312
In e na ional Jou nal o Ad ance and Applied Resea ch
www.ijaa .co.in
ISSN – 2347-7075
Impac Fac o – 8.141
Pee Re iewed
Bi-Mon hly
Vol. 6 No. 38
Sep embe - Oc obe - 2025
AI in Clima e Science and En i onmen al Sus ainabili y: P edic ion,
Moni o ing
Rupali Shinde
Assis an P o esso , Depa men o Compu e Science,
D . D. Y. Pa il Science and Compu e Science College, Aku di, Pune-411044
Co esponding Au ho – Rupali Shinde
DOI - 10.5281/zenodo.17315924
Abs ac :
A i icial In elligence (AI) has eme ged as a ans o ma i e ool in add essing clima e change
and p omo ing en i onmen al sus ainabili y. This pape e iews key applica ions o AI in a eas such as
clima e modeling, esou ce managemen , en i onmen al moni o ing, and disas e p edic ion. D awing
om ecen li e a u e, i highligh s bene i s like enhanced p edic i e accu acy and esou ce e iciency,
while add essing challenges including high ene gy consump ion and da a biases. Fu u e di ec ions
emphasize g een AI de elopmen and e hical go e nance o maximize AI's posi i e impac on
sus ainable de elopmen goals (SDGs).
Keywo ds: A i icial In elligence, Clima e Science, En i onmen al Sus ainabili y, Machine
Lea ning, G een AI, Clima e Modeling, Sus ainable De elopmen Goals
In oduc ion:
Clima e change poses one o he mos
p essing global challenges, wi h ising
empe a u es, ex eme wea he e en s, and
biodi e si y loss h ea ening ecosys ems and
human socie ies. A i icial In elligence (AI)
and Machine Lea ning (ML) o e powe ul
capabili ies o analyze as da ase s, p edic
en i onmen al changes, and op imize
sus ainable p ac ices. In clima e science, AI
enhances modeling o complex sys ems like El
Niño-Sou he n Oscilla ion (ENSO) o ecas s
and sea-le el ise p edic ions. Fo
en i onmen al sus ainabili y, AI suppo s
e icien esou ce managemen ,
deca boniza ion, and ci cula economy
ini ia i es, aligning wi h SDGs such as 7
(A o dable and Clean Ene gy), 13 (Clima e
Ac ion), and 15 (Li e on Land). This pape
ou lines he s uc u e o a esea ch pape on
his opic, inco po a ing key insigh s om
ecen e iews o demons a e how o popula e
each sec ion wi h subs an ia ed con en .
Li e a u e Re iew:
The li e a u e on AI in clima e science
and sus ainabili y is apidly expanding, wi h
e iew pape s syn hesizing applica ions ac oss
domains.
AI in Clima e Modeling and P edic ion:
AI excels in p edic i e modeling by
in eg a ing me eo ological, geospa ial, and
oceanic da a o o ecas ex eme e en s like
hu icanes, hea wa es, and loods. Deep
lea ning echniques imp o e mul i-yea
clima e o ecas s, such as ENSO pa e ns,
enabling be e mi iga ion s a egies.
Addi ionally, AI analyzes sa elli e image y o
assessing de o es a ion a es and ca bon
seques a ion, in o ming conse a ion e o s
in a eas like he Amazon ain o es .
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Applica ions in En i onmen al Moni o ing
and Resou ce Managemen :
AI acili a es eal- ime pollu ion
de ec ion, ai quali y o ecas ing, and wildli e
conse a ion by p ocessing sa elli e and senso
da a o ack de o es a ion, ice mel , and illegal
poaching. In ene gy sys ems, AI op imizes
g ids and mic og ids, in eg a ing enewables
like sola and wind h ough p ecise o ecas s,
educing losses and emissions. P ecision
ag icul u e uses AI-d i en d ones and senso s
o minimize wa e and e ilize use, de ec
c op diseases, and p edic yields, suppo ing
ood secu i y and soil heal h.
