Discussion & Limitations

  • Discussions

The scope of our study is limited to government sector, which has not been the focus of previous studies. Previous studies paid more attention on national and regional levels or city level, including industrial, residential, and community emissions. In addition, the boundary of inventories within such studies varies regarding the inclusion of scope 3 emissions. Each city used a different method of reporting and establishing inventories. The majority of methodologies in previous studies tend to use per capita emission, which is more suitable for the analysis of national and regional levels. At municipal level, it is more significant to know about specific categories of energy usage such as lighting, fleet, water, and building to identify potential opportunities of energy saving.


Our study will be helpful for those who seek government specific case studies. Other cities with similar economic and geographical features of Durham City and County can imitate energy saving initiatives which are applicable for their cities. Given limited data, our report examines how the City and County government can measure and evaluate the progress on the GHG reduction plan within each category: building, lighting, water, wastewater, vehicle fleet, and landfill. Our study can be a guideline of how to keep track of energy saving initiatives in the future. A list of suggested criteria for future inventory is provided in Appendix 2.


Given the amount of information we acquired, we categorized projects into two main types. The first type of projects are large scale projects with immediate changes to energy use. These projects include Traffic Signal, Waste Treatment, Landfill Methane, and large Buildings projects. Once these projects are completed, there will be a significant reduction to energy consumption. Durham City and County should make sure that the proper long term energy monitoring system is in place so energy savings can be analyzed. New buildings need to be taken into account when comparing to the baseline. The other type of projects are continuous upgrade projects that occur on a smaller scale with smaller energy improvements. These projects include Fleet and Buildings upgrades and maintenance. These projects occur more frequently as vehicles are retired and replaced and buildings are upgraded, however the impacts of these projects are not as apparent right away. Because there are also more projects, it is hard to keep track of individual project details for review. It is important to be able to organize and categorize these continuous improvement projects so Durham can analyze the expected long term reduction of these projects.


Overall, better tracking of project information and expected energy reduction is necessary to sustain long term greenhouse gas reduction, which can reduce the issue of trade-off between accuracy and precision. Despite limited information for building upgrade projects, energy use intensity of County buildings shows a slightly decreasing trend. After few years, it would continuously decrease due to Detention facilities upgrades, which is one of high energy use intensity buildings. The baseline should be adjusted in the future due to new buildings coming online, and a long-time systematically tracking mechanism should be developed.


  • Limitations

There were similar challenges we encountered while evaluating all the above projects. A common problem for most of the projects we discussed was the lack of data. Officials at the various departments did not always provide us with complete data. In several cases, there were no records of the data even with the respective departments. In a few instances, some of the available data was not always reliable.


Our report cannot be compared to the previous report by ICLEI for all the projects because of inconsistencies in data collection. Our study scope is very different from ICLEI’s scope that includes community inventory and public school operations. Another reason is that most project upgrades were installed a few years after the ICLEI report was published. Thus, when the goal is to find the effectiveness of the upgrades, a comparison of emissions prior to and after the implementation of upgrades and finding an overall trend in the emission data is more meaningful than to compare with the baseline established by ICLEI.


The data available to us were not in the same time period. Therefore, we cannot compare which project is more effective and helpful for reducing GHG emissions under the same year. We also did not account for weather effects which can influence energy consumption in our analysis, still due to the incompleteness of data. Specific challenges and limitations of projects are listed below:


Buildings Upgrade Project

─      The square footage data for the buildings was not available as a result of which it was not possible to calculate building energy efficiency. ICLEI faced the same problem that they were able to obtain the square footage data for less than 25% of buildings (ICLEI, 2007c).

─      The exact dates of the building upgrades were unavailable so a comparison of energy use before and after the upgrades was not possible.


Transportation Projects

─      City fleet department was not able to provide any vehicle miles or fuel consumption data.

─      Duration of available data was inconsistent and therefore not suitable for comparison.


Water Management Project

─      Flow data for water management facilities was available only from 2011, although wastewater records were available from 2000.

─      Monthly energy data was not available for both water and wastewater prior to 2011. Therefore, the energy usage could not be compared over seasons.

─      The flow data for the Brown plant are not entirely reliable because the meters are outdated and worn. On the other hand, the Williams plant readings are extremely accurate because of magnetic meters that were installed.

─      The effect of operational measures to reduce efficiency like operating the water treatment plants more during off-peak hours is beyond the scope of this analysis.


Furthermore, we also noticed one point that the average grid electricity coefficients provided by our client (see Table 6) have been decreasing over time as power generation sources become less polluting. Therefore, a part of the GHG reduction is due to factors outside of Durham City and County projects.