Local Air Research Articles

The Tula Industrial Area Field Experiment: Quantitative Measurements of Formaldehyde, Sulfur Dioxide, and Nitrogen Dioxide Emissions Using Mobile Differential Optical Absorption Spectroscopy Instruments

The Tula industrial area in Central Mexico comprises, among other industries, a refinery and a thermoelectric power plant. It is well known for its constant emissions of gases into the atmosphere and considered an important area where pollutants released into the atmosphere have an influence on local and regional air quality. During March and April 2017, a field campaign was conducted with the objective of quantifying formaldehyde (HCHO), sulfur dioxide (SO2), and nitrogen dioxide (NO2) emissions from this industrial area using mobile differential optical absorption spectroscopy (DOAS) instruments. Calculated average emissions of the Francisco Perez Rios Power Plant and the Miguel Hidalgo Refinery were 3.14 ± 2.13 tons per day of HCHO, 362.08 ± 300.14 tons per day of SO2, and 24.76 ± 12.82 tons per day of NO2. From the measurements conducted, the spatial distribution patterns of SO2, NO2, and HCHO were reconstructed, showing a dispersion pattern of SO2 and NO2 towards the southwest of the industrial complex, impacting agricultural and urban areas. Occasionally, and usually during the morning hours, SO2 and NO2 were dispersed towards the north or northeast of the industrial complex. In the case of HCHO, dispersion was observed towards the south and southeast of the industrial complex. The far-reaching implications of this study are that for the first time, formaldehyde emissions were quantified. In addition, a follow-up study was conducted regarding nitrogen dioxide and sulfur dioxide emissions from the Tula Industrial area.

Can the infection risk in elevators be negligible? A comparative study of airborne infection probability in elevators and conference rooms

People in crowded and poorly ventilated elevators are at risk of respiratory infection. However, due to the short duration of the elevator ride, the transmission of respiratory diseases in elevators does not get enough attention. To evaluate the infection risk, this study investigated the airborne transmission of respiratory diseases in the hospital elevator by comparison to the conference room. A validated computational fluid dynamics (CFD) model was adopted to simulate airflow, temperature and tracer gas dispersion in the elevator and conference room. We used Wells-Riley model to evaluate the infection probability of the susceptible persons. In addition, the influences of source patient posture and ventilation strategy on the transmission of tracer gas were analyzed. The results showed that the infection probability in the elevator with 5 min (average 2.70%) was higher than that in the conference room with 50 min (average 1.77%). The effects of source patient posture and ventilation strategy on the infection probability in the elevator were more significant than those in the conference room. Local air circulation could gather the tracer gas inside a confined space in the elevator and led to a high infection probability. The infection risk of respiratory diseases in the elevator was non-negligible.

Characteristics of Ozone Photochemical Reaction and Emission Reduction Strategies in Summer and Autumn in Shangqiu

Recently, ozone （O3） pollution in Shangqiu has become increasingly prominent, especially in summer and autumn, crucially affecting the local environmental air quality. Based on the monitoring data of O3 pollution days from the Environmental Monitoring Station in June and September 2022 （representing summer and autumn） in Shangqiu, an observation-based model （OBM） was used to study the causes and photochemical reaction characteristics of O3 pollution in the city and precursor emission reduction strategies were studied. The observation results indicated that during summer in Shangqiu, the ρ（O3） and O3 daily maximum 8 h moving concentrations [ρ（MDA8-O3）] were 149.7 μg·m-3 and 195.4 μg·m-3, whereas in autumn, ρ（O3） and ρ（MDA8-O3） were 119.8 μg·m-3 and 173.9 μg·m-3, respectively； the O3 concentration in summer was significantly higher than that in autumn. Ozone sensitivity research showed that the generation of O3 in summer and autumn in Shangqiu was controlled by volatile organic compounds （VOCs）. Among them, oxygen-containing volatile organic compounds （OVOCs）, aromatic hydrocarbons, and alkenes contributed the most to the ozone generation potential （OFP） and ·OH reactivity （L·OH）, and the control must have been strengthened. The OBM simulation results indicated that the maximum O3 generation rates in summer and autumn were 23.0×10-9 h-1 and 13.6×10-9 h-1, with maximum net generation rates of 17.4×10-9 h-1 and 10.4×10-9 h-1 and the maximum and maximum net generation rates of O3 in summer were 1.68 times higher than those in autumn, indicating that the photochemical reactions in summer were significantly stronger than those in autumn. Compared with that in summer, the generation of O3 in autumn was greatly influenced by regional inputs from other regions or cities, with a maximum input of 14.2×10-9 h-1. The prevention and control of O3 pollution in the summer and autumn seasons in Shangqiu should mainly focus on controlling VOCs. The reduction ratio of VOCs/nitrogen oxides （NOx） in autumn should be greater than that in summer and the reduction ratios of 3∶1 in summer and 4∶1 in autumn could be adopted for control.

