The digital age and how its technologies are driving sustainability in business. This article will explore some of the many impacts that digitalization has had on sustainability business transformation and how these impacts interact with the triple-bottom-line.
Digitalization can be defined as the integration of modern technologies into our everyday lives. This integration is made possible thanks to the digitization of information. Digitization is the process of converting physical data such as written information into digitized data that can be stored on the Internet of Things (IoT). The IoT exists as an interactive virtual interchange of data made possible by software and other developed technologies.
The convergence of data on the Internet of Things has led to technologies that are capable of real-time analysis, machine learning, and artificial intelligence. Such technologies are responsible for driving sustainability initiatives at an accelerated rate and are becoming a major tech for good force. For example, robotic manufacturing machinery and automation have led to the reduction of waste. Precision agriculture is aided by GIS and remote sensing, and so on.
Digitalization and sustainability
Digitalization in Agriculture
As the world’s population continues to grow, as does the global demand for food, animal feed, and fiber products. Changing climate conditions have presented issues with a warmer climate, altered rain patterns, and an increase in extreme weather events like droughts and floods. The result of these changes includes an increase in costs related to production, pest control, and disease control.
To combat these looming issues, the agricultural world has been forced into innovation through digitalization. Digitalization has helped farmers with land assessments, soil-crop suitability, weather information, crop growth, biomass and productivity, and precision farming. These technologies have assisted farmers in creating greener operations by optimizing crop rotation schedules.
GIS-based technologies and remote sensing has increased knowledge of topography, land use, soil types, climatic conditions, and suitability for sustainable citrus orchards in China. Potato farms in Saudi Arabia use the same technology to monitor vegetation dynamics, crop health, and yield. Italian farmers have gone as far as implementing the technologies to monitor agricultural plastic waste and recycling. Smart drone-based imagery has assisted in the early detection of pests and diseases in the coconut industry in India and led to more sustainable operations.
Precision agriculture and robotics are putting the data gathered from GIS-based technologies into action. More efficient watering and fertilizing techniques have reduced water and fertilizer waste by up to 20% in Nebraska. Organic farmers are finding success in eliminating the use of pesticides altogether through the use of weed zapping robots. Remote sensing equipment on the robots quickly identifies the weeds and the robot then evaporates the weed with up to 12,000 volts of electricity.
Gene sequencing has taken it one step further by giving life to crops that are more climate change-resistant. Digitalization of genomes has empowered us to identify, isolate, and selectively breed for traits that are drought resistant, pest resistant, have a higher yield, and so on. Genome-assisted breeding in legumes has resulted in the production of high-quality seeds that are more stress-tolerant, productive, and have a higher nutritional content. Wheat, barley, and rye have similarly seen improvements in plant growth and yield-related traits to help keep up with the pressures associated with a growing population. Genetically modified organisms often get a bad rap, but in the Philippines, Vitamin A-enriched rice is helping with a national malnourishment crisis.
Digitalization in Energy
Conventional energy grids are designed around a single source of generation, such as a large power plant. The demand for electricity is based on weather conditions, climatology, and even societal habits. Detailed data modeling has empowered conventional energy grids to accurately gauge the amount of electricity needed on any given day to prevent the over or under generation of energy.
The introduction of renewable energies has complicated digital sustainability in the energy sector. Conventional energy grids are one-directional, whereas a grid comprised of rooftop solar panels and wind turbines result in a distributed energy generation system. Generating energy closer to home prevents the loss of energy through the lengthy transmission process. But what happens when too much or not even electricity is generated? In a distributed energy generation system, digitalization is essential to preventing energy shortages and energy waste.
Smart digital meters can help prevent the overuse of electricity at peak times. They can also be used for intermittent electricity generation to prevent waste. For example, a smart digital meter can choose to heat the water instead of sending energy back to the grid when it is not needed. These same smart management electricity systems are used to optimize peer-to-peer electricity trading throughout the grid. Neighboring communities can now generate electricity for one another instead of relying on a singular power plant many miles away.
The grid becomes even more complex when introducing many different sources of energy. In a smart grid environment, there can be wind turbines, PV solar panels, nuclear power, fossil fuel power, hydroelectric, and more sources all contributing to a singular grid. A smart grid system ideally encourages the generation of renewable energies before fossil fuels, coal, or nuclear. Digitalization enables a smart grid system, but energy management policies often hinder them with their politics.
It’s impossible to talk about digitalization in the energy sector without talking about industry and transportation. In fact, these industrial activities and transportation together combine for more than half of the total energy usage on the planet. Unfortunately, these industries have some of the lowest optimization and efficiency rates. For example, diesel engines are only about 45% efficient. This means that 55% of the energy produced to power a diesel engine is wasted.
Data logging in the transportation sector has reduced environmental impacts related to fossil fuel combustion by optimizing onboard fuel consumption. Interconnected devices on the Internet of Things have resulted in dynamic route optimization, fuel capacity optimization, maintenance needs, and even allows the habits of drivers to be considered. Data logging has saved costs related to fossil fuel consumption, reduced emissions, and increased the longevity of a truck’s life.
Digitalization in Water Quality
Wastewater treatment plants, drinking water treatment plans, and desalination plants are all complex and sensitive facilities that remove pollutants, impurities, and salts from targeted bodies of water. The removal of pollutants, impurities, and salts all require their own unique processes that must be integrated with one another. Traditionally, these types of plants have relied on generalization rather than accuracy meaning that they oversize their facilities and overtreat, which ultimately increases capital expenditures.
In addition, failure to adequately maintain instrumentation and controls leads to inaccurate readings that impact the final product of the water quality. Remote sensing and digitalization can better identify maintenance needs and pollutant levels within a water body in real-time. The use of artificial intelligence has further enabled passive data to be used as actionable data in the decision-making process.
The Flint, Michigan water crisis highlighted the need for integrated water sensing to ensure that water quality is up to safe drinking water standards. Although Flint got the spotlight, the issue is an endemic problem worldwide. Smart cities of the future offer a holistic approach to manage the finite resource of fresh water. Decentralized smart technologies are being implemented as old-fashioned infrastructure is replaced that allows water quality to be monitored at the point of use. These decentralized technologies work in conjunction with artificial intelligence to identify water quality issues and quickly address them by implementing remediation methods.
Digitalization has been a driving force in the world of sustainability. Many of the complex environmental challenges are being tackled thanks to digitalization and the use of data on integrated systems. This article explores how digitalization has impacted energy, water quality, and agriculture in the world.
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Author: Jordan Pogorzelski holds a BA in Conservation and Environmental Science from the University of Wisconsin – Milwaukee. He started his career at the Wisconsin Department of Natural Resources working in the Bureau of Waste and Materials Management. Soon after, his life goals brought him out to Salt Lake City, Utah to work as the Stormwater Program Coordinator at the Utah Department of Transportation. He also works as a part-time Sustainability Research Coordinator for a start-up called AMAST, an online wholesaler marketplace for construction materials. Jordan is currently pursuing an MBA with a specialization in Sustainability Management and Analytics at Concordia University. In his free time, Jordan enjoys the many recreational opportunities that Utah has to offer. He likes to explore the outdoors by hiking, camping, fishing, and snowboarding.