Ambient (outdoor) as well as indoor air pollution are key environmental health risk factors contributing to the disease burden. Sources of air pollution include transportation, industries, energy production and use, construction, dust, brick kilns and waste burning among others. Air pollutants can either be released directly into the atmosphere (primary emissions) or can form as a result of chemical interactions (secondary pollutants).
Key air pollutants of interest are described below:
(i) Carbon Monoxide
Carbon monoxide (CO) a colorless and odorless gas, which at high levels can be harmful to humans by impairing the amount of oxygen transported in the bloodstream to critical organs. Although high concentrations of CO are more of a concern indoors, emissions outdoors, particularly in developing countries can be high. New evidence also reveals that long-term exposure to low concentrations is also associated with a wide range of health effects. The main sources of ambient CO include motor vehicle exhaust and machinery that burn fossil fuels.
(ii) Nitrogen dioxide
Nitrogen dioxide, mainly emitted by power generation, industrial and traffic sources, is an important constituent of particulate matter and ozone. There is growing evidence that independently, it can increase symptoms of bronchitis and asthma, as well as lead to respiratory infections and reduced lung function and growth. Evidence also suggests that NO2 may be responsible for a large disease burden, with exposure linked to premature mortality and morbidity from cardiovascular and respiratory diseases.
Ozone is a gas made up of 3 oxygen atoms; it has the chemical formula O3. Ozone found at ground level, where people live and breathe, is formed by chemical reactions between nitrogen oxides and volatile organic compounds in the presence of sunlight. For this project, ozone levels are measured in units of parts per billion (ppb) by volume. Ozone concentrations, averaged over the summer season in each region when ozone levels tend to be highest, are used to represent the exposures experienced by human populations in those regions.
(iv) Particulate Matter (PM)
Particulate matter (PM) are inhalable and respirable particles composed of sulphate, nitrates, ammonia, sodium chloride, black carbon, mineral dust and water. Particles with a diameter of less than 10 microns (PM10), including fine particles less than 2.5 microns (PM2.5) pose the greatest risks to health, as they are capable of penetrating peoples’ lungs and entering their bloodstream. Sources of PM include combustion engines (both diesel and petrol), solid-fuel (coal, lignite, heavy oil and biomass) combustion for energy production in households and industry, as well as other industrial activities (building, mining, manufacture of cement, ceramic and bricks, and smelting).
(v) Sulphur Dioxide
Sulfur dioxide (SO2) is primarily produced from the burning of fossil fuels (coal and oil) and the smelting of mineral ores that contain sulphur. Exposure to SO2 affects the respiratory system and the function of the lungs, and causes irritation of the eyes. Inflammation of the respiratory tract from SO2 can aggravate asthma and chronic bronchitis, as well as increases the risk of infection, leading to increased hospital admissions and visits to emergency rooms. SO2 also combines with water in the air to form sulfuric acid – the main component of acid rain.
2.1 Impacts of air pollution
There is a large body of research on the impact of air pollutants on human health and studies have conclusively shown that long-term exposure to PM increases mortality and morbidity and can lead to respiratory as well as cardiovascular diseases.
2.2 Air Quality Index
The Air Quality Index (AQI) is an index for reporting daily air quality. It tells how clean or polluted the air is, and what associated health effects might be a concern for people. The AQI focuses on health effects people may experience within a few hours or days after breathing polluted air. Countries and regions often calculate AQI with different metrics since their standards are different, rendering it difficult to compare AQIs across platforms, even for data from the same stations (see image below).
Typically, the AQI values are roughly in the following range:
# What is the difference between AQI and pollutant concentrations?
2.3 Measurement and monitoring of air pollution
Fixed-site (ambient) monitoring: Such monitoring is often conducted as part of long-term monitoring networks focused on measurement of air pollutants. Air quality instruments are operated at a particular site over long intervals, and data can be used for understanding temporal patterns and undertaking trend analysis. There are a number of monitor types including manual instruments and real-time air quality monitoring equipment. Costs can vary based on the type of technology being used in the system. Location of air quality monitors depends on the purpose of the monitoring program, and typically, monitoring is conducted across a range of sites including urban, rural and source-impacted sites (e.g., roadside, industrial, commercial etc.).
