Tools for the Characterization of Pesticide Risk in Food Products-An

Overview

Mihaela Roșca 1

, Raluca-Maria Hlihor 1,2

, Petronela Cozma 1 and Maria Gavrilescu

1

1 “Gheorghe Asachi” Technical University of Iasi, Faculty of Chemical Engineering and Environmental

Protection, Department of Environmental Engineering and Management, 73 Prof. Dr. Docent D. Mangeron

Str., 700050 Iasi, Romania 2 “Ion Ionescu de la Brad” University of Agricultural Sciences and Veterinary Medicine of Iasi, Faculty of

Horticulture, Department of Horticultural Technologies, 3 Mihail Sadoveanu Alley, 700490 Iasi, Romania 3 Academy of Romanian Scientists, 54 Splaiul Independentei, RO-050094 Bucharest, Romania

Abstract. The presence of pesticides in plant products is a consequence of their use due to farming

activities for pests and disease combating. Due to various chemical active substances used as pesticides

which can cause adverse effects on human health, it is necessary to carry out risk assessments studies

regarding the pesticides residues in fruits and vegetables. In this work, some of the most used models for

assessing risks posed by the presence of chemicals in environment are addressed: USEPA human health risk

assessment methodology, The Monte Carlo Risk Assessment (MCRA), the dynamiCROP model, DEEMTM

-

Dietary Exposure Evaluation Model and PRIMo – Pesticide Residue Intake Model. To ensure a detailed risk

estimation of pesticide we have shown that it is necessary to know information on pesticides characteristics,

food consumption estimates and effects on human health. Considering these aspects, this paper is focused on

the distribution and the levels of pesticides residues in food along with a short description of several tools

used for risk assessment and the main databases specific for each program. These tools will be further applied

for specific case studies developed within our research group.

Keywords: MCRA, dynamiCROP, DEEMTM

, USEPA model, PRIMo, pesticides databases

1. Introduction

Although the negative effects of pesticides on human health are well known worldwide, the farmers

continue to apply different types of pesticides for pests and diseases control and, consequently for increasing

fruits and vegetables production to meet the market demand [1], [2]. Food and Agriculture Organization of

the United Nations (FAO) gave an extensive definition for pesticides: “Pesticide means any substance or

mixture of substances intended for preventing, destroying or controlling any pest, including vectors of

human or animal disease, unwanted species of plants or animals causing harm during or otherwise

interfering with the production, processing, storage, transport or marketing of food, agricultural

commodities, wood and wood products or animal feedstuffs, or substances which may be administered to

animals for the control of insects, arachnids or other pests in or on their bodies. The term includes

substances intended for use as a plant growth regulator, defoliant, desiccant or agent for thinning fruit or

preventing the premature fall of fruit, and substances applied to crops either before or after harvest to

protect the commodity from deterioration during storage and transport” [3]. This definition reveals in fact

the complexity of scientific research on pesticides synthesis, properties, uses, and their effects on

environment and humans on short, medium and long terms and accounts the opportunity of our past and

present studies in this area [4]-[6].

Corresponding author. Tel.: + 0040753312588.

E-mail address: roscamihaela23@yahoo.com.

International Proceedings of Chemical, Biological and Environmental Engineering, V0l. 101 (2017)

DOI: 10.7763/IPCBEE. 2017. V101. 11

75

Pesticides produced and used for different proposes can be classified based on chemical family as:

organophosphates, carbamates, organochlorides, phosphorothioate, pyrethroids [2]. World Health

Organization (WHO) classifies pesticides according to their hazard potential in 5 major groups [7]: Ia -

extremely hazardous; Ib - highly hazardous; II - moderately hazardous; III - slightly hazardous; U - unlikely

to present acute hazard. Based on the principal action on pests, pesticides were classified in: insecticides,

miticides, herbicides, nematicides, fungicides, molluscicides and rodenticides [8].

The human exposure to pesticides can produce neuritis, psychiatric manifestations, hepatorenales

disorders, neurological, immunological, metabolic and endocrine diseases. The most common negative

effects associated with the presence of pesticide residues in the human body are: nausea, vomiting, blurred

vision, coma, difficulty in breathing, deficit hyperactivity disorder, disorder in fetuses and children etc. [4],

[6], [8], [9].

Based on the information provided by International Agency for Research on Cancer (IARC), most of the

pesticides used are considerate carcinogenic, probably carcinogenic or possibly carcinogenic substances to

humans. For example gamma-hexachlorocyclohexane (lindane) is included in Class 1 - carcinogenic to

humans, dichlorodiphenyltricholoroethane (DDT) in Class 2A - probably carcinogenic to humans, 2,4-

dicholorophenoxyacetic acid (2,4-D) in Class 2B - possibly carcinogenic to humans [10], [11].

