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Pesticide Annual Report Data

DEC, in cooperation with Cornell University (Cornell), presents the pesticides sales and application data. These data are collected under the auspices of the Environmental Conservation Law Article 33, Title 12, known as the Pesticide Reporting Law (PRL). The reporting community, DEC and Cornell work together to provide the best information that can reasonably be compiled. However, the data are neither entirely accurate nor complete. On occasion the data will be updated.

Please Note:

Although DEC and Cornell have gone to great lengths to assure the quality of the data, there are still significant concerns regarding the validity of the data received from the regulated community. Users of the data are strongly cautioned about limitations of the data. Please review the following information prior to using the data for any purpose.

Data Revisions

As part of standard quality assurance processes, DEC and Cornell have identified reports that contained quantities that appear to fall outside of accepted parameters. Staff reviewed reports containing these "out-of-range" quantities and the responsible applicators and businesses were contacted. Reporting errors were corrected by staff with the approval of the applicator or business. The corrected data were forwarded to Cornell and substituted for the original reports in the database. However, not all of the "out-of-range" data can be verified.

Several applicators and sellers incorrectly reported applications and sales for some cooling tower and wood preservative products in pounds rather than gallons. These errors dramatically inflated the reported use and sales of those products. Cornell was able to correct the units for those products from pounds to gallons. The corrected units are reflected in the data.

Cornell has developed validation programs to verify certification identification numbers, commercial permit numbers, and several other key elements of the data. Cornell provided error reports to DEC and DEC staff has attempted to correct the data.

Data Qualifications

Annual report submissions are accepted by DEC at face value. Neither DEC nor Cornell can attest to the accuracy of the data. However, the data go through a manual review and a more detailed review with various computer applications for obvious or likely errors. Follow-up with the applicators and distributors is conducted and corrections are made when possible.

Legibility Problems

Prior to 2023, the PRL allowed the regulated community to submit pesticide records that were handwritten. Some of the data on the handwritten forms was not decipherable. Data that was unreadable is stored in the database as "Illegible" and therefore those quantities of pesticides cannot be counted.

ZIP Code Issues

The use of ZIP codes to define application and sales locations creates several problems. ZIP codes are postal delivery locations. Large wilderness areas and farmland may have few, or no, postal delivery locations. Assigning a ZIP code for an application or intended application for these geographic areas is problematic.

ZIP codes may also include more than one contiguous location. Without additional address data there is no way to know where applications or intended applications occurred. For example, Harris Hill, Williamsville and portions of Clarence, NY all share one zip code.

In cases of special ZIP codes, which are unique for certain locations (for example, a single building or campus), the data is reassigned to a ZIP code that represents a larger area, if one exists. Without this step, specific pesticide applications could be identified. This step is not necessary for data reported by county.

Multiple or Undetermined Quantities Reported

Quantities for some pesticides were reported using both weight and volume based units. Rather than reject quantities reported using the inappropriate unit, the reports list both measurements as they were reported to DEC.

Products listed with a quantity of zero means that applications or intended applications of the product were made, but that the quantity was indecipherable, the reported unit of measure was invalid, or the quantity was negligible (less than 0.01).

Over- Reporting

The database may contain over-reporting of pesticides actually used or sold. There is no way to determine how much of the reported amounts are higher than they should be, but several factors contribute to this:

  • Private applicators often return unused pesticides. The products may be returned a year or two after the initial purchase. The reporting system does not have a way to account for returns. Only the original sale is on recorded.
  • Commercial Permit Holders (sellers of restricted-use pesticides) report sales of restricted pesticides to other distributors. These distributors may sell the same pesticide a second time, possibly to another distributor, who may sell it yet a third time. Each sale is reported. There is no way of identifying reports of multiple sales of a single volume of pesticide.
  • Pesticide products are routinely diluted with inert material prior to application. Some applicators report the diluted amount applied, not the undiluted amount as required by DEC. DEC and Cornell review reports in an attempt to identify obvious occurrences of this error; however, not all occurrences are obvious or corrected.

Active Ingredients

Data are not reported by active ingredient. This makes the database different from most other pesticide tracking databases, which may cause difficulties in comparing NY reporting data with data from other states. However, DEC and Cornell have developed a mechanism for displaying active ingredient summaries for those products being reported.

Unknown Sales to Private Applicators

Commercial Permit Holders must report sales of general use agricultural pesticides to certified private applicators. However, certified private applicators can purchase general use agricultural pesticides from non-commercial permit holders. Under these circumstances, these sales and the associated use information would not be captured by the PRL data.

