Estimation of on-road NO2 concentrations, NO2/NOX ratios, and related roadway gradients from near-road monitoring data

Integrating traffic pollution dispersion into spatiotemporal NO2 prediction

Accurately predicting ambient NO2 concentrations has great public health importance, as traffic-related air pollution is of major concern in urban areas. In this study, we present a novel approach incorporating traffic contribution to NO2 prediction in a fine-scale spatiotemporal model. We used nationally available traffic estimate dataset in a scalable dispersion model, Research LINE source dispersion model (RLINE). RLINE estimates then served as an additional input for a validated spatiotemporal pollution modeling approach. Our analysis uses measurement data collected by the Multi-Ethnic Study of Atherosclerosis and Air Pollution in the greater Los Angeles area between 2006 and 2009. We predicted road-type-specific annual average daily traffic (AADT) on road segments via national-level spatial regression models with nearest-neighbor Gaussian processes (spNNGP); the spNNGP models were trained based on over half a million point-level traffic volume measurements nationwide. AADT estimates on all highways were combined with meteorological data in RLINE models. We evaluated two strategies to integrate RLINE estimates into spatiotemporal NO2 models: 1) incorporating RLINE estimates as a space-only covariate and, 2) as a spatiotemporal covariate. The results showed that integrating the RLINE estimates as a space-only covariate improved overall cross-validation R2 from 0.83 to 0.84, and root mean squared error (RMSE) from 3.58 to 3.48 ppb. Incorporating the estimates as a spatiotemporal covariate resulted in similar model improvement. The improvement of our spatiotemporal model was more profound in roadside monitors alongside highways, with R2 increasing from 0.56 to 0.66 and RMSE decreasing from 3.52 to 3.11 ppb. The observed improvement indicates that the RLINE estimates enhanced the model's predictive capabilities for roadside NO2 concentration gradients even after considering a comprehensive list of geographic covariates including the distance to roads. Our proposed modeling framework can be generalized to improve high-resolution prediction of NO2 exposure - especially near major roads in the U.S.

Interannual evolution of the chemical composition, sources and processes of PM2.5 in Chengdu, China: Insights from observations in four winters

The air quality in China has improved significantly in the last decade and, correspondingly, the characteristics of PM2.5 have also changed. We studied the interannual variation of PM2.5 in Chengdu, one of the most heavily polluted megacities in southwest China, during the most polluted season (winter). Our results show that the mass concentrations of PM2.5 decreased significantly year-by-year, from 195.8 ± 91.0 µg/m3 in winter 2016 to 96.1 ± 39.3 µg/m3 in winter 2020. The mass concentrations of organic matter (OM), SO42-, NH4+ and NO3- decreased by 49.6%, 57.1%, 49.7% and 28.7%, respectively. The differential reduction in the concentrations of chemical components increased the contributions from secondary organic carbon and NO3- and there was a larger contribution from mobile sources. The contribution of OM and NO3- not only increased with increasing levels of pollution, but also increased year-by-year at the same level of pollution. Four sources of PM2.5 were identified: combustion sources, vehicular emissions, dust and secondary aerosols. Secondary aerosols made the highest contribution and increased year-by-year, from 40.6% in winter 2016 to 46.3% in winter 2020. By contrast, the contribution from combustion sources decreased from 14.4% to 8.7%. Our results show the effectiveness of earlier pollution reduction policies and emphasizes that priority should be given to key pollutants (e.g., OM and NO3-) and sources (secondary aerosols and vehicular emissions) in future policies for the reduction of pollution in Chengdu during the winter months.

