Methods

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Methodology

The ultimate goal is to create a vehicle emissions model that uses site specific transportation data to estimate the vehicular pollutants emitted into the air affecting a relatively small area population – neighborhood scale during day and night times. In order to get to the ultimate goal, this project will evaluate the correlation that exists between vehicle traffic and air pollution on the Route 11 road near VMI. Factors effecting emissions, such as weather, temperature, wind speed, wind direction and physical roadway features (lane width, closet distance to an intersection), was also explored and included in the analysis.

TRAFFIC DATA

The traffic data was recorded by the Traffic Recorder (PEEK). The PEEK could measure necessary traffic data for the research including number of vehicles, direction of vehicles moving, speed of vehicles, and type of vehicles. The PEEK could be set in varies time interval, but in this research, the data was collected in 10 minutes interval. The location for setting up the PEEK was on the sidewalk route 11, in front of Alumni Memorial Field Stadium (VMI football stadium). The data from the PEEK could tell how the volume, speed and types of vehicles would affect emission gases. If there are many vehicles traveling at specific time and location, the emission gases will possibly be increased according to more combustion of engines. However, speed of vehicles and types of vehicles would be important factors for producing emission gases also.

The PEEK Traffic Recorder would collect the traffic data from the air pressure when vehicles travel pass two black tubes which were set up across the street. Two black tubes were needed for setting up the PEEK. Firstly, the width of lane road must be measured by a rolling distance measuring wheel before cutting the tubes. The distance between the tubes were 16 feet apart, and the PEEK was in the middle (each tube was 8 feet apart from the PEEK). So, total length included the width of the road and 8 feet additional. At the edge of the lane road both sides, hammered nails to the ground to connect the tubes with the nails. Tied ropes to almost the end of the tubes, and connected to the nails. Tied one end of the tubes tightly, so the air would not flow outside, and another end was connected to the PEEK. In order to make sure that the tubes were attached to the road well, and then used black duck tapes attached the tubes along the road. After the PEEK Traffic Recorder was connected to the tubes, then the air pressure from the vehicles passing the tubes would be measured and sent to the PEEK. However, the PEEK recorded separately in direction. Before put the tubes into the PEEK, made sure that which direction was connected to which number of the PEEK connector.

Overall, all the necessary distances would be measured by a rolling distance measuring wheel. The rolling wheel was used to measure physical roadway data including the width of lane on the route 11, distances and the closet distance from the PEEK to an intersection, a traffic light and a crosswalk. Each length would be measured twice for the accuracy by choosing the average. After all the necessary distances were measured, drew the plan view by using the AutoCAD program, and got the VMI map from Google Earth Pro. Drawing plan view would help understanding the physical roadways feather in a big picture. Stopping distance, braking and turning points could be predicted, and these factors might have relationship with the emission gases.

The goal of the research was to find the relationship between vehicle emissions and the traffic data. The PEEK needed to be set up at the same time as the gas analyzer (Horiba PG350) started. Both the PEEK and the Horiba were recorded in 10 minutes time interval for every 3 to 4 days, also all the data would be transferred to excel program for continue analyzing. Before analysis, the data from the PEEK must be transferred to excel.

Gas analyzer (Horiba PG300)

Discuss what was used to capture the data, how it was set up, and where it was located. Also descried how the PEEK Traffic Recorder captures and registers information (i.e. discuss the pulse of air, the separation of direction). You should include a picture to help the reader visualize what you are righting. Inform the reader how long it was placed on the road, the intervals that the data was recorded. Don’t forget to mention that the data was transferred to a spread sheet and synchronized with the emissions data collected on site

 

EMISSIONS DATA

The Horiba PG300 was used to detect emissions gases including No, NOx, CO, CO2, SO2 and O2. The Horiba was a gas analyzer which could be set up at specific location, and recorded at the specific time. The Horiba was set up inside the football ticket office near the Cameron Hall side. It was located very close to the main street (Route 11), so it could detect all emission gases that were produced by vehicles traveling on the route 11 around Cameron hall, VMI football field, the back side of Preston library and the back side of Nichols engineering build areas. The data was recorded in 10 minutes interval, and collected and downloaded the data every 3 to 4 days. And again the Horiba must be started recording at the same time as the traffic recorder (PEEK).

