GREEN I.T AND DATACENTER: A STUDY OF ENVIRONMENTAL MANAGEMENT INDICATORS

Objective: Identify the environmental indicators from the ABNT ISO NBR 14031 standard applicable to data centers to improve energy efficiency and environmental management. Theoretical Framework : The study addresses concepts of Green IT, practices for data center efficiency, and the indicators from the ABNT NBR ISO 14031 standard, including environmental, managerial, operational, and condition performance indicators. Method: Bibliometric research to support the theme, through searches on the Scopus and IEEE platforms, with content analysis of the main references, including the NBR ISO 14031 standards. Results and Discussion: Operational indicators from the NBR ISO 14031 standard were identified and adapted for data centers, such as the quantity of reused materials, energy used and saved, and specific emissions. The practical application of these indicators was detailed. Research Implications: The research contributes to the application of Green IT practices and energy efficiency in data centers, providing a basis for the adoption of environmental management indicators. Originality/Value : Although there are various individual studies related to Green IT or data centers, there are few studies relating these themes together. Thus, this study fills this gap by promoting an integrated approach to Green IT and environmental management, and providing support for data center managers towards Green IT.


INTRODUCTION
The energy efficiency parameters used in the area of Datacenters infrastructure have been the subject of research and studies aimedAt achieving the best results to ensure the best performance and functioning of these environments.
According to Veras (2012), the efficiency of the The increase in energy costs has made with that the Datacenters rethink the strategy to ensure greater economy and efficiency, considering the types of equipment installed and their operation.
The exponential growth of the Internet associated with the introduction of new artificial intelligence technologies has increased the supply and enhancement of several services to the market, such as the intensive use of machine learning in place of traditional information processing techniques (Martins et al., 2022(Martins et al., , 2023)).Other applications, hitherto not considered, have also proved attractive from the expansion of the Internet, increasing the need for servers (Ito et al., 2013).
In this scenario, there is also a rapid increase in the number of servers, which results in a great demand in the supply of power to the Datacenters.Large corporations, with appropriate information security policies (Galegale et al., 2017), focused on replacing traditional energy with renewable sources in their Datacenters, further encouraging them to establish Green IT Datacenters (Zhou et al., 2015).
Having said that, it is possible to identify the following research problem: what indicators of the ABNT ISO NBR 14031:2015 can be applied to the activities of a Datacenter?Faced with this questioning, this research aims to identify the environmental indicators of the standard that can be applied to Datacenters.To achieve this goal, it was found that it was assumed that there wasa a necessary: identifying the relevant scientific production on the topics of Green and Datacenter IT; describing the concept of Green IT and identifying in the ABNT ISO NBR 14031:2015 the indicators related to the activities of a Datacenter.
The methodology used to develop this study was the use of bibliographic research.
According to Gil (2010), bibliographic research is based on already published material.
Traditionally, this research modality includes printed material, such as books, magazines, newspapers, theses, dissertations, and annals of scientific events.However, due to the dissemination of new information formats, these searches now include other types of sources, such as disks, magnetic tapes, CDs, as well as material made available through the Internet.
Thus, the present article aimed to study the main bibliographical references that combine the terms to identify the main works and themes explored.

THEORETICAL FRAME
This theoretical benchmark presents, as concepts relevant to the subjects that drive this study, the definitions and standards that deal with Green IT, the factors that interfere in the efficiency of aDatacenter, and the indicators of ISO 14031:2015.

GREEN IT
The term Green IT refers to the study and practice of designing, manufacturing, and using hardware, software, and communication systems in an efficient and effective manner, with impact In addition, IT Verdeanalso uses IT to support, assist and leverage other environmental initiatives and help create green awareness.Total power consumption in a Datacenter, with the increase in the number of servers and computers, is steadily increasing, resulting in more greenhouse gas emissions and incorrect disposal of electronic equipment that ends up in landfills, polluting the land and contaminating its water.Murugesan, 2010.Green IT can also be defined as the study and practice of using computing resources in a efficient fashion to reduce Green IT is applicable to many high-tech domains, such as datacenters, mobile computing, and enterprise systems.In addition, it is noted that 2% of global carbon dioxide emissions can be attributed to IT systems (Bener et al., 2014).

EFFICIENCY IN DATACENTER
There are two main factors that drive the efficiency of a locallyDatacenter: In this scenario, a large portion of the focus on cost and performance.
The metric used in Datacenters to measure its efficiency The EUP is calculated by dividing the total amount of energy that is consumed in (possibly) the infrastructure by the energy used to perform the information processing.The EUP is therefore expressed as a ratio, with overall efficiency improving as the quotient decreases to 1. Thus, in order to achieve this metric, companies are adopting best practices in infrastructure efficiency, such as for example: using hot/cold corridors, installing fence panels in cabinets, sealingopenings in elevated floors and adjusting the temperature of air conditioning machines.It is also noted that this practice relies on cost and performance documentation communicating data on business terms to fund future improvements making IT take responsibility for pursuing Green IT (Stansberry, 2013).
According to Chauhan and Saxena (2013), another energy saving opportunity is related to the various cloud components, highlighting the following practices for improving energy efficiency: • Because the cloud environment uses virtual machines (VMs) instead of dedicated physical machines, developers must design software for virtual machines and operating system instances using software development practicesefficiently; • Explore opportunities to customize operating system elements while keeping only those needed to perform the required task by creating a lightweight virtual machine instance that can save energy by reducing boot time and software image storage; • Consider that the design and installation of infrastructure components (hardware and computing devices) in the cloud can significantly affect energy consumption; • Practice virtualization, since multiple machines • Adopt clean energy sources andrevolving energy, • Store energy to make better use of energy sources and avoid waste.

