10: Recommendations 10.1 Recommendations 10.1 10.2 Transport Sector Action Plan 10.1 10.2.1 Approach and Issues 10.1 10.2.2 Recommended Plan 10.2 10.3 Water Environment 10.7 10.4 Solid Waste Management 10.8 10.5 Soil Erosion vis-à-vis Land Sliding 10.9 10.6 Biological Environment 10.10 10.7 Glaciers 10.10
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LIST OF FIGURES
Figure 1.1 Study area of Rohtang Pass 1.3 Figure 2.1 Air Quality Monitoring Locations 2.2 Figure 2.2 Air Quality Monitoring Locations 2.3 Figure 2.3 RSPM Concentrations in April at 3 Locations 2.6 Figure 2.4 PM2.5 Concentrations in April at 3 Locations 2.6 Figure 2.5 RSPM Concentrations at the Monitoring Sites in May 2.11 Figure 2.6 PM2.5 Concentrations at Monitoring Locations During May 2.12 Figure 2.7 Site wise Variation of Elements (As, Ni and Pb) 2.13 Figure 3.1 Wind Rose for the Month of May, 2012 3.2 Figure 3.2 The Three Vehicle Counting Locations 3.3 3 Figure 3.3 Contour Map of PM10 in μg/m Due to Vehicular Sources & Paved Road Dust 3.5 3 Figure 3.4 Three Dimensional Contour Map of PM10 in μg/m Due to Vehicular Sources 3.6 and Paved Road Dust 3 Figure 3.5 Observed and Predicted Concentrations of PM10 in μg/m at the Monitoring Sites 3.6 3 Figure 3.6 Contour Map of NO2 in μg/m Due to Vehicular Sources in the Study Domain 3.7 3 Figure 3.7 Three Dimensional Contour Map of NO2 in μg/m Due to Vehicular Sources 3.7 3 Figure 3.8 Observed and Predicted Concentrations of NO2 in μg/m at the Monitoring Sites 3.8 Figure 3.9 Contour Map of CO in μg/m3 Due to Vehicular Sources in the Study Domain 3.8 Figure 3.10 Three Dimensional Contour Map of CO in μg/m3 Due to Vehicular Sources 3.9 Figure 3.11 Observed and Predicted Values of CO in μg/m3 Due to Vehicular Sources at the 3.9 Monitoring Sites Figure 4.1 Beas and Chenab River Basin 4.1 Figure 4.2 Water Sampling Locations Between Manali to Koksar 4.3 Figure 8.1 Tourist Influx at Manali During 2011 8.3 Figure 9.1 Base Map of Study Area (Manali to Khoksar) 9.2 Figure 9.2 Location Map of Ground Truth and Ground Control Points 9.6 Figure 9.3 False Colour Composite (FCC) Image of 17 July 2012 9.8 Figure 9.4 False Colour Composite (FCC) Image of 27 October 2011 9.9 Figure 9.5 False Colour Composite (FCC) Image of 31 January 2011 9.10 Figure 9.6 False Colour Composite (FCC) Image of 29 October 2005 9.11 Figure 9.7 Supervised Classification for LULC (17 July 2012) 9.12 Figure 9.8 Supervised Classification for LULC (27 October 2011) 9.13 Figure 9.9 Supervised Classification for LULC (31 January 2011) 9.14 Figure 9.10 Supervised Classification for LULC (29 October 2005) 9.15
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LIST OF TABLES
Table 1.1 Air Quality Levels and Number of Vehicles 1.5 Table 2.1 Ambient Air Pollutants and their Standard Measurement Procedures 2.4 Table 2.2 Air Quality Status at Palchen (Winter) 2.5 Table 2.3 Air Quality Status at Kothi (Winter) 2.7 Table 2.4 Air Quality Status at Solang Valley (Winter) 2.7 Table 2.5 Average Concentration of Ions in μg/m3 in Winter 2.7 Table 2.6 Average Concentration of Elements in μg/m3 in Winter 2.8 Table 2.7 Air Quality Status at Palchen (Summer) 2.9 Table 2.8 Air Quality Status at Kothi (Summer) 2.9 Table 2.9 Air Quality Status at Solang Valley (Summer) 2.10 Table 2.10 Air Quality Status at Marhi (Summer) 2.10 Table 2.11 Air Quality Status at Koksar (Summer) 2.10 Table 2.12 Average Concentrations of Ions in Summer at 5 Monitoring Locations 2.13 Table 2.13 Average Element Concentrations in Summer at 5 Monitoring Locations 2.13 Table 3.1 Applicable Emission Factors for Vehicular Source 3.4 Table 3.2 Vehicle Weight 3.4 Table 3.3 Paved Road Emission Load (kg/day) 3.5 Table 3.4 Percent Exceedance of PM10 and PM2.5 During May and April 3.9 Table 4.1 Water Sampling Locations 4.2 Table 4.2 Physico-chemical Characterization of Beas and Chandra River Water Samples 4.6 Table 4.3 Physico-chemical Characterization of Springs and Municipal Water Supply Samples 4.6 Table 4.4 Physico-chemical Characterization of Ground Water and Nallah Samples 4.7 Table 4.5 Trace Metal Analysis of Water samples from Rivers, Springs, Ground Water, Water 4.8 Supply Schemes and Nallahs Table 4.6 List of Algal Species Found in the Water Bodies of Rohtang Study 4.9 Table 4.7 Density and Species Composition of Phytoplankton in Water Samples Collected 4.9 from Various Sources Table 5.1 Tourist Statistics for Manali for the Period 2011 5.2 Table 6.1 Details of Soil Sampling Locations 6.5 Table 6.2 Physical Characterization of Soil Samples Collected Between Manali-Rohtang NH-21 6.6 Table 6.3 Chemical Characterization of Soil Samples Collected Between Manali- 6.6 Rohtang NH-21 Table 6.4 Mechanical Characterization of Soil Samples Collected Between Manali- 6.7 Rohtang NH-21 Table 7.1 Select Locations for Biodiversity Studies During May, 2012 7.1 Table 7.2 A : Flora of Rohtang Pass Region in Manali Forest Range Kullu District 7.4 Table 7.2 B: Flora of Rohtang Pass Region, with Medicinal Value, in Manali Forest Range, 7.4 Kullu District & Koksar Region of Lahul District Table 7.3 A. Density, Frequency and Dominance and IVI of Trees in Solang Valley 7.7 Table 7.3 B. Density, Frequency and Dominance and IVI of Trees in Kothi (Tungu) 7.7 Forest Area Table 7.3 C. Density, Frequency and Dominance and IVI of Trees in Gulaba (Rahla Fall) 7.7 Forest Area
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Table 8.1 Prediction of Particular matter Emissions (Kg/day) from Vehicles 8.3 Table 8.2 Sampling Locations for Collection of Snow Samples 8.4 Table 8.3 OC and EC Concentration in Glacier Samples 8.8 Table 8.4 Ion Concentration (in mg/kg) in Glacier Samples 8.10 Table 8.5 Molecular Markers and Their Probable Sources 8.11 Table 9.1 Details of Satellite Data 9.3 Table 9.2 Details of Ground Truth Locations in the Study Area 9.4 Table 9.3 Landuse Pttern of Study Area in Percentage 9.17
LIST OF PLATES
Plate 4.1 Water Sampling at Various Source 4.3 Plate 4.2 Field Laboratory Established for Water Quality Analysis for Physico-Chemical 4.4 Parameters Plate 4.3 Water Quality Analysis for Microbiological 4.5 Plate 5.1 Tourist Places at Manali Rohtang Pass 5.1 Plate 5.2 Solid Waste Management at Manali 5.4 Plate 5.3 Common Toilet Facility and Portable Prefabricated Toilets 5.5 Plate 5.4 Horses used by Tourist as Source of Animal Dung 5.5 Plate 5.5 Tourist Throwing Liter Along the Road 5.6 Plate 5.6 Non Compliance of Waste Management by Hotels 5.6 Plate 5.7 Promotional Activities for Clean Environment, H.P. Govt. 5.6 Plate 5.8 Food Vendors Adding to Nalla Pollution 5.7 Plate 6.1 Vehicles Plying on Rohtang Pass 6.3 Plate 6.2 Road Widening Activities 6.4 Plate 6.3 Titling of Retaining Wall and Need for River Diversion for Road Widening 6.4 Plate 6.4 Collection of Soil Samples 6.5 Plate 6.5 Collection of Core Soil Samples 6.6 Plate 7.1 Study of Forests by Plotless Sampling Method 7.3 Plate 7.2 Vegetation at Different Altitude in the Study Area 7.6 Plate 7.3 Dominant Flora in Study Area 7.8 Plate 7.4 Fish Culture Activities at Trout Farm, Patlikuhal 7.12 Plate 7.5 Impact of Tourism on Biotic Component of Study Area 7.14 Plate 8.1 Traffic Congestion at Beas Nalla Near Marhi 8.4 Plate 8.2 Vehicular Movement at Snow Covered Rohtang Pass 8.4 Plate 8.3 Snow Sample Collection in Clean Glass Bottles 8.5 Plate 8.4 Snow Sample Collection on Top of Snow Pack 8.5 Plate 8.5 Millipore All-Glass Filter Assembly with Suction Pump 8.5 Plate 8.6 Exposed Quartz Filter 8.6 Plate 8.7 DRI’s EC OC Analyzer 8.7 Plate 8.8 Block Diagram of EC- OC Analyzer 8.7 Plate 8.9 Dionex ICS-3000 Ion Chromatography (IC) System 8.9
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LIST OF ANNEXURES
Annexure 2.1 CPCB- National Ambient Air Quality Monitoring Standards Annexure 4.1 Uniform Protocol on Water Quality Monitoring Order, 2005 Annexure 4.2 The methodology for sample collection and preservation techniques, Standard Operating Procedures (SOP) (APHA) Annexure 4.3 The analytical techniques used for water analysis for selected parameters (APHA) Annexure 4.4 “BIS: 10500-2012 (second revision) Specifications for Drinking Water Annexure 4.5 Water Quality Criteria – CPCB Annexure 6.1 Methods Adopted for Soil Analysis for Mechanical Properties and Significance of These Parameters Annexure 6.2 Chandel et al., 2009. RS & GIS Based Landslide Hazard Zonation of Mountainous Terrains A Study from Middle Himalayan Kullu District, Himachal Pradesh, India. International Journal of Geomatics and Geosciences, Volume 2, No 1, 2011 Annexure 7.1 Medicinal Flora in Lahul District Annexure 9.1 Ground Truth Survey (Rohtang Pass) with For assessment of LULC
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Chapter 1
Introduction 1.1 Preamble
Rohtang Pass about 4111 meter above the mean sea level is also called Rohtang La by Buddhists, or Rohtang Jot by Kullui locals. It is a high mountain pass across the Pir Panjal range of the Himalaya that connects the Kullu Valley with the Lahul and Spiti valleys of Himachal Pradesh. It is at a distance of 51 km from the town of Manali. The pass provides a natural divide between the sub-humid/humid Kullu Valley with a primarily Hindu culture (in the south), and the arid/semi-arid high-altitude Lahul and Spiti valleys with a Buddhist culture (in the north). The pass lies on the watershed between the Chenab and Beas Basins. On the southern side of this pass, the Beas River emerges from underground and flows southward and on its northern side, the Chandra River, a source stream of the river Chenab, flows westward.
The weather at Rohtang Pass is highly variable and generally very cold and closed in the winter from November and opens sometime in May. Long before the pass opens, tourists start visiting its road at whatever point has been cleared to experience snow. This point is called the snow point and is a major attraction with snow sledges, skis and all kinds of tourist attractions set up. A gateway to the adjoining tourist destinations, this scenic spot provides excellent opportunities for trekking. Rohtang Pass is the 'Highest Jeepable Road in the World and offers spectacular views of the Himalayas. The Border Road Organization (BRO) of Indian Army maintains and broadens the Leh Manali Highway and ensures safety as well as movement of vehicles. It is not particularly high or difficult to cross on foot by Himalayan standards, but it has a well-deserved reputation for being dangerous because of unpredictable snowstorms and blizzards. This pass is an ancient trade route between the people on either side of Pir Panjal. This has been the oldest and most frequented pass in the region, and it is the main pass leading from one cultural region (Indian) to another, quite different one, to the north. The tedious journey is often dangerous owing to the high velocity wind and the unpredictable snowfall.
The road through the Kullu Valley, past Manali and over the Rohtang Pass to Keylong, and Lahul and on to Ladakh, has become very busy during the summer months as an alternate military route, following the Kargil Conflict in 1999 in addition to tensions in Kashmir. Traffic jams are common as military vehicles, trucks, and goods carriers try to navigate the narrow roads and rough terrain, compounded by snow and ice at certain points and the large number of tourists vehicles. Partially due to the military significance of the pass, the Indian government began building the $320 million Rohtang Tunnel project in 2010 which promises to create a year-around link which is much safer and faster.
Study of Rohtang Pass | 1.1 The city nearest to Rohtang pass is Manali which is at an altitude of 1,950 m (6,400 ft) in the Beas River valley . It is an important hill station in the mountains of Himachal Pradesh, India, near the northern end of the Kullu Valley. It is located about 250 km north of state capital, Shimla. Manali with population of approx. 30,000 is administratively a part of the Kullu district.
Himachal Pradesh Pollution Control Board (HPPCB) has been directed by Hon’ble High Court to undertake a study of Rohtang pass. HPPCB has also been asked to submit an alternative proposal to reduce the pressure of tourist vehicles and to fix the permissible number of vehicles and visitors that should be allowed to ply in the region. The Court further indicated that soil and water quality needs to be studied. Minimal damage to the ecology especially on the biodiversity of the area due to developmental activities in the region needs to be ensured. Study should include all related aspects of developments such as air quality, roads, vehicles, availability of water etc. Keeping in view the above, it is proposed to conduct a study on air, water, soil pollution and biodiversity around Rohtang Pass area from Solang Nala to Khoksar which is beyond Nehru-Kund near Bhang village up to Khoksar. Map of the study area is depicted in Figure 1.1.
1.2 Study Objectives
The main objectives of the study of “Rohtang Pass Region” given to NEERI is to : • Evaluate the change in environmental quality in terms of air, water, soil, ecology/biodiversity, due to the activities carried out in the vicinity of Rohtang pass due to tourists influx • Identify adverse effects on environmental status, if any, and • Provide remedial measures on resultant impacts to prevent expected environmental degradation.
1.3 Scope of Work
Environmental component-wise (envisaged) scope of work is given below:
1.3.1 Air Environment a) Air quality monitoring • Air quality monitoring w.r.t. major parameters i.e. PM10, PM2.5, SO2 NO2, CO & HC along
with Chemical speciation of PM10 and PM2.5 for EC, OC, Pb, As, Ni, Anions and cations. • 5 days continuous monitoring each in winter and summer season at 5 locations, preferably
simultaneously. 24-Hr sampling for PM10, PM2.5, SO2 and NO2, whereas grab sampling thrice a day for CO & HC. The monitoring locations shall be finalized in consultation with HPPCB. Since power supply may not be available at Rohtang Pass, the sampling shall be carried out using battery operated equipment (accordingly, monitoring strategy may need to be redefined).
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Figure 1.1: Study Area of Rohtang Pass
Study of Rohtang Pass | 1.3 • Continuous meteorological measurements (wind speed, wind direction, temperature, humidity, etc.) during air quality monitoring period. b) Preparation of emission inventory • Assessment of vehicular traffic on the major road (Manali-Leh-Highway) during the study periods shall be carried out. Number of different categories of vehicles (such as cars, buses, trucks etc.) passing through the region shall be counted and vehicular emission inventory shall be developed using appropriate emission factors. • Other activities leading to air pollution, emanating from nearby villages (e.g. cooking and mechanized agricultural/ horticultural activity etc.) will also be considered. c) Air quality modeling • Air quality modeling shall be undertaken using appropriate model. The reduction in air quality levels after applying control techniques for vehicle sources shall be ascertained. • Assessment of atmospheric assimilation potential of vehicular transport emissions in Rohtang Pass.
1.3.2 Water Environment a) Surface water (River/ Ponds) • Assessment of surface water quality and quantity in Rohtang Pass area between Solang, Kothi to Khoksar on NH-Manali-Leh. Water quantity will be assessed through secondary records. • Assessment of water quality of various water resources in Beas and Chandra rivers and hill streams at 5 or more locations. • Water quality shall be assessed for the parameters specified under “Uniform Protocol on Water Quality Monitoring Order, 2005” prescribed by Ministry of Environment & Forests.
1.3.3 Land Environment
This will have three sub-components viz. land quality in relation to soil erosion, solid waste generation due to tourist activities and bio-diversity.
Soil Erosion
Erosion is the prime process, which is responsible for the variation in topography. It is aggravated due to human interventions through indiscriminate cutting of trees, mining, overburden dumping, etc., thus affecting natural ecosystem. Areas affected by severe soil erosion need immediate attention for soil conservation measures like bunding, contour farming, gully, farm forestry, water harvesting, etc.
Study of Rohtang Pass | 1.4 • Sampling of soil will be carried out in areas of Solang, Kothi, Marhi upto Khoksar on NH- Manali-Leh Road in the Rohtang Pass and analyzed for related parameters to study the impact on soil erosion.
1.3.4 Solid Waste
• Assessment of solid waste generation due to the tourist activities
1.3.5 Biodiversity
• Assessment of flora and fauna including sensitive terrestrial systems in the study area • Delineation of existing land use pattern and practices in the project area using Remote Sensing Imageries • Assessment of impacts on landuse pattern due to the proposed developments • Assessment of impact on flora and fauna of the study region.
1.4 Past Studies
To assess the impact of vehicles on air, air quality monitoring was conducted in April 2011, by Himachal Pradesh State Pollution Control Board (HPSPCB) before the start of tourist season. Number of vehicles on the road was also counted. Thereafter monitoring was conducted during the peak tourist season in May 2011. The concentration of NO2 before the tourist season was below detection limit, whereas the average NO2 concentration during peak season increased to 11.1 3 μg/m . This can be attributed to Vehicular pollution. The average PM10 concentration prior to tourist season was 23 μg/m3 while the average concentration during the peak tourist season was 3. 25μg/m The sources of PM10 are vehicles, re-suspended road dust, burning of wood. Pb, As, Ni were not detected at any time. SO2 was also under Below Detectable Level (BDL). Table 1.1 gives the details of air quality monitoring conducted by HPSPCB.
Table 1.1 : Air Quality Levels and No of Vehicles Parameters Kothi Tungu Nalla Marhi Fourway 6.4.11 7.4.11 26.5.11 27.5.11 28.5.11 29.5.11 RSPM (μg/m3) 19 26 25 20 18 36 Pb (μg/m3) ND ND ND ND ND ND As (ng/m3) ND ND ND ND ND ND Ni (ng/m3) ND ND ND ND ND ND 3 SO2 (μg/m ) BDL BDL BDL BDL BDL BDL 3 NO2 (μg/m ) BDL BDL 11 11.9 BDL 14.2 No of vehicles 10 11 156 143 141 142 crossed point of monitoring location
Study of Rohtang Pass | 1.5 Chapter 2
Air Quality Monitoring
2.1 Winter Air Quality Monitoring
Air quality monitoring was carried out for 6 days continuously at the three selected locations viz.
Solang valley, Palchen and Kothi. Level of pollutants such as RSPM, PM2.5, SO2, NOx, CO,
NMHC and HC were recorded. Further, PM2.5 samples were analyzed for EC/OC, ions and elements. Figures 2.1 and 2.2 shows the three monitoring locations.
2.1.1 Description of Sites
Each site description has been presented with a view to bring out the overall characteristics of sites.
Solang Valley : Solang valley, popularly known as Snow Point, is 13 km northwest of Manali. Solang Valley is known for its beautiful landscape, thrilling snow-capped mountain peaks and the view of the glaciers. Many tourists throng this place especially during the winter skiing festival. The monitoring location was about 100m from the main road connecting the Solang valley with Manali.
Palchen : Palchen is situated on the Manali-Leh highway at a distance of 9 km from Manali. the Hamta peaks are located further ahead.
Kothi : Located at a distance of 12 km from Manali, Kothi is situated on the Manali-Leh highway. Kothi is a picturesque village and has a thrilling view of the deep gorge through which the Beas River swiftly races, an idyllic village, which boasts of a superb view of the deep gorge, and the Beas River rushing through it. The monitoring location at Kothi was located very close to the Leh- Manali highway and hence is kerb site.
Teflon and Quartz filter papers were used alternatively for PM2.5 to carry out EC and OC analysis for alternate days. During April, Rohtang pass was not open and very few tourists were present in Manali. Roads were opened few kilometers above Gulaba and Marhi was not accessible.
Pollutants Monitored : RSPM, PM2.5, SO2, NO2 and CO were monitored at all the three air- + + + monitoring sites. Further, PM2.5 samples were analyzed for EC and OC, ions (Na , NH4 , K , +2 +2 - - - -2 - - Mg , Ca , F , Cl , NO2 , SO4 , Br , NO3 and PO4) and elements (As, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn). Table 2.1 presents the details of sampling instrument, sampling principle, flow rate, analytical method and instrument for each monitoring attributes.
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Figure 2.1 : Air Quality Monitoring Locations
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Figure 2.2 : Air Quality Monitoring Locations
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Table 2.1: Ambient Air Pollutants and their Standard Measurement Procedures Particulars RSPM PM 2.5 NOX SO2 CO OC/EC Sampling Respirable Airmetric Impingers Impingers Model PM10 Instrument particulate attached to attached to 8762 IAQ- Sampler matter sampler RPM sampler RPM CALc with Quartz sampler filter Sampling Filtration of Chemical Chemical Suction by Filtration of Principle aerodynamic absorption in absorption Pump aerodynami sizes with a suitable media in suitable c sizes with size cut by media a size cut by impaction impaction Flow rate 1.1 m3/min 5 LPM 0.5 LPM 0.5 LPM --- 5LPM Sampling 24 hourly 24 hourly 24 Hourly 24 Hourly Grab 24 hourly Period sampling thrice a day Analytical Electronic Electronic Spectrophoto- Spectro- Model OC/EC instrument Balance, Micro meter photometer 8762 IAQ- Analyser Respirable Balance, CALc particulate Airmetrics matter sampler Analytical Gravimetric Gravimetric Colorimetric Colorimetric Non- TOR/TOT method Improved Jacobs & dispersive Method West & Gaeke Hochheiser infrared NIOSH Method Modified 5040 method Min. 5 µg/m3 5 µg/m3 9 µg/m3 4 µg/m3 1ppm 0.2 µg/ 0.5 Reportable cm2 punch value
Particulars Ions NMHC HC Metals Sampling PM2.5 Sampler Low volume Low volume PM2.5 Sampler Particulate collected Instrument Particulate sampling pump sampling pump on Teflon filter collected on connected to connected to Quartz filter Tedlar bags Tedlar bags Sampling Filtration of Suction by Auto suction Filtration of aerodynamic sizes with Principle aerodynamic Pump by pump a size cut by impaction sizes with a size cut by impaction Flow rate 5 LPM 0.5 lpm 0.5 lpm 5 LPM Sampling 24 hourly 24 Hourly 24 Hourly Period Analytical Ion GC - FID with GC - FID with Inductively coupled plasma optical instrument Chromato-graph Methaniser Methaniser emission spectrometry (ICPOES) Analytical Ion Chromato- Flame ionization Flame Emission spectroscopy to produce method graphy detector ionization excited atoms and ions that Analysis detector emit electromagnetic radiation at Analysis wavelengths characteristic of a particular element. The intensity of this emission is indicative of the conc. of the element Minimum Varies with ion to 0.05 ppm 0.05 ppm Varies with element to element Reportable ion value
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2.1.2 Results of Winter Monitoring
The 24 hourly concentrations of PM2.5 and RSPM for summer season at all the locations are presented in Figures 2.3 and 2.4. The National Ambient Air Quality Standards of Central Pollution Control Board is presented in Annexure 2.1. a) Palchen Site : The 24 hourly observed concentrations for winter season are presented in Table 3 2.2. The RSPM and PM2.5 concentrations at Palchen were within the CPCB standard of 100 µg/m 3 and 60 µg/m . SO2 and NO2 were also very low and well below the CPCB standards. As the site was 100 m away from the Leh Manali highway, the concentrations are within the limits. CO values ranged between 0-1 ppm. OC and EC account for 30% and 9% respectively and thus indicate the contribution from sources like automobile exhaust and biomass burning. The average OC/EC ratio was found to be 5.7 indicating secondary aerosol formations. OC can be directly emitted to the atmosphere in the particulate form (primary) or can be produced by gas to particle conversion processes (secondary). EC is emitted from combustion sources. Since primary OC and EC are mostly emitted from the same sources, EC can be used as a tracer for primary combustion- generated OC (Gray, 1986; Strader et al., 1999). The formation of secondary organic aerosol (SOA) increases the ambient concentration of OC and the ambient OC/EC ratio. OC to EC ratios exceeding the expected primary emission ratio are an indication of SOA formation.
Table 2.2: Air Quality Status at Palchen (Winter) Pollutants Min Max Avg SD N RSPM (µg/m3) 34 78 56 15.3 6 3 PM2.5 (µg/m ) 25 35 29 5.2 3 3 OC (µg/m ) in PM2.5 8.3 15.3 11.0 3.8 3 3 EC (µg/m ) in PM2.5 2.3 5.1 3.5 1.4 3 3 TC (µg/m ) in PM2.5 10.6 20.5 14.5 5.2 3 3 SO2 (µg/m ) BDL 4 2 1.56 6 3 NO2 (µg/m ) BDL BDL 5 0.79 6 b) Kothi Site : The observed concentrations for winter season are presented in Table 2.3. The
RSPM concentrations are within the CPCB standards. SO2 and NO2 values were very low. OC and EC account for 17% and 3% respectively of PM2.5. The average OC/EC ratio was found to be 6.4 indicating formation of secondary aerosols.
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Palchen
Kothi
Solang
Figure 2.3 : RSPM Concentrations in April at 3 Locations
Figure 2.4: PM2.5 Concentrations in April at 3 Locations
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Table 2.3: Air Quality Status at Kothi (Winter) Pollutants Min Max Avg SD N RSPM (µg/m3) 31 94 66 26.8 6 3 PM2.5 (µg/m ) 21 32 26 6.0 3 3 OC (µg/m ) in PM2.5 6 10 8 2.0 3 3 EC (µg/m ) in PM2.5 1 2 1.5 0.3 3 3 TC (µg/m ) in PM2.5 7 12 10 2.1 3 3 SO2 (µg/m ) BDL 3 2 1.5 6 3 NO2 (µg/m ) 5 5 5 0 6 c) Solang Site : The 24 hourly observed concentrations for winter season are presented in Table
2.4. The RSPM and PM2.5 at Solang was within the CPCB standards for all six days of monitoring.
SO2 and NO2 values were also very low. As the site was 200 m away from the Leh Manali highway, the concentrations are within the limits. CO values ranged between 0-1. ppm. The average OC and EC account for very high value of 44% and 6% respectively of PM2.5 and thus indicate the contribution from sources like automobile exhaust. The average OC/EC ratio was 5.3.
