Constraining effects of aerosol-cloud interaction by accounting for coupling between cloud and land surface.

Aerosol-cloud interactions (ACIs) are vital for regulating Earth's climate by influencing energy and water cycles. Yet, effects of ACI bear large uncertainties, evidenced by systematic discrepancies between observed and modeled estimates. This study quantifies a major bias in ACI determinations, stemming from conventional surface or space measurements that fail to capture aerosol at the cloud level unless the cloud is coupled with land surface. We introduce an advanced approach to determine radiative forcing of ACI by accounting for cloud-surface coupling. By integrating field observations, satellite data, and model simulations, this approach reveals a drastic alteration in aerosol vertical transport and ACI effects caused by cloud coupling. In coupled regimes, aerosols enhance cloud droplet number concentration across the boundary layer more homogeneously than in decoupled conditions, under which aerosols from the free atmosphere predominantly affect cloud properties, leading to marked cooling effects. Our findings spotlight cloud-surface coupling as a key factor for ACI quantification, hinting at potential underassessments in traditional estimates.

Modifications on the coastal atmospheric sulfur and cloud condensation nuclei along the Eastern China seas by shipping fuel transition.

Marine fuel combustion from shipping releases SO2 and forms sulfate particles, which may alter low cloud characteristics. A series of strategies were implemented to control the sulfur content of ship fuel oil from 2018 to 2020, offering insights into the effects of the ship fuel oil transition on sulfur-related pollutants and the consequent cloud condensation nuclei (CCN) in the atmosphere. Compared to 2018 in the southeast China waters, shipping SO2 emission decreased by 78 % in 2020, resulting in a 76 % reduction in ship-related total sulfur concentration, and a decrease of 54 % in CCN number concentration under supersaturation 0.2 % (CCN0.2) contributed by shipping. The response of CCN0.2 to ship-related sulfate modification is more pronounced in relatively clean environments than polluted environments, highlighting the uneven changes in coastal CCN along the Eastern China Sea induced by the ship fuel policies. CCN can trigger the formation of cloud droplets, 2020 fuel regulation may have and will reduce the cooling radiative forcing effect with strong spatial heterogeneity. The study provides insights into the variations in coastal atmospheric sulfur-related pollutants and CCN in uneven response to changes in ship fuel oil, prompting the need for further comprehensive assessments of the climate effects resulting from potential shifts in ship fuel use in the future.

On Nucleation Pathways and Particle Size Distribution Evolutions in Stratospheric Aircraft Exhaust Plumes with H2SO4 Enhancement.

Stratospheric aerosol injection (SAI) is proposed as a means of reducing global warming and climate change impacts. Similar to aerosol enhancements produced by volcanic eruptions, introducing particles into the stratosphere would reflect sunlight and reduce the level of warming. However, uncertainties remain about the roles of nucleation mechanisms, ionized molecules, impurities (unevaporated residuals of injected precursors), and ambient conditions in the generation of SAI particles optimally sized to reflect sunlight. Here, we use a kinetic ion-mediated and homogeneous nucleation model to study the formation of H2SO4 particles in aircraft exhaust plumes with direct injection of H2SO4 vapor. We find that under the conditions that produce particles of desired sizes (diameter ∼200-300 nm), nucleation occurs in the nascent (t < 0.01 s), hot (T = 360-445 K), and dry (RH = 0.01-0.1%) plume and is predominantly unary. Nucleation on chemiions occurs first, followed by neutral new particle formation, which converts most of the injected H2SO4 vapor to particles. Coagulation in the aging and diluting plumes governs the subsequent evolution to a narrow (σg = 1.3) particle size distribution. Scavenging by exhaust soot is negligible, but scavenging by acid impurities or incomplete H2SO4 evaporation in the hot exhaust plume and enhanced background aerosols can matter. This research highlights the need to obtain laboratory and/or real-world experiment data to verify the model prediction.

Hidden danger: The long-term effect of ultrafine particles on mortality and its sociodemographic disparities in New York State.

