How low-cost air sensors empower economically developing nations to improve their air quality monitoring infrastructure

How low-cost air sensors empower economically developing nations to improve their air quality monitoring infrastructure

With the advent of accurate and reliable low-cost air sensors, economically developing countries experiencing the detrimental human, environmental, and economic impacts of air pollution can establish comprehensive air quality monitoring networks for the first time. Air quality managers in these regions can bypass the traditional notion that air quality data must come exclusively from federal reference method (FRM) or federal equivalent method (FEM) equipment to be useful. Adopting hybrid Air Quality Monitoring 2.0 networks that leverage data from both FRM & FEM equipment and properly-calibrated low-cost sensors allows them to leverage the low costs, high-resolution data coverage, and flexible network design offered by low-cost air sensors to rapidly and cost-effectively establish precisely-located air quality monitoring networks.

The effects of poor air quality on human health

Air pollution has devastating effects on public health worldwide. The most significant source of human illness and death due to air pollution is particulate matter. Fine particulate matter, also known as PM2.5, is the primary cause of deaths resulting from cardiovascular and respiratory problems, as well as lung cancer. PM10 also contributes to pollution-related deaths. The WHO reports that if PM10 pollution were reduced from 70 to 20 micrograms per cubic meter, there would be a 15% reduction in air pollution-related deaths

In 2016, the WHO reported that 4.2 million deaths occur due to ambient air pollution each year. As our understanding of air pollution’s multifaceted health impacts deepens, the number of preventable deaths that can be traced back to poor air quality continues to increase. 

A new study from a team of U.S. and U.K. scientists published in Environmental Research estimates that fine-particle pollution may cause as many as 8.7 million premature deaths per year, double the WHO’s estimates and three times the combined number killed by HIV/AIDS, tuberculosis, and malaria in 2018. Researchers are still working to understand the full extent of PM’s impact on human health.

The disproportionate impact of air pollution in economically developing regions

Though poor air quality is harmful to human health across the globe, air pollution exerts its most devastating impacts on those in economically developing nations. According to the UN News, 88% of deaths resulting from ambient air pollution occur in developing countries, with the greatest number of deaths occurring in the Western Pacific and South-East Asia. A reported 91% of the total global population lives in areas exceeding the WHO’s recommended air quality levels.

Each year, air pollution causes 7 million premature deaths around the world, with outdoor pollution responsible for more than half of that total...Tragically, these deaths are wholly preventable.” — Achim Steiner, UNEP Executive Director

Air pollution impacts not only human health but also the economies of growing nations. The World Bank reports that ambient air pollution’s impacts on human health cost $5.7 trillion globally, or 4.8% of the global GDP. Individual countries experiencing higher-than-average levels of air pollution can face costs equivalent to 5% to 14% of their GDP — air pollution is an expensive problem to have!

Why air quality is often poor in economically developing countries

Economically developing countries tend to rely heavily on fossil fuels for both domestic and industrial energy production, resulting in elevated levels of air pollution. Polluting fuels such as biomass, coal, and kerosene used for cooking, heating, and lighting release particulate matter into the air. In economically developing African nations, for example, vehicle, powerplant, industrial, and household fuel combustion all contribute to particulate matter release.

Industrial processes can also contribute significantly to air pollution. As economically developing countries by definition prioritize economic growth, there is often little to no regulation of industrial air pollution. Industrial processes that rely on dirty energy sources release large quantities of PM and other pollutants into the air. Poor waste management, including the burning of industrial and domestic waste, can result in air pollution as well. 

In addition to ambient and industrial air pollution, indoor air pollution is another source of illness and death in economically developing regions. A reported 3 billion people around the world depend on coal and biomass as their primary source of domestic energy, and the smoke from these energy sources contain many harmful pollutants, including PM, nitrogen dioxide, carbon monoxide, and formaldehyde. Women and children are disproportionately impacted by indoor air pollution, as they tend to be more exposed to environments that use biomass in open fires and indoor cooking stoves.

