Sullivan

Facebook Linkedin

Category: bloglist

There is one conclusion that we all can agree on, i.e., there is no commodity more critical to the human race than food production.  The U.S. agricultural output produces surpluses of high-quality food production.  While organic produce is increasing, the ability to feed the U.S. population and export to the world is dependent on the prudent use of pesticides that increase the yields and quality of food production.  Prudent use requires sound and effective environmental management of the risks associated with the use of pesticides.  Exposures can be associated with the application of pesticides and subsequent drift as well as via direct contact of the food that is purchased.  This blog focused on airborne exposures, which can be to applicators, farm workers, and the general public as bystanders.  When there are conflicting views on the adequacy of environmental management, particularly involving the air quality component, litigation becomes the manner of resolution.  The question addressed in this blog is:  what are the limitations of standard air quality modeling methods when applied to agricultural meteorology?

 

Evaluating airborne exposures to pesticides involves two key factors:  (1) emission rates to the atmosphere as a function of time, and (2) atmospheric dispersion and transport.   Emission rates are typically determined based on field study research where air quality and meteorological monitoring systems are used in conjunction with air quality models to compute emission rates of active ingredients (and inert constituents if needed) as a function of time, and (2) air quality models, such as the EPA-approved AERMOD model, are then used to account for the transport and dispersion of these emissions as a function of location.

 

The methodology to compile emission rates to the atmosphere is well established and based on two primary methods, i.e., the integrated horizontal flux method, and the back calculation (regression) method.  In the comparative field research conducted by Sullivan Environmental, these two methods tend to produce generally comparable results.  The use of air quality models for the application in air quality models, however, requires some context.

 

Air quality models such as AERMOD were developed primarily for modeling industrial sources such as power plants, and similar sources.   They were not optimized for modeling agricultural applications, especially those associated with fumigation activities and other pesticide applications where there are irrigated, compacted, and bedded agricultural fields.   The nocturnal dispersion rates are understated in many applications by standard models and often are associated with worst-case conditions.  This model limitation can result in increased conservatism (overstating) when evaluating sources such as agricultural fumigants.  Whether involved with regulatory or litigation-related matters, there are practical steps that can be taken to reduce the inherent conservatism of air quality models when applied in agricultural settings. 

 

The fundamental development of dilution treatment in air quality models dates back to the massive research study Project Prairie Grass conducted in Nebraska during the summer of 1956.  This legacy study was conducted during dry summertime conditions on unirrigated hay fields where the soil was near the wilting point.  In the words of the authors (Borad, 1958): “ Most likely all of these values, except those above a 20-cm depth on 6 August, and those of the compacted layer and the sand below, represent.

the wilting point of the individual samples, or are very slightly higher.” These soil conditions are markedly different in terms of heat capacity and heat conductivity than soils associated with pesticide applications such as agricultural fumigants.  Using meteorological data they have collected at 25 field studies, Sullivan Environmental (Sullivan, D.A., Sullivan R.D., and Hlinka, D,J, Methyl Bromide Alternatives Outreach Conference, 2016) has demonstrated that unlike the assumptions in AERMOD and other models, moderate atmospheric dilution conditions typically occur on fumigated fields during nocturnal conditions with light winds and clear skies, i.e., not worst-case inversion conditions as would be assumed based on dispersion rates from Project Prairie Grass.  Sullivan Environmental has demonstrated that standard air quality models, such as AERMOD, can be used without model modification to more realistically estimate air quality concentrations based on realistic consideration of actual field conditions.

 

In conclusion, context can be very important when applying air quality models.  In terms of forensic agricultural meteorology and in regulatory matters, applying standard air quality models based on wilting point soil conditions can substantially overstate near-field (applicators, farm workers, and bystanders) during nocturnal conditions because of the marked differences between irrigated soil (in some cases also involving compaction and tarping) compared to the wilting point soils from Project Prairie Grass that serve as the basis in models such as AERMOD to compute the rates of atmospheric dispersion.  The staff of Sullivan Environmental are recognized experts in air quality analysis for pesticide exposures, including applying this expertise in litigation.

