Street Canyon Effect — a useful model?

I mentioned briefly about the Street Canyon Effect in my previous posts, and I thought that I should be elaborating on what it is about in more detail.

In summary, the street canyon model is a model of air pollution on the streets, flanked by columns of high rise buildings (what we increasingly see in urban areas). Important geometrical information for this model includes the aspect ratio (aspect ratio = height of buildings/width of street), which is used to classify the street canyons into different categories.

Because the street canyon affects the temperature, wind speed, and wind direction within the canyon, it consequently affects the air quality within the street canyon. For instance, through fluid mechanics, researchers found that street level pollution through contributions by vehicle exhaust is higher at the leeward side as compared to the windward side. Neighbouring street canyons may also affect the type of wind flow and hence air quality.

Why is this important?

  1. Implications of Traffic-related Air Pollution (TRAP) — small particulate pollutants such as PM2.5 and other traffic pollutants are harmful to health. In fact, the Global Burden of Disease 2010 estimated that 3.1 million deaths are due to exposure to ambient particulate matter.
  2. Increasing urbanisation trend in many regions around the world meant that more people are exposed to heavy traffic associated with the urban environment.

Researchers have applied this model to many different cities. One example is the research by Zhou and Levy (2008) on the impact of street canyon effects on population exposure to traffic pollutants in mid-town Manhattan, New York City, using the Operational Street Pollution Model (mentioned 2 posts previously!)  which is based on the Street Canyon Model. Their research found that there is a pressing need to control mobile emission sources on the streets to reduce population exposure to traffic air pollutants.

Also, Hong Kong is notorious for its street canyons; perhaps the air purifier (that I posted about yesterday) will definitely be a step to targeting the city’s pollution issues.

All in all, there are practical usage of such models, especially since it is hard to obtain data from every single region. However, we must always be aware of any potential limitations — for instance, the exclusion of certain air pollutants, simplification of reality to models (because that will happen to make models work!).

Sources:

Cheung, C. and Kao, E. (2015). Scientists examine the health risks of Hong Kong’s notorious “Street Canyons”. South China Morning Post. [Online] Retrieved from: http://m.scmp.com/news/hong-kong/article/1615357/scientists-examine-health-risks-hong-kongs-notorious-street-canyonsscientists-examine-health-risks-hong-kongs-notorious-street-canyons [last accessed: 9 April 2015]

Wang, A. and Ho, B. (2013). Characterising Urban Street Canyons in Downtown Vancouver. [Online] Retrieved from: http://ibis.geog.ubc.ca/courses/geob370/students/class13/bho/ [last accessed: 9 April 2015]

Zhou, Y. and Levy, J. I. (2008). The Impact of Urban Street Canyons on population exposure to traffic-related primary pollutants. Atmospheric Environment 42(13): 3087-3098.

Air Purifier as a Bus Stop?

Hong Kong’s air pollution is extremely bad. And a recent article shows how one company, Sino Group teamed up with another, Arup, to develop a roadside air purifier. The air purifier, while being unable to solve the problem directly (point and diffuse sources of air pollution such as industries, mainly from mainland China, and vehicles on the streets), at the very least emphasises how bad the air is for residents.

This purifier can remove pollutants such as PM2.5 too, and pumps out the clean air at the top so that the device forms an air curtain, and may also cut down the street canyon effect caused by buildings (the street canyon model is also used for the OSPM model mentioned in the previous blog posts!)

I have to replicate the photo from the article here, just to show how it actually looks like!

Clifford (2015) however notes that if the government were serious about minimizing street level pollutants, they should be actively trying to reduce the number of pollution sources too. I do agree with that but I suppose a stark reminder about the poor air quality seems to be a good campaign method — it has at the very least, caught my attention even though i am viewing it on a computer screen. Reducing pollutants just not involves active measures, but also about being sufficiently aware and sustaining the reduction through an understanding and awareness of the present day scenario.

Sources:

Clifford, M. (2015) Beat the Hong Kong Smog: Outdoor Air Purifier Doubles As Bus Stop. Forbes. [Online] Retrieved from: http://www.forbes.com/sites/mclifford/2015/04/07/beat-the-hong-kong-smog-outdoor-air-purifier-doubles-as-bus-stop/ [last accessed: 8 April 2015]

Six Cities Study (the US) — Air Pollution and Mortality

When we meet with the smog (or hazy air), our first reaction tends to be because it is unsightly and it is foul-smelling, and not because it is harmful to our health. While we have much more knowledge about how harmful air pollutants are (especially small particulates such as PM2.5), back in the 1970s this was not always the general knowledge.

