UGC NTA NET/JRF Exam, Environmental Sciences, September-2022

The BOD₅, test is commonly used for several reasons:
• To determine the amount of oxygen that will be required for biological treatment of the organic matter present in a wastewater
• To determine the size of the waste treatment facility needed
• To assess the efficiency of treatment processes
• To determine compliance with wastewater discharge permits seeded. The BOD value is expressed in milligrams per liter, according to the following equation.

A circular economy is a systemic approach to economic development designed to benefit businesses, society, and the  environment.

In contrast to the 'take-makewaste' linear model, a circular economy is regenerative by design and aims to gradually decouple growth from the consumption of finite resources.

After defining what an economy actually is, this learning path explores the nuances of the concept of a circular economy, including the difference between biological and technical materials, the different opportunities that exist to keep materials and products in use, and the history of the idea.

Regardless of how wastes are technically categorized by regulatory agencies, their pollutant-releasing capacities depend on their physical characteristics, which determine their mode of transport into the environment.

The four major waste types based on physical characteristics combustible wastes, solid wastes, sludge and slurry wastes, and wastewaters-are presented in Figure, which shows how each of these types can eventually release pollutants into the atmospheric, terrestrial, and aquatic environments.

Combustible wastes yield byproducts that can be released directly into the atmosphere as gases or particulate pollutants when they are not properly filtered.

Solid wastes can release pollutants into the atmosphere via dust or particular transport, or when these wastes come into contact with water, their soluble constituents can be leached out into the soil surface or below.

Sludge and slurry wastes can release pollutants into the soil and groundwater from both their solid and liquid phases.

Wastewaters, owing to their liquid state, are always potential sources of pollution if discharged directly into the aquatic or terrestrial environment without proper treatment.

Environmental Impact Assessment (EIA) is a process of evaluating the likely environmental impacts of a proposed project or development, taking into account interrelated socio-economic, cultural and humanhealth impacts, both beneficial and adverse.

EIA is usually required for a development project when:
(i) There are potentials for transboundary impact.
(ii) Many people are likely to be affected by the project.
(iii) There are protected areas in the project area of influence.

In statistics, the p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct. The p-value serves as an alternative to rejection points to provide the smallest level of significance at which the null hypothesis would be rejected.

A smaller p-value means that there is stronger evidence in favour of the alternative hypothesis. In practice, the significance level is stated in advance to determine how small the p-value must be to reject the null hypothesis.

Because different researchers use different levels of significance when examining a question, a reader may sometimes have difficulty comparing results from two different tests. P-values provide a solution to this problem.

Test methods to evaluate hypotheses with measurement data are summarized in the following Table. We distinguish parametric and non-parametric tests depending on the format and distribution of the underlying raw data.
Table: Overview of parametric and non-parametric test methods

The main characteristic of the parametric tests consists in the fact that the analyzed models have a specific distribution.

The main characteristic of the non-parametric is that only a very general assumption is made, more general than parametric test.

Early statisticians noticed the same shapе coming up over and over again in different distributions-so they named it the normal distribution.
Normal distributions have the following features:
Symmetric bell shape
• Mean and median are equal; both located at the center of the distribution
• ≈68% of the data falls within 1 standard deviation of the mean
• ≈95% of the data falls within 2 standard deviations of the mean
• ≈99.7% of the data falls within 3 standard deviations of the mean

The probability of a Type II error is defined to be the probability of not rejecting the null hypothesis when, in fact, the null hypothesis is not correct.

(This is sometimes referred to as a false negative.") Again, in the food example, suppose that the sample estimate of ẞ is not sufficiently greater than zero for the researcher to conclude that the null hypothesis should be rejected.

If, in fact, there is a positive relationship between the two variables in the population and the null hypothesis of no positive relationship is not true, the researcher would have committed a Type II error by failing to reject the null. For example, suppose that we want to test the following hypotheses:

H₀: The drug ineffective; vs. Hₐ: The drug is effective.
Then a type I error occur if we conclude that the drug is effective when in fact it is not. On the other hand, a type II error occurs if we claim that the drug is ineffective when in fact it is effective.