ISSS608 2018-19 T1 Assign Zuo Anna Task 3
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Relationships between the factors mentioned and the air quality measure detected in Task 1 and Task 2
Insights from Task1
Patterns combined with local meteorological characteristics
Overview on the Patterns
From Task 1, we detect some characteristics on the air pollution by drawing time series lines over the five years.
For proper analysis, we created three groups in the different combinations over the stations based on the different time period they recorded.
- From 2013 to 2016, we found that the concentration on P10 was extremely high on January and December every year, hence, we named it “U pattern”.
- In 2017, the data is only provided over two months, November and December. The days which are in more serious air condition were mainly concentrated on 8th, 11th to 13th, 25th to 27th and 31st which is the most serious polluted day in December.
- In 2018, the daily and hourly patterns can be observed based on the hourly readings provided over the year. We found that common pattern for concentration on P10 during the days is that the it went higher at night (20:00 to 0:00) and early morning (0:00 to 6:00).
Local meteorological characteristics
- From the local meteorological time series chart, we can detect more meteorological characteristics in December in each year. The highlighted parts show that the readings on temperature, wind speed and visibility are lower, while the related humidity and surface pressure are higher. The combination of the meteorological characteristics especially for the lower wind speed and higher humidity may lead the pollution hard to spread and dissipated, thus lead to the pollution concentrated to the Sofia city.
Local energy sources
- As reported in the survey for air pollution, it is known that commercial, institutional and household fuel combustion dominates emissions of primary PM10 and PM 2.5. The second largest source of emissions of primary PM10 is industry, followed by transport.
- By analysing the air pollution patterns, the most possible reasons that lead to higher concentration on P10 should be household burning of fossil fuels or biomass, and industry. Winters are relatively cold and snowy in Sofia, so the temperature In January and December turn to be very low and people need more electricity which is generated by fossil fuels. By researching the information about Sofia City, we know that Bulgarian directive is set on manufacturing refuse-derived fuel (RDF) for use in cement kilns to produce heat and electricity, in addition to cement clinker. Currently, three cement plants in Bulgaria – Devnya Cement, Zlatna Panega Cement, and Holcim – use RDF in their production cycle, effectively contributing towards Bulgaria’s existing air quality issue.
- Just about a third of Sofia’s waste goes to recycling and composting, while the remainder is turned into RDF for further incineration or landfilled. The plan to build an incinerator in Sofia means adding yet another source of particulate matter, mercury and other hazardous pollutants to the already hard-to-breathe air in the city. What’s more, the burning of imported waste has grabbed national headlines in Bulgaria, with inhabitants of Devnya claiming that soot from burnt garbage is spreading across the district.
Insights from Task2
Insights | Dashboard Visualization |
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Complex interactions in local topography
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Complex interactions in local meteorology Then we go on the meteorological characteristics affected on the air condition.
The heatmap shows us the location with higher readings on the pollution has a slightly lower Humidity and Pressure but higher Temperature degree.
The treemap give us more detailed views on the relationship between air pollution and three meteorological characteristics. The light colour grids with lower Humidity and the deeper colour grids with higher temperature always have much higher pollution readings, and they are all under the lower pressure air condition.
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