Burning fields, fading memories: exploring the effects of sugarcane burning on air quality and cognitive functioning – A case study in Northeast Thailand

This study assessed the relationship between PM2.5 concentration and the working memory of sugarcane farmers (n = 444) in Khon Kaen Province, one of the largest sugarcane producers in the Northeast region of Thailand. The relationship between the ambient PM2.5 concentrations and the working memory of sugarcane farmers was evaluated using two working memory outcomes. These outcomes included a working memory difficulty score derived from self-report of difficulty in daily tasks that require working memory and an objective memory test score consisting of a set of number recall exercises. The PM2.5 concentration data in this study were obtained from air quality monitoring stations located in the vicinity of the study locations, ensuring both precision and relevance to local air conditions. The regression results showed that farmers in the low-burn farming zone had less difficulty with working memory and better performance on number recall exercises, compared to farmers in the high-burn farming zones, even after controlling for health and socio-economic factors. Our findings highlight the potential impacts of PM2.5 exposure on the cognitive functions of farmers who burn sugarcane residues in Thailand. Our study supports the need for the government of Thailand or health agencies to establish an effective policy to reduce sugarcane residue burning in Thailand.

A Radar-Based Methodology for Aerosol Plume Identification and Characterisation on the South African Highveld

Biomass burning on the South African Highveld annually injects substantial amounts of aerosols and trace gases into the atmosphere, impacting the global radiative balance, cloud microphysics, and regional air quality. These aerosols are transported as plumes over long distances, posing challenges to existing in situ and satellite-based monitoring techniques because of their limited spatial and temporal resolution, particularly in environments with low-level sources. This study aims to develop and validate a novel radar-based methodology to detect, track, and characterise aerosol plumes, addressing the limitations of existing in situ and satellite monitoring techniques. Using high-resolution volumetric reflectivity data from an S-band radar in Pretoria, South Africa, a traditional storm tracking algorithm is adapted to improve plume identification. Case studies of plume events in June and August 2013 demonstrate the radar’s effectiveness in distinguishing lower vertical profiles and reduced reflectivity of plumes compared with storm echoes. The adapted algorithm successfully tracked the spatial and temporal evolution of the plumes, revealing their short-lived nature. Results indicate that radar-derived geospatial characteristics have the potential to contribute significantly to understanding the impacts of plumes on local air quality. These findings underscore the critical need for high spatio-temporal resolution data to support effective air quality management and inform policy development in regions affected by biomass burning.

Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements

Abstract. In this study, we demonstrate the utility of available correlative measurements of carbon species to identify regional and local air mass characteristics as well as their associated source types. In particular, we combine different regression techniques and enhancement ratio algorithms with carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) total column abundance from 11 sites of the Total Carbon Column Observing Network (TCCON) to infer relative contributions of regional and local sources to each of these sites. The enhancement ratios provide a viable alternative to univariate measures of relationships between the trace gases that are insufficient in capturing source-type and transport signatures. Regional enhancements are estimated from the difference between bivariate regressions across a specific time window of observed total abundance of these species (BERr for bulk enhancement regression ratio) and inferred anomalies (AERr for anomaly enhancement regression ratio) associated with a site-specific background. Since BERr and AERr represent the bulk and local species enhancement ratio, respectively, its difference simply represents the site-specific regional component of these ratios. We can then compare these enhancements for CO2 and CH4 with CO to differentiate between combustion and non-combustion air masses. Our results show that while the regional and local influences in enhancements vary across sites, dominant characteristics are found to be consistent with previous studies over these sites and with bottom-up anthropogenic and fire emission inventories. The site in Pasadena shows a dominant local influence (> 60 %) across all species enhancement ratios, which appear to come from a mixture of biospheric and combustion activities. In contrast, Anmyeondo shows more regionally influenced (> 60 %) air masses associated with high-temperature and/or biofuel combustion activities. Ascension Island appears to only show a large regional influence (> 80 %) on CO / CO2 and CO / CH4, which is indicative of transported and combustion-related CO from the nearby African region, consistent with a sharp rise in column CO (3.51 ± 0.43 % ppb yr−1) at this site. These methods have important applications to source analysis using spaceborne column retrievals of these species.

Achieving deep transport energy demand reductions in the United Kingdom

The transport sector is a crucial yet challenging area to decarbonize, given its heavy reliance on fossil fuel usage, carbon-intensive infrastructure and car-centric lifestyles. It remains the largest contributor to local air pollution in cities yet has the potential to improve people's physical and mental health. This research investigated the potential contribution of transport energy demand reduction to climate change mitigation and improving public health. Using a comprehensive bottom-up modelling framework, the Transport Energy and Air pollution Model (TEAM), this study provides an integrated assessment of the impacts of deep mobility-related energy demand reductions, including lifecycle carbon emissions, local air pollution and health impacts. Using a sociotechnical scenario approach and the UK as a case study, this research reveals that energy demand reductions of up to 61 % by 2050 compared to baseline levels are achievable and can enhance citizens' quality of life. Business as usual approaches which rely on a technical transition miss the legislated carbon budgets and result in higher energy demand in 2050. More comprehensive scenarios deliver a reduction of up to 72 % in total lifecycle carbon emissions by 2050, with approximately half of the reduction achieved through mode shifting and avoiding travel, while the other half comes from vehicle energy efficiency, electrification, and downsizing of the vehicle fleets. The research shows that it can lead to significant co-benefits such as improved local air pollution and public health. The feasibility and practicality of policy measures and integrated strategies identified for achieving deep transport-energy demand reductions are discussed.

A moderator of tropical impacts on climate in Canadian Arctic Archipelago during boreal summer

The Canadian Arctic Archipelago consists of important international trade routes, and local surface air temperatures (SAT) greatly control sea ice melting in situ during boreal summer (June-July-August-September). However, the drivers of the Arctic Archipelago summer SAT variability have not yet been fully elucidated. Here, we find that the impact of tropical Indo-Pacific convection on the Arctic Archipelago SAT through induced poleward-propagating Rossby wave train is strongly modulated by Russian Arctic sea surface temperature anomalies (SSTA). Negative Russian Arctic SSTA lead to a weakened East Asia westerly jet via equatorward Rossby wave activity. The weakened westerly jet enhances the meridional gradient of the potential vorticity over the North Pacific, guiding the poleward-propagating Rossby wave to the Arctic Archipelago and therefore affecting the local SAT. Conversely, positive Russian Arctic SSTA impede the northward-propagating Rossby wave via enhancing the East Asia westerly jet, resulting in a weakened relationship between the tropical Indo-Pacific convection and Arctic Archipelago SAT. The present study proposes a mechanism whereby changes in the Tropical-Arctic connection stem from thermal conditions elsewhere in the Arctic, through shaping poleward-propagating Rossby waves by changing the background mean flow.

Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment

Currently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements. It was found that regional sources of pollution were mostly responsible for the PM2.5 and PM1 concentrations. In contrast, PM10 was mostly associated with local sources. The total particle number and the lung deposited surface area of PM were almost solely associated with traffic, while black carbon was associated with both the sources from the urban background and local traffic. Our analysis showed that while the effect of the hyperlocal sources, such as emissions from construction works or traffic, do not exceed the distance of a couple of hundred meters, they can influence the health of thousands of people in densely populated areas. Thus, using this novel approach we illustrate the limitations of the present measurement network paradigm and offer an alternative and versatile approach to understanding the hyperlocal factors that affect urban air quality. Mobile monitoring by citizen scientists is shown to have huge potential to enhance spatiotemporal resolution of air quality data without the need of extensive and expensive campaigns.

Effect of horizontal cartridges on the uniformity of flow field distribution inside a cartridge filter

Cartridge filters are widely utilized in industrial dust removal due to their advantages of high dust removal efficiency, compact size relative to bag filters, and the capacity to reuse collected dust. However, the conventional upright installation of the cartridges' front row directly faces the air inlet, which is directly impacted by the high-velocity dirt airflow and is often broken. This setup also disrupts airflow distribution, leading to uneven mass flow distribution and localized high velocity. To address these challenges, this study proposes horizontally installing the cartridges, by utilizing the bottom cone to buffer the airflow. This not only resolves issues of localized cartridge breakage but also promotes uniform airflow distribution, thereby prolonging filter service life. Computational Fluid Dynamics (CFD) is employed to simulate the changes in the flow field within the physical model, using finite element iterative calculations. This approach reduces experimental costs while providing precise data. Therefore, numerical simulation is used to verify the effectiveness of horizontal cartridges in improving the uniformity of the flow field distribution in the cartridge filter. The results showed that the horizontal cartridge filter improved the mass flow distribution uniformity by 54.9%, the peak velocity difference was reduced by 69.63%, and the maximum velocity was reduced by 68.42% compared to the upright cartridge filter. Horizontal cartridges have a more uniform flow field distribution, effectively avoiding problems such as abrasion and rupture of the filter media caused by excessive local air velocity.

Investigating the efficacy of a fast urban climate model for spatial planning of green and blue spaces for heat mitigation

Problems caused by urban heat have prompted the exploration of urban greenery and blue spaces for heat mitigation. Various numerical models can simulate heat-related processes, but their use as support-tools to urban planners remains underexplored, particularly at the city-scale, due to high computational demand and complexity of such models. This study investigates the spatial relationships between urban heat, urban form and urban green and blue spaces with the fast climate model TARGET (The Air-temperature Response to Green/blue-infrastructure Evaluation Tool), which only requires minimal inputs of standard meteorological data, land cover and building geometry data. Using the City of Zurich as our case study, we: (i) validated the TARGET model against air temperature measurements from private sensor networks, (ii) performed a sensitivity analysis to identify key variables affecting urban heat, and (iii) investigated urban heat relationships with blue-green cover at locations frequented by pedestrians. Presence of urban green and blue spaces across the region shows potential for reducing local air temperatures by up to 5.2 °C (with urban forest). Investigating this relationship at different locations in the city revealed key districts that should potentially be targeted for reduction of pedestrian heat-impacts, due to their high pedestrian traffic, fewer green and blue spaces and high daytime air temperatures. Our results not only provide insights into the cooling effect of different amounts of green and blue features in the urban environment, but also demonstrates the application and integration potential of simplified models like TARGET to support the planning of more liveable future cities.

Comprehensive numerical and experimental analysis the impact of employing vortex generators on evaporative cooling process

