The CMPDIL matrix measures magnitude using
a scale of 0-4. In comparison to Leopold matrix, CMPDIL matrix measures impacts
using a low resolution scale. A '+' or '-' sign is used to indicate respectively
a beneficial or adverse impact. Impact values correspond to the following
interpretations:
A matrix total is obtained by using the expression
Where Pi = importance weight of the ith parameter (i = 1,2, .....14).
Mij = magnitude of impact on the ith parameter due to jth activity. (j = 1,2, ..........11)
EI = Total environmental impact due to the project.
The total impact score is interpreted as below.
The significance of impact scores, as given above, cannot be justified logically as there is no cause effect relationship.
It is surprising that both underground and opencast coal mining projects are assessed in India using the same matrix. Putting mining activities only under eleven categories (including community development!) is difficult to support. In fact the classification is not based on unit operations. Entire mining operation has been clubbed into three activities, viz., extraction, transportation and waste dumping. For underground mining this further reduces to only two, as waste dumping is negligible. To sum up, it is observed that the CMPDIL matrix is not a well-composed matrix. The evaluation is subjective and the interpretation of significance is not based on logic. This method was adopted in 1986 and it should have been suitably revised with the help of pertinent research and development on EIA.
The matrix methodologies reviewed above are essentially non-mathematical matrices, which can be applied for assessing direct impacts only. Various other forms of environmental impact matrices have been developed. Some of them are site specific, some others are presentation or display formats. These methodologies have been reviewed by other EIA scholars including Bisset (1984) Canter (1979), Clark et al. (1980), Sanwal (1995) and Majumdar (1996).
5.6 Methodologies for Assessing Indirect Impacts
Environmental components are aggregated into hierarchical groupings that exhibit varying intra- and inter-group dependencies (Wathern 1984). Impact on one component of the environment may induce a chain of impacts on other inter-related components. Since EIAs are often undertaken with imperfect knowledge of these higher order impacts unexpected indirect impacts may occur. Attempts to incorporate indirect impacts into EIA studies led to development of other types of matrix methodologies, such as, stepped (or cross impact) matrix, component interaction matrix (CIM), network methodology, etc. Many of these matrices involve algebric operations and are therefore called mathematical matrices. Some of these methodologies have been reviewed by Canter (1996), Majumdar (1996), Sanwal (1995) and Wathern (1984). From the point of view of this study, which is oriented towards developing countries, these methodologies may not be of much help as under the prevailing status of resource availability these methodologies may not be easily applicable. The author therefore has kept these methodologies, except simple networks, beyond the purview of this study.
According to Sorenson and Moss (1973) the network methodology was first suggested by the Travellers Research Corporation in 1969. While the matrix methodology analyses the cause-effect relationship, the network approach attempts to understand cause-condition-effect network so that complex indirect effects can be identified. According to Glasson et al. (1994) the network methodologies recognise that environmental systems consist of a complex web of relationship. The network methodologies attempt to reproduce the web.
Sorenson network (Sorenson 1971) was one of the first networks to be applied as an EIA methodology. Sorenson (1971) categorised environmental factors into six categories, namely; water, climate, geophysical, biota, access and aesthetics. The network utilises a matrix format to identify potential causes of environmental change associated with a proposed development action. The development action and its alternatives are examined through networks that relate uses to causal factors (project activities), to first order condition changes, to second-and higher order condition changes, and finally, to effects.
For example, development of a coastal area for residential purposes will involve construction of high-density apartments, play areas and parking areas. These may be considered as project activities. These will necessitate removal of trees, excavation, hard topping of open lands and laying of sewer systems. These are the causal factors. Hard topping and tree removal will cause increased surface run-off. Therefore increases in surface run-off is one initial condition which leads to a consequent condition of 'flooding', which in turn leads to a terminal effect' gulling and erosion'. Logically the chain can be extended further. In fact many higher order impacts can be traced over varying spatial and temporal scale. According to Sorenson and Moss (1973) once the initial cause of change has been traced through all subsequent impacts and changes in environmental conditions to its final impacts, the quest for subsequent changes may be stopped. In other words Sorenson network analyses traces secondary or higher order impacts but the analysis is limited to primary dependency. Largely following Sorenson (1971) an impact tree may be constructed for a proposal to develop a residential complex in a coastal area as shown in Figure 5.3
The Sorenson network does not provide any guideline for measurement of impacts. Neither any provision is made to arrive at a final project impact score nor any attempt is made to assess individual impacts in terms of magnitude and significance. The major utility of Sorenson network in EIA is therefore limited to the following two areas.
1. it may be used as a very useful tool for project screening to identify the project components requiring further detailed analysis.
2. it may be a very effective communication tool because the display format used is comprehensive.
According to Jain et al. (1977) a major strength of the approach is its ability to identify the pathways by which both primary and secondary impacts are produced.
| . |
Impact value
|
| No appreciable impact |
0
|
| Appreciable impact |
1
|
| Significant impact |
2
|
| Major impact |
3
|
| Severe impact |
4
|
A matrix total is obtained by using the expression
Where Pi = importance weight of the ith parameter (i = 1,2, .....14).
