The paper considers the problem of assessing the ecological state of the environment in the region. An approach to the intelligent analysis and estimation of anthropo-technogenic pollution of a territory with the application of integral indicators which take into account environmental pollution is proposed. To estimate the integral indicator parameters, distributed group expertise technology is used, supporting a mechanism for control of expert estimates consistency, taking into account experts' competency in the relevant subject areas. Using the proposed approach, the problem of risk assessment of environmental impact of chemical air pollutants has been solved. Methods for control of expert estimates consistency based on the procedure of feedback with experts made it possible to increase the reliability of evaluation results and also to decrease the influence of a random expert error on the final assessment. The obtained aggregated risk estimates were used to construct, calculate and visualize the integral indicator of radioactive and chemical contamination of the districts of Bryansk region.
Today, scientific problems of monitoring and evaluating biological and medical
consequences of anthropo-technogenic pollution of the environment are a priority for
state policy in all economically developed countries [
Analysis of environmental pollution using traditional statistical methods is not
always possible due to the lack of unity and required accuracy of measurement results
of environmental pollution indicators used in monitoring and the absence of a unified
structured system for assessing environmental pollution [
Multi-criteria optimization is a group of decision-making methods. These methods consist in finding an optimal solution that satisfies several criteria not reducible to each other, based on a certain optimality principle.
An expert approach is based on the use of the collective opinion of experts (i.e.,
specialists in the relevant subject areas) in the preparation and decision-making
process. Expert opinions are usually expressed partly in quantitative and partly in
qualitative forms. Expert methods are used in situations where the choice, justification and
assessment of the consequences of decisions cannot be performed on the basis of
accurate calculations. The current level of information and communication
technologies makes it possible to organize distributed interaction of experts among
themselves, as well as with decision-makers and managers of expertise, using modern
communication networks, primarily the Internet. Due to the above circumstances, a
new phenomenon called networked expertise is emerging. Within its framework,
expert networks and network expert communities are being created and are actively
developing [
Due to the heterogeneity of environmental statistical data in estimating anthropotechnogenic pollution, it seems difficult to fully assess the risk of a specific impact of pollutants on the environment. Therefore, in this study, we have applied an approach to estimating the environmental situation on the example of Bryansk region using multi-criteria optimization methods together with the distributed expertise technology.
Earlier in [
Transferring the decision-making process to a distributed environment complicates
the use of traditional methods of organizing expert activity [
In this paper, it is proposed to consider implementation features of the technology for supporting group expertise in a distributed environment aimed at estimating the ecological state of the environment on the example of Bryansk region.
Intelligent Analysis of the Ecological State of Environment with Application of… 3 2
The purpose of applying networked expertise in this study is to assess the importance (priority, hazard) of chemical and radiation pollutants for each environmental media (air, water, soil) and food. One of the main tasks of expert estimates is to obtain weight coefficients of each of the specific environmental media pollutants. A separate subtask is to estimate the degree of influence of a particular pollutant on the environmental media based on the exposure hazard.
To obtain an objective expert opinion, each of the conditions must be met: • availability of an expert group consisting of experts with subject matter expertise; • availability of an analytical group with knowledge of mathematical apparatus for obtaining and processing expert information.
In general, preparation and conduct of the networked expertise includes such stages as
formation of an expert group, choice of a type and method of obtaining expert
estimates, assessment of expert estimates consistency, and determination of the final
(aggregated) consistent expert estimate. In addition, an important task arises related to
assessing experts’ competency in the relevant subject area and taking it into account
in the estimation model, both at the stage of assessing expert estimates consistency
and at the stage of forming the final assessment. Solution to the listed problems is
based on the use of information technology for group expertise support in a
distributed environment [
The first step after obtaining a set of individual estimates of objects is to check the consistency of this set taking into account the experts’ competency. When working with numerical (cardinal) estimates, the consistency of the set of individual estimates W = {w1 , …, wm} can be evaluated using a spectral coefficient: K S (W ) = 1 − k=1 p p p k k − k k − k ln( k )
k=1 k=1 p G k − ( p + 1)/ 2 ln( p) k=1 z , where k is the sum of the coefficients of experts’ relative competency ci; their estimates are represented by the k-th scale mark; G = m / ln(m) p ln(p) is a scale factor; 1 if z* = TRUE; z =
0 if z* = FALSE, q−1 q−1 z* = [k (1) = 1] [k (q) = p] [ k (d ) = k (d +1) ] d=1[k (d ) − k (d + 1) = const]. d =1 (1) (2)
Expression (3) is a Boolean function that specifies the necessary and sufficient
conditions for the equality of the consistency coefficient (1) to zero. In this case, q is the
number of subgroups of experts who gave the same estimates, k(d) is the number
of the scale mark corresponding to the estimate received from the experts of the d-th
subgroup (d = 1, …, q), k(d) is the sum of the competency coefficients of the experts
of the d-th subgroup (a more detailed description can be found in [
After calculating the consistency coefficient, it is necessary to compare its value
with the threshold values TO (detection threshold) and TU (application threshold), and
to assess whether the consistency degree of the set of expert estimates is sufficient to
be used to calculate the aggregated estimate [
Considering this fact, we can say that one of the important aspects of organizing
group expertise in a distributed environment is the control of expert estimates
consistency based on conducting a feedback procedure with experts [
ci m w0 = ci wi .
i=1 (4) (5)
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Let us consider, for example, the problem of expert estimation of the risk of the impact of chemical air pollutants on the environment. The expertise objects are 15 chemicals (CO, NO, NO2, ammonia, ethanol, suspended solids, formaldehyde, acetic acid, hydrogen fluoride, manganese, iron oxide, hydrogen sulfide, petroleum hydrocarbons, xylene, toluene).