Let us not forget that it took a serious hazy event in 2013 for Singapore to include PM2.5 in its Pollutant Standard Index (PSI) too.

A guide to reading the PSI released by the NEA in 2014 (with PM2.5 included within the PSI readings). Retrieved from: http://www.nea.gov.sg/images/default-source/anti-pollution-and-radiation-protection/psi-handy-guide.jpg?sfvrsn=2

As such, the “Harvard Six Cities Study” is famous for being one of the first to look at the correlation between air pollution and mortality over a long time period, and which lead to substantive action taken by the US government to regulate fine air particulates. The study reported the mortality of 8,111 randomly selected residents from six different U.S cities — Harriman (Tennesse), Portage (Wisconsin), St. Louis (Missouri), Steubenville (Ohio), Topeka (Kansas) and Watertown (Massachusetts) — with the aim of estimating the effects of air pollution on mortality while keeping other risk factors under control. These randomly selected residents were recruited between 1974 and 1977, and had their medical and occupational history recorded. These participants were also subjected to lung function tests. Air quality from their surroundings is taken by both ambient air monitoring stations in their towns, and also from air sampling devices worn by some participants or such devices from their homes. These residents were contacted all the way till 1991 to determine their health status, while death certificates are collected for those who have passed away in order to find out what is their cause of death.

What the study found is that mortality due to lung cancer and cardiopulmonary disease is most strongly associated with levels of fine air pollutants. Many other researchers have published follow-up articles based on this research (which is neatly summarised by the article from The Pump Handle by Monforton (2012).

Just last year, 20 years after the follow-up research for the study ended (in 1994), the lead author of the original paper, D. Dockery, gave a brief overview on what changes there have been since the study was published. These include new standards put in place by the Governmental Protection Agency (EPA), and an improvement in both health and air quality in the six cities from the original study. Another important point he made is that the federal Office of Management and Budget found that the largest estimated benefit from all federal regulations in 2007, is the reduction of just one air pollutant — fine particulate matter. The impacts of the study not just includes new standards in place, but has also laid “a firm scientific foundation for regulatory policies” .

This “six cities study” and it’s subsequent follow-ups definitely paint a clear picture of what is at stake for air pollution, and the benefits that cities may reap (not just in terms of health) if they take active steps to decrease the amount of fine particulate matter in the air.

Sources:

Dockery, D., Pope, C. A., Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., Ferris Jr, B. G. and Speizer, F. E. (1993). An Association between Air Pollution and Mortality in Six U.S. Cities. The New England Journal of Medicine. 329:1753-1759

Feldscher, K. (2014) Landmark air pollution study turns 20. Harvard School of Public Health — Featured News Stories. [Online] Retrieved from: http://www.hsph.harvard.edu/news/features/six-cities-air-pollution-study-turns-20/ [last accessed 3 April 2015)

Lauerman, J. F. (n.d). A Tale of Six Cities. Flue Cube. [online] Retrieved from: http://www.fluecube.com/harvard-six-cities [last accessed: 4 April 2015]

Monforton, C. (2012) Public Health Classics: Assessing air pollution and health in six U.S. cities, researchers’ findings changed the air we breathe. The Pump Handle [Online]. Retrieved from: http://scienceblogs.com/thepumphandle/2012/11/02/public-health-classics-assessing-air-pollution-and-health-in-six-u-s-cities-researchers-findings-changed-the-air-we-breathe/ [last accessed: 4 April 2015]

National Environment Agency (2014) PSI (with effect from 1st April 2014). PSI. [Online]. Retrieved from: http://www.nea.gov.sg/anti-pollution-radiation-protection/air-pollution-control/psi/psi [last accessed: 3 April 2015]

Traffic Pollution Modelling — Article Summary

After several posts about pollution sources and effects of street pollution, I thought that it would be interesting to look at how researchers observe and track pollution. One way that they do so is by modelling; modelling is a useful tool to have for long term predictions, but as this paper by Berkowicz et al (2006)  will show, there is still room for improvement for these models.

The paper summaries comparisons between data obtained from traffic pollution modelling with the COPERT model and OSPM mdoel (Operational Street Pollution Model) and that of actual street level measurements. They found that there are significant underestimations present in the modeled data, and proposed a new set of parameters (traffic emission factors, to be precise) which appears to give more accurate results.