Table 2.4: Air Quality Status at Solang Valley (Winter) Pollutants Min Max Avg SD N RSPM (µg/m3) 29 70 48 14.6 6 3 PM2.5 (µg/m ) 24 35 29 5.6 3 3 OC (µg/m ) in PM2.5 9 18 15 4.4 3 3 EC (µg/m ) in PM2.5 1.9 2.5 2.2 0.3 3 3 TC (µg/m ) in PM2.5 11 20 17 4.7 3 3 SO2 (µg/m ) BDL BDL 2 0 6 3 NO2 (µg/m ) BDL BDL 5 0 6
Concentration of Ions : Ions were analyzed in PM2.5 samples. Table 2.5 gives the concentration of ions at the three monitoring locations. Lithium, Sodium, Magnesium, Calcium, Nitrite and Phosphate were analyzed but not detected at any of the sites.
Table 2.5 Average Concentration of Ions in μg/m3 in Winter Palchan Kothi Solang Li+ BDL BDL BDL Na+ BDL BDL BDL NH4+ 1.900 BDL BDL K+ BDL BDL 0.472 Mg+2 BDL BDL BDL Ca+2 BDL BDL BDL F- 0.279 BDL BDL Cl- BDL BDL 1.241 - NO2 BDL BDL BDL -2 SO4 10.216 BDL BDL Br- 0.660 BDL BDL - NO3 BDL 0.800 0.280 -3 PO4 BDL BDL BDL
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Concentration of Elements : Table 2.6 gives the average concentration of elements in PM2.5 at three monitoring locations. At Kothi, As is exceeding the CPCB standard of 6 ng/m3. Ni is below detectable level at all monitoring sites. Concentration of Pb is also well below the CPCB standard of 1 μg/m3 at all the sites. Fe is the most abundant metal.
Table 2.6 Average Concentration of Elements in μg/m3 in winter Palchen Kothi Solang As BDL 0.011 BDL Cd BDL BDL BDL Co BDL BDL 0.006 Cr 0.633 0.193 0.204 Cu 0.073 0.062 0.057 Fe 8.348 3.487 4.991 Mn 0.056 0.033 0.042 Ni BDL BDL BDL Pb 0.014 0.005 0.111 Zn 0.734 0.293 0.673
2.2 Summer Air Quality Monitoring
Five sampling sites were selected which were representative of Rohtang pass area. Monitoring was carried out at five locations during May 2012 for 10 days. These included the three locations monitored earlier. Figure 2.1 shows the five monitoring locations. The description of two additional sampling locations is given below.
Marhi: Marhi is a "shanty town of roadside restaurants" in Himachal Pradesh, India, located midway between Manali and Rohtang La on the Manali-Leh Highway. Buses traveling the highway often stop in Marhi for passengers to eat. The settlement is seasonal, with most businesses closing for the winter.
Khoksar: Khoksar is located in Lahul & Spiti district of Himachal Pradesh State in India. Khoksar is located on the other side of Rohtang pass. To reach Khoksar one has to cross the Rohtang pass. It is the best location for White Water Rafting. This is covered heavily by snow during the winter months. This place is thinly populated and once snow fall starts, people move to other warm places. Khoksar being very thinly populated with very few vehicles can be considered as a background site.
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2.2.1 Results of Summer Monitoring
Figures 2.5 and 2.6 give the concentrations of RSPM and PM2.5 at the five monitoring locations. a) Palchen Site : Table 2.7 gives the 24 hourly observed concentrations for summer season. The percent exceedance of RSPM at Palchen was 30. PM2.5, NO2 and SO2 were within the CPCB standards of 60, 80 and 80 µg/m3. The average OC and EC account for very high value of 30% and
12% respectively of PM2.5. The average OC/EC ratio was 3.2 which indicates that there may be formation of secondary organic carbon aerosols. CO values ranged between 0-1 ppm. Methane observed at Palchen was 2.53 ppm whereas nonmethane hydrocarbon was not found at Palchen.
Table 2.7 : Air Quality Status at Palchen (Summer) Pollutants Min Max Avg SD N RSPM (µg/m3) 32 118 82 31.3 10 3 PM2.5 (µg/m ) 23 53 35 12.4 5 3 OC (µg/m ) in PM2.5 8 15 11 3.8 5 3 EC (µg/m ) in PM2.5 2 5 4 1.5 5 3 TC (µg/m ) in PM2.5 10 20 15 5.2 5 3 SO2 (µg/m ) BDL BDL BDL 0 10 3 NO2 (µg/m ) 5 10 5 3.29 10 b) Kothi Site: Table 2.8 gives the 24 hourly observed concentrations for summer season. The percent exceedance of RSPM and PM2.5 at Kothi were 0 and 17 percent respectively. NO2 and SO2 levels were within CPCB standards. The average OC and EC account for 29 and 14% respectively of PM2.5. The average OC/EC ratio was 4.3. CO values ranged between 0-1.0 ppm. Methane ranged between 0.99 and 1.61 ppm. Non-methane hydrocarbon observed at Kothi ranged between 0.11 and 0.31 ppm.
Table 2.8 : Air Quality Status at Kothi (Summer) Pollutants Min Max Avg SD N RSPM (µg/m3) 63 98 83 12.4 10 3 PM2.5 (µg/m ) 11 64 28 19.3 6 3 OC (µg/m ) in PM2.5 7 9.5 8 1.4 4 3 EC (µg/m ) in PM2.5 2 9.3 4 4.3 4 3 TC (µg/m ) in PM2.5 9 19 13 5.3 4 3 SO2 (µg/m ) BDL 37.8 3.8 11.9 10 3 NO2 (µg/m ) 5 11 6 1.2 10 c) Solang Site: The 24 hourly observed concentrations for Solang site for summer season are given in Table 2.9. The percent exceedance of RSPM at Solang was 40 whereas PM2.5 was found to be within the CPCB limits. Several tourist activities like paragliding, snow tubing, skiing were observed at Solang which resulted in more tourists and hence higher value of RSPM. SO2 and NO2 levels were very low. The average OC and EC account for 36 and 12% respectively of PM2.5. The
Study of Rohtang Pass | 2.9 average OC/EC ratio was 2.9. CO values ranged between 0-1 ppm. Methane was 2.88 ppm and nonmethane hydrocarbon was 0.15 ppm. Table 2.9 : Air Quality Status at Solang Valley (Summer) Pollutants Min Max Avg SD N RSPM (µg/m3) 55 132 93 26.6 10 3 PM2.5 (µg/m ) 19 53 33 14.6 6 3 OC (µg/m ) in PM2.5 11 12 12 0.6 6 3 EC (µg/m ) in PM2.5 3 5 4 0.7 6 3 TC (µg/m ) in PM2.5 15 17 16 1.2 6 3 SO2 (µg/m ) BDL BDL BDL 0 10 3 NO2 (µg/m ) BDL 12 6 2.5 10 d) Marhi Site: The 24 hourly observed concentrations for summer season are given in Table
2.10. RSPM and PM2.5 concentrations were within the CPCB limits. SO2 and NO2 concentrations were very low. The average OC and EC account for 36 and 8% respectively of PM2.5. The average OC/EC ratio was found to be as high as 5.7. CO values were found to be 0 ppm. Methane ranged between 1.97 and 2.15 ppm whereas non-methane hydrocarbon was not found at Marhi. The sampling site was about 250 m from the highway and therefore the concentrations were low. Table 2.10 : Air Quality Status at Marhi (Summer) Pollutants Min Max Avg SD N RSPM (µg/m3) 13 84 50 24.4 9 3 PM2.5 (µg/m ) 15 40 25 9.4 6 3 OC (µg/m ) in PM2.5 8 10 9 0.9 4 3 EC (µg/m ) in PM2.5 1 3 2 1.1 4 3 TC (µg/m ) in PM2.5 9 13 11 1.8 4 3 SO2 (µg/m ) BDL BDL BDL 0 10 3 NO2 (µg/m ) BDL 6 5 2.5 10 e) Khoksar Site: The 24 hourly observed concentrations for summer season are given in Table
2.11. RSPM and PM2.5 concentrations were within the CPCB limits. SO2 and NO2 levels were below detectable limits. The average OC and EC account for very high value of 62 and 23% respectively of PM2.5. The average OC/EC ratio was found to be 2.7. CO values were found to be 0 ppm. Methane observed at Khoksar ranged between 2.31 to 2.48 ppm and non-methane hydrocarbon was not found at Khoksar. Khoksar being very thinly populated with very few vehicles has very low concentrations of pollutants. Table 2.11 : Air Quality Status at Khoksar (Summer) Pollutants Min Max Avg SD N RSPM (µg/m3) 26 44 37 7.8 5 3 PM2.5 (µg/m ) 19 24 21 6.3 3 OC (µg/m3) in PM2.5 11 15 13 ---- 2 EC (µg/m3) in PM2.5 3 7 5 ---- 2 TC (µg/m3) in PM2.5 14 22 18 ---- 2 3 SO2 (µg/m ) BDL BDL BDL 0 10 3 NO2 (µg/m ) BDL BDL BDL 0 10
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Palchen
Kothi
Solang
Marhi
Koksar
Figure 2.5 : RSPM Concentrations at the Monitoring Sites in May
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Palchen
Solang
Kothi
Marhi
Khoksar
Figure 2.6: PM2.5 Concentrations at Monitoring Locations During May
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Concentration of Ions in PM2.5 : Table 2.12 gives the levels of ions in PM2.5. Lithium, Sodium, Magnesium, Bromide and Phosphate were analyzed but not detected in any of the sites.
Table 2.12 Average Concentrations of Ions in Summer at 5 Monitoring Locations Palchan Kothi Solang Marthi Khoksar Li+ BDL BDL BDL BDL BDL Na+ BDL BDL BDL BDL BDL + NH4 BDL 2.777 2.769 1.839 BDL K+ 3.172 1.919 1.121 1.369 BDL Mg+2 BDL BDL BDL BDL BDL Ca+2 BDL BDL BDL BDL 6.457 F- 4.359 BDL BDL 0.467 BDL Cl- BDL BDL BDL 2.473 2.634 - NO2 BDL 9.029 BDL BDL BDL -2 SO4 BDL BDL BDL BDL 11.251 Br- BDL BDL BDL BDL BDL - NO3 0.650 0.550 0.657 0.795 0.442 -3 PO4 BDL BDL BDL BDL BDL All values in µg/m3
Concentration of Elements in PM2.5 : Table 2.13 gives the concentration of elements in PM2.5 at five monitoring locations. As is exceeding the CPCB standard of 6 ng/m3 at Marhi. Average concentration of Ni is also exceeding the standard of 20 ng/m3 at all sites except Palchen. However, concentration of Pb is well below the CPCB standard of 1 μg/m3 at all the sites.
Table 2.13 : Average Element Concentrations in Summer at 5 Monitoring Locations Palchen Kothi Solang Marhi Khoksar As BDL BDL BDL 0.022 BDL Cd BDL BDL 0.035 BDL BDL Co BDL BDL 0.01 BDL BDL Cr 0.729 1.076 0.358 0.699 0.242 Cu 0.173 0.271 0.263 0.114 0.057 Fe 9.824 10.921 5.695 8.316 5.035 Mn 0.947 0.212 0.777 0.080 0.050 Ni BDL 0.181 0.071 0.158 0.026 Pb 0.120 0.145 0.042 0.126 0.027 Zn 0.512 0.325 0.351 0.237 0.507 All values in µg/m3
Figure 2.7 represents variation of carcinogenic elements at sampling sites.
3 /m g μ Conc. in
Figure 2.7 : Site wise Variation of Elements (As, Ni and Pb)
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2.3 Conclusions
3 RSPM values were reported in the range of 13 to 132 µg/m . PM2.5 values were varying from 11 to 3 3 3 64 µg/m . OC and EC concentration in PM2.5 was reported to be 6 to 18 µg/m and 1 to 9.3 µg/m respectively. The gaseous pollutants (SO2 and NO2) were within the standard during all the sampling days.
- - Ionic composition of particulate matter at the sampling sites indicated the presence of Cl , NO 3, - + + - SO 4, NH4 shows impact of vehicular transport, whereas K and Cl also indicate the contribution of biomass burning.
During the study period, concentration of carcinogenic elements viz. As and Ni exceeded the prescribed CPCB standards, whereas Pb concentration at all the sites is within stipulated standards. Irrespective of season crustal element ‘Fe’ is the most abundant metal.
The results show that though the overall pollution is less, some trends show that deterioration has started.
References • Gray, H.A., Cass, G.R.; Huntzicker, J.J., Heyerdahi, E.K., Rau, J.A. (1986). Characteristics of Atmospheric Organic and Elemental Carbon Particle Concentrations in Los Angeles. Environmental Science and Technology. 20: 580-589. • Strader, R., Lurmann, F.; Pandis, S. (1999).Evaluation of Secondary Organic Aerosol Formation in Winter. Atmospheric Environment. 33, 4849-4863.
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Chapter 3
Air Quality Modeling
3.1 Preamble
Himachal Pradesh boasts of beautiful landscapes and mountains in their pristine form. It is one of the top tourist destinations in the country. Rohtang pass provides excellent opportunities for trekking and offers spectacular views of the Himalayas. During the peak period in May and June around 10,000 tourists visit Rohtang pass every day. According to the Tourism department, about 2200 to 2500 vehicles ply to the pass every day. According to BRO, about 3600 vehicles ply to the pass. According to the NEERI study during May end of 2012, the total no of vehicles along the road between Manali and Palchen were 3180.
The width of the road is not enough to sustain such a heavy traffic and this leads to massive traffic jam daily. This also leads to higher emissions. The BRO has started constructing the Rohtang tunnel which is expected to be completed by 2015. The traffic to Leh, Lahoul and Spiti areas will get diverted after the tunnel construction is over leading to improvement in traffic jams. Therefore, there is a great concern about the vehicle management in this area and therefore air quality modeling was carried out.
Air quality modeling was carried out for summer season for the Month of May, 2012. EPA regulatory model AERMOD (Cimorelli, 2005) which is a state of the art dispersion model was used to predict spatial distribution of PM10, NO2 and CO concentrations in ambient air. The AERMOD model is applicable to rural and urban areas, flat and complex terrain, surface and elevated releases, and multiple sources (including, point, area and volume sources). AERMOD is a steady-state plume model.
In the stable boundary layer (SBL), it assumes the concentration distribution to be Gaussian in both the vertical and horizontal. In the convective boundary layer (CBL), the horizontal distribution is also assumed to be Gaussian, but the vertical distribution is described with a bi-Gaussian probability density function. The convective boundary layer, or dry adiabatic layer is the lower tropospheric layer in contact with the ground heated by the sun and swept by the wind. The convective phenomena and wind causes significant air mixing with horizontal and vertical turbulences. Additionally, in the CBL, AERMOD treats “plume lofting,” whereby a portion of plume mass, released from a buoyant source, rises to and remains near the top of the boundary layer before becoming mixed into the CBL. AERMOD also tracks any plume mass that penetrates into the elevated stable layer, and then allows it to re-enter the boundary layer when and if appropriate.
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Recently USEPA has developed the meteorological preprocessor IMD-AERMET which uses routine data from the IMD to estimate the meteorological inputs required to apply AERMOD. IMD AERMET requires only a single surface measurement of wind speed wind direction and ambient temperature. Like ISCST3, AERMOD also needs observed cloud cover. Surface characteristics in the form of albedo, surface roughness and Bowen ratio, plus standard meteorological observations (wind speed, wind direction, temperature, and cloud cover), are input to AERMET. AERMET then calculates the PBL parameters: friction velocity, Monin-Obukhov length, convective velocity scale, temperature scale, mixing height, and surface heat flux (H). These parameters are then passed to the INTERFACE (which is within AERMOD) where similarity expressions (in conjunction with measurements) are used to calculate vertical profiles of wind speed (u), lateral and vertical turbulent fluctuations, potential temperature gradient (d2/dz), and potential temperature.
3.2 Meteorological Data
Meteorological conditions play a vital role in transport and dispersion of pollutants in the atmosphere. The hourly surface meteorological data viz. wind speed and direction and surface temperature required as input to the model were collected at Manali. Meteorological data was collected using a continuous wind monitoring instrument round the clock during May 2012 (summer season). The wind rose for May is given in Figure 3.1. The prominent directions during May are South (S), South South East (SSE), and South East (SE) with a high calm percentage of 65%.
Figure 3.1: Wind Rose for the Month of May, 2012
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3.3 Vehicular Sources
Vehicular emissions are considered to be one of the major source categories of air pollution in cities and major highways. The quantity of air pollutants emitted by different categories of vehicles is directly proportional to the average distance traveled by each type of vehicle, number of vehicles plying on the road, quality of fuels being used, age and technology of vehicles in use etc. However, several other factors, such as inadequate and poorly maintained roads as well as adopted practices of inspection and maintenance of vehicles; unplanned traffic flow, and non-availability of effective emission control technology etc. also contribute to the air pollution from vehicular sources.
Vehicle Count: In order to prepare emission inventory of vehicular sources, primary data on traffic count were collected in the identified study zone. All types of vehicles moving on the Leh Manali Highway were counted manually from 7 am to 7pm at four monitoring sites in May 2012 on two days. The vehicles are categorized into four major categories as heavy motor vehicles, car petrol, car diesel and two wheelers. Emissions from the tail pipes of the automobiles were estimated on the basis of vehicle kilometers traveled (VKT) by different types of vehicles and the fuel used. Figure 3.2 shows the three vehicle counting locations.
Figure 3.2 : The Three Vehicle Counting Locations
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According to the NEERI study during May end of 2012, the total no of vehicles along the road between Manali and Palchen were 3180. The no of vehicles plying from Palchen to Marhi were 1836 whereas the no of vehicles plying from Palchen to Solang valley were 1344. Highest percentage was observed for cars, which was 86%. Average percentage of two wheelers and heavy motor vehicles observed were 12 and 2% of the total number of vehicles.
3.4 Applicable Emission Factors
Emission Factors for different types and makes of vehicles have been developed by Automotive Research Association of India (ARAI), Pune in 2007 under CPCB guidance [2]. The emission factors used in the emission load calculations are summarized in Table 3.1.
Table 3.1 : Applicable Emission Factors for Vehicular Source Type of Vehicle NOx (gm/km) PM (gm/km) CO (gm/km) Trucks (post 2000) 9.300 1.240 6.00 Car petrol (post 2005) 0.090 0.002 0.84 2 wheeler (post 2005) 0.150 0.013 0.72 Car diesel (post 2005) 0.280 0.015 0.06
3.5 Paved Road Dust
The other source considered for modeling was paved road dust. As motor vehicles move over road surface, settled dust from the paved surface is emitted by the turbulent wake of the vehicles. Emissions are estimated as a function of the silt loading of the paved surface and mean weight of the vehicles traveling over the surface. Data source included road length, vehicle km traveled, and vehicle counting at few locations. The Table 3.2 gives the vehicle weight and Table 3.3 gives the paved road emission load.
Table 3.2: Vehicle Weight Vehicle Count %Vehicle Avg. Weight [3] Veh. Weight by % May 2012 Count (A) (kg) (B) (A*B) (kg) 2 W 745 0.117 175 20.5 Heavy motor 110 0.017 20000 346.0 vehicles cars 5503 0.866 1425 1233.4 Total 6358 1 1599.9
Annual /Long Term Avg. Emission Factor E =[{ k (sL/2)0.65 (W/3 )1.5}-C] (1-P/4N).
Where, E = particulate emission factor (having units matching the units of k) k = particle size multiplier for particle size range and units of interest sL = road surface silt loading (grams per square meter) (g/m2) W = average weight (tons) of the vehicles traveling on the road P = No. of wet days with at least 0.254 mm of precipitation during avg. period C = Break and tire wear correction (PM10=0.1317) N = No. of days in averaging period (365 /year, 30/monthly, 91/seasonal);
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Values of k (g/vkt) for PM10 = 4.6 Value of road surface silt loading was taken as 0.531 from ADB 2005 [3].
Therefore EF (PM10) = [{4.6*((0.531/2)^0.65)*((1.599/3)^1.5)}-0.1317]*((1-120/(4*365))) =0.5701 g/VMT = 0.354 g/VKT
Table 3.3 : Paved Road Emission Load (kg/day) Road Emission Load Palchen to Solang 9.52 Palchen to Marhi 62.41 Marhi to Khoksar 2.79 Manali to Palchen 40.55
3.6 Modeling Results
3.6.1 PM Concentration
Predicted concentration contours of PM are shown in Figure 3.3 and 3.4. The concentrations range between 0.to 90 μg/m3.
3 Figure 3.3 : Contour Map of PM10 in μg/m Due to Vehicular Sources & Paved Road Dust
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3 Figure 3.4: Three Dimensional Contour Map of PM10 in μg/m due to Vehicular Sources and Paved Road Dust
The observed and predicted concentration of PM10 is presented in Figure 3.5.
Figure 3.5: Observed and Predicted Concentrations of PM in μg/m3 10 at the Monitoring Sites
3.6.2 NO2 Concentration
Average concentration contours for the month of May, for NO2 are shown in Figure 3.6 and 3.7. 3 The concentration range between 0.0 to 10.05 μg/m . The observed concentration of NO2 lies between 0 to 14 μg/m3.
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3 Figure 3.6: Contour Map of NO2 in μg/m Due to Vehicular Sources in the Study Domain
3 Figure 3.7: Three Dimensional Contour Map of NO2 in μg/m Due to Vehicular Sources
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The observed and predicted concentration of NO2 is presented in Figure 3.8.
3 Figure 3.8 : Observed and Predicted Concentrations of NO2 in μg/m at the Monitoring Sites
3.6.3 CO Concentration
Average concentration contours for the month of May, for CO are shown in Figure 3.9 and 3.10. The concentration range between 0.0 to 9 μg/m3. The observed concentration of CO lies between 0 to14 μg/m3.
3 Figure 3.9 : Contour Map of CO in μg/m Due to Vehicular Sources in the Study Domain
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3 Figure 3.10: Three Dimensional Contour Map of CO in μg/m Due to Vehicular Sources
The observed and predicted concentration of CO is presented in Figure 3.11.
Figure 3.11: Observed and Predicted Values of CO in μg/m3 Due to Vehicular Sources at the Monitoring Sites
3.7 Conclusions
The monitoring results show that the overall pollution is less. The percent exceedance for April and May with the 24 hourly CPCB standards are given in Table 3.4.
Table 3.4 : Percent Exceedance of PM10 and PM2.5 During May and April Summer (May) Winter (April) Location PM10 PM2.5 PM10 PM2.5 Palchen 30 0 0 0 Kothi 0 16.7 0 0 Solang 40 0 0 0 Marhi 0 0 - - Khoksar 0 0 - -
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The results show that deterioration has started. With increase in tourists over the years the air quality would deteriorate further unless it is taken care.
References
1. AERMOD: Description of Model Formulation, Alan J. Cimorelli et al, USEPA, Office of Air Quality Planning and Standards, Emissions Monitoring and Analysis Division, Research Triangle Park, North Carolina, 2004
2. Emission Factor development for Indian vehicles, as a part of Ambient Air Quality Monitoring and Emission Source Apportionment Studies, ARAI, Pune, CPCB, MOEF, August, 2007
3. Strengthening Environmental Management at the State Level (Cluster) Component E- Strengthening Environmental Management at West Bengal Pollution Control Board, TA No. 3423-IND, Asian Development Bank, Nov. 2005
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Chapter 4
Water Environment
4.1 Introduction & Objective
Water quality assessment is important to evaluate the existing water environment and the expected impact due to the tourist activities. The study of water environment aims at • To understand the baseline characteristics, • To identify water polluting sources; • To identify critical parameters of water characteristics and their origin; • To predict impact on water quality • To suggest appropriate preventive and mitigation measures
Objective: To assess the various water resources in Beas and Chandra river and hill streams covering Rohtang pass area between Manali to Khoksar on NH- Manali Leh.
4.2 Methodology
The area between Manali to Khoksar was considered for present study. Beas and Chenab are the two major rivers flowing through the selected study area. The river Beas has its origin at Beas Kund near the Rohtang pass in the Pir-Panjal range to the north of Kulu, at an elevation of 4085 m. Chenab River is formed as the result of conflux of Chandra and Bhag river at Tandi in the lap of Upper Himalayas. Both the rivers are perennial with continuous input of water from nearby springs and glaciers. The water shade maps of these rivers are given in Figure 4.1. The samples were collected from upstream and downstream of major towns of both the rivers to know their water quality. Water sampling locations within study area were finalized based on • Preliminary site visits • Approachability of areas • Identification of major water bodies through Google maps
Figure 4.1 : Beas and Chenab River Basin
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The water samples from various river stretches, springs, ground water, nallah and municipal water supply schemes were collected from selected study area during April and May 2012 to review the overall water quality. There are 21 hand pumps in study area, but due to surplus of surface water availability, these hand pumps are not used frequently. To assess ground water quality hand pump samples were also collected. List of water sampling locations is given in Table 4.1 and depicted in Figure 4.2. The collection of samples from various sources is presented in Plate 4.1.
Table 4.1: Water Sampling Locations Category Sample Name of Location Latitude (N) Longitude (E) Code River R1 Beas river at Dhundi 32°21’21.3” 77°07’42.9” Water R2 Beas river at Shanang 32°16’29.6” 77°10’48.0” R3 Beas river at Bahang 32°16’23.2” 77°10’48.9” R4 Beas river at Vashisth 32°15’53.3” 77°11’04.9” R5 Beas river at U/S of Manali 32°14’43.9” 77°11’29.1” R6 Beas river at D/S of Manali 32°13’57.3” 77°11’18.1” R7 Chandra river at Sissu 32°26’51.2” 77°08’58.6” R8 Chandra river at Khoksar 32°24’33.6” 77°14’05.3” R9 Chandra river at Gramphu 32°23’36.3” 77°15’32.7” Springs S1 Marhi Spring 32°21’06.7” 77°12’ 58.8” S2 Gulaba Spring 32°20’24.8” 77°13’04.7” S3 Rahallah Fall 32°20'11.0" 77°13'70.0" S4 Palchan Spring 32°18'32.0” 77°10'40.0” S5 Nehru Kund 32°16’42.8” 77°10’52.0” S6 Vashishth Kund 32°15’55.1” 77°11’16.5” Ground GW1 Hand Pump at Palchan 32°18'34.0" 77°10'41.0" Water GW2 Hand Pump at Bahang 32°16'21.0” 77°10'56.2” GW3 Hand Pump at Nehru Kund 32°17'15.8" 77°10'39.0" Water WS1 Khoksar 32°24’31.6” 77°14’07.3” Supply WS2 Marhi 32°21’05.4” 77°12’57.2” WS3 Solang 32°18'44.0" 77°10'40.2" WS4 Kothi 31° 8'17.6" 77°29'47.5" Nallah N1 Beas Nallah U/S 32°19'23.1" 77° 9'15.5" N2 Beas Nallah D/S 32°18'45.5" 77°10'40.6" N3 Solang Nallah 32°18’47.5” 77°09’27.4” N4 Palchan Nallah 32°18'30.0” 77°10'39.0” N5 Rani Nallah 32°21'46.0" 77°14'40.0"
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Figure 4.2: Water Sampling Locations Between Manali to Khoksar
Plate 4.1 : Water Sampling at Various
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4.3 Sampling Procedure
The water quality was assessed for various physico-chemical and microbiological parameters specified under “Uniform Protocol on Water Quality Monitoring Order, 2005” prescribed by Ministry of Environment & Forests (Annexure 4.1). The samples were collected and analyzed as per the procedures specified in ‘Standards Methods for the Examination of Water and Waste Water’ published by American Public Health Association (APHA) 21st edition (2005).
