Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study.

BACKGROUND: Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate trends in black carbon and PM2·5 concentrations and their attributable mortality burden across the USA. METHODS: In this study, we derived daily concentrations of PM2·5 and its highly toxic black carbon component at a 1-km resolution in the USA from 2000 to 2020 via deep learning that integrated big data from satellites, models, and surface observations. We estimated the annual PM2·5-attributable and black carbon-attributable mortality burden at each 1-km2 grid using concentration-response functions collected from a national cohort study and a meta-analysis study, respectively. We investigated the spatiotemporal linear-regressed trends in PM2·5 and black carbon pollution and their associated premature deaths from 2000 to 2020, and the impact of wildfires on air quality and public health. FINDINGS: Our results showed that PM2·5 and black carbon estimates are reliable, with sample-based cross-validated coefficients of determination of 0·82 and 0·80, respectively, for daily estimates (0·97 and 0·95 for monthly estimates). Both PM2·5 and black carbon in the USA showed significantly decreasing trends overall during 2000 to 2020 (22% decrease for PM2·5 and 11% decrease for black carbon), leading to a reduction of around 4200 premature deaths per year (95% CI 2960-5050). However, since 2010, the decreasing trends of fine particles and premature deaths have reversed to increase in the western USA (55% increase in PM2·5, 86% increase in black carbon, and increase of 670 premature deaths [460-810]), while remaining mostly unchanged in the eastern USA. The western USA showed large interannual fluctuations that were attributable to the increasing incidence of wildfires. Furthermore, the black carbon-to-PM2·5 mass ratio increased annually by 2·4% across the USA, mainly due to increasing wildfire emissions in the western USA and more rapid reductions of other components in the eastern USA, suggesting a potential increase in the relative toxicity of PM2·5. 100% of populated areas in the USA have experienced at least one day of PM2·5 pollution exceeding the daily air quality guideline level of 15 µg/m3 during 2000-2020, with 99% experiencing at least 7 days and 85% experiencing at least 30 days. The recent widespread wildfires have greatly increased the daily exposure risks in the western USA, and have also impacted the midwestern USA due to the long-range transport of smoke. INTERPRETATION: Wildfires have become increasingly intensive and frequent in the western USA, resulting in a significant increase in smoke-related emissions in populated areas. This increase is likely to have contributed to a decline in air quality and an increase in attributable mortality. Reducing fire risk via effective policies besides mitigation of climate warming, such as wildfire prevention and management, forest restoration, and new revenue generation, could substantially improve air quality and public health in the coming decades. FUNDING: National Aeronautics and Space Administration (NASA) Applied Science programme, NASA MODIS maintenance programme, NASA MAIA satellite mission programme, NASA GMAO core fund, National Oceanic and Atmospheric Administration (NOAA) GEO-XO project, NOAA Atmospheric Chemistry, Carbon Cycle, and Climate (AC4) programme, and NOAA Educational Partnership Program with Minority Serving Institutions.

A Global-Scale Mineral Dust Equation.

A robust method to estimate mineral dust mass in ambient particulate matter (PM) is essential, as the dust fraction cannot be directly measured but is needed to understand dust impacts on the environment and human health. In this study, a global-scale dust equation is developed that builds on the widely used Interagency Monitoring of Protected Visual Environments (IMPROVE) network's "soil" formula that is based on five measured elements (Al, Si, Ca, Fe, and Ti). We incorporate K, Mg, and Na into the equation using the mineral-to-aluminum (MAL) mass ratio of (K2O + MgO + Na2O)/Al2O3 and apply a correction factor (CF) to account for other missing compounds. We obtain region-specific MAL ratios and CFs by investigating the variation in dust composition across desert regions. To calculate reference dust mass for equation evaluation, we use total-mineral-mass (summing all oxides of crustal elements) and residual-mass (subtracting non-dust species from total PM) approaches. For desert dust in source regions, the normalized mean bias (NMB) of the global equation (within ±1%) is significantly smaller than the NMB of the IMPROVE equation (-6% to 10%). For PM2.5 with high dust content measured by the IMPROVE network, the global equation estimates dust mass well (NMB within ±5%) at most sites. For desert dust transported to non-source regions, the global equation still performs well (NMB within ±2%). The global equation can also represent paved road, unpaved road, and agricultural soil dust (NMB within ±5%). This global equation provides a promising approach for calculating dust mass based on elemental analysis of dust.

