Greetings from Blue Yamuna
A Foundation Dedicated to Turn the Yamuna Water Blue
The Role of Environmental Indicators in Mining Operations
Subijoy Dutta, PE
Institute for Urban Environmental Research, GWU
1496 Harwell Ave., Crofton, MD 21114, Phone: 202-994-2781; Email:
subijoy at msn dot com
Elizabeth F. Wells, PhD
Dept. of Biological Sciences, George Washington University, Lisner Hall, Rm.
348, 2023 G. Street NW, Washington, DC 20052, Ph: 202-994-6970; e-mail:
efwekks at gwu dot edu
Abstract
Watersheds and airsheds are the major focus of various environmental
programs in federal, state, and local agencies today. A significant part of
mining regulations are designed for protection of the environment.
Environmental management thus takes up a significant fraction of the
resources. Regulatory requirements of sampling and analysis of mine
drainage, spoil piles, and emissions are on the rise with the advancement of
technology. These requirements are often hard to comply with, especially for
the small miners and quarry operators. A healthy environment is often
reflected by a few common indicators, which could be easily observed and
monitored at a much lower cost and in a more definitive manner.
This paper examines the possibility of meeting the ultimate objective of
minimizing the impact of mining on the environment by monitoring the total
health of the watershed and its habitat by use of environmental indicators.
Introduction
As the urban sprawl continues its stride towards suburban areas, health of
local watersheds is becoming increasingly important to the resident
population because of the dearth of clean and pollution-free environment. In
response to this and other water quality concerns, the U.S. Environmental
Protection Agency (EPA) has stepped forward with a revision to the
regulatory requirement of the Total Maximum Daily Loads (TMDL) under section
303(d) of Clean Water Act (CWA). Amendments to regulations 40 CFR part
122.4(i) and 40 CFR part 130 were made to provide states, territories, and
authorized tribes with the necessary information to identify impaired water
bodies and to establish TMDLs to restore water quality. States, territories,
and authorized tribes establish the section 303(d) lists of impaired waters
and submit to EPA for approval of the lists or to add waters to the
submitted lists, if EPA determines that the list is not complete. TMDLs have
been applied to several mining sites because of the causal link between the
impaired water body and the source of pollution. The most common examples of
mining sites where TMDLs have been applied include the following sites from
EPA Regions 8 and 10 (USEPA 2000):
Animis River,
Coeur d'Alene site,
South Dakota Black Hills area (e.g., Whitewood Creek)
Colorado's Cripple Creek, and
West Fork of Clear Creek.
The top three causes of impairment of water bodies
nationally include sediments, nutrients, and pathogens (USEPA 2000). Mine
runoffs are oftentimes linked with high sediment concentrations. As a
result, the surface water sampling and monitoring requirements in mining
operations have been increased in certain areas. For example, in case of
greater water quality concerns, the State of Minnesota sometimes requires
the sand and gravel operators, and rock quarries to submit water quality
analyses including pH, maximum turbidity, total suspended solids (TSS),
total phosphorus, and other potential pollutants, at certain times during
their operation, in addition to their initial permit application and
renewal. The cost of these additional sampling and monitoring could be
formidable for small operators. Also, some operators are unable to perceive
the broad picture involving the local watershed and fail to employ the most
effective control for silts and sediments in the mine runoff.
This paper examines the use of various environmental
indicators to provide a more comprehensive picture to the mine operators and
communities in a watershed concerning the health of their watershed and
possible signs of ecological "brown spots". By using these indicators, all
of the stakeholders from the watershed can develop an integrated approach to
protecting the health of their watershed. This should lead to a more
sustainable growth and development in that watershed as compared to the
standard regulatory mandates.
