Enabling Transformation
Use Cases - Applied Research
Scientific bodies, Research and Academic Institutions, Government and Regulatory bodies
Empowering Scientific Communities to Understand the Link between Pollution and Social Outcomes
Determine Sources and Types Of Air Pollutants For Diagnosing specific disease symptoms
As economic and urban development continue to grow at a rapid pace, it is also important to consider their impact on the environment and our health. Data on emissions and their health impacts has never been more valuable. Determining cause and effects on health, because of specific Air pollutants will be important in the future.
Research and Healthcare stakeholders need tools that will help them acquire and analyze emission knowledge for establishing links between pollution and various health and socio-economic outcomes. This is also critical in creating accountability between government, research, and citizen groups. Mentioned below are the outcomes possible by using the Vāyu Darpan suite of Tools.
Actionable Information
- Accessible data that allows any research organization to build detailed emission inventories from pollution sources and hotspots
- Data access via API and technology protocols enable integration with healthcare, demographic and socio-economic datasets
- Scenario simulation which generate predictive assessments and model emission impacts on socio-economic and development trends
- Software-as-a-Service (SaaS) delivery model which allows for remote data collection and eliminates the need for on-field resource deployment
Solution Delivery Process
Vāyu Darpan-EIT
Delivers data on emission contributors and sources with respective geospatial locations
Choose Data
Choose common demographic/urban metrics (population, vehicle count, etc.) as inputs
Sectors & Activity
ML-driven environmental models estimate emission contribution of sectors & urban activities
Scenario Analysis
AI-driven geospatial models attribute emissions to specific locations and hotspots
Benefits
Accurate assessment of pollution exposure to employees
Sustainable development and expansion planning to ensure regulatory compliance and avoid fines
Vāyu Darpan-EPP
Metrics can be modelled to simulate correlative emission impacts and enable predictive planning
Solution Delivery Process
Choose Data
Choose common demographic/urban metrics (population, vehicle count, etc.) as inputs
Sectors & Activity
ML-driven environmental models estimate emission contribution of sectors & urban activities
Scenario Analysis
AI-driven geospatial models attribute emissions to specific locations and hotspots
Vāyu Darpan-EIT
Delivers data on emission contributors and sources with respective geospatial locations
Vāyu Darpan-EPP
Metrics can be modelled to simulate correlative emission impacts and enable predictive planning
Benefits
Accurate assessment of pollution exposure to employees
Sustainable development and expansion planning to ensure regulatory compliance and avoid fines
Vāyu Darpan - Use Case
As a
diagnostic tool
Members of the research and scientific community can now benefit from the capability of Vāyu Darpan-EIT to entirely automate the process of collecting and analyzing data from emission sources. This eliminates the need for time-consuming and resource-intensive field surveys and data collection.
Emissions studies and audits can be conducted remotely and cost-effectively which can be further integrated for building correlations with Health and Socio-economic indices.
Bridging Science, Technology and Policy
Building correlations between emissions and their Health Impacts
A prominent research institute has been tasked with identifying the root cause of a sudden spate of contractions of a particular cardiovascular disease in a city. Initial findings indicated that the disease was a direct result of high levels of air pollution.
There are a number of urban activities including construction, traffic movement and manufacturing, operating within the city and each of these activities causes a different type of pollutant to be emitted. It is difficult to identify the pollutant responsible for causing the reported cardiovascular disease.
The Research Institute must investigate the matter and accurately identify emission source emitters and correlate the outcomes to the disease. Traditional approaches would require field-deployment of large research teams to collect and analyze data, which could prove time-consuming and cost prohibitive.