Samples for chemical analysis were collected in polyethylene carboys. Samples collected for heavy metal analysis were acidified (1 ml HNO3/100 ml). Samples for microbiological analysis were collected in sterilized glass bottles. Samples for phytoplankton were preserved using Lugol’s Iodine in plastic bottles of 100 ml capacity. Basic parameters like pH, temperature, colour, odour, turbidity and dissolved oxygen were analyzed at sampling sites using portable water testing kits. Field laboratory was set up at Manali HPPCB laboratory to conduct physico-chemical and microbiological analysis (Plates 4.2 and 4.3). The methodology for sample collection and preservation techniques was followed as per the Standard Operating Procedures (SOP) mentioned in Annexure 4.2. The analytical techniques used for water analysis for selected parameters are given in the Annexure 4.3.
Plate 4.2 : Field Laboratory Established for Water Quality Analysis for Physico-Chemical Parameters
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Plate 4.3 : Water Quality Analysis for Microbiological
The analytical results of all the water samples are presented in Tables 4.2 to 4.4. The results of trace metals analysis is given in Table 4.5. All the results are compared with standards for drinking water as per “BIS: 10500-2012 (second revision) Specifications for Drinking Water” and CPCB water quality standards (Annexure 4.4 and 4.5). The results of phytoplankton are presented in Tables 4.6 and 4.7.
4.4 General Observations
The general observations of selected water samples are as indicated below:
¾ Physico-chemcial Parameters : The various water sources in study region are pristine having less turbidity. It is observed that all physico-chemcial parameters for surface, spring and ground water along with municipal water supply samples were much below the desirable limits of drinking water standards. The pH of water samples showed that all the collected samples were neutral to slightly alkaline. Nitrate, ammonical nitrogen and phosphorus were most of the time below detectable level. Low nutrient concentration in water samples indicates there is no chance of eutrophication. It indicates that there is no pollution due to domestic and industrial effluent.
Though no significant water pollution in terms of chemical constituents was observed, the water quality gets deteriorated from upstream to downstream where large population is concentrated.
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Table 4.2 : Physico-chemical Characterization of Beas and Chandra River Water Samples Sam. pH Temp EC TDS Tur. T- Ca- Mg- T- Cl2 SO4 NO3 NH3-N T-PO4 DO BOD TC FC Code (0C) (μS/cm) Alk. Har. Har. Har. R1 7.5 7.5 114.4 68.6 1.0 59.0 21.0 22.0 43.0 6.0 6.5 BDL BDL BDL 7.2 2.4 - - R2 7.4 7.2 107.0 64.1 6.0 34.0 37.0 8.0 45.0 5.0 15.0 BDL BDL BDL 7.8 3.4 800 200 R3 7.3 6.8 100.0 60.1 5.0 28.0 33.0 15.0 48.0 5.5 14.0 BDL BDL BDL 7.4 2.8 - - R4 7.2 6.2 93.0 55.2 3.0 27.0 32.0 14.0 46.0 6.0 9.8 BDL BDL BDL 7.8 3.2 5000 2200 R5 7.0 6.4 97.6 58.5 2.0 26.0 39.0 8.0 47.0 5.0 13.0 0.4 BDL BDL 7.4 3.1 1300 550 R6 7.1 6.7 89.3 53.6 3.0 30.0 32.0 16.0 48.0 6.0 5.5 0.4 0.8 BDL 7.5 3.5 TNC TNC R7 7.2 8.0 111.6 67.0 2.0 26.0 36.0 16.0 52.0 1.0 24.5 0.6 0.17 BDL 7.5 2.7 - - R8 6.7 8.0 119.7 71.8 5.0 24.0 41.0 19.0 60.0 1.0 28.0 0.4 BDL BDL 6.9 1.9 - - R9 7.1 8.2 109.0 65.4 3.0 24.0 37.0 11.0 48.0 1.5 24.5 0.5 0.98 BDL 7.2 2.4 - - All samples are colourles and odourless. Temp.- Temperature, EC- Electrical Conductivity, TDS- Total Dissolved Solids, Tur.- Turbidity. T-Alk- Total Alkalinity, Ca-Har.- Calcium Hardness, Mg-Har. –Magnesium Hardness, T-Har.- Total Hardness , Cl2- Chlorides, SO4- Sulphate, NO3- Nitrate,NH3-N- Ammonical Nitrogen, DO- Dissolved Oxygen, BOD- Biochemical Oxygen Demand, TC- Total Coilforms, FC-Fecal Coliforms, BDL- Below Detectable Limit. All parameters are in mg/L. TC and FC are expressed in CFU/100ml.
Table 4.3: Physico-chemical Characterization of Springs and Municipal Water Supply Samples Sam. pH Temp EC TDS Tur. T- Ca- Mg- T- Cl2 SO4 NO3 NH3-N T-PO4 DO BOD TC FC Code (0C) (μS/cm) Alk. Har. Har. Har. S1 7.8 8.0 26.0 15.6 2.0 9.0 5.0 3.0 8.0 1.5 BDL BDL BDL BDL 8.3 2.8 2000 1100 S2 7.6 5.0 34.5 20.7 6.0 8.0 6.0 3.0 9.0 3.5 3.3 BDL BDL BDL 7.7 2.6 - - S3 7.3 8.5 28.6 17.1 1.0 10.0 5.0 1.0 6.0 2.5 BDL 0.4 BDL BDL 7.5 2.3 - - S4 7.4 9.2 110.1 66.1 6.0 33.0 41.0 16.0 57.0 5.0 15.0 BDL 0.45 BDL 7.8 2.5 - - S5 7.3 8.0 98.8 59.3 1.0 28.0 44.0 14.0 58.0 5.5 10.0 BDL BDL BDL 7.8 2.3 - - S6 7.4 50+ 448.0 268.8 3.0 165 26.0 4.0 30.0 123 29.0 0.4 1.26 BDL 2.6 0 300 150 WS1 6.8 4 31.2 18.7 1.0 9.0 9.0 5.0 14.0 2.0 BDL 0.5 BDL BDL 7.1 2.6 - - WS2 7.5 16 25.5 15.3 3.0 8.0 7.0 2.0 9.0 1.0 BDL 0.2 BDL BDL 6.7 1.4 200 95 WS3 7.0 9 66.5 39.9 1.0 16.0 24.0 11.0 35.0 4.5 7.5 BDL BDL BDL 6.9 1.7 - - WS4 7.5 6 130 78 1 45 45 16 61 6.0 5.5 BDL BDL BDL 7.2 2.2 - - All samples are colourles and odourless. Temp.- Temperature, EC- Electrical Conductivity, TDS- Total Dissolved Solids, Tur.- Turbidity. T-Alk- Total Alkalinity, Ca- Har.- Calcium Hardness, Mg-Har. –Magnesium Hardness, T-Har.- Total Hardness , Cl2- Chlorides, SO4- Sulphate, NO3- Nitrate,NH3-N- Ammonical Nitrogen, DO- Dissolved Oxygen, BOD- Biochemical Oxygen Demand, TC- Total Coilforms, FC-Fecal Coliforms, BDL- Below Detectable Limit All parameters are in mg/L. TC and FC are expressed in CFU/100ml.
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Table 4.4: Physico-chemical Characterization of Ground Water and Nallah Samples Sam. pH Temp EC TDS Tur. T- Ca- Mg- T- Cl2 SO4 NO3 NH3-N T-PO4 DO BOD TC FC Code (0C) (μs/cm) Alk. Har. Har. Har. GW1 7.4 11 180.6 108.4 4.0 70.0 80.0 25.0 105.0 12.5 9.8 BDL BDL BDL - - - - GW2 7.4 18 177.0 106.2 1.0 76.0 73.0 12.0 85.0 7.0 15.0 0.5 BDL BDL - - 100 20 GW3 7.4 15 156.0 93.6 3.0 66.0 72.0 11.0 83.0 3.0 13.0 0.5 0.17 BDL - - 6000 2400 N1 6.6 9.0 31.0 18.6 5.0 7.0 6.0 2.0 8.0 1.5 2.5 0.5 0.35 BDL 7.5 2.8 100 15 N2 6.5 9.0 25.7 15.4 5.0 6.0 7.0 1.0 8.0 1.5 BDL 0.3 0.45 BDL 7.2 2.5 300 50 N3 7.0 10.3 47.1 28.3 5.0 14.0 12.0 11.0 23.0 3.5 2.5 0.4 BDL BDL 6.8 1.9 1500 600 N4 7.4 10 63.6 38.2 1.0 19.0 19.0 9.0 28.0 4.5 6.5 BDL BDL BDL 6.8 1.6 6000 4000 N5 6.6 8 23.2 13.9 5.0 6.0 6.0 1.0 7.0 1.5 BDL 0.2 BDL BDL 6.9 2.2 - - All samples are colourles and odourless. Temp.- Temperature, EC- Electrical Conductivity, TDS- Total Dissolved Solids, Tur.- Turbidity. T-Alk- Total Alkalinity, Ca-Har.- Calcium Hardness, Mg-Har. –Magnesium Hardness, T-Har.- Total Hardness , Cl2- Chlorides, SO4- Sulphate, NO3- Nitrate,NH3-N- Ammonical Nitrogen, DO- Dissolved Oxygen, BOD- Biochemical Oxygen Demand, TC- Total Coilforms, FC-Fecal Coliforms, BDL- Below Detectable Limit. All parameters are in mg/L. TC and FC are expressed in CFU/10
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Table 4.5: Trace Metal Analysis of Water samples from Rivers, Springs, Ground Water, Water Supply Schemes and Nallahs Sample Cd Cr Cu Ni Pb Zn code Rivers R1 BDL BDL 0.1 BDL BDL 0.1 R2 BDL BDL 0.1 BDL 0.01 0.6 R3 BDL BDL 0.1 BDL 0.01 1.9 R4 BDL BDL 0.2 BDL 0.01 0.2 R5 BDL BDL 0.1 BDL BDL 0.2 R6 BDL BDL 0.1 BDL BDL 0.2 R7 BDL BDL 0.03 BDL BDL 0.1 R8 BDL BDL 0.04 BDL BDL 0.1 R9 BDL BDL 0.1 BDL BDL 0.1 Springs S1 BDL 0.01 0.3 BDL 0.02 0.3 S2 BDL 0.02 0.1 BDL 0.02 0.2 S3 BDL BDL 0.04 BDL BDL 0.2 S4 BDL BDL 0.1 BDL 0.01 0.6 S5 BDL BDL 0.1 BDL 0.02 0.1 S6 BDL BDL 0.04 BDL BDL 0.1 Ground Water GW1 BDL BDL 0.1 BDL BDL 0.9 GW2 BDL BDL 0.04 BDL BDL 0.3 GW3 BDL BDL 0.1 BDL BDL 2.1 Organized Water Supply WS1 BDL BDL 0.05 BDL BDL 0.1 WS2 BDL BDL 0.04 BDL BDL 0.1 WS3 BDL BDL 0.1 BDL BDL 0.2 WS4 BDL 0.01 0.2 BDL 0.02 0.4 Nallah N1 BDL BDL 0.1 BDL BDL 0.1 N2 BDL BDL 0.1 BDL BDL 5.4 N3 BDL BDL 0.1 BDL BDL 0.3 N4 BDL BDL 0.1 BDL BDL 0.2 N5 BDL BDL 0.1 BDL BDL 0.1 BIS 0.003 0.05 0.05-1.5 0.02 0.01 5-15 10500:2012 All values are in mg/L. BDL: Below Detectable Limit
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Table 4.6: List of Algal Species Found in the Water Bodies of Rohtang Study Bacillariophyceae Cyanophyceae Navicula Oscillatoria Nitzschia Aphnocapsa Diatomella Cholorophyceae Mellosira Spirogyra Meridion Tabellaria Cymbella Gyrosigma
Amphora
Table 4.7: Density and Species Composition of Phytoplankton in Water Samples Collected from Various Sources Location Total Percentage of Different Genera Count/10ml Bacillariophyceae Cyanophyceae Chlorophyceae Spring near Marhi 20 100 -- -- Spring near Gulaba 130 100 -- -- Beas river at Bahang 90 88.9 -- 11.1 Beas river at Shanang 70 85.7 14.3 -- Beas river at D/S 20 100 -- -- of Manali Chandra river at Sissu 10 -- 100 -- Nehru Kund 190 100 -- -- Solang Water Supply 30 100 -- -- Khoksar Water Supply 11 -- 100 -- Palchan Nallah 530 18.9 81.1 -- Solang Nallah 20 -- 100 -- Beas Nallah U/S 01 -- 100 -- Beas Nallah D/S 04 -- 100 --
¾ Organic Constituent: All the water samples had adequate oxygen content. The natural conditions like low temperature and huge turbulence in river flows in the hilly terrain result in high DO values. River water samples collected from urbanized areas like Bahang, Shanang, Manali etc. have BOD values slightly higher than ‘Class C’ drinking water CPCB standard, which can be attributed to domestic waste discharges. This situation indicates that there is significant input of organic waste of human origin. The slower biodegradation rate at low temperature leads to high BOD values.
¾ Microbiological Parameter : The surface water samples having high organic load and all nallah showed presence of large number of Total and fecal coliforms. The possible reason for this is use of waterways for defecation large number of human population due to inadequate sanitation facilities as well as dumping of different kinds of solid wastes. Chandra river water has not shown presence of coliform thereby indicating adequate dilution of insignificant
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domestic releases due to thin resident’s density. The presence of coliform organisms indicates that fecal wastes entering into the river is contaminating the water, which may lead to gastrointestinal diseases, hepatitis or other water born diseases.
¾ Trace Metals: The water samples from all the sources were analyzed for environmental trace metals for which drinking water guidelines are prescribed. The results indicate that the values for Cd, Cr and Ni were below detectable limit. In most of the samples other trace metal concentrations like Cu and Zn were within the acceptable limits. Some of the samples had exceeded the acceptable limit for Cu but well within the permissible limit. All these results indicate that there is no threat from metal contamination. The findings are supportive to fact that there are no industries located in study area and the water sources originated by melting of snow.
¾ Biological Quality: Water samples from various water sources viz. spring, river, nallah, water supply source etc. were analyzed for phytoplankton. The observed data indicates that phytoplanktons are represented mainly by Bacillariophyceae as dominant group with occasional occurrence of Cyanophyceae and cholorophyceae. Total nine species of Baccillariophyceae included Navicula, Nitzschia, Diatomella, Mellosira, Meridion, Tabellaria, Cymbell, Gyrosigma, Amphora. Presence of Baccillariophyceae indicates naturally productive conditions.
Oscillatoria and Aphanocpsa belonging to the class Cyanophyceae were observed with density. The blue-green algae belonging to Cyanophyceae use water as an electron donor and produce oxygen in the presence of light. Spirogyra belonging to the class Chlorophyceae was observed scantily. Spirogyra is a filamentous green alga which is common in freshwater habitats. These organisms are responsible for photosynthesis
Total count varied from nil to 53 per ml. The highest number was observed at Palchan nallah with dominance of cyanophyceae (81%) and diversity index 1.09 indicating nutrient enrichment. Beas River at Shanang and Nehru kund with diversity index value 2.23 and 2.21 respectively, indicate clean water condition with less of nutrients.
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Chapter 5
Impact of Tourism on Solid Waste Management and Sanitation
5.1 Preamble
Himachal Pradesh is blessed with number of tourist places with lofty Himalayas draped with snow, deep valleys, vast woods, chilled rivers, green surroundings, scenic lakes etc, that add to its overall fascination. It is often called “The Valley of Gods”. The Himachal Pradesh government is promoting state tourism which is one of the major financial resources. Better staying facilities for the tourists, organization of adventurous sports activities such as trekking, skiing, ice skating, river rafting, paragliding, etc. are provided by the concerned authorities.
Manali is one of the pleasing hill stations and a hot favorite place for the visitors who have a deep desire in naturally rich scenic beauty. There are various natural and manmade tourist attractions in and around Manali like Vashishth hot Spring, Hadimba Temple, Solang Valley, Gulaba and Rohtang Pass up to Khoksar (Plate 5.1).
Plate 5.1: Tourist Places at Manali Rohtang Pass Manali and surrounding tourist attractions are visited by large number of people. The details of the number of tourists flux visiting Manali to enjoy the natural beauty of Manali and Rohatang Pass is presented in Table 5.1.
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Table 5.1: Tourist Statistics for Manali for the Period 2011 Sr. Month Indian BNS Foreigner BNS No Visitors 1 January 1,19,234 1,70,257 5247 8140 2 February 1,48,530 2,10,471 5367 6741 3 March 2,40,520 3,11,478 7811 8625 4 April 3,80,885 4,71,256 12897 15243 5 May 3,44,810 4,12,534 14828 16247 6 June 3,89,508 3,95,217 14694 16357 7 July 1,80,534 1,93,216 14470 16236 8 August 1,80,412 1,92,569 15361 18451 9 September 1,97,893 2,11,357 17136 16567 10 October 2,71,432 2,97,451 16117 18324 11 November 1,02,579 1,29,874 7844 8367 12 December 1,03,190 1,70,367 6716 7569 Total 26,59,527 31,66,0471,38,488 1,56,867 BNS – Bed Night stay, Source: Green text barrirer, Bahang, SDM office Manali
At tourist places, “Tourism and municipal solid waste (MSW) & sanitation sustainability” need careful investigation, as tourism fluxes could have a strong impact on the implemented waste management systems. Hence a methodical and systematic way of solid waste management and sanitation is essential to protect the environment.
5.2 Geographical Features of the Study Area
Manali, the major hill station is entitled as the Switzerland of India and is the base station where most of the tourists stay and travel towards nearby areas like Solang, Palchan, Kothi, Marhi, and Rohtang pass.
Being the heart of the tourist place, Manali is full of hotels, bars, restaurants, travel agents, guides, & and out door photographers. The statistical data of all these is given below: (This is up to 30th Dec 2011) Hotels: 598 Bars & Restaurants: 56 Travel agents: 578 Guides: 121 Out door Photographers: 328
All the hotels provide 9,058 rooms with a bed capacity of 19, 563. Besides these, there are about 139 home stay arrangements with 356 rooms having 720 bed capacities. The “Atal Bihari Mountaineering Institute at Solang” has hostel facility which accommodates good number of people. The tourists are issued passes for visiting the Kelong-Khoksar route, so the tourist influx can be calculated from the number of tourist passes issued.
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5.3 Wastewater Treatment Plant at Manali
The Wastewater (Domestic Sewage) Treatment Plant (STP) is installed near Manali. Total sewage generated is about 1.82 MLD. About 85% of sewage generated in the town is collected and treated with biological aerobic treatment at this STP. Collection and transportation of sewage take place through 18.82 km sewer lines. This line will be extended to 21.05 km and construction has already been started for the additional 2.23 km sewer lines required. Bigger hotels have their own STP’s while smaller hotels are connected to the common STP’s. Some of the hotels particularly at Solang release the wastewater openly on the land creating unhygienic conditions. Other villages in the study area also do not have organized wastewater collection and treatment systems. The domestic wastewater ultimately joins river Beas through small nallas.
5.4 Solid Waste Management for Manali
The total population of Manali including the floating population is approximately 40,000. Solid waste collection in Manali is well organized. Solid waste management plant started in the year 2003 - 04 at Rangari, about 3.5 km away from Manali town. The plant is installed in collaboration with Indo-Norwegion Company. Solid waste generated by about 60% of total population is collected by door to door campaign supported through Mahila Mandal team members. This practice is also followed in Solang, Marhi and Kothi. There is provision of bins for bio- degradable and non bio-degradable materials for segregation of domestic waste at source. The amount of solid waste collection is about 5-7 tones/day, which rises up to 13-15 tones/day during peak period of tourism (Plate 5.2).
Littering and use of plastics is totally banned in the state. Special Area Development Authority (SADA) is involved in collection of garbage from Rohtang, Solang and Marhi area and the collected garbage is treated at Rangari Solid waste Treatment plant. About 10% of the solid waste is subjected to composting, and the rest is being recycled and dumped at the open landfill sites. The waste collected initially goes for segregation at plant site into two categories viz. biodegradable and non-biodegradable. The non-biodegradable material is further separated into 4 different types: glass, tin, plastics and paper. The glass, tin, papers and plastics are recycled and sold in the market. The segregated biodegradable wastes are dumped into 240 compost pits of 2.75 x1.20 x 1.20 m dimensions each available for pit composting at the treatment plant. Each pit is having the capacity of 1 tone. The plant also has leachate treatment facility.
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Plate 5.2: Solid Waste Management at Manali
Littering in Manali-Rohtang area is being looked after by the chairman Special Area Development Authority (SADA) and SDM Manali. The agreement to manage litter solid waste in the area is through a contractor which has shown better results. Mahila Mandal collects the litters from Solang, Kothi and Marhi area. Jute bags are provided for collection. This project needs to be made more accountable for regular day to day cleaning, collection and safe disposal of solid waste including non-biodegradable material. The solid waste collection in other places like Palchan and Rohtang Pass is not satisfactory.
5.5 Sanitation
Common toilet facilities are provided in some of the villages (Plate 5.3). The picnic spots like Marhi, Solang, Gulaba and Rohtang pass are provided with Portable toilets. The waste disposal system adopted for portable toilets are not available. During the field visit installation of portable toilets at picnic spots was not observed.
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Portable
Community Toilet
Plate 5.3: Common Toilet Facility and Portable Prefabricated Toilets
There are about 18 prefabricated potable toilets but they are not sufficient for the entire tourist population. It is informed that the waste material from these toilets is brought back to Manali by shifting the toilets to Manali city for appropriate treatment at sewage Treatment plant and placing it back at Rohtang pass. However, the modality and actual functioning of this facility with respect to duration of placement, load on each unit, spillage during transportation of the unit if any, for disposal/cleaning /collection of waste etc is not physically observed during the field visit during May 2012 as these units were not placed at Rohtang pass. These mobile toilets are not placed throughout the year. As a result, people are left with no choice but attend the nature calls in the open. This practice is contaminating the water environment. Being a cold place, the biodegradation rate is not fast which takes longer time for stabilization of waste.
Besides these, Animal dung is another type of waste generated and it scatters in the hilly slopes. Generally horses are being used for tourist activities. A 1,000 lb (454 kg) horse can generate 30 lbs (13kg) of dung. More than 1300 kgs of manure is expected to be generated daily by approx 1000 horses. Large numbers of horses are also used to carry tourists in difficult hilly areas. The owners of Plate 5.4: Horses used by Tourist as horses should be instructed to take necessary Source of Animal Dung precautions to collect such waste and help to prevent pollution (Plate 5.4).
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Tourists are not following required practices to keep the places clean which add a negative impact on the environment of this beautiful place (Plate 5.5). While traveling towards Rohtang pass region, large number of tourists throw the plastics/paper tea cups, wrapping papers,
Plate 5.5 : Tourist Throwing Liter Along the Road corn stalk etc indiscriminately here and there. Hotels accommodating large number of tourists also throw the garbage and the liquid waste Plate 5.6: Non Compliance of Waste Management by Hotels from toilets on the open land (Plate 5.6).
The display boards for maintaining the environmental cleanliness are placed on the way along the roads (Plate 5.7). But stipulated rules are not followed. These malpractices should be controlled by Pollution control Board at the earliest. Records of collection of fine should be evaluated to check the implementation of clean eco friendly practices. The campaign for Clean Environment initiated by the school children in Manali town was observed during the field visit. Such activities should be promoted.
Plate 5.7: Promotional Activities for Clean Environment, H.P. Govt.
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However, it was observed that the state has achieved 100% ban on use of plastic bags. No plastic carry bags were noticed in the area and there is a fine of Rs. 1000/- if anyone is found using plastic bags. Paper bags have replaced these plastics bags and are being widely used by everyone, from vendors to local people to tourists. 40 quintals of poly bags used earlier were reused for road construction (Plate 5.8). These were from milk pouches, chips packets, oil packets, mineral water bottles etc.
Plate 5.8 : Food Vendors Adding to Nalla Pollution
For Eco tourism and protection of scenic environment, there is an urgent need for proper integrated method in handling and disposal of solid waste so that the beauty of the place remains undisturbed.
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Chapter 6
Assessment of Soil, Soil Erosion and Conservation Measures for Erosion
6.1 Introduction
The land deterioration due to erosion is a big problem in hilly regions. Erosion is the prime process, which is responsible for the variation in topography. During erosion process, soil and rocks are removed from the Earth's surface by natural processes such as wind or water flow, and then transported and deposited in other locations. Apart from natural causes, it is aggravated due to human interventions through indiscriminate cutting of trees, mining, overburden dumping, etc., thus affecting natural ecosystem. Areas affected by severe soil erosion need immediate attention for soil conservation measures like bunding, contour farming, gully, farm forestry, water harvesting, etc. Splash erosion, sheet erosion, rill erosion, gully erosion, stream channel erosion, tunnel erosion, tillage erosion are some of the classes of erosion.
Factors affecting erosion rates are broadly identified as wind speed and Precipitation, Soil Structure and composition, vegetation cover and topography. Human activities that increase erosion rates are Agricultural practices, Deforestation, Roads, Urbanization and Climate change. • Wind erosion is a major geomorphologic force, especially in arid and semi-arid regions. The rate and magnitude of soil erosion by wind is controlled by the factors like erodability of soil, soil surface roughness, climate, unsheltered distance, vegetation cover, Wind erosion may create adverse operating conditions in the field. Wind erosion is more common in Rajasthan. • As a direct result of rainfall, three primary types of erosion occur as a direct result of rainfall sheet erosion, rill erosion, and gully erosion. • Sheet erosion is the transport of loosened soil particles by surface runoff either of rain water or the melted snow water that is flowing downhill in thin sheets. • Rill erosion refers to the development of small, momentary concentrated flow paths, which function as both sediment source and sediment delivery systems for erosion on hill slopes. • Gully erosion occurs when runoff water accumulates, and then rapidly flows in narrow channels during or immediately after heavy rains or melting snow, removing soil to a considerable depth.
Soil properties influencing erodibility include texture, structure and cohesion. Texture refers to the combination of sizes of the individual soil particles. Three broad size classifications are clay, silt, and sand. Soil having a large amount of silt is most susceptible to erosion from both wind and water. Structure refers to the degree to which soil particles are clumped together, forming larger clumps and pore spaces. Structure influences both the ability of the soil to absorb water and its physical resistance to erosion. Cohesion refers to the binding force between soil particles and
Study of Rohtang Pass | 6.1 influences the structure. When moist, the individual soil particles in a cohesive soil cling together to form a doughy consistency. Clay soils are very cohesive while sandy soils are not.