Distinct urban-rural gradients of air NO2 and SO2 concentrations in response to emission reductions during 2015-2022 in Beijing, China

Nitrogen dioxide (NO2) and sulfur dioxide (SO2) are two major air pollutants in urban environment. Emission reduction policies have thus been implemented to improve urban air quality, especially in the metropolises. However, it remains unclear whether the air concentrations of NO2 and SO2 in and around large cities follow a same spatial pattern and how their characteristics change over time in response to the emission reductions. Using ground-based monitoring datasets of air NO2 and SO2 concentrations in Beijing, China, we tested the hypothesis of urban air pollutant islands and evaluated their seasonal and inter-annual variations during 2015-2022. The results showed that air NO2 concentrations increased significantly towards the urban core, being in line with the hypothesis of urban air pollutant island, while air SO2 concentrations showed no such spatial patterns. The urban air NO2 island varied seasonally, with larger radius and higher air NO2 concentrations in spring and winter. In response to the emission reduction, the annual mean radius of the urban air NO2 island showed a rapid decrease from 45.8 km to zero km during the study period. The annual mean air NO2 concentration at the urban core showed a linear decrease at a rate of 4.5 μg m-3 yr-1. In contrast, air SO2 concentration decreased nonlinearly over time and showed a legacy in comparison to the emission reduction. Our findings suggest different urban-rural gradients of air NO2 and SO2 concentrations and highlight their distinct responses to the regional reductions of anthropogenic emissions.

Integrating large-scale stationary and local mobile measurements to estimate hyperlocal long-term air pollution using transfer learning methods

Mobile air quality measurements are collected typically for several seconds per road segment and in specific timeslots (e.g., working hours). These short-term and on-road characteristics of mobile measurements become the ubiquitous shortcomings of applying land use regression (LUR) models to estimate long-term concentrations at residential addresses. This issue was previously found to be mitigated by transferring LUR models to the long-term residential domain using routine long-term measurements in the studied region as the transfer target (local scale). However, long-term measurements are generally sparse in individual cities. For this scenario, we propose an alternative by taking long-term measurements collected over a larger geographical area (global scale) as the transfer target and local mobile measurements as the source (Global2Local model). We empirically tested national, airshed countries (i.e., national plus neighboring countries) and Europe as the global scale in developing Global2Local models to map nitrogen dioxide (NO₂) concentrations in Amsterdam. The airshed countries scale provided the lowest absolute errors, and the Europe-wide scale had the highest R². Compared to a "global" LUR model (trained exclusively with European-wide long-term measurements), and a local mobile LUR model (using mobile data from Amsterdam only), the Global2Local model significantly reduced the absolute error of the local mobile LUR model (root-mean-square error, 6.9 vs 12.6 μg/m³) and improved the percentage explained variances compared to the global model (R², 0.43 vs 0.28, assessed by independent long-term NO₂ measurements in Amsterdam, n = 90). The Global2Local method improves the generalizability of mobile measurements in mapping long-term residential concentrations with a fine spatial resolution, which is preferred in environmental epidemiological studies.

A critical review and prospect of NO2 and SO2 pollution over Asia: Hotspots, trends, and sources

Nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) are two major atmospheric pollutants that significantly threaten human health, the environment, and ecosystems worldwide. Despite this, only some studies have investigated the spatiotemporal hotspots of NO₂ and SO₂, their trends, production, and sources in Asia. Our study presents a literature review covering the production, trends, and sources of NO₂ and SO₂ across Asian countries (e.g., Bangladesh, China, India, Iran, Japan, Pakistan, Malaysia, Kuwait, and Nepal). Based on the findings of the review, NO₂ and SO₂ pollution are increasing due to industrial activity, fossil fuel burning, biomass burning, heavy traffic movement, electricity generation, and power plants. There is significant concern about health risks associated with NO₂ and SO₂ emissions in Bangladesh, China, India, Malaysia, and Iran, as they pay less attention to managing and controlling pollution. Even though the lack of quality datasets and adequate research in most Asian countries further complicates the management and control of NO₂ and SO₂ pollution. This study has NO₂ and SO₂ pollution scenarios, including hotspots, trends, sources, and their influences on Asian countries. This study highlights the existing research gaps and recommends new research on identifying integrated sources, their variations, spatiotemporal trends, emission characteristics, and pollution level. Finally, the present study suggests a framework for controlling and monitoring these two pollutants' emissions.