‘Each of London’s 33 boroughs has a minimum of one and up to half a dozen analysers,’ he explains. These monitoring sites form part of the London Air Quality Network (LAQN) and vary in size from one the size of a post box on Oxford Street to the huge shipping container opposite Madame Tussauds on Marylebone road. Some of the sites measure a single pollutant, such as NO2 or particulate matter (PM), in a location where boroughs are keen to closely monitor air pollution, and others measure the entire range of legislated air pollutants. The large site on Marylebone road and another in South Kensington also take additional measurements solely for research purposes.
Link to article
Low-cost Sensors: Low-cost sensors offer an opportunity to generate high-resolution data at a lower cost, and with fewer deployment and access limitations (Snyder et al. 2013, EST). A number of community projects have been launched worldwide for crowd-funded air pollution measurements, and while such sensors can be useful in designing citizen science projects and generating novel data, there are still a number of uncertainties associated with the accuracy of measurements using low-cost sensors (Lewis and Edwards 2016, Nature). So far, such monitors have not been proven to provide long-term, accurate data without systematic calibration (Lewis and Edwards 2016, Nature; Rai et al. 2017, STOTEN). Efforts are underway to improve precision among such sensors, and latest analyses are supporting the case for deployment of well-designed low-cost sensors for measurement of air pollution at the city level. If designed carefully, such networks can provide valuable data on spatial variability of pollutants, and help in identification of hyperlocal pollution hotspots. Additionally, such instruments can be used as indicative instruments to define and design more efficient regulatory monitoring networks.
Low-cost sensors are currently available for a range of air pollutants including particulate matter (PM), and gases (E.g., nitrogen oxides, ozone and carbon monoxide), and the technology is rapidly evolving leading to improvements at a very rapid pace.
Satellite Monitoring: Data on aerosol optical depth (AOD) is typically collected via satellite overpass measurements (e.g., MODIS- https://modis.gsfc.nasa.gov/) and can be used for AQ applications such as forecasting, tracking pollution sources and plumes, and as input/evaluation for AQ models (Duncan et al. 2014, AE).
The most common use of satellite data has been the use of aerosol optical depth (AOD) data which can be used for estimation of PM concentrations. AOD is a dimensionless number that is related to the amount of aerosol in the vertical column of atmosphere over the observation location, and indicates how much direct sunlight is prevented from reaching the ground by these aerosol particles (more about AOD here). A value of 0.01 corresponds to an extremely clean atmosphere, and a value of 0.4 would correspond to a very hazy condition.
NASA WorldView , an open source project, provides near-real-time data on a daily basis, well suited to event analysis, in a clean, intuitive interface and all data, software and services are freely available for public use.
There are three main ways to use satellite data for policy applications: for qualitative applications (e.g., to detect trends in air pollution or understand spatial patterns), for quantitative applications (to quantify changes over time), and for more advanced analysis (e.g., to derive ground-level air pollution concentrations which can then be used for modelling and health studies). Satellite data have been used for wide-ranging studies, including the estimation of health effects related to air pollution as part of the Global Burden of Disease study, and for detection of agricultural burning and wildfires in India(example 1 and 2).
MODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (originally known as EOS AM-1) and Aqua (originally known as EOS PM-1) satellites. Terra MODIS and Aqua MODIS are viewing the entire Earth’s surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.
Sentinel 5-P was launched in October 2017 and will perform atmospheric monitoring. The Tropomi instrument on board is the most advanced multispectral imaging spectrometer to date, and this allows collection of highly detailed and accurate atmospheric data.
Visible Infrared Imaging Radiometer Suite (VIIRS) collects visible and infrared imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. The data is used to measure cloud and aerosol properties, ocean color, sea and land surface temperature, ice motion and temperature, fires, and Earth’s albedo.
Let’s check out an animation for AOD data over the years.
