Climate change is not a distant threat looming on the horizon! The more destructive storms, deluges, and droughts the world experiences, the more we have this sobering thought: the earth is running out of time to heal and protect itself. If India must do something significant, such as achieving net-zero emissions target by 2070, it has to ramp up efforts in adaptation and mitigation, starting from immediate crisis response to long-term planning.
It is easier said than done!
Both climate mitigation (tackling the cause) and adaptation (tackling the impact) require every stakeholder to make informed decisions. It can’t happen without granular and actionable insights. This is where the potential of artificial intelligence (AI) can be tapped into. As a tool, AI is useful when it comes to collating and interpreting large and complex data sets. Be it hazards forecasting, calculating GHG emissions or assessing threats to natural habitats, the technology can be leveraged for empowering stakeholders to take a more data-driven approach to climate adaptation and mitigation.
Urban Waste Management
Urban waste is a conundrum in most cities of India. They are not just an eye sore, but a source of methane emissions, which is more potent than carbon dioxide in warming the atmosphere. According to the Global Methane Tracker 2022, waste sector accounts for about 20% of methane emissions in India. For example, 26% of methane emissions in Mumbai originated in landfills. It is 6% for Delhi.
With reports suggesting Indian cities generating up to 165 million tonnes of municipal solid waste by 2030, there is concern that most of the waste collected ends up in landfills. A social enterprise in the southern city of Chennai is using informal waste pickers to tackle the problem. A startup, Kabadiwalla Connect, has induced technology into the equation by piloting AI-powered solutions to connect waste collectors with recycling facilities. It is expected to empower the informal sector and decentralise waste management.
Energy Efficiency and Transition
There is another important frontier of climate action: fighting energy poverty to fuel India’s growth and accelerating our move towards net zero emission. This cannot happen without ensuring efficiency of energy operations. Fortunately, we are at a time when energy-intensive sectors such as power, transport, and heavy industry are beginning to decarbonise and transition to low-carbon energy systems. However, these changes bring forth strategic and operational challenges, which is where AI can intervene. It can help relevant stakeholders identify patterns and insights in data, improve system performance, and predict possible outcomes of new interventions.
AI is already being leveraged to support transition towards alternate energy sources. For instance, supply forecasting for solar energy can be used for detecting areas where there is potential to implement solar energy. AI is also helping develop efficient and interconnected energy systems by improving grid operations and demand-side management.
Accurate Forecasting and Early Warning System
Early warning systems aid in mitigating impacts of extreme weather events. AI can be used to analyse data from weather stations, satellite images and sensor networks. This, in turn, helps to identify conditions that could cause natural disasters like floods, wildfires, and hurricanes. For instance, the Google Flood Forecasting Initiative uses Google’s infrastructure and models developed by AI to provide precise flood forecasting information and notify people via alerts in at-risk regions, in real-time. It processes on-ground data obtained from governmental agencies to predict location and timing of floods, along with its severity.
Similarly, Microsoft India and Sustainable Environment and Ecological Development Society, (SEEDS) have collaborated to create an AI model called Sunny Lives. When implemented, it will be able to predict heatwave risks in India. It has also been used to predict cyclones and floods.
The infrastructure we design and build today should be ready for a zero-carbon world, but that has not been the case. Commercial buildings, for example, are not managed as efficiently as they should have been, and they end up being wasteful. According to recent data, around 40% of carbon footprint is generated by construction of buildings and their upkeep due to various processes, including lighting, cooling, and heating of building materials.
To develop sustainable commercial infrastructure, we need to construct or upgrade buildings in a way that they make optimum use of energy. Using AI-based management systems to optimise energy use can save energy lost from these buildings due to excess heating and cooling that are often beyond the needs of the occupants.
Farmers in India, for generations, have depended on their traditional wisdom to sow seeds, irrigate lands, and harvest their produce. However, extreme weather events are now challenging their wisdom and causing rural distress. We either hear news of low yield and crop losses due to erratic rain and prolonged drought or stories of production glut, wherein farmers incur huge losses because of excess production and low market demand. So, how do we fix this?
Farmers in India need intelligent solutions to improve quality of their harvest, get faster market access for the produce, and reduce wastage. The country has started walking in that direction. Some Indian farmers are reportedly adopting AI-led smart farming strategies to decide on crop suitability, application of fertilisers and pesticides, management of weeds and irrigation needs. In fact, ICRISAT, headquartered in Hyderabad, is reportedly collaborating with Microsoft to enable Indian farmers to harness the power of AI to increase agricultural yields while maintaining environmental sustainability.
Telangana, for example, has deployed an AI-based solution, which provides early alerts on pest attack to cotton farmers, and thereby, reducing crop loss. Initially implemented in 150 villages, the technology reportedly led to “more than 20 per cent increase in net profit for 7,000 farmers”. This AI-powered pest management system is now being scaled up to support other smallholder farmers.
Real-time monitoring of changes happening on the ground is crucial for designing an effective response. Globally, AI-enabled drones, real-time monitoring devices, and infra-red cameras are being lapped up for surveillance and assessment. Technology is being developed to use satellite imaging and radar data to monitor tree growth and measure carbon sequestration a particular forest is contributing to.
Illegal tree logging, which contributes 10% of global warming emissions, is a menace, all governments are fighting, but shortage of trained human resources is an impediment. AI is already being put into use to address this challenge. Google’s AI framework, TensorFlow, can identify sounds of chainsaws and logging trucks to unmask illegal activities and plan effective environmental protection efforts.
We, as a nation, are increasingly becoming aware of AI’s ability to perform cognitive tasks like thinking, analysing, problem solving, and decision making with higher levels of intelligence. We are also aware of the gaps we need to plug to build a climate-resilient country, and how each sector can be strengthened to prepare for climate contingencies. It is time we invested in understanding how we marry the challenges with opportunities and make optimum use of this technology.