To analyze and estimate the objects, an expert group was formed, which included six independent experts specializing in various environmental aspects. The experts’ competency was assessed on the basis of their level of knowledge in the expertise subject area. The corresponding competency coefficients are presented in Table 1. Expert’s number, i Competency coefficient, ci A numerical rating scale with values from 1 (least influence) to 15 (greatest influence) was chosen as the estimation scale.
To process the results of expert estimation, the initial spectral consistency coefficients of each obtained expert estimate set were calculated, the detection and application thresholds were determined. In cases where the consistency coefficient value appeared to be less than the value of the application threshold, the method of increasing the consistency was used based on the procedure of feedback with experts. Table 2 presents the results of increasing the consistency, as well as the final aggregated estimates and the corresponding ranks of the expertise objects.
Analysis of the results of solving the estimation problem showed the following.
As a result of increased consistency, it was possible to ensure complete consistency of expert estimates for objects such as manganese, xylene, and toluene – the final consistency coefficient exceeds the application threshold (the corresponding cells in the table are highlighted in green). For formaldehyde, the consistency coefficient of estimates exceeded the application threshold from the beginning, which allows us to speak about the consistency of the initial set of estimates for this object.
The initial coefficient value of the expert estimate consistency for four objects (CO, ammonia, acetic acid, petroleum hydrocarbons) did not exceed the detection threshold. This means that the consistency of the corresponding estimates is below the acceptable threshold (the corresponding cells in the table are highlighted in red). Consistency increasing procedure led to an increase in the consistency coefficient, but the application threshold was not exceeded. Also, it was not possible to ensure high consistency of expert estimates for the suspended solid object, although the initial value of the consistency coefficient exceeded the detection threshold. The cells in the table corresponding to the situation when the estimates consistency coefficient is between the detection and application thresholds are highlighted in yellow.
For all the other objects, the initial value of the consistency coefficient exceeded the detection threshold. As a result of the consistency increase, it was possible to make it close to the application threshold though not exceeding it. This also allows us to conclude that the final expert estimates for these objects are sufficiently consistent.
In the course of increasing the consistency, reasons for the low consistency of estimates of some objects were identified. It was found that, in most cases, the opinions of experts with numbers 5 and 6, who had the least competence in the subject area, differed significantly from the other experts’ opinions. In this regard, it was decided to replace these two experts with one new expert whose competence roughly coincides with the competence of expert 4 and is estimated by the coefficient с5´ = 0.143 (exactly equal to the sum of the values c5 and c6). The estimation process was repeated with the renewed expert group. The results are shown in Table 3.
The results of the repeated expertise lead to the following conclusions.
For seven objects (CO, NO, ethanol, formaldehyde, manganese, xylene, toluene), the final value of the consistency coefficient of expert estimates exceeds the application threshold, which means that the estimates are completely consistent.
For the rest of the objects (NO2, ammonia, suspended solids, acetic acid, hydrogen fluoride, iron oxide, hydrogen sulfide, petroleum hydrocarbons), the application threshold could not be exceeded, but it was possible to approach it to an adequate degree This allows to calculate the final aggregated estimate with acceptable accuracy.
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The resulting aggregated risk estimates of the impact of chemical air pollutants on
the environment were used to construct an integral indicators of environmental
pollution in accordance with the methodology described in [
No. As can be seen from the presented data, the most chemically contaminated territories are Dyatkovsky district and the city of Bryansk; in terms of the density of radioactive contamination, the following districts are the most contaminated: Novozybkovsky, Gordeevsky, Krasnogorsky, Zlynkovsky, Klintsovsky, Klimovsky, Starodubsky and Dyatkovsky districts. 5
The paper considers an approach to the intelligent analysis of ecological situation, based on the application of multi-criteria optimization and technology for supporting group expertise in a distributed environment. An informative and reliable method for estimating anthropo-technogenic pollution of a territory is proposed. It uses integral indicators taking into account environmental pollution. This method was used to assess radioactive and chemical contamination of the districts of Bryansk region.
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Expert technologies make it possible to overcome the limitations imposed by methods of statistical data processing as well as those associated with the impossibility of processing heterogeneous environmental and statistical data by traditional methods. Meanwhile, the transition from traditional methods of expert estimation to network ones provides an effective form of distributed interaction among the participants in this process and helps to reduce its total duration. In turn, the use of models and methods for control of expert estimates consistency contributes to an increase in the reliability of estimation results and a decrease in the influence of a random expert error on the final assessment.