Arctic amplification-induced decline in West and South Asia dust warrants stronger antidesertification toward carbon neutrality.

Dust loading in West and South Asia has been a major environmental issue due to its negative effects on air quality, food security, energy supply and public health, as well as on regional and global weather and climate. Yet a robust understanding of its recent changes and future projection remains unclear. On the basis of several high-quality remote sensing products, we detect a consistently decreasing trend of dust loading in West and South Asia over the last two decades. In contrast to previous studies emphasizing the role of local land use changes, here, we attribute the regional dust decline to the continuous intensification of Arctic amplification driven by anthropogenic global warming. Arctic amplification results in anomalous mid-latitude atmospheric circulation, particularly a deepened trough stretching from West Siberia to Northeast India, which inhibits both dust emissions and their downstream transports. Large ensemble climate model simulations further support the dominant role of greenhouse gases induced Arctic amplification in modulating dust loading over West and South Asia. Future projections under different emission scenarios imply potential adverse effects of carbon neutrality in leading to higher regional dust loading and thus highlight the importance of stronger anti-desertification counter-actions such as reforestation and irrigation management.

Large-scale climate patterns offer preseasonal hints on the co-occurrence of heat wave and O3 pollution in China.

Heat waves and air pollution extremes exert compounding effects on human health and food security and may worsen under future climate change. On the basis of reconstructed daily O3 levels in China and meteorological reanalysis, we found that the interannual variability of the frequency of summertime co-occurrence of heat wave and O3 pollution in China is regulated mainly by a combination of springtime warming in the western Pacific Ocean, western Indian Ocean, and Ross Sea. These sea surface temperature anomalies impose influences on precipitation, radiation, etc., to modulate the co-occurrence, which were also confirmed with coupled chemistry-climate numerical experiments. We thus built a multivariable regression model to predict co-occurrence a season in advance, and correlation coefficient could reach 0.81 (P < 0.01) for the North China Plain. Our results provide useful information for the government to take actions in advance to mitigate damage from these synergistic costressors.

Improving Estimates of Sulfur, Nitrogen, and Ozone Total Deposition through Multi-Model and Measurement-Model Fusion Approaches.

Earth system and environmental impact studies need high quality and up-to-date estimates of atmospheric deposition. This study demonstrates the methodological benefits of multimodel ensemble and measurement-model fusion mapping approaches for atmospheric deposition focusing on 2010, a year for which several studies were conducted. Global model-only deposition assessment can be further improved by integrating new model-measurement techniques, including expanded capabilities of satellite observations of atmospheric composition. We identify research and implementation priorities for timely estimates of deposition globally as implemented by the World Meteorological Organization.

Characterization of ground-based atmospheric pollution and meteorology sampling stations during the Lake Michigan Ozone Study 2017.

The Lake Michigan Ozone Study 2017 (LMOS 2017) in May and June 2017 enabled study of transport, emissions, and chemical evolution related to ozone air pollution in the Lake Michigan airshed. Two highly instrumented ground sampling sites were part of a wider sampling strategy of aircraft, shipborne, and ground-based mobile sampling. The Zion, Illinois site (on the coast of Lake Michigan, 67 km north of Chicago) was selected to sample higher NOx air parcels having undergone less photochemical processing. The Sheboygan, Wisconsin site (on the coast of Lake Michigan, 211 km north of Chicago) was selected due to its favorable location for the observation of photochemically aged plumes during ozone episodes involving southerly winds with lake breeze. The study encountered elevated ozone during three multiday periods. Daytime ozone episode concentrations at Zion were 60 ppb for ozone, 3.8 ppb for NOx, 1.2 ppb for nitric acid, and 8.2 µg m-3 for fine particulate matter. At Sheboygan daytime, ozone episode concentrations were 60 ppb for ozone, 2.6 ppb for NOx, and 3.0 ppb for NOy. To facilitate informed use of the LMOS 2017 data repository, we here present comprehensive site description, including airmass influences during high ozone periods of the campaign, overview of meteorological and pollutant measurements, analysis of continuous emission monitor data from nearby large point sources, and characterization of local source impacts from vehicle traffic, large point sources, and rail. Consistent with previous field campaigns and the conceptual model of ozone episodes in the area, trajectories from the southwest, south, and lake breeze trajectories (south or southeast) were overrepresented during pollution episodes. Local source impacts from vehicle traffic, large point sources, and rail were assessed and found to represent less than about 15% of typical concentrations measured. Implications for model-observation comparison and design of future field campaigns are discussed.Implications: The Lake Michigan Ozone Study 2017 (LMOS 2017) was conducted along the western shore of Lake Michigan, and involved two well-instrumented coastal ground sites (Zion, IL, and Sheboygan, WI). LMOS 2017 data are publicly available, and this paper provides detailed site characterization and measurement summary to enable informed use of repository data. Minor local source impacts were detected but were largely confined to nighttime conditions of less interest for ozone episode analysis and modeling. The role of these sites in the wider field campaign and their detailed description facilitates future campaign planning, informed data repository use, and model-observation comparison.