In this context, the main purpose of this paper is to make an overview on several tools used in human

health risk assessment of pesticides in food. For better understood the necessity for risk assessment generated

by the presence of pesticides in fruits and vegetables, the paper will provide some information about the

values of pesticides residues in food reported by different organizations and agencies. The description of the

risk assessment methodology, the most applied models and tools and the principals databases used for the

risk assessment programs are also provided, generating prerequisites for their application in various case

studies addressing the assessment of pesticide risk in food products.

2. Pesticide Residues in Food

Due to the negative effects on environment and human health induced by exposure to pesticides,

different organizations or authorities developed and implemented several programs to control and monitor

pesticides residues in food products (e.g. cereals, fruits, vegetables etc.). Among these, the most important

are: Pesticide Action Network for worldwide, U.S. Department of Agriculture’s (USDA) and European Food

Safety Authority (EFSA).

According to 2014 EFSA annual report on pesticide occurrence in food plants, approximately 97.1% of

the analyzed samples (summing 82,649 samples) didn’t contain pesticide residues or their concentrations

were below the maximum residue levels (MRLs). The report is based on 69.4% samples from EU and EEA

countries, 25.7% samples from the third countries, while 4.9% of the samples were of unknown origin. The

highest MRL for pesticides was found in plant samples such as spinach, beans, mandarins, carrots, rice, pears,

oranges and cucumbers [12]. In 2015, at European level 84,341 food samples were analyzed for 774

pesticides [13]. The origin of food plants were: 69.3% from EU Member States, Iceland and Norway, 25.8%

from products imported from third countries, while the rest is of unknown origin. The percentage of the

samples for which pesticides residues were not found or the concentrations were below the MRL is similar

with the percentage reported in 2014 (97.2% vs. 97.1%). In 2015, only 1.7% of samples exceeded the MRL,

increasing over the previous year (from 1.6%). The highest MRL was identified in broccoli, table grapes,

sweet peppers, peas without pods, wheat, aubergines and bananas [12], [13]. The results of pesticides

residues in conventional and organic products in 2015 reported by EFSA are shown in Fig. 1a.

In 2014, the U.S. Food and Drug Administration (FDA) regulatory pesticide residue monitoring program,

analyzed 6,638 samples for pesticides, of which 6,272 were human foods and 366 animal foods. The

majority of human foods samples (4,814) have been taken from imported products, and only 1,458 samples

came from food products obtained in the USA. Also, 70.9% of samples from domestic market and 52.9% of

samples from imported products didn’t contain pesticides residues. Pesticides found in 1.4% of samples

taken from USA products and 11.8% of samples from imported products were below the MRL. The majority

of the samples analyzed by FDA in 2014 were taken from fruits and vegetables, representing 75.7% for

76

imported products and only 36.1% for fruits and vegetables from domestic market [14]. The result

concerning pesticides residues in products from domestic market and imported (cereals, diary/eggs, fish,

fruits, vegetables and other) are presented in Fig. 1b.

66.7

43.2

32.3

15.1

28

12.7

11.7

17.1

14

13.92.5

3.4

1.3

0.4

6.8

0.6

0.7

0.3

0

1.8

0 20 40 60 80 100

Fruits and nuts

Vegetables

Cereals

Animal products

Other

% of the samples analysed w ith quantif ied residues below the MRL

03691215

% of samples analysed w ith quantif ied residues above the MRL

Conventional products (quantif ied residues ≤ MRL)

Organic products (quantif ied residues ≤ MRL)

Conventional products (quantif ied residues > MRL)

Organic products (quantif ied residues > MRL)

(a)

26.5

8.3

16

43.8

37.5

21.8

0

0.6

10.2

10.6

16.9

29.921.1

0

0.6

10.2

10.6

16.9

0

0

0

0.5

1.5

7.6

0 20 40 60 80 100

Cereals

Dairy/Eggs

Fish

Fruits

Vegetables

Other

% of the samples analysed w ith quantif ied residues below the MRL

0510152025303540

% of samples analysed w ith quantif ied residues above the MRL

Products from import (quantif ied residues ≤ MRL)

Pruducts from domestic market (quantif ied residues ≤ MRL)

Products from import (quantif ied residues > MRL)

Pruducts from domestic market (quantif ied residues > MRL)

(b) Fig. 1: (a) Pesticides residues in organic and conventional foods at European level in 2015 [13] and (b) pesticides

residues in products from import and from domestic market in USA – in 2014 [14]

3. Risk Assessment and Management

The negative effects to human health caused by the presence of pesticide residues in fruits, vegetables

and cereals are based on the gravity of exposure for short or long time and on the exposed population

category, adults being the least affected one (Fig. 2). Thus, the population exposure to different pesticide

residues in food products requires a health risk assessment [6], [15].

