In this short communication, we estimate that California's wildfire carbon dioxide equivalent (CO₂e) emissions from 2020 are approximately two times higher than California's total greenhouse gas (GHG) emission reductions since 2003. Without considering future vegetation regrowth, CO₂e emissions from the 2020 wildfires could be the second most important source in the state above either industry or electrical power generation. Regrowth may partly of fully occur over a long period, but due to exigencies of the climate crisis most of the regrowth will not occur quickly enough to avert greater than 1.5 degrees of warming. Global monetized damages caused by CO₂e from in 2020 wildfire emissions amount to some $7.1 billion USD. Our analysis suggests that significant societal benefits could accrue from larger investments in improved forest management and stricter controls on new development in fire-prone areas at the wildland-urban interface.

Ozone levels have been declining in the Los Angeles, CA, USA area for the last four decades, but there was a recent uptick in the 4th highest daily maximum 8-h (MDA8) ozone concentrations from 2014 to 2018 despite continued reductions in the estimated precursor emissions. In this study, we assess the emissions and meteorological impacts on the 4th highest MDA8 ozone concentrations to better understand the factors affecting the observed MDA8 ozone using a two-step generalized additive model (GAM)/least squares approach applied to the South Coast Air Basin (SoCAB) for the 1990 to 2019 period. The GAM model includes emissions, meteorological factors, large-scale climate variables, date, and the interactions between meteorology and emissions. A least squares method was applied to the GAM output to better capture the 4th highest MDA8 ozone. The resulting two-step model had an R² of 0.98 and a slope of 1 between the observed and predicted 4th highest MDA8 ozone. Emissions and the interactions between the maximum temperature and emissions explain most of the variation in the peak MDA8 ozone concentrations. Declining emissions have lowered the 4th highest MDA8 ozone concentration. Meteorology explains the higher than expected 4th-high, ozone levels observed in 2014–2018, indicating that meteorology was a stronger forcer than the continued reductions in emissions during that time period. The model was applied to estimate future ozone levels. Meteorology developed from climate modeling of the representative concentration pathway (RCP) scenarios, and two sets of emissions were used in the application. The modeling results indicated climate trends will push ozone levels slightly higher if no further emissions reductions are realized and that of two emissions trajectories modeled, the more stringent is required to reliably meet the federal ozone standard given annual meteorological variability.

High concentrations of ground-level ozone affect human health, plants, and animals. Reducing ozone pollution in rural regions, where local emissions are already low, poses challenge. We use meteorological back-trajectories, air quality model sensitivity analysis, and satellite remote sensing data to investigate the ozone sources in Yuma, Arizona and find strong international influences from Northern Mexico on 12 out of 16 ozone exceedance days. We find that such exceedances could not be mitigated by reducing emissions in Arizona; complete removal of state emissions would reduce the maximum daily 8-h average (MDA8) ozone in Yuma by only 0.7% on exceeding days. In contrast, emissions in Mexico are estimated to contribute to 11% of the ozone during these exceedances, and their reduction would reduce MDA8 ozone in Yuma to below the standard. Using satellite-based remote sensing measurements, we find that emissions of nitrogen oxides (NOₓ, a key photochemical precursor of ozone) increase slightly in Mexico from 2005 to 2016, opposite to decreases shown in the bottom-up inventory. In comparison, a decrease of NOₓ emissions in the US and meteorological factors lead to an overall of summer mean and annual MDA8 ozone in Yuma (by ∼1–4% and ∼3%, respectively). Analysis of meteorological back-trajectories also shows similar transboundary transport of ozone at the US-Mexico border in California and New Mexico, where strong influences from Northern Mexico coincide with 11 out of 17 and 6 out of 8 ozone exceedances. 2020 is the final year of the U.S.-Mexico Border 2020 Program, which aimed to reduce pollution at border regions of the US and Mexico. Our results indicate the importance of sustaining a substantial cooperative program to improve air quality at the border area.

Understanding how mercury (Hg) accumulates in the aquatic food web requires information on the factors driving methylmercury (MeHg) contamination. This paper employs data on MeHg in muscle tissue of three black bass species (Largemouth Bass, Spotted Bass, and Smallmouth Bass) sampled from 21 reservoirs in California. During a two-year period, reservoirs were sampled for total Hg in sediment, total Hg and MeHg in water, chlorophyll a, organic carbon, sulfate, dissolved oxygen, pH, conductivity, and temperature. These data, combined with land-use statistics and reservoir morphometry, were used to investigate relationships to size-normalized black bass MeHg concentrations. Significant correlations to black bass MeHg were observed for total Hg in sediment, total Hg and MeHg in surface water, and forested area. A multivariate statistical model predicted Largemouth Bass MeHg as a function of total Hg in sediment, MeHg in surface water, specific conductivity, total Hg in soils, and forested area. Comparison to historical reservoir sediment data suggested there has been no significant decline in sediment total Hg at five northern California reservoirs during the past 20 years. Overall, total Hg in sediment was indicated as the most influential factor associated with black bass MeHg contamination. The results of this study improve understanding of how MeHg varies in California reservoirs and the factors that correlate with fish MeHg contamination.

Two hundred sixty-three fine particulate matter (PM₂.₅) samples were collected over fourteen months in Fresno and Bakersfield, California. Samples were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and 160 organic molecular markers. Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) source apportionment models were applied to the results in order to understand monthly and seasonal source contributions to PM₂.₅ OC. Similar source categories were found from the results of the CMB and PMF models to PM₂.₅ OC across the sites. Six source categories with reasonably stable profiles, including biomass burning, mobile, food cooking, two different secondary organic aerosols (SOAs) (i.e., winter and summer), and forest fires were investigated. Both the CMB and the PMF models showed a strong seasonality in contributions of some sources, as well as dependence on wind transport for both sites. The overall relative source contributions to OC were 24% CMB wood smoke, 19% CMB mobile sources, 5% PMF food cooking, 2% CMB vegetative detritus, 17% PMF SOA summer, 22% PMF SOA winter, and 12% PMF forest fire. Back-trajectories using the Weather Research and Forecasting model combined with the FLEXible PARTicle dispersion model (WRF-FLEXPART) were used to further characterize wind transport. Clustering of the trajectories revealed dominant wind patterns associated with varying concentrations of the different source categories. The Comprehensive Air Quality Model with eXtensions (CAMx) was used to simulate aerosol transport from forest fires and thus confirm the impacts of individual fires, such as the Rough Fire, at the measurement sites.

On-road mobile sources play a significant role in air quality modeling and these models require gridded, hourly emission inputs. Due to its geographical and meteorological diversity and stringent air quality regulations, California state always poses big challenge for air quality modelers and policy makers. At the same time, the impact of ambient temperature on vehicle emissions has been well researched in the past few decades and it is vital to prepare a reliable on-road gridded emission inventory for air quality modeling. This technical paper introduces a gridding method that takes temperature impacts into account, calculates emissions from grid-level to county, and attempts to quantify the likely effects of such a bottom-up, temperature sensitive approach on a gridded on-road emission inventory. To provide confidence in the proposed SMOKE-EMFAC method, a detailed analysis was carried out to compare the results with the default EMFAC output, and the results were within ±1%. Applying detailed grid level temperatures, we also found that criteria pollutant distributions are sensitive to them, and they are in accordance with previous US-EPA study. The proposed method could be very useful while testing different complex emission regulations and policies due to its inherent flexibility.

Pyrethroid-resistant Hyalella azteca with voltage-gated sodium channel mutations have been identified at multiple locations throughout California. In December 2013, H. azteca were collected from Mosher Slough in Stockton, CA, USA, a site with reported pyrethroid (primarily bifenthrin and cyfluthrin) sediment concentrations approximately twice the 10-d LC50 for laboratory-cultured H. azteca. These H. azteca were shipped to Southern Illinois University Carbondale and have been maintained in pyrethroid-free culture since collection. Even after 22 months in culture, resistant animals had approximately 53 times higher tolerance to permethrin than non-resistant laboratory-cultured H. azteca. Resistant animals held in culture also lacked the wild-type allele at the L925 locus, and had non-synonymous substitutions that resulted in either a leucine-isoleucine or leucine-valine substitution. Additionally, animals collected from the same site nearly three years later were again resistant to the pyrethroid permethrin. When resistant animals were compared to non-resistant animals, they showed lower reproductive capacity, lower upper thermal tolerance, and the data suggested greater sensitivity to, 4, 4′-dichlorodiphenyltrichloroethane (DDT), copper (II) sulfate, and sodium chloride. Further testing of the greater heat and sodium chloride sensitivity of the resistant animals showed these effects to be unrelated to clade association. Fitness costs associated with resistance to pyrethroids are well documented in pest species (including mosquitoes, peach-potato aphids, and codling moths) and we believe that H. azteca collected from Mosher Slough also have fitness costs associated with the developed resistance.

Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) < 28%; for daily pesticide loading, NSE = 0.18 and PBIAS = −1.6%. This modeling framework will be useful for assessing the relative exposure from pesticides related to spray drift and runoff in receiving waters and the design of management practices for mitigating pesticide exposure within a watershed.

Boscalid is one of the most frequently detected pesticides in main coastal estuaries in California, with concentrations as high as 36 μg/L. However, ecotoxicology information about boscalid to aquatic organisms is scarce. To investigate toxic effects and mechanisms of boscalid on freshwater algae Chlorella vulgaris (C. vulgaris), C. vulgaris were exposed to a range of boscalid concentrations (0, 0.8, 1.6, 2.4 and 3.2 mg/L) for 96 h to study the changes in photosynthetic pigment contents, responses of the antioxidant enzyme system and alterations in endogenous substances. Results indicated that the growth of algae and the content of chlorophyll and carotenoids were significantly inhibited by 1.6 mg/L boscalid. Reactive oxygen species (ROS) and oxidative damage of C. vulgaris could be induced by boscalid, in accordance with significant changes in ROS levels and a series of antioxidant enzyme activities. Moreover, the alterations in endogenous substances showed that boscalid could affect photosynthesis and energy metabolism of C. vulgaris. These results demonstrated that boscalid could induce impacts on C. vulgaris mainly through disturbing the photosynthesis, oxidative damage and energy metabolism. The present study provided a better understanding of the negative effects and mechanisms of bosaclid in microalgae.