Module: Environmental Monitoring & Data Analysis

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Environmental Monitoring & Data Analysis
Module Code	ENS1005 (ITS: CS319)
Faculty	Chemical Sciences	School	Science & Health
NFQ level	8	Credit Rating	5

Description

Data Analysis: To introduce students to the most important and widely used statistical techniques for the evaluation of laboratory based data. The focus is to demonstrate the use of these techniques from a practical problem-solving viewpoint and to acquaint them with the interpretation of the results arising from a statistical analysis. Particular emphasis will be placed on understanding the assumptions on which these statistical techniques are based and how to check or validate these assumptions. Environmental monitoring: To introduce students to the core concepts in environmental monitoring, it's importance and how to carry out an effective monitoring programme. The student will learn how to design and evaluate monitoring programmes for a range of different environmental scenarios.

Learning Outcomes

1. Determine and communicate the importance and application, and essential components of an effective monitoring programme
2. validate the assumptions associated with statistical analysis.
3. Determine and communicate the importance, application and essential components of an effective monitoring programme
4. Evaluate the reliability and comparability of monitoring programmes, including monitoring frequency, data interpretation, and reporting requirements, and application of this to existing programmes
5. Describe different approaches taken to monitoring air, soil and sediments, and water quality using field and laboratory techniques, considering spot and continuous sampling
6. Select monitoring methods and sampling sites and design monitoring programmes for a range of different environmental scenarios

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Online activity	24	Pre-recorded material and other activities.
Lecture	12	Synchronous lectures/tutorials
Independent Study	89	Revising and practicing material for both parts of the module, including application of statistical methods to tutorial sheets.
Total Workload: 125

Section Breakdown
CRN	20425	Part of Term	Semester 2
Coursework	0%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	Y
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Margaret McCaul	Module Teacher	Kieran Nolan, Mary Pryce, Patrick O'Malley

Type	Description	% of total	Assessment Date
Assessment Breakdown
Loop Exam	Online exam or assignment that will cover the students knowledge of and ability to apply a range of data analysis approaches to different problems.	50%	Week 7
Assignment	An assignment will explore different aspects of the importance, theory and application of environmental monitoring.	50%	Week 8

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Indicative Reading List

Books:

James N. Miller, Jane C. Miller: 2010, Statistics and Chemometrics for Analytical Chemistry, 6th Edition, Pearson, England, 9780273730422

Articles:
None

Other Resources

None