Paola Crippa

The supplement contains additional analyses and plots in support to the main findings in the paper. The code for this work is available at the following GitHub repository: github.com/Env-an-Stat-group/24.Zhang.AoAS.

We present a new ensemble of 36 numerical experiments aimed at comprehensively gauging the sensitivity of nested Large Eddy Simulations (LES) driven by large scale dynamics. Specifically, we explore 36 multiscale configurations of the Weather Research and Forecasting (WRF) model to simulate the boundary layer flow over the complex topography at the Perdigão field site, with five nested domains discretized at horizontal resolutions ranging from 11.25 kilometers to 30 meters. Each ensemble member has a unique combination of the following input factors, (i) large-scale initial and boundary conditions, (ii) subgrid turbulence modeling in the gray zone of turbulence, (iii) subgrid-scale (SGS) models in LES simulations and (iv) topography and land cover datasets. We probe their relative importance for LES calculations of velocity, temperature and moisture fields. Variance …

Coupling Large Eddy Simulations (LES) with Numerical Weather Prediction (NWP) models has promising applications for wind energy. Regional climatology, optimal siting of wind turbines as well as short term wind energy forecasts can be improved by considering all the energetic scales of atmospheric motions. However, the complexity of NWP-LES coupled simulations introduces challenges and uncertainties that need to be addressed. This study focuses on understanding the relative importance of different factors and assumptions in NWP-LES calculations for wind energy applications. Using a recent large ensemble of LES simulations driven by NWP boundary conditions over the complex terrain of the Perdigão area, our analysis reveals significant discrepancies in wind power estimates across ensemble members, particularly over hilltops. Depending on the model configuration and the coupling technique …

Recent studies have highlighted the importance of accurate meteorological conditions for urban transport and dispersion calculations. In this work, we present a novel scheme to compute the meteorological input in the Quick Urban & Industrial Complex (QUIC) diagnostic urban wind solver to improve the characterization of upstream wind veer and shear in the Atmospheric Boundary Layer (ABL). The new formulation is based on a coupled set of Ordinary Differential Equations (ODEs) derived from the Reynolds Averaged Navier–Stokes (RANS) equations, and is fast to compute. Building upon recent progress in modeling the idealized ABL, we include effects from surface roughness, turbulent stress, Coriolis force, buoyancy and baroclinicity. We verify the performance of the new scheme with canonical Large Eddy Simulation (LES) tests with the GPU-accelerated FastEddy solver in neutral, stable, unstable and …

Toxic air pollution is arguably the most pressing human health concern today, accounting for approximately 7–9 million premature deaths worldwide. In the United States, more than 200,000 early deaths are attributable to air pollution and almost half of these are estimated to result from emissions originating in neighboring states–ie, transboundary air pollution. Yet more than 40% of these deaths are assessed to be cause by air pollution produced by neighboring states. This article examines the governance mechanisms used by the US to address this transboundary issue, with a focus on section 126 of the Clean Air Act. All section 126 petitions submitted from 2000–2022 (N= 13), critical factors including case length, evidence used, and case outcome are compiled and assessed using comparative case analysis. From this analysis, four main issues and corresponding recommendations to enhance US governance mechanisms related to section 126 are developed: the need for policy and procedural reforms to adjust the burden of proof on petitioning states the need for clarity on the criteria for sufficient evidence for petitioners; potential practical measures to address challenges with response timelines in petitioning process; and the means by which section 126 petitioning capacity can be made accessible to all states. The article concludes with a discussion on the significance of modeling techniques employed in the petitioning process by the US EPA and states to facilitate informed–and fair–decision-making processes.

Ambient air pollution is an increasing threat to society, with rising numbers of adverse outcomes and exposure inequalities worldwide. Reducing uncertainty in health outcomes models and exposure disparity studies is therefore essential to develop policies effective in protecting the most affected places and populations. This study uses the concept of information entropy to study tradeoffs in mortality uncertainty reduction from increasing input data of air pollution versus health outcomes. We study a case scenario for short‐term mortality from particulate matter (PM2.5) in North Carolina for 2001–2016, employing a case‐crossover design with inputs from an individual‐level mortality data set and high‐resolution gridded data sets of PM2.5 and weather covariates. We find a significant association between mortality and PM2.5, and the information tradeoffs indicate that a 10% increase in mortality information reduces …

