LocationsThis is the fourth article in the Blog Article Series on Air Pollution.
This image was generated with the assistance of DALL·E 3
Currently, 55% of the global population resides in urban areas, a figure that is predicted to rise to 68% by 2050. Forecasts indicate that urbanisation along with the overall population growth, could result in an additional 2.5 billion people living in urban regions by 2050. Nearly 90% of this increase is anticipated to occur in developing countries in Asia and Africa, which are also experiencing the fastest rates of urbanisation.
As urban centres worldwide grapple with air quality challenges, innovative monitoring techniques are becoming increasingly useful for effective environmental management and public health protection. Building on previous articles on the potential of low-cost sensors (LCS) for air quality monitoring, this article delves into the findings of a two-year study conducted by the Singapore's National Environment Agency (NEA).
Image comparison of a LCS and an air quality monitoring station
NEA
The NEA has conducted a two-year field trial on the use of LCS to monitor ambient air quality, namely fine particulate matter (PM2.5) and nitrogen dioxide (NO2), within a residential estate in Singapore.
In this article, we will share the assessments and insights gained which included the:
- Performance and reliability of LCS in continuous ambient air monitoring
- Dispersion patterns (vertically and horizontally) of air pollutants within a residential estate
- Insights on air pollutant levels across the estate with integrated dispersion modelling capabilities
The use of such LCS technology provides a good alternative method of monitoring air quality, as it is cost-efficient, easy to install and maintain, and can be placed where there are land constraints. Although the accuracy and sensitivity of the measurement are not as high compared to the more sophisticated scientific analysers (fixed ambient air monitoring stations) such as those that adopt the United States Environmental Protection Agency (USEPA) Federal Reference Method, these sensors are still able to provide valuable insights on localised air quality and its dispersion patterns in a built-up urban environment.
Background
The study deployed a network of 30 LCS across the residential estate and were strategically placed on lampposts and overhead bridges along/next to the expressways and roads, as well as at various heights to monitor both horizontal and vertical dispersion patterns of the air pollutants.
LCS deployed across a residential estate
NEA
Sensor Performance
The field performance of the sensors was good, with excellent solar charging of batteries and cellular signal strength. The air quality data completeness was close to 100%, and the accuracy of the measurements met the USEPA’s recommended guideline target values.
Insights on Air Quality Within the Residential Estates
The study showed that the buffer distance and/or green buffers between the expressways and roads and residential buildings has an influence on the air quality although the air quality remained within the 2005 WHO Air Quality Guidelines.
A diurnal pattern in the PM2.5 levels was also observed which correlated with the traffic patterns along the expressway, with pollutant levels rising from midnight and peaking at 7am.
Vertical Dispersion of Air Pollutants
It was found that the PM2.5 concentrations exhibited a non-linear vertical dispersion pattern, decreasing in levels as it dispersed upwards to about 17m above ground, before increasing in levels at higher elevations. The trees (at varying heights) and flora planted between the expressways and residential buildings and within the estate had provided a buffer effect resulting in a reduction in the PM2.5 levels at the heights of these green buffers. Beyond the height of the trees and green buffers, the air pollutants converge resulting in the increased PM2.5 levels observed, after which winds disperse the pollutants.
For NO2, the concentrations were observed to be highest at ground level and generally decreased with elevation. This dispersion pattern could be influenced by NO2 absorption by the trees and flora, and other complex chemical processes in the ambient atmosphere.
Diagram showing PM2.5 deflection over the top of trees
Cleugh, H. A. (1998). Effects of windbreaks on airflow, microclimates and crop yields.
Horizontal Dispersion of Air Pollutants
In general, with greater distances from the pollution source, i.e. vehicle emissions along expressways and road dust, there is a greater dispersion of air pollutants. This was observed where the pollutant levels decreased with distance from the expressways and roads. The presence of plants and trees between the expressways and road further added to the filtering (or trapping) effect especially for PM2.5. This shows that while the flora can provide a filtering effect, by trapping the particles in between the leaves, the removal of particulate matter is not permanent as it can be resuspended by winds, unless rainfall washes away the trapped particles from the leaves and deposits them on the ground.
Enhancing Monitoring Capability with the Integration of Air Dispersion Model
The integration of the LCS data with a customised air dispersion model had enabled a mapping of the air quality across the residential estate. Real-time meteorological data, traffic emissions, and LCS measurements, were taken into account to generate hourly air quality heat maps, thereby providing a continuous assessment of air quality within the estate.
Key insights gained included:
Higher PM2.5 and NO2 levels were observed at traffic intersections, likely due to vehicle deceleration and acceleration patterns.
Pollution levels decreased rapidly with distance from these hotspots, indicating effective dispersion in the urban environment.
Most residential areas, including those near intersections, showed pollutant levels within WHO guidelines.
Continuous Coverage of Air Quality Data vs Discrete Data Point from Individual Sensor
NEA
Future Use of LCS
This study showed that data from LCS by themselves, or when combined with a dispersion model, can be useful for cities to understand the complex air quality patterns within cities and neighbourhoods. Air quality information can be provided for a localised area at high spatial resolution to gain insights into air pollutant accumulation and dispersion within an estate. Such insights can be useful for urban /city planning and development and facilitate in identifying suitable interventions to safeguard the health of residents and the public.
Moving forward, NEA will be exploring the use of such LCS in other resident estates to better understand and assess if similar pollutant dispersion patterns and insights are observed, which could help in future estate development in Singapore and optimise the use of green buffers and flora to safeguard the health of the public in an urbanised and dense city-state.