Although previous studies have shown increased health risks of particulate matters, few have evaluated the long-term health impacts of ultrafine particles (UFPs or PM0.1, ≤ 0.1 µm in diameter). This study assessed the association between long-term exposure to UFPs and mortality in New York State (NYS), including total non-accidental and cause-specific mortalities, sociodemographic disparities and seasonal trends. Collecting data from a comprehensive chemical transport model and NYS Vital Records, we used the interquartile range (IQR) and high-level UFPs (≥75 % percentile) as indicators to link with mortalities. Our modified difference-in-difference model controlled for other pollutants, meteorological factors, spatial and temporal confounders. The findings indicate that long-term UFPs exposure significantly increases the risk of non-accidental mortality (RR=1.10, 95 % CI: 1.05, 1.17), cardiovascular mortality (RR=1.11, 95 % CI: 1.05, 1.18) particularly for cerebrovascular (RR=1.21, 95 % CI: 1.10, 1.35) and pulmonary heart diseases (RR=1.33, 95 % CI: 1.13, 1.57), and respiratory mortality (borderline significance, RR=1.09, 95 % CI: 1.00, 1.18). Hispanics (RR=1.13, 95 % CI: 1.00, 1.29) and non-Hispanic Blacks (RR=1.40, 95 % CI: 1.16, 1.68) experienced significantly higher mortality risk after exposure to UFPs, compared to non-Hispanic Whites. Children under five, older adults, non-NYC residents, and winter seasons are more susceptible to UFPs' effects.

Mysteriously rapid rise in Legionnaires' disease incidence correlates with declining atmospheric sulfur dioxide.

Legionnaires' disease (LD) is a severe form of pneumonia (∼10-25% fatality rate) caused by inhalation of aerosols containing Legionella, a pathogenic gram-negative bacteria. These bacteria can grow, spread, and aerosolize through building water systems. A recent dramatic increase in LD incidence has been observed globally, with a 9-fold increase in the United States from 2000 to 2018, and with disproportionately higher burden for socioeconomically vulnerable subgroups. Despite the focus of decades of research since the infamous 1976 outbreak, substantial knowledge gaps remain with regard to source of exposure and the reason(s) for the dramatic increase in LD incidence. Here, we rule out factors indicated in literature to contribute to its long-term increases and identify a hitherto unexplored explanatory factor. We also provide an epidemiological demonstration that the occurrence of LD is linked with exposure to cooling towers (CTs). Our results suggest that declining sulfur dioxide air pollution, which has many well-established health benefits, results in reduced acidity of aerosols emitted from CTs, which may prolong the survival duration of Legionella in contaminated CT droplets and contribute to the increase in LD incidence. Mechanistically associating decreasing aerosol acidity with this respiratory disease has implications for better understanding its transmission, predicting future risks, and informed design of preventive and interventional strategies that consider the complex impacts of continued sulfur dioxide changes.

Ultrafine Particles and Hospital Visits for Chronic Lower Respiratory Diseases in New York State.

