North Carolina Modeling Considerations
In May and June 2018, North Carolina Department of Environmental Quality (NC DEQ) released various updates regarding air quality modeling for facilities located in North Carolina. The updates address the following topics.
♦ Modeling guidance for toxics
-Guidance for quarries
-Guidance for on-site meteorology
♦ Available North Carolina modeling data
In May 2018 NC DEQ released an update for toxics modeling guidance, titled Guidelines for Evaluating the Air Quality Impacts of Toxic Pollutants in North Carolina. In this guidance, NC DEQ has removed Section 1.2.3, which discussed specific modeling guidelines for quarries. The guidance addressed dispersion modeling to demonstrate compliance with the National Ambient Air Quality Standards (NAAQS) for particulate matter with a diameter of less than 10 micrometers (PM10) which has instead been published in a new guidance document specifically addressing quarries titled Quarry Guidance for Refined Modeling.
If NC DEQ requires modeling for a quarry, typical sources will include crushers, screens, conveyor dumps, truck dumps, open pit, and haul roads. The previous NC DEQ modeling guidance required all new quarries and quarries that proposed modifications to their primary crusher, to undergo dispersion modeling to demonstrate compliance with the NAAQS for PM10. With the new guidance, NC DEQ no longer requires this analysis. However, NC DEQ may still require an air quality dispersion modeling analysis if there is a concern that the new quarry or modification will cause an exceedance of the NAAQS or another applicable state or federal regulation. The new guidance no longer limits modeling to project modifications to the primary crusher and NC DEQ may require modeling for modifications involving other emissions units at the quarry. Specific guidelines from NC DEQ for conducting the analysis remain unchanged. For instance, 24-hour PM10 remains the primary pollutant to evaluate, and 24-hour and annual concentrations of total suspended particles (TSP) will also be required in the analysis.
Additionally, the May 2018 NC DEQ toxics modeling guidance update revised Section 5.6, which addresses the comparison of applicable air toxics modeling results to the acceptable ambient levels (AAL) for toxic air pollutants listed in 15A NCAC 02D Section .1104. The guidance has been updated to reflect requirements in Appendix W to 40 CFR Part 51 around the use of onsite meteorological data. Consistent with previous guidance, if the most recent year of meteorological data is used and modeling results are below 50% of the applicable AAL, no further modeling is needed. This holds true whether airport or onsite meteorological data is used in the modeling analysis. Under the new guidance, if airport meteorological data is used, and the modeling results are over 50% but under 100% of the applicable AAL, an analysis using five years of met data is required. If onsite meteorological data is used, the model results using one year of met data are acceptable as long as they are under 100% of the applicable AAL. In all cases, if modeling results indicate an exceedance of an AAL, an evaluation of permit restrictions and/or source modifications will be necessary, along with remodeling to demonstrate compliance.
In a separate update, NC DEQ has specified that AERMOD version 18081 should be used in future modeling submittals. NC DEQ has updated North Carolina surface profile elevations and meteorological data sets to reflect data from 2013 to 2017. These data sets should be used in any future modeling.
If you have questions about how these updates could affect your facility, or if you need assistance in conducting an air quality modeling analysis, please contact us.
Reflections from 2018 Year End Reporting – Part 3: Temperature Monitoring Impacts on Data Validity
Welcome to the third of a five-part blog series hosted by ALL4’s Continuous Monitoring Systems (CMS) Practice Area that looks back at some of the key points of discussion that came up while completing reports for the second half and fourth quarter of 2018 reporting periods. In Part 3, we take a quick look at how, or if, the status of temperature monitoring systems affects CMS data. Be sure to check out Part 1: Validation Sequence Impact on Data Validity and Part 2: Ancillary Analyzer Impacts on Data Validity.
CMS have their own monitoring components that function as self-checks to ensure the “health”, or representativeness and accuracy of the data being collected. Examples of this are temperature monitoring components, typically thermocouples, often installed to monitor the temperature of sample lines and sampling equipment associated with the CMS. The temperature of these sampling components is monitored to ensure that the components are adequately heated to remove moisture or prevent condensation in a sample. Although the temperature monitoring systems are a component of the CMS used to indicate if there is an issue with sampling equipment, their outputs do not necessarily impact data validity, but can cause data to be suspect or require additional scrutiny. Therefore, if a temperature monitor shows a fault status, or if a temperature monitor is not responsive on a certain day, CMS data for associated CMS is suspect and will require additional scrutiny. The fault status or failed calibration serves as an indication to inspect and potentially service a component of the CMS; however, the validity of the CMS data associated with it is not affected.
Note that although this blog focuses on sample system temperature monitoring, stack temperature monitors are also utilized by facilities to convert actual volumetric flowrates to standard volumetric flowrates. Similar to sampling temperature monitoring systems, if a stack temperature monitor shows a fault status or alarm, the stack temperature data and any subsequent CMS data dependent on stack temperature would be suspect and require additional scrutiny.