Overview of the Lake Michigan Ozone Study 2017.

The Lake Michigan Ozone Study 2017 (LMOS 2017) was a collaborative multiagency field study targeting ozone chemistry, meteorology, and air quality observations in the southern Lake Michigan area. The primary objective of LMOS 2017 was to provide measurements to improve air quality modeling of the complex meteorological and chemical environment in the region. LMOS 2017 science questions included spatiotemporal assessment of nitrogen oxides (NO x = NO + NO2) and volatile organic compounds (VOC) emission sources and their influence on ozone episodes; the role of lake breezes; contribution of new remote sensing tools such as GeoTASO, Pandora, and TEMPO to air quality management; and evaluation of photochemical grid models. The observing strategy included GeoTASO on board the NASA UC-12 aircraft capturing NO2 and formaldehyde columns, an in situ profiling aircraft, two ground-based coastal enhanced monitoring locations, continuous NO2 columns from coastal Pandora instruments, and an instrumented research vessel. Local photochemical ozone production was observed on 2 June, 9-12 June, and 14-16 June, providing insights on the processes relevant to state and federal air quality management. The LMOS 2017 aircraft mapped significant spatial and temporal variation of NO2 emissions as well as polluted layers with rapid ozone formation occurring in a shallow layer near the Lake Michigan surface. Meteorological characteristics of the lake breeze were observed in detail and measurements of ozone, NOx, nitric acid, hydrogen peroxide, VOC, oxygenated VOC (OVOC), and fine particulate matter (PM2.5) composition were conducted. This article summarizes the study design, directs readers to the campaign data repository, and presents a summary of findings.

A multiphase CMAQ version 5.0 adjoint.

We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint model provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation, and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosol dynamics and thermodynamics, cloud chemistry and dynamics, diffusion, and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with algorithmic differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or finite-difference method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the complex variable method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM and CVM. In an example application of the full multiphase adjoint model, we provide the first estimates of how emissions of particulate matter (PM2.5) affect public health across the US.

Natural gas shortages during the "coal-to-gas" transition in China have caused a large redistribution of air pollution in 2017.

The Chinese "coal-to-gas" and "coal-to-electricity" strategies aim at reducing dispersed coal consumption and related air pollution by promoting the use of clean and low-carbon fuels in northern China. Here, we show that on top of meteorological influences, the effective emission mitigation measures achieved an average decrease of fine particulate matter (PM2.5) concentrations of ∼14% in Beijing and surrounding areas (the "2+26" pilot cities) in winter 2017 compared to the same period of 2016, where the dispersed coal control measures contributed ∼60% of the total PM2.5 reductions. However, the localized air quality improvement was accompanied by a contemporaneous ∼15% upsurge of PM2.5 concentrations over large areas in southern China. We find that the pollution transfer that resulted from a shift in emissions was of a high likelihood caused by a natural gas shortage in the south due to the coal-to-gas transition in the north. The overall shortage of natural gas greatly jeopardized the air quality benefits of the coal-to-gas strategy in winter 2017 and reflects structural challenges and potential threats in China's clean-energy transition.