Vegetation is probably the most important physical factor influencing soil erosion. A good vegetation cover shields the soil from the impact of raindrops, provides organic matter, slows runoff, and filters sediment. It also binds the soil together, making it more resistant to runoff.
Topography: Slope length, steepness and roughness affect erodibility. Generally, the longer the slope, the greater is the potential for erosion. The greatest erosion potential is at the base of the slope, where runoff velocity is greatest and runoff concentrates.
Slope steepness, along with surface roughness, and the amount and intensity of rainfall control the speed at which runoff flows down a slope. The steeper the slope, the faster is the water flow that causes erosion with increased sedimentation.
6.2 Geomorphology of the Study Area
Himachal Pradesh (HP) is a hill state with altitude ranging from 350m above MSL along Punjab plains to 6816 m above MSL in Kinnaur dist. The general landscape presents an intricate mosaic of mountain ranges, hills and valleys. The study region falls in middle and greater Himalaya topographic region which have most of the high altitude conifers, broad leaved forest, alpine meadows, land under horticulture, glaciated landscape, thin vegetation and low human population density.
The soils of HP vary according to aspect, slope and climatic conditions. The soil in study region is characterized as brown hill soils (over sandstones and shales)#, podsolic or sub-montane and the glacial and eternal snow types which are not fully developed as they are found in snow covered areas. The soils are generally thin but deep only in valleys.
Soils of HP are under great stress and strain due to sheet and gully erosion. Sheet and gully erosion caused due to heavy rains is the predominant phenomenon due to which the top layer of a soil over large areas gets washed away. When rainwater flows down the slopes making deep and narrow furrows, Gully erosion occurs. Such gullies make the land unfit for cultivation and result in the formation of badlands. The study region has snow covered areas and snow melts during summer months. The streams or water from melted snow flow along the slope and causes erosion.
# Source: Velayutham & Bhattacharyya, NBSS &LUP, ICAR, Nagpur (2000)
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The hilly terrain with great slopes is another reason for soil erosion. The presence of moderate or steeper slopes (ie. > 5 – 10%), and/ or readily erodible soil profiles are prone to soil erosion. Soils with relatively high silt and fine sand fractions are most susceptible to erosion, while very fine grained, high plasticity clay soils are least susceptible.
6.3 Site Factors for Erosion
The natural soil erosion occurs due to factors like sheet and gully erosion due to rain and snow water flows, moderate to deep slopes and erosion prone soils profiles.
Apart from the natural causes, human interventions like road broadening activities are also causing soil erosion in the study region. Existing Manali to Rohtang road of 51 km is double lane road with the width of 12 m. However, based on the town/village placement, diversion of river Beas and hilly turnings at certain locations, the width is less and ranged from 7 to10 m. This road is used by BRO for supply of material to Leh Ladak which is carried out by big Army vehicles. Large number of private taxies also plies every day to carry tourists to scenic places along the Manali – Rohtang road (Plate 6.1). The current carrying capacity of the road is under stress due to movement of large number of vehicles. Traffic jams have become very common due to multiple factors.
Plate 6.1 : Vehicles Plying on Rohtang Pass
To ease out the load of traffic, Boarder Road Organization (BRO) has undertaken the job of widening the road from Manali to Rohtang - Khoksar which is 71 km long. To undertake the road widening activity, clearance from forest department and other formalities for cutting the mountains have been already completed. The whole project is expected to be completed by 2015.
At the time of visit during April 2012, about 6.5 km road from Manali towards Rohtang is widened. All engineering aspects like construction of retaining wall, provision of outlets for water streams are implemented during widening activity (Plate 6.2).
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Plate 6.2: Road Widening Activities
The incidences of tilting of retaining walls had occurred at few places due to stress resulting in eroding of roads (Plate 6.3). The nature of soil and its characteristics are creating hurdles because the types of soil is such that even the small disturbance like the vibrations of machines, lead to large landslide. Natural land slide and cloud burst is a common phenomenon that hampers the progress of the widening activity.
Plate 6.3: Titling of Retaining Wall and Need for River Diversion for Road Widening
The road widening activity has resulted in landslides and soil is spread on the road thereby blocking the roads for traffic. In order to evaluate the quality of soils and geology which can cause landslides/ soil erosion, the number of soil samples was collected at appropriate locations along Manali – Rohtang pass National highway during April and May 2012 (Plate 6.4). The list of the locations is presented in Table 6.1.
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Plate 6.4 : Collection of Soil Samples
Table 6.1: Details of Soil Sampling Locations Sample Sample Location Latitude (N) Longitude (E) Code S1 Palchan 32°18'32.0” 77°10'40.0” S2 Solang 32°18'44.0" 77°10'40.2" S3 Kothi 31° 8'17.6" 77°29'47.5" S4 Between Marhi and Gulaba 32°20’24.8” 77°13’04.7” S5 Marhi 32°21’06.7” 77°12’ 58.8” S6 B/W Upper Marhi & Radi Nallah 32°21'46.0" 77°14'40.0"
S7 Khoksar/Basi Dang 32°24’33.6” 77°14’05.3” S8 Rohtang Tunnel muck 32°21’21.3” 77°07’42.9”
During May, 2012, the attempt was made to collect the core of soil from the area where the land slide had occurred. A stainless steel pipe of 2 feet length and 4 inch diameter was used to collect a core sample. The samples were collected at Solang, Kothi, Marhi, Radinala and Khoksar. Since these areas are covered with snow in earlier months, the soil at the selected sites was damp and hence the core sample could be collected. Figure 6.5 shows the site view during sample collection.
The soil samples were analyzed for physical and chemical properties. The analytical results for physical and chemical parameters for the soil samples are presented in Tables 6.2 and 6.3 respectively.
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Plate 6.5 : Collection of Core Soil Samples
Table 6.2 : Physical Characterization of Soil Samples Collected Between Manali-Rohtang NH-21 Grain Size Bulk Sample Sample Distribution Colour Texture Density Code Location Sand Silt Clay (g/cc)* (%) (%) (%) S1 Palchan Brownish gray 64.1 33.3 2.6 Sandy loam 1.51 S2 Solang Drak gray 63.1 32.9 4.0 Sandy loam 1.53 S3 Kothi Black 68.4 24.6 7.0 Sandy loam 1.62 S4 Between Brown gray Marhi and 52.1 30.6 17.3 Sandy loam 1.45 Gulaba S5 Marhi Brown gray 45.8 34.2 20.0 Loam 1.42 S6 B/W Upper Dark gray Marhi & 47.3 36.1 16.6 Loam 1.45 Radi Nallah S7 Khoksar/Basi Dark gray 52.3 38.4 9.3 Sandy loam 1.54 Dang S8 Tunnel Gray 85.0 10 5.1 Loamy sand 1.70 * Calculated from texture.
Table 6.3: Chemical Characterization of Soil Samples Collected Between Manali- Rohtang NH-21 Sample Sample Location pH EC OC OM T-N T-P Code (µS/cm) (%) (%) (mg/kg) (mg/kg) S1 Palchan 6.6 277 0.8 1.4 148 13 S2 Solang 6.8 219 0.9 1.6 187 19 S3 Kothi 6.8 221 1.2 2.1 208 27 S4 Between Marhi and 2.4 6.3 356 1.4 367 33 Gulaba S5 Marhi 6.9 171 1.3 2.2 342 30 S6 B/W Upper Marhi & 1.6 6.3 124 0.9 210 18 Radi Nallah S7 Khoksar/Basi Dang 6.6 107 0.8 1.4 176 12 S8 RohtangTunnel 6.2 70 0.2 0.3 104 8
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The core samples were processed for evaluation of mechanical properties like grain size, liquid limit, plastic limit, and plasticity index; sheer test etc so that the reasons for the landslides and soil erosion occurring naturally can be explained scientifically. The detailed methodology adopted for this testing and its significance with soil erosion/ landslides is provided in Annexure 6.1. The test results are presented in Table 6.4.
Table 6.4 : Mechanical Characterization of Soil Samples Collected Between Manali- Rohtang NH-21 Sample Grain Size Analysis Direct I/D Mark Shear Test
) ) 2 % ( (%) NMC (%) Silt (%) Clay (%) Sand (%) Sand Gravel (%) (%) Gravel Angle F (kg/cm Specific Gravity Gravity Specific Cohesion Free Swell Index Plasti-City Index Index Plasti-City Plastic Limit (%) Liquid Limit (%) Liquid Dry Den-Sity (g/cc) Bulk Den-SityBulk (g/cc) Solang 31 54 12 03 NL NP NP 11 1.82 1.64 05 2.64 0.0 24 Kothi 19 44 32 05 NL NP NP 12 1.84 1.64 06 2.64 0.0 22 Marhi 48 39 11 02 NL NP NP 11 1.82 1.64 04 2.64 0.0 26 Radinala 36 50 11 03 NL NP NP 09 1.80 1.65 04 2.64 0.0 25 Khoksar 34 50 14 02 NL NP NP 10 1.91 1.74 04 2.64 0.0 24 NMC: Natural moisture content
6.4 Results and Discussions
The soil samples have been collected from eight locations on Manali – Rohtang – Khoksar National Highway NH-21. The observations of soil characteristics are as under;
Textures: Soil texture is one of the most important physical properties of soil. It refers to the basic composition of the soil, which consists of sand, silt and clay contents. The soil texture directly or indirectly affects almost every single characteristic of the soil. It also enables to measure the possibility of risks, such as erosion, and it helps to select adequate crops for production.
The texture of soil sample collected at locations S-1 to S-4 and S-7 are sandy-loam. Loamy texture is observed for samples at S-5 and S-6. The texture of Muck from Rohtang tunnel (S-8) which consists of broken rocks is sandier and falls under the class Loamy sand.
Colour: Color indicates chemical, biological and physical transformations and translocations that have occurred within a soil. Soil organic matter causes a dark brown to black color in the soil. A bright and light color can be related to an alluvial horizon, where carbonates and clay minerals have been leached out. Black colour of the soil indicates that they are very hard when it is dry, slowly permeable for water and roots. The grey coloured soil is poorly drained having low permeability, which causes anaerobic conditions in the soil. Such soil is frequently waterlogged.
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The soil samples were brown gray, dark gray and black in colour, whereas sample from Tunnel is gray in colour.
Bulk density: If the bulk density is less or near to 1.0 it means, that the soil density is low and it should have high organic matter content. Dark color of the soil may confirm this fact. If the value is higher than 2.0, we consider the soil a very dense soil. The reason can be various, but usually we can find the cause in compaction of the soil and low organic matter content. Sandy textured soils have higher bulk density than clayey soils.
The values for loam type soils are generally between 1.2 and 1.6 and clayey soils have a bulk density less 1.2. The bulk density of all soil samples was in the range of 1.42 to 1.62 g/cc and that for tunnel muck was 1.7 g/cc. The observation from bulk density confirms the texture reported.
Soils which show massive structures and less porosity will show bulk densities ranging from 1.6 to 1.7g/cc, water movement will be hindered at this point down the profile. Sample from tunnel has been originated by boring of hard rock of mountains.
6.5 Chemical Properties
Soil tests for chemical properties are conducted to evaluate soil fertility at a specific time. Nutrient content continuously varies with time. Therefore, soil tests should be made on a regular basis. The measurement of nutrients creates a focus on the nutrient content available for plant growth.
The observations on physico-chemical characteristics of the soils are presented below:
• pH: Based on the pH, the soils are classified in different categories. Nutrients availability is controlled by pH. The soil samples have pH values in the range between 6.2 & 6.9 indicating slightly acidic to near neutral nature. The pH observed is mostly suitable for agriculture and cultivation of crops. • Conductivity: The collected soil samples have conductivity in the range between 107 µmhos/cm and 356 µmhos/cm .However, conductivity of muck sample from tunnel was 70 µmhos/cm indicating low dissolved constituents.. • Organic Matter: Soil Samples collected from study area have Organic Matter between 1.4 and 2.4 % range. Whereas muck sample collected from tunnel has very low organic matter (0.3%). The values for soil represent the soil condition rich in organic matter. Soil organic matter content in most common mineral based soils ranges from 1% to 6%. Sandy textured soils are usually the lowest and soils dominated by clay the highest*.
______* The Nature and Nurturing of Soil Organic Matter, (http://209.213.232.153/TR/articles/Organic_matter.pdf)
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• Total Nitrogen: Soil samples collected show concentration of total Nitrogen as its values has ranged between 148.0 to 367 mg/kg indicates low concentration of nitrogen. The muck from tunnel has very low nitrogen content (104 mg/kg). • Total Phosphorus: Phosphorus has low mobility in the soil. Its availability decreases in wet and cold soils. The samples have medium to low concentrations of total phosphorous as its values are ranged between 12.0 to 33 mg/kg. Muck sample from tunnel is deficient in Total phosphorus (8.0 mg/kg).
Podozolic and sub-montane soils which are generally found in hilly regions of Himachal Pradesh are usually deficient in nitrogen, phosphorus and humus. Overall physico – chemical quality of soil tested confirms characteristic of normal hilly soil with slightly low nutrients and organic matter.
The mechanical properties of soil samples collected from study area have indicated low clay content and absence of Atterberg's Limits like liquid limit, plastic limit and plasticity index which support more soil erosion. Cohesion i.e binding capacity of soil is good when clay content and plasticity index is more. The natural moisture content is also low. The cohesion values are 0. All these observations indicate that the binding capacity of soil is poor which will tend to soil erosion and landslides even with minor impacts of vibration due to manmade activities like building, road construction and even the consistent heavy load of traffic.
The study conducted by Vishwa B.S. Chandel et al., 2011 (Annexure 6.2) for Kullu district has stated the following:
The susceptibility to landslides is inherent in the natural characteristics of the landscape and there is a definite relationship between landslide occurrence and geo-physical setup of the area. The high slope angles, drainage density, high local relief and geological structure produce suitable conditions for landslide occurrence; the torrential rainfall in monsoon season is invariably the immediate trigger. In Kullu district, out of total of 49 landslides during 1971-2009, nearly 63.27 per cent occurred in monsoons; 26.53 per cent were recorded during winter months (January- March) while pre and post monsoon seasons together recorded less than 10 per cent landslides.
In addition, the past events show that these have close association with the land use and were confined to the built-up (roads) and agricultural lands. The intensification of human activities, encroachment on vulnerable land, uncontrolled settlement and rampant expansion of roads adds to landslide vulnerability. It is pertinent to note that landslide activity is largely confined to the inhabited part of the district primarily in the vicinity of the rivers and roads and this is substantiated by field visits and data. These are the prime locations of all human activities and this enhances the risk potential of this disaster.
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The landslide probability values obtained through satellite imageries of LANDSAT ETM+, IRS P6, ASTER along with Survey of India (SOI) topographical sheets formed the basis for deriving baseline information on various parameters like slope, aspect, relative relief, drainage density, geology/lithology and land use/land cover, were classified into no risk, very low to moderate, high, and very high to severe landslide hazard risk zones. The results show that over 80 per cent area is liable to high severe landslide risk and within this about 32 per cent has very high to severe risk.
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Chapter 7
Biological Environment 7.1 Introduction
Biodiversity refers to the variety and variability of all life forms in the planet. In practice, it refers to all living beings present in the ecosystems. In view of the need for conservation of environmental quality and biodiversity, including current international focus on the global crisis in biodiversity, the present study at Rohtang Pass region, a tourist hub, envisages to meet following objectives. • Delineation of biodiversity in the study area of Rohtang Pass • Assessment of impact of tourism on flora and fauna of the study region • Mitigate measures to conserve and preserve the biodiversity
The demarcated area from Manali to Khoksar on Manali-Leh National Highway in Figure 1.1 is studies for biological environment.
7.2 Methodology
1. (A) Assessment of Flora at Select Locations in the Study Area
Considering the accessibility and approachability, the assessment of flora was carried out in the study area at select locations (Table 7.1) which falls in Kullu Forest Division and Lahaul Forest Division comprising Manali and Keylong Forest ranges, respectively.
Table 7.1 : Select Locations for Biodiversity Studies During May, 2012 Forest Division Study Name of Forest Latitude (N) Longitude (E) & Range Locations Manali Forest Solang Valley Kangni forest 32°17'16.6" 77°08'26.4" Range, Kullu (2/1 Kangni C.IIb) Forest Division Tungu (Kothi) Kothi-Tich forest 32°18'32.0" 77°10'40.0" (2/11 Kothi-Tich C.Ia) Gulaba Kothi-Tich forest 32°19'25.0" 77°12'21.0" (2/11 Kothi-Tich C.Ib) Marhi Undemarcated forest 32°20′56.0" 77°13′04.0" Keylong forest Khoksar range, Lahaul 32°24’33.6" 77°14’05.3" Forest Division
Flora was assessed for density, diversity, species composition & Importance Value Index (IVI) using plotless (or Point-Quarter) sampling method following Rau and Wooten, 1980. Sampling locations were randomly selected on the slopes, along and off the roads. In this method, vegetation measurements are determined from points. A number of randomly determined points/plots were sampled. Each point represents the centre of the measurement area and is divided into
Study of Rohtang Pass | 7.1 four 90° quadrants. In each of the quadrants studied measurements, using a measuring tape, were done to collect data on the distance to the closest plant from the centre point, tree girth- perimeter, and tree height, canopy cover of trees and identification of the trees/plants available in the study area (Plate 7.1). The following parameters were calculated from the field observation data. IVI was calculated using following formulae :
Importance value = (relative density + relative dominance + relative frequency) / 3
The density measurements may over emphasize the importance of a species that consist of many small individuals; the dominance measurements over emphasize about a species that consists of few, very large individuals; and the frequency measurements may over emphasize the importance of distribution of individuals belonging to a particular species in the vegetation sampled, regardless of the size or number of those individuals. Therefore, importance value index is a reasonable measure to assess the overall significance of species since it takes into account several properties of species in the vegetation.
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Plate 7.1: Study of Forests by Plotless Sampling Method Forest type is defined as a unit of vegetation which possesses similar characteristics of physiognomy, structure, function, floristic composition and phenology influenced by climate and topography. The forest types in this region were broadly categorized into Himalayan Moist Temperate forests and Sub-Alpine and Alpine forests. Himalayan Moist Temperate forests are distributed in temperate zone (from 2000m to 3000m) which were mostly dominated by conifers and mainly comprised of Cedrus deodara (Deodar), Abies pindrow (Fir/Tosh), Picea smithiana (Spruce/Rai), Acer caesium (Maple), Betula utilis (White trunk Birch/ Bhojpatra), Aesculus indica (Horse chestnut/Khanor), Populus ciliata (Poplar) and Juglans regia (Walnut/Akhrot). Majority of the forest blocks at lower reaches comprised of Abies pindrow (Fir), Picea smithiana (Spruce) and Cedrus deodara (Deodar); however, at higher reaches, vegetation was dominated by Acer caesium (Maples) (Table 7.2 A).
The Sub-Alpine and Alpine forests are distributed in alpine zone (above 3000m), from Marhi to Khoksar in the study area and are ecologically very important as it is in these areas that the rivers originate from the glaciers. Vegetation is mostly herbs and shrubs with occasional trees of the temperate zone. The zone is rich in medicinal plants (Table 7.2 B) and is at threats due to overgrazing and unscientific and rampant extraction of medicinal plants.
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Table 7.2 A : Flora of Rohtang Pass Region in Manali Forest Range Kullu District Plants Botanical Plants Common Name Forests Vegetation Name Tungu Gulaba Solang Salix elegans Willow/Beuns + + + Acer calsium Maple + +++ ‒ Abies pindrow Tosh +++ + + Picea smithiana Rai ++ + + Pinus wallichiana Kail + ‒ + Poplas ciliata Poplar + ‒ + Pinus padus Birdcherry/ Jamu + ‒ ‒ Betula utilis Bhojpatra /White trunk Birch ‒ + ‒ Quercus Kharsu / ‒ ‒ ++ semecarpifolia Brown oak Juglans regia Walnut/ Akhrot + ‒ + Cedrus deodara Deodar + ‒ + Alnus nitida Kosh ‒ ‒ + Fraxinus floribunda Ash/ Angu ‒ + ‒ Rhodendron arboreum Baras Present where the tree line ends Robinia pseudoacacia Black locust/ Pseudocasia ‒ ‒ ++ Taxus baccata Yew/ Barmi/ Rakhal ‒ + + Berberis aristata Kasmal ‒ ‒ + Indigofera gerardiana Kathi ‒ + + + Present; - Absent; ++ Subdominant; +++ Dominant Source: primary data collected by Scientists CSIR NEERI, Nagpur
Table 7.2 B : Flora of Rohtang Pass Region, with Medicinal Value, in Manali Forest Range, Kullu District & Khoksar Region of Lahul District Botanical Name Common Name Uses Manali Aconitum heterophylum Padish Root has medicinal value, extract used against fever Girardinia heterophylum Bichubuti Root extract is used as anti-coagulant against intrinsic blood clotting, extract used against fever Gentiana kurroo Karu Root is used against fever, stomach ache Thymus serpyllum Ban ajwayan Leaves used against gastric troubles Khoksar Betula utilis Bhig Outer bark is locally used for roofing Hippophae rhamnoides Chug Medicinally used in lung complaint Salix elegans Bes Used for making sports goods and wicker baskets Juniperus communis Bithal • Juniper fruits are commonly used in herbal medicine, as a household remedy, and also in some commercial preparations. • Especially useful in the treatment of digestive disorders plus kidney and bladder problems. • Fully ripe fruits are strongly antiseptic, aromatic, carminative, diaphoretic, strongly diuretic, rubefacient, stomachic and tonic Source: Working plan, Kullu Forest Division (Manali Forest Range), Lahaul Forest Division (Keylong forest range)
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Solang valley is one of the attractive tourist sites in Kangni forest which covers an area of 61.78 ha and is located at an altitude of 2438-3048 metres. Solang valley is heavily populated with tourists due to sport activities like mountain biking, para gliding etc. In this region, forest vegetation mainly comprised of 8 tree species, Cedrus deodara being the dominant genera (Plate 7.2 A) followed by Aesculus indica and Picea smithiana. Occurrence of broad leaved genera like Aesculus indica (Khanor), Juglans regia (Walnut), Poplas ciliata (Poplar) and Prunus padus (Birdcherry) were also found as mixed vegetation. The importance value index varied between 28.39 to 3.81 highest being for Picea smithiana ( Rai ) and lowest for Salix elegans (wild willow) (Table 7.3 A). The deodar is used for timber and hence is a commercially valuable tree species.
In Kothi-Tich forest, Tungu region covers an area of 212.12 ha and it is located at an altitude of 2560-2650 metres. A mixed plantation of Abies pindrow (Tosh), Picea smithiana (Rai) with some Pinus wallichiana (Kail) and sprinkling of Cedrus deodara (deodar) occurs in this region. The plantation of Tosh was carried out in 1962, as confirmed by forest officials, which resulted as the dominant genera, acquired upto 50m height, of the existing vegetation in this region. A few trees of Acer caesium (Maple), Poplas ciliata (Poplar), Salix elegans (Wild willow) and Prunus padus (Birdcherry) were also found scattered along the roadside plantation. While 150-200 yrs old Abies pindrow (Tosh) trees were recorded, new plantation comprised Abies pindrow, Pinus wallichiana and Picea smithiana.. Along the roads, Tosh and Rai plantations (Plate 7.2 B & C) were dominant in this area with importance value index varying between 54.56 to 4.06 for Tosh and Kail respectively (Table 7.3 B). However, the timber yielding Tosh plant is expected at the age of 150 years of a tree, it is one of the commercially important species of this region. Medicinal herbs like Girardinia heterophylum (Bichubuti) and Thymus serpyllum (Ban ajwayan) were also recorded in this region.
The study area also comprise of Patalsu Reserve forest which covers an area of 54.63ha and occurs at an elevation of 2865 to 3322 mts. The region was not accessible and hence, no biological assessment was carried out in this forest area.
At Gulaba, forest area is spread over an area of 152.10 ha and this site is located at an altitude of 2650-2743 metres. Maple (Acer caesium) was recorded as dominant trees (Plate 7.2 D) among Betula utilis (Bhojpatra), Picea smithiana (Rai), Quercus semecarpifolia (Kharsu), Salix elegans (Wild willow) and Abies pindrow (Tosh). Tree line ends at Gulaba near Rahala Fall region. The importance value index ranged from 50.61 for Maple trees to 7.29 for Tosh (Table 7.3 C). Higher up above tree line there lies an extensive pasture interspersed with thaches and rocky outgrowth.
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A] Cedrus deodara dominant at B] Abies pindrow dominant Solang Valley at Tungu
C] Picea smithiana dominant D] Acer caesium dominant at Tungu at Gulaba
E] No Vegetation at Marhi F] Grassland and Snow Covered Area at Khoksar in Lahaul Plate 7.2 : Vegetation at Different Altitude in the Study Area
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Table 7.3 A : Density, Frequency and Dominance and IVI of Trees in Solang Valley Name of Average Relative Relative Relative IVI Ranking Trees Height (m) Density Frequency Dominance Rai 58 20.83 21.43 42.91 28.39 1 Khanor 47 16.67 14.29 37.73 22.89 2 Deodar 11 29.17 21.43 1.96 17.52 3 Walnut 36 12.5 14.29 8.84 11.88 4 Poplar 26 8.33 7.14 2.26 5.91 5 Tosh 45 4.17 7.14 6.01 5.77 6 Birdcherry 6 4.17 7.14 0.16 3.82 7 Wild Willow 4 4.17 7.14 0.13 3.81 8
Table 7.3 B : Density, Frequency and Dominance and IVI of Trees in Kothi (Tungu) Forest Area Name of Average Relative Relative Relative IVI Ranking Trees Height (m) Density Frequency Dominance Tosh 11.00 65.62 50 48.08 54.56 1 Rai 28.75 24.99 28.57 29.77 27.77 2 Maple 10 3.12 7.14 14.12 8.12 3 Wild Willow 8 3.12 7.14 6.87 5.71 4 Kail 15 3.12 7.14 1.91 4.06 5
Table 7.3 C : Density, Frequency and Dominance and IVI of Trees in Gulaba (Rahla Fall) Forest Area Name of Average Relative Relative Relative IVI Ranking Trees Height (m) Density Frequency Dominance Maple 6.75 50 36.36 65.46 50.61 1 Rai 5.75 25 27.27 19.73 24 2 Kharsu 4 6.25 18.18 4.55 9.66 3 Wild Willow 8 12.5 9.09 3.67 8.42 4 Tosh 12.9 6.25 9.09 6.53 7.29 5
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Beyond Gulaba, Marhi is an alpine area with no tree-line (Plate 7.2 E) and it is categorised as undemarcated forest area. The place remains a stopover for transit visitors and tourists during summer and autumn seasons. This region was mostly snow covered and there was no vegetation recorded during study period. This area is surrounded by lush green meadows during june- august.