Implementing effective policy to protect human health from the adverse effects of air pollution, such as premature mortality, requires reducing the uncertainty in health outcomes models. Here we present a novel method to reduce mortality uncertainty by increasing the amount of input data of air pollution and health outcomes, and then quantifying tradeoffs associated with the different data gained. We first present a study of long-term mortality from fine particulate matter (PM2.5) based on simulated data, followed by a real-world application of short-term PM2.5-related mortality in an urban area. We employ information yield curves to identify which variables more effectively reduce mortality uncertainty when increasing information. Our methodology can be used to explore how specific pollution scenarios will impact mortality and thus improve decision-making. The proposed framework is general and can be applied to …

Modeling atmospheric turbulence in the convective boundary layer is challenging at kilometer and subkilometer resolutions, as the horizontal grid spacing approaches the size of the most energetic turbulent eddies. In this range of resolutions, termed terra incognita or gray zone , partially resolved convective structures are grid dependent and neither traditional 1D mesoscale parameterizations nor 3D large-eddy simulations closures are theoretically appropriate. Leveraging on a new set of one-way nested, full-physics multiscale numerical experiments, we quantify the magnitude of the errors introduced at gray zone resolutions in a real-case application and we provide new perspectives on recently proposed modeling approaches. The new set of experiments is forced by real-time-varying boundary conditions, spans a wide range of scales, and includes traditional 1D schemes …

Implementing effective policy to protect human health from the adverse effects of air pollution, such as premature mortality, requires reducing the uncertainty in health outcomes models. Here we present a novel method to reduce mortality uncertainty by increasing the amount of input data of air pollution and health outcomes, and then quantifying tradeoffs associated with the different data gained. We apply this method to a real case scenario for short-term mortality from fine particulate matter (PM2. 5) in North Carolina, employing commonly used epidemiology models that combine several sources of air pollution data with individual-level health outcome data. We fit our epidemiological models several times with varying amounts of health and/or pollution data and employ information yield curves to identify which variables more effectively reduce mortality uncertainty when increasing information. In addition to effective …

The authors found some errors in Figs. 11-14. The figures did not show the Taiwan and South China Sea Islands. The authors would like to apologise for any inconvenience caused.

Improved characterization of the spatiotemporal extent, intensity, and causes of extreme aerosol optical depth events is critical to quantifying their regional climate forcing and the link to near‐surface air quality. An analysis of regional‐scale extreme aerosol events over the eastern United States is undertaken using output from the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA‐2) reanalysis and observations from the MODerate resolution Imaging Spectroradiometers (MODIS). Six extreme aerosol optical depth (AOD) events during 2003–2007, dominated by anthropogenic emissions and characterized by a regional scale extent, are identified and simulated using the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) applied at 12 km resolution. Statistical analyses show output from WRF‐Chem during these events is generally negatively biased …

A document providing additional technical details and supplementary details.

The representation of air quality and meteorology over Asia remains challenging for chemical transport models as a result of the complex interactions between the East Asian monsoons and the large uncertainty (in space and time) of the high anthropogenic emissions levels over the region. High spatial resolution models allow resolving small-scale features induced by the complex topography of this region. In this study, the Weather Research and Forecasting model with Chemistry (WRF-Chem) was used to simulate the spatial and seasonal variability of main physical and chemical variables over Asia for the year 2015 at 8-km horizontal resolution to enable resolving small-scale features induced by the region complex topography. The simulated atmospheric composition was evaluated against satellite retrievals (MOPITT, IASI + GOME2, MODIS and OMI) in addition to ground-based observations in China for the …

Assessment of exposure and mortality attributable to air pollution is one of the most important tasks to inform strategies for mitigation and prevention of the negative effects of degraded air quality. While the vast majority of studies rely on either satellite data or sparse (and expensive) monitoring networks and focus on global- or regional-scale assessments, emerging low-cost citizen science networks are a new source of information that can be used to provide more detailed estimates at urban scale, thereby refining previous estimates and providing spatially resolved information at census tract resolution. In this work, we demonstrate how a citizen science network, validated with a reference air pollution station, provides sensibly different (and spatially resolved) estimates of air pollution levels and associated exposure/mortality than assuming constant air pollution across the analyzed urban area. Specifically we focus …

