Group20 Overview

OVERVIEW

PROPOSAL

POSTER

APPLICATION

REPORT

Abstract

Like other countries, China has to date followed a pattern of grow first, clean up later. Many developed cities have serious environment problems. Particularly, in 2015, Beijing had experienced heavy smog for 6 months and severe polluted days for more than 1 month. Everyone was talking about air quality and health. In recent years, government has put the green development in the first place, so dose our air quality become better?

Key Objectives

1) To visualize the trend of air quality of each city

2) To visualize main factors causing air pollution of each city

2) To discover the changing relationship between economic development and environmental pollution

2) To discover the relationship between air quality and residents' health

Project Timeline

Task(s)	Week
Confirmation of topic, data-set and proposal	7
Email consultation with Prof Kam for feedback on proposal	8 (18 Jun)
Sketch out visual analytics solution	9
F2F consultation with Prof Kam for feedback on sketch	10
Implementation of visual analytics solution using Tableau/R	11
F2F consultation with Prof Kam for feedback on progress/obstacles	12
Finalize the wiki report and poster	13
Poster presentation cum conference	14 (14 Aug)

Visualization Approach

• Our visualization will base on R Shiny and we will do the time series analysis and forecasting by using historical data to estimate air quality index in future.

• We will conduct interactive geographic analysis to discover what factor influences the AQI such as number of cars, forest cover rate, GDP.

• In addition, we will explore whether the first-tier city only pursue high GDP and leave alone the air quality then trigger respiratory disease

Data Source

All these first-tier city AQI and responding date and some index contribute to API(PM2.5,PM10,SO2,CO,NO2,O3)(2014-2017).
GDP in those first tier city from 2014-2017.
Forest cover rate in the province of those cities.
Car number in those cities(2016-2017).
Total factory numbers in those cities.
Respiratory disease.

http://data.stats.gov.cn/easyquery.htm?cn=E0103
https://www.aqistudy.cn/historydata/
http://www.sc.stats.gov.cn/tjcbw/tjnj/2017/zk/indexch.ht
http://www.stats-hb.gov.cn/
http://www.bjstats.gov.cn/tjsj/
http://www.gzstats.gov.cn/tjsj/hgjjsjk/
http://www.gdstats.gov.cn/tjsj/zh/
http://tjj.zj.gov.cn/tjsj/ydsj/gy/
http://www.njtj.gov.cn/
http://www.cqtj.gov.cn/tjsj/sjjd/
http://stats.tj.gov.cn/
http://tj.jiangsu.gov.cn/
http://www.shaanxitj.gov.cn/
http://www.hntj.gov.cn/
http://www.ln.stats.gov.cn/
http://www.stats-sd.gov.cn/
http://www.ha.stats.gov.cn