Model predicting social acceptance behavior to implement ELV policy: Exploring the role of knowledge toward ELV policy on social acceptance in Malaysia

Effective management of end-of-life vehicles (ELVs) represents a sound strategy to mitigate global climate change. ELVs are contaminants that pollute water, air, soil, and landscape. This waste flow must be adequately treated, but no proper rule oversees the disposal of ELV waste in Malaysia. This study aims to determine the extent of implementing the ELV policy and the social readiness in implementing environmentally friendly ELV disposal in Malaysia. The questionnaire seeks public input on critical ELV concerns such as public perception of the phenomena, environmental and safety standards, and recycling and treatment facilities. This research uses a cross-sectional design with 448 respondents in the survey. Fit models in structural equation modeling are evaluated using a variety of goodness-of-fit indicators to ensure an actual hypothesis. This study's advantages include the availability of representative samples and allowing for comparable and generalizable conclusions to larger communities throughout Malaysia. It is found that personal experience is significantly correlated with social readiness. The cause of ELV vehicles knowledge was the vital mediator, along with recycling costs knowledge. Thus, knowledge regarding ELV management costs is the most decisive mediation variable to predict public acceptance. The recommended strategy to reduce resentment and rejection of ELV policy is to disseminate information about the negative ELV impact on environmental and social sustainability.

Multi-air pollution risk assessment in Southeast Asia region using integrated remote sensing and socio-economic data products

Air pollution has massive impacts on human life and poor air quality results in three million deaths annually. Air pollution can result from natural causes, including volcanic eruptions and extreme droughts, or human activities, including motor vehicle emissions, industry, and the burning of farmland and forests. Emission sources emit multiple pollutant types with diverse characteristics and impacts. However, there has been little research on the risk of multiple air pollutants; thus, it is difficult to identify multi-pollutant mitigation processes, particularly in Southeast Asia, where air pollution moves dynamically across national borders. In this study, the main objective was to develop a multi-air pollution risk index product for CO, NO2, and SO2 based on Sentinel-5P remote sensing data from 2019 to 2020. The risk index was developed by integrating hazard, vulnerability, and exposure analyses. Hazard analysis considers air pollution data from remote sensing, vulnerability analysis considers the air pollution sources, and exposure analysis considers the population density. The novelty of this study lies in its development of a multi-risk model that considers the weights obtained from the relationship between the hazard and vulnerability parameters. The highest air pollution risk index values were observed in urban areas, with a high exposure index that originates from pollution caused by human activity. Multi-risk analysis of the three air pollutants revealed that Singapore, Vietnam, and the Philippines had the largest percentages of high-risk areas, while Indonesia had the largest total high-risk area (4361 km2). Using the findings of this study, the patterns and characteristics of the risk distribution of multiple air pollutants in Southeast Asia can be identified, which can be used to mitigate multi-pollutant sources, particularly with respect to supporting the clean air targets in the Sustainable Development Goals.

Photocatalytic-treated asphalt road in Copenhagen for urban NO x removal

Atmospheric nitrogen oxides ( NO x = NO + NO 2 ) are key pollutants and short-lived climate forcers contributing to acid rain, photochemical smog, aerosol formation and climate change. Exposure to nitrogen dioxide ( NO 2 ) emitted mainly from transportation, causes adverse health effects associated with respiratory illnesses and increased mortality even at low concentration. Application of titanium dioxide ( TiO 2 )-based photocatalysis in urban environment is a new air cleaning solution, activated by sunlight and water vapour to produce OH radicals, able to remove NO x and other pollutants from the planetary boundary layer. This study is a large-scale evaluation of NO x removal efficiency at a near-road environment with applied photocatalytic NOxOFF™ technology on an urban road west of Copenhagen, thus supporting local municipality in meeting their clean-air Agenda 2030. The photocatalytic NOxOFF™ granulate containing TiO 2 nanoparticles was applied on an asphalt road in July 2020 and ambient NO x was measured during a six-month monitoring campaign. It is the first NO