Mij = magnitude of impact on the ith parameter due to jth activity. (j = 1,2, ..........11)
EI = Total environmental impact due to the project.
The total impact score is interpreted as below.
|
Upto 1000
|
No appreciable impact on the environment |
|
1001-2000
|
Appreciable but reversible impact, mitigation measures required. |
|
2001-3000
|
Significant impact, mostly reversible after a short period. Mitigation measures crucial. |
|
3001-4000
|
Major impact which is mostly irreversible. Project site/mining technology to be reviewed. |
|
4000 & above
|
Permanent irreversible impact. Alternative site to be considered. |
The significance of impact scores, as given above, cannot be justified logically as there is no cause effect relationship.
It is surprising that both underground and opencast coal mining projects are assessed in India using the same matrix. Putting mining activities only under eleven categories (including community development!) is difficult to support. In fact the classification is not based on unit operations. Entire mining operation has been clubbed into three activities, viz., extraction, transportation and waste dumping. For underground mining this further reduces to only two, as waste dumping is negligible. To sum up, it is observed that the CMPDIL matrix is not a well-composed matrix. The evaluation is subjective and the interpretation of significance is not based on logic. This method was adopted in 1986 and it should have been suitably revised with the help of pertinent research and development on EIA.
The matrix methodologies reviewed above are essentially non-mathematical matrices, which can be applied for assessing direct impacts only. Various other forms of environmental impact matrices have been developed. Some of them are site specific, some others are presentation or display formats. These methodologies have been reviewed by other EIA scholars including Bisset (1984) Canter (1979), Clark et al. (1980), Sanwal (1995) and Majumdar (1996).
5.6 Methodologies for Assessing Indirect Impacts
Environmental components are aggregated into hierarchical groupings that exhibit varying intra- and inter-group dependencies (Wathern 1984). Impact on one component of the environment may induce a chain of impacts on other inter-related components. Since EIAs are often undertaken with imperfect knowledge of these higher order impacts unexpected indirect impacts may occur. Attempts to incorporate indirect impacts into EIA studies led to development of other types of matrix methodologies, such as, stepped (or cross impact) matrix, component interaction matrix (CIM), network methodology, etc. Many of these matrices involve algebric operations and are therefore called mathematical matrices. Some of these methodologies have been reviewed by Canter (1996), Majumdar (1996), Sanwal (1995) and Wathern (1984). From the point of view of this study, which is oriented towards developing countries, these methodologies may not be of much help as under the prevailing status of resource availability these methodologies may not be easily applicable. The author therefore has kept these methodologies, except simple networks, beyond the purview of this study.
According to Sorenson and Moss (1973) the network methodology was first suggested by the Travellers Research Corporation in 1969. While the matrix methodology analyses the cause-effect relationship, the network approach attempts to understand cause-condition-effect network so that complex indirect effects can be identified. According to Glasson et al. (1994) the network methodologies recognise that environmental systems consist of a complex web of relationship. The network methodologies attempt to reproduce the web.
Sorenson network (Sorenson 1971) was one of the first networks to be applied as an EIA methodology. Sorenson (1971) categorised environmental factors into six categories, namely; water, climate, geophysical, biota, access and aesthetics. The network utilises a matrix format to identify potential causes of environmental change associated with a proposed development action. The development action and its alternatives are examined through networks that relate uses to causal factors (project activities), to first order condition changes, to second-and higher order condition changes, and finally, to effects.
For example, development of a coastal area for residential purposes will involve construction of high-density apartments, play areas and parking areas. These may be considered as project activities. These will necessitate removal of trees, excavation, hard topping of open lands and laying of sewer systems. These are the causal factors. Hard topping and tree removal will cause increased surface run-off. Therefore increases in surface run-off is one initial condition which leads to a consequent condition of 'flooding', which in turn leads to a terminal effect' gulling and erosion'. Logically the chain can be extended further. In fact many higher order impacts can be traced over varying spatial and temporal scale. According to Sorenson and Moss (1973) once the initial cause of change has been traced through all subsequent impacts and changes in environmental conditions to its final impacts, the quest for subsequent changes may be stopped. In other words Sorenson network analyses traces secondary or higher order impacts but the analysis is limited to primary dependency. Largely following Sorenson (1971) an impact tree may be constructed for a proposal to develop a residential complex in a coastal area as shown in Figure 5.3
The Sorenson network does not provide any guideline for measurement of impacts. Neither any provision is made to arrive at a final project impact score nor any attempt is made to assess individual impacts in terms of magnitude and significance. The major utility of Sorenson network in EIA is therefore limited to the following two areas.
1. it may be used as a very useful tool for project screening to identify the project components requiring further detailed analysis.
2. it may be a very effective communication tool because the display format used is comprehensive.
According to Jain et al. (1977) a major strength of the approach is its ability to identify the pathways by which both primary and secondary impacts are produced.