Data Management Methodology

The following description summarizes the methodology that was used to produce this report of the Pesticide Report Law data:

How the Data are Characterized

Pesticide products were summarized using the EPA registration number, not the product name.

Pesticide products registered with one EPA number may have different product names. All registered product names are available in a separate report (Pesticide Products by Name and EPA Registration Number).

Non-standard applications and sales are flagged for separate reporting when:

  • sales or applications did not occur during the report year;
  • applications or sales occurred outside of New York State;
  • a general use product was reported on Form 25 (Annual Report for Restricted Pesticide Sales form).

All quantities are rounded to two decimal positions.

The data summaries include information on data that were reported incompletely or incorrectly. These data have been identified by using a set of standard descriptions. The reason for including this information is that partial data may still have some informational value. The descriptions used are:

Term Description
"Unreported" no value reported for this field
"Illegible" unreadable value reported for this field
"Invalid" an invalid EPA Registration Number is a number that did not match those EPA Registration Numbers for pesticide products registered at any time in New York State. An invalid county or zip code is a county or zip code that does not exist in New York State.
"Irregular" two values reported for one field on the report form or a value that could not be mapped to the report form field for any reason

Quality Assurance for reports sent in on paper

Extensive computerized data quality assurance processes are followed in producing the final reports. A brief description of these processes is outlined below.

Preliminary Quality Assurance for reports submitted on paper

The contractor who performs the data entry of the paper reports has a data quality process. This includes:

  • Decipher non-standard form submissions
  • Code illegible/irregular values
  • Reformat dates
  • Validate Certification & Permit IDs
  • Standardize city using zip code look up, and
  • Duplicate dittoed fields

Preliminary Quality Assurance for reports submitted in an electronic format
Most of the electronic data are formatted using one of the bureau's software applications. When the pesticide reports are received at Cornell a number of validation processes are performed. Cornell validates the file format and checks the data values as outlined here. This preliminary validation process enables the bureau to contact the report submitters for corrections in a timely fashion. Briefly, this involves:

  • Files are verified by checking:
    - Are the required number of fields present
    - Are files named so the type of data can be identified (applications, sales etc.)
    - Do the fields contain required data types (numbers, characters etc.)
    - Are fields the expected length
  • After the files have been verified, two batch data cleansing processes are run. Cooling tower and wood treatment products are converted from pounds to gallons, if necessary. And liquid products reported as dry ounces are converted to fluid ounces.
  • Next, pesticide quantities are scanned to identify amounts above a given threshold. Businesses are contacted for each out-of-range value and corrections made as appropriate. Common errors include misplaced or incorrectly data-entered decimal points and systematic computer-generated errors.

The electronic service bureau also accepts a limited number of reports that were not created in one of the bureau's software applications. These reports are closely reviewed and manually reformatted. These reviews include:

  • County and zip code look ups
  • EPA Registration Numbers looked up
  • Outreach to businesses/applicators

Data Validation

The primary data quality assurance process is our data validation application.

  • Fields checked against set up tables (Example- Zip code valid?)
  • Value checks (Example- Date month and day within valid ranges?)
  • Presence checks (Example- Required fields reported?)

The following types of edits are performed:

  • Format error
  • Validation error
  • Illegible, Irregular or Null value reported
  • Formulation state
  • Density error
  • Report year, date mismatch
  • Date range greater than 1 year
  • Out of state

Some data cleansing is also done by the computerized data validation application. The initial reported value is always retained whenever a correction is made. For example, California revision codes are stripped from EPA Registration Numbers and units of measure are matched against known spelling and punctuation variants.

The audits generated by the data validation application are compiled in a report. Many of the businesses that appear on the report are contacted and asked to provide corrections.

The final layer of data quality checking is a series of reviews performed by DEC staff and Cornell staff. DEC staff performs three different processes to improve the data.

  • The first process is to make corrections where the data is known to be incorrect. The errors occur in all of the fields of data collection. For example, reported EPA numbers that do not correspond to registered products or county codes that do not correspond to the address.
  • The second process is to review "out of range data." Staff reviews large sales and application information to be certain that the reported amount is the intended value.
  • The third process is comparing aggregated data from year to year within counties. Large increases and decreases within counties are investigated and verified.

All of the annual report information is self reported. Many applicators, technicians and commercial permittees report that they made no applications or sales. There is no practical way to verify this.

More about Pesticide Annual Report Data:

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    Division of Materials Management
    Bureau of Pesticides Management
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