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Accurate information on agricultural water needs and withdrawals at appropriate spatial and temporal scales remains a key limitation to joint water and land management decision-making. We use InVEST ecosystem service mapping to estimate water yield and water consumption as functions of land use in Fresno County, a key farming region in California's Central Valley. Our calculations show that in recent years (2010-2015), the total annual water yield for the county has varied dramatically from ~0.97 to 5.37 km3 (all ±17%; 1 MAF ≈ 1.233 km3), while total annual water consumption has changed over a smaller range, from ~3.37 to ~3.98 km3 (±20%). Almost all of the county's water consumption (~96% of total use. takes place in Fresno's croplands, with discrepancy between local annual surface water yields and crop needs met by surface water allocations from outside the county and, to a much greater extent, private groundwater irrigation. Our estimates thus bound the amount of groundwater needed to supplement consumption each year (~1.7. km3 on average). These results, combined with trends away from field crops and toward orchards and vineyards, suggest that Fresno's land and water management have become increasingly disconnected in recent years, with the harvested area being less available as an adaptive margin to hydrological stress. [ABSTRACT FROM AUTHOR]

Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM 2.5 concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM 2.5 over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM 2.5 . Smoke contributions to daily PM 2.5 concentrations have increased by up to 5 μg/m 3 in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM 2.5 above 100 μg/m 3 per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.

Using hourly measures across a full year of crowd-sourced data from over 1000 indoor and outdoor pollution monitors in the state of California, we explore the temporal and spatial relationship between outdoor and indoor particulate matter (PM) concentrations for different particle sizes. The scale of this study offers new insight into both average penetration rates and drivers of heterogeneity in the outdoor-indoor relationship. We find that an increase in the daily outdoor PM concentration of 10% leads to an average increase of 4.2-6.1% in indoor concentrations. The penetration of outdoor particles to the indoor environment occurs rapidly and almost entirely within 5 h. We also provide evidence showing that penetration rates are associated with building age and climatic conditions in the vicinity of the monitor. Since people spend a substantial amount of each day indoors, our findings fill a critical knowledge gap and have significant implications for government policies to improve public health through reductions in exposure to ambient air pollution.