The impact of power generation emissions on ambient PM2.5 pollution and human health in China and India.

Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM ≤ 2.5 µm in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.

Modeling regional pollution transport events during KORUS-AQ: Progress and challenges in improving representation of land-atmosphere feedbacks.

This study evaluates the impact of assimilating soil moisture data from NASA's Soil Moisture Active Passive (SMAP) on short-term regional weather and air quality modeling in East Asia during the Korea-US Air Quality Study (KORUS-AQ) airborne campaign. SMAP data are assimilated into the Noah land surface model using an ensemble Kalman filter approach in the Land Information System framework, which is semi-coupled with the NASA-Unified Weather Research and Forecasting model with online chemistry (NUWRF-Chem). With SMAP assimilation included, water vapor and carbon monoxide (CO) transport from northern-central China transitional climate zones to South Korea is better represented in NUWRF-Chem during two studied pollution events. Influenced by different synoptic conditions and emission patterns, impact of SMAP assimilation on modeled CO in South Korea is intense (>30 ppbv) during one event and less significant (<8 ppbv) during the other. SMAP assimilation impact on air quality modeling skill is complicated by other error sources such as the chemical initial and boundary conditions (IC/LBC) and emission inputs of NUWRF-Chem. Using a satellite-observation-constrained chemical IC/LBC instead of a free-running, coarser-resolution chemical IC/LBC reduces modeled CO by up to 80 ppbv over South Korea. Consequently, CO performance is improved in the middle-upper troposphere whereas degraded in the lower troposphere. Remaining negative CO biases result largely from the emissions inputs. The advancements in land surface modeling and chemical IC/LBC presented here are expected to benefit future investigations on constraining emissions using observations, which can in turn enable more accurate assessments of SMAP assimilation and chemical IC/LBC impacts.

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique.

Estimates of Health Impacts and Radiative Forcing in Winter Haze in Eastern China through Constraints of Surface PM2.5 Predictions.

The Gridpoint Statistical Interpolation (GSI) Three-Dimensional Variational (3DVAR) data assimilation system is extended to treat the MOSAIC aerosol model in WRF-Chem, and to be capable of assimilating surface PM2.5 concentrations. The coupled GSI-WRF-Chem system is applied to reproduce aerosol levels over China during an extremely polluted winter month, January 2013. After assimilating surface PM2.5 concentrations, the correlation coefficients between observations and model results averaged over the assimilated sites are improved from 0.67 to 0.94. At nonassimilated sites, improvements (higher correlation coefficients and lower mean bias errors (MBE) and root-mean-square errors (RMSE)) are also found in PM2.5, PM10, and AOD predictions. Using the constrained aerosol fields, we estimate that the PM2.5 concentrations in January 2013 might have caused 7550 premature deaths in Jing-Jin-Ji areas, which are 2% higher than the estimates using unconstrained aerosol fields. We also estimate that the daytime monthly mean anthropogenic aerosol radiative forcing (ARF) to be -29.9W/m2 at the surface, 27.0W/m2 inside the atmosphere, and -2.9W/m2 at the top of the atmosphere. Our estimates update the previously reported overestimations along Yangtze River region and underestimations in North China. This GSI-WRF-Chem system would also be potentially useful for air quality forecasting in China.

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study.

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O3/ can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O3 source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O3 sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (<10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100% emission reduction) source contribution obtained from linearly scaling the North American mean O3 sensitivities to a 20% reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models' mean O3 sensitivities to the 20% EAS emission perturbations are ~8% (May-June 2010)/~11% (2010 annual) lower than those estimated by eight global models, and the multi-model ensemble estimates are higher than the HTAP1 reported 2001 conditions. GEOS-Chem sensitivities indicate that the EAS anthropogenic NO x emissions matter more than the other EAS O3 precursors to the North American O3, qualitatively consistent with previous adjoint sensitivity calculations. In addition to the analyses on large spatial-temporal scales relative to the HTAP1, we also show results on subcontinental and event scales that are more relevant to the US air quality management. The EAS pollution impacts are weaker during observed O3 exceedances than on all days in most US regions except over some high-terrain western US rural/remote areas. Satellite O3 (TES, JPL-IASI, and AIRS) and carbon monoxide (TES and AIRS) products, along with surface measurements and model calculations, show that during certain episodes stratospheric O3 intrusions and the transported EAS pollution influenced O3 in the western and the eastern US differently. Free-running (i.e., without chemical data assimilation) global models underpredicted the transported background O3 during these episodes, posing difficulties for STEM to accurately simulate the surface O3 and its source contribution. Although we effectively improved the modeled O3 by incorporating satellite O3 (OMI and MLS) and evaluated the quality of the HTAP2 emission inventory with the Royal Netherlands Meteorological Institute-Ozone Monitoring Instrument (KNMI-OMI) nitrogen dioxide, using observations to evaluate and improve O3 source attribution still remains to be further explored.