At Khoksar in Lahaul forest division, most of the part was snow-covered (Plate 7.2 F). During the study period, vegetation was mostly herbs and shrubs with small patch of dried Betula utilis (Bhojpatra). This tree has white paper-like bark which was used in ancient times for writing Sanskrit scriptures, sacred mantras and texts. The Khoksar zone is rich in medicinal plants (Table 7.1 B and Annexure 7.1). Flora comprising of Hippophae rhamnoide , Juniperus communis, Aconitum heterophylum, Artemisia maritime, Morchella esculenta, Picrorhiza kurroa, Thymus serphyllum, Jurinea macrocephala, Aconitum violaceum, Podophyllum emodi, Saussurea lappa, Carum carvi, Crocus sativus, Jurinea dolomiaea, Nardostachys jatamansi, Rosa damascene, Thymus linearis, Viola odorata.
During the survey, 20 tree species and 19 herb species were recorded in the study area out of which Cedrus deodara , Abies pindrow , Picea smithiana, Aesculus indica and Acer caesium were found to be dominant (Plate 7.3). Most of herb species are medicinal plants found in Khoksar.
Cedrus deodara (Deodar) Pinus wallichiana (Kail) Plate 7.3 : Dominant Flora in Study Area
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Abies pindrow (Tosh) Picea smithiana (Rai)
Acer caesium (Maple) Populas ciliata (Popular)
Prunus padus (Birdcherry) Aesculus indica (Khanor) Plate 7.3 (Contd..) : Dominant Flora in Study Area Study of Rohtang Pass | 7.9
Betula utilis (Bhojpatra) Salix elegans (Wild Willow)
Plate 7.3 (Contd..) : Dominant Flora in Study Area
1. (B) Assessment of Fauna at Select Locations in the Study Area
The fauna of the study area include mammals and avifauna & fisheries. The data with reference to communities of animals and birds in study area were collected from concerned wildlife departments including information from local people.
Wildlife : The study area was rich in a variety of wildlife due to its deep compact forest cover, prolific growth of fodder species and presence of predator and prey animals. The varied terrain, dense, compact contiguous forests of different types had contributed to the richness of wildlife and still the environment continues to be conducive though there is continuous pressure on the wildlife habitats by human interference, especially tourism. Due to rapid growth of population and better road links facilitated the communication to deep forest responsible for the slow and steady degradation of fauna. The fauna of study area included Capra sibirica (Ibex), Fes uncia (Snow leopard), Moschus moschiferus (Musk deer), Ursus torquatus (Black bear), Canis lupas (Wolves), Vulpes vulpes (Red Indian Fox), Ursus arctos (Brown bear), Canis aureus indicus (Himalayan Jackal), Martes flavigula (Yellow throated Mantin) in the forests of Kothitich, Kangni and Lahaul- Spiti Valley.
Avifauna : Avifauna is an important part of the ecosystem playing the various roles as scavengers, pollinators, predators of insect pest etc. They are also the bio-indicators of different status of environment like urbanization, industrialization and human disturbance. They are one of the best indicators of ecosystem. The areas having good bird diversity signifies healthy forest. They can be sensitive indicators of pollution problems and function as early warning system. Information
Study of Rohtang Pass | 7.10 regarding birds in study area was collected from officials of concerned Wildlife Departments and enquiry from local people. Wide varieties of birds are found in Manali forest range including Lophophorus impejanus (Monal), Tetraogallus himalayensis (Snow cock), Chukar pectoris (Chukar), Pucrasia macrolopha (Koklass pheasant), Garrulax lineatus (Streaked laughing thrush), Myophonus caeruleus (Blue whistling thrush), Urocissa flavirostris (Yellow billed blue magpie), Megalaema virens (Himalayan hill Barbet), Saxicola ferreus (Bush chats), Columbia leuconota (Snow Pigeon), Tragopan melanocephalus (Western horned tragopan), Gallus gallus (Red jungle fowl), Syrmaticus humiae (Cher pheasant), Pavo cristatus (Pea fowl) , Lophura leucomelanos (Khaleej), Columba livia (Blue rock pigeon), Motacilla alba (Wagtail), Anthus roseatus (Himalayan pipit), Carpodacus nipalensis (Spectacle rosefinch), Aquila chrysaetos (Golden Eagle), Gyps himalayensis (Himalayan griffon vulture), Terpsiphone paradisi (Paradise fly catcher), Melanerpes superciliaris (Woodpecker), Phoenicurus ochruros (Black redstart), Chaimarrornis leucocephalus (White capped redstart), Gennaeus albicristatus (Kalij), Falio peregrinus (Sahin falcon), Venellus indicus (Red wattled lapwing), Megalaima ascatica (Blue throated barbet), Bubo bubo (Indian great horn owl), Apus melba (Alpine swift), Dendrocitta vagabunda (Treepie), Acridotheres tristis (Indian myna), Parus major (Gray tit), Pericrocotus cinnamomeus (Small minivet), Buchanga atra (Black drongo), Gypaepus barbatus (Lammergeyer), Pericrocotus speciosus (Indian scarlet minivet), Tinnunculus alaudarius (Kestrel) and Graculus eremite (Red-billed Chough).
In Lahaul region, Alectoris chukar (Chukar), Tetraogallus himalayensis (Himalayan Snowcock), Columbia leuconota (Snow Pigeon), Pyrrhocorax graculus (Yellow-Billed Chough) and Corvus macrorhynchos (Jungle Crow) are the main avifaunal species found.
Fisheries Activities : Beas and Chenab are the two major rivers flowing through the selected study area. Information pertaining to fisheries activities was collected Trout Farm, Himachal Pradesh Fisheries Dept., Patlikuhal, Dist. Kullu. There are three main components of fisheries in this area as follows:
Game Fisheries : In the study area, from Manali to Beas nala, game fisheries is common recreational activity. Trouts (Rainbow and Brown trout) and Schizothorex sp. (Indigenous species) are the major varieties of fishes found in this region. Fish angling is the popular activity among the aqua-tourists. More than 500 anglers visit Kullu for angling competition. H.P. Fisheries dept. and Tourism dept. has authority to issue licence to anglers to carry out angling at very meager rate of Rs.100 per day. Beas River and its tributaries are used for angling. Clear water is needed for the game. Depending upon the climate and water turbidity, these activities are carried out.
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Culture Fisheries : Trout is an exotic species which is cultured in this region. Rainbow trout is cultured by private fish farmers in Nehru Kund at Bhang and also Trout Farm, Himachal Pradesh Fisheries Dept., Patlikuhal (Plate 7.4). At Trout Farm, Patlikuhal, trout ova are reared and bred successfully and the technology is transferred to the general masses of the state. There is a Trout growers’ association which look into the interests of trout growers.
Capture Fisheries : Capture fisheries is prohibited as there are cold water streams and the fishes are left for sport fisheries to attract aqua- tourism.
Rearing Ponds Harvest of Mature Fishes
Rearing of Fingerlings in Tanks
Plate 7.4 : Fish Culture Activities at Trout Farm, Patlikuhal
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2. Impact of Tourism on Biotic Component in the Study Area
Tourism and the environment have a very complex and interdependent relationship. Today, tourism is one of the largest industries, which contributes to world economy and is a great source of foreign exchange for many developing countries, whose major assets are their natural resources. Rohtang, being a popular tourist destination has an influx of approximately 18,000-20,000 tourists and vehicles going to the top of the mountain every day during summer from May to September.
Anthropogenic activities have left a strong impact on the flora and fauna of Rohtang pass. It was reported by forest officials that when new saplings were planted along the road, they did not survive due to heavy tourist activities which resulted in uprooting of the saplings. For example, at Tungu (Kothi), the plantation in the vicinity of road side could not attain the forest structure as compared to that away from the road side due to heavy access of tourists to this site leading to trampling and plucking of new samplings of the plantation and also due to heavy grazing (Plate 7.5 A). Moreover, vehicular pollution leading to gaseous emissions is also harmful to plants (Plate 7.5 B). Tourist activities like trekking and mountain biking (Plate 7.5 C) on the slopes has caused destruction of old as well as new plantations. Increased use of horses and sledges has caused loosening of the soil. Tourist influx has correspondingly resulted in new infrastructure in the form of road construction. Road construction activities have had a disastrous effect on the natural habitats of flora and fauna. They have caused heavy soil erosion and destruction of forest cover (Plate 7.5 D). Incidence of solid waste disposal including polythene and plastics has increased due to influx of tourists and has ruined the aesthetic value of the region (Plate 7.5 E).
Fauna is in this region is also greatly affected by anthropogenic activities, as tourists cause disturbance and destruction of their natural habitat. Incidences of hunting and poaching have also increased. Infrastructural development has destroyed vast amount of forest cover which makes the fauna in this region vulnerable. Fish angling is a popular game activity which is a costly affair and is one of the main source of revenue generation in this region. Lots of anglers come for sport fisheries which also generates employment to guides, hoteliers, drivers etc. But on other hand, such activities disturb the fish migration for spawning and also cause habitat destruction. Activities like garbage disposal in water streams also affects the water flow regime and in turn the riverine fisheries.
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A] No regeneration of new plantation along B] Tourist activities and Vehicular the roads due to uprooting by tourists Pollution near Plantation
C] Trampling of New Plantation D] Soil Erosion Due to Mountain Biking
E] Plastic and Garbage Disposal
Plate 7.5 : Impact of Tourism on Biotic Component of Study Area
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Chapter 8
Assessment of Impacts of Vehicular Pollution on Glacial Environment
8.1 Preamble
Rohtang Pass located at an altitude of more than 13,000 feet in the Pir Panjal range is the main tourist attraction. The place is visited by thousands of tourists. Petrol and diesel driven vehicles are used as a mode of transport. Due to cold weather and walls of snow along the road, the pollutants released through the exhaust get adhered to the glaciers and remain there till melting of snow starts. These pollutants absorb heat and enhance the melting of glaciers thereby disturbing the ecosystem. The water formed due to melting of ice gets contaminated by the vehicular pollution and adds contaminants such as PAHs, having distinct markers to the receiving water bodies.
Aerosols released by the vehicles are suspended particulates and have adverse effects on climate and health. Carbonaceous fraction of aerosols is further classified into two sub categories viz. Elemental carbon (EC) and Organic carbon (OC). EC is optically absorptive and OC is the non- absorptive fraction of the carbonaceous aerosol. Elemental carbon has primary source of emissions from industrial processes, vehicles. Wood burning is the single major source of non-fossil EC. EC is often used as a tracer for diesel exhaust particles (Götschi et al., 2002). OC can be emitted from above emission sources and generated from chemical reactions among primary gaseous organic carbon species in the atmosphere (Kim et al., 2000). Primary Organic carbon is emitted directly from combustion of fossil fuels, biomass burning, vegetative detritus and meat cooking. Secondary Organic aerosols are formed from the oxidation products of volatile organic compound (VOC) gases (Seinfeld and Pandis, 1998). Volatile organic compounds are usually oxidized to OH, O3 or
NO3, and once oxidized their products accumulate and can form aerosols by condensing on already available particles (Bowman et al., 1997).
Black Carbon (BC) is emitted in the atmosphere due to incomplete combustion of fossil fuels, biofuel, and biomass. It consists of elemental carbon in several forms. The largest sources of black carbon are Asia, Latin America, and Africa. Some estimates put that China and India together account for 25-35% of global black carbon emissions. On a global basis, approximately 20% of black carbon is emitted from burning biofuels, 40% from fossil fuels, and 40% from open biomass burning (Ramanathan and Carmichael, 2008).
In the Himalayas, the glaciers cover approximately 33, 000 sq. km. area and this is one of the largest concentrations of glacier-stored water outside the Polar Regions. Elemental carbon or black carbon is chemically non reactive and therefore when deposited into the snow pack, it remains
Study of Rohtang Pass | 8.1 unchanged with no conversion into other chemical species. When black carbon is deposited on ice and snow, it absorbs sunlight, raises the surface temperature and causes the snow to melt. The water from these glaciers forms an important source of run-off into the North Indian rivers during the critical summer months. It was found that a concentration of 15 μg kg−1 of BC in snow may reduce the snow albedo by ∼1% (Warren and Wiscombe, 1980 Cited from Ming et al., 2009). Black Carbon (BC) has emerged as a major contributor to climate change, possibly second to carbon dioxide (CO2) as the main driver of change (Ramanathan and Carmichael, 2008). Increase in melting of Glaciers is one of indicators of climate change. Glacier retreat provides a clear indication of warming phenomenon since the Little Ice Age (LIA), which occurred from approximately 1650 to 1850 (Oerlemans, 2005).
8.2 Selection of Sampling Locations at Rohtang Pass
Rohtang Pass remains snowbound in winters for nearly six months, cutting off the tribal Lahaul- Spiti Valley in Himachal as well as the strategically vital Ladakh region of Jammu and Kashmir. The terrain and climate of the area pose serious problems in maintaining road communication for more than four months at a stretch. The area faces heavy snowfall, high-velocity winds and sub- zero temperatures. The snow melts during summer season and fresh snow layer gets deposited every year during winter season.
Tourism in Himachal Pradesh is one of the most important sectors for the state’s economy. Large number of tourist’s inflow leads to extremely high influx of vehicles. Being the hilly region, the approachability to this place through rail and air is restricted. The two wheelers and cars comprise 82% of the total vehicle population whereas the commercial vehicles account for only 18% of the total vehicular population. This composition of vehicular population coupled with high growth rates of personal vehicles has caused serious problem of traffic congestion, accidents and pollution. (http://moef.nic.in/soer/state/SoER%20Himachal%20Pradesh.pdf). The tourist influx during January to December 2011 recorded at Manali is presented in Figure 8.1. The maximum visitors were recorded during April to June followed by decline in July to September probable due to rains. Rise in tourist has noticed during October just prior to start of snowfall (November to March). Plate 8.1 depicts typical traffic congestion scenario caused by increasing rate of vehicular population. The vehicular movement during snowfall season is seen in Plate 8.2.
Study of Rohtang Pass | 8.2
Figure 8.1: Tourist Influx at Manali During 2011
Correlation of Tourist Influx vis-vis Vehicles Plying on Rohtang Pass
Large number of tourists is visiting Manali and Rohtang area. The maximum number of tourist (both Indian and Foreigners) recorded during June 2011 was 4, 15, 000. Based on assumptions of number of tourist and type of vehicle, the total numbers of vehicles per day are calculated. Considering that four persons are traveling in a single vehicle and it is a car, then about 3458 vehicles will ply every day. The number of vehicles will get reduced to 1730 for eight sitter passenger cars and merely 700 for twenty sitter bus. The expected particulate matter load due to various types of vehicles with highest tourist influx of 4,15,000 is given in Table 8.1.
Table 8.1: Prediction of Particular Matter Emissions (Kg/day) from Vehicles Road Cars 8 20 Length 100% 100% 60%+40% 50%+50% 40%+60% Sitter Sitter (Km) D P (D+P) (D+P) (D+P) Vehicles Vehicles 20 4.15 0.28 2.60 2.21 1.83 3.46 6.65 40 8.30 0.55 5.20 4.43 3.65 6.92 13.3 60 12.45 0.83 7.80 6.64 5.48 10.38 19.95 80 16.60 1.11 10.40 8.85 7.30 13.84 26.6 100 20.75 1.38 13.00 11.07 9.13 17.3 33.25 D: Diesel, P: Petrol, Emission factor (g/km) considered for diesel driven car 0.06, Petrol driven car 0.004, 8 sitter vehicles 0.1 and 20 sitter vehicles 0.475 Ref: Air Quality Monitoring Project-Indian Clean Air Programme (ICAP), The Automotive Research Association of India, March 2008
If the diesel driven cars are only used as tourist vehicles, the emissions of particulate matter (PM) will be higher as compared to diesel driven eight sitter vehicles. The concentration of black carbon is also likely to be increased in proportion to concentration of PM. Using eight sitter vehicles will not only reduce the PM emissions by around 17 % but will also result in less traffic congestion due to decreased number of vehicles plying on the road. Though number of vehicles on road will be reduced by using 20 sitters the PM emissions will be higher due to higher emission factors. Moreover the nature of NH 21 which passes through hilly terrain from Manali to Rohtang with slopes and turnings it will be difficult to use 20 sitter buses which required more space.
Study of Rohtang Pass | 8.3
Plate 8.1: Traffic Congestion at Beas Nalla Near Marhi
Plate 8.2: Vehicular Movement at Snow Covered Rohtang Pass
To realize the impact of vehicular emissions on glaciers, snow samples were collected at different locations. Table 8.2 gives the details about the sampling locations.
Table 8.2: Sampling Locations for Collection of Snow Samples Sampling Location Latitude Longitude Blank (5m right side away from the 32º23’05.40” N 77º14’51.52” E road at Top of Rohtang) Top of Rohtang 32º22’15.46” N 77º14’47.82” E Near Gramphu 32º22’26.32” N 77º14’55.97” E Between upper Marhi and Rani Nallah 32º21’10.20” N 77º13’06.41” E Rani Nallah 32º21’19.67” N 77º13’11.33” E Beas Nallah 32º20’56.85” N 77º13’17.85” E Rahalla Fall 32º19’58.25” N 77º12’56.38” E Marhi 32º20’56.02” N 77º13’05.78” E 5 km from Marhi towards Manali 32º21’22.56” N 77º13’46.54” E 4 km from Marhi towards Manali 32º21’15.08” N 77º13’21.66” E 3 km from Marhi towards Manali 32º21’14.79” N 77º12’54.63” E
Study of Rohtang Pass | 8.4
8.3 Sampling Procedure
• Snow samples were collected with the help of stainless steel pipe of two feet length of four inch diameter from different locations starting from Marhi to Khoksar on Manali Rohtang National highway NH-21 • The collected snow from the core was transferred to clean glass bottles of three liter capacity. • Just before processing for filtration, the snow samples were melted in a microwave oven.
Plate 8.3 and 8.4 depicts methodology adopted for collecting the snow samples.
Plate 8.3: Snow Sample Collection Plate 8.4: Snow Sample Collection in Clean Glass Bottles on Top of Snow Pack
Details of Set up of Assembly used to process the snow samples (Plate 8.5)
Plate 8.5: Millipore All-Glass Filter Assembly with Suction Pump
Study of Rohtang Pass | 8.5
Suction assembly: Millipore all-glass filter assembly with suction pump was used for filtration
Quartz filter papers: Tissue Quartz Filters manufactured by PALL Life Science was used to collect the particulate matter. The diameter of the filter is 47mm and the pore size is 1μ. Salient features of Quartz filter are: • It is mat of pure quartz fibers • It melts at > 9000 C • It has low blank levels for ions as it is pre-washed during manufacture • It has low hygroscopic character (Source: Chow et al., 1995)
Hence these filters are suitable and can be used for Carbon and ion analysis
Preconditioning of Filter papers These filters passively adsorb organic vapours and hence to eliminate the chances of overestimation of organic fraction, the filters are fired at 9000 C in Muffle Furnace before further processing them on site and were then stored in air tight Petri slides.
Filtration Procedure
• The fixed volume of liquefied snow samples were filtered through pre – fired Tissue Quartz filters. • The filters were dried in a desiccator.
8.4 Processing of Filters in the Laboratory
The filters were stored at -200 C before further analysis. The filters were then cut into 2 equal halves using filter cutter. One of them was used for Elemental and Organic Carbon analysis and the other half was extracted in Double Distilled Water for Ion analysis. Plate 8.6 shows typical Quartz Filter after filtering the sample. Plate 8.6 : Quartz Filter
8.5 EC OC Analysis
Instrument used: The Thermal/Optical Reflectance (TOR), Thermal/Optical Transmittance (TOT), and Thermal Manganese Oxidation (TMO) methods have been most commonly applied in aerosol studies for the analysis of organic and elemental carbon. Desert Research Institute’s Thermal/Reflectance Optical Carbon Analyzer, (Model 2001 A, Protocol Improve A) was used for the analysis. Plate 8.7 shows DRI’s EC OC Analyzer. This instrument can measure carbon content in the range of 0.05 – 750 μg C/cm2.
Study of Rohtang Pass | 8.6
Plate 8.7 : DRI’s EC OC Analyzer
Principle: The analysis is based on liberating carbon compounds at different temperatures. The 2 sample boat having a punch of 0.5-cm area is passed through oxygenator having heated MnO2 at 0 900 C. Here, volatilized carbon compounds get converted to CO2. Methanator having hydrogen 0 enriched Nickel catalyst reduces CO2 to CH4 at 425 C. The CH4 concentration is detected using 0 FID detector at 125 C. CH4 concentration is equivalent to elemental and organic carbon present in the sample. The results are noted in terms of reflectance based upper split values for regular OC, regular EC and TC in µg/filter. Following figure shows block diagram for DRI’s Carbon Analyzer (Plate 8.8).
Plate 8.8 : Block Diagram of EC- OC
Study of Rohtang Pass | 8.7
To differentiate the impact of vehicular exhaust on glaciers from other polluting sources like wood burning, biomass burning, vegetative detritus etc., in addition to EC OC analysis, ion analysis was also carried out.
The results for OC and EC concentration in glacier samples are given in Table 8.3.
Table 8.3: OC and EC Concentration in Glacier Samples Organic Elemental Sampling Location Carbon Carbon Blank (5m right side away from the 0.556 0.015 road at Top of Rohtang) Near Gramphu 2.798 0.022 Top of Rohtang 5.720 0.053 Rani nallah 6.445 0.040 Betn Upper Marhi - Rani Nallah 8.854 0.067 Beas nallah 9.838 0.158 Rahalla Fall 8.615 0.137 Marhi 11.419 0.227 3 km From Marthi towards Manali 15.123 0.455 4 km From Marthi towards Manali 13.263 0.249 5 km From Marthi towards Manali 14.572 0.416 Note: All the values are reported in mg/kg of snow
Observations
The lowest concentrations of 0.556 mg/kg of Organic Carbon (OC) and 0.015 mg/kg of Elemental Carbon (EC) also termed as black carbon were observed in sample collected at 5m right side away from the road at Top of Rohtang Pass which was considered as control/reference site not directly exposed to vehicular exhaust. The highest concentration of OC (15.123 mg/kg) and concentration of EC (0.455 mg/kg) was found at sampling site located 3 km from Marthi towards Manali. Maximum visitors were observed in and around Marhi and large number of tourist vehicles, other heavy duty traffic vehicles and snow scooters were observed near the selected site. Similarly, the values of EC and OC at 4 km (13.263 and 0.249 mg/kg respectively) and 5 km (14.572 and 0.416 mg/kg respectively) locations show the similar trend of high concentration. The locations above Marhi showed significant decrease in OC and EC concentration as less tourist vehicles were passing beyond Marhi towards Rohtang due to traffic restrictions.
Similar concentration range of EC (0.02 to 0.98 mg/kg) was also observed in samples collected from glaciers in west China during 2004-2006 (Ming et al., 2009). In a study by Huang et al., 2010, the concentration of black carbon in Northern China was estimated to 0.03 – 0.05 mg/kg (30- 50 ppb).
Study of Rohtang Pass | 8.8
8.6 Ion Analysis
Ions in snow can act as very good tracers for identifying the emission sources (Hanks, 2003). Aerosol ions refer to chemical compounds which are soluble in water. In water soluble fraction of the filter paper, different ions viz. Chloride, Nitrate, Sulphate, Phosphate, Sodium, Potassium, Calcium, Magnesium and Ammonium were analyzed.
Filter Extraction: The filters were extracted in 50 ml double distilled water by sonicating for one hour, followed by shaking for one hour and storing it overnight in refrigerator. It was then filtered through 0.45 μ pore size Millipore filter.
Instrument used: The samples were analyzed by Dionex ICS-300 Ion Chromatography system comprising of suppressor column, analytical column and a conductivity detector. Plate 8.9 shows instrument used for ion analysis.
Plate 8.9: Dionex ICS-3000 Ion Chromatography (IC) System
Principle: A sample of the mixture to be analyzed (analyte) is injected into a carrier fluid (the eluent). The combination is passed through a column containing a stationary fixed material (adsorbent). Compounds contained in the analyte are then partitioned between the stationary adsorbent and the moving eluent / analyte mixture Different dissolved materials adhere to the adsorbent with different forces. The ones that adhere strongly are moved through the adsorbent more slowly as the eluent flows over them. As the eluent flows through the column the components of the analyte will move down the column at different speeds and therefore separate from one another. A detector is used to analyze the output at the end of the column. Each time analyte molecules/ions emerge from the chromatography column the detector generates a measurable signal which is usually printed out as a peak on the chromatogram. A suppressor is being used to
Study of Rohtang Pass | 8.9 reduce the background conductance of the eluent and at the same time enhance the conductance of the sample ions.
The results for ion analysis in glacier samples are given in Table 8.4.
Table 8.4: Ion Concentration (in mg/kg) in Glacier Samples Sampling Location Potassium Chloride Phosphate Blank (5m right side away ND ND ND from the road at Top of Rohtang) Near Gramphu ND ND ND Top of Rohtang ND ND ND Rani nallah 0.439 0.766 ND Betn Upper Marhi - Rani Nallah 0.145 0.828 ND Beas nallah 0.062 3.249 0.026 Rahalla Fall 0.083 0.610 ND Marhi 0.076 0.805 0.053 3 km From Marthi towards Manali 0.204 1.134 ND 4 km From Marthi towards Manali 0.127 0.810 ND 5 km From Marthi towards Manali ND ND ND Note – ND: Not Detected
Observations
Amongst the different ions analyzed, potassium, chloride and phosphate were detected in different samples. The highest concentration of potassium was observed at Rani nallah (0.439 mg/kg). Beas nallah had the highest concentration of chloride (3.249 mg/kg). The presence of chloride indicates contribution from vehicular exhaust. But, the presence of potassium along with chloride confirms that biomass burning also plays a significant role in ionic composition of glaciers. Absence of sulphates and nitrates may be due to negligible concentration of SO2 and
NO2 observed during air quality analysis.
8.7 Analysis of Molecular Marker
Another approach for evaluating the existence and impact of vehicular pollution on glacier is examination of presence of molecular markers on snow.
Analysis of individual compounds like alkanes, alkenes, carboxylic acids, hopanes, steranes and aromatic compounds like Polycyclic Aromatic Hydrocarbons (PAHs) which constitute OC fraction, commonly referred as “molecular markers” (Simoneit, 1999) should be done to gain further in-sights into the sources of OC. Components of OC and their emission sources are listed in Table 8.5.
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Table 8.5: Molecular Markers and Their Probable Sources Molecular Markers Probable Sources PAHs Automobiles, resuspended soils, refineries, power plants. n-alkanes Vehicular exhaust, natural gas combustion, coal combustion, wood burning, cooking emissions from meat or vegetables and natural sources like vegetative detritus, pollens and microbial spores. Hopanes and Steranes Vehicular emissions Levoglucosan Biomass burning
The results on EC-OC and ionic composition should be indicative of presence and extent of vehicular impact on glaciers in the areas of Rohtang Pass. For confirmation additional analysis on molecular markers is recommended. Estimation of molecular markers along with the implementation of appropriate short term and long term control strategies for the polluting sources will help in keeping the surrounding environment clean and healthy for living.