The human health risk assessment has the role to estimate the nature and likelihood of adverse health

effects produced by the exposure to pesticides, now or in the future. The types of exposures to pesticides

from different environmental compartments of concern and the steps involved in risk assessment are shown

in Fig. 2.

Risk assessment is based on scientific knowledge with consideration of inherent uncertainties. Risk

assessment and management are described as continuous processes [16], so after the human health risk

assessment was done in the risk management process, a number of measures for reduction of the negative

77

effects produced by pesticides are necessary to be taken. In this step, the risk managers must weight policy

alternatives by integrating risk assessment results with social, economic, and political factors. Examples of

approaches for risk management which can be used to reduce the human risk are as follows [17]: unrestricted

use of pesticides if these have low risk; restricting its use to certified application in case of pesticides with

medium risk; lowering application rates; reducing the number of applications; increasing application

intervals; providing longer intervals between application and harvest; using alternative application methods.

Fig. 2: Groups of humans affected by pesticides and steps in risk assessment

4. Tools for Risk Assessment

Risk assessment of pesticides in foods can be performed using several methods and tools, which can be

applied for the evaluation of professional and non-professional risks [18]. The most important models and

tools were developed by the European Food Safety Authority (EFSA) and US Environmental Protection

Agency (USEPA).

The Monte Carlo Risk Assessment (MCRA) software tool was developed by European Commission

under the supervision of National Institute for Public Health and the Environment for the Netherlands

(RIVM) through the ACROPOLIS project. The development of the software tool had as a basis the

fundamental objective of the ACROPOLIS project to improve risk assessment strategies in Europe and to

develop a framework for cumulative and aggregate risk assessment of pesticides [19], [20]. This tool can be

applied for probabilistic exposure and risk assessment of chemicals in the diet. Other exposure routes such as

inhalation or dermal contact could be considered. With MCRA 8, the Cumulative Exposure Assessment for

chemicals grouped in a Cumulative Assessment Group for which a single health effect is considered relevant

can be also performed [19], [21].

For risk assessment with the help of MCRA system statistical models, shared data and data uploaded by

the user are considered together. The scalability of the software allows processing of cumulative assessment

groups of pesticides containing up to 100 active substances [20]. MCRA can be used for several options,

such as [19]: acute (short-term) risk assessment; chronic (long-term) risk assessment; empirical or parametric

modeling of residue level; modeling of processing effects, unit variability and nondetected levels;

bootstrapping to assess the uncertainty of percentiles; comparison with deterministic point estimates (IESTI).

Monte Carlo simulation provides several advantages over deterministic, or “single-point estimate”

analysis [19]: probabilistic results; graphically represented results; sensitivity analysis; scenario analysis;

correlation of inputs.

The dynamiCROP model was developed for quantification and evaluation of human health impacts

caused by direct application of plant protection products onto agricultural field crops, such as wheat, and

subsequent intake by humans via ingestion. A transparent matrix algebra framework is at the basis of the

software running [22], [23]. A dynamic analysis for the ingestion pathway of different plant protection

products represent the main scope of the software [23].

This model developed for human health impacts evaluation due to uptake of pesticides into multiple crop

types is able to answer four questions [22]:

78

(i) how can health impacts induced by human intake of pesticides via ingestion of different food crops be

characterized and evaluated in a transparent, consistent and concise way?

(ii) how the dynamic behavior of pesticides in crops and the subsequent human intake are influenced by

crop characteristics, substance properties and application times?

(iii) what are the differences between crop-specific characterization factors from direct pesticide

application to different food crops and generic characterization factors from continuous, diffuse emissions to

the environment?

(iv) how can substitution of pesticides be evaluated and their health impacts compared on a similar

functional basis?

Therefore, if the dynamiCROP model is applied, a risk and/or an impact assessment for human health

from indirect exposure via ingestion of food products due the direct application of plant protection products

will be provided. Since dynamiCROP uses a spatial domain approach, there is no impediment in the

assessment of human health impacts for application pattern, crop production area, population etc. performed

according to the underlying input parameters [23]. The dynamiCROP model was fully parameterized by

developing crop-specific regression models with focus on the system driving aspects, such as time to crop

harvest, degradation in and on crops, residence time in soil and some substance properties [23].

