Environmental impact Assessment Sample
Introduction
Here the primary purpose of this report is entirely committed to the environmental impact assessment approach significantly. That is why here in this report, a critical assessment of an opencast mining project in Scotland is going to be processed. In the very first section of this report, a brief description of the project that in is context approached to be mining project in the location is going to be processed so that a better level of understanding regarding the primary rationale for development taking place is going to be considered including elements such as project components, stages, timescale and projected lifetime effectively. Next here, this report will express the description of the location or environment under which the project is going while taking into consideration the sensitive receptors effectively. A scoping matrix is going to be developed along with brief explanations of the most significant scores in the matrix.
Additionally, legislation and policy regarding the mining project followed in Scotland along with secondary baseline data are also going to be approached. Finally, a critical analysis of the prediction methods that could be used for the project impact and its possible mitigation measures is going to be explored. At the tail end of this report, the overall process for submission and review of an EIA and decision-making in Scotland jurisdiction will be briefly explained.
Part A
Project description
Here the Scotland mining project is about Scotgold’s Grampian project, which is considered to be aiming towards the extraction of gold and various base metal resources in the terrain of Grampian, Scotland effectively (Kunze and Pernicka, 2020). The Colonist mine is considered to be the central location of this mining project which has been bound by a lease agreement with the company Scotgold effectively. Under this context of the agreement, the company was able to get permission to start working on this project of mining significantly.
According to Kumar, Dimitrakopoulos and Maulen (2020), the most significant rationale for the mining project development in the location of Scotland is identified as the requirement for producing gold from it effectively (Cononish Gold and Silver Mine, Scotland, 2022). In This context, it has been determined that the whole project consists of two vital stages, out of which it has been identified that phase one is already started. It is already completed in the month of February 2022 (Pohrebennyk et al., 2019). On the other hand, it has been determined that the second phase of this mining project was started in March 2022. The estimated mining allowance of the project in this property is about 10 years.
Description of the location and environment
According to various research studies about this project, it has been identified that the entire deposit of the mine is situated at Tyndrum, which is found to be located very near to Colonish farm. In this context, it has been identified that the location of the project is just about 90km from the city of Glasgow, Scotland (Almeida et al., 2021). The geology of the mining project location is found to be containing very early stage quartz structures, which is also segmented into multiple proterozoic rocks significantly. As per Fan et al. (2022), in accordance with the project of mining in the location of colonish farm at Scotland, the vital sensitive receptors are identified to be the nearby local community people who are directly exposed with the mining project disposals and also toxic emitted gases as well. In addition to that, some of the most significant sensitive receptors in this context are drinking water quality, wildlife, natural habitat, household facilities nearby the project location significantly.
Scoping matrix
| Environmental parameters /
Project actions |
A.
Carbon Emission |
B.
Water Ph level |
C.
Dissolved oxygen |
D.
Dissolved organic materials |
E.
Solar radiation |
F.
Mechanical abrasion |
G.
Moisture variation |
H. temperature variation | I.
Salinity |
J.
Geographical variation |
| 1. project planning: In this phase, strategic planning of the entire mining process is processed for the successful completion of the project | 1 | 3 | 4 | 2 | 3 | 2 | 1 | 2 | 2 | 2 |
| 2. researching the target location: This phase includes the discovery of the target location which is suitable for mining.