RATIONALE: Exposure to particulate matter is associated with various adverse health outcomes. Ultrafine particles are a unique public health challenge due to their size. However, limited studies have examined their impacts on human health, especially across seasons and demographics. OBJECTIVES: To evaluate the effect of ultrafine particle exposure on the risk of visiting the emergency department for a chronic lower respiratory disease in New York State NYS, 2013-2018. METHODS: We used a case-crossover design and conditional logistic regression to estimate how ultrafine particle exposure led to chronic lower respiratory disease-related emergency department visits. GEOS-Chem-APM, a state-of-the-art chemical transport model with a size-resolved particle microphysics model, generated air pollution simulation data. We then matched ultrafine particle exposure estimates to geocoded health records for asthma, bronchiectasis, chronic bronchitis, emphysema, unspecified bronchitis, and other chronic airway obstructions in NYS from 2013-2018. In addition, we assessed interactions with age, ethnicity, race, sex, meteorological factors, and season. MEASUREMENTS AND MAIN RESULTS: Each interquartile range increase in ultrafine particle exposure led to a 0.37% increased risk of a respiratory-related emergency department visit on lag 0-0 (95% CI: 0.23-0.52%) and a 1.81% increase on lag 0-6 (95% CI: 1.58-2.03%). The highest risk was in the subtype emphysema (lag 0-5: 4.18%, 95% CI: 0.16-8.37%), followed by asthma (lag 0-6: 2.00%), chronic bronchitis (lag 0-6: 1.78%), other chronic airway obstructions (lag 0-6: 1.60%), and unspecified bronchitis (lag 0-6: 1.49%). We also found significant interactions between UFP health impacts and season (fall, 3.29%), temperature (<90th percentile, 2.27%), relative humidity (>90th percentile, 4.63%), age (children <18, 3.19%), and sex (men, 2.06%) on lag 0-6. CONCLUSION: In this study, UFP exposure increased chronic lower respiratory disease-related emergency department visits across all seasons and demographics, yet these associations varied according to various factors, which requires more research.

Ambient heat and diabetes hospitalizations: Does the timing of heat exposure matter?

BACKGROUND: Although ambient heat exposure is linked with diabetes mortality, the impacts of heat exposure on diabetes-related hospitalizations remain controversial. Previous research did not examine the timing of heat-diabetes associations and relation with comorbidities/risk factors. OBJECTIVE: We examined the association between heat exposure and diabetes-related hospitalizations in the transitional and summer months and identified populations vulnerable to heat. METHODS: We conducted a time-stratified case-crossover study. Data on diabetes hospital admissions (primary diagnosis of type 1 and type 2 diabetes, 2013-2020) were collected by the New York State (NYS) Department of Health under the state legislative mandate. We treated temperature and air pollutants as continuous variables and defined the heat exposure as per interquartile range (IQR, a measure between the 25th and 75th percentiles) increase of daily mean temperature. Conditional logistic regressions were performed to quantify the heat-diabetes associations after controlling for air pollutants and time variant variables. Multiplicative-scale interactions between heat and demographics/comorbidities/risk factors on diabetes hospitalizations were investigated. RESULTS: Each IQR increase in temperature was associated with significantly increased risks for diabetes admissions that occurred immediately and lasted for an entire week during multi-day lags in the transitional month of May (ranges of excess risk: 3.1 %-4.8 %) but not in the summer (June-August) (ranges of excess risk: -0.3 %-1.3 %). The significant increases in the excess risk of diabetes were also found among diabetes patients with complications of neuronopathy (excess risk: 27.7 %) and hypoglycemia (excess risk: 19.1 %). Furthermore, the modification effects on the heat-diabetes association were significantly stronger in females, Medicaid enrollees, non-compliant patients, and individuals with comorbidities of atherosclerotic heart disease and old myocardial infarction. CONCLUSIONS: Ambient heat exposure significantly increased the burden of hospital admissions for diabetes in transitional rather than summer months indicating the importance of exposure timing. Vulnerability to heat varied by demographics and heart comorbidity.

Environmental exposure disparities in ultrafine particles and PM2.5 by urbanicity and socio-demographics in New York state, 2013-2020.

