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Impact of the Environmental Impact Assessment (EIA)

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Published: Fri, 15 Dec 2017


Extensive researches carried out have pointed to the fact that impact prediction in the EIA process has been problematic and it lacked transparency, scientific rigour or both (Badr et al 2004, Glasson et al 2005).

Therefore the aim of this research paper is to evaluate impact prediction in the EIA process by comparing impact prediction practices in three environmental impact statements for one environmental component: Air quality.

Methods to identify, access and evaluate impacts were analyzed and how extensively they were used in predicting impacts.

A checklist was developed for to comparative analysis and descriptor for symbols awarded to various stages of impact prediction outlined.

The result shows that important prediction methods were either omitted or not extensively used in some of the cases. This research paper is therefore in agreement that impact prediction is not practiced in a transparent and scientifically rigorous manner.


Recent environmental issues that has emerged due to large industrial developments with effects on the environment has led to the birth of the process called Environmental Impact Assessment (EIA) which can be defined as “the need to identify and predict impacts on the environment and on man’s wellbeing of legislative proposals, policies, programmes, projects and procedures and to interpreter and communicate information about the impacts” (Munn 1979).

EIA can also be defined as “a process by which information about the environment is collected both by the developer and from other sources and taken into account by the relevant decision making body before a decision is given on whether the development should go ahead”(DOE 1995). It can also be defined more simply as “an assessment of the impacts of a planned activity on the environment” (UNECE 1991).

Since the introduction of EIA over 30 years ago, the potential benefits has been widely recognized and it has been adopted and implemented in more than 100 countries by numerous aid and funding agencies (Petts 1999).In essence, EIA is a process that assesses the impact of developments on the environment in a systematic, holistic and multidisciplinary way taking into consideration all environmental components (Glasson et al 2005). EIA as a process involves a number of steps which are as follows

  • Description of project
  • Screening
  • Scoping/consideration of alternatives
  • Baseline studies public consultation&participation
  • Impact prediction
  • Preparation of Environmental Impact Statement(EIS)
  • Decision making
  • Post decision making and monitoring

The EIA process is a cyclical process with feedbacks and interaction between all the steps and public consultation (stakeholder engagement) involved in all the steps.

Aggregated studies have shown that EIA practices in some regions of the world have been and remain problematic, but there is evidence that the quality is improving over time (Lee and Brown 1992, DOE 1996, Cashmore et al 2002). However, disaggregated studies indicate that the quality with which certain components of the environment are addressed is significantly more problematic than suggested by the aggregated studies (Glasson and Heanley 1993, Chadwick 2002, Badr and et al 2004).

Impact prediction in the EIA process has been a problematic despite being the key and heart of the EIA process (Badr and et al 2004). Despite its centrality in the process, many studies have underemphasized prediction and it is not often treated as an explicit stage in the process, models are not detailed and there are little discussions of limitations (Glasson et al 2005).

Therefore, the research for the effectiveness of impact prediction in the EIA process will focus on the Environmental Impact Statement (EIS) which is the document that holds the pre consented states of EIA, and is often readily assessable component of the process (Badr et al 2004).

This research paper aims at contributing to the development of grounded initiatives for enhancing EIA effectiveness by looking at impact prediction practices in three different EIS’s looking into one environmental component which is AIR QUALITY.

The following EIS’s will be used for this research paper

CASE 1-A350 Westbury Bypass EIS

CASE 2-River Tud Residential Development EIS

CASE 3- Kingshill Recycling Centre Biomass Energy Plant EIS

The objective of this research is to analyze how extensively impact prediction practices have been carried out in each of these case studies. The following is the structure of the paper: methodology, results, discussion and conclusion.


The objective of impact prediction is to identify the magnitude and other dimensions of identified change in the environment with the project or action in comparison with the situation without the project or action. It also provides the basis for the assessment of significance (Glasson et al 2005).