|
4 | 3 | 2 | 1 | 5 | 5 | 5 | 3 | 4 | 3 |
| 3. Geological mapping: In this phase, the discovery of the location environmental geology is discovered for identifying the mineralization of the location | 2 | 2 | 4 | 5 | 3 | 2 | 1 | 3 | 4 | 4 |
| 4. activity of exploration: In this phase, a geographical survey around the location is processed. | 1 | 2 | 1 | 3 | 4 | 5 | 2 | 1 | 2 | 3 |
| 5. mineral discovery: In this phase, the discovery of the mine site, mineral deposits are performed | 2 | 3 | 3 | 4 | 2 | 1 | 2 | 2 | 1 | 1 |
| 6. collection of permit and license: In order to start working on the locating for the mining project, licenses from the government of the area has been taken. | 1 | 2 | 4 | 5 | 3 | 5 | 3 | 2 | 5 | 5 |
| 7. feasibility analysis of the project: In this context study of the study of the feasibility analysis of this project is performed. | 1 | 3 | 2 | 5 | 4 | 5 | 3 | 4 | 2 | 1 |
| 8. construction phase: In this phase, the construction project action for mine development was started. | 1 | 2 | 3 | 4 | 2 | 3 | 4 | 2 | 3 | 2 |
| 10. The phase of extraction: In this overall mining project cycle, this is the extraction phase in which gold was extracted. | 1 | 1 | 2 | 4 | 5 | 4 | 3 | 2 | 5 | 2 |
| 11.milling: Here in this phase, shaping of the acquired metals are processed | 4 | 5 | 2 | 1 | 3 | 4 | 5 | 2 | 2 | 1 |
| 12. processing of raw materials: Gold and silvers from the mine are being processed and refined in this phase effectively. | 1 | 2 | 2 | 1 | 3 | 2 | 4 | 4 | 3 | 4 |
| 13. Mine site location reclamation: A thorough modification of the mine land in the location of Scotland is performed in this phase of project action effectively. | 2 | 3 | 4 | 1 | 2 | 3 | 4 | 4 | 2 | 1 |
| 14. costing plan for the reclamations: Overall budget of the land reclamation was accomplished in this section of the overall project action. | 1 | 3 | 2 | 2 | 1 | 1 | 2 | 1 | 2 | 1 |
| 15. future development plan: In this context of the project, future development measures are taken under consideration so that better aspects of mine preservation can be acknowledged. | 1 | 2 | 3 | 1 | 1 | 2 | 1 | 2 | 2 | 2 |
A brief explanation for the most significant scores in the matrix
Carbon emission: carbon emission also account for the carbon footprint, which is considered to be measured by volume in terms of per million and its unit is found to be ppmv. It is an imperative environmental parameter as it plays a significant role in the GHS emissions (Lacoste et al., 2019).
Water pH level: The pH of water is considered a vital environmental parameter, and this is found to be measured through quantity or concentration significantly. In this context, it has been identified that high-level pH refers to better water quality, and a low level refers to the acidic nature of water effectively (Wang and Zhang, 2021). Emission of industrial disposal can cause a rise in the water level pH.
Dissolved Oxygen: The environment parameter dissolved oxygen refers to the non-compound oxygen that is found in the water effectively. The significance of this environmental parameter is because the entire aquatic life and natural habitat are entirely associated with this ecological parameter (Bruckner et al., 2022). It is considered extremely important for maintaining this parameter as it can significantly hamper the overall quality of water.
Salinity: The overall margin of dissolved salt in the water is considered salinity. It is unambiguous terms that are closely affected by any possible chemical contamination, such as factories’ and project emissions (Patterson et al., 2021). It has been found that salinity and conductivity were measured in a composite mannerism to get better measurement output effectively.
Moisture variation: Moisture variation is considered to be another most vital environmental parameter entirely connected with soil effects and properties of solid materials effectively.
Part B
Legislation and Policy
As per Caddick et al. (2018), In order to enhance the better scope for environment welfare and sustainability, the Scottish government has put out some most significant regulatory policies and legislations in view towards minimizing the carbon emission from nature in the context of energy consumption and industrial disposed greenhouse gas effectively. In the context of the carbon emission reduction process target adopted by the government of Scotland, it has been identified that the country has set up a target towards adopting UN sustainable development goals, which means that by 2045 the country is entirely dedicated to reducing the emission of carbon and achieve net-zero margin effectively (Bruckner et al., 2022). As per the act 2009 of the Scottish government, the country Scotland is dedicated to reducing carbon emission by 80% in the year 2050 and 42% by 2020. It is regarded as the local authority that has already carried out numerous regulations to control the action of carbon emission (Wang and Zhang, 2021). In addition to that, the government of Scotland has developed a duty report that highlights all the regulatory duties and actions regarding the reduction of carbon emissions. In order to ensure the removal of carbon emissions, the Scotland government has closed power stations of coal fire and gas fires and is rebuilding all the power stations by adopting low carbon footprint technologies. In addition to that, the Scottish government is also developing policies to reduce the emission from shipping and variation purposes. The government also incorporates the carbon tax so that carbon emission from fuel combustion can be reduced.
Discussion on Secondary baseline Data
In terms of assessing a better margin of datasets regarding the overall carbon emission of this country, the Scottish government has set out some datasets that will give better identification of the current environmental situation and enhance the regulatory activities of the Scotland public effectively (Patterson et al., 2021). The act 2009 by the government of Scotland is set out to reduce carbon emissions by 80% in the year 2050. In addition to that, the comprehensive interim report for the Scotland environment is found to be targeted for getting reduced up to 42% effectively. In this context, the secondary baseline data for the country legislation is set for the target between 2020 to 2022, and then another target date is set from 2023 to 2027 effectively. Every sector of Scotland is found to be giving a new Strategic approach towards the energy transition approach and ensuring sustainable economic development of this country effectively. However, till now, it has been identified that Scotland has managed to reduce the margin of energy consumption by 12% in the year 2020 and in addition to that, the government’s continuous action towards carbon emission control has provided 11% of growth heat or energy demand of this company via approaching renewable energy sources significantly (Lacoste et al., 2019). Following the latest baseline datasets, it has been identified that the carbon emission of the country Scotland has been accounted for getting reduced by 51.5% during 2019. Apart from that, there are some others in which reduction has been noticed such as reduction in emission from the power stations by 71.8% and business emission by 36.7% and carbon emission from waste is reduced by 73.5% significantly.