Reduced energy usage is an important concern in vapor compression cooling systems, particularly in hot climates. These systems function poorly in hot weather and consume a lot of electricity. Evaporative condensers use the cooling impact of evaporation to facilitate the process of heat rejection and thereby increase energy efficiency. This work evaluates the impact of employing vortex generators on the performance of an evaporative condenser. The analysis is performed using a validated numerical model, a commercial CFD code. The proposed vortex generators are parallel plates with sinusoidal and zigzag patterns. Dry air enters a channel equipped with four vortex-generating plates and water spray. The incoming dry air cools due to the two-phase heat transfer during air contact with the sprayed water droplets, and the cooled air with the proper humidity level exits the channel. The investigated parameters include longitudinal nozzle position, inlet air flow rate, pitch, and the height of the vortex generator plates in two sinusoidal and zigzag modes and the obtained results are compared with the plain channel model. Greater inlet air velocity resulted in superior output temperatures and pressure drops, yet lower outlet relative humidity and water mass percentage. According to the findings, the air pressure drop and outlet dry temperature are raised by 152 % and 5 %, respectively, when the incoming air velocity is altered from 0.4 to 0.6 m. s−1 (50 % growth), and the nozzle position is moved from X = 1.35 m to X = 1.85 m (37.04 % change) from the channel entrance, while the relative humidity and water mass fraction are decreased by 19 % and 11 %, respectively. Additional research revealed that the vortex flow level is lower when the nozzle is positioned farther away from the plates, and the water spray's impact on lowering the local air temperature in vortex-flowing areas is more substantial when it is positioned closer to the plates. Furthermore, increasing wave height and pitch values of vortex generators result in a more extensive air pressure drop in the channel, and vice versa. This means that, at a fixed pitch, a higher plate wave height raises the amount of vortex flows. According to the findings, sinusoidal vortex plates have better efficiency than the zigzag ones, and in a channel equipped with water spray, the use of vortex plates before the water spray nozzles lowers the dry temperature at the outlet by about one °C compared to that of the plain channel.

Air–Sea Coupling Feedbacks over Tropical Instability Waves

Abstract Tropical instability waves (TIWs) are oceanic features that form around the equatorial Pacific cold tongue and influence the large-scale circulation and coupled climate variability including El Niño–Southern Oscillation. Local air–sea coupling over TIWs is thought to play an important role in the atmosphere and ocean’s energy and tracer budgets but is not well captured in coarse-resolution models. In this study, we isolate the impacts of TIW thermal (sea surface temperature–driven) and current (surface current–driven) feedbacks by removing TIW signatures in air–sea coupling fields in a high-resolution regional coupled model. The thermal feedback is found to damp TIW temperature variance by a factor of 2, associated both with the direct dependence of surface heat fluxes on SST (∼74%) and indirect impacts on surface winds (∼35%) and air temperature and humidity (∼−9%). These changes lead to cooling of the cold tongue SST by up to 0.1°C through reduced TIW-driven meridional heat fluxes and associated small changes in atmospheric circulation. The current feedback is decomposed into TIW (i.e., mesoscale) and mean (i.e., large-scale) components using separate experiments, with both having distinct impacts on TIWs and the mean state. The mesoscale current feedback reduces TIW eddy kinetic energy (EKE) by 22% through the eddy wind work, while the mean current feedback induces a further reduction of 8% by extracting energy from the mean currents and thus reducing barotropic EKE shear production. An improved understanding of small-scale tropical Pacific processes is needed to address biases in coarse-resolution models that impact their predictions and projections of Pacific climate variability and change. Significance Statement Tropical instability waves (TIWs) are oceanic features with ∼1000-km wavelengths that propagate westward on either side of the eastern equatorial Pacific cold tongue. TIWs drive lateral and vertical heat fluxes that impact several aspects of El Niño–Southern Oscillation. While climate models with a moderate, 1/4° ocean resolution can capture some TIW variability, they fail to properly represent many associated processes such as the impact of TIWs on the overlying atmosphere. Using sensitivity studies performed using a high-resolution regional coupled model, we study the impact of TIW air–sea coupling on the eastern Pacific climate system. Increased understanding of small-scale processes from studies such as this is essential to understand and address biases in models used for seasonal climate predictions and projections in the Pacific region.