Due to the recent polar vortex we experienced across the country, the low temperatures triggered setpoint alarms in temperature monitoring systems that many of our clients did not even know existed. These setpoint alarms may have caused invalid data to be logged by the data acquisition and handling system (DAHS). Although the DAHS tagged the data as invalid, the data collected during the alarming period was representative and in-control with respect to ongoing quality assurance activities; therefore, valid for use in compliance demonstrations. In some cases the temperature monitoring system setpoints were adjusted or the data validity status was revised to tag data as suspect for review but not automatically invalidating data. If you have questions about temperature monitors and their impact on CMS data validity at your facility, or any other aspects of CMS, please reach out to me. I can be reached at 610.933.5246 extension 139, or at mcarideo@all4inc.com.
Don’t forget to look for Part 4 this five-part blog series next week on DAHS upgrades and how they should be proactively managed. To ensure that you do not miss out on the action, signup below for our 4 The Record articles.
Reflections from 2018 Year End Reporting – Part 2: Ancillary Analyzer Impacts on Data Validity
Welcome to the second of a five-part blog series hosted by ALL4’s Continuous Monitoring Systems (CMS) Practice Area. If you missed Part 1, be sure to check it out here. In Part 2, we review how ancillary analyzers can affect continuous monitoring system’s (CMS) data validity. Examples of ancillary analyzers include volumetric flow monitors, diluent analyzers such as oxygen (O2) or carbon dioxide (CO2), and fuel flowmeters.
Provided herein is an example of how a volumetric flow monitor can impact data across several CMS, and it is important to note that this example is not only applicable to volumetric flow monitors, but to any ancillary analyzer. Volumetric flow monitors are a common component to many CMS. Whether it is a carbon monoxide (CO), nitrogen oxide (NOX), or sulfur dioxide (SO2) continuous emissions monitoring systems (CEMS), volumetric flow monitors are often used to convert pollutant concentrations to units of mass. Therefore, the “health” (i.e., valid or invalid status) of the volumetric flow data is equally important as the CO, NOX, or SO2 concentration data for mass rate CEMS. An emission source typically has one volumetric flow monitor that can serve multiple mass rate CEMS. Thus, the ongoing quality assurance (QA) validations (sometimes referred to as “calibrations”) for a single volumetric flow monitor can impact multiple CMS.
In this past quarterly and semi-annual reporting period at ALL4, we saw the volumetric flow monitor validations affect data in the two different scenarios outlined below.
- The volumetric flow analyzer failed a daily validation which caused invalid and out-of-control (OOC) volumetric flow data, thus invalidating the CO, NOX, and SO2 mass emission rate data from the last successful validation until a validation (or actual calibration) was passed the following day.
- The volumetric flow analyzer’s validations exceeded the maintenance limit for five consecutive days unnoticed by the facility. On the fifth day that the maintenance limit was exceeded, volumetric flow data (and thus CO, NOX, and SO2 mass emission rate data) became invalid from the time the maintenance limit was exceeded until a passing (below the maintenance limit) validation (or actual calibration) was completed days later. Note that this example is specific to CEMS required to comply with the QA procedures of 40 CFR Part 60, Appendix F.
The take-away here is that ancillary analyzers are often relied upon by many CMS at a facility, and therefore, the health of the data collected by the ancillary analyzers is critically important to those CMS. Failing ongoing daily validations, or exceeding maintenance limits on consecutive days, is an easy way to quickly accrue multiple hours of invalid and OOC ancillary analyzer data that impacts multiple CMS.
If you have any questions about a volumetric flow monitor’s impact on data, or any other general CMS questions, please reach out to me. I can be reached at 610.933.5246 extension 139, or at mcarideo@all4inc.com.
Don’t forget to read Part 3: Temperature Monitoring and Impacts on Data Validity of this five-part blog series on how temperature monitoring system data affects (or doesn’t affect) CMS data validity! To ensure that you do not miss out on the action, signup for our 4 The Record subscription below to receive these articles directly in your inbox.
Reflections from 2018 Year End Reporting – Part 1: Validation Sequence Impact on Data Validity
Welcome to the first of a five-part blog series hosted by ALL4’s Continuous Monitoring Systems (CMS) Practice Area. Each blog will look back at some of the key technical issues that our team encountered while completing CMS reports for the second half and fourth quarter of 2018 reporting periods. In Part 1, we focus on a topic that seems to come up quite frequently for us across industries and CMS of all types – that is, the impact a validation sequence has on CMS data validity.
If you are familiar with CMS, the idea of a validation (sometime referred to as “calibration”) sequence is not foreign to you. If you aren’t, then let’s quickly review. Continuous Monitoring Systems often consist of multiple analyzers (or monitors) that link together to produce data for compliance demonstration purposes. Each of the analyzers in the system are typically validated (checked for accuracy) on a regular basis (or after a maintenance activity), and the analyzer validations are completed in sequence. For example, a carbon monoxide (CO) analyzer validation may be followed by an oxygen (O2) validation. So how does the validation sequence impact the validity of the data recorded by the system?
