5 Big Ideas on Using Big Data in Sustainability Measures
In the era of sustainability, we are facing a long list of challenges to address – the impacts of decarbonisation to the economy, reduce carbon dioxide emissions, water consumption, reduce economic inequalities, adapting to climate change, maintaining biodiversity, improving water quality and much more.
On the other hand, the world is moving fast. Land use, carbon dioxide emissions, extreme weather events, water consumption, air quality, or the species disappearance occur every day before we realize that they are actually happening.
Fortunately, we are also in the age of Big Data. Governments and private companies produce and record thousands of data sets such as electronic transactions, instant consumption of water and energy. These data sets are generating huge volumes of records that can be used by businesses and institutions for patterns analysis of behaviour; but the data have not been widely used to measure sustainability.
In addition, advanced software tools can now be used to observe patterns and reveal regularities. Although we often fail to define sustainability, we are able to define the “unsustainability” such as droughts, floods, soil loss and erosion, irreversible loss of species.
Climate change data
In physics and ecology, for example, the discipline of climate change and relate tries to process large volumes of data to analyze increase in carbon dioxide emissions and their effects on the ecosystem. Recent extreme weather events, from 45 degrees in Australia, severe drought in California, temporary Cantabrian and Atlantic, or flooding of Indonesia, or the polar vortex in the U.S. are probably related to climate change and its solution – the commitment to sustainable development.
Water consumption data
Public or private water companies collect thousands of instant water consumption data sets in different parts, which can be modelled cycle, not only to adjust supply and demand, but to determine what may be the water quality resultant, and to calculate the pollution dilution in drought, or volume of water resulting for determining circulating environmental flows.
Emission data
In a polluted city, thermal power stations or near incinerators can produce more or less emissions depending on the weather. This collected data can be used to produce pollution level report. According to pollution level, city officials can then take actions to minimize pollution, for example, restricting traffic or stopping the polluting plants.
Data from wireless devices
Sensors and wireless devices may form an excellent collection system to generate sustainability reporting, receptors that can enable the citizen to make their informed decisions. For example, to monitor real-time urban congestion information or inform citizens to avoid outdoor exercise when a city is contaminated.
Data Visualization and simulation
Visualization and communication of sustainability processes can help citizens and decision makers to visualize the problems of the existing sustainability. For examples, simulations of air pollution and predict potential negative impacts on sensitive population such as children, the elderly, pregnant women.
Fortunately, the era of sustainability is also the era of data intelligence. When we have much more data to monitor, measure, report and understand our environmental issues, we are able to optimize operations, processes and better maintain resources. When we have more information, we create new opportunities to improve and make more progress on sustainability. But surely, this will be a long-term commitment.