Use of Indicators by the Loudoun County Environmental Indicator
Project (LEIP)
To study the environmental impact of proliferating growth and
development in Loudoun County, Virginia, various indicators of change are
studied by LEIP, under the auspices of the Geography Department at the
George Washington University. There are fifteen different indicators used by
the LEIP. They are Roadside imagery, Aerial imagery, Digitized imagery,
Conventional map imagery, Forested areas, Agricultural lands, Wetlands,
Riparian areas, Impervious surfaces, Urbanized areas, Listed plant species,
Key soil types, Water quality, Air quality and Historic and cultural sites.
These indicators are monitored at various sites in the county and the
changes studied and analyzed. Seventeen sites throughout the county were
selected for long term monitoring. These sites represent a wide variety of
environmental conditions ranging from forest areas and riparian zones to
shopping centers and residential areas of varying densities. Amongst the
findings on various indicators as (LEIP 2000) the following few sample
observations from a few indicators are summarized here.
Roadside Imagery
Continuous changes to familiar landmark or its setting to a
new form have been routinely observed in LEIP's roadside image logs. Almost
daily changes were apparent along Route 50. The concentration and extension
of commercial facilities along Route 28 have placed a deeply engraved rubber
stamp of urbanism in this suburban setting by placement of several
multistory buildings along the Route 28 corridor. The inventory of images
captured by LEIP in 2000 have been marked with both significant and subtle
changes when compared to the previous years.
Remote Sensing Technologies for Mapping Changes in Forest Cover
A series of landscape metrics was calculated and presented by
LEIP to show how patterns of forest fragmentation have changed in the county
during the past three decades. The results revealed that there were
increases in forest fragmentation in most watersheds of the county,
especially between 1987 and 1999. Later, LEIP acquired a new digital land
cover map of the Washington-Baltimore metropolitan region which was used as
a basis for analyzing the relationship between the size of the forest
fragments and the percent of urbanized area per major watershed. For the
eleven major watersheds the calculated mean forest fragment size is plotted
against the percent urbanized land as shown in the figure below. Each of the
data points in the figure represent one major watershed in Loudoun County.
Figure 1. Mean forest fragment size (in km2) versus
percent urbanized land in major watersheds, Loudoun County, VA (Fuller 2000)
With the progress of urbanization the forest patches are
getting smaller and smaller. These patches are less likely to support an
ecologically diverse wildlife and plant species. A diverse wildlife
population normally requires a large continuum of forest cover without
fragmentation. For example, many songbird species found in the mid-Atlantic
region usually occur in forest patches of 1 Km2 or greater in area. Using
the relationship shown in the above figure, the amount of urbanized area
likely to result in a mean forest patch size of 1 Km2 for maintaining viable
population of songbirds is 52.58 percent (Fuller 2000). This could be an
approximate value of maximum urbanization potential in a watershed while
maintaining the minimum forest patch size requirement for a viable songbird
population. Similarly, the forest fragmentation could be tied to other
ecological factors identified in a watershed.
Environmental Indicators for Monitoring Impacts of
Mining Operations
Impacts of mining operations on the watershed and sensitive
waterbodies are generally monitored by regulatory agencies a little more
carefully by requiring the operators to submit water quality data at certain
times during the operation. For small scale mining operations this
requirement becomes too cost intensive. The validity of such data are also
questionable because of the possibility of bias exercised in the sampling
time and location. In addition, the reported results are subject to sampling
and analytical errors and oftentimes do not provide a clear and
comprehensive picture of the actual damage done to the local environment due
to a mining operation. Effective use of environmental indicators in such
operations could possibly resolve these problems. Amongst many different
indicators, such as aquatic life, vegetational stress, satellite imagery,
aerial imagery, roadside imagery, forested areas, water quality, air
quality, wildlife species, and genetic biomarkers, only the following three
different indicators will be covered briefly in this paper.
Aquatic Life
Aquatic environments reflect the effects of acid mine
drainage (AMD) most clearly.
Most lakes and streams have a pH between 6 and 8 (USDI 2000).