According to the EIS legislation (S1.4) impact prediction should include assessment of direct and indirect, primary and secondary, cumulative, short, medium and long-term, permanent and temporary, reversible and irreversible, positive and negative effects of a project (Walker and Dalton 2001 in Morris and Therivel 2009).

A variety of models are used to estimate air quality impact of sources on receptors to prepare and review new industrial and other sources application and to develop air quality management plans for an area or region and they are the Gaussian, numerical, statistical and physical methods (Jacko and Breche 2003 in salvato et al 2003).

There are four stages in impact prediction and they are

  • Impact identification-this brings together the project characteristics and baseline environmental characteristics with the aim of ensuring that all potentially significant environmental impacts are identified and taken into account in the EIA process.( Glasson et al 2005). Ensuring compliance with regulations is an important factor when choosing impact identification methods for assessment. The pathway and receptors are also identified. The methods include checklists, matrices, and quantitative methods and overlay maps.
  • Impact assessment-this involves the detailed analysis of impact to determine their magnitude, significance and expert judgement. There are different methods of impact assessment: professional judgement (qualitative), mathematical methods (quantitative), physical methods, laboratory methods and case to case methods. When choosing prediction methods, the assessor should be concerned about the appropriateness for the task involved, will the method produce what is wanted?, can the method be applied to different projects and allow predictions to be compared? (Lee 1987, Glasson et al 2004).
  • Significance of evaluation- when impact have been predicted, the impacts are then evaluated for acceptability. Criteria for significance include the magnitude and likelihood of impacts, the geographical level. The most formal evaluation method is the comparison of predicted changes in the area to air quality standards, objectives or guideline values, and determining whether they are likely to be exceeded at any location, after taking into account the existing and predicted baseline conditions (Walker and Dalton 2001 in Morris and Therivel 2009). Dispersion models such as DBRM screening method is used to evaluate significance, and the Gaussian model. Other methods are the cost and benefit analysis, multi criteria method, empirical data analysis and simple criteria.
  • Impact mitigation- This is the measure envisaged in order to avoid, reduce and if possible, remedy significant adverse effects (CEQ 1997). Mitigation measures such as change of technology or modification of industrial processes can be implemented. Monitoring should be continued after completion since numerical prediction models contain uncertainties. Continued monitoring is necessary to access the effectiveness of any mitigation measure proposed in an EIA and to ensure that any potential air and climate problems identified have been minimized or mitigated (Walker and Dalton 2001 in Morris and Therivel 2009).

A checklist has been developed for the purpose of evaluating impact prediction practices looking at air quality component in three EIS case studies.


Impact identification

Case 1

The relevant legislation and policy context was the first method used to identify impacts of the development in air quality. The EU legislation was also looked at, the National Legislative and future legislative measures were also used in impact identification. Relevant policy measures like National planning policy, regional policy and local development framework was used to identify impacts. The limit value of AQS objectives were measured and if it was likely to exceed the objectives declared in the AQMA, then an action plan is to be prepared and implemented.

The baseline information was acquired from the local authority and national air quality information archive (NAQIA). Therefore, because of the baseline studies, analysis of the background of air quality data available for the study area showed that the concentration of NO2 and PM10 are generally low in comparison to the relevant AQS objectives and limit value (Wiltshire county council 2007). Future predictions of air quality also carried out.

Although qualitative method was used in this exercise, it was not clearly used to identify impacts. Checklists, matrices and overlay maps were not used.

Source- pathway-receptor clearly identified.

Case 2

Although legislative standards were mentioned, it was not mentioned extensively like in case 1.

Baseline data of the environment was obtained from the national environmental technology centre (NETEN) and department of environment. Baseline studies were not used extensively for impact prediction in case 2. Knowledge of baseline conditions is essential because, even when a development is likely to add small amounts of pollution to the area, it could lead to air quality standard of the area being exceeded if air quality in the area is already poor or may become poor in the future(Morris and Therivel 2009). No future predictions of impacts carried out.