Well, validations take time to run, and the data collected during a validation is not valid and is excluded from hourly compliance averages. The applicable regulation stipulates the minimum amount of valid data points needed to calculate a valid hourly average during maintenance or validation hours. The timing of the validation sequence could prevent the minimum amount of valid data points from being collected within an hour, resulting in invalid hourly averages that need to be unnecessarily reported as downtime. In other words, the CMS could be accruing avoidable invalid data that decreases the overall monitor availability for the reporting period. This issue is sometimes compounded because the validation sequence timing can affect the data validity for multiple CMS. An example of this might be an O2 analyzer relied upon by a corrected concentration emission limitation (ppmvd @ 15% O2) continuous emissions monitoring systems (CEMS) at a facility, such as CO and/or nitrogen oxides (NOX). The timing of the O2 analyzer’s calibration could be the cause of invalid hourly compliance averages for both the CO and NOX corrected concentration emissions. This can be further complicated by the time associated with the validation of other analyzers preceding or following in the validation sequence, such as sulfur dioxide (SO2).
We encountered multiple examples of this while completing CMS reports this past month, and successfully worked with our clients and supporting vendors to adjust the validation sequence (and sometimes even the recommended blended validation gases) to maximize data availability for our clients. Maximizing data availability is important for ALL4 and our clients to avoid any potential penalties or fines because of federal and state data availability requirements. If you have questions about validation sequences at your facility, or any other aspects of CMS, please reach out to me. I can be reached at (610) 933-5246 extension 139, or at mcarideo@all4inc.com.
Don’t forget to read Part 2 this five-part blog series on how ancillary analyzers can affect CMS data validity! To ensure that you do not miss out on the action, signup below for our 4 The Record articles to receive timely updates of current hot issues, as well as in-depth articles that highlight important regulatory topics.
Requirements to Include Formaldehyde in Volatile Organic Compound (VOC) Emissions
On December 6, 2018, the New Jersey Department of Environmental Protection (NJDEP) presented at a regulatory update meeting. One of the topics discussed is the inclusion of formaldehyde in the calculation of volatile organic compound (VOC) emissions from spark ignited internal combustion (IC) engines which combust gaseous fuels including:
- Natural gas
- Landfill gas
- Biogas
Incomplete combustion of these fuels in IC engines leads to products of incomplete combustion (PIC), which we might often think of as carbon monoxide (CO). However, formaldehyde is also a PIC and was identified as having a high air toxic health risk in New Jersey. Some health risks linked to formaldehyde include short-term respiratory issues such as coughing and chest pain and in the long term, exposure to formaldehyde increases the risks of respiratory cancers. NJDEP has taken a proactive approach and already issued notification letters to facilities clarifying that formaldehyde emissions must be included and properly accounted for in VOC emissions.
Current stack testing methods used to determine VOC emissions (e.g., U.S. EPA Method 25A, Method 18) are not designed to quantify formaldehyde emissions. However, U.S. EPA Method 323 or Method 320 may be used to determine formaldehyde emissions. The takeaway from this is that the stack testing methods used to determine total VOC emissions could bias the total VOC emissions low when formaldehyde is present in the exhaust stream. Formaldehyde is also not included in the current VOC emissions standard found in Table 1 of 40 CFR Part 60, Subpart JJJJ (Standards of Performance for Stationary Spark Ignition Internal Combustion Engines). Moving forward, NJDEP is now requiring VOC emissions from combustion of gaseous fuels in IC engines to be calculated as the sum of nonmethane hydrocarbons (NMHC) and formaldehyde.
NJDEP estimates that in 2017, 96% of the formaldehyde emissions from stationary sources in New Jersey resulted from the combustion of natural gas, landfill gas, or biogas. When NJDEP reviewed stack tests on engines which combust landfill gas and natural gas, it was observed that formaldehyde emissions from IC engines varied widely and could represent the majority of total VOC emissions depending on the IC engine.
What Does this Mean for My Facility?
NJDEP has already required that all facilities must complete a permit modification to adjust for this limit no later than 90 days before the current permit’s expiration date. In the future, IC engines which combust a gaseous fuel and require stack testing will be required to conduct formaldehyde testing to properly quantify VOC emissions in New Jersey.
If you believe your IC engine now exceeds permitted VOC limits with the inclusion of formaldehyde emissions, it may be time to consider adding a control technology to ensure compliance with your limits. NJDEP found through stack testing that up to a 96% reduction in formaldehyde emissions is achievable in natural gas IC engines when using an oxidation catalyst (CO emissions also decreased by up to 98%). Another option for combusting landfill gas is to implement more stringent pre-combustion siloxane controls which will reduce the risk of incomplete combustion.
If you have questions about how NJDEP’s position on formaldehyde emissions affects your facility and what steps you should take to ensure your permit modification is completed, please reach out to me at 571.392.2592 x505, or at sbharucha@all4inc.com.
