Delta Police Department roll out ‘Leave it Empty’ campaign to change community behaviour

Delta Police Department's 'Leave it Empty' campaign mirror hangars.

Thefts from vehicles in the Delta/Ladner region have seen a significant rise compared to last year.

As of April 2, 2017, reports of thefts from vehicles are at 248 year to date(YTD) compared to 199(YTD) in 2016, a 24% increase in crimes. The Delta Police Department (DPD) are reporting an overall 39% increase in this type of crime compared to last year.

The DPD launched a campaign called “Leave it Empty” on April 14, 2017 to spread awareness of the growing issue and engage the community in a change of behaviour to reduce the number of thefts from vehicles, one of Delta’s most prominent crimes.

“A significant amount of valuables are being left behind in the vehicle in plain view. Which essentially is an invitation to the opportunistic criminal looking for an easy win as far as gaining either loose change or property that is of value,” says Sharlene Brooks, Public Affairs Coordinator for the Delta Police Department.

Items stolen range from loose change to purses, wallets, passports and garage door openers or other small electronics.

“It's not just about the theft from vehicles, it's about preventing theft of identity,” says Brooks. “Once they have your passport, your credit cards or your drivers license, that then becomes a much easier target for stealing your identity and then we see fraud.”

“I do know it’s a huge problem, but habits can be hard to break,” says Bonni Wilson, 30, a resident from the 11000 block of 95A avenue in North Delta. “Even knowing it’s probably the number one crime in our area, we have two small DVD players for the kids and our GPS that we’ll probably still leave in the car.”

Traditional media and press releases notifying the community to not leave valuables in their car had minimal effect on the overall reduction of the crime.

“We also work in partnership with our community police stations. [Officers] go out and will do a campaign and leave notices on the windshield of vehicles saying: ‘we saw that you had valuables in the vehicle’ so they will reinforce that lock it or loose it type of initiative,” says Brooks.

Victims of theft or auto break-ins are encouraged to not wipe down their car or drive their vehicle until police have responded and investigated the scene.

The DPD sends the “Forensic [Investigation] Services out to those calls to see if there is any forensic evidence that has been left behind. In other words, finger prints or any other things of evidentiary value,” says Brooks.

“We sweat the small stuff because our philosophy is 'no call too small' we don't want these smaller things taking root and becoming bigger issues in our community.”

Aside from spreading awareness and knowledge, the campaign aims to shift the behaviour of residents into remembering to remove valuables from their vehicle before leaving it unattended or parked.

“In leaving your vehicle empty, you remove the invitation of theft,” says Brooks.

To get the community more actively involved the DPD launched their social media campaign and handed out mirror hangers that read: “Nothing to steal but this sign. Please don’t steal the sign.”

The reverse side of the hangar contains detailed instructions and tips for individuals to follow to reduce the chances of any would be thieves from entering the vehicle and stealing property.

In just one month the campaign hasn’t seen a huge change in theft from auto offences, but according to Brooks “we’re getting reports of vehicles being rummaged through but no theft.”

“I used to leave my keys in the car whenever I was at the gym, or going somewhere I didn’t want to carry my keys around, because I have a keypad lock on my car,” says Wilson, “But since the campaign has come out, I’ve stopped doing that.”

A ‘take the pledge’ button is available on the DPD’s website for community members to pledge their commitment to leaving their vehicle empty. So far, just under 120 community members have taken the pledge.

“We’re hopeful that by raising awareness we’re going to see participation in changing of what we do. . . if we just change this than we can minimize or mitigate this from continuing,” says Brooks.

Energy Expenditures: Natural Gas vs. Electricity

Households in Alberta use more energy than any other province in Canada, according to data from Statistics Canada.

 

According to Statistics Canada, Canada ranks among the top energy consumers worldwide, almost equal to the United States. “That’s because of our long travel distances, our long winters, and an economy based partly on high energy consuming industries, such as mining, forestry, petrochemical, pulp and paper, aluminium smelters, refining and steel manufacturing,” says Marinka Ménard of the Manufacturing, Construction and Energy Division of Statistics Canada.

Energy Consumption is broken down into 3 different categories; electricity, natural gas and heating oil. In the dataset I used for this analysis there were cases in which provincial data was not included for natural gas and heating oil. For the purposes of this analysis I will be focusing on electricity and natural gas energy consumption across Canada.

