Los Angeles County is the largest county in the nation with a population of approximately 10 million people. By 2050, the county is projected to have a 15% increase in population, adding 1.5 million more residents. With projected urban population growth alongside the effects of climate change, providing Angelenos with reliable energy, water and an environment that will enhance their health will be a challenge. The UCLA Sustainable LA Grand Challenge (SLA GC) was developed to address these problems and ultimately transition Los Angeles County to 100% renewable energy, 100% locally sourced water, and enhanced ecosystem and human health by 2050. In response to SLA GC’s original goals, The NOW Institute research team undertook a first-round assessment of where the county stands today and what can be done to achieve those targets by 2050.

Plant water use accounts for a major portion of the total water use in Los Angeles. Reducing water use in irrigation systems from lawns and gardens to parks is essential to achieving significant reductions in water expenditure across the urban landscape, while still maintaining critical urban greenery for public health and wellness. However, current technologies that monitor the water status of plants are time-consuming and destructive to the plants themselves. Thus, a new technology that efficiently estimates leaf water status in plants using noninvasive remote sensing technology will aide in managers’ ability to maximize water use efficiency in parks and open space.

The Sustainable LA Grand Challenge of UCLA has an ambitious goal of helping transition Los Angeles County to 100% renewable energy by 2050 through innovations in science, technology and policy. An important first step is to determine the balance of accessible renewable energy resources and its distribution and storage. To address this data gap, researchers assessed the 2050 renewable energy potential for the Los Angeles region (defined by the City of Los Angeles, Los Angeles County and the greater metropolitan area, including the surrounding counties) and presented feasible pathways for achieving the 100% renewable energy goal. This study is a preliminary assessment of the energy portfolio for the entire L.A. region.

Both the City of Los Angeles and Los Angeles County are engaged in various scientific projects to better understand, measure and preserve biodiversity in the region. However, missing from these approaches is any attempt to capture or measure the social, cultural and political perception of these critical resources across neighborhoods and different demographic groups. Biodiversity is both affected and perceived differently by different groups of people in urban environments, and there are many controversies associated with biodiversity management (e.g. coyote culling and pet safety, secondary poisoning from rat control, environmental contamination, flood control, habitat restoration, etc.).    City and County managers have only sparse and anecdotal data on how individuals respond to or engage with these issues and how their values relate to the goals and practices of biodiversity conservation. This project attempts to address this gap by eliciting responses directly from residents and collectives in the Los Angeles region to shape a more complete narrative of public understanding of and engagement on biodiversity issues. 

California’s climate is one of extremes, susceptible to rapid shifts between drought and flood. For example, the state experienced a record multi-year dryness between 2012–2016 followed by extreme wetness during the 2016–2017 winter. With global climate change, warming is likely to cause even greater precipitation variability in the future. But patterns of change by region and over time in precipitation extremes in California remain uncertain.  

California’s water infrastructure is set up for flood control, with conveying streamflow to the ocean as efficiently as possible as its primary aim. Capturing and using more stormwater is one key way that Los Angeles County can decrease its dependency on water supplies sourced from hundreds of miles away. In adapting the state’s infrastructure for stormwater capture, storage and use, it is essential to plan carefully for the precipitation extremes of the future, which will become more intense and frequent due to climate change.  Atmospheric rivers—long corridors of water vapor traveling from the Pacific Ocean to California—are responsible for producing heavy precipitation and determining the state’s flood risk. Given this context, it is critical to understand how atmospheric river events will change in a warming world. In this project, researchers quantify projected changes in future precipitation driven by extreme atmospheric rivers in California by combining global climate model (GCM) with regional modeling.  

Los Angeles County has high rates of food insecurity, federal food assistance and chronic diet-related diseases, in part due to lack of access to fresh fruits and vegetables and limited green space and safe outdoor spaces in many communities. Urban agriculture has the potential to improve public health through increased food access and consumption, thus may help address urban food insecurity. However, there is very limited data and documentation of urban agriculture activities (e.g. size, production, crop types) in the County. Recognizing this data gap, this project expanded the current documentation efforts and assessed the production potential focusing on how urban agriculture affects public health by integrating health impact assessment (HIA) methodology, geospatial analysis and policy review. 

The City of Los Angeles is undertaking various initiatives to track and reduce energy and water consumption in existing buildings. Currently, there are significant barriers such as unreliable data and non-standardized tracking mechanisms in obtaining consumption data from the City’s building stock. Recognizing this challenge, the objective of Howe’s project is to create energy and water prediction tools that will determine the future needs based on the historical record of municipal buildings using regression models.