# How many fixed-site monitors are operating in the Kathmandu Valley?
# Are there any low-cost monitor networks in Nepal?
2.4 Source Apportionment of Air Pollutants
The term, source apportionment (SA) describes techniques used to quantify the contribution of different sources to atmospheric particulate matter (PM) concentrations. Source apportionment techniques are used widely for quantitative estimation of the contribution of different sources to ambient PM concentrations and can be implemented in many different ways, receptor modelling being one of the methods. There are three key approaches for source apportionment including use of emission inventories and dispersion models, receptor models and monitoring data. Essentially, receptor models (RMs) form a subset of source apportionment techniques and apportion the pollutant concentrations based on the measured ambient air data and the knowledge about composition of the contributing sources.
2.4.1 Receptor Models
Receptor models (RMs) form a subset of source apportionment techniques and apportion the pollutant concentrations based on the measured ambient air data and the knowledge about composition of the contributing sources. Such models provide relevant information for development of air pollution management and control programs, validation of dispersion models and are particularly helpful in cases where complete emissions inventories are not available. With the assumption that the relative concentrations of chemical species are preserved between sources and receptors, receptor models use the principle of mass conservation for apportionment of PM mass to different air pollution sources. Chemical receptor modelling methods utilize the chemical composition of airborne particles for identification and apportionment of sources of PM in the atmosphere. Each source has a characteristic emission profile, and differences among the profiles can be used for quantitative apportionment of mass to different emission sources.
2.4.2 Dispersion Models
Dispersion modeling uses mathematical formulations to characterize the atmospheric processes that disperse a pollutant emitted by a source. Based on emissions and meteorological inputs, a dispersion model can be used to predict concentrations at selected downwind receptor locations. Commonly used models include AERMOD and CALINE3.
2.5 How to access air quality data?
There are a number of websites, apps and analog sources for accessing air quality data. Popular websites for AQ data include:
AQICN curates AQI data from more than 60 countries around the world. AQI information can be accessed here. Currently, data from the US Embassy and Phora Durbar stations is available on the website. However, historical data cannot be downloaded from this website.
#Let’s check the current AQI data for Kathmandu on the AQICN website.
OpenAQ fights air inequality through open data, open-source tools, and a global, grassroots community. Because data need a collaborative community for impact. OpenAQ’s community has collected air quality measurements from 8,511 locations in 67 countries, and data are aggregated from 110 government level and research-grade sources. OpenAQ’s mission is to enable previously impossible science, impact policy, and empower the public to fight air pollution. Historical data are available for download and analysis. There is a also a vibrant community which can be useful if you have specific questions or are looking for collaborators.
# Let’s download data for an AQ station for Nepal from the OpenAQ website.
- State of Global Air
In addition to the real-time data, long-term trends can also be useful in determining changing patterns of air quality in a city/region/country. Annual country-level PM2.5 data (and associated mortality/morbidity) data are currently available on the State of Global Air (SoGA) website run by the Health Effects Institute. Data are available for download and analysis.
#Let’s take a look at data for Nepal on the SoGA website.
- Climate Data Store, ECMWF
This is an excellent open repository of meteorological and air pollution data (among other climate-related datasets). Data are available for download and analysis but you will need to register on the website.
- Resource Watch
A WRI product, the ResourceWatch combines a wide range of datasets including fires, power plants, tree cover, urban population and air quality among others.
# Let us try to access a fire dataset for Nepal on the website.
This informational material is from the following websites:
Header Image (link)
- Primer on Air Quality Management (link)
- Primer on Pollution Source Apportionment (link)
- Air Pollution Monitoring 101 (link)
- Global AOD data: AOD data can be downloaded from NASA Earth Observations (NEO) free of cost here. This data comes from Terra/MODIS and Aqua/MODIS.
- HAQAST (Health and Air Quality Applied Sciences Team): HAQAST is a collaborative team that works in partnership with public health and air quality agencies to use NASA data and tools for public benefit.
- NASA ARSET (Applied Remote Sensing Training) program: In-person and online trainings are offered all year round. Keep an eye out for the next training if you are interested!
- Training module on VIIRS (link)
- Air Sensor Toolbox for Citizen Scientists, Researchers and Developers (link)
- A brief history of air quality sensors