Machine learning-based surrogate models for fast impact assessment of a new building on urban local microclimate at design stage

The rapid urbanization introduces changes in the local urban microclimate. Many efforts have been paid on the impact assessment of building design on local microclimate. However, there is still a lack of efficient and accurate prediction method for assessing the impacts on local microclimate when making the design of individual buildings. Two complementary machine learning-based surrogate models are proposed, including an SVR-based local air temperature model and a LightGBM-based local wind velocity model. They are identified by evaluating and comparing eight alternative machine learning models, four for each model development. 200 sets of CFD simulation data corresponding to different building designs are used for the model training and validation. The results show that the developed surrogate models can dramatically reduce computation time (from over 5 h to less than a second for a single prediction) while keeping the same order of accuracy of CFD simulations for local microclimate prediction of individual buildings. It therefore facilitates the fast, comprehensive and accurate prediction of the impacts on the local microclimate at the early design stage of new construction and renovation of individual buildings, for designers to deliver preferred local microclimate and/or avoid unacceptable microclimate changes.

Accounting for plume rise of aircraft emissions and shoreline meteorology enhances AERMOD’s description of concentrations measured around Los Angeles airport

ABSTRACT The Aviation Environmental Design Tool (AEDT), developed by the FAA, is used to analyze the environmental impact of airport activities on air quality and noise near airports. AEDT incorporates AERMOD to estimate concentrations resulting from aircraft emissions, which possess horizontal momentum as well as buoyancy. The current version (v23132) of AERMOD incorporates plume dynamics associated with such emissions as an ALPHA option. AERMET, AERMOD’s meteorological processor does not account for the meteorology of the land-water interface that is likely to be important for airports located on the shorelines of lakes or oceans. An approach to include these effects in AERMOD was previously developed. This study examines the impact of including plume rise and shoreline effects in AERMOD by evaluating model estimates of NOX and SO2 with corresponding measurements made during the Los Angeles Airport Air Quality Source Apportionment Study (AQSAS) in the winter and summer of 2012. The performance statistics resulting from this model evaluation suggest that the inclusion of plume rise of aircraft emissions and shoreline effects on meteorological inputs is likely to improve AERMOD’s ability to estimate the impact of airport emissions on surrounding air quality. Implications: Because airport emissions, particularly those from aircraft, affect local air quality, the National Environmental Policy Act (NEPA) requires the use of dispersion models such as AERMOD to assess compliance of air quality regulations when potential expansions of airport activity are planned. The current regulatory version of AERMOD does not include aircraft-specific plume rise and shoreline-related meteorological processes, which affect the dispersion of airport emissions. The preliminary evidences presented in our previous work suggest that the incorporation of these effects will enhance AERMOD’s ability to estimate NOX and SO2 concentrations associated with airport emissions. These enhancements are beneficial not only for policy-making and regulatory compliance but also for promoting sustainable development near airports and protecting public health.

Aerosol composition, air quality, and boundary layer dynamics in the urban background of Stuttgart in winter

Abstract. Aerosol distributions are of great relevance for air quality, especially for cities like Stuttgart, which has limited air exchange due to its location in a basin. We collected a comprehensive set of data from remote sensing and in situ methods including radiosondes for the urban background of downtown Stuttgart to determine the impact of boundary layer mixing processes on local air quality and to evaluate the simulation results of the high-resolution large eddy simulation (LES) model PALM-4U at 10 m grid spacing. Stagnant meteorological conditions caused accumulation of aerosols, and chemical composition analysis shows that ammonium nitrate (37 ± 9 %) and organic aerosol (OA; 34 ± 9 %) dominated during this winter study. Case studies show that clouds during previous nights can weaken temperature inversion and accelerate boundary layer mixing after sunrise by up to 3 h. This is important for ground-level aerosol dilution during the morning rush hour. Furthermore, our observations validate results of the LES model PALM-4U in terms of boundary layer heights and aerosol mixing for 48 h. The simulated aerosol concentrations follow the trend of our observations but are still underestimated by a factor of 4.5 ± 2.1 due to missing secondary aerosol formation processes and uncertainties of emissions and boundary conditions in the model. This paper firstly evaluates the PALM-4U model performance in simulating aerosol spatio-temporal distributions, which can help to improve the LES model and to better understand sources and sinks for air pollution as well as the role of horizontal and vertical transport.