METHODOLOGY
Initially, a bibliographic research was carried out to substantiate the theme.Afterwards, a study of the main bibliometric references that combine the terms to identify the main works and themes explored was carried out.Thus, initially, a search was conducted on the Scopus and IEEE platform, with access, by means of SBC-SociedadePesticides, in November 2018, whose results can be observed in Table 1.The definition of the expression used was composed by the keywords IT Green and Datacenter, using the logical operator AND for searching the journals, with date filter for five years, in the period of2013.Because no results were displayed for the search with this expression, the words were changed to English language, changing the search expression to this expression.With the help of the software EXCEL2016 It is important to note that the research done in isolation with each keyword resulted in numerous articles.However, using the logical operator, the result was null for research with words in Portuguese and, using the key words in English, resulted 23articles, showingthat scientific publication on the topics together is still small, which motivated the study for the elaboration of this article.
Looking at the amount of articles published annually since 2013, it can be observed that the scientific research production related to Green IT in Datacenter peaked in 2014, decreased 67% in 2016 and presented the stabilization trend in the year 2017, as observed in Figure 2.

Table 2
Indicators identified in the Environmental Aspects requirement.

Operational Performance Indicators Source
Table 3 Indicators identified in the Operational Control requirement • Operational Control -Physical Installations: -Number of hours of preventive maintenance equipment/year; -Average monthly fuel consumption; -Average monthly water consumption.
In order to clarify the use of the indicators mentioned, Table 5 presents an interpretation for each of these indicators, allowing their individualization according to the segment applied in the Datacenters.Finally, Table 6 presents examples of variables that can be used to obtain the identified environmental identifiers, with parameter suggestions for each indicator.The aim of the work is not to indicate formulae or methodologies for the appropriate calculations, but rather to clarify the relationship of indicators with their inputs.-Quantity of each type of energy used -The indicator can be set as a function of the energy matrix that provides power to the Datacenter, such as solar, wind, or free market power.

Examples of variables and parameters for the identified indicators
-Amount of energy saved due to energy -Average monthly fuel consumption -The indicator can be calculated by measuring the amount of fuel spent for the operation of generators.
-Average monthly water consumption -The indicator can be calculated by measuring the amount of water spent for use in air conditioning cooling towers.
The adoption of the above mentioned indicators will depend on each Datacenter, after evaluation of the environmental aspects relevant to its functioning and adherence to the standard.

CONCLUSION
The terms IT Green, Datacenter, and ISO14031:2015 have been little used by different groups in the scientific community.In other words, it is noted that there are few studies relating to IT topics, either Green or Datacenter, but, individually, there are several works related to each of the themes.
It is also noted that there is no consensus in relation to the theory of the activities of a Datacenter.It should also be noted that there are no published works that show the relationship of the theme with the environmental management indicators proposed by NBR ISO 14031:2015, in the period analyzed.
___________________________________________________________________________ Rev. Gest.Soc.Ambient.| Miami | v.18.n.1 | p.1-15 | e07740 | 2024.4 2.3 ABNT NBR ISO 14031:2015 -INDICATORSThe ABNT NBR ISO 14031:2015 standard supports the requirements and guidelines of other standards, ABNT NBR ISO 14001 and ABNT NBR ISO 14004 respectively, and can be used independently.The standard also provides guidance for the design and use of environmental performance assessment in an organization and is applicable to all organizations regardless of type, size, location and complexity.Internal disclosure and communication of information describing the organization's environmental performance is important to assist employees in fulfilling their responsibilities, thus enabling the organization to achieve its established criteria.ISO 14031:2015 describes two categories of indicators for Environmental Performance Assessment, presented in Figure 1.

Figure 1
Figure 1Interrelations of an organization's administration and operations with the condition of the environment

Figure 2
Figure 2Publications of articles on the subject

Figure 3
Figure 3Operations of an Organization of equipment with parts designed for easy disassembly, recycling and reuse -# of hours per year a specific piece of equipment is in operation -No. of emergency situations (e.g.explosions) or non-routine operations (e.g.operational shutdowns) per year -Total area of soil used for production purposes -Ground area used to produce a unit of energy -Average fuel consumption of the vehicle fleet -# of fleet vehicles with pollution abatement technology

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Quantity of materials discarded or reused -The greater the quantity of materials discarded, the better the indicator Environmental aspects -Energy Interpretation -Amount of energy used per year or per product unit -The lower the energy consumed, the better the indicator Quantity of each type of energy used -The more renewable sources used, the better the indicator Amount of energy saved due to energy conservation programs The more energy saved, the better the indicator Environmental aspects -Emissions Interpretation -Quantity of specific emissions per year -The lower the emission value, the better the indicator Noise measured at a certain location -The lower the noise emitted, the better the indicator Operational Control -Physical Installations Interpretation -Number of hours of preventive equipment maintenance/year -The higher the number of preventative maintenance, the better the indicator -Average monthly fuel consumption -The lower the fuel consumption, the better the indicator -Average monthly water consumption -The lower the water consumption, the better the indicator The research revealed the existence of other indicators that could be used for measurements in Datacenters, however, the present study limited itself to identifying those related to the ISO NBR 14031:2015 standard, according to the objective of the work.

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Quantity of materials discarded or reused -The indicator can be calculated by the total weight of uninstalled equipment.Environmental aspects -Energy Example -Amount of energy used per year or per product unit -The indicator can be calculated by means of the difference between the target consumption and the actual value of energy spent.

Table 1
List of selected articles Noise measured at a certain location -The indicator may be calculated by measuring the level of noise generated in relation to the level permitted by local law.
--The indicator can be calculated by the difference between established values and values performed in preventive maintenance.