BACKGROUND: The spatiotemporal and demographic disparities in exposure to ultrafine particles (UFP; number concentrations of particulate matter (PM) with diameter ≤0.1 µm), a key subcomponent of fine aerosols (PM2.5; mass concentrations of PM ≤ 2.5 µm), have not been well studied. OBJECTIVE: To quantify and compare the aerosol pollutant exposure disparities for UFP and PM2.5 by socio-demographic factors in New York State (NYS). METHODS: Ambient atmospheric UFP and PM2.5 were quantified using a global three-dimensional model of chemical transport with state-of-the-science aerosol microphysical processes validated extensively with observations. We matched these to U.S. census demographic data for varied spatial scales (state, county, county subdivision) and derived population-weighted aerosol exposure estimates. Aerosol exposure disparities for each demographic and socioeconomic (SES) indicator, with a focus on race-ethnicity and income, were quantified for the period 2013-2020. RESULTS: The average NYS resident was exposed to 4451 #·cm-3 UFP and 7.87 µg·m-3 PM2.5 in 2013-2020, but minority race-ethnicity groups were invariably exposed to greater daily aerosol pollution (UFP: +75.0% & PM2.5: +16.2%). UFP has increased since 2017 and is temporally and seasonally out-of-phase with PM2.5. Race-ethnicity exposure disparities for PM2.5 have declined over time; by -6% from 2013 to 2017 and plateaued thereafter despite its decreasing concentrations. In contrast, these disparities have increased (+12.5-13.5%) for UFP. The aerosol pollution exposure disparities were the highest for low-income minorities and were more amplified for UFP than PM2.5. DISCUSSION: We identified large disparities in aerosol pollution exposure by urbanization level and socio-demographics in NYS residents. Jurisdictions with higher proportions of race-ethnicity minorities, low-income residents, and greater urbanization were disproportionately exposed to higher concentrations of UFP and PM2.5 than other NYS residents. These race-ethnicity exposure disparities were much larger, more disproportionate, and unabating over time for UFP compared to PM2.5 across various income strata and levels of urbanicity.

The importance of ammonia for springtime atmospheric new particle formation and aerosol number abundance over the United States.

New particle formation (NPF) and subsequent growth can contribute upwards of 50 % of the global cloud condensation nuclei (CCN) budget. It is also a significant source of ultrafine aerosols (PM0.1) with health implications. Ammonia (NH3) can play a significant role in enhancing NPF and contributing to the growth of nucleated particles. Understanding these processes are vital for air quality and climate. Here, we examine the role of NH3 in NPF and consequent effects on aerosol number concentrations (including CCN) and size distributions during springtime over the United States (US). We use the GEOS-Chem chemistry transport model coupled with the size-resolved Advanced Particle Microphysics (APM) Model. We also employ measurements of particle number size distributions, CN10 (condensation nuclei > 10 nm), CCN0.4 (CCN at 0.4 % supersaturation), and aerosol composition (SO4, NO3, NH4, Organics) at the Southern Great Plains site (SGP). The impact of NH3 in ion-mediated nucleation is the improved capturing of the occurrence of almost all springtime (March-April) NPF events observed at SGP during 2015-2020. Furthermore, this brings the magnitude and temporal variations of particle number concentrations in stronger agreement with observations; mean fractional bias for modeled CN10(CCN0.4) reducing from -1.26 to -0.27 (-0.75 to -0.54) and overall good-agreement (∣FractionalBias ∣ < 0.6) improving from 8.5 to 54 % (31 to 42 %). The contribution of NH3 in new particle formation is important for springtime abundance of ultrafine aerosols (explaining 63 ± 15 % of CN10) and CCN (16 ± 10 % of CCN0.4) over the US. Our analysis shows that the deviation of CCN0.4 is strongly correlated with PM1-NH4+ deviations, suggesting the importance of improved model representation of ammonium for more accurate quantification of potential cloud forming particles.

Remote Aerosol Simulated During the Atmospheric Tomography (ATom) Campaign and Implications for Aerosol Lifetime.