The state of air quality monitoring networks in developing nations

While some economically developing countries have air quality monitoring networks in place, many of these regions lack effective or extensive monitoring networks. Without robust air pollution measurement equipment in place, these countries do not have access to the air quality data required to understand and act on pollution trends.

The footprint of air quality monitors in regions such as Europe and Africa are vastly different, demonstrating the inequality in air pollution data availability across the world. Sparsely populated, regional monitors do not provide adequate geographical coverage to monitor pollution in areas with large populations, where air quality tends to be the worst. Image sourced from the Real-time Air Quality Index Visual Map.

For many economically developing countries, investing in reference-grade equipment is not an option due to budgetary constraints, yet air quality data is desperately needed as a first step to mitigating the negative health and economic impacts of air pollution. Hybrid networks that leverage both FRM & FEM equipment and low-cost air sensors present a compelling solution for countries in this situation. 

Developing countries can use low-cost sensors to establish air quality monitoring networks for the first time

Developing countries have traditionally believed that they face a trade-off between economic development and environmental health, but we now understand that economic and environmental health are deeply intertwined. Unchecked pollution comes with significant economic costs that cannot be overlooked. 

The same activities that damage air quality also tend to produce greenhouse gases, which further weaken the economic wellbeing of developing countries — the World Economic Forum reports that economically developing regions will bear 75-80% of the impact costs from climate change. 

Collecting accurate, widespread data is the first step in taking action to reduce air pollution and mitigate the significant human and environmental costs of air pollution. As our understanding of the economic costs of air pollution deepens, politicians have begun to act with more urgency to address air pollution in developed and developing countries alike. 

By utilizing low-cost air quality sensors, developing countries can bypass expensive traditional air quality monitoring technologies and quickly establish high-resolution networks that produce valuable data*. This approach empowers economically developing regions to begin to make informed, data-driven decisions about air quality.

* It is important to note that for an indicative monitoring network to produce usable data, a colocation with an FRM or FEM-grade instrument is required. This can be a challenge in locations with little or no reference-grade equipment, but can be resolved by borrowing or renting reference-grade equipment for the relatively short period of time required for a colocation. This solution is much more cost-effective than purchasing reference-grade equipment outright for colocation purposes. 

The UNEP in Kenya reports that for about the same cost as a single monitoring station, countries can set up entire networks using low-cost sensors. Indicative air quality sensors allow for higher-density deployment for the same cost, as well as more flexible deployment scenarios that can be tailored to meet individual countries’ needs. Air quality data can be collected from a large number of low-cost sensors dispersed across a city or region to get an accurate sense of local trends in pollution.

These sensors are affordable enough that they can be deployed at the neighborhood level by communities in areas where air pollution is particularly bad. Traditional monitors spaced far apart can easily miss these more granular changes.

In Bengaluru, India, for example, the local community leveraged funding from NGOs to install 30 low-cost air quality sensors across the city in 2019. The network was deployed at strategic locations across the city, with an emphasis on sites frequented by vulnerable populations such as schools and hospitals. You can read more about the Bengaluru air quality monitoring network and its impact on the community here

Clarity Node-S low-cost air sensors were deployed in hospitals around Bengaluru to measure air pollution.


Traditional monitoring networks are also expensive to maintain, difficult to locate, and require significant planning and lobbying to obtain funding and permitting from the local government. Indicative sensors can be easily and quickly deployed in large numbers and do not require infrastructure to house the monitors, presenting fewer barriers to entry.

In Kinshasa, the capital city of the Democratic Republic of Congo with a population of 11 million people, air quality monitors have only been put into place for the very first time recently, demonstrating the large gap between investment in air quality monitoring infrastructure and the need for pollution management. The affordability of low-cost air sensors can make air quality measurement possible in places where air quality data has never been available before. 

Recently, several Clarity Node-S sensors were also installed in Brazzaville in the Republic of the Congo to better understand and characterize air quality in the region. 

Two Clarity Node-S displayed at the US Embassy in the Democratic Republic of the Congo. The solar-powered air pollution monitoring devices will be installed as part of a collaboration between Dan Westervelt of Columbia University’s Lamont Doherty Earth Observatory and Marien Ngouabi University in Brazzaville, Congo, facilitated by the US State Department Air Quality Fellows program.