There was no mention of the use of matrix or checklist for impact identification in this case.

The source, pathway and receptor not clearly identified for air quality.

Case 3

Most of the legislative standards considered. The UK air quality standards 1989 limits value for pollutants, the air regulations and air quality objectives clearly listed.

Baseline studies of the area without the project was mentioned but not considered extensively.

Checklists or matrices not used in prediction.

Source-pathway and receptors identified.

Overall, the main problem of impact identification is the failure to use systematic methods such as checklists, matrices or networks for impact predictions which agrees with Badr et al 2004 “Most WIA studied failed to provide any information on methods used to identify impacts”.

Impact assessment

Case 1

Constituent impact stages equally divided and assessed

Quantitative assessment method was used for the operational phase of the development for the assessment of local air quality. Impacts on sensitive receptors in the area as a result of the operation of the bypass in the future were analysed using detailed dispersion modelling. DDM was used for the analysis of traffic emissions. Atmospheric dispersion modelling system (ADMS-Roads) was also used and it analysed dispersion of pollutants from industrial and road traffic sources.

Qualitative assessment was used in the construction phase of the project. This assessment concluded that emissions will be greater in the operational stage, since the construction was short term, then impact will not be significant.

Meteorological data was used for the input into the dispersion model.

Case 2

Impacts talked about in construction and operation stages although not extensively.

There was no mention of quantitative or computer model to assess air quality impact. The lack of quantitative analysis means that practitioners could not compare predictions with air quality and legislative standards and this is why evaluation of significance is poorly evaluated. (Badr et al 2004)

Although qualitative judgement used, but not transparently and scientifically used

Metrological data not mentioned at all in impact assessment.

Case 3

Construction phase impact omitted and operational phase focused on.

Quantitative model used. ADMS model used to assess atmospheric impacts of emission from the project, future predictions considered.

Qualitative method not mentioned in impact assessment. Expert opinion provided it is backed up with reason and justification which supports that opinion, such as comparison with similar existing development is a very good method for predicting impacts (Morris and Therivel 2009).

Metrological data was used in calculating annual mean of NO2 and SO2

Overall, the problem of impact assessment was the use of quantitative methods. In case 2, for construction emission, it was said that “it is for the most part not practical to quantify the emissions arising during construction of the dwelling” (South Norfolk County2001).Qualitative assessment only extensively used in case 1 and omitted in case 2 and 3. Future climate baseline levels are usually predicted for the purposes of an EIA, given the major limitations for current models in predicting regional changes, let alone local changes attributed to global warming due to the atmospheric concentrations of green house gases (Walker and Dalton 2001 in Morris and Therivel 2009)

Significance evaluation

Case 1

Short term mean concentrations of pollutants NO2 and PPM10 were calculated and compared against the relevant AQS objectives. Significance of impacts communicated both numerically and descriptively. Significance also calculated using the comparative method looking at the standard of air quality without the project.

Descriptors clearly provided for the significance of air quality based on the magnitude of change in the context of existing conditions.

The level of effects of project clearly identified as local effects.

Case 2

Although long term mean concentrations mentioned, how numeric values arrived at is not transparent. Comparative method not clearly stated.

Level of impact local, national or regional not analyzed.

Case 3

Comparative method was used to compare quantitative dispersion ADMS model results with relevant AQS/AQO’s.

Geographical level of the impact not mentioned although, it was stated in the summary that “the process design has included mitigation measures to reduce impacts on local and national air quality” (North Wiltshire county).

Overall, the significance of impact was well explained in case 1. It was transparent and scientifically rigorous (Badr et al 2004). Methods for significance of impact in case 2 and 3 not transparent although, Comparative measures were used in case 3, the level of impact was not clearly stated. Therefore the main problem of significance of impact was the transparency of the procedure.

Impact mitigation

Case 1

Mitigation measures were clearly put in place for significant impacts. Construction and operation mitigation plan well listed. CEMP prepared for the project.