Natural gas, as explained by the U.S. Energy Information Administration, is a non-renewable, naturally occurring resource formed millions of years ago from decaying organic matter mixing with rock and earth. Tiny pockets created in the rock house the natural gas for many years to come. Electricity is considered a secondary energy source. That means it requires a primary source of energy—either renewable or non-renewable—to be turned into electrical power.

Quebec ranks highest for electricity use at 67.3 gigajoules (GJ) per household, while Alberta ranks lowest at 25.9GJ per household. In natural gas energy consumption Alberta uses the most with 119.2 GJ per household and Quebec being second to lowest with 82.6 GJ per household.





One reason due to the high use of natural gas in Alberta versus other provinces can be attributed to the sheer volume of Alberta’s natural gas resources. According to Alberta Energy there is “an estimated 77 trillion cubic feet (Tcf) of remaining recoverable conventional natural gas.” The price of natural gas, across all provinces, fluctuates with market demand. For Alberta and the proximity of natural gas resources to individual homes, the cost of natural gas is significantly lower, 32% lower than the national average of natural gas prices.

Electricity rates, according to Statistics Canada, are among the lowest in Quebec, and while rates are steadily on the rise, there is not as much market fluctuation with electricity as there is with natural gas, making it a more financially stable source of energy for provinces further from natural gas resources.

Quebec also makes use of hydroelectric power, a renewable primary energy source converted into electricity. When you consider the low cost of electricity and the fact that the main source of energy is a primary source converted into electricity, it is easy to understand why Quebec would have the highest use of electricity across Canada.

Though I was not able to find a definitive answer to understand why Alberta’s overall energy consumption is so much more than other provinces, it can be speculated that natural gas uses, on average, more gigajoules than electricity. When you consider the overall use of electricity as being significantly lower than natural gas consumption it can be said that type of energy uses few gigajoules than other types of energy.

Data Update 3

Household in Alberta use more energy than any other province in Canada, according to data from Statistics Canada.

Below you will see the amount of total energy consumption of each province per household.

One question I cannot answer with my dataset is how much percent of income is a household with $20,000 annual income spending on energy compared to a household with $150,000 annual income. If I could locate a dataset—or information—detailing the breakdown energy rates for each province I could determine how much on average each household spends on energy. To find this data I would look at the Ministry of Energy for each province. In the event of not finding accessible data on each department's website I would file an FOI request.

Another few questions I am unable to answer with my dataset is why is Alberta’s energy use so high and why is Quebec’s so low? The dataset shows that Quebec has the highest use of electricity and Alberta has the highest use of natural gas. Does electricity use fewer gigajoules than natural gas or vice versa? Is Quebec’s energy consumption so low because of the efficiency of electricity? To find these answers will require more research on energy consumption in Alberta and Quebec. To find data that may help answer this I will use the Alberta Utilities Commission site and the Hydro Quebec site to find relevant information.

Tableau Chart

Tableau chart

Data Update 2

Alberta is the highest ranked province for total household energy consumption at 137.1 Gigajoules (GJ) per household. That’s 39% higher than BC’s total household energy consumption of 92.1 GJ per household.

The "slice" worksheet in my excel workbook contains the total energy consumption in GJ per household for each individual province in the year 2013 (the most recent year included in the dataset), sorted from highest to lowest. Three other worksheets are province energy consumption in GJ per household by energy type—electricity, heating oil and natural gas—as opposed to a total of all energy types.

In the dataset I have chosen—when broken down into different types of energy—Alberta is lowest in electricity consumption and highest in natural gas consumption, while B.C. lands roughly in the middle range for both categories. I was surprised to see how little energy per household was used in Quebec compared to Alberta, seeing as how Quebec has more than double the population of Alberta.

With this dataset I will be able to see which provinces use electricity, natural gas or heating oil the most. Additional research into how accessible different types of energy are to each province will help draw conclusions on how each province contributes to greenhouse gas emissions, and how energy consumption compares among provinces.

An article by the Globe and Mail discussed Trudeau’s plan of reducing Greenhouse Gas emissions across Canada. The article mentioned a national plan is not viable as each province has different practices in place and access to energy varies among provinces. At the end of the article there is a breakdown of each province and details about GHG emissions and plans—like a carbon tax or carbon cap—to reduce excessive energy consumption.