Category: bloglist

Sullivan Environmental and our research partner Ajwa Analytical Laboratories have conducted over 50 studies to characterize emission rates as a function of time from the application and subsequent off-gassing of agricultural fumigants.  Many insights gathered from this research have broader applications to other complex area sources of air pollutants.

 

The first question:  what is an agricultural fumigant?    When you go to the store and see high-quality produce, much of what you see was produced with the benefit of agricultural fumigants.  Fumigants are generally applied as a liquid or gas and injected into the ground prior to planting, fumigants create an environment that is more conducive to the growth of young crops by suppressing weeds, disease, and nematodes (small worm-like creatures that nibble at the tender roots).    Applications general are made by injecting a fumigant(s) into the soil, or via drip irrigation, hand-line, or center pivot application.    The chemicals break down in the soil (biodegrade) but some of the liquid volatilizes and is released into the atmosphere.  We measure how much is released across test fields as a function of time, generally for 4 days to 14 days after application.  We typically find daytime and nighttime differences in emission rates with a steadily decreasing trend.  By two weeks, the chemicals typically present are in negligible quantities in the soil and off-gassing effectively ceases in most cases.

 

How would the lessons learned from agricultural fumigants be useful for other sources such as landfills, waste lagoons, oil & gas fields, or complex chemical operations?  The methods used and refined for agricultural fumigants can be directly applied in most cases or adapted in others to refine the estimation of emission rates.  Why is this important?  In air quality analysis, as in most analyses involving health and safety, conservative assumptions are used to simplify the analysis when more specific data are not available.  One approach to refine, and in many cases lower the emission rates beyond default treatments, is to empirically measure the emissions in representative circumstances.

 

We use two methods that can be applied to most area source assessments:  (1) profile sampling in conjunction with the integrated horizontal flux (IHF) method, and (2) the back-calculation method whereby air concentrations are measured all around an area source and dispersion modeling is used to compute the emission rate based on regression methods.  We have found the following refinements to be important:

 

The IHF Method is Generally Preferred as the More Cost-Effective and Efficient Way to Conduct the Research

 

  • If only the average emission rate across the area source, one profile is generally sufficient.
  • If there is a need to evaluate the variability in emission rates across an area source, establishing a profile in each quadrant and in the center of the area source provides a basis to evaluate both composite emissions and spatial variability.
  • Five-level profiles are generally required by regulatory agencies for agricultural fumigants. We find five-level profiles helpful if there is a need to quantify uncertainty.  On the other hand,  with three-level profiles we essentially get the same straight line of concentration or wind speed as a function of the natural logarithm of height (at least within the first 3 m of the atmosphere where most profiles are established).
  • If an active source, there may be a need to either wear a respirator and other personal protective equipment or to have the respirator available as needed.
  • We rely on solar-powered and shielded environments for our sampling pumps. Changing batteries at 3:00 AM or having sampling pumps buffeted by rain and wind obviously are problems to be avoided.  The shelters and equipment need to be durable. Murphy’s Law must be respected.  The wind will blow 50 mph (which has happened) and there will be torrential rains.  The samplers must continue working.
  • 2D sonic anemometer profiles are preferred. While cup and vane systems are much more interesting to watch as compared to a sonic anemometer with no moving parts, the only monitors that are reliable in all wind conditions are sonic.  If you do not know wind speed (generally because it is below the threshold) you cannot compute flux with either the IHF or back-calculation method.  It simply is not worth the risk of using the less costly standard cup and vane wind sensors.

 

The Back-Calculation Method is Preferred in Certain Circumstances

 

This method requires full coverage around the area source with air quality monitors and one representative source of wind data.  Generally, eight monitors are spaced approximately uniformly around the compass at a distance of 10-25 m from the edge of the area source.   It is never a good idea to try to second guess the wind and focus the monitors downwind of the prevailing flow.  Murphy’s Law will demonstrate the problem.    The method is simple in concept.  A dispersion model, such as AERMOD, is run with a normalized emission rate of 1 μg m-2 sec-1, and period-average concentrations are computed for each measured time block for each monitoring site.  Regression is then used to compute the emission rate.