USEPA human health risk assessment methodology focuses on the estimation of the nature and

probability of adverse health effects in humans due the exposure at chemicals found in the environmental

compartments. To apply the USEPA strategy for risk assessment several questions are requested be the

starting point of the procedure, namely [24], [25]:

(i) what types of health problems are caused by pesticides in the environment?

(ii) what is the chance that people will experience problems when exposed to different levels of

pesticides?

(iii) is there a low level below which some chemicals don’t pose a human health risk?

(iv) what pesticides are people exposed to and for how long?

(v) are legal limits for pesticide residues in food (tolerances or maximum residue limits) protective of

human health?

(vi) are people more likely to be susceptible or exposed to pesticides because of factors such as age,

genetics, pre-existing health conditions, ethnic practices, gender, where they work, where they play, what

they eat, etc.

The methodology of human health risk assessment proposed by USEPA follows the 4 major steps of risk

assessment. The risk to human health from pesticide exposure depends on both the toxicity of the pesticide

and the likelihood of people coming into contact with it, and can be expressed as Eq. (1) [8], [25].

RISK = TOXICITY x EXPOSURE (1)

Therefore, assessment of risk generated by the toxicity of pesticide residues in food for acute

toxicological effects and chronic toxicological effects (noncancer risk) is expressed as a Population

Adjusted Dose (PAD), and represent the reference dose (RfD) divided by any additional safety factor [25].

The toxicity for acute effects is expressed as an acute PAD (aPAD) and can be calculated using Eq. (2).

The acute RfD (aRfD) in this case is an estimation of the level of one-day exposure to a pesticide residue that

is believed to have no significant deleterious effects and can be calculated by Eq. (3). The aRfD is the value

of the report between No Observed Adverse Effect Level (NOAEL) from acute animal toxicity studies and

the appropriate uncertainty factors. In case of chronic toxicological effects, the toxicity is expressed as a

chronic PAD (cPAD) (Eq. 4). For the chronic RfD (Eq. 5), the level of daily exposure to a pesticide residue

is considered over a 70-year life span, and it is believed that harmful effects are not significant for this level.

NOAEL is taken from studies addressing chronic animal exposures [25].

FQPAtoUniqueFactorSafety

aRfDaPAD

(2)

79

FactorsyUncertaint

NOAELaRfD

(3)

FQPAtoUniqueFactorSafety

cRfDcPAD

(4)

FactorsyintUncerta

NOAELcRfD

(5)

The acute food risk is expressed as a percentage of the aPAD (% aPAD) (Eq. 6) and, if the value

calculated of % aPAD is less than 100, the risk is being considered as acceptable. The chronic food risk (%

cPAD) is expressed similarly with the acute food risk, and can be calculated using Eq. (7) [25].

100//

//%

daykgmgaPAD

daykgmgExposureFoodaPAD

(6)

100//

//%

daykgmgcPAD

daykgmgExposureFoodAveragecPAD

(7)

Linear cancer risk is expressed as a probability and is calculated using Eq. (8). For carcinogenic effects,

the toxicity portion of the risk is expressed as a cancer potency factor (q*) [25].

1day/kg/mg

*qday/kg/mgExposureFoodAverageriskCancer

(8)

Based on data acceptable for the consumption, daily intake (ADI) and Acute References Doses (ARfD)

values, the risk can be calculated. The estimated daily intake (EDI) of pesticide residues is calculated as

given by Eq. (9):

wieghtbodymean

RLFEDI ii

(9)

where: Fi- food consumption data, RLi - residue level in fruits and vegetables.

The long-term risk assessment is performed by calculating the hazard quotient (HQ) (Eq. 10):

100ADI

EDIHQ

(10)

After the calculation of HQs the values are summed up to give a chronic hazard index (cHI) (Eq. 11):

HQcHI (11)

DEEMTM

- Dietary Exposure Evaluation Model is a software developed by Novigen Sciences, Inc. in

2000, to be used for the estimation of population exposure due to consumption of food with pesticides. The

first version of this software and the data about food consumption provided by the USDA Continuing

Surveys of Food Intake by Individuals (CSFII) reported in 1992 and 1996 was used. The DEEM™ program

includes four software modules: the main DEEM™ module, the acute analysis module, the chronic analysis

module, and the RDFgen™ residue distribution module [26], [27]. The main DEEM™ module creates and

edit residue files for specific chemical or cumulative applications, and represents the base for the DEEM™

Acute, Chronic, and RDFgen™ modules. The RDFgen™ module is used to create summary statistics and

Residue Distribution Files based on USDA Pesticide Data Program (PDP) monitoring data or user-provided

residue data. The Acute analysis and Chronic analysis modules based on USDA consumption data provide

information on dietary exposure assessment. For acute, chronic, and/or cancer risk assessment using DEEM-

FCID software it is necessary to insert the data by types of information, as follows [27]: (1) pesticide’s

toxicological data; (2) residue concentrations in foods; (3) any adjustment factors related with the potential

constituent levels in the diet of people. The program can be used to estimate total exposure for different

groups of population divided by age, gender or ethnicity [27].