Figure 1: CO2 emission in Scotland
(Source: Patterson et al., 2021)
Critical analysis of the types of prediction methods that could be used for the project impact
According to Yusuf, Olayiwola and Afagwu (2021), prediction methods are necessary for each project. Especially for the industrial project like the mining of minerals requires a proper prediction method that will help the project manager evaluate the overall activities and the period they will get to complete the project process effectively. By understanding the need for prediction methods required in the project, it could be stated that this mining project needs to use specific prediction methods, which are displayed below.
Straight-line method: It is one of the simplest and easiest forecasting methods the project manager uses by gathering the historical data of the geographic location trends of Scotland where the mining projects need to be held.
Moving average: It is another forecasting model, which is a smoothing technique that looks for the underlying pattern of the dataset and thus estimates the future values accordingly. The standard type of three-month and five-month moving averages has been taken effectively.
Simple linear regression: It have analysis has been mainly used to study the relationship, which includes the variables for the clear prediction purpose (Paduszyński, 2021). Under this prediction process, it will effectively compare both independent and dependent variables by addressing the statistical model required for the project’s prediction process.
Among the prediction mentioned above methods for the mining project, it is necessary to use the straight-line method effectively. The effective use of the prediction methods will help the project manager predict the overall instances of the activities that need to be held for the valuable addition of the project.
Critical analysis of the types of possible mitigation measures
As per Bagheri et al. (2021), many risks can emerge in the mining project. One of the significant challenges which the project manager in the project can face is mainly the risk of explosion, which can have a high impact on the life of the people. The next wind blast outburst is another significant risk that the people associated with the mining project may face. Lastly, finance and time cost is another effective central area that can create a challenging factor for completing the project. Accident risks are evident in the mining projects as they may hurt the employees due to the chemical and hazardous substances associated with the mining projects.
According to Mohammadzadeh, Bagheri and Ghader (2020), the project manager must use some mitigation strategies to reduce the impact of the risk on the employees and other stakeholders. Those natural disasters cannot be mitigated fully like a wind storm. Other than that, the time risk can be reduced by implementing proper schedule techniques. Next, the financial risk can be reduced by using proper budgeting techniques, which will help to keep track of the ongoing activities. Employees need to give appropriate training to use it for self-defence and avoid injuries effectively. The project manager must ensure that dust reduction measures need to be used in the mining environment to reduce the outburst of dust.
A brief explanation of the overall process submission and EIA review and Decision-making
Environmental impact assessment (EIA) has been used as a tool that will help make decisions related to the important decision concerning the project approval, which will include the conditions that need to be fulfilled. For the mining project, it is necessary to evaluate the impact of carbon emitted in the mining process. This review will ensure that the project can reduce the environmental impact and lead to the project’s effective approval. Most of the time, it has been observed that mining projects are very harmful to the environment, so the project manager must address the EIA report so that they can effectively state the needs of the project.
Conclusion
It can be concluded from the above report that it is necessary to ensure all the required activities are addressed in the mining projects. The proper forecasting tool will provide that the project manager can effectively predict the future predictability of the project. Next, several risks are addressed by the project manager that the employees can face during the mining project, so proper mitigation strategies will effectively reduce the possible dangers which are encountered in the mitigation process.