Reactive nitrogen chemistry in aerosol water as a source of sulfate during haze events in China.

Fine-particle pollution associated with winter haze threatens the health of more than 400 million people in the North China Plain. Sulfate is a major component of fine haze particles. Record sulfate concentrations of up to ~300 µg m-3 were observed during the January 2013 winter haze event in Beijing. State-of-the-art air quality models that rely on sulfate production mechanisms requiring photochemical oxidants cannot predict these high levels because of the weak photochemistry activity during haze events. We find that the missing source of sulfate and particulate matter can be explained by reactive nitrogen chemistry in aerosol water. The aerosol water serves as a reactor, where the alkaline aerosol components trap SO2, which is oxidized by NO2 to form sulfate, whereby high reaction rates are sustained by the high neutralizing capacity of the atmosphere in northern China. This mechanism is self-amplifying because higher aerosol mass concentration corresponds to higher aerosol water content, leading to faster sulfate production and more severe haze pollution.

"What We Breathe Impacts Our Health: Improving Understanding of the Link between Air Pollution and Health".

Air pollution contributes to the premature deaths of millions of people each year around the world, and air quality problems are growing in many developing nations. While past policy efforts have succeeded in reducing particulate matter and trace gases in North America and Europe, adverse health effects are found at even these lower levels of air pollution. Future policy actions will benefit from improved understanding of the interactions and health effects of different chemical species and source categories. Achieving this new understanding requires air pollution scientists and engineers to work increasingly closely with health scientists. In particular, research is needed to better understand the chemical and physical properties of complex air pollutant mixtures, and to use new observations provided by satellites, advanced in situ measurement techniques, and distributed micro monitoring networks, coupled with models, to better characterize air pollution exposure for epidemiological and toxicological research, and to better quantify the effects of specific source sectors and mitigation strategies.

Assessment of biomass burning smoke influence on environmental conditions for multi-year tornado outbreaks by combining aerosol-aware microphysics and fire emission constraints.

We use the WRF system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the US during spring. The model is configured with an aerosol-aware microphysics parameterization capable of resolving aerosol-cloud-radiation interactions in a cost-efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included and smoke emissions are constrained using an inverse modeling technique and satellite-based AOD observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low-level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud-level tending to burn-off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF-Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near-storm environments. This provides reliability on the aerosol-aware microphysics scheme as a less computationally expensive alternative to WRF-Chem for its use in applications such as NWP and cloud-resolving simulations.

Atmospheric dispersion of PCB from a contaminated Lake Michigan harbor.

Indiana Harbor and Ship Canal (IHSC) in East Chicago is an industrial waterway on Lake Michigan and a source of PCBs to Lake Michigan and the overlying air. We hypothesized that IHSC is an important source of airborne PCBs to surrounding communities. We used AERMOD to model hourly PCB concentrations, utilizing emission fluxes from a prior study and hourly meteorology provided by the State of Indiana. We also assessed dispersion using hourly observed meteorology from a local airport and high resolution profiles simulated by the Weather Research and Forecasting model. We found that emissions from IHSC waters contributed about 15% of the observed ΣPCB concentrations close to IHSC when compared on an hourly basis and about 10% of observed annual concentrations at a nearby school. Concentrations at the school due to emissions from IHSC ranged from 0 to 18,000 pg m-3, up to 20 times higher than observed background levels, with an annual geometric mean (GSD) of 19 (31) pg m-3. Our findings indicate that IHSC is an important source of PCBs to East Chicago, but not the only source. Four observed enriched PCB3 samples suggest a nearby non-Aroclor source.

