代写GGR376、代做data留学生、代做R编程设计、R语言代写

日期：2020-03-29 05:28

Assignment 3: Air Pollution Interpolation and Clustering

41 Marks

Interpolation: A method of constructing new data points within the range of a discrete set of

known data points.

Clustering: Grouping a set of objects in such a way that objects in the same group (called a

cluster) are more similar (in some sense) to each other than to those in other groups (clusters).

Groups:

You will work in groups of 4, which you have the option to select on Quercus.

Background:

Air quality is a global human health issue and recent estimates from the global burden of disease

study indicate that 7.6% of global deaths can be attributed to particulate matter ambient air

pollution (Cohen et al. 2017). The greatest occurrences of these deaths is in east and south Asian

countries of low and middle incomes; however, in the United States ambient particulate matter

air pollution is estimated as the sixth highest risk factor for death, causing 18.5 deaths per

100,000 people (Cohen et al. 2017). In addition to particulate air pollution, mortality is

associated with gaseous air pollutants that include ground-level ozone and nitrogen dioxide

(Jerrett et al. 2009; Hoek et al. 2013). Health Canada estimates 14,400 deaths annually can be

attributed to anthropogenic air pollution, which includes both acute and chronic mortality

(Health Canada 2017). Mortality is not the only negative human health outcome, chronic and

acute ambient air pollution exposure is associated with negative effects on the respiratory,

cardiovascular, nervous, urinary and digestive systems (Kampa and Castanas 2008). In addition

to human health issues, plant life is very well understood to be negatively affected by air

pollution exposure. The relationship is so strong that plants are reliable biomonitors for sulphur

dioxide, ground-level ozone, and nitrogen dioxide (Cen 2015). While less understood, past

research identifies toxic effects to wildlife from air pollution (Newman and Schreiber 1988).

Research Problem:

You will select five contiguous states in the United States to conduct spatial interpolation and

spatial clustering of annual average nitrogen dioxide (NO2), ozone (O3) and particulate matter

2.5 (PM2.5) air pollution concentrations.

When the groups are determined, each group will be provided a year and one state. This state

must be included in your set of five states and data must be from the provided year.

Format:

You are given a template for the final assignment, which is in the format of an academic journal

article. You are to complete this template for submission.

Major Tasks

Interpolation

You will create an interpolated air pollution surfaces for each pollutant in your study area. You

will use both IDW interpolation and Kriging. Remember, when conducting interpolation the key

steps include:

1. Method Selection

2. Initial parameter selection (e.g. k)

3. Fit Variogram (if kriging)

4. Cross-Validate – Use LOOCV

5. Iterate parameters / variogram models

6. Prediction

Spatial Clustering

You will apply spatially constrained clustering to identify regions that contain monitors that are

most similar in air quality using all three pollutants during the clustering.

Tools you can use for spatially-constrained clustering include:

? R

o spdep::skater

o spdep::ClustGeo

? Semi-constrained

o spatialcluster::scl_redcap

? Installed from Github: https://github.com/mpadge/spatialcluster

? GeoDa (https://geodacenter.github.io/)

o Open-source GUI

Data:

The EPA provides many prepared datasets. For this assignment the easiest to work with is the

Annual Summary Data – Concentrations by Monitor:

https://aqs.epa.gov/aqsweb/airdata/download_files.html#Annual

You can view a map of the stations at this link:

https://epa.maps.arcgis.com/apps/webappviewer/index.html?id=5f239fd3e72f424f98ef3d5def54

7eb5&extent=-146.2334,13.1913,-46.3896,56.5319

You will need to use the layer selector button to add layers.

RUBRIC

Section 5 Points 4 Points 3 Points 2 Points 0 Points

Title & Abstract Clear and descriptive

with no errors or

omissions.

Clear and descriptive

with one error or

omissions.

Clear and descriptive

with 2-4 errors or

omissions.

Partially clear and

descriptive or with >4

errors or omissions.

Not clear or

descriptive.

Introduction Exceptional

introduction that grabs

interest of reader and

states topic.

Proficient introduction

that is interesting and

states topic.

Basic introduction

that states topic but

lacks interest or > 3

errors.

Basic introduction

that partially states

topic but lacks interest

or > 5 errors.

Does not introduce

topic.

Methods All methods are

clearly defined.

Research could be

reproduced, e.g. R

code commented in

detail.

Most methods are

clearly defined.

Many methods are

defined.

Some methods are

defined.

Unclear what work

was completed.

Results Results provide reader

necessary information

to understand work.

Results provide reader

most information to

understand work.

Results provide reader

some information to

understand work.

Results provide a

broad overview, but

lack clarity and detail.

Results do not support

the article.

Discussion Exceptional

comparisons and

contrasts within and

between other works.

Proficient

comparisons and

contrasts within and

between other works.

Basic comparisons

and contrasts within

and between other

works.

Few comparisons and

contrasts within and

between other works.

Discussion does not

support the article.

Conclusions Conclusions

summarize research

and are supported by

results.

Conclusions partially

summarize research

and are supported by

results.

Conclusions are not

well supported by

results.

Conclusions are not

supported by the

article.

Formatting No formatting issues:

table headings, figure

captions, etc.

1-2 formatting issues:

table headings, figure

captions, etc.

3-4 formatting issues:

table headings, figure

captions, etc.

4-5 formatting issues:

table headings, figure

captions, etc.

References References are

completed and follow

all structure.

1-3 issues with the

references.

> 3 issues with

references.

Overall Presentation Professional University Level Near University Level Below University

Level

Well Below

University Level