Reference list
Almeida, E.P., Carreiro, M.E.A., Rodrigues, A.M., Ferreira, H.S., Santana, L.N.L., Menezes, R.R. and Neves, G.A., (2021).A new eco-friendly mass formulation based on industrial mining residues for the manufacture of ceramic tiles. Ceramics International, 47(8), pp.11340-11348.https://www.sciencedirect.com/science/article/pii/S0272884220338761
Bagheri, H., Hashemipour, H., Ghalandari, V. and Ghader, S., (2021). Numerical particle size distribution equation solution: Rapid expansion of supercritical solution (RESS) process. Particuology, 57, pp.201-213.https://www.researchgate.net/profile/Sattar-Ghader/publication/348782912_Numerical_solution_of_particle_size_distribution_equation_Rapid_expansion_of_supercritical_solution_RESS_process/links/605c68f2299bf17367690aaf/Numerical-solution-of-particle-size-distribution-equation-Rapid-expansion-of-supercritical-solution-RESS-process.pdf
Bruckner, B., Hubacek, K., Shan, Y., Zhong, H. and Feng, K., (2022). Impacts of poverty alleviation on national and global carbon emissions. Nature Sustainability, pp.1-10.https://www.nature.com/articles/s41893-021-00842-z
Caddick, Z.A., Gregory, K., Arsintescu, L. and Flynn-Evans, E.E., (2018). A review of the environmental parameters necessary for an optimal sleep environment. Building and Environment, 132, pp.11-20.https://data-cene.com/static/pdf/Caddick%20et%20al.%20-%202018%20-%20A%20review%20of%20the%20environmental%20parameters%20necessary%20for%20an%20optimal%20sleep%20environment.pdf
Cononish Gold and Silver Mine, Scotland (2022). Available at: https://www.mining-technology.com/projects/cononish-gold-and-silver-mine
Fan, C., Liu, Y., Liu, C., Zhao, W., Hao, N., Guo, W., Yuan, J. and Zhao, J., (2022).Water quality characteristics, sources, and assessment of surface water in an industrial mining city, southwest of China. Environmental Monitoring and Assessment, 194(4), pp.1-21.https://link.springer.com/article/10.1007/s10661-022-09908-7
Kumar, A., Dimitrakopoulos, R. and Maulen, M., (2020).Adaptive self-learning mechanisms for updating short-term production decisions in an industrial mining complex. Journal of Intelligent Manufacturing, 31(7), pp.1795-1811.https://link.springer.com/article/10.1007/s10845-020-01562-5
Kunze, R. and Pernicka, E., (2020). Pre-industrial mining in the Medni Rid. Prehistoric Mining and Metallurgy at the Southeast Bulgarian Black Sea Coast (RessourcenKulturen Band 10), pp.398-425.https://www.academia.edu/download/65538889/Pre_Industrial_Mining_in_Medni_Rid_Geochemical_Analyses.pdf
Lacoste, A., Luccioni, A., Schmidt, V. and Dandres, T., (2019). Quantifying the carbon emissions of machine learning. arXiv preprint arXiv:1910.09700.https://arxiv.org/pdf/1910.09700?ref=https://githubhelp.com
Mohammadzadeh, M., Bagheri, H. and Ghader, S., (2020). Study on extraction and separation of Ni and Zn using [bmim][PF6] IL as selective extractant from the nitric acid solution obtained from zinc plant residue leaching. Arabian Journal of Chemistry, 13(6), pp.5821-5831.https://www.sciencedirect.com/science/article/pii/S1878535220301258
Paduszyński, K., (2021). Extensive Databases and Group Contribution QSPRs of Ionic Liquid Properties. 3: Surface Tension. Industrial & Engineering Chemistry Research, 60(15), pp.5705-5720.https://pubs.acs.org/doi/full/10.1021/acs.iecr.1c00783.
Patterson, D., Gonzalez, J., Le, Q., Liang, C., Munguia, L.M., Rothchild, D., So, D., Texier, M. and Dean, J., (2021). Carbon emissions and ample neural network training. arXiv preprint arXiv:2104.10350.https://arxiv.org/pdf/2104.10350.pdf**
Pohrebennyk, V., Koszelnik, P., Mitryasova, O., Dzhumelia, E. and Zdeb, M., (2019).Environmental monitoring of soils of post-industrial mining areas. Journal of Ecological Engineering, 20(9).https://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-0ca6c289-bdfb-41b6-870c-3761203430f5/c/7_Pohrebennyk_Environmental_Monitoring_JEE_2019_9.pdf
Wang, Q. and Zhang, F., (2021). The effects of trade openness on decoupling carbon emissions from economic growth–evidence from 182 countries. Journal of cleaner production, 279, p.123838.https://www.ncbi.nlm.nih.gov/pmc/articles/pmc7443063/
Yusuf, F., Olayiwola, T. and Afagwu, C., (2021). Application of Artificial Intelligence-based predictive methods in Ionic liquid studies: A review. Fluid Phase Equilibria, 531, p.112898.https://scholar.google.com/citations?user=4rDLF68AAAAJ&hl=en&scioq=predictive+methods&oi=sra
………………………………………………………………………………………………………………………..
Know more about UniqueSubmission’s other writing services:
