Atmospheric Observatory

Atmospheric Observatory at Sonipat, Haryana

Centre for Atmospheric Sciences (CAS), IIT Delhi, has created a world-class atmospheric observation research facility in its Sonipat campus. The Sonipat observatory is currently equipped with six instruments in three focus areas: air pollution, climate, and weather. The observatory will be equipped with numerous state-of-the-art equipment with the latest technology such as radars, lidars, and mass spectrometers to study the atmosphere and climate system. The observatory will enable researchers to make new discoveries about our climate system and find sustainable solutions to some of the country's pressing problems like severe air pollution, erratic monsoon, and various other extreme weather events associated with climate change.

Based on data published by the World Health Organization (WHO)1, New Delhi and 11 other North Indian cities rank among the world's top 25 cities with the worst air quality. In India, poor air quality is estimated to cause more than a million deaths every year2 and a loss of 1.44% of its GDP3. India is also extremely vulnerable to the impact of climate change. Every year, it faces extreme weather events in floods and cyclones, which take lives, destroy homes and agricultural yields, and result in substantial revenue losses. For the last two decades, India has been experiencing more erratic monsoon and extreme air pollution events, thereby posing a real threat to Indian agriculture and our economy.

Continuous long-term monitoring of air pollution and meteorology from this observatory will help us estimate trends and impacts of policy intervention on air quality and regional climate. Real-time source apportionment of air pollutants using observations and modeling from this observatory will provide actionable information to the concerned authorities with immediate and long-term abatement strategies. Measurements of toxicity of air pollutants using state-of-the-art equipment and measurement techniques will enable researchers for the first time to generate an India-specific dose-response function for the health impact of air pollution. Real-time data on vertical profiles of air pollution, clouds, and meteorological conditions will help researchers understand some of the complex atmospheric processes in a much better way. The knowledge gained from the observations will improve the representation of air pollution and clouds in air quality forecasting and monsoon prediction models, thus, reducing errors in forecasting severe pollution, fog, rainfall, and other extreme weather events.


1 WHO Global Ambient Air Quality Database (update 2018)
2 Balakrishnan et al., “The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017”, Lancet Planetary health, 2019
3 India state-level disease burden initiative air pollution collaborators (2021), Health and economic impact of air pollution in the states of India: the Global Burden of Disease Study 2019, Lancet Planetary Health.

Commitments from National and International Agencies

Atmospheric Observatory: Instruments in Place

Theme I: Air Pollution

1. Scanning Mobility Particle Sizer Spectrometer (SMPS) with Optical Particle Sizer (OPS) and DustTrak

Integrated aerosol measurement system with TSI Model 3938-SMPS (Scanning Mobility Particle Sizer Spectrometer), model 3330-OPS (Optical Particle Sizer), and model 8543 DustTrak Environmental Monitor

Real-time measurements of aerosol number and mass concentration and aerosol size distribution (from nanoparticle to super-micron size range) at high resolution


  1. Aerosol particle size and concentration measurements are, in general essential for air quality monitoring and prediction

  2. Real-time measurements help us understand the aerosol concentration variability at a high temporal resolution

  3. Provides information to estimate emission sources of aerosols in the air

  4. Used to describe the evolution of aerosol size distribution in chemical transport models

Other details:

  1. Measure aerosol mass concentration as PM-total, PM10, PM2.5 and PM1.0

  2. 1-nm SMPS has capability for accurate nanoparticle sizing

2. Time of Flight Aerosol Chemical Speciation Monitor (TOF- ACSM)


TOF - ACSM - PM2.5 (Time-of-Flight Aerosol Chemical Speciation Monitor) from Aerodyne Research, Inc.

Real-time measurements of non-refractory aerosol particle mass concentration and aerosol chemical composition


  1. Particulate Matter (PM) mass concentration measurements are, in general essential for air quality monitoring and prediction and air pollution health impact assessments

  2. PM chemical composition measurements help to identify the toxicity of various chemicals in the air

  3. PM and their chemical composition measurements help estimate the aerosol emission sources sectors

Other details:

  1. High measurement sensitivity (10 minute, 3σ) for major PM particles such as organic (0.06 μg m-3), sulfate (0.006 μg m-3), nitrate (0.007 μg m-3), ammonium (0.06 μg m-3), and chloride (0.003 μg m-3)

  2. Aerosol Size range: 40 nm to 1 μm (vacuum aerodynamic diameter)

  3. Allows quantification of organic aerosol species including hydrocarbon-like organic aerosol

3. Aerosol Mass and Optical Depth (AMOD) Sampler

AMOD (Aerosol Mass and Optical Depth) sampler from NASA

Measurements of Aerosol Optical Depth (AOD) and surface-level PM2.5


  1. Simultaneous measurements of AOD and PM2.5 help researchers validate satellite-based aerosol monitoring

  2. Provides information about the relation of AOD with surface PM2.5 concentration

  3. PM2.5 mass concentration measurements are required to monitor and predict air quality and to assess PM2.5 public health impacts

  4. Measurements of AOD help to understand the radiative effects of atmospheric aerosols

  5. Provides data needed to characterize aerosol in the full atmospheric column

Theme II: Climate

4. Greenhouse gas (GHG) analyser

PICARRO G2301 GHG (greenhouse gas) analyser based on CRDS (Cavity Ring-Down Spectroscopy) technology

Real-time continuous measurements of major greenhouse gases (GHGs) such as CO2, CH4, and H2O


  1. Help us understand the GHG temporal variability at a finer scale (say, hourly variation of CO2 concentrations in the ambient atmosphere)

  2. To capture the sudden emission episodes and transport driven mixing

  3. Help us to estimate the sources and sinks (fluxes) of GHGs

Other details:

  1. Simultaneous and continuous measurements of atmospheric concentrations of GHGs such as CO2 (guaranteed precision over 5 seconds: < 50 parts per billion (ppb)), CH4 (< 1 ppb), and H2O (< 30 ppb)

  2. Cavity Ring-Down Spectroscopy (CRDS) optical sensing technology-based laser gas concentration analyser

Theme III:  Weather

5. LiDAR Ceilometer with depolarization measurement

Vaisala LiDAR (light detection and ranging) Ceilometer CL61 with depolarization measurement capability

Real-time measurements of cloud base height (up to 5 layers simultaneously), cloud thickness, cloud type, and vertical structure of low-level clouds


  1. Information on clouds, precipitation, sky condition, dust, and volcanic ash data within the planetary boundary layer (PBL) are essential to predict local weather accurately

  2. Measurements of atmospheric conditions in PBL help to forecast air quality accurately

  3. Ceilometer data needed to represent cloud processes in models better

Other details:

  1. Ceilometer helps detect precipitation/fog and sky condition

  2. Provide attenuated backscatter profiling for the full range of up to 15.4 km

  3. Provide depolarization ratio profile, and parallel and cross polarized backscatter profiles with full range

  4. The depolarization data enables differentiation between solid, liquid, or mixed-phase clouds and precipitation and detection of potential dust and volcanic ash

6. Automatic Weather Station (AWS) with multiple meteorological and solar radiation sensors

A picture containing sky, outdoor, grassDescription automatically generated

SEMS (Solar Energy Measurement System) Model: METEODATA 3000C series AWS (Automatic Weather Station) from GEONICA

Continuous monitoring of meteorological and solar radiation data


  1. Continuous data on meteorological and solar radiation helps to understand daily variation in local weather and better weather forecasting

  2. Help us to understand local variations in air quality and chemical reactions in the air

  3. AWS data on various atmospheric parameters are, in general, needed for weather and climate studies/models

Other details:

  1. Measures atmospheric pressure (barometric pressure sensor with accuracy of ±0.5 hPa at standard temperature), ambient temperature (temperature sensor with accuracy of ±0.2°C with radiation shield, relative humidity (humidity sensor with accuracy of ±3% with radiation shield),

  2. Measures wind speed (sensor with accuracy of ±0.5 m/s or 3% of reading), wind direction (wind direction sensor with accuracy of ±5°),

  3. Measures precipitation with tipping bucket rain gauge with accuracy of ±5% up to 30 mm/hr

  4. Measures global horizontal irradiance (pyranometer with a sensitivity of ≥ 7 to 25 x 10-6 V/(W/m2): un-shaded), diffuse horizontal irradiance (shaded pyranometer), and direct normal irradiance (pyrheliometer with sensitivity range of 10 to 30 x 10-6 V/(W/m2))


Centre for Atmospheric Sciences, Block VI,
Indian Institute of Technology Delhi
Hauz Khas, New Delhi-110 016, India