At last year’s Glasgow COP26, India pledged to reach net zero by 2070. Meanwhile, Part 2 of the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), released earlier this year, listed India as the country most “economically harmed” by climate change.
The IPCC’s AR6 is the first in its report’s 30-year history to devote an entire chapter to innovation and technology development. The immense potential of new technologies for adaptation and mitigation of climate change is recognized by both policy makers and investors. Recent innovations in climate mitigation technology include:
Clean, reliable energy solutions and decarbonization technologies that drive zero-emission manufacturing. Developing an elogistics platform and mobile his application to help reduce emissions from transportation by promoting the adoption of electric vehicles (EVs). Using precision agriculture platforms to optimize agricultural production and reduce food waste. Evidence also shows the increasing use of artificial intelligence (AI) and machine learning (ML)-powered applications and tools in many sectors to reduce greenhouse gas (GHG) emissions. I’m here. AI and ML can help you perform compute-intensive simulations for big and raw data analysis, forecasting and forecasting for disaster management, resource optimization, advanced scientific modeling, and real-time decision making.
Using AI and ML to improve energy efficiency and reduce waste and deadweight assets can limit GHG emissions. The global evidence in this area is very encouraging. For example, in California, USA, intelligent traffic control signals powered by machine learning have reduced traffic congestion, reduced equipment budgets, increased reliability, and effectively eliminated manual monitoring of traffic signals. increase. The system catalogs vehicle types, along with vehicle entry/exit, direction, and speed at intersections. Such smart traffic light mechanisms significantly reduce emissions by reducing vehicle idling time.
Meanwhile, in Ottawa, Canada, AI is being considered to manage EV charging during peak electricity demand, optimize energy consumption, reduce GHG emissions, and balance overall energy demand and supply. increase. The UK is using AI to assess demand for EVs and develop ultra-high quality EV charging networks. In Indonesia, an AI-powered model is being developed to solve the problem of waste management.
AI, ML, and the Internet of Things (IoT) can also help effective water management by analyzing real-time water loss, detecting water contaminants, and enabling smart irrigation. ML algorithms predict groundwater levels in China and South Korea, and Singapore uses computational modeling to predict water quality in coastal areas. We also developed a low-cost portable remote microinvertebrate detector that uses AI to test real-time water samples, respond to commands, and send live reports and alerts in special cases.
According to India’s 3rd Biennial Update Report (BUR3) to the United Nations Framework Convention on Climate Change, electricity production is the largest contributor to CO2 emissions (40%), followed by road transport (9%) and steel (5%). ), and cement production in 2016 (4%). Current estimates suggest that these sectors will continue to be major sources of emissions. This is an excellent opportunity to explore technological solutions and drive innovation towards energy efficiency and reduction of his GHG emissions.
(Taneja leads cross-cutting initiatives and Murthy leads the Center for Climate, Environment, Sustainability, Science, Technology and Policy Research (CSTEP))
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