We investigate and assess how well a global chemical transport model (GEOS-Chem) simulates submicron aerosol mass concentrations in the remote troposphere. The simulated speciated aerosol (organic aerosol (OA), black carbon, sulfate, nitrate, and ammonium) mass concentrations are evaluated against airborne observations made during all four seasons of the NASA Atmospheric Tomography Mission (ATom) deployments over the remote Pacific and Atlantic Oceans. Such measurements over pristine environments offer fresh insights into the spatial (Northern [NH] and Southern Hemispheres [SH], Atlantic, and Pacific Oceans) and temporal (all seasons) variability in aerosol composition and lifetime, away from continental sources. The model captures the dominance of fine OA and sulfate aerosol mass concentrations in all seasons. There is a high bias across all species in the ATom-2 (NH winter) simulations; implementing recent updates to the wet scavenging parameterization improves our simulations, eliminating the large ATom-2 (NH winter) bias, improving the ATom-1 (NH summer) and ATom-3 (NH fall) simulations, but producing a model underestimate in aerosol mass concentrations for the ATom-4 (NH spring) simulations. Following the wet scavenging updates, simulated global annual mean aerosol lifetimes vary from 1.9 to 4.0 days, depending on species. Aerosol lifetimes in each hemisphere vary by season, and are longest for carbonaceous aerosol during the southern hemispheric fire season. The updated wet scavenging parameterization brings simulated concentrations closer to observations and reduces global aerosol lifetime for all species, indicating the sensitivity of global aerosol lifetime and burden to wet removal processes.

Compositional Constraints are Vital for Atmospheric PM2.5 Source Attribution over India.

India experiences some of the highest levels of ambient PM2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMBModified: 0.19; NMBBase: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMBModified: 0.08; NMBBase: 1.64) and ammonium simulation (NMBModified: 0.49; NMBBase: 0.90). We use this validated simulation to estimate a population-weighted annual PM2.5 exposure of 61.4 µg m-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM2.5 aerosol source attribution for health assessments and air quality management in India.

Identifying joint impacts of sun radiation, temperature, humidity, and rain duration on triggering mental disorders using a high-resolution weather monitoring system.

BACKGROUND: Mental disorders (MDs) are behavioral or mental patterns that cause significant distress or impairment of personal functioning. Previously, temperature has been linked to MDs, but most studies suffered from exposure misclassification due to limited monitoring sites. We aimed to assess whether multiple meteorological factors could jointly trigger MD-related emergency department (ED) visits in warm season, using a highly dense weather monitoring system. METHODS: We conducted a time-stratified, case-crossover study. MDs-related ED visits (primary diagnosis) from May-October 2017-2018 were obtained from New York State (NYS) discharge database. We obtained solar radiation (SR), relative humidity (RH), temperature, heat index (HI), and rainfall from Mesonet, a real-time monitoring system spaced about 17 miles (126 stations) across NYS. We used conditional logistic regression to assess the weather-MD associations. RESULTS: For each interquartile range (IQR) increase, both SR (excess risk (ER): 4.9%, 95% CI: 3.2-6.7%) and RH (ER: 4.0%, 95% CI: 2.6-5.4%) showed the largest risk for MD-related ED visits at lag 0-9 days. While temperature presented a short-term risk (highest ER at lag 0-2 days: 3.7%, 95% CI: 2.5-4.9%), HI increased risk over a two-week period (ER range: 3.7-4.5%), and rainfall hours showed an inverse association with MDs (ER: -0.5%, 95% CI: 0.9-(-0.1)%). Additionally, we observed stronger association of SR, RH, temperature, and HI in September and October. Combination of high SR, RH, and temperature displayed the largest increase in MDs (ER: 7.49%, 95% CI: 3.95-11.15%). The weather-MD association was stronger for psychoactive substance usage, mood disorders, adult behavior disorders, males, Hispanics, African Americans, individuals aged 46-65, or Medicare patients. CONCLUSIONS: Hot and humid weather, especially the joint effect of high sun radiation, temperature and relative humidity showed the highest risk of MD diseases. We found stronger weather-MD associations in summer transitional months, males, and minority groups. These findings also need further confirmation.

Particle surface area, ultrafine particle number concentration, and cardiovascular hospitalizations.