 

The back-calculation method is ideally suited to circumstances where there is an access complication or a lot of complexity within the source.  Examples would be:

 

  • A lagoon where establishing a profile is problematic (although profiles could be established near the edge at all four quadrants).
  • A complex chemical facility or other locations where the emissions are not uniformly distributed.
  • Sources where there are major obstructions to flow, such as buildings, trees, or crops that would adversely affect in-field profiles.

 

Atmospheric Dilution Rates Over the Area Source Can be Different from Standard Modeling Assumptions

 

When using the back-calculation method, or when modeling exposures based on flux data computed by any method, it is important to accurately represent the rate of dispersion of airborne emissions.  This is especially true when there is a need to model off-source exposures in the near-field, such as within ~ 100 m of a source.    Dispersion models assume dilution rates based on meteorological conditions.  During sunny summer afternoons with light winds, vigorous atmospheric dilution will be assumed.  On the other hand, during nighttime conditions with light winds and clear skies, standard model assumptions will treat dilution as substantially suppressed, i.e. inversion conditions.  One complication for area sources is that the standard assumption may not apply to the particular source at hand.  Agricultural fumigants are an excellent example.  Irrigated and tarped bedded fields experience dilution conditions that are more consistent with neutral atmospheric conditions (moderate dilution) than stable, inversion conditions.  This condition has been measured many times with mid-field profiles.  Similarly, during daytime conditions that would be characterized as unstable with vigorous mixing, the mid-field temperature profiles show trending more towards neutral conditions.  Other area sources could experience similar observations, such as a waste water lagoon.  Measuring data to characterize atmospheric stability, such as temperature profiles and co-variance monitoring of sensible and latent heat flux over the source in question can refine back-calculated emission rates and subsequent near-field modeling.

 

Avoid Modeling Results from Area Sources Associated with Intermittent Sources as Though Always Operating at the Maximum Emission rates

 

Intermittent sources are problematic for standard modeling analysis.  As an example, consider a chemical plant that makes a special batch of a product a few times per year.  When the process for the particular batch is in operation, emissions occur in a predictable manner until completed, and then the batch ceases to operate.  The same intermittent process occurs for agricultural fumigants where perhaps once every three years a field will be fumigated.  Should a modeler assume that the process is always in operation?  Well, that is one valid way to conservatively approach the problem.  This approach will overstate the impacts and provide a way to confidently regulate operations.  The alternative approach is to treat the emissions in a Monte Carlo manner and “turn on” the source on a random basis consistent with the operational frequency and seasonality of the source.  The Monte Carlo approach will provide an unbiased estimate of the expected distribution of exposures.

 

In the 1990s, Sullivan Environmental developed the TOXST model for the U.S. Environmental Protection Agency which provides a means to address intermittent sources in a Monte Carlo manner.  Although developed for ISCST3 dispersion modeling, the same basic methodology can be used with the primary dispersion model in use at this time, i.e. AERMOD, through the proper use of hourly emission files and post-processing.  A specialized model, FEMS, provides a Monte Carlo solution for agricultural fumigants.  The FEMS approach also could be used for other complex areas source with substantial variability in emissions.

Category: bloglist

Pesticides are used to enhance crop yield and quality, which provide important benefits to feeding the world’s population.  Along with the benefits, there are potential risks associated with airborne exposures to applicators as well as bystanders.  The emissions from such operations need to be managed in an environmentally responsible manner.

 

There are different classes of pesticides, such as fumigants that are applied pre-plan (methyl bromide, metam sodium, chloropicrin, 1,3 dichloropropene, etc.), less volatile pesticides such as that are used with crops in the field, and non-volatile pesticides in powder form.   Focusing on the volatile pesticides, it is important for the long-term viability of such pesticides to be applied and sealed when necessary in a manner that is within health criteria as established by the U.S. Environmental Protection Agency and other regulatory authorities.

