Albuquerque | Climate Pollution Reduction Grant Data Consultant

Albuquerque skyline with pink sky.

Climate Pollution Reduction Grant Data Consultant

Lotus is currently working with the City of Albuquerque, New Mexico to complete several projects to support its Comprehensive Climate Action Plan (CCAP) as a part of Albuquerque’s Climate Pollution Reduction Grant (CPRG). Lotus’s scope includes the creation of a four county-wide community greenhouse gas and co-pollutant emissions inventories, a business-as-usual model, and greenhouse gas emissions reductions forecasting for all measures included in the City’s CCAP. Lotus will also support Albuquerque in developing several other deliverables necessary for the CCAP, including a workforce analysis, regular federal reporting, and a cost analysis for the measures included in the CCAP. 

Albuquerque has also requested Lotus support additional CPRG-funded projects that include developing a benefits analysis, assistance with guiding a climate vulnerability assessment and tree canopy analysis, graphic design for the CCAP, and drafting educational materials for a take action campaign.

Additional scope that Lotus will provide beginning in 2026 includes developing a benefits analysis to inform the development and implementation of climate pollution reduction measures. The benefits analysis will include a climate vulnerability assessment, tree canopy model, and other relevant activities to help local governments prioritize climate action and implementation. Lotus will utilize existing data sets and models, and where unavailable, will conduct research or interviews to fill any information gaps.

For the Climate Vulnerability analysis, Lotus will summarize current risks, threats, and hazards and will detail predicted future vulnerabilities to the four counties and City of Albuquerque, including those to social, economic, environmental, and infrastructure, amongst other sectors. The full vulnerability and risk assessment will include a write-up with key takeaways.

The tree canopy model will include the identification of high-impact tree planting locations (LIDAC focus, maximizing co-benefits such as traffic calming, home energy savings, etc.). The overlay map of data will include available data such as demographic data, heat data, and transportation data down to the census block group.  It will also overlay city property and parks. 


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