Well-planned greenery improves air urban quality - Modelling the effect of altered airflow and pollutant deposition

Urban air quality is influenced by vegetation through alterations in airflow and pollutant deposition processes. We investigated these interactions by integrating the Vegetation Impact Dynamic Assessment model (VIDA) with the Large-Eddy Simulation model PALM. Our analysis focus on nitrogen dioxide (NO₂) and particulate matter (PM) concentrations at the local scale, considering three tree genera. Our findings reveal the necessity of accounting for both gaseous pollutants and particles separately due to their differing mechanisms of deposition onto leaves. The coupled PALM-VIDA model demonstrates a significant reduction in PM levels across the modelling domain and within street canyons when deposition to vegetation is incorporated. Reduction in NO₂ through deposition to vegetation is lower but human NO2 exposure can still be decreased if tree species selection and placement leads to desirable effects on air flow. Sparse tree arrangements or species with sparse crowns facilitate ventilation and are often better at reducing NO₂ concentrations in street canyons compared to denser vegetation with higher deposition but negative effects on ventilation. Our study informs urban planning and green infrastructure design, underscoring the multifaceted role of urban greenery in air pollution mitigation strategies. Its main conclusion is that both deposition processes and the influence of air mixing and ventilation need to be considered to accurately assess the effects of urban trees on local air quality. Ill-considered placement and species selection may cause a net increase in pollutants underneath the trees. However, careful planning can address this risk and instead improve overall air quality.

Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community.

The Community Multiscale Air Quality Model (CMAQ) is a local- to hemispheric-scale numerical air quality modeling system developed by the U.S. Environmental Protection Agency (USEPA) and supported by the Community Modeling and Analysis System (CMAS) center. CMAQ is used for regulatory purposes by the USEPA program offices and state and local air agencies and is also widely used by the broader global research community to simulate and understand complex air quality processes and for computational environmental fate and transport and climate and health impact studies. Leveraging state-of-the-science cloud computing resources for high-performance computing (HPC) applications, CMAQ is now available as a fully tested, publicly available technology stack (HPC cluster and software stack) for two major cloud service providers (CSPs). Specifically, CMAQ configurations and supporting materials have been developed for use on their HPC clusters, including extensive online documentation, tutorials and guidelines to scale and optimize air quality simulations using their services. These resources allow modelers to rapidly bring together CMAQ, cloud-hosted datasets, and visualization and evaluation tools on ephemeral clusters that can be deployed quickly and reliably worldwide. Described here are considerations in CMAQ version 5.3.3 cloud use and the supported resources for each CSP, presented through a benchmark application suite that was developed as an example of a typical simulation for testing and verifying components of the modeling system. The outcomes of this effort are to provide findings from performing CMAQ simulations on the cloud using popular vendor-provided resources, to enable the user community to adapt this for their own needs, and to identify specific areas of potential optimization with respect to storage and compute architectures.

Seasonal variation and origins of C1–C5 alkyl nitrates: A year-long study at a Hong Kong coastal site

Alkyl nitrates (RONO₂) are key reactive nitrogen compounds with significant impacts on local and regional air quality. The concentrations of alkyl nitrates can vary significantly across different regions, especially in areas with varying levels of human activity. Long-term observation of alkyl nitrates is necessary to assess the intensity of photochemical reactions and the contributions from different sources. In this study, we present the first continuous year-long monitoring results of eight alkyl nitrates via whole air sample collection and GC-MSD/ECD analysis at a coastal site in Hong Kong. Source apportionment analysis via positive matrix factorization (PMF) revealed distinctive seasonal variations in the source contributions for the eight alkyl nitrate species. Furthermore, increased contributions from biomass combustion were found in autumn and winter, while marine emissions primarily influenced methyl nitrate levels during summer. Our study highlights the significant impact of biomass burning from inland areas on photochemical pollutants in Hong Kong. Cross-regional cooperation in the Greater Bay Area (GBA) is necessary for more comprehensive management of secondary photochemical pollution.

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.