Total sulfur analysis of fine particulate mass on nylon filters by ICP-OES.

Sulfur (S) and sulfate (SO4 2- ) in fine particulate matter (PM2.5 ) are monitored by the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at remote and rural sites across the United States. Within the IMPROVE network, S is determined from X-ray fluorescence (XRF) spectroscopy from a Teflon filter, and SO4 2- is determined via ion chromatography (IC) from a nylon filter. Differences in S and SO4 2- estimates may indicate the presence of organosulfur (OS) species or biases between sampling and analytical methods. To reduce potential biases, an inductively coupled plasma-optical emission spectroscopy (ICP-OES) method was developed to allow for analysis of SO4 2- and S from a single filter extract. Sulfur (ICP-OES) and SO4 2- (IC) estimates from 2016 IMPROVE filters correlated strongly, suggesting that, on average, ICP-OES accurately estimated S. However, observed differences between slopes suggested the presence of water-soluble OS species, especially during summer. Organosulfur species are important indicators of secondary organic aerosols formed through reactions of biogenic and anthropogenic pollutants and can be quantified through laboratory techniques such as reverse-phase liquid chromatography (RPLC) or hydrophilic liquid interaction chromatography (HILIC) coupled to electrospray ionization-high-resolution tandem mass spectrometry (RPLC/ESI-HR-MS/MS and HILIC/ESI-HR-MS/MS, respectively), and field techniques using Aerodyne aerosol mass spectrometry (AMS). However, these methods are costly and introduce relatively large uncertainties when scaled for large networks such as IMPROVE. The method described in this report provides an inexpensive complement to XRF, which measures total S (insoluble and water-soluble S) to estimate water-soluble S and OS concentrations in PM.

Author Correction: Global and regional trends of atmospheric sulfur.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Global and regional trends of atmospheric sulfur.

The profound changes in global SO2 emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and Europe. Europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and East Asia. The uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. The agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget.

Employers' views of the "Healthy Hub Roadshow": a workplace HIV testing intervention in England.

We explored employer uptake and perceptions of workplace human immunodeficiency virus (HIV) testing delivered to employees as part of Healthy Hub Roadshow, a multi-component general health check. Intervention included health checks with tailored advice delivered to 776 employees at 20 events hosted by 11 different workplaces (29 approached, 38% employer uptake). Delivery partners were third sector organisations with significant expertise in HIV testing and support. Health checks included optional HIV test (using 4th generation Insti finger prick rapid tests), Body Mass Index (BMI), blood glucose, blood pressure, and cholesterol. Mixed-methods evaluation included post-event online survey and qualitative interviews with participating employers. Declining employers were invited to complete an online feedback survey. Workplace HIV testing was positively received by all participating organisations, although 78% (14/18) of declining organisations did not provide their reasons for non-participation. Factors of importance to employers included the perceived trustworthiness of delivery partners, being able to provide engaging opportunities for employee health, offering HIV testing as part of a wider health check, and having visible top-level managerial support. Concerns about hosting the events were rare and related to having limited budgets for future events, and the potential loss of productivity related to attendance during work time. Employers indicated that they would not actively seek out workplace HIV testing as part of health promotion efforts, but they were highly receptive to its inclusion in workplace health and wellbeing provision by credible external delivery partners. In conclusion, workplaces are an untapped arena for HIV awareness raising and testing in the UK. Employers should be encouraged and supported to offer opt-in HIV testing as part of a wider workplace health and wellbeing provision for employees.

Simulation of airborne trace metals in fine particulate matter over North America.