References
1. National Carbonaceous Aerosols Programme (NCAP), 2011. Black Carbon Research Initiative Science Plan INCCA: Indian Network for Climate Change Assessment
2. Ramanathan, V. and Carmichael, G., 2008. Global and regional climate changes due to black carbon. Nature Geoscience, 1(156)
3. Ming J., Xiao C., Cachier H., Qin D., Qin X., Li Z., Pu J., 2009. Black Carbon (BC) in the snow of glaciers in west China and its potential effects on albedos. Atmospheric Research, 92: 114-123
4. http://moef.nic.in/soer/state/SoER%20Himachal%20Pradesh.pdf
5. DRI (2000). Standard Operating Procedure – Thermal/Optical Reflectance Carbon analysis of Aerosol Filter Samples, DRI – SOP 2 – 204.6
6. Huang J., Fu Q., Zhang W., Wang X., Zhang R., Ye H., Warren S., (2010). Dust and Black Carbon in Seasonal Snow across Northern China. Bulletin of the American Meteorological Society, doi: 10.1175/2010BAMS3064.1
7. Hanks K., (2003). Water Insoluble Particulate Organic and Elemental Carbon Concentrations and Ionic Concentrations from Snowpits Obtained at Summit, Greenland. M.Sc. Thesis, Georgia institute of Technology
8. Standard Operating Procedure for the analysis of Anions and Cations in PM2.5 Speciation samples by Ion Chromatography. SOP MLD 064, California Environmental Protection Agency Air Resource Board
9. Simoneit B.R.T., (1999). A Review of Biomarker Compounds as Source indicators and Tracers for Air Pollution. Environmental Science and Pollution Research, 6: 159-169
Study of Rohtang Pass | 8.11
Chapter 9
Remote Sensing Analysis 9.1 Introduction
Remote Sensing technology has emerged as a powerful tool in providing reliable information on various natural resources at different levels of spatial details. It has played an important role in effective mapping and periodic monitoring of natural resources including land use land cover (LULC) estimation. With the availability of high resolution remote sensing data, newer areas of remote sensing applications have been identified, techniques of data processing have been improved and computer based image processing systems have become more effective.
9.2 Study Area
The study area comprises of Manali to Khoksar including Rohtang Pass and lies between 32° 13’ and 32° 25'N latitudes and 77° 9' and 77° 17’E longitudes in district of Kullu, Himalchal Pradesh. The study area is considered as 2 km buffer of road from Manali to Palchan and 1km buffer of road from Palchan to Khosar (Rohtang Pass) for the assessment of current practices and changes in land use land cover in the region. The details of the study area are provided in Figure 9.1 considering national highway (NH-21), roads, village and drainage including Beas river and its tributaries based on the Survey of India Toposheet No 52H3. The total geographical area of the boundary is 8548.6 sq.km. The study area comes under the PirPanjal range of the Himalaya that connects the Kullu Valley with Lahul and Spiti valleys of Himachal Pradesh. The Rohtang pass is open from May to November while closed in winter (December to April) due to snow cover.
9.3 Methodology
For assessment of LULC, satellite images of the study area were collected based on the availability of the data. Since, the study area is covered by snow during December to April and open (Rohtang Pass) during May to November, images were collected for the month of January, July and October. Satellite image of 17 July 2012 was procured for the assessment of current LULC practices in the study area. Image of 31 January 2011 was collected to visualise the spatial extent of snow cover in the study area while 27 October 2011 and 29 October 2005 images were procured based on its availability and being free from cloud and snow cover as well as assessment for change in LULC. The methodology for remote sensing analysis of satellite imageries is divided into following headings: • Acquisition of Satellite data • Collection of ground truths and ground control points (GCP) • Pre-processing of data • Geo-referencing and rectification
Study of Rohtang Pass | 9.1
Figure 9.1: Base Map of Study Area (Manali to Khoksar)
Study of Rohtang Pass | 9.2
• Supervised classification • Estimation of LULC • Accuracy assessment
The satellite data were procured from National Remote Sensing Centre (NRSC), Hyderabad for remote sensing analysis. Indian Remote Sensing (IRS) data P6 Linear Imaging Self-Scanning (LISS) III of 17 July 2012 was procured to assess the current LULC practices in the study area especially around Rohtang Pass. Apart from latest satellite image, other images were also collected namely IRS P6 LISS III (27 October 2011), IRS P6 LISS-IV (29 October 2005), and LANDSAT ETM+ (31 January 2011) for LULC mapping. The details of imageries are presented in Table 9.1.
Table 9.1: Details of Satellite Data Sr. Satellite Sensor Resolution m Date of Pass 1 IRS P6 LISS III 23.5 17 July 2012 2 IRS P6 LISS 23.5 27 October 2011 3 LANDSAT7 Pan ETM + 15 31 January 2011 4 IRS P6 LISS IV 5.8 29 October 2005
The spatial resolution and the spectral bands in which the sensor collects the remotely sensed data are two important parameters for any land use survey. IRS P6 LISS III data offers spatial resolution of 23.5 m with the swath width of 141 x 141km.LISS III data is collected in four visible bands namely green (Band 2: 0.52-0.59μm), red (Band 3: 0.62-0.69μm), near Infrared (NIR) (Band 4:0.77-0.89μm) and short wave infrared band (Band 5: 1.55-1.75μm) with orbit repeat period of 24 days.IRS P6 LISS IV data offers spatial resolution of 5.8m with the swath width of 23.5 x 23.5km. LISS IV data is collected in Multi-spectral mode in three spectral bands as green (Band 2:0.52 to 0.59μm), red (Band 3: 0.62-0.68μm) and NIR (Band 4: 0.76 to 0.86μm). LANDSAT- 7 Enhanced Thematic Mapper (ETM) is downloaded from Global Land Cover Facility which offers spatial resolution of 15 m with pan image with swath width of 170 x 185km. The data is collected in seven bands namely blue-green (Band 1:0.45-0.52μm), green (Band 2: 0.52-0.60 μm), red (Band 3: 0.63-0.69 μm), near infrared (NIR) (Band 4: 0.75-0.90 μm), mid- infrared (MIR) (Band 5 and 7L: 1.55-1.75 μm) and far-infrared (FIR) (Band 6: 2.08-2.35 μm) with orbit repeat period of 16 days. The shapes, sizes, colours, tone and texture of several geomorphic features are visible in IRS and LANDSAT data. Spectral bands provide high degree of measurability through band combination including FCC generation, bands rationing, classification etc. These features of the IRS and LANDSAT data are particularly important for better comprehension and delineation of the land use land cover classes.
Study of Rohtang Pass | 9.3
The remote sensing analysis was performed on ERDAS Imagine 10 on high-configured computer. This software package is a collection of image processing functions necessary for pre-processing, rectification, band combination, contrast stretching, filtering, statistics, classification etc. Arc Map 10 was also used for final layout presentation of base map, drainage, False Colour Composites (FCC) and LULC maps.
The satellite data from the compact disc was loaded on the hard disk and by studying quick looks (the sampled image of the appropriate area); the sub-scene of the study area is extracted. Imageries were geo referenced and rectified with ground control points (GCP) from Survey of India Toposheet and field data collected during ground truth survey. Detailed survey was carried out using Global Positioning System (GPS) and digital camera for collection of ground truth and GCP in the study area for LULC analysis. The locations of ground truth points in the study area are geographically presented in the map (Figure 9.2) and details are provided in Table 9.2. Various activities and locations of the land mark were captured through digital camera to assess the current practices of LULC in the study area (Annexure 9.1).
Table 9.2 : Details of Ground Truth Locations in the Study Area
Sr. Details of Ground Trothing Locations Latitude N Longitude E Rohtang Pass (Palchan to Khoksar) 1 Built-up (Palchan) 32º 18’ 33” 77º 10’ 31” 2 Beas Kund Hydro Power Plant 32º 18’ 32” 77º 10’ 30” 3 Built-up 32º 18’ 46” 77º 10’ 44” 4 New Construction (Kothi) 32º 19’ 03” 77º 11’ 22” 5 New construction 32º 19’ 06” 77º 11’ 30” 6 Natural Forest (TOSH) 32º 19’ 17” 77º 11’ 37” 7 Steel Bridge 32º 19’ 21” 77º 11’ 37” Small Hydro Electric Power Project 8 32º 19’ 59” 77º 11’ 49” (Marhi Power House) site at Kothi 9 Shops (Temporary) at Gulaba 32º 19’ 31” 77º 12’ 05” 10 DETT Gulaba (BRO) 32º 19’ 23” 77º 12’ 05” 11 Exposed rock near Raila Fall 32º 19’ 57” 77º 12’ 56” 12 Beas Nallah d/s Marhi 32º 20’ 55” 77º 13’ 16” 13 Bridge on Beas Nallah 32º 20’ 57” 77º 13’ 17” 14 Grass Land near Marhi 32º 21’ 00” 77º 13’ 10” 15 Rohtang top (near Beas kund) 32º 22’ 17” 77º 14’ 47” 16 Landslide 32º 21 32” 77º 13’ 43” 17 Built up (Marhi) 32º 20 57” 77º 13’ 04” 18 Permanent Structures 32º 19’ 06” 77º 11’ 33” 19 Built-up (Near Hill View Cafe) 32º 19’ 00” 77º 11’ 20”
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Table 9.2 : Details of Ground Truth Locations in the Study Area
Sr. Details of Ground Trothing Locations Latitude N Longitude E 20 Built-up (Kothi) 32º 19’ 01” 77º 11’ 14” 21 New Construction (Kothi) 32º 18’ 47” 77º 10’ 51” 22 Bridge on Beas River 32º 18’ 23” 77º 10’ 52” Palchan to Manali Apple orchard near confluence of Solang and 23 32º 18’ 19” 77º 10’ 56” Beas river 24 Forest along road (Kulang) 32º 17 43” 77º 10’ 57” RCC Bridge on nala near Snow and Avalanche 25 32º 16 08” 77º 10’ 57” Estt. (SASE) 26 Forest around Circuit House 32º 15’ 00” 77º 11’ 09” 27 Forest (Log Huts area) 32º 14’ 59” 77º 10’ 26” 28 Apple Orchards (Log Huts area) 32º 14’ 59” 77º 10’ 33” 29 Forest (Hotels Highlands) 32º 15’ 06” 77º 10’ 47” 30 Tiraha Log Huts (new and old Manali) 32º 15’ 10” 77º 10’ 54” 31 Bridge onMalanashu River 32º 15’ 09” 77º 10’ 47” 32 Forest along Malanashu River 32º 15’ 04” 77º 10’ 41” 33 Forest near Hadimba Temple 32º 14’ 50” 77º 10’ 42” 34 Forest surrounding Hadimba Temple 32º 14’ 55” 77º 10’ 51” 35 Forest along Hadimba Temple Road 32º 14’ 49” 77º 11’ 00” 36 Forest near Wildlife Information Centre 32º 14’ 51” 77º 11’ 21” 37 Nehru Park Mal Road 32º 14’ 45” 77º 11’ 23” 38 Bridge on Beas Bypass Rohtang 32º 14’ 46” 77º 11’ 23” 39 Forest along Beas River 32º 15’ 13” 77º 11’ 17” 40 Manali Model Town 32º 14’ 36” 77º 11’ 20” 41 Built up (near Gompa road) 32º 14’ 34” 77º 11’ 18” 42 Forest along Manali-Kullu road 32º 14’ 14” 77º 11’ 12” 43 Open land (Manali potato ground) 32º 13’ 59” 77º 11’ 18” 44 Aleo village near manali 32º 14’ 23” 77º 11’ 18” 45 Apple orchard 32º 13’ 53” 77º 11’ 49” 46 Built- up (Khoksar) 32º 24 30” 77º 15’ 05”
LULC maps were prepared using supervised classification technique based on maximum likelihood classifier. The training areas for classification were homogeneous, well spread throughout the image. Training sets were used throughout the satellite image for similar land use classes based on spectral responses and acquisition of ground truth data (Annexure 9.1). After evaluating the statistical parameters of training sets, the training areas were rectified by deleting no congruous training sets and creating new ones.
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Figure 9.2: Location Map of Ground Truth and Ground Control Points
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9.4 Results and Discussions
The land use land cover classification system standardized by Department of Space, for mapping different agro-climatic zones has been adopted in the present study. This classification system has six major LULC classes at level I and twenty-seven at level II (Annexure 9.2). The various categories of LULC observed in the study area is classified into major groups like forest (evergreen and scrub), vegetation (plantation, grassland, shrubs etc.), built-up, barren (exposed rock), water body and snow.
False Colour composites
FCC images of the study area were prepared based on the buffer (2km and 1km) from the road. In FCC images of IRS P6 (LISS III and IV) and LANDSAT 7 ETM+, forest appears as dark red, vegetation/plantation appears as red and pink red, built-up and water body as cyan, exposed rock as grey and greenish and snow as white. Attributes such as colour, tone, texture, shape and size were used for visual image interpretation. Figure 9.3 through 9.6 represent the FCC images of 17 July 2012, 27 October 2011, 31 January 2011 and 29 October 2005, respectively. Cloud cover and its shadow was found in FCC image of 17 July 2012 as white and black patches, respectively (Figure 9.3). Ground truth data was collected and used for training different classes of LULC and for accuracy assessment of the classification.
In FCC image of July 2012, most of the study area is occupied with forest (evergreen and scrub) and vegetation/plantation cover due to the effect of monsoon season and rest of the area is occupied with built-up, water body, barren and snow. Even in FCC image of October 2011, major LULC classes are forest (evergreen and scrub) and vegetation/plantation (Figure 9.4). FCC image of 31 January 2011 depicts the occupancy of the snow cover in most of the study area due to winter season (Figure 9.5). FCC image of 29 October 2005 provides the distinct identification of the LULC classes due to its finer spatial resolution (5.8 m) as compared to July 2012 (23.5m), October 2011 (23.5) and January 2011 (15m) images. October 2005 image is also free from snow and cloud cover for better assessment of the LULC in the study area (Figure 9.6).
Supervised Classification
Supervised classifications of the images were carried out for LULC with seven different classes as evergreen forest, scrub forest, vegetation/plantation, built-up, barren (exposed rock), water body and snow. Figure 9.7 to Figure 9.10 represents the LULC classification of images of 17 July 2012, 27 October 2011, 31 January 2011 and 29 October 2005, respectively. LULC maps were prepared by assigning the colour to individual classes as given in legend namely evergreen forest as dark green, scrub forest as yellow green, vegetation/ plantation as lawn green, built- up as red,
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Figure 9.3 : False Colour Composite (FCC) Image of 17 July 2012
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Figure 9.4 : False Colour Composite (FCC) Image of 27 October 2011
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Figure 9.5 : False Colour Composite (FCC) Image of 31 January 2011
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Figure 9.6 : False Colour Composite (FCC) Image of 29 October 2005
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Figure 9.7 : Supervised Classification for LULC (17 July 2012)
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Figure 9.8 : Supervised Classification for LULC (27 October 2011)
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Figure 9.9 : Supervised Classification for LULC (31 January 2011)
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Figure 9.10 : Supervised Classification for LULC (29 October 2005)
Study of Rohtang Pass | 9.15 barren (exposed rock) as magenta, water body as blue and snow as pale turquoise colour. The inventory of LULC classes in all the classified maps is illustrated in Figure 9.11. Classified image of 17 July 2012 indicates 3.7% built-up, 25.2% evergreen forest, 14.7% scrub forest, 34.5% vegetation/plantation, 18.1% barren (exposed rock), 2.9% water body and 0.9% snow cover in the study area (Figure 9.7). Similarly, inventory of classified image of 27 October 2011 (3.4% built- up, 25.2% evergreen forest, 14.0% scrub forest, 28.4% vegetation/plantation, 19.6% barren (exposed rock), 2.8% water body and 6.6% snow), 31 January 2011(2.1% built-up, 17.1% evergreen forest, 1.5% scrub forest, 6.7% vegetation/plantation, 0.9% barren (exposed rock), 1.6% water body and 70.1% snow) and 29 October 2005 (2.8% built-up, 26.3% evergreen forest, 13.3% scrub forest, 30.6% vegetation/plantation, 24.5% barren (exposed rock) and 2.5% water body) indicated percentage area under different classes of LULC (Figure 9.8 through Figure 9.10).
Figure 9.11 : Inventory of Land Use Land Cover in the Study Area
Classified image of 17 July 2012was used for post classification accuracy assessment as this was the only latest image available along with current practices of LULC as recorded during ground truth survey in July 2012. Based on spatial extent of LULC classes and variability of distribution across the study area, a suitable sample size of 36 was used for the accuracy assessment. Accordingly, an error matrix was generated to assess the overall accuracy. The overall accuracy of supervised classification is found to be 81%. The user’s and producer’s accuracies of the classification are as 75% and 73%, respectively.
Classified images indicated that forest and vegetation are the main classes of LULC in the study area (Figure 9.11). Percentage of evergreen forest decreased marginally from 26.3% to 25.2% in the study area during 2005 to 2011. Simultaneously, scrub forest has increased from 13.3% to 14% in the study area during the same period.
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Vegetation/plantation includes horticultural land (apple orchard), farm land, natural vegetation, grass land etc. Vegetation/plantation was estimated more in July 2012 image as compared to October 2005 image due to monsoon season which favours the growth of natural vegetation. Due to growth of natural vegetation in the upper Rohtang Pass region during monsoon, barren land (exposed rock) was estimated comparatively less in July 2012 as compared to October 2005 image.
Built-up area has been increased from 2.8% to 3.7% in the study area during 2005 to 2012 especially at Manali, Palchan and adjoining to these areas. Built-up was found to be slightly increased (0.2% of the study area) between Khoksar and Palchan as per image analysis of July 2012 as compared to October 2005 image. Similarly, an increase (0.74%) in built-up was observed between Palchan and Manali as per image analysis of July 2012 and October 2005. During survey from Palchan to Khoksar, built-up was observed at Palchan, Kothi, Marhi and Khoksar. Temporary shops were also observed at Gulaba. New construction activities were also observed in between Palchan and Kothi. No settlement/built-up was observed between Marhi to Khoksar except one Gompa (temple) at Rohtang top.
Percentage area occupied by the water body class is more or less same in all the images except January 2011 image where it was found less due to snow cover. Since, the study area comes under Himalayan region and is covered with snow during winter season (December– March), image of January 2011 was also analysed for LULC classes. About 70% of the study area was found to be covered by snow (Figure 9.9) therefore other LULC classes were estimated to be lesser as compared to July 2012, October 2011 and October 2005 images.
Useful analysis could be based on data Sets of 29th October, 2005 and 27th October, 2011. The classified images of these two data sets are given in Table 9.3.
Table 9.3 : Landuse Pttern of Study Area in Percentage 29th October, 2005 27th October, 2011 Built Up Area 2.8 3.4 Evergreen Forest 26.3 25.2 Scrub Forest 13.3 14.0 Vegetation / Plantation 30.6 28.4 Barren (Exposed Rock) 24.5 19.6 Water Body 2.5 2.8 Snow 0.0 6.6 * Values expressed in percentage.
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9.5 Summary of Remote Sensing Analysis
The remote sensing analyses of the satellite images provide some useful initial information about land use and related changes. Useful analysis could be manly based on images of 29th October, 2005 compared with 27th October, 2011 as other images show high snow cover during winter month. In terms of percentage change, the data does not show any alarming trend as of now; however, it is important to note that small percentage in built area at in appropriate place or sensitive landslide zones can be detrimental to environment.
It is therefore, necessary to adopt following measures and integrate the same in planning of development in the region: - All areas of the region should be subjected to annual satellite surveillance along with ground truthing. This will help in documenting the conditions of the select important regions, as also any other changes in rest of the places. - Micro-planning to the scale of 1:100 m grid should be done so that slopes and elevations can be better documented along with possible planning. - Slope area should be strictly regulated through town planning and local corporation.
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Chapter 10
Recommendations
10.1 Recommendations
Himachal Pradesh state boasts of numerous picturesque tourist destinations, which are responsible for generating much of the revenue for the state. The economy of Himachal Pradesh depends greatly on tourism. National Highway 21, the road through the Kullu Valley, past Manali and over the Rohtang Pass to Keylong, and Lahul and on to Leh in Ladakh, has become very busy during the summer months as an alternate military route, following the Kargil Conflict in 1999 in addition to tensions in Kashmir. Traffic jams are common as military vehicles, tourist vehicles, trucks, and goods carriers try to navigate the tight roads and rough terrain, compounded by snow and ice at certain points and the large number of tourist vehicles.
10.2 Transport Sector Action Plan
During the peak season in May and June about 2200 to 2500 vehicles ply on this highway according to the Tourism Department. However, as per figures supplied by the BRO, between 7331 and 7376 vehicles ply (both ways). According to the NEERI study, during the end of May, the number of vehicles on Palchen Rohtang highway was 3250 on both ways out of which 80% are cars. About 10,000 people visit the Rohtang pass every day. The width of the road from Manali to Rohtang is not wide enough to sustain this traffic leading to massive traffic jams. The snow deposits in the upper valley turn black with the layer of carbon and soot generated by the vehicles and the snow has started melting earlier as by July.
10.2.1 Approach and Issues • The approach for developing the action plan for particulate matter reduction for the vehicular sector are : o Targeting the most polluting vehicles (vehicles emitting high emissions per km) o Targeting the most used vehicles o Targeting the vehicles with high growth rate vehicles such as cars and two wheelers have the highest growth rate) • Stakeholders important for overall implementation & improvement are : o Transport operators o State govt. authorities o Academics and research institutions o Health care authorities o Enforcement authorities (RTO) o NGO’s o Tour Operators/ Hotels o Oil Companies
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• Contribution of Different Type of Vehicles
Based on vehicle count carried out by NEERI during the study period it appears that cars/ taxis/ jeeps/ SUVs dominate the overall vehicles moving on Manali-Rohtang-Leh Highway. HMV constitute a very small percentage of vehicles on the NH-21. • Growth Rate of Vehicles The total number of vehicles counted by NEERI on the road from Manali to Palchen and back during end of May 2012 was 6359. Assuming a growth rate of 9% per annum (Since the growth rate of vehicles in India is 9% per annum (1) the number of vehicles in 2022 will be 15000. Growth rate of VKT will also be about 9% per annum. The calculated emission of PM, NOx and CO for the years 2012 and 2022 without any control for a distance of 43 km from north of Manali to Rohtang are given below. This increase shall be more than 100% of current emission load.
PM (Kg/day) NOX (Kg/day) CO (Kg/day) 2012 2022 2012 2022 2012 2022 3.11 7.34 34.03 80.26 56.75 133.86
10.2.2 Recommended Plan • Restriction of Traffic: Several transportation service options are available for encouraging reductions in energy consumption and fuel emissions. These initiatives focus on reducing the use of private vehicles for internal transportation purposes. They include creating public transit fee structures or introduction of congestion charges that encourage visitors to shift from private vehicle use to public modes of travel. Such interventions are especially applicable for tourism destinations that want visitors to experience their communities in a more engaging and tactile fashion. Although it is unlikely that planning solutions can completely eliminate the use of private automobiles within destination areas, minimizing vehicle use can enhance the experience of tourists by decreasing noise and air pollution. Such actions can contribute to a more relaxed atmosphere and increasing recreational opportunities. • Vehicle Fitness Test: The complete fleet system to be examined. Vehicular fitness tests may be made mandatory and only those may be allowed to operate which comply with the vehicular emission norms. A fitness centre should be established in Manali. This center shall be managed by qualified and properly trained manpower. At this center (can also be called Vahan Nagari/ Mechanic and Testing Nagari), a comprehensively planned inspection and certification unit can be set up. The inspection and certification system development and its implementation should
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involve all the stakeholders such as the respective association of various commercial transport, private owners, testing authority and NGOs. • Lowering the Age of Vehicles: More stringent options may be introduced such as only commercial vehicles with less than 4 yrs age may be allowed to ply from Manali to Rohtang • Low Cost Buses : LCB may be introduced which will reduce the total number of vehicles per day travelling on Manali-Leh Highway. Provide better frequency of buses to reduce congestion during peak period. Better bus quality to be provided in terms of sitting space. The vehicles are the main sources of air pollution in Manali Rohtang highway. And hence this will help to reduce the air pollution to a large extent. Low cost bus travel can be achieved through high congestion charges to be collected from private vehicles. The mode of collection shall be as given in box below : Subsidization of Public Transport, Higher Car User Charges Objective Efficient and cheaper public transport Cost Mechanism to be detailed Stakeholders Residents, users of public transport Remarks All taxis, private cars which go towards Rohtang to pay Rs. 300/- (this cost will be exclusive of current parking charges). The funds thus collected shall be directly passed on to the State Government, which will run efficient, high frequency buses along all the routes. The bus fare will be kept low. Bus route shall be designed to cover almost all areas of the region.
• Installing Ropeways with intermediate stops at suitable places is also required for better tourism option and experience. This will reduce the pollution from vehicular traffic and also reduce the traffic congestion to a large extent. • While planning for the Ropeways, at all intermediate stops, only battery operated vehicles should be used for short distance travels. Government incentive should be given in terms of waiver of registration fee and any other Government levies for all battery operated vehicles. Also at each of these stops, a vehicular parking area shall be created to avoid congestion. • Introduction of air routes like helicopters may be examined. • Battery Operated Snow Scooters: Snow scooters are observed during the snow period spoiling the snow from air emissions and oil spillage. Only battery operated snow scooters may be allowed to avoid spoiling the snow with fuel oil and black carbon. • Fuel (Sulphur) Options − Emphasis on use of low S diesel equivalent to Bharat Stage IV should be given in Manali Region − Rationalization of price structure of fuel within and also adjoining states. − Fuel quality parity across adjoining states as fuel prices and quality are not same in all the states, operators want to fill in inferior quality fuel outside the region.
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− Central Government and Refineries related oil companies to be contacted for introduction of BS IV huel in HP, especially in Manali. • Fuel (Adulteration) − Oil companies to ensure better movement of their produce to avoid adulteration. − High degree of education and awareness to the petrol pumps operators. − Oil companies to show pro-activeness in promoting the better lubricants (ban on low grade lubricants). − Ministry of Petroleum and Natural Gas (MoPNG) should develop better specification for the lubricants to be used. HPSPCB may contact MoPNG for the necessary assistance. − Oil companies to actively undertake programmes such as BPCL’s Pure for Sure; HPCL’s Club HP and IOC’s Q & Q etc. to provide better fuel quality. − MoPNG to strengthen anti adulteration cell and establish a cell in HP. • Fuel (Alternatives) − HDDV and LDDV to operate on diesel of low S (350 ppm ) diesel, equivalent to BS IV. − Vehicles should be subjected to strict, reliable and reproducible inspection for smoke levels. − Smoke levels should be brought below 45 HSU (Hartridge Smoke Unit) by the use of DOC (Diesel Oxidation Catalyst) or DPF (Diesel Particulate Filter), whichever achieves the desirable result. • Retro Fitment of Emission Control Technology − Evaluation of all the private vehicles emission control system (catalytic converter were first introduced in the year 1995) through a proper inspection schedule. − Evaluate the need for emission control device replacement for all the vehicles which have become more than 8 years old. − All the grossly polluting vehicles plying only within the city, such as school buses, water tankers, garbage trucks etc should be fitted with emission control devices. − As retrofitment of emission control devices also needs a certain levels of fitness of the vehicle, it would be desirable to follow the norm after developing the same through the inspection and certification procedures − Vehicle manufacturer should be asked to give emission warranty for the complete period of the operation of the vehicle. − Delineation of useful vehicles life along with the emission warranty for a longer period should be demanded from vehicle manufacturer.