AI o Sus ainable U ban and Indus ial
P ac ices:
In sma ci ies, AI op imizes a ic,
public anspo , and esou ce dis ibu ion,
while enabling p edic i e main enance and ai
quali y moni o ing. Indus ial applica ions
include op imizing ene gy in manu ac u ing,
such as cemen p oduc ion, and suppo ing
ci cula economies h ough AI-enhanced
was e so ing and supply chain analysis. G een
AI app oaches, di ided in o "g een-by AI" (AI
o eco- iendly p ac ices) and "g een-in AI"
(ene gy-e icien AI design), u he educe he
en i onmen al oo p in o AI i sel .
Me hodology:
Fo a esea ch pape on his opic, he
me hodology sec ion would desc ibe he
app oach o da a collec ion and analysis. This
could in ol e a sys ema ic li e a u e e iew
using da abases like Scopus o PubMed, wi h
inclusion c i e ia ocusing on pee - e iewed
a icles om 2020 onwa d. Tools like AI-
based ex analysis (e.g., na u al language
p ocessing) could be employed o ca ego ize
applica ions and ex ac hemes. I empi ical, i
migh include ML model de elopmen , such as
using Py hon lib a ies like sciki -lea n o
Tenso Flow o simula e clima e p edic ions,
wi h alida ion me ics like accu acy and F1-
sco e.
Resul s and Discussion:
1. Bene i s:
AI's in eg a ion yields signi ican
bene i s, including imp o ed p edic i e
accu acy o clima e impac s, educed
g eenhouse gas emissions h ough op imized
ene gy use, and enhanced biodi e si y
p o ec ion ia moni o ing. I p omo es
esou ce e iciency in ag icul u e and indus y,
os e ing esilience o disas e s and suppo ing
sus ainable u ban de elopmen . G een AI
makes high-quali y esea ch accessible
wi hou high compu a ional cos s, aligning
wi h eco-conscious p ac ices.
2. Challenges:
Despi e bene i s, challenges pe sis .
AI's ene gy-in ensi e aining con ibu es o
ca bon emissions and e-was e, c ea ing an "AI
g een pa adox." Da a biases ampli y
inequali ies, while he "black box" na u e
educes anspa ency and us . High
implemen a ion cos s and da a p i acy issues
exace ba e di ides, pa icula ly in de eloping
egions, alongside sho ages o specialized
expe s.
Challenge
Desc ip ion
Risk Le el ( om
li e a u e)
Ecological Foo p in
High ene gy and wa e use in AI ope a ions
High (16/20)
Da a Bias and Quali y
Biases pe pe ua ing inequali ies; lack o
s anda diza ion
High (20/20)
In e p e abili y
"Black box" models hinde ing accoun abili y
Medium (12/20)
Implemen a ion
Ba ie s
Cos s and access di ides
High (16/20)
IJAAR Vol. 6 No. 38 ISSN – 2347-7075
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Fu u e Di ec ions:
To o e come challenges, u u e
esea ch should p io i ize ene gy-e icien
algo i hms like TinyML and spa se models,
powe ed by enewables. Emphasize
explainable AI (XAI) o anspa ency, e hical
amewo ks o bias mi iga ion, and
in e na ional collabo a ions o b idge di ides.
In eg a ion wi h IoT and ci izen science could
enhance eal- ime moni o ing, while policy
adap a ions ensu e esponsible AI deploymen .
Conclusion:
AI holds immense po en ial o
ad ance clima e science and en i onmen al
sus ainabili y, om p edic i e modeling o
esou ce op imiza ion. Howe e , add essing i s
en i onmen al oo p in and e hical conce ns is
c ucial o equi able bene i s. By adop ing
g een AI p ac ices and os e ing
in e disciplina y collabo a ion, we can ha ness
AI o achie e a mo e sus ainable u u e.
This ou line demons a es a s anda d esea ch
pape o ma , adap able wi h o iginal da a o
deepe analysis.
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