While the health impacts of larger particulate matter, such as PM10 and PM2.5, have been studied extensively, research regarding ultrafine particles (UFPs or PM0.1) and particle surface area concentration (PSC) is lacking. This case-crossover study assessed the associations between exposure to PSC and UFP number concentration (UFPnc) and hospital admissions for cardiovascular diseases (CVDs) in New York State (NYS), 2013-2018. We used a time-stratified case-crossover design to compare the PSC and UFPnc levels between hospitalization days and control days (similar days without admissions) for each CVD case. We utilized NYS hospital discharge data to identify all CVD cases who resided in NYS. UFP simulation data from GEOS-Chem-APM, a state-of-the-art chemical transport model, was used to define PSC and UFPnc. Using a multi-pollutant model and conditional logistic regression, we assessed excess risk (ER)% per inter-quartile change of PSC and UFPnc after controlling for meteorological factors, co-pollutants, and time-varying variables. We found immediate and lasting associations between PSC and overall CVDs (lag0-lag0-6: ERs% (95% CI%) ranges: 0.4 (0.1,0.7) - 0.9 (0.7-1.2), and delayed and prolonged ERs%: 0.1-0.3 (95% CIs: 0.1-0.5) between UFPnc and CVDs (lag0-3-lag0-6). Exposure to larger PSC was associated with immediate ER increases in stroke, hypertension, and ischemic heart diseases (1.1%, 0.7%, 0.8%, respectively, all p < 0.05). The adverse effects of PSC on CVDs were highest among children (5-17 years old), in the fall and winter, and during cold temperatures. In conclusion, we found an immediate, lasting effects of PSC on overall CVDs and a delayed, prolonged impact of UFPnc. PSC was a more sensitive indicator than UFPnc. The PSC effects were higher among certain CVD subtypes, in children, in certain seasons, and during cold days. Further studies are needed to validate our findings and evaluate the long-term effects.

The independent and synergistic impacts of power outages and floods on hospital admissions for multiple diseases.

Highly destructive disasters such as floods and power outages (PO) are becoming more commonplace in the U.S. Few studies examine the effects of floods and PO on health, and no studies examine the synergistic effects of PO and floods, which are increasingly co-occurring events. We examined the independent and synergistic impacts of PO and floods on cardiovascular diseases, chronic respiratory diseases, respiratory infections, and food-/water-borne diseases (FWBD) in New York State (NYS) from 2002 to 2018. We obtained hospitalization data from the NYS discharge database, PO data from the NYS Department of Public Service, and floods events from NOAA. Distributed lag nonlinear models were used to evaluate the PO/floods-health association while controlling for time-varying confounders. We identified significant increased health risks associated with both the independent effects from PO and floods, and their synergistic effects. Generally, the Rate Ratios (RRs) for the co-occurrence of PO and floods were the highest, followed by PO alone, and then floods alone, especially when PO coverage is >75th percentile of its distribution (1.72% PO coverage). For PO and floods combined, immediate effects (lag 0) were observed for chronic respiratory diseases (RR:1.58, 95%CI: 1.24, 2.00) and FWBD (RR:3.02, 95%CI: 1.60, 5.69), but delayed effects were found for cardiovascular diseases (lag 3, RR:1.13, 95%CI: 1.03, 1.24) and respiratory infections (lag 6, RR:1.85, 95%CI: 1.35, 2.53). The risk association was slightly stronger among females, whites, older adults, and uninsured people but not statistically significant. Improving power system resiliency could be a very effective way to alleviate the burden on hospitals during co-occurring floods. We conclude that PO and floods have independently and jointly led to increased hospitalization for multiple diseases, and more research is needed to confirm our findings.

Rapid sulfuric acid-dimethylamine nucleation enhanced by nitric acid in polluted regions.