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• Phase out of the Private Vehicles − The vehicles older than 15 years may go through the inspection and certification every year. Vehicles not meeting the norm should be phased out. − The vehicles should be able to meet the current norms at that time of certification. − Vehicles between 8 and 15 years should go through inspection and certification every two years. − Other vehicles can go through the inspection every three years. The basic purpose of such certification process shall be to identify vehicles needing phase-out − Voluntary phase out of vehicles after 15 years with an incentive can be introduced by HP Government. It can plan to give Rs. 20,000/- for phasing out >15 years vehicles. • Roads and Pavement − Better road quality can dramatically reduce the re-suspended dust as well as direct contribution from vehicles. − Pavement improvement is the other major issue within the city. A micro-planning exercise should be undertaken to upgrade pavements and kerbside. • Traffic Management − Pedestrian movement on pavement should be a priority to reduce congestion on roads within the city. − Awareness, training and inspection of the road users in terms of abiding by the traffic rules. − Augmentation of capability of the personnel involved, better resource availability in terms of manpower and infrastructure for RTO and Traffic police. − Coordination with all the other concerned authorities in the city. • Institutional Arrangement − The APEX Body should be created comprising of representatives of HP State Pollution Control Board, Department of Environment and Transport Commissioner Office.
Policy Level (MMC, DoE, TCO, CPCB, MoEF)
Monitoring and Regulatory Public Transport Facilities MMC, HPSPCB, RTO, (Taxi, Manali Transport System, LDDV, HDDV Operators) Anti Adulteration Cell
Preventive and Treatment Other Stakeholders Hospitals, Clinics • Oil Companies, Retailers • Vehicle Manufacturers • Ngo, Public, Others • Tour/Hotel Operators Problem Identification and Prediction Research Institutes, Academic Institutes
Interrelationships of Institutional Arrangement for Effective Control and Planning Management
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• Clean Rohtang Fund: It is proposed that a separate fund should be created called ‘Clean Rohtang Fund’. This will be used for various programmes and activities which can be undertaken locally to improve current situation. Purpose of the Fund − Promotion of public transport − Setting up of fuel testing laboratories − Setting up of vehicle inspection facilities and emission check − Introduction and promotion of alternate fuel − Promotion of health facilities − Targeted research activities for preventive action − Providing incentive to old grossly polluting vehicles • Source of Fund The “Clean Rohtang Fund” may generate funds from the following routes: a. Restricted Entry Charges in Rohtang Area b. Higher Parking Charges in city c. Clean Air Surcharge for Sale of Fuel d. Fixed One Time Surcharge on Existing Population of Vehicles e. Clean Air Surcharge on New Vehicles to be Sold in the State • Estimated Collection of Fund
Methods of Levying Charges Collection a Restricted entry charges Rs. 300/- per day b Higher parking charges Rs. 50/hr c Fuel cess 0.25 for petrol and 0.15 for diesel --- d Fixed one time charge on existing vehicle Rs. 5000/- per vehicle e Fixed one time charge on new vehicles Rs.10000/- per vehicle
• Collection Protocol of Surcharges − Places where Life-Time Tax is taken from the owners, they do not necessarily go to any Road Transport Authority for payment of Road Tax. Collection of surcharge from such vehicle owners might be difficult. − The only regular contact point for all vehicles is the Insurance Companies who provide them with annual insurance coverage. − This is a mandatory requirement as per Motor Vehicles Act of 1988 u/s 146, Chapter XI where 3rd Party Insurance is compulsory for all vehicles other than Government (Central, State and Local Authority). − The above mentioned funds can be collected at the time of annual renewal of insurance through insurance companies.
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• Rohtang Tunnel is a tunnel being built under the Rohtang Pass in the eastern range of the Himalayas on the Leh-Manali Highway. With 8.8 km length, the tunnel is expected to reduce the distance between Manali and Keylong by about 60 km. Rohtang pass receives heavy snowfall and blizzards during winter months and it is open from May to October. Lying on the Manali-Leh axis, this is one of the two routes to Ladakh. The other route through the Zoji La pass on the Srinagar-Drass-Kargil-Leh highway also gets blocked by snow for nearly four months in a year. These two routes are vital to feed military supplies into the sub-sector west and the Siachen Glacier. The Rohtang Tunnel will be very important for the military supplies and will be open through out the year. Out of 8.82 km 2.7 km of the tunnel is already constructed and is expected to be commissioned in 2015. The 85 km distance from Manali to Keylong on the other side of Rohtang Pass is usually covered by vehicles in about five to six hours, without counting the long hours of traffic jams on the hilly route. The same distance would now be covered in less than half-an-hour through the tunnel and without traffic snarls. Keylong would be just 25 km from the North Portal of the tunnel. Once the Rohtang tunnel is commissioned, people going to Keylong, Ladakh and military supplies will travel through the tunnel reducing the traffic through Rohtang pass.
10.3 Water Environment
• The water environment in study area mainly shows contamination due to domestic discharges. As there is no water polluting industries in the study region up to Manali. • The villages/ townships along the Beas and Chandra River have small inhabitants and no organized wastewater collection system is installed by Gram Panchayat. The domestic waste ultimately joins river Beas and Chandra through small drains and streams. Currently impact of such waste is not significant because of the quantity of flow in these rivers and adequate aeration due to turbulence created in hilly terrain. Small scale waste water treatment facilities like phytorid nature based treatment systems should be adopted before releasing the domestic waste into the rivers. • Due to absence of sanitation facilities, the tourists are compelled to use open places for attending the nature calls. Hence there is urgent need to adopt well-designed and adequate sanitation facilities along with proper treatment and disposal of collected liquid waste at important tourists places. • Strict action needs to be taken to discourage increasing use of waterways by tourist for sanitation purpose.
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10.4 Solid Waste Management
Investing in environmentally sensitive solid waste management systems that emphasize reuse, reduction, recycling and composting can minimize the amount of waste sent to landfills. • The solid waste collection system should be for the entire region up to Rohtang pass. • Additional treatment methods like vermi composting, aerobic composting and anaerobic composting can be used as on site batch process. • The current practice of dumping in the open land and recycling some of the plastic and paper should be improved. • Tourists should be specified strict instructions to throw the used articles in the dustbins only and not to pollute the environment. • After regular intervals, dustbins should be emptied for collection of solid waste. • The animal dung should be properly collected and can be used for composting or methane generation process. • The number of portable/public toilets with appropriate treatment of the waste generated should be increased to cater ever increasing tourist population. Generally for residential areas for 50 persons 1 seat of toilet is considered for sanitation program. The toilet will be used for 10 minutes by each user. Hence, the number of tourist should be considered for deciding the extent of toilet facilities. • Adequate manpower should be provided for cleaning and maintaining public toilets with provision of funds. • The toilet system should have minimum use of water which can restrict the volume of waste to be collected and can be subjected to use of Biodigestor technology. • A fine should be collected from the tourists who are found not using the facilities. • The land filling should be done in a scientific manner. • Civil society should be made more conscious about their responsibility towards the environment. • The number of dust bins at frequently visited tourist places must be increased with efficient collection system. • Dhabas and vender shops should use biodegradable items and take proper precautions for safe disposal of the food waste. • Awareness of General public can play a important role foe environmental protection. Public awareness programmes through hoardings, television can be organized. This will help in solid waste management and disposal.
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With these recommendations, it may be possible to maintain the sustainable solid waste management in the state. The SADA and other related departments should initiate public awareness programmes so that the menace of solid waste disposal, littering and management can be smoothly controlled.
10.5 Soil Erosion vis-à-vis Land Sliding
The study region is facing soil erosion due to the nature of soil strata and manmade activities like road broadening and other construction though deforestation i.e. green cutting is totally banned. The soil erosion is occurring due to climatic reasons of snow melting and rains.
Corrective measures which can be tried for minimization of landslides and soil erosion due to rains/snow water flowing are as follows: • Install earth works along the slide prone areas • Drainage correction • Proper land use measures by plantation of vegetation, horticulture • Construction of Protection wall • Structural works to stabilize gully heads formed so that they no longer erode • Gully reshaping, battering and re-vegetating to prevent further erosion • Diversion banks to divert runoff and prevent it building up energy • Drop structures to control water flow • Overgrazing can also encourage soil erosion
The geological and mechanical properties should be considered while planning the activities like construction and traffic management.
Large quantity of water from the small hydal power plant like Kothi and Marhi and many others are released in the hilly slopes in valley which may wash out the top soil. Such flows should be properly regulated to avoid soil loss. In small catchments for hydel plant releases, natural springs and falls, possibility of construction of bandharas or small check dams, can help intercept runoff of sediment and gully erosion. However, this approach needs detailed Engineering feasibility and approval from Department of Natural Resources to construct dams. Nehru kund at Marhi is one of the examples of above suggestion which has formed a water body and spot of attractions for the people. There is a need to undertake micro-planning of the entire region especially the areas of construction or on near slopes.
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10.6 Biological Environment
• Tourist activities should be restricted to areas of ecological importance like natural habitats of endangered species of plants and animals. • Developmental activities like road construction should be carefully planned to avoid habitat fragmentation affecting the animal corridors. • The tourists should also be made conscious towards the environmental impact through effective posters and proverbs along the roadside. • The entry point of the city as also in each hotel, a 5 minutes “do’s and dont’s” video can be shown to all tourists. In addition printed matter on the above should be given to all tourists to create awareness. • Strict fines should be implemented on tourists found loitering in the region with plastics and polythene bags.
10.7 Glaciers
• The transport sector is considered as the third-largest source of energy-related black carbon emissions in Asia as a whole and it is projected to become the second-largest source with ever increasing vehicular traffic. So, the control of transport-based black carbon emissions form an essential part in any comprehensive black carbon control strategy. • Within the transport sector, on-road diesel combustion accounts for the majority of black carbon emissions, due to diesel’s much higher emission factors compared to petrol and its dominance as a transport fuel in Asia. • The current study has confirmed the impact of vehicular traffic on snow in Rohtang region. However, the concentrations of black carbon observed were low. • During the interim period of recommended measures a continuous study of following should be considered. − Vehicle type and count − Impact on snow by analysis of black carbon and molecular markers This will help in better understanding and also to modify the plans in future. • The impact of vehicular movement can be ascertained by carrying out analysis of Molecular
Markers. Control of transport-related black carbon emissions can be achieved as given in Section 10.2.2.
References 1. Rameshwar Dayal Sharma, Sandeep Jain, Kewal Singh, 2011. Growth Rate of Motor Vehicles in India - Impact of Demographic and Economic Development. Journal of Economic and Social Studies. Volume 1, Number 2, 2011
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ANNEXURES ______Annexure 2.1
NATIONAL AMBIENT AIR QUALITY STANDARDS CENTRAL POLLUTION CONTROL BOARD
Notification : No. B- 29016/20/90/PCI-L- In exercise of the powers conferred by Sub-section (2) (h) of section 16 of the Air (Prevention and Control of Pollution) Act, 1981 (Act No. 14 of 1981) and in supersession of the Notification No.(s).S.O.384 (E), dated 11th April, 1994 and S.O. 935(E), dated 14th October, 1998, the Central Pollution Control Board hereby notify the National Ambient Air Quality Standards with immediate effect, namely : -
Sr. Pollutant Time Concentration in Ambient Air Weighted Industrial, Ecologically Methods of Measurement Average Residential, Sensitive Rural and Area (notify Other Area by Central Government) 1. Sulphur Dioxide Annual * 50 20 * Improved West and Gaeke 3 (SO2), µg/m 24 Hours ** 80 80 * Ultraviolet fluorescence 2. Nitrogen Dioxide Annual * 40 30 * Modified Jacob & Hochheiser 3 (NO2), µg/m (Na –Arsenite) 24 Hours ** 80 80 * Chemiluminescence 3. Particulate Annual * 60 60 * Gravimetric Matter (Size less 24 Hours ** 100 100 * TOEM than 10 µm) or * Beta attenuation 3 PM10 µg/m 4. Particulate Annual * 40 40 * Gravimetric Matter (Size less 24 Hours ** 60 60 * TOEM than 2.5 µm) or * Beta attenuation 3 PM2.5 µg/m 5. Ozone (O3) 8 hours ** 100 100 *UV photometric µg/m3 1 hour ** 180 180 * Chemiluminescence * Chemical Method 6. Lead (Pb) Annual * 0.50 0.50 * AAS/ ICP Method after µg/m3 24 Hours ** sampling on EPM 2000 or equivalent filter paper *ED- XRF Using Teflon Filter 7. Carbon 8 hours ** 02 02 * Non Dispersive Infra Red Monoxide (CO) 1 hour ** 04 04 (NDIR) Spectroscopy mg/m3 8. Ammonia (NH3) Annual * 100 100 * Chemiluminescence µg/m3 24 Hours ** 400 400 * Indophenol Blue Method
A2.1_1 Sr. Pollutant Time Concentration in Ambient Air Weighted Industrial, Ecologically Methods of Measurement Average Residential, Sensitive Rural and Area (notify Other Area by Central Government) 9. Benzene (C6H6) Annual * 05 05 * Gas Chromatography Based Continuous Analyzer * Adsorption and Desorption followed by GC Analysis 10. Benzo(a)Pyrene Annual * 01 01 * Solvent extraction followed (BaP) – by HPLC /GC Analysis Particulate Phase only, ng/m3 11. Arsenic (As), Annual * 06 06 * AAS/ ICP Method after ng/m3 sampling on EPM 2000 or equivalent filter paper 12. Nickel (Ni) Annual * 20 20 * AAS/ ICP Method after ng/m3 sampling on EPM 2000 or equivalent filter paper
* Annual arithmetic mean of minimum 104 measurements in a year at a particular site taken twice a week 24 hourly at uniform intervals. ** 24 hourly or 08 hourly or 01 hourly monitored values, as applicable shall be compiled with 98% of the time in a year. 2% of the time, they may exceed the limits but not on two consecutive days of monitoring.
Note : Whenever and wherever monitoring results on two consecutive days of monitoring exceed the limits specified above for the respective category, it shall be considered adequate reason to institute regular or continuous monitoring and further investigation.
Sant Prasad Gautam [ADVT-III/4/184/09/Exty.]
Note : The notification on National Ambient Air Quality Standards were published by the Central Pollution Control Board in the Gazette of India, Extraordinary vide notification No(s). S.O. 384(E), dated 11th April, 1994 and S.O. 935(E), dated 14th October, 1998.
A2.2_2 Ministry of Environment and Forests NOTIFICATION S.O. 2151, New Delhi, the 17th June, 2005
WHEREAS the Water Quality Assessment Authority (WQAA) was constituted by the Central Government vide Order No. S.O. 583 (E) dated the 29th May, 2001 and No. S.O. 635 (E) dated the 27th October, 2004 to exercise powers under section 5 of the Environment (Protection) Act, 1986 (29 of 1986) for issuing directions and for taking measures with respect to matters referred to in clauses (ix), (xi), (xii) and (xiii) of sub-section (2) of section 3 of the said Act and to standardize method(s) for water quality monitoring and to ensure quality of data generation for utilization thereof and certain other purposes; AND WHEREAS it is necessary and expedient to evolve water quality assessment and monitoring protocol as directed by the Water Quality Assessment Authority in order to maintain uniformity in the procedure for water quality monitoring mechanism by all monitoring agencies, departments, Pollution Control Boards and such other agencies so that water related action plans may be drawn up on the basis of reliable data; AND WHEREAS the uniform process on water quality monitoring shall provide frequency of monitoring, procedure for sampling, parameters for analysis, analytical techniques, quality assurance and quality control system, infrastructure requirement for laboratories, procedure for data processing, reporting and dissemination and such other matters as the Central Government deems necessary for the said purpose, both for surface and ground water; AND WHEREAS due to the deterioration of the river water quality, health and livelihood of the downstream people are being severely affected and concerns are raised time and again; AND WHEREAS the immediate maintenance and restoration of ‘wholesomeness’ of the river water quality is the mandate under the Water (Prevention and Control of Pollution) Act, 1974 (6 of 1974) and that of maintenance of the ground water quality by the Central Ground Water Authority constituted under the provisions of the Environment (Protection) Act, 1986; AND WHEREAS sub-rule (4) of rule 5 of the Environment (Protection) Rules, 1986, provides that whenever it appears to the Central Government that it is in public interest to do so, it may dispense with the requirement of notice under clause(a) of sub-rule(3) of the said rule”; AND WHEREAS the Central Government is of the opinion that it is in public interest to dispense with the requirement of notice under clause (a) of sub-rule (3) of rule 5 of the said rules to issue the Order. NOW, THEREFORE, in exercise of the powers conferred by section 3 of the Environment (Protection) Act, 1986, the Central Government hereby makes the following order, namely:-
1. Short title and commencement:- a) This order may be called the Uniform Protocol on Water Quality Monitoring Order, 2005”. b) It shall come into force on the date of its publication in the Official Gazette.
2. Application:- It shall apply to all organizations, agencies and any other body monitoring surface and ground water quality for observance of uniform protocol on water quality monitoring.
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3. Definitions:- In this Order, unless the context otherwise requires – (1) “Agencies” means water quality monitoring agencies (government or non-government, local bodies) and other organizations including research and academic institutions involved in water quality monitoring of surface and ground waters; (2) “Authority” means the Water Quality Assessment Authority (WQAA) constituted under sub- sections (1) and (2) of section 3 of the Environment (Protection) Act, 1986; (3) “Baseline stations” means the monitoring location where there is no influence of human activities on water quality; (4) “Flux stations or Impact stations” means the location for measuring the mass of particular pollutant on main river stem for measuring the extent of pollution due to human interference or geological feature at any point of time and is necessary for measuring impact of pollution control measures adopted; (5) “Monitoring” means standardized measurement of identified parameters in order to define status and trends of water quality; (6) “Protocol” means a system of uniform water quality monitoring mechanism developed by the Water Quality Assessment Authority constituted under sub-sections (1) and (3) of section 3 of the Environment (Protection) Act, 1986; (7) “Quality Assurance Programme” means a programme described in paragraph 12 of this Order; (8) “Trend station” means the monitoring location designed to show how a particular point on a watercourse varies over time due, normally, to the influence of man’s activities; (9) “Water quality monitoring network” means a systematic planning for collection, preservation and transportation, storage, analysis of water samples and dissemination of data for national water bodies restricted to surface and ground water in the country.
4. Monitoring station and frequency of sampling:- (1) The frequency of sampling in respect of surface water shall be as follows:- a) all the stations shall be a combination of Baseline, Trend and Flux or Impact stations b) the Baseline stations shall be monitored four times a year for perennial rivers and lakes and three to four times a year for seasonal rivers. Trend stations shall be monitored with an increased frequency of once in a month i.e. twelve times in a year. Flux or Impact stations shall be monitored twelve to twenty-four times in a year depending upon pollution potential or importance of water use. c) all agencies shall follow the sampling frequency and parameters for analysis of surface water as mentioned in the Table – I given below:
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Table – I Frequencies and parameters for analysis of surface water samples
1 2 3 Type of Station Frequency Parameters Baseline Perennial rivers and lakes: (A) Pre-monsoon: Once a year Four times a year Analyse 25 parameters as listed below: (seasonal) a) General: Colour, Odour, Temperature, Seasonal rivers: pH, Electrical Conductivity (EC), Dissolved 3-4 times (at equal spacing) Oxygen (DO), Turbidity, Total Dissolved during flow period Solid (TDS) Lakes: b) Nutrients: Ammoniacal Nitrogen (NH4-N), Nitrite & Nitrate Nitrogen (NO + NO ) 4 times a year (seasonal) 2 3 Total Phosphate (Total P) c) Demand parameters: Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD) d) Major ions: Sodium (Na), Potassium (K), Calcium (Ca), Magnesium (Mg),
Carbonate (CO3) Bicarbonate (HCO3), Chloride (Cl), Sulphate (SO4) e) Other inorganic: Fluoride (F), Boron (B) and other location specific parameter, if any f) Microbiological: Total coliform and Faecal Coliform (B) Rest of the year (after the pre-monsoon sampling) at every three months interval Analyse 10 parameters: Colour, Odour,
Temperature, pH, EC, DO, NO2 + NO3 , BOD, Total coliform and Faecal Coliform Trend or impact Once every month starting A. Pre-monsoon: Analyse 25 parameters as listed or flux April-May (pre-monsoon) for baseline monitoring i.e. 12 times a year B. Other months: Analyse 15 parameters as listed below (a) General : Colour, Odour, Temp, pH, EC, DO and Turbidity
(b) Nutrients : NH3 - N, NO2 + NO3 , Total P (c) Organic Matter : BOD, COD (d) Major ions : Cl (e) Microbiological: Total and Faecal coliforms C. Micropollutant: Once in a year/pre monsoon. a) Pesticides – Alpha Benzenehexachloride (BHC), Beta BHC, Gama BHC (Lindane), OP-Dichlorodiphenyltrichloroethane (OP-
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DDT), PP-DDT, Alpha Endosulphan, Beta Endosulphan, Aldrin, Dieldrin, Carbaryl (Carbamate), Malathian, Methyl Parathian, Anilophos, Chloropyriphos b) Toxic Metals:- Arsenic (As), Cadmium (Cd), Mercury (Hg), Zinc (Zn), Chromium (Cr), Lead (Pb) Nickel (Ni), Iron (Fe) (The parameters may be selected based on local need) Note: I. The parameters mentioned in the above Table shall be the minimal requirement. This does not, however, restrict analysis of more parameters depending upon the specific requirements of the analyzing agency and its manpower availability. II. For lakes or reservoirs, monitoring of additional parameters, like total Kjeldhal Nitrogen, Chlorophyll, total Plankton count and productivity, shall be included in the list of parameters. III. If bio-monitoring is done in river or lakes or reservoirs, additional specific parameters are to be considered.
(2) Ground Water The frequency of sampling in respect of ground water shall be as follows: a. All stations shall be classified as Baseline stations b. 20-25% of Baseline stations shall be classified as Trend stations where there is a perceived problem. c. All agencies shall follow the sampling frequency and parameters for analysis of ground water as mentioned in the Table-2 given below:
Table – 2 Frequencies and parameters for analysis of Ground Water samples
1 2 3 Type of Station Frequency Parameters Baseline Twice a year A. Pre and Post Monsoon Season: Analyse 20 (Pre and post monsoon parameters as listed below: season) a. General: Colour, Odour, Temperature, pH, EC, TDS
b. Nutrients: NO2 + NO3 , Orthophosphate c. Demand Parameter: COD
d. Major Ions: Na+, K +, Ca++, Mg++, CO3--, HCO3-; CI, SO4, --%Na & SAR e. Other inorganics: F, B and other location- specific parameters, if any
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Trend Twice a year A. April-May: Analyse 20 parameters as listed for (Pre and post Baseline monitoring monsoon) B. Other times: Analyse 14 parameters as listed below:-
f. General: Colour, Odour, Temperature, EC, pH, TDS, %Na & SAR
a) Nutrients: NO2 + NO3, orthophosphate b) Demand parameter: COD c) Major ions: Cl d) Other inorganics: F,B e) Microbiological: Total coliform and Faecal coliform
C. Micropollutant (parameters may be selected based on local need): 2. Pesticides- Alpha BHC, Beta BHC, Gama BHC (Lindane), OP-DDT, PP-DDT, Alpha Endosulphan, Beta Endosulpham, Aldrin, Dieldrin, 2, 4-D, Carbaryl (Carbamate), Malathian, Methyl, Parathian, Anilphos, Chloropyriphos. 3. Toxic Metals – As, Cd, Hg, Zn, Cr, Pb, Ni, Fe (Pesticides and Toxic metals may be analysed once a year in pre monsoon on selected locations) Note:- I. The parameters mentioned in the above Table shall be the minimal requirement. This does not, however, restrict analysis of more parameters depending upon the specific requirements of the analyzing agency and its manpower availability. II. If Chemical Oxygen Demand (COD) value exceeds 20 mg/I, the sample shall be analysed for Biochemical Oxygen Demand (BOD) also.
5. Sample Collection (1) The procedure for sample collection in respect of surface water shall be as under: a) Samples for Baseline and Trend stations shall be collected from well-mixed section of the river or main stem 30 cm below the water surface using a Dissolved Oxygen (DO) sampler or weighted bottle. b) Samples for Impact stations shall be collected from the point of interest, such as bathing ghat, down stream of point discharge, water supply intakes and other sources. c) The Dissolved Oxygen (DO) in the sample shall be fixed immediately after collection and Dissolved Oxygen (DO) analysis shall be done either in the field or in laboratory. (2) The procedure for sample collection in respect of ground water shall be as under:
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a) Open dug wells, which are not in use or have been abandoned, shall not be considered as water quality monitoring station. However, such well could be considered for water level monitoring. b) Weighted sample bottle to collect sample from an open well about 30 cm below the surface of water may be used. The plastic bucket, which is likely to skim the surface layer only, shall not be used. c) Samples from the production tube wells shall be collected after running the well for about five minutes. d) Non-production piezometers shall be purged using a submersible pump. The purged water volume shall equal 4 to 5 times the standing water volume, before sample is collected. e) For bacteriological samples, when collected from tube wells or hand pump, the spout or outlet of the pump shall be sterilized under flame by spirit lamp before collection of sample in container.
6. Sample preservation and transportation (1) The type of containers and sample preservation to be adopted shall be as mentioned in the Table-3 below: Table – 3
1 2 3 Analysis Container Preservation General Glass, PE 40C, dark BOD Glass, PE 40C, dark
COD, NH3, NO2, NO3 Glass, PE H2SO4, PH<2 Coliform Glass, PE, Sterilised 40C, dark DO BOD bottle DO fixing chemicals Fluoride PE None P Glass None Pesticides Glass, Teflon 40C, dark
Toxic metals Glass, PE HNO3, PH<2
(2) Samples shall be transported to concerned laboratory as soon as possible, preferably within forty-eight hours of collection. (3) Analysis for coliforms shall be started within twenty-four hours of collection of sample. If time is exceeded, it should be recorded with the result. (4) Samples containing microgram /l metal level should be stored at 40C and analyzed as soon as possible. If the concentration is of mg /l level, it can be stored for up to 6 months, except mercury, for which the limit is 5 weeks. (5) Sample Identification for the water sample analysis for surface and ground water samples shall be as mentioned in the Form-I and Form-II.