Differences between magnitudes and health impacts of BC emissions across the United States using 12 km scale seasonal source apportionment.

Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, which provides source-receptor relationships at highly resolved sectoral, spatial, and temporal scales. While damage resulting from anthropogenic emissions of BC is strongly correlated with population and premature death, we found little correlation between damage and emission magnitude, suggesting that controls on the largest emissions may not be the most efficient means of reducing damage resulting from anthropogenic BC emissions. Rather, the best proxy for locations with damaging BC emissions is locations where premature deaths occur. Onroad diesel and nonroad vehicle emissions are the largest contributors to premature deaths attributed to exposure to BC, while onroad gasoline emissions cause the highest deaths per amount emitted. Emissions in fall and winter contribute to more premature deaths (and more per amount emitted) than emissions in spring and summer. Overall, these results show the value of the high-resolution source attribution for determining the locations, seasons, and sectors for which BC emission controls have the most effective health benefits.

Light absorption properties and radiative effects of primary organic aerosol emissions.

Organic aerosols (OAs) in the atmosphere affect Earth's energy budget by not only scattering but also absorbing solar radiation due to the presence of the so-called "brown carbon" (BrC) component. However, the absorptivities of OAs are not represented or are poorly represented in current climate and chemical transport models. In this study, we provide a method to constrain the BrC absorptivity at the emission inventory level using recent laboratory and field observations. We review available measurements of the light-absorbing primary OA (POA), and quantify the wavelength-dependent imaginary refractive indices (kOA, the fundamental optical parameter determining the particle's absorptivity) and their uncertainties for the bulk POA emitted from biomass/biofuel, lignite, propane, and oil combustion sources. In particular, we parametrize the kOA of biomass/biofuel combustion sources as a function of the black carbon (BC)-to-OA ratio, indicating that the absorptive properties of POA depend strongly on burning conditions. The derived fuel-type-based kOA profiles are incorporated into a global carbonaceous aerosol emission inventory, and the integrated kOA values of sectoral and total POA emissions are presented. Results of a simple radiative transfer model show that the POA absorptivity warms the atmosphere significantly and leads to ∼27% reduction in the amount of the net global average POA cooling compared to results from the nonabsorbing assumption.

Health impacts and economic losses assessment of the 2013 severe haze event in Beijing area.

Haze is a serious air pollution problem in China, especially in Beijing and surrounding areas, affecting visibility, public health and regional climate. In this study, the Weather Research and Forecasting-Chemistry (WRF-Chem) model was used to simulate PM2.5 (particulate matters with aerodynamic diameter≤2.5 µm) concentrations during the 2013 severe haze event in Beijing, and health impacts and health-related economic losses were calculated based on model results. Compared with surface monitoring data, the model results reflected pollution concentrations accurately (correlation coefficients between simulated and measured PM2.5 were 0.7, 0.4, 0.5 and 0.6 in Beijing, Tianjin, Xianghe and Xinglong stations, respectively). Health impacts assessments show that the PM2.5 concentrations in January might cause 690 (95% confidence interval (CI): (490, 890)) premature deaths, 45,350 (95% CI: (21,640, 57,860)) acute bronchitis and 23,720 (95% CI: (17,090, 29,710)) asthma cases in Beijing area. Results of the economic losses assessments suggest that the haze in January 2013 might lead to 253.8 (95% CI: (170.2, 331.2)) million US$ losses, accounting for 0.08% (95% CI: (0.05%, 0.1%)) of the total 2013 annual gross domestic product (GDP) of Beijing.

Simulating and explaining passive air sampling rates for semivolatile compounds on polyurethane foam passive samplers.

Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semivolatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semivolatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations, simulates nonlinear PUF uptake, and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, IL, during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds and confirming quasilinear uptake. Results indicate hourly, daily, and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify the importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding that PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%).