The Horiba PG300 captured the emission gases passed through analyzer tubes to the reader. The gas analyzer collected concentration of all emission gases. The units of NO, NOx, SO2, CO are in part per million (ppm), for CO2 and O2 are in %Volume (%vol). The Horiba needed to be set up at the closet distance to the PEEK as possible because the goal is to get the result in the smallest scale as possible, so the data must be accurate as much as possible. Both the Horiba and PEEK were recorded at the same time and not far apart from each other. This will make the traffic and emissions data are accurate for analyzing. The data from Horiba PG300 were transferred to excel spread sheet for analyzing along with the traffic data.

Weather condition Same as above. Describe what, where, how, and when. (Also include a picture)

WEATHER DATA

Weather conditions would be another factor can affect the emission gases. The main weather data were temperature, humidity, air pressure, wind direction and wind speed. Firstly, vehicles produce carbon dioxide by burning fossil fuel. Carbon dioxide or CO2 is the majority of greenhouse gas, and it causes the temperature of the world increasing. However, thinking back about the possibility that the emission gases would be effected by temperature. According to U. S. Environmental Protection Agency (EPA), there was a research showed some relationship between the temperature and emissions. “For temperatures above 75 degrees, the increase in emissions is due to indirect effect of temperature via air conditioning for CO and NOx, and combination of air conditioning and evaporative emissions for HC. There is no temperature effect on starts above 75 degrees for HC, CO, and NOx. The relatively large increase in overall NOx emissions at temperatures higher than 75 degrees F is caused by the influence of air conditioning on running emissions, which make up a higher share of overall emissions relative to HC and CO (Choi et al, 4). ” As the same research, the researchers also studied about the how emissions effected by humidity, “For NOx, emissions are affected by both the direct effect of humidity adjustment and the indirect effect of air conditioning adjustment. Because gasoline and diesel have different humidity correction coefficients, the sensitivities are slightly different – gasoline vehicles are more sensitive to humidity although the differences are minimal (Choi et al, 6).” Also other emission gases got effected from humidity, “For HC and CO, for both gasoline and diesel, only the indirect effect of humidity through air conditioning adjustment applies for temperatures greater than 75 degrees; there is no humidity effect for temperatures less than or equal to 75 degrees (Choi et al, 6).” According to the research, temperature and humidity could affect the emission gases in both direct and indirect way. There must be a chance in this research for seeing some more relationship between temperature and emissions, also humidity and emissions. Wind speed and direction could change the speed and direction of emissions.  Both wind direction and speed were hypothesized to be factors that could affect the emissions. According to The effect of external wind speed and direction on sampling point concentrations, air change rate and emissions from a naturally ventilated dairy building, “The measured data were classified according to four wind direction groups: 0°–10° (N), 85°–95° (E), 175°–185° (S), and 265°–275° (W), with consideration for similar wind frequencies and representation of each major side for further analyses and comparisons. The results showed that wind speed and wind direction had significant influence on air change per hour (ACH) (P < 0.05) both individually and when interacting” (Chayan et al). Wind speed and direction might be able to change the flowing rate and direction of the emissions.

Comparison to MOVES

MOVES (Motor Vehicle Emission Simulator) is a tool for measuring the emission data. MOVES is an online emission detector, and it was created by EPA (The United States Environmental Protection Agency). So, everyone can use MOVES to know amounts of emissions in specific scale including national, county and project scale. MOVES also provides a lot of specific details for anyone interested in specific time, location, types of road, types of emissions, type of vehicle, etc. However, MOVES does not always give the results for you; if you live in a very small county, MOVES might not be able to give you a result. Considering about workers in manufactories, workers in construction zones in big city and outdoor workers, these people are getting a lot of emissions into their body without knowing how much emission at that area and time.

The emission data from MOVES was collected in national scale because both county and project scales did not give any data according to not having enough input data for Lexington city, Virginia. However, MOVES could provide the emission data for specific types of emission and specific date, month and year in Lexington city, Virginia. After MOVES with all input data was completed, then the data was calculated into percent change in each emission, and graphs were created from the interested data. The data and graphs would be compared to the emission data from Horiba PG300. The difference between these two tools would give some thoughts and ideas about emissions in large and small scale.