PRIMo – Pesticide Residue Intake Model was developed initially by EFSP for risk assessment of

temporary MRLs. Presently, it can be applied for chronic and acute risk assessment. For assessing risk with

this model, there are currently used data about national food consumption and unit weights (data provided by

the Member States of European Union) and different implemented and internationally agreed risk assessment

methodologies to assess the short-term (acute) and long-term (chronic) exposure of consumers. Using

PRIMo model, chronic and acute dietary consumer exposure to pesticide residues can be estimated for

children and adults [28].

80

5. Databases for Risk Assessment

The methods and tools for risk assessment and risk management of pesticides in fruits and vegetables

require many input data on the maximum residue level, the physico-chemical properties of pesticides

(potential for leaching, sorption, volatilization, photodegradation, microbial or chemical degradation etc.),

the toxicology/ ecotoxicology, potential effects on human health etc. Consequently, various organizations

such as the World Health Organization (WHO), Environmental Protection Agency (USEPA), European

Commission and others developed on-line databases, which provide parts of the necessary input data for the

methods and tools used in risk assessment. Several databases are presented below:

- IRIS (Integrated Risk Information System) is a database elaborated and maintained by the US

Environmental Protection Agency and contains information on the human health effects caused by exposure

to various substances from environment. This database was developed in order to facilitate the risk

assessments, decision-making processes and regulatory activities by providing information about the

chemical substances toxicology. In the files provided by IRIS for different pesticides, values of oral

reference doses and inhalation reference concentrations (RfDs and RfCs) for chronic noncarcinogenic health

effects and hazard identification, oral slope factors, and oral and inhalation unit risks for carcinogenic effects

can be found [29].

- PPDB (Pesticide Properties DataBase) – was developed by the Agriculture and Environment

Research Unit (AERU) at the University of Hertfordshire in 2007 with the purpose to support risk

assessments and management of pesticides. PPDB database holds data about chemical identity,

physicochemical proprieties, human health and ecotoxicological effects for almost 2300 pesticide (synthetic

and natural including those with veterinary applications) and over 700 records for associated metabolites

approved for use in the EC and other countries The information provided by this database can be accessed on

the PPDB website, or through the IUPAC website [30].

- EU - Pesticides database was developed and maintained by European Commission with the leading

goal to give the necessary data about the pesticide residues in fruits and vegetables (378 products), the

Maximum Residue Levels (MRLs) for different pesticides and different data about 1,359 active substances.

This database is used especially by the member states of EU for risk assessment and management of

pesticides in food plants [31].

- European Chemicals Agency (ECHA) (the new version of European Chemical Substances

Information System (ESIS)) is a source of information on the chemicals manufactured and imported in

Europe, and provide data on their hazardous properties, classification and labeling [32].

- International Uniform Chemical, Information Database (IUCLID) is a software program which

provides information on environmental fate and pathways, ecotoxicity/ toxicity and physical-chemical

proprieties of chemical substances [33].

- US ECOTOX database represents a source for chemical environmental toxicity data on aquatic life,

terrestrial plants and wildlife [34].

6. Conclusions

Pesticides are intensively used in the pest control by the farmers, being found in variable quantities in

different food plants. Their negative effects to human health are especially visible for fetuses and children.

For a good management of pesticides usage, different organizations, such as EFSA or USEPA developed

different software tools to facilitate risk assessment strategies of pesticides residues found in food. These

programs were developed based on mathematical models and could be implemented by considering different

databases such as IRIS, PPDB, EU - Pesticides database, ECHA, IUCLID or US ECOTOX. In applying

these software packages for modeling risks to human health, data on pesticides characteristics and

concentrations, food consumption and effects to human health are essential. Extensive work is still necessary

in understanding the behavior, fate and transport of pesticides along different environmental compartments

so as to implement robust risk assessment strategies.

7. Acknowledgements

81

This work was supported by a grant of the Romanian National Authority for Scientific Research and

Innovation, CNCS/CCCDI - UEFISCDI, project number PN-III-P2-2.1-PED-2016-1662, within PNCDI III.

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