Air Dispersion Modeling: An Effective Tool for Air Quality Management
Kaibigan ng Kaunlaran at Kalikasan ("KKK" or Friends of Progress and the Environment) is a Philippine Non-Government Organization organized in 2008. The KKK's mission is to provide science-based holistic perspectives to government policy makers and to stakeholders, to encourage a united approach with regard to sustainable development.
KKK recognizes that even the most basic air pollution precautions can have a radical influence on the success of environmental protection efforts, if such measures are embraced by community leaders. Policy makers and stakeholders are key factors in the promotion and acceptance of air quality management strategies.
Unfortunately, some of these precautions are met with skepticism and resistance, making it very difficult to shift the course of environmental transformation towards a healthier direction.
One cause of this resistance is the gap of knowledge between those who have the relevant information and the people whose cooperation is necessary for the proper implementation of these remedies.
In order to implement the necessary environmental precautions, industry experts with knowledge of the problem must have a common view of the situation with the stakeholders of relevant corporations, the transport sector, the oil companies, as well as the greater public.
KKK recognizes that it is of great importance that this gap be bridged; that people be informed about the process of how air management strategies are devised, because a better understanding of the issue would inspire more cooperation and diligence from everyone involved.
KKK's primary approach to solving environmental issues is reflected in their mission statement; they seek, "To address environmental issues through the lens of science in order to clarify current difficulties in the understanding of these issues and thereby minimize conflicts arising from them."
This desire to inform both community leaders and the public has compelled the organization to produce their own website that focuses on the latest trends and technologies regarding pollution management, with the intention of turning the website into a knowledge resource that is available to everyone.
Included in the site is information about The Metro Manila Air Dispersion Modeling Project.
Shell Philippines provided the funding for a project involving an Air Dispersion Modeling for Metro Manila that is expected to be completed by July 2015. This project was accomplished through a combined effort among Kaibigan ng Kaunlaran at Kalikasan (KKK), Clean Air Asia, individual professionals, with cooperation from the Manila Observatory.
By way of a background the much earlier modeling done in 1990 under the URBAIR project had limited emissions inventory. The meteorological data, vital to the model was sourced from limited PAGASA stations. The software use was a Norwegian model compared to the more updated model used in the current work.
In the early 2000s another modeling work was done for the DOH to make assessment on health impacts of air quality. More expanded emissions inventory were used using GIS map of all roads in Metro Manila.
In contrast, the current works include households and street side emissions at the municipal and barangay levels. Traffic data are more extensive and are based on hourly information and on actual counts covering all roads except the barangay roads.Three-dimensional meteorological data which are now available are used.
The current modeling technology used is a state-of-the art in regulatory modeling.
This project was presented in the World Cities Summit Forum in Singapore, by Clean Air Asia's Deputy Executive Director Glynda Bathan-Baterina. During her presentation she discussed how air quality management would greatly benefit from the development of a comprehensive emissions inventory. Such an inventory can be used as a tool to identify the key sources of emissions and what reduction measures are appropriate for specific areas.
Air Dispersion Modeling (ADM) provides exactly this kind of information; information that will help key leaders identify the correct strategy for Air Quality Management. What enables dispersion modeling to make measurements with this level of accuracy is its use of mathematical formulations in characterizing atmospheric processes. It is able to trace emissions to as source and predict concentrations by measuring a number of meteorological factors.
This methodology has been presented in several meetings and conferences, and has gone through rigorous examination, to check the efficiency and accuracy of this method of air quality evaluation.
On August 31 2014, a presentation about the area source emission factor study related to the emission inventory component of the project was delivered at the International Aerosol Conference (IAC).
On September 12, 2014, the project team met with Assistant Director Eva Ocfemia of the Department of Environment and Natural Resources – Environmental Management Bureau (DENR-EMB). In that meeting, the project team presented the objectives, status, and outcome that EMB can consider for inclusions in the National Air Quality Status Report.
On November of 2014, the preliminary result of the emission inventory component was presented in the "Cities Solutions of for Clean Air" session of the BAQ 2014 conference that was held in Colombo, Sri Lanka.
The purpose of these presentations is to allow the project to be scrutinized by the top experts in the field. The rationale for the project has always been to provide objective, scientific information that would best allow for the composition and implementation of the most rational policies.
Traditional air quality monitoring baselines are simply not enough to provide a complete picture of what air quality management tools and strategies are necessary for the given area. For one, the traditional model has limitations with regard to how accurately it can measure air quality since the EMB monitoring stations are limited. Furthermore, the traditional baseline does not provide input on where the pollution comes from.
With the ADM, we will be able to produce a visual chart that could display various levels of PM2.5 in Metro Manila. In addition to that, the project also seeks to identify and indicate which factors contribute to air quality (PM2.5).
An Air Dispersion map of Metro Manila illustrated above indicates levels of air quality within the various sectors of Metro Manila. The red zones represent "hot spots" wherein air pollution is bad, green areas represent "good zones," and yellow areas represent those within acceptable limits.
A quick glance at the graph reveals that not all areas require equal levels of air quality management, simply because air quality in Metro Manila is not uniform for each area. Some areas have a higher level of air pollution, yet the tools used to monitor baseline pollution rates fail to detect these differences and what causes them.
Instead of making policies based on "problem areas," ADM would allow for a source-centered approach, pinpointing the source of the problem itself, so that the policies developed to prevent pollution are directed towards specific sources.
For example, one policy that could be developed based on the data collected through Air Dispersion Modeling is the necessity of regulating the quality of fuel used for vehicles, the type of vehicles allowed on the road, and the regulation of stationary sources of emissions, such as small grill businesses popular in urban areas like Manila.
These factors play a dominant role in air quality and air quality management, but these problems exist in a very specific environmental context. Every environment needs a different set of solutions, because environments differ from each other. Air Dispersion Modeling is among the few methods that can allow for the strategic development of area-specific solutions.
There is a need to harmonize traditional measures with ADM. The implementation of such a harmonization will allow for a more sensitive analysis of multiple contributing factors; information that is not available through traditional air quality monitoring baselines.
For one, ADM factors in the climate and the area's topography to come up with more accurate results, regarding where the pollution is coming from and where it is going. It provides meteorological information regarding where the wind is going, how fast the wind is going, where rainfall will land, and how much humidity an area has. ADM considers the density of tall buildings and how the presence of these structures could prevent air from properly ascending to the atmosphere, thus keeping the pollutants at ground level.
Aside from that, ADM can also provide in-depth information on how road traffic, the types of vehicles found on these roads, and even the fuel these vehicles use can contribute to the growing problem of air pollution.
There is a need to combine the traditional monitoring baseline with Air Dispersion Modeling. Doing so would allow for the provision of input about where the pollution is coming from. Aside from that, this harmonization also allows for a more sensitive analysis of multiple contributing factors (traffic, topography, climate, etc.); information that is not available through traditional air quality monitoring baselines.
A shift towards this combination will provide community and industry leaders the necessary data to make the most informed decisions about which air management strategies is most appropriate for their specific situation. More importantly, this shift could improve the public's general understanding of which factors create dangerous air conditions and encourage them to make their own personal contributions to the proper management of air pollution.
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