A pH between 6.5 and 9.0 is harmless to most aquatic species. However, near
an acid mine spoil site, AMD water flows to streams, lakes, and ponds which
may greatly acidify the water. Lakes and streams become acidic when the
water itself and its surrounding soil cannot buffer the acidic water enough
to neutralize it. The pH of many AMD waters fall below 5.0. Generally, the
young of most species are more sensitive to changes in acidity than adults.
When the acidity of a lake or stream drops the pH to less than 6.0, there
are decreases in the reproductive success in many aquatic species. As the
acidity increases to a pH level below 5.0, the number of aquatic species
that live in lakes and streams decreases. Some species like frogs are able
to tolerate acidic waters but eventually disappear due to low prey (mayfly)
populations. At a pH of less than 4.5, most fish species can not survive.
Figure 2 shows that not all adult fish, shellfish, or their food insects can
tolerate the same amount of acid (top wide bars). It also shows the levels
of acidity that are harmful to reproduction for each species listed in the
chart (narrow bars below the top wide bars). Figure 2. Degree of acidity endurable by different
aquatic species
A small water body (part of a stream or a small baffle part
of a stream or lake), downstream of the active mine boundary, could be
stocked with some of the sensitive aquatic species and used as a control
area. This water body could be periodically checked to evaluate the impact
of mining operations.
Biomonitoring methods using macrophytes, phytoplankton, and
periphyton also have the potential to be useful tools for monitoring impacts
of mine effluents on the aquatic environment. All of these methods are
undergoing further testing and evaluation by various agencies. A good
example is EPA's Mid-Atlantic Integrated Assessment (MAIA) project, where
the evaluation of anthropogenic activities on aquatic ecosystems and
integration of watershed studies at different scales are being conducted to
develop a landscape assessment on the environmental condition of the
Mid-Atlantic region.
Vegetational Stress
Some terrestrial plant species have better survivability
under acidic condition in the mine area. Examples are Pines (Pinus spp.),
Black Locust (Robinia pseudoacacia), Broomsedge (Andropogon virginicus),
Common cattail (Typha latifolia), Common reed (Phragmites australis),
Flowering dogwood (Cornus florida), River birch (Betula nigra), Sericea
lespedeza (Lespedeza cuneata), Sugar maple (Acer saccharum), and American
sycamore (Platanus occidentalis)(USDI 2000)
http://plants.usda.gov/)
However, there are a few sensitive plant species that will
exhibit stress and show decline in population and growth when impacted by
acidic drainage or high metals or other contaminants from the mining
operation. Amongst a wide variety of species from the plant database
provided by Natural Resources Conservation Service of the US Department of
Agriculture (USDA 2002), the following few species are presented as samples
of sensitive vegetation which could reveal adverse impacts of mining
operations because of their high sensitivity to low pH and low tolerance to
other adverse impacts of mining.
1. Purple crowberry (Empetrum nigrum, pH 4.3-7.8); 2. Kura
clover (Trifolium ambiguum, pH 6.0-7.4); 3. Redosier dogwood (Cornus sericea
L., pH 4.8-7.5), 4. Dotted blazingstar(Liatris punctata, pH 6.0-7.8).
Similar to the aquatic indicator, a control area with some of
the sensitive plant species could be monitored using photographic imagery
and reported to the regulatory agency. Proper selection of the control area
will be a critical factor for its effective use as an indicator.