 

There are two ways to evaluate human exposure to volatile pesticides:  (1) direct measurement, and (2) AERMOD air quality dispersion modeling on emission rates that are a function of the pesticide, application method, and sealing method.  Sullivan Environmental conducts analysis based on both of these methods. 

 

Direct Measurement: Our staff has conducted over 50 field trials to evaluate emission rates for pesticides during application and as a function of time after application.  Fugitive (non-stack) emissions like this are complex with typical variability by the time of day with downwind trends.   Emission rates to the atmosphere depend on (a) the chemical/physical properties of the pesticide, (b) the method in which it is applied, (c) the method, if any, to seal the application, and potentially soil type and soil temperature.   Studies of this nature can provide a direct measurement of airborne concentrations on the field and in the immediate vicinity of the field as well as emissions input to air quality computer modeling of airborne concentrations to which applicators and bystanders can be exposed.

 

Air Quality Modeling:  Field studies, such as described above, can provide the emissions data to the atmosphere that are needed to support air quality dispersion modeling of concentrations within and beyond the treated field.  There can be significant differences in the rate of atmospheric dilution while the emitted plumes are traveling over treated fields which are caused by the increased heat capacity of the treated soil.  Pre-application soil moisture, compaction associated with the application process, and sealing based on tarping of additional water application has been found to eliminate nocturnal inversion conditions (worst-case dilution conditions)( for that portion of the flow over treated fields.   Air quality modeling can be used to estimate airborne concentrations to workers conducting the application, and bystanders off the treated field at various distances downwind.

Category: bloglist

Landfills are essential to communities to manage municipal waste in an environmentally responsible manner.   They also are a large source of the release of the greenhouse gas methane.  In some cases, landfills also produce significant odor complaints, most notably associated with the release of the gas hydrogen sulfide, which is a gas with a low odor threshold and foul-smelling rotten eggs odor.   Depending on the sequencing of the cells at a landfill, certain areas may release more or less gas, i.e., the releases are not necessarily uniform across the full extent of the landfills.  Odors and other releases can be monitored by our staff or modeled by our staff using dispersion modeling software such as AERMOD.

 

Sullivan Environmental has expertise in characterizing complex fugitive area sources that can be brought to bear on landfill impacts.  We have refined two techniques that can be used to compute emission rates of chemicals such as hydrogen sulfide:  (1) a profile method where we collected concentrations and wind data along masts between 0.3 and 3-6 m and rely on the integrated horizontal flux method, and/or (2) the back-calculation method where we rely on measured concentrations around the perimeter of the source in conjunction with normalized air quality dispersion modeling to back-calculate the emission rate.  If there are multiple areas to be assessed, multiple source areas can be assessed on a concurrent basis, with sufficient upwind monitoring at each area to promote isolation.  The back-calculation approach also could be used to evaluate composite airborne emissions from wastewater lagoons.

 

Once emission rates are identified, then air quality dispersion modeling can be used to display expected worst-case, average, and percentile frequency analysis relative to odor thresholds.  We rely on the AERMOD dispersion modeling in most modeling applications.  We also use the CALPUFF model for certain applications.

 

Sullivan Environmental has extensive air quality monitoring equipment to support our air quality programs, including the following (partial list):

 

  • 40 solar-powered, self-contained air quality sampling systems that can address a wide array of air pollutants based on validated methods.
  • 15 sonic anemometers to support multiple meteorological sampling profiles to complement air quality monitoring and support data interpretation.
  • 2, 3-dimensional sonic anemometers to provide heat flux data, and three-dimensional turbulence data to further support air quality modeling initiatives.
  • 3 Odor sampling systems to support the collection of odor samples for presentation to odor laboratory panels.
  • 2 soil monitoring systems to measure soil temperature and soil moisture at multiple sampling depths.