Why is modelling prone to inaccurate data? This is because of what modelling actually is. For instance, modelling looks at data on source emissions, which is often calculated based on 1) traffic data and 2) vehicle specific emission factors. These are sometimes not actual measurements; for instance, the authors note that vehicle specific emission factors are often estimated with different methods and are found not to just vary according to vehicle type, but also on driving conditions — this is something that had not been taken into account.

Parameters assigned to different models may also be problematic. For instance, the COPERT modelling in European context aims to be a simple method for estimation of national emissions of traffic related pollutants. It uses vehicle emission factor, which is a function of vehicle speed; differentiation between vehicle types, fuel used, engine capacity or weight, emission legislation category. It also includes correction for cold starts and degradation of emission reduction equipment with mileage. This sounds good, and simplified, but unfortunately the authors note that the parameters used may be erroneous.

For example, they thought that emissions predictions on the national is not quite possible because it is difficult to isolate source pollutions on the national level — there are many variables that complicates pollution levels, as compared to merely street measurements.

Meanwhile, the Danish OPSM model (Berkowicz, 2000; cited in Berkowicz et al, 2006), is a simple parametrized model (parametrization of flow and dispersion conditions — how air pollutants are dispersed in the atmosphere —  in street canyons). The good thing about this model is that it requires little CPU time so that the model can be modeled for longer time periods — this is useful because this is precisely what models try to do (predicting what will happen in the long term given a certain set of conditions)

However, an important result from this paper is that while models provide a good estimation for street level pollution, they are rather unreliable when it comes to providing data urban /regional studies. This is because it is easier to isolate pollution sources on the streets, as compared to that of the whole region. Despite so, traffic pollution modelling is a tricky process.  Factors involved in modeling may be inaccurate, and may result in underestimation of data (for instance, too low emissions attributed to heavy diesel traffic (5% of traffic) resulted in  underestimations of NOx on the street of Jagtvej, Copenhagen, by almost 30%, and an underestimation of CO2 by 60%.

The authors concluded the paper by warning readers that it is essential to note any potential biases from inaccurate emission values attributed to different vehicles, and calls for more comparison between models and actual street level measurements. These information will better improve existing models.

Source:

Berkowicz, R., Winther, M. and Ketzel, M. (2006). Traffic pollution modelling and emission data. Environmental Modelling and Software 21: 454-460

Throwaway Culture a cause of Increasing Pollution?

Clean Water Action (CWA), an American environmental advocacy group working for clean, safe and affordable water in the USA, found from their research in Oakland, Richmond, San Jose, and South San Francisco from October 2010 to April 2011 that the biggest source of rubbish on the streets is fast food, accounting for 49% of the total rubbish collected. They also claim that up to 21% could have been eliminated by reusable alternatives.

The contribution of rubbish thrown on the streets to pollution is something authorities should look into and try to minimise. Not only is rubbish unsightly on the streets, it also contributes to the pollution of waterways (For example, stormwater pollution, which I briefly wrote about 2 months ago!). In addition, improper waste management is not enviornmentally sustainable — an article from The Guardian by Walshe (2013) describes how New York’s waste management used to include using garbage trucks that are sent to landfills, and how residents are affected by not just the sight but also the stench of rubbish.

What other cities have been doing include recycling and conservation efforts to reduce the amount of rubbish generated, so it is not merely a shifting of rubbish out of sight but includes actual management. However, Walshe (2013) points out that not only is it hard to change the disposable mentality of New Yorkers, the lack of public recycling facilities and ineffective measures (such as the nickel deposit on bottles) are factors affecting for the lackluster recycling measures in the city of New York. For instance, Walshe notes that the “nickel deposit on bottles” are not seen as valuable enough to encourage people to claim them by recycling — most people do not feel that the nickel (approximately 5 cents) is worth the trouble.

This is something that perhaps we can consider when thinking about measures to target pollution: can we think of something that people will be willing to comply with, and yet economically sustainable? I do not think that a ‘carrot and stick’ approach will necessarily work in the long run (perhaps the ease of improper disposal of rubbish and excessive use of energy resources, for example, is an easier option for many people such that small monetary benefits may not be significant), and the change in mindset is something that is much harder the cultivate but yet much more sustainable.

How then, do we change behaviour? In these articles’ cases, how do we modify the throwaway culture?

As cliche as it sounds, we have to work from the ground. And before we can start thinking about changing the mindsets of other people, we should perhaps look at how we can modify our daily habits to reduce the amount of disposable trash that we generate. For instance, we could bring our own containers when ordering take-aways (it will be interesting to know how successful is ProjectBox by NUS SAVE — the initiative lets staff and students obtain a $2 discount off their next canteen meal if they use their own containers for 10 times). I have not tried this myself, but the last time I am at the canteen, I still saw these printouts pasted on the canteen stores.