Remote Sensing Methodologies
Aerial photography and Satellite imagery could also be used
to monitor the periodic changes at a mine site. The data from a remote
sensor is digitally stored as a matrix of numbers. A picture element (pixel)
is the smallest element of a digital image representing the reflectance from
one specific location (i,j) of row and column out of a matrix comprising of
the whole picture. A variety of multispectral and hyperspectral remote
sensing systems are being used today. A few commonly used remote sensing
technologies categorized by the type of technology are furnished below
(Jensen 2000):
Multispectral Imaging using Discrete Detectors and Scanning Mirrors
Landsat Multispectral Scanner (MSS)
Landsat 7 Enhanced Thematic Mapper Plus (ETM+)
NOAA Geostationary Operational Environmental Satellite (GOES)
NOAA Advanced Very High Resolution Radiometer (AVHRR)
Multispectral Imaging using Linear Arrays
SPOT 4 High Resolution Visible Infrared (HRVIR)and Vegetation Sensor
Indian Remote Sensing System (IRS)
Space Imaging (IKONOS)
Earthwatch (Quickbird)
Imaging Spectrometry Using Linear and Area Arrays
Airborne Visible-Infrared Imaging Spectrometer (AVIRIS)
NASA Terra Moderate Resolution Imaging Spectrometer (MODIS) Digital Frame
Cameras
Litton Emerge Spatial
Positive Systems
Satellite Photographic System
Russian KVR-1000
NASA Space Shuttle Photography
Changes in disturbed area, spoil pile accumulation, and
watercourse diversions at a mine site can be easily mapped by using remote
sensing technologies. By reviewing temporal changes in satellite imagery of
an area, the forest canopy cover, the forest types (deciduous vs.
evergreen), and the vegetative cover ( forest vs. savanna) of the area could
be determined (Brakken 2002). Determining water quality using hyperspectral
data is also possible with new high resolution imagery provided by such
satellites as IKONOS and Quickbird. Using high resolution and clear
distinction between the reflected wavelengths in the blue (0.45 ?m), and
yellow (0.8 ?m) region, the sediment load in a surface water near a mine
site can be estimated. Remote sensing can be used to periodically monitor
the changes in permit boundary, forest cover, site runoff, drainage ditches,
slope erosion, and spoil piles by the regulatory agencies and other
stakeholders. One similar program is being used for enforcement by the
Technology Information Processing System (TIPS) program of the Office of
Surface Mining (OSM). The remote sensing technique would allow an early
warning and identification of environmental problems at a mine site. By
proper use of the remote sensing imagery, a timely alert could be relayed to
the mine operator to resolve the problem before it grows too large,
difficult and expensive to handle.
References
1. USDA 2002, Online Plants Database , http://plants.usda.gov,
Natural Resources Conservation Service. April.
2. Brakken, K.T 2002, Personal Communication, U.S. DOE,
Rocky Flats Environmental Technology Site, Golden, CO, April.
3. LEIP 2000, Annual Report , Published by the George
Washington University, Washington, DC.
4. Fuller, D.O. 2000, The Effect of Urbanization on Forest
Fragmentation in Loudoun County, LEIP Annual Report 2000, The George
Washington University, Washington, DC.
5. Jensen, J.R. 2000, Remote Sensing of the Environment:
an earth resource perspective, Prentice-Hall, New Jersey.
6. USDI 2000, Old Ben Scout Reservation Natural Resources
and Mining Handbook, Office of Surface Mining, Alton, IL, May.
7. US EPA 2000, Total Maximum Daily Load (TMDL) FAQs,
Office of Water, Mining Waste Scientist to Scientist Meeting, EPA/ORD
National Exposure Research Laboratory, Las Vegas, NV, June.
Note: Rivers of the World (ROW) Foundation is a Tax-Exempt(501(c)3)Organization. All contributions to the ROW Foundation (Fed. Tax ID 26-062-3120 )qualify to be deductible from U.S. income taxes. All Rivers of the world foundation team members are participating in the Rivers/Stream restoration and protection activities on their personal time and contributing their personal funds. Not a single volunteer of the Foundation is receiving any compensation, rather they are paying towards the cause. They are conducting the activities in compliance with applicable regulations (US 18 U.S.C. 207 , 5 CFR 2635, and others; India - IPC for Ethics) in their respective countries. They are dedicated to Restore/Protect Rivers/Steams of the World and provide clean water for the poor and needy.