Alternative technology option also adopted for some impacts.

Monitoring not mentioned in mitigation measures.

Case 2

Mitigation measures not clearly outlined in this case. Although some preventive measures were outlined, it was not done satisfactorily.

No alternative technology options adopted.

Monitoring not mentioned in mitigation measures.

Case 3

Mitigation measures outlined for construction and operations stages but not decommissioning stage.

Alternative technology included in process design to reduce local and national air quality impacts

Monitoring of NOx, SO2, PM10, CO outlined. (Annually).

The overall problem of mitigation measures is the lack of emphasis on monitoring of air quality during construction and operation phases.

A continuous air quality monitoring system for the measurement of selected gaseous air pollutants, particles and metrological conditions over a large geographical area, can make possible immediate intelligence and reaction when ambient air quality levels or emissions increase beyond established standards (Jacko and Breche 2003in Salvato et al 2003).

Numerical prediction models contain uncertainties so monitoring should be continued after completion of the development to compare predictions with those that actually occur and continued monitoring is also necessary to access the effectiveness of any mitigation measures proposed in an EIA to ensure that any potential and climate problems identified have been minimized or eliminated (Walker and Dalton in Morris and Therivel 2009)


The aim of this research paper was to evaluate impact prediction in the EIA process by comparing impact prediction practices in three environmental stated for air quality. The research looked at different stages of impact prediction and how the methods for the stages were used and how extensively impact prediction was carried out.

Results showed that although impact prediction practices were carried out, it was problematic in the impact identification methods in all cases, methods such as checklists, matrices and networks were not used at all while qualitative method which is used for impact assessment was omitted in a case (case 2). This automatically takes its toll on significance evaluation which uses expert opinion for evaluating significance.

Uncertainties associated with the accuracy of a prediction due to the use of inaccurate or partial information on the project or baseline environmental conditions, unanticipated changes in the project during one or more of the changes of the life cycle and oversimplification and errors in the application of methods and models (Glasson et al 2004) was not given consideration at all in any of the cases.

Monitoring changes in air quality standard was also a problem. While mitigation measures were proposed, there was no mitigation monitoring plan. Numerical prediction models contain uncertainties so monitoring should be continued after the completion of the development to compare predictions with those that actually occur (Walker and Dalton in Morris and Therivel 2009). Monitoring should be strengthened to enhance impact prediction.

It is therefore logical to conclude that different developments or projects determine how extensively impact prediction is practiced. Emphasis is given to air quality predictions for developments like power stations, power plants and road constructions. Emphasis on impact prediction declines for developments such as residential buildings and shopping malls.


  • Badr E,-L, Cashmore,M and Cobb, D (2004) ‘The considerations of impact upon the aquatic environment in environmental impact statements in England and Wales’. Journal of environmental assessment policy and management, 6(1):19-49.
  • DOE (Department of the Environment (DOE) (1995) preparation of environmental statements for planning projects that require environmental assessment. A good practice guide. London. HMSO
  • Glasson, J, R, Therivel and Chadwick A (2005) introduction to environmental impact assessment 3rd Edition. London. Routledge
  • Jacko B, La Breche T (2003) air pollution and noise control in Salvato J. A, Numerow N, Land Agardy
  • E, J (2003) Environmental Engineering 5th edition. Canada. John Wiley and sons.
  • Norfolk County Council (2001) proposed residential and associated development at River Tud, Costessey Environmental Impact Statement 2001. Norfolk County Council.
  • Walker D and Dalton H (2001) air quality and climate in Morris P and Therivel R (2009) Methods of Environmental impact assessment 3rd edition. London. Routledge
  • Wiltshire County Council, (2007) A350 Westbury bypass Environmental Impact Statement 2007. Trowbridge, Wiltshire County Council.
  • Wiltshire County Council (2000) Biomass Energy Plant Kingshill Recycling Centre Cricklade North Wilshire Environmental Impact statement 2000. Tollgate, Wiltshire county Council.

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