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Air pollution data analysis to support monitoring activities in the HKH region



Date & Time

09 August 2021 to 13 August 2021


Parth Sarathi Mahapatra , Siva Praveen Puppala & Mohammad Rabi Qazizada


The Atmospheric Watch Initiative (AWI) focuses on monitoring emissions of key air pollutants and climate species in the Hindu Kush Himalaya (HKH) region. The initiative conducts rigorous scientific and social analysis using multiple datasets and/or combinations of field, modelling, and remote-sensing data to address growing concerns about deteriorating air quality, impacts on ecosystems and health, changes in atmospheric heating and cooling, and changes in the strength and timing of the monsoon. These studies are critical in informing and influencing policies and mitigation strategies in the region.

Since its establishment, the AWI, in collaboration with government partners in Nepal and Bhutan (Department of Environment (DoEnv) and National Environment Commission (NEC), respectively), has set up state-of-the-art air quality monitoring stations with aerosol and trace gas measuring instruments in these countries. The National Environmental Protection Agency (NEPA) of Afghanistan is also working towards establishment of a network of air quality monitoring stations and collaborating with ICIMOD.


About the training

Currently, there are five operational ambient air quality monitoring stations in Bhutan and 13 in Nepal, with plans for expansion. It is imperative to analyse data generated from these stations to aid in proper interpretation and informed decision making. Proper analysis requires knowledge of different statistical tools and software. Therefore, in 2020, the AWI organized a basic training on data analysis to support better understanding of the air quality data generated from the stations for officials from the DoEnv, NEC, and NEPA; researchers; and representatives from knowledge institutions. Building on this training, the AWI is organizing an advanced training on the air quality data analysis on 9–13 August 2021 to further strengthen capacity and fill knowledge gaps in the analysis of air quality data. This training is aimed at fostering knowledge sharing among the HKH region’s lead governmental environmental entities and knowledge bodies.



This training is targeted at key stakeholders such as government officials and researchers to enhance their fundamental understanding of different statistical tools for the rigorous and appropriate analysis of atmospheric composition data. This will also support ICIMOD’s efforts as a regional organization to enhance data analysis capacities.


Expected outcomes

Upon completion of the training, the participants are expected to have a better understanding of atmospheric composition data analysis.


Time (IST) Programme Details
Day 1 – Review session from basic training programme
11:00–11:30 Introductory remarks Introductory remarks by Ekonnect and ICIMOD

Remarks by members of DoEnv, NEC, and NEPA

11:30–12:30 Data quality checks (DQC) Recap of outliers, missing data, repeat values

Use of MS Excel to assess outliers and missing data during basic training programme

12:30–13:30 Descriptive statistics Brief recap and application in MS Excel for sample data sets
13:30–14:00 Lunch break
14:00–15:30 Hypothesis testing and comparison of datasets Significance and hypothesis testing, t-test, z-tests, how to perform hypothesis testing using MS Excel
15:30–16:00 Q&A session
Day 2 – Introduction to R Studio
11:00–11:30 Q&A and recap mentimeter quiz
11:30–13:00 Introduction to R Studio Participants will install R Studio on their systems and go through basic libraries and codes
13:00–14:00 DQC Outliers, missing data, repeat values, and hypothesis testing using R Studio
14:00–14:30 Lunch break
14:30–15:30 Correlation and regression analysis Concept on linear regression and Pearson correlation matrix using R Studio
15:30–16:00 Hands-on exercise with Q&A
Day 3 – Trend and violation analysis in R Studio
11:00–11:30 Q&A and recap mentimeter quiz
11:30–13:30 Trend analysis Concepts on Mann Kendall long-term trend and short-term changes using R Studio
13:30–14:00 Lunch break
14:00–15:30 Violation analysis Concepts on violation over standards, violation index/location importance index
15:30–16:00 Hands-on exercise with Q&A
Day 4 – Meterological data and use of remote sensing
11:00–11:30 Q&A and recap mentimeter quiz
11:30–13:30 Meteorological data processing Windrose, pollution rose, and polar plots

How to access and use OpenAir library in R for creating wind, pollution rose diagrams, and polar plots

13:30–14:00 Lunch break
14:00–16:00 Introduction to Q-GIS and processing of air quality data Mapping and spatio-temporal analysis in Q-GIS
Day 5 – Case studies and citizen data science
11:00–11:30 Q&A and recap mentimeter quiz
11:30–13:30 Data interpretation and decision making in AQM Combining violaion analysis, trend analysis, and meteorology for data-driven decision making
13:30–14:00 Lunch break
14:00–15:30 Case studies on application of advanced data analytics in cities Examples on how advanced air quality data analytic practices across the world Analytics from decentralized data collected by citizens using low-cost sensors
15:30–16:00  Closing remarks Participants, ICIMOD team member