Trace metal distributions are of relevance to understand sources of fine particulate matter (PM2.5), PM2.5-related health effects, and atmospheric chemistry. However, knowledge of trace metal distributions is lacking due to limited ground-based measurements and model simulations. This study develops a simulation of 12 trace metal concentrations (Si, Ca, Al, Fe, Ti, Mn, K, Mg, As, Cd, Ni and Pb) over continental North America for 2013 using the GEOS-Chem chemical transport model. Evaluation of modeled trace metal concentrations with observations indicates a spatial consistency within a factor of 2, an improvement over previous studies that were within a factor of 3-6. The spatial distribution of trace metal concentrations reflects their primary emission sources. Crustal element (Si, Ca, Al, Fe, Ti, Mn, K) concentrations are enhanced over the central US from anthropogenic fugitive dust and over the southwestern U.S. due to natural mineral dust. Heavy metal (As, Cd, Ni and Pb) concentrations are high over the eastern U.S. from industry. K is abundance in the southeast from biomass burning and high concentrations of Mg is observed along the coast from sea spray. The spatial pattern of PM2.5 mass is most strongly correlated with Pb, Ni, As and K due to their signature emission sources. Challenges remain in accurately simulating observed trace metal concentrations. Halving anthropogenic fugitive dust emissions in the 2011 National Air Toxic Assessment (NATA) inventory and doubling natural dust emissions in the default GEOS-Chem simulation was necessary to reduce biases in crustal element concentrations. A fivefold increase of anthropogenic emissions of As and Pb was necessary in the NATA inventory to reduce the national-scale bias versus observations by more than 80 %, potentially reflecting missing sources.

Space-time trends of PM2.5 constituents in the conterminous United States estimated by a machine learning approach, 2005-2015.

Particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) is a complex mixture of chemical constituents emitted from various emission sources or through secondary reactions/processes; however, PM2.5 is regulated mostly based on its total mass concentration. Studies to identify the impacts on climate change, visibility degradation and public health of different PM2.5 constituents are hindered by limited ground measurements of PM2.5 constituents. In this study, national models were developed based on random forest algorithm, one of machine learning methods that is of high predictive capacity and able to provide interpretable results, to predict concentrations of PM2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) across the conterminous United States from 2005 to 2015 at the daily level. The random forest models achieved high out-of-bag (OOB) R2 values at the daily level, and the mean OOB R2 values were 0.86, 0.82, 0.71 and 0.75 for sulfate, nitrate, OC and EC, respectively, over 2005-2015. The long-term temporal trends of PM2.5 sulfate, nitrate, OC and EC predictions agreed well with their corresponding ground measurements. The annual mean of predicted PM2.5 sulfate and EC levels across the conterminous United States decreased substantially from 2005 to 2015; while concentrations of predicted PM2.5 nitrate and OC decreased and fluctuated during the study period. The annual prediction maps captured the characterized spatial patterns of the PM2.5 constituents. The distributions of annual mean concentrations of sulfate and nitrate were generally regional in the extent that sulfate decreased from east to west smoothly with enhancement in California and nitrate had higher concentration in Midwest, Metro New York area, and California. OC and EC had regional high concentrations in the Southeast and Northwest as well as localized high levels around urban centers. The spatial patterns of PM2.5 constituents were consistent with the distributions of their emission sources and secondary processes and transportation. Hence, the national models developed in this study could provide supplementary evaluations of spatio-temporal distributions of PM2.5 constituents with full time-space coverages in the conterminous United States, which could be beneficial to assess the impacts of PM2.5 constituents on radiation budgets and visibility degradation, and support exposure assessment for regional to national health studies at county or city levels to understand the acute and chronic toxicity and health impacts of PM2.5 constituents, and consequently provide scientific evidence for making targeted and effective regulations of PM2.5 pollution.

Origin of Fine Particulate Carbon in the Rural United States.