I will still be using the original dataset to help with my final analysis.

I have also found a more concise dataset that I have used for this update.

Data Update #1

1. What dataset will you use for your final report? (describe your dataset, include a link to it and claim it at the URL above).

The dataset I have chosen to use for my final assignment is from Stats Canada. I will be using information collected on energy consumption throughout Canada. This data was last modified March 18^th 2016 and is recorded every two years. For my assignment I will be looking at 2011 and 2013 data.

2. Describe the dataset. What kind of data does it contain?

The dataset contains information on household energy consumption by income across Canada and shows data for each province. The energy is listed as total energy consumption and is also broken down by type of energy; natural gas, electricity and heating oil. For each income bracket there is a calculated percentage for each type of energy used.

All energy usage is measured in gigajoules and is further listed as gigajoules per household.

The data also contains number of households. In some cases the number of household’s multiplied by gigajoules per household does not equal total gigajoules and that is because some households use more than one type of energy.

Data provided is for years 2011 and 2013.

3. Is there anything about your data that you don’t understand? (i.e. what a column heading means). How will you find this out?

The first thing I question about this data is how heating oil and natural gas is measured in gigajoules. I will look at conversion rates of natural gas and heating oil to electric energy to determine any potential inaccuracies in the recorded data.

In some cases the data is listed as F or E. According to the page I retrieved the data from F means the data was too unreliable to be published and E means use that particular data with caution.

I plan to reach out to a contact person with Stats Canada to find out what constitutes information as being too unreliable to be published versus “Income not stated.”

4. What are some questions you hope to answer with your data? List at least three. (you don’t need the answers at this point)

The following are questions I plan to answer with this dataset:

1. How do energy costs scale with income? For example: how much percent of income is a household with $20,000 spending on energy compared to a household with a $150,000 income.
2. Which province has the highest total energy consumption? Lowest? I would also like to show the highest/lowest for each different energy type; natural gas, electricity and heating oil.
3. How does 2011 compare to 2013?

Data Visualization Analysis

The data visualization I have chosen to analyze is from WNYC news. It shows the proximity of parks and open space to neighbourhoods throughout New York. How Big Is Your Piece of the Park? has two semi-interactive maps. The first shows the density of acres of park per 1000 residents. The second shows distance in miles from the nearest park. Both maps are color coded to show density and range and allow users to scroll over a specific neighbourhood or area to view exact numbers relevant to each map.

Fig. 1: Acres of open space per 1000 residents

1.) Certain parts of the map with this pale shade have a message of “This tract is not a significant residential area.” which makes it really difficult to differentiate between the neighbourhoods corresponding to those colours versus those that are not considered significant enough.

Fig. 2: Close up example of shade variance among map

Furthermore, the pale shades do not even represent the lowest amount of acres per resident. Because the colour legend has two distinct colours that don’t necessarily fade cohesively into each other, the map feels like it is trying to relay two different sets of information between the pink and green. The darkest green portions of the map represent a park or open space, while the lighter green portions represent a neighbourhood. This creates a bit of an unclear picture of the amount of park space across New York upon first inspection.

I feel that if the colour legend for this map had been one colour in varying shades it could more accurately represent the amount of acres per resident in a more straightforward way.

2.) There is no clear specifications for what is considered a park or open space. For example there is a neighbourhood or area that has more elementary schools or daycares, there would be much more parks in that area. However, those parks would not necessarily be for public use. The data also doesn’t seem to account for parks that are considered dangerous, or heavily occupied by homeless or transient folk.

Fig. 3: Distance to nearest park in miles

The second map (Fig. 3) has a similar colour legend ranging from blue to brown representing the distance in miles to the nearest park. The distance is measured in a straight line and doesn’t account for obstacles in the way, which would mean the route traveled would equal a greater distance than just a straight path to the nearest park. I do recognize that tracking the actual distance walked to each individual park would be significantly more difficult to record than recording the distance in a straight line. Though I do believe technology exists to get a more accurate reading of actual distance traveled, so for that reason I feel this map is a little on the misleading side.

Overall, the data is presented in a relatively easy way to read, with a few things potentially distorting the information. I think the type of chart used and the ability to hover over a given area was the right method to express this information. Using a more accurate means of mileage tracking would greatly improve the second visualization.