Approach to the Solution
- Plug in locally available data on urban activities and demographics into Vayu Darpan–EIT and analyze the activity data to generate geospatially accurate emission inventories and information on pollution hotspots
- Compare the information on emission assessments and hotspots with locations of cardiovascular disease occurrence
- Build correlations and validate them statistically between commonly occurring emission contributors and cardiovascular disease
- Build action plans to correct the emission hotspots which are impacting the disease occurrence
Stakeholders and Beneficiaries
- Citizens gaining positive health outcomes because of reduced pollution exposure
- Medical Professionals, who are now empowered with knowledge on emission sources that are causing health risks
- Regulators, who can take informed decisions and build the right capacities to control emissions based on scientifically validated data
- Research organizations, who can reduce costs through the automated analytics approach and avoid on-field deployment of researchers
- Healthcare service organizations, who can formulate coordinated action plans based on the analyzed data
Short Term Impact
- By establishing a cause & effect correlation between emission activities and health outcomes, it will allow the stakeholders to create urgent control action plans
- SaaS delivery models can enable data-sharing and coordination between regulators, research, and healthcare personnel
- Cost and Time savings when compared with traditional emission survey plans that involve field deployment of scientific consultants over several months
- Assessed data on Emission profiles and hotspots can now be correlated with other types of health risks and demographic parameters within the same city
Long Term Impact
- Valuable health benefits and improved quality of life for citizens who will be empowered with information to implement corrective measures along with other stakeholders
- Creation of a Pollution vs Health correlation model which can be replicated for any disease and enable actionable strategies against specific disease conditions
- Establishing a sustainable and inclusive ecosystem of shared accountability and coordination between Government, Citizens, and Industries with respect to addressing pollution emission
- Successful integration of authenticated scientific data into applied research and policy formulation that can be implemented at National, State and Local levels
Vāyu Darpan - Use Case
As a
Planning tool
Vāyu Darpan Emission Planner and Predictor (EPP) is an easy and scientifically robust method of creating Emission Impact Assessment outcomes, estimates and correlations that will enable Government, Industry, and Society to take remedial actions.
Bridging Science, Technology and Policy
SDG planning through emission forecasts due to socio-economic trends
A university based in New Delhi has been contracted to help the country plan for its future development while keeping UN-defined Sustainable Development Goals. It has been asked to pay specific attention to environmental and air quality impacts on health and urban development growth
This is a complex study and requires the university to consider economic growth as well as its consequential effects which would include health impacts, urban migration, urban development, increased traffic density and higher industrial outputs
To add to the complexity, the country has less than 10 years to achieve the UN-defined SDGs. This action plan must be prepared in time to enable the country to take appropriate corrective actions. To achieve this plan a scalable and cost effective solution such as Vāyu Darpan-EPP needs to be implemented
Approach to the Solution
- Identify specific parameters and locations which are likely to drive economic growth
- Include parameters such as urban population growth, traffic density, construction activity, types of Industry required and others to drive growth
- Use Vayu Darpan - EPP to estimate emission contributions of each activity based on the defined parameters
- Simulate activity parameters to achieve growth metrics and health impacts based on generated emission predictions
- Recast development strategies in consideration of Climate Change and Pollution impacts
Stakeholders and Beneficiaries
- Citizens gaining positive health outcomes of planned reduction in pollution exposure
- National, State and Local planning committees and taskforces, who can now have access to actionable and predictive data on environmental and social impacts of their decisions
- University/Research institutes, who can avoid field-deployment of their researchers and benefit from cost and time overruns and get access to authenticated data
Short Term Impact
- Development of an executable Sustainability Action Plan for the Nation which balances development, health, and environmental interests
- SaaS delivery models that enable data-sharing and coordination between National planning committees, Research organizations and Citizen groups
- Cost and Time savings compared with traditional survey plans involving field deployment of scientific consultants over extended periods of time
- Emission forecasts and predictions that can be continuously modified to reflect real-world and policy changes
Long Term Impact
- Valuable health benefits and improved quality of life for citizens
- Long-term Sustainable Development Action Plan that can be replicated at State, Local and Municipal levels
- Shared accountability and coordination between Government, Citizens, and Industries towards addressing pollution and Climate Change
- Successful integration of authenticated scientific data into applied research and policy formulation initiatives