Accurate wind speed estimates at turbine hub height are critical for wind farm operational purposes, such as forecasting and grid operation, but also for wind energy assessments at regional scales. Power law models have widely been used for vertical wind speed profiles due to their simplicity and suitability for many applications over diverse geographic regions. The power law requires estimation of a wind shear coefficient, α, linking the surface wind speed to winds at higher altitudes. Prior studies have mostly adopted simplified models for α, ranging from a single constant, to a site-specific constant in time value. In this work we (i) develop a new model for α which is able to capture hourly variability across a range of geographic/topographic features; (ii) quantify its improved skill compared to prior studies; and (iii) demonstrate implications for wind energy estimates over a large geographical area. To achieve this we …

Atmospheric pollution of particulate matter (PM) is a major concern for its deleterious effects on human health and climate. Over the past 50 years, Equatorial Asia has experienced significant land-use change and urbanization, which have contributed to more intense and frequent extreme PM concentrations associated with increased anthropogenic and wildfire emissions. Recent advances in remote sensing instrumentation and retrieval protocols have enabled effective monitoring of PM from space in near real time with almost global coverage. In this study, long-term satellite-based observations of key chemical and physical parameters, integrated with ground-based concentrations of PM with aerodynamic diameter< 10 μm (PM 10) measured at 52 stations, are used to develop a machine learning approach for continuous PM 10 monitoring. As PM atmospheric pollution, like most of environmental processes, is …

BackgroundExposure to poor air quality leads to increased premature mortality from cardiovascular and respiratory diseases. Among the far-reaching implications of the ongoing COVID-19 pandemic, a substantial improvement in air quality was observed worldwide after the lockdowns imposed by many countries. We aimed to assess the implications of different lockdown measures on air pollution levels in Europe and China, as well as the short-term and long-term health impact.MethodsFor this modelling study, observations of fine particulate matter (PM2·5) concentrations from more than 2500 stations in Europe and China during 2016–20 were integrated with chemical transport model simulations to reconstruct PM2·5 fields at high spatiotemporal resolution. The health benefits, expressed as short-term and long-term avoided mortality from PM2·5 exposure associated with the interventions imposed to control the …

Policymakers worldwide have set challenging sustainable energy targets to decarbonize their economy. Despite the ambitious pledges, several emerging countries still lack an actual progress towards the envisioned goals, often due to the scarcity of accurate data. Here, we propose a practical methodology for bridging the gap between the wind energy targets and their implementation. We illustrate our new methodology by focusing on Saudi Arabia, which endeavors to play a leading role in the renewable energy sector and pledges to install 16GW of wind capacity by 2030. We propose a blueprint for the optimal wind farms buildout, combining novel high-resolution model simulations, a unique set of observations, land-use restrictions and a thorough cost assessment. The most suitable technological option is selected among multiple turbine models for each potential site. Our findings suggest that Saudi Arabia is …

Equatorial Asia experiences frequent degraded air quality conditions, as a result of the complex interaction between the abundant air pollution sources and the local/regional meteorological patterns, which ultimately impact densely populated cities. Due to the scarcity of extensive observational datasets, both observational and modeling studies have been rather limited in their spatio-temporal extent and/or the certainty of their estimates. This study presents a country-wide, multi-decadal analysis of PM10 observations (i.e. particulate matter with aerodynamic diameter < 10 μm) from a network in Malaysia comprising 52 monitoring sites, which allows a novel and comprehensive assessment of the spatio-temporal variability of the country's air quality. Through statistical analyses and adoption of a parsimonious statistical model, we investigate the influence of urban and wildfire emissions, as well as of key …

Atmospheric pollution from fine particulate matter (PM 2.5) is one of the major concerns in China because of its widespread and harmful impacts on human health. In recent years, multiple studies have sought to estimate the premature mortality burden from exposure to PM 2.5 to inform policy decisions. However, different modeling choices have led to a wide array of results, with significant discrepancies both in the total mortality burden and in the confidence intervals. Here, we present a new comprehensive assessment of PM 2.5-related mortality for China, which includes quantification of the main sources of variability, as well as of age and province-specific premature mortality trends during 2015–2018. Our approach integrates PM 2.5 observations from more than 1600 monitoring stations with the output of a high-resolution (8 km) regional simulation, to accurately estimate PM 2.5 fields along with their uncertainty …