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MATERIALS AND METHODS
2.1. Study area
The Mavallipura landfill site is located north of Bangalore, India
at Latitude 13 500 North, Longitude 77360 East in the state of
Karnataka. This landfill site has been used as a processing site for
the municipal solid waste generated from Bangalore city. The
average annual rainfall is 978 mm. Rainy seasons are from June to
September and the secondary rainy season is from November to
December. Mavallipura village is located about 20 Kilometer away
from Bangalore. About 100 acres of land in and around the village
are used for dumping Bangalore's MSW by the Bruhat Bengaluru
Mahanagara Palike (BBMPeGreater Bangalore Municipal Corporation) that began accepting waste from 2005. Mavallipura landfill
site is about 40.48 ha located in Mavallipura village, of which
approximately 35 acres is used for landfill. The landfill was maintained at M/s Ramky Environmental Engineers commissioned in
2007 which had the capacity to sustain about 600 tonnes of waste.
However, the BBMP has been sending almost 1000 tonnes of
garbage from Bangalore city every day. Citizens around Mavalipura
village demand that the landfill site must be stopped immediately
as it is illegal and unscientifically managed and thus it is nowclosed
for land filling. A little soil cover (0.3 m thickness) has been applied
on a daily basis, and MSW is dumped in an unscientific manner that
has resulted in steep, unstable slopes, leachate accumulationwithin
the MSW mass, and leachate runoff into nearby water bodies such
as pond and opened well.
2.2. Sampling and physico-chemical analysis
Fig. 1 gives the view of (a) sampling locations points on google
earth and also shows (bef) the location of sample points in
Mavallipura landfill site. In order to observe the spatiotemporal
variations of the geochemistry of leachate and ground waters, three
undiluted representative leachate samples (L1 leachate collected
directly from landfill, L2 leachate collected from landfill sump, L3
leachate collected from landfill pond) and another two samples of
water from the nearby pond (P4) and open well (G5) were collected
from downstream of Mavallipura landfill site in the month of April
2012. Three replicates of each of the sample were analyzed for
every location. After the sample collections, these landfill sites were
abandoned and were restricted to any further treatment and
disposal due to agitation in the nearby local communities. Therefore further sampling was not possible, and the analysis was carried
out for only one season. The samples were collected in labeled clean
bottles that were rinsed thrice before sample collection. The pH and
electrical conductivity (EC) were recorded on site at the time of
sampling with digital pH meter and digital EC meter, respectively.
For the analysis of biological oxygen demand (BOD), 300 ml capacity BOD bottles were used for the collection of samples. For
heavy metal analyses, samples were separately collected in prewashed polyethylene containers of 100 ml capacity and acidified
(few drops of concentrated nitric acid were added to the leachate
sample) onsite to avoid precipitation of metals. The samples were
then transported in cooler boxes at a temperature below 5 C
immediately to the laboratory. Leachate samples was stored in a
refrigerator at 4 C before proceeding with the laboratory analysis.
Physico-chemical parameters, ionic parameters, trace elements
analysis was carried out according to standard methods for the
examination of water and wastewater unless otherwise stated
(APHA, 1998).
2.3. Statistical analysis
Univariate analysis was performed to know the nature of the
sample and extent of spread across mean. Correlation coefficient (r)
is computed to explore significant relationships between changes
in physico-chemical variables against biological variables (bacterial
and algal communities). Multivariate analysis - Detrended Correspondence Analysis (CCA) was performed to understand transitions
in biological communities with the varying physico-chemical variables to know relationships among them and identifying the most
impacting drivers. Cluster Analysis (CA) was performed in order to find out the spatial similarity and patterns across sites. These statistical analyses were carried out using open source statistical
package PAST 2.14 (downloaded from http://www.nhm.uio.no/
norlex/past/download.html).
2.4. Scanning electron microscopy (SEM)
The dried suspended solids in leachate were mounted on stubs
with a carbon-impregnated film and sputtered with a 15 nm layer
of gold coating. Imaging and observations were conducted in the
FEI ESEM Quanta 200 (3 imaging modes: HV; LV and ESEM) through
a Quanta LV/ESEM (at high pressures with a standard secondary
[EvehateThorley] and solid state scatters detector) as per discussed
protocols (Mahapatra et al., 2014). Specimens were examined with
a working distance of 10 mm and a low accelerating voltage of 10/
12 kV to reduce beam damage.