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7. Sample records 1) Each laboratory shall have a bound register, which shall be used for registering samples as they are received. A format for sample receipt register is annexed as Form-III. 2) The Laboratory In-charge shall maintain a register for assignment of work to specific analyst.
8. Analytical techniques Each agency shall follow the analytical techniques prescribed in the Standard Methods for Analysis of Water and Wastewater published by American Public Health Association (Latest Edition) or Bureau of Indian Standard(BIS) Methods for Testing Water and Wastewater-methods of sampling and testing (physical and chemical) (IS:3025)
9. Analysis records and data validation A recommended format for recording data including all parameters except toxic metals and trace organics is enclosed as Form – IV. Report of heavy metals and trace organics as per Table 2 may be recorded separately. Validation checks should be performed in the laboratory on completion of the analysis. The results of laboratory analyses shall be entered in the format provided in Form – II for validation.
10. Manpower requirements in laboratories The manpower requirements shall be optimized by the concerned monitoring agencies in order to get the maximum utilization of mandays, for timely completion of analysis.
11. Data Processing, Reporting and Dissemination Each monitoring agency shall process the analytical data and report the data after validation to the Data Centre at the Central Pollution Control Board. The Central Pollution Control Board shall store the data and disseminate through website or electronic mail to various users on demand.
12. Quality Assurance and Accreditation of Laboratories The Quailty Assurance Programme for the laboratories of various agencies shall contain a set of operating principles, written down and agreed upon by the organization, delineating specific functions and responsibilities of each person involved. Each laboratory of water quality monitoring agencies shall follow the guidelines of Quality Assurance Programme prescribed by their respective Central Laboratory or Headquarters and shall participate in Inter Laboratory Quality Assurance Programme like Proficiency Testing (PT) organized by them or any other agency on regular basis. The Water Quality Laboratories shall seek recognition from the Ministry of Environment and Forests, Government of India or accreditation from National Accreditation Board for Testing and Calibration Laboratories (NABL) under the Ministry of Science and Technology, Government of India.
[F.No.15011/8/2004-NRCD] M.SENGUPTA, Advisor
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FORM – I Sample identification for surface water samples analysis and record
Sample Code Observer Agency Project Date Station Code Time Parameter Code Container Preservation Treatment Glass PVC PE Teflon None Cool Acid Other None Decant Filter (1) General (2) Bacteriology (3) BOD
(4) COD, NH3, NO3 (5) Toxic Metals (6) Trace Organics
Source of Sample Water Point Approach Medium Matrix o River o Main Current o Bridge o Water o Fresh o Drain o Right Bank o Boat o Suspended Matter o Brackish o Canal o Left Bank o Wading o Biota o Salt o Reservoir (Lake o Sediment o Effluent / tank / Ponds) Sample Type o Grab o Time Comp o Flow comp o Depth-integ o Width-integ Sample Device o Weighted bottle o Pump o Depth Sampler Field Determination Temp oC pH EC micromhos/cm DO mg/l Odour code (1) Odour free (6) Septic Colour code (1) Light brown (6) Dark green (2) Rotten eggs (7) Aromatic (2) Brown (7) Clear (3) Burnt sugar (8) Chlorinous (3) Dark brown (8) Other(specify) (4) Soapy (9) Alcoholic (4) Light green (5) Fishy (10) Unpleasant (5) Green Remarks Weather o Sunny o Cloudy o Rainy o Windy Water vel (m/sec) o High(>0.5) o Medium(0.1 – 0.5) o Low(<0.1) o Standing Water Use o None o Cultivation o Bathing & Washing o Cattle washing o Melon / vegetable farming in river bed o Organised water supply
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FORM – II Sample identification for ground water samples
Sample Code Observer Agency Project Date Station Code Time Source of Sample o Open dug well o Hand pump o Tube Well o Piezometer Parameter Code Container Preservation Treatment Glass PVC PE Teflon None Cool Acid Other None Decant Filter (1) General (2) Bacteriology (3) BOD (4) COD (5) Toxic Metals (6) Trace Organics Field Determination Temp oC pH EC micromhos/cm DO mg/l Odour code (1) Odour free (6) Septic Colour code (1) Light brown (6) Dark green (2) Rotten eggs (7) Aromatic (2) Brown (7) Clear (3) Burnt sugar (8) Chlorinous (3) Dark brown (8) Other(specify) (4) Soapy (9) Alcoholic (4) Light green (5) Fishy (10) Unpleasant (5) Green If well is purged, complete below Office Well Data Diameter Q cm Depth D m Static Water Level (Avg.) SWL m Water Column (D-SWL) H m Initial Volume Well V L Projected Pump Discharge PQ L/s Projecting time of pruging (V/PQ) PT min Field Flow Measurement Static Water Level on arrival SWL m Actual pump setting M Purging duration min Pump discharge before sampling Q L/min Pump discharge after sampling Q L/min Volume purged V L Dynamic water level DWL m Field Chemical Measurement Time at start of sampling started T (oC) EC (micromhos/cm) pH + 10 min + 20 min + 30 min +40 min
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FORM-III Sample Record for Analysis
Date / Date / Station Project Collecting Preservation Parameter Lab. time time Code agency / Code Sample received collected collector No. at lab 1 2 3 4 5 6 7 8
Sample receipt register Note: Column (3) gives the station code conventionally followed by the monitoring agency Column (4) gives the project under which the sample is collected Column (7) corresponds to the parameter(s) code given in the sample identification form Column (8) gives the laboratory sample assigned to the sample as it is received in the laboratory. Note that the numbering has two parts separated by hyphen. The first part is assigned in a sequential manner as samples are received from various stations. If two samples are collected at the same time from a station for different sets of analysis, the first part of the number is the same. The second part corresponds to the parameter code as given in the sample The result of the analysis of all the samples having the same first part of the code would be entered in the data entry system as one sample having the same station code and time of sample collection
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ANNEXURE II
Standard Operating Procedure for Water Sampling
Sample Parameters Sample Collection Storage/Preservation Size (ml) Grab sampling pH 50 On site analysis Plastic/glass container Electrical Grab sampling 50 On site analysis Conductivity Plastic/glass container Grab sampling Turbidity 50 On site analysis Plastic/glass container Grab sampling Refrigeration, can be Total Dissolved Solids 100 Plastic/glass container stored for 7 days Alkalinity Plastic/glass containers 100 Refrigeration, 14 days Grab sampling Add HNO to pH <2, Hardness 100 3 Plastic/glass container refrigeration; Grab sampling Chlorides 50 Not required; 28 days Plastic/glass container Grab sampling Sulphates 100 Refrigeration, 28 days Plastic/glass container Nitrates Plastic Containers 100 Refrigeration, 48 hrs Add H SO to pH<2, Ammonical Nitrogen Plastic/glass containers 100 2 4 refrigeration; 28 days Phosphate Plastic/glass containers 100 Refrigeration; 48 hrs. Grab sampling BOD 500 Refrigeration, 48 hrs Plastic/glass container Trace Metals (Hg, Cd, Plastic/glass containers Add HNO to pH <2, 100 3 Cu, Fe, Zn, Pb ) rinse with 1+1 HNO3 Grab sample; 6 months Microbiology (TC, FC) Sterile glass bottle 100 Refrigeration; 24 hrs
Source: Standard Methods for the Examination of Water and wastewater, Published by APHA, AWWA, w.e.f. 20th Edition, 2005. ANaNEXURE III
Methodology for Sampling and Analysis of Water
Sr. Parameters Methods (APHA) No. 1 pH APHA-4500-H+ 2 Colour APHA-2120 C 3 Odour IS:3025, part-4 4 Temperature APHA-2550 B 5 Electrical Conductivity APHA-2510 B 6 Total Dissolved Solids APHA-2540 C 7 Turbidity APHA-2130 B 8 Alkalinity APHA-2320 B 9 Total Hardness APHA-2340 C 10 Chlorides APHA-4500 Cl- -2 11 Sulphates APHA-4500 SO4 - 12 Nitrate APHA-4500 NO3 13 Ammonical Nitorgen APHA-4500 NH3 14 Total Phosphate APHA-4500 P 15 Dissolved Oxygen (DO) APHA-2500 O 16 BOD APHA-5210 B 17 Coliforms APHA-9215 D Source: Standard Methods for the Examination of Water and wastewater, Published by APHA, AWWA, w.e.f. 20th Edition, 2005.
Annexure III
Water Quality Criteria- CPCB
Class of Designated-Best-Use Criteria water • Total Coliforms Organism MPN/100ml Drinking Water Source shall be 50 or less without conventional pH between 6.5 and 8.5 A • treatment but after • Dissolved Oxygen 6mg/l or more disinfection • Biochemical Oxygen Demand 5 days 20°C 2mg/l or less • Total Coliforms Organism MPN/100ml shall be 500 or less Outdoor bathing pH between 6.5 and 8.5 B • (Organised) • Dissolved Oxygen 5mg/l or more • Biochemical Oxygen Demand 5 days 20°C 3mg/l or less • Total Coliforms Organism MPN/100ml Drinking water source shall be 5000 or less after conventional pH between 6 to 9 C • treatment and • Dissolved Oxygen 4mg/l or more disinfection • Biochemical Oxygen Demand 5 days 20°C 3mg/l or less pH between 6.5 to 8.5 Propagation of Wild life • D Dissolved Oxygen 4mg/l or more and Fisheries • • Free Ammonia (as N) 1.2 mg/l or less • pH betwwn 6.0 to 8.5 Irrigation, Industrial • Electrical Conductivity at 25°C micro Cooling, Controlled E mhos/cm Max.2250 Waste disposal • Sodium absorption Ratio Max. 26 • Boron Max. 2mg/l Below-E Not Meeting A, B, C, D & E Criteria Source: http://cpcb.nic.in/Water_Quality_Criteria.php Annexure 6.1
Methods Adopted for Soil Analysis for Mechanical Properties and Significance of These Parameters
For evaluation of soil properties to find the causes of soil erosion and land slides occurring frequently in the study area of Rohtang pass, the soil samples at selected locations were tested for specific mechanical properties. The selected parameters, the methods adopted and significance of parameters are presented in following table:
Parameter Method Specifications of Significance method Grain size analysis Sieve IS : 2720 (Part 4)- Indicates the quantity of gravel, sand, Analysis 1985 silt and clay which are responsible for Particle size Hydrometer, the cohesive property or binding distribution USDA Textural capacity of the particles of the soil. Triangle Atterberg's Limits: The moisture conditions viz. liquid limit, plastic limit, along with shrinkage limit are referred to as the "Atterberg Limits", The Atterberg limits are used to identify the soil's classification and allows for the use of empirical correlations for some other engineering properties Liquid limit % Mechanical IS : 2720 (Part 5)- The moisture content, expressed as a method 1985 percentage of the weight of the oven- dried soil, at the boundary between the liquid and plastic states of consistency.
Plastic limit % Mechanical IS : 2720 (Part 5)- The moisture content, expressed as a method 1985 percentage of the weight of the oven- dry soil, at the boundary between the plastic and semisolid states of consistency.
Plasticity index % A dimensionless number: the By calculation. numerical difference between its Soils with a high PI tend to be liquid limit and its plastic limit. The clay, those with a lower PI tend to plasticity index is the size of the be silt, and those with a PI of 0 range of water contents where the soil (non-plastic) tend to have little or exhibits plastic properties. no silt or clay.
A6.1_1
Parameter Method Specifications Significance of method Bulk density Soil density IS: 2720 • Bulk density of soil is an (g/cc) (Part-7) – 1987 indicator of soil compaction Dry density - and depends greatly on the (g/cc) mineral make up of soil. It is Specific IS: 2720 calculated as the dry weight Gravity (Part3/ of soil divided by its Section 1) – volume. 1987 • Dry density means the density of the soil when it is dry e.g. there is no water. • Specific gravity G is defined as the ratio of the weight of an equal volume of distilled water at that temperature both weights taken in air. • The knowledge of specific gravity is needed in calculation of soil properties like void ratio, degree of saturation etc. Free swell Free swell or differential IS: 2720 Used for Prediction of swelling index % free swell, also termed as (Part 40) – characteristics to measure Swell free swell index, is the 1977 potential and swell pressure increase in volume of soil With their ability to swell and without any external shrink in relation to the constraint when subjected to environment's water content, submergence in water. expansive soils are considered as geonatural hazards and form a challenge to geotechnical and construction engineers. Addressing the problems associated with these soils Direct shear The strength of a material is IS: 2720 This test is performed to test the greatest stress it can (Part 13). determine the consolidated- sustain; The direct shear test drained shear strength of a measures shear strengths as ASTM sandy to silty soil. a function of normal stress. D3080 Period. The test does not measure “friction angle” or “cohesion,” as these values are parameters that are derived from the test results.
A6.1_2
Parameter Method Specifications Significance of method Cohesion Cohesion is the shear ASTM Indicates soil consistency. (kg/cm2) strength or the force that D5321 binds together like particles Tests are often done to determine in the structure of a soil. the soil's cohesiveness before Angle f ASTM building construction. Friction angle in direct D3080-04 Consideration of “friction angle” shear test and “cohesion” simply as mathematical parameters used to describe shear strength data is of great benefit to practitioners
Safe Bearing - I.S. 6403 – Bearing capacity is the power of Capacity 1981 foundation soil to hold the forces (t/m2) from the superstructure without undergoing shear failure or excessive settlement.
Factors Influencing Bearing Capacity
Bearing capacity of soil depends on many factors. The following are some important ones.
1. Type of soil 2. Unit weight of soil 3. Surcharge load 4. Depth of foundation 5. Mode of failure 6. Size of footing 7. Shape of footing 8. Depth of water table 9. Eccentricity in footing load 10. Inclination of footing load 11. Inclination of ground 12. Inclination of base of foundation
A6.1_3 Annexure 6.2
RS & GIS Based Landslide Hazard Zonation of Mountainous Terrains A Study from Middle Himalayan Kullu District, Himachal Pradesh, India
Vishwa B. S. Chandel1, Karanjot Kaur Brar2, Yashwant Chauhan3 Email : [email protected] 1. Map Curator, Centre of Advanced Study in Geography, Department of Geography, Panjab, University, Chandigarh 2. Associate Professor, Centre of Advanced Study in Geography, Department of eography, Panjab University, Chandigarh 3. Product Specialist (Remote Sensing), ESRI Muscat, Oman,
ABSTRACT Land slides are short Lived and suddenly occurring phenomena; it is just a hazard when it occurs in an uninhabited place, however it turns into a disaster causing extraordinary landscape changes and destruction of life and property when it occurs in the vicinity of human habitation. Land slides are common and cause massive damage in tectonically active Himalayas. The western Himalayan district of Kullu with a location on the southern side of Pir panjal mountain range has an established history and inherent susceptibility to massive land slides. Using remote sensing and GIS a land slide Hazard Zonation can be worked out.
The study conducted by Vishwa B S Chandel et al has used the satellite imageries of LANDSAT ETM+, IRS P6, ASTER along with Survey of India (SOI) topographical sheets formed the basis for deriving baseline information on various parameters like slope, aspect, relative relief, drainage density, geology/lithology and land use/land cover. The weighted parametric approach was applied to determine degree of susceptibility to landslides. The landslide probability values thus obtained were classified into no risk, very low to moderate, high, and very high to severe landslide hazard risk zones. The results show that over 80 per cent area is liable to high severe landslide risk and within this about 32 per cent has very high to severe risk.
Results The susceptibility to landslides is inherent in the natural characteristics of the landscape and there is a definite relationship between landslide occurrence and geo-physical setup of the area. The high slope angles, drainage density, high local relief and geological structure produce suitable conditions for landslide occurrence; the torrential rainfall in monsoon season is invariably the immediate trigger. Out of total of 49 landslides during 1971-2009, nearly 63.27 per cent occurred in monsoons; 26.53 per cent were recorded during winter months (January- March) while pre and post monsoon seasons together recorded less than 10 per cent landslides. In addition, the past events show that these have close association with the land use and were confined to the built-up (roads) and agricultural lands. The intensification of human activities, encroachment on vulnerable land, uncontrolled settlement and rampant expansion of roads adds to landslide vulnerability. It is pertinent to note that landslide activity is largely confined to the inhabited part of the district primarily in the vicinity of the rivers and roads and this is
A6.2_1 substantiated by field visits and data. These are the prime locations of all human activities and this enhances the risk potential of this disaster.
Landslide Hazard Analysis: Conclusion/Findings The analysis shows that almost entire district is prone to landslide risk of varying magnitude. Over 80 per cent area is liable to high-severe landslide risk and within this about 32 per cent has very high to severe risk while about 48 per cent of the total area has high risk of landslide occurrence (Table 1). Such areas include southern slopes of Pir-Panjal range in Rohtang- Manali area, southern off-shoot of Pir-Panjal forming western border of Kullu valley and slopes on the northern parts of Parbati river valley particularly in the areas around Malana valley (map 8). Another section of high-severe risk comprise of Kullu-Larji-Rampur (KLR) geological window which spread over Hurla, Sainj and Banjar areas of district. The rocks are not only highly deformed but the area also possesses active faults/thrusts. The northern part of Nirmand tahsil also falls in this very high landslide risk class.
Table 1: Kullu district: Landslide hazard zones Landslide Risk Category Area (km.2) Area (per cent)
1 No Risk 23.22 0.42 2 Low-Moderate 1068.65 19.42 3 High 2650.19 48.16 4 Very High-Severe 1960.94 32.00 Total 5503 100 Source: ASTER DEM, LANDSAT ETM+ (2005); IRS P6 LISS III (2005)
Source: ASTER DEM, LANDSAT ETM+ (2005); IRS P6 LISS III (2005),Map 8
A6.2_2 The present study demonstrates high degree of hazarduousness of Kullu district of Himachal Pradesh, India. The higher degree of landslide hazard is associated with geo-physical elements especially slope, relative relief and lithology of the area. The presence of faults, particularly in the vicinity of human occupancy enhances vulnerability. Vulnerability is compounded by mindless and rampant expansion of settlement onto vulnerable land and ambitious road construction that aids this settlement. In addition, anthropogenic activities play a significant role in triggering such events.
______Reference: INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES, Volume 2, No 1, 2011
A6.2_3 Annexure 7.1
Medicinal Flora in Lahul District
Plants Local English Habitat Uses Name Name Aconitum Padish Indian Commonly found in Root has medicinal value, heterophylum Atees alpine and sub-alpine extract used against fever regions of Himalaya at an altitude of 1800 – 4500 m Artemisia Gandha Sea Worm- Drier parts of salt Leaf decoction is in maritima wood marshes[17] in sand intermittent fever, yields and shingle santinin trade Morchella Guchhi Common Fruit bodies are Sought-after as good edible esculenta morel sometimes found fungi, Extracts from the fruit solitary, but more often bodies in groups, on the have antioxidant properties. ground in a variety of habitats. A preference for soil with a limestone base Picrorhiza Karoo, Kuru Found in the higher Roots of medicinal value, used kurroa Katuka mountain elevations at against scorpion stings, has 2700 - 3600 metres. anti-inflammotary activity Himalayas from Kashmir to Sikkim Thymus Ban Creeping Found in Dry The leaves, and especially the serphyllum ajwain Thyme grassland, usually on essential oil contained in them, calcareous soils are antiseptic, deodorant, disinfectant and expectorant Jurinea Dhoop Juniper Found in western Root used as Poultice; macrocephala Himalayas form Stomachic. A decoction of the Kashmir to Kumaon root is cordial. It is given in the region treatment of colic and puerperal fever. The juice of the roots is used in the treatment of fevers. The bruised root is applied as a poultice to eruptions. The root extract is used as an incense
A7.1_1 Plants Local English Habitat Uses Name Name Aconitum Tilla Monkshood Shrubberies and open The entire plant is used in violaceum slopes, 3600 - 4800 Tibetan medicine, it is said to metres from Pakistan have a bitter taste and a to C. Nepal cooling potency. Antidote, anti-inflammatory and febrifuge, it is used in the treatment of snake and scorpion bites, contagious infections and inflammation of the intestines Podophyllum Bankakri Himalayan Scrub forests and Rhizomes and roots are emodi May Apple alpine meadows, cholagogue, cytostatic and usually in humus rich purgative soils, 2000 - 3500 metres in the Himalayas. Very abundant in fir forests in Kashmir Saussurea Kuth Costus/ Kut Found in the alpine Root used as antioxidant, lappa root regions in moist areas diuretic, asthma and of open slopes inflammation. Also used as adjunct for cancer treatment Carum carvi Jeera Carraway Found in north Dried fruits are used as spice Himalayan region. and flavouring agents. Fruits Cultivated as winter are stomachic and carminative. crop in plains and lower hills and summer crop in high hill zone Crocus Kesar Saffron Found in cold regions Used for colouring butter, sativus of H.P. subtropical cheese, confectionary etc. used climate zones of as nerve sedative, Kangra and Kinnaur emmenagogue, stimulant, between Oct-Dec stomachic, abortifacient and remedy for catarrhal affections of children Jurinea Dhoop Guggal Distributed in Chamba, Aromatic roots used as incense dolomiaea Dhoop kangra, Kinnaur, in houses, temples and Shimla, Kullu and religious ceremonies. Roots Chambal- Spiti district are considered to be stimulant between Sept. – Oct. and given in fever after child birth. Bruised roots are applied to eruptions and decoction is given in colic.
A7.1_2 Plants Local English Habitat Uses Name Name Nardostachys Jatamansi/ Indian Found in Alpine Rhizomes are tonic, stimulant, jatamansi Batchir Nard Himalaya at an altitude anti spasmodic, diuretic, of 3000-5000 m deabstruent, and stomachic, between July- Sept. laxative. Infusion of rhizome is useful in epilepsy, palpitation of heart and chorea. Root extract shows sedative properties Rosa Shatpatri Damask Found in temperate and Oil is used in perfumery and damascena rose sub tropical type of for flavouring food products, climate between tobacco, and alcoholic liquors. March- June Rose oil used for treatment of gall stone. Rose water used for washing eyes Thymus Ban Wild thyme Found in Himalayas at Shoots used for flavouring non linearis ajwain altitude of 1500-4500 alcoholic beverages. Posses’ m between March- Oct. antispasmodic, antiseptic, expectorant, carminative, anthelumintic and stimulant properties. Seeds are given as vermifuge Viola odorata Banafsaj Sweet Found at an altitude of Herb is expectorant, Violet 1500- 1800 m between diaphoretic, antipyretic and April- July diuretic. Flowers are emollient, demulcent and household remedy for coughs, sore throat, hoarseness and ailments of infants. Leaves are said to relieve pain due cancerous growths particularly of mouth and throat Source : Working Plan Lahul district & discussion with Divisional Forest Officer (DFO- Mr. Chandel)
A7.1_3 Annexure 9.1 Ground Truth Survey (Rohtang Pass)
Plate I: Built-up in Palchan (Lat 32º 18’ 33”N and Long 77º 10’ 31”E)
Plate II: Built-up and new construction activities in Kothi (Lat 32º 19’ 03”N and Long 77º 11’ 22”E)
Plate III: Forest (Tosh) along Rohtang Pass Plate IV: Hydro Electric Marhi Project at Kothi (Lat 32º 19’ 17” N and Long 77º 11’ 37” E) (Lat 32º 19’ 59”N and Long 77º 11’ 49”E)
A9.1_1
Plate V: Temporary shops in Gulaba Plate VI: BRO camp and office, Gulaba (Lat 32º 19’ 31”N and Long 77º 12’ 05”"E) (Lat 32º 19’ 23”N and Long 77º 12’ 05”E)
Plate VII: Exposed rock near Raila Fall Plate VIII: Storage on Beas nallah for Marhi PH (Lat 32º 19’ 57”N and Long 77º 12’ 56”E) (Lat 32º 20’ 55”N and Long 77º 13’ 16”E)
Plate IX: Build-up in Marhi (Lat 32º 20 57”N and Long 77º 13’ 04”E)
A9.1_2
Plate X: Landslide on Rohtang Pass (Lat 32º 21’ 32”N and Long 77º 13’ 43”E)
Plate X: Grass land near Marhi Plate XI: Rohtang top (Gompa) (Lat 32º 21’ 00”N and Long 77º 13’ 10”E) (Lat 32º 22’ 17”N and Long 77º 14’ 47”E)
(Palchan to Manali)
Plate XII: Apple orchard near confluence of Plate XIII: Forest along road (Kulang) Beas river and Solang nala (Lat 32º 17’ 43”N and Long 77º 10’ 57”E) (Lat 32º 18’ 19”N and Long 77º 10’ 56”E)
A9.1_3 (Manali)
Plate XIV: Confluence of Beas and Manalashu Plate XV: Forest around Circuit House, Manali (Lat 32º 15’ 18”N and Long 77º 11’ 21”E) (Lat 32º 15’ 00”N and Long 77º 11’ 09”E)
Plate XVI: Forest (Log hut area, Manali) Plate XVII: Apple orchard (Log hut area, Manali) (Lat 32º 14’ 59”N and Long 77º 10’ 26”E) (Lat 32º 14’ 59”N and Long 77º 10’ 33”E)
Plate XVIII: Forest along Manalashu river Plate XIX: Forest around Hadimba temple (Lat 32º 15 04”N and Long 77º 10’ 41”E) (Lat 32º 14’ 55”N and Long 77º 10’ 51”E)
A9.1_4
Plate XX: Forest near Wildlife Information Centre (Lat 32º 14’ 51”N and Long 77º 11’ 21”E)
Plate XXI: Forest along Beas river Plate XXII: Manali Model Town (Lat 32º 15 13N and Long 77º 11’ 17”E) (Lat 32º 14’ 36”N and Long 77º 11’ 33”E)
Plate XXIII: Bridge on Beas river (Bypass) Plate XXIV: Open land (Manali potato ground) (Lat 32º 14’ 46”N and Long 77º 11’ 23”E) (Lat 32º 13’ 59”N and Long 77º 11’ 18”E)
A9.1_5 Annexure 9.2
Land Use Land Cover (LU/LC) Classification Scheme (NRSA, 1995)
Sr. Level - I Level – II No. 1. Built-up Land 1.1 Towns/cities 1.2 Villages 1.3 Road/Railway
2. Agricultural 2.1 Crop land Land 2.2 Fallow / Plantation
3. Forest 3.1 Evergreen/Semi-evergreen forest 3.2 Deciduous forest 3.3 Scrub Forest 3.4 Forest blank 3.5 Forest plantation 3.6 Mangrove 3.7 Cropland in Forest
4. Wasteland 4.1 Salt affected land 4.2 Waterlogged land 4.3 Marshy/Swampy land 4.4 Gullied/Ravinous land 4.5 Land with or without scrub 4.6 Sandy area (coastal and desert) 4.7 Mining / Industrial Wasteland 4.8 Barren rocky/Stony Waste/sheetrock area
5. Water bodies 5.1 River/Stream 5.2 Tank/Canal 5.3 Lake/Reservoir
6. Others 6.1 Shifting cultivation 6.2 Grassland/Grazing land 6.3 Salt Pans 6.4 Snow cover/Glacial area
A9.1_6