Economically developing nations can also face challenges in holding polluters accountable for the damage they cause to human and environmental health. This is partially due to the financial and political resources required to do so, but the lack of adequate air quality data is also a significant challenge when pursuing regulatory action. 

The data collected by low-cost sensors is highly localized, allowing authorities to pinpoint pollution trends and sources and enact fines to discourage further pollution. Clarity has recently been working with the environmental agencies of several African nations to establish air quality monitoring networks for this purpose. 

Because air quality data from these networks will enable the collection of fines by regulators, they will quickly become financially self-sustaining. The ability to enforce air quality regulations against polluters will generate funds that can be used to sustain and grow the networks. This funding will also be used to promote further air quality initiatives such as clean-up efforts, and grants for other clean air programs. 

Punishment for violating pollution laws incentivizes greater political and financial support for these policies, generating a cycle of support for cleaner air. The snowball effects of less air pollution and slowed climate change can also benefit agricultural production, decrease drought duration, and slow the spread of diseases. 

The benefits of monitoring air quality in economically developing regions

Investing in low-cost sensor networks empowers developing countries and their citizens with direct, transparent access to pollution data. Data is the basis of understanding air pollution and the first step to mitigating it. Having an extensive air quality monitoring network of properly-calibrated low-cost sensors enables data-driven and educated decision-making.

By establishing an air quality monitoring network, developing countries can improve their citizens’ health, decrease air pollution-related deaths, and bolster their economy:

[P]ollution management can enhance competitiveness, for example, through job creation, better energy efficiency, improved transport, and sustainable urban and rural development” — World Bank

Hybrid air quality monitoring networks that leverage indicative sensors also promote greater environmental justice because of the granularity of the data they collect. While traditional air quality monitoring networks can miss neighborhood-level pollution changes, networks that leverage indicative monitors shed light on these disparities, which are often rooted in racial and economic inequality. On a global scale, greater air quality data coverage helps to address the data gap between developed and developing countries.

Data-driven air quality policy and regulatory enforcement also contribute to climate change mitigation, which benefits both individual countries and the planet as a whole.

In fact, the economic benefits of good air quality alone often outweigh the costs of climate change reduction strategies. Calculations based on the reduction of deaths, illness, and lost workdays in the United States due to temperature increases from air pollution total an approximate $700 billion per year in savings. Because developing countries disproportionately bear the damages and costs from global air pollution deaths, this number would likely be even higher for such regions. These savings far outweigh the costs of actions to reduce climate change.

Economically developing nations around the world are evaluating this hybrid approach to air quality data collection, and we expect to see more developing countries adopt hybrid networks that leverage the strengths of both FRM & FEM and low-cost sensors equipment in the coming years. 

It is important to note that even countries with established air quality monitoring networks such as the United States can benefit from the affordability of indicative monitoring networks. You can read more about the United States Congressional Accountability Office’s recent recommendation for low-cost sensor deployment in the United States here.

Economically developing countries can adopt Air Quality Monitoring 2.0 to rapidly and cost-effectively build air quality monitoring capacity

Economically developing nations often face the highest levels of air pollution, yet rarely have the air quality monitoring infrastructure required to address it due to the prohibitive costs of traditional air quality measurement technologies.

By implementing properly-calibrated low-cost air quality sensors alongside owned or rented FRM & FEM equipment, developing regions can leapfrog the traditional, cost-prohibitive approach to air quality monitoring network design in favor of hybrid Air Quality Monitoring 2.0 networks. This approach comes with a range of benefits including a lower upfront investment when establishing a network, higher-resolution data coverage, and flexible network design to fit the unique needs of each region.

Improved air quality promotes greater citizen health, life expectancy, and environmental justice. Countries also benefit economically when pollution-related damages are mitigated, creating a virtuous cycle in which cleaner air leads to a more resilient economy and a healthier population.

Leave a comment

Please note, comments must be approved before they are published