Sources:

Cheeseman, G. (2011) Fast Food Garbage Makes up 50% of street (and Pacific Gyre) litter. Triple Pundit. [Online]. Retrieved from: http://www.triplepundit.com/2011/06/fast-food-big-source-trash-pollution/ [last accessed: 27 March 2015].

Walshe, S. (2013). New York’s Waste Management plans don’t address throwaway culture. The Guardian [Online]. Retrieved from: http://www.theguardian.com/sustainable-business/new-york-waste-management-plans-conflict [last accessed: 27 March 2015]

Gadgets to monitor air quality at Edmonton

I came across this interesting initiative to help raise awareness on air pollution in the city of Edmonton, Alberta.

In response to the poor air quality (in particular, during the 2009/10 and 2010/11 winters when calm wins and a temperature inversion trapped air pollutants in the city) in Edmonton, Alberta Capital Airshed (a provincial industry and environmental advisory group) are partnering with city authorities to make portable and personal air quality monitors for citizens in the city by making use of crowd-mapping software with the help of HabitatMap. This is done with the aim of raising awareness about the dangers of poor air quality which residents may not be aware of, such as that of PM2.5 which are too small to be seen with the naked eye.

How the monitors work is that participants will bring their monitors along, and the monitors will take in data which will be uploaded real-time to an online map that is available to the public. These monitors measures the amount of PM2.5 in the air by running a small stream of air past an infrared LED light. A small sensor located in the device measures how much light is scattered by the PM2.5 particles in order to detect the PM2.5 concentrations in the air.

Here is a picture of the monitor!

Picture of the air quality monitor which will be provided to some residents of the city of Edmonton. Source: https://postmediaedmonton.files.wordpress.com/2015/02/airbeam-project.jpeg?w=300&h=225

Sources:

Slote, E. (2015) New air quality gadgets demystify pollution. Edmonton Journal [Online] Retrieved from: http://www.edmontonjournal.com/quality+gadgets+demystify+pollution/10830951/story.html [Last accessed: 21 March 2015]

Noisy Roads

Noise is a prominent feature in many urban areas, coming from not just transport but also industries. There are various studies done on the effect occupational and environmental noise exposure on humans, such as that by Stansfield & Matheson (2003), and also the effects of noise exposure on the ecology system (Forman & Alexander, 1998). I’ll try to give a brief summary on these two papers.

Noise as an environmental stressor and nuisance (Stansfield & Matheson, 2003), and is found to cause progressive loss of hearing (under continuous exposure), with an increase in the threshold of hearing sensitivity. Other than auditory effects on health, continuous exposure to noise can give rise to a host of other problems for the human population too.

  • Sleep disturbances
  • Impaired cognitive performances
  • Cardiovascular Diseases
  • Psychological disorders

Meanwhile, Forman & Alexander (1998) highlights how roads impact local ecology with various local hydrological and erosional effects. I will however, focus on the section on ‘Vehicle Disturbance and Road Avoidance‘. The research highlights how different species are affected by vehicle disturbances, and in particular, songbirds who are extremely sensitive to noise levels (for instance, the most sensitive woodland species, the cuckoo, showed a decline of density at 35 decibels.) The article further describes the effect of traffic noise in affecting animals, which not only includes increase in stress levels due to the noise, but other disturbances and changes to the ecosystem which includes the barrier effect of roads which affects the population of various species and their distribution (one example is the genetic structure of small local populations of the common frog in Germany).

Reading this article reminded me of a series of pictures I saw online about wildlife bridges.

I think I’ll need to read more about the benefits of such bridges, but I can see how these bridges can have the potential to remove the barrier effects of roads, and reducing the number of road kills if animals use them. I doubt they will remove the effects of toxic particulates and noise from vehicles though, but this is the least we can do along existing highways that have already been built to minimize further damage to local ecology.

Source/s:

Forman, R. and Alexander, L. (1998). Roads and their major Ecological Effects. The Annual Review of Ecology, Evolution, and Systematics 29:207-231

Stansfeld, S. and Matheson, M. (2003). Noise pollution: non-auditory effects on health. British Medical Bulletin 68: 243-257

The World Geography (2012) Unusual Bridges for Animals — Wildlife Overpasses. [Online] Retrieved from: http://www.theworldgeography.com/2012/06/unusual-bridges-for-animals-wildlife.html [Last accessed: 15 March 2015]