Recent research [Wang et al., Nature 581, 184-189 (2020)] indicates nitric acid (NA) can participate in sulfuric acid (SA)-ammonia (NH3) nucleation in the clean and cold upper free troposphere, whereas NA exhibits no obvious effects at the boundary layer with relatively high temperatures. Herein, considering that an SA-dimethylamine (DMA) nucleation mechanism was detected in megacities [Yao et al., Science 361, 278-281 (2018)], the roles of NA in SA-DMA nucleation are investigated. Different from SA-NH3 nucleation, we found that NA can enhance SA-DMA-based particle formation rates in the polluted atmospheric boundary layer, such as Beijing in winter, with the enhancement up to 80-fold. Moreover, we found that NA can promote the number concentrations of nucleation clusters (up to 27-fold) and contribute 76% of cluster formation pathways at 280 K. The enhancements on particle formation by NA are critical for particulate pollution in the polluted boundary layer with relatively high NA and DMA concentrations.

Significant underestimation of radiative forcing by aerosol-cloud interactions derived from satellite-based methods.

Satellite-based estimates of radiative forcing by aerosol-cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from -0.38 to -0.59 W m-2) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RFaci further increases to -1.09 W m-2 when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.

Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales.

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Reducing the PM2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74-1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52-0.95] million deaths; 19.2%), industrial (0.45 [0.32-0.58] million deaths; 11.7%), and energy (0.39 [0.28-0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

Simulating the impacts of ship emissions on coastal air quality: Importance of a high-resolution emission inventory relative to cruise- and land-based observations.

This work studied the impacts of ship emissions at a high temporal resolution on the real-time concentrations of PM2.5, NO2, and SO2 in urban harbors and coastal sea areas, taking the Yangtze River Delta (YRD) as an example. The WRF-Chem model with 3 nested grids and ship emissions derived from an automatic identification system (AIS) were combined to simulate the air quality. The AIS data showed significant temporal fluctuations in ship emissions, with hourly mean fluxes of approximately 1082.41 ± 444.41 and 593.55 ± 404.95 g/h/km2 near ports and in the channel waters of the YRD, respectively. The monthly mean contributions of shipping emissions reached 80.72% (2.15 ppbv) and 81.79% (8.79 ppbv) to ambient SO2 and NO2 in Ningbo Port, and 10.61% (6.96 µg/m3) to PM2.5 in Shanghai Port, respectively, regions with dense ship traffic. The relative differences in the PM2.5, SO2, and NO2 concentrations modeled using monthly and hourly ship emissions accounted for -10-15%, -10-30%, and - 5-30%, respectively. Compared with cruise- and land-based measurements, the simulations using hourly emissions were in much better agreement with the observations than those using monthly emissions and appropriately captured some air pollutant concentration peaks. Simulations during shipping-related periods with hourly ship emissions improved the normalized mean bias (NMBs) from -43.03%, 301.49%, and 223.02% to -27.28%, 90.45%, and 167.52%, respectively, for PM2.5, SO2, and NO2, highlighting the importance of using ship emissions with a fine temporal resolution. Our study showed that ignoring hourly fluctuations in ship emissions during air quality modeling leads to considerable uncertainties, especially in coastal urban areas and harbors with high ship activities. These results imply that data with a high temporal resolution, such as hourly ship emissions, are necessary to understand the realistic impacts of shipping traffic and to implement more precise control policies to improve coastal air quality.

Constraining remote oxidation capacity with ATom observations.

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half of the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July-August 2016 and January-February 2017 to evaluate the oxidation capacity over the remote oceans and its representation by the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NO y concentrations, ozone photolysis frequencies) also show minimal bias, with the exception of wintertime NO y . The severe model overestimate of NO y during this period may indicate insufficient wet scavenging and/or missing loss on sea-salt aerosols. Large uncertainties in these processes require further study to improve simulated NO y partitioning and removal in the troposphere, but preliminary tests suggest that their overall impact could marginally reduce the model bias in tropospheric OH. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by a comprehensive simulation of both biotic and abiotic ocean sources of VOCs. Additional sources of VOC reactivity in this region are difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOCs, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in both model acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean sources of VOCs in the model increases cOHRmod by 3% to 9% and improves model-measurement agreement for acetaldehyde, particularly in winter, but cannot resolve the model summertime bias. Doing so would require 100 Tg yr-1 of a long-lived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land.