2.5. Energy dispersive X-ray analysis (EDAX)
Leachate samples were filtered, and the residue was dried with
vacuum drier. The samples were then subjected to energy dispersive analysis by X-rays (EDAX) employing a Quanta LV (Environmental SEM: at high pressure, with a standard secondary
[EvehateThorley] and solid state scatter detector) attached to Energy Dispersive X-ray analysis with an ultra thin window detector
(EDAX) for the determination of composition of elements. The
High-resolution SEM equipped with a Schottky field emission
source with high voltage variable between 200 V and 300 kV was
used for taking images of mineral particles as per methods used
earlier (Mahapatra et al., 2013a).
2.6. Microbiological analysis
50 ml of leachate and water samples were fixed with 70%
alcohol. Microscopic analysis especially algae was performed using
Light Microscope (Lawrence and Mayo) at 40 with the help of
morphological keys as per literature (Prescott, 1959; Desikacharya,
1959). Keys include external appearance, colour, morphological
characteristics, size, structure, and orientation of chloroplast,
pigment colouration, etc. Images were captured using Caliper Pro
software and DIC (Digital Interference Contrast) microscope. Algal
images were taken with 100 oil immersion lens. Drop count
method was employed for counting algal population (Mahapatra
et al., 2013a; Mahapatra, 2015). The relative abundance of algal
communities was examined. Samples collected were concentrated
by centrifuging 15 ml volume. Algae were enumerated using
representative 20 ml of the concentrated sample, where it was
placed over the slides with cover slips for microscopic observations
and density was computed by the ratio of a number of cells counted
in the given quantity of water sample. Bacterio-plankton population was analyzed by first filtering the collected samples with
2.5 mm sieve and then through microscopy.
2.7. Leachate pollution index (LPI)
LPI formulation process involves selecting variables, deriving
weights for the selected pollutant variables, formulating their subindices curves, and finally aggregating the pollutant variables to
arrive at the LPI (Kumar and Alappat, 2003). The rating was done on
a scale of‘1’ to ‘5’. The value ‘1’ was used for the parameter that has
lowest relative significance to the leachate contamination while
value ‘5’ was to be used for the parameter that has highest relative
significance (Kumar and Alappat, 2003). The LPI is calculated using
the following equations:
 .............................. (1)
where LPI ¼ the weighted additive LPI, Wi ¼ the weight for the ith
pollutant variable, Pi ¼ the sub-index score of the ith leachate
pollutant variable, n ¼ number of leachate pollutant variables used
in calculating LPI. Weights are so selected that,
 .................................... (2)
However, when the data for all the leachate pollutant variables
included in LPI are not available, the LPI can be calculated using the concentration of the available leachate pollutants. In that case, the
LPI can be calculated by the equation:
 ............................. (3)
where m is the number of leachate pollutant parameters for which
data are available, but in that case, m < 18 and SW < 1 contamination from the pollutant to the overall leachate pollution. LPI
values have grades that represent the overall leachate contamination potential of a MSW landfill. It is an ascending order scale index;
wherein a lower index value indicates a good environmental condition. The Assessment of leachate quality at any early stage may be
undertaken to (a) to identify whether the solid waste leachate are
hazardous, (b) to identify a suitable landfill design, (c) to develop a
sustainable leachate treatment process and d) to foresee the impacts of leachate on ground water by adopting various monitoring
and surveillance strategies.
2.8. Water quality index (WQI)
Water Quality Index is calculated based on various important
parameters like pH, electrical conductivity, TDS, total alkalinity,
total hardness, total suspended solids, calcium, magnesium, chloride, nitrate, sulphate, dissolved oxygen and biological oxygen demand. By using standards of drinking water quality recommended
by the Bureau of Indian Standards (BIS), Indian Council for Medical
Research (ICMR) and World Health Organization (WHO). The unit
weight arithmetic index (Brown et al., 1972) was used for the
calculation of WQI of the water body. Furthermore, the quality
rating of sub-index (qn) was calculated using the following
expression.
 .......................... (4)
where,
qn ¼ Quality rating for the nth water quality parameter
Vn ¼ Estimated value of the nth parameter at a given sampling
station
Sn ¼ Standard permissible value of the nth parameter.
Viw ¼ Ideal value of the nth parameter [i.e. zero for all parameters except the pH and dissolved oxygen (7 and 8 mg/l
respectively)]. Water Quality Index was calculated from the
quality rating with unit weight linearly.
 ............................ (5)
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