Carbonaceous compounds are a significant component of fine particulate matter and haze in national parks and wilderness areas where visibility is protected, i.e., class I areas (CIAs). The Regional Haze Rule set the goal of returning visibility in CIAs on the most anthropogenically impaired days to natural by 2064. To achieve this goal, we need to understand contributions of natural and anthropogenic sources to the total fine particulate carbon (TC). A Lagrangian chemical transport model was used to simulate the 2006-2008 contributions from various source types to measured TC in CIAs and other rural lands. These initial results were incorporated into a hybrid model to reduce systematic biases. During summer months, fires and vegetation-derived secondary organic carbon together often accounted for >75% of TC. Smaller contributions, <20%, from area and mobile sources also occurred. During the winter, contributions from area and mobile sources increased, with area sources accounting for half or more of the TC in many regions. The area emissions were likely primarily from residential and industrial wood combustion. Different fire seasons were evident, with the largest contributions during the summer when wildfires occur and smaller contributions during the spring and fall when prescribed and agricultural fires regularly occur.

Deposition of reactive nitrogen during the Rocky Mountain Airborne Nitrogen and Sulfur (RoMANS) study.

Increases in reactive nitrogen deposition are a growing concern in the U.S. Rocky Mountain west. The Rocky Mountain Airborne Nitrogen and Sulfur (RoMANS) study was designed to improve understanding of the species and pathways that contribute to nitrogen deposition in Rocky Mountain National Park (RMNP). During two 5-week field campaigns in spring and summer of 2006, the largest contributor to reactive nitrogen deposition in RMNP was found to be wet deposition of ammonium (34% spring and summer), followed by wet deposition of nitrate (24% spring, 28% summer). The third and fourth most important reactive nitrogen deposition pathways were found to be wet deposition of organic nitrogen (17%, 12%) and dry deposition of ammonia (14%, 16%), neither of which is routinely measured by air quality/deposition networks operating in the region. Total reactive nitrogen deposition during the spring campaign was determined to be 0.45 kg ha(-1) and more than doubled to 0.95 kg ha(-1) during the summer campaign.

Revised algorithm for estimating light extinction from IMPROVE particle speciation data.

The Interagency Monitoring of Protected Visual Environments (IMPROVE) particle monitoring network consists of approximately 160 sites at which fine particulate matter (PM2.5) mass and major species concentrations and course particulate matter (PM10) mass concentrations are determined by analysis of 24-hr duration sampling conducted on a 1-day-in-3 schedule A simple algorithm to estimate light extinction from the measured species concentrations was incorporated in the 1999 Regional Haze Rule as the basis for the haze metric used to track haze trends. A revised algorithm was developed that is more consistent with the recent atmospheric aerosol literature and reduces bias for high and low light extinction extremes. The revised algorithm differs from the original algorithm in having a term for estimating sea salt light scattering from Cl(-) ion data, using 1.8 instead of 1.4 for the mean ratio of organic mass to measured organic carbon, using site-specific Rayleigh scattering based on site elevation and mean temperature, employing a split component extinction efficiency associated with large and small size mode sulfate, nitrate and organic mass species, and adding a term for nitrogen dioxide (NO2) absorption for sites with NO2 concentration information. Light scattering estimates using the original and the revised algorithms are compared with nephelometer measurements at 21 IMPROVE monitoring sites. The revised algorithm reduces the underprediction of high haze periods and the overprediction of low haze periods compared with the performance of the original algorithm. This is most apparent at the hazier monitoring sites in the eastern United States. For each site, the PM10 composition for days selected as the best 20% and the worst 20% haze condition days are nearly identical regardless of whether the basis of selection was light scattering from the original or revised algorithms, or from nephelometer-measured light scattering.

Hygroscopic organic aerosols during BRAVO?

The hygroscopic properties of the organic fraction of aerosols are poorly understood. The ability of organic aerosols to absorb water as a function of relative humidity (RH) was examined using data collected during the 1999 Big Bend Regional Aerosol and Visibility Observational Study (BRAVO). (On average, organics accounted for 22% of fine particulate matter with an aerodynamic diameter less than 2.5 microm (PM2.5) mass). Hourly RH exceeded 80% only 3.5% of the time and averaged 44%. BRAVO aerosol chemical composition and dry particle size distributions were used to estimate PM2.5 light scattering (Bsp) at low and high ambient RH. Liquid water growth associated with inorganic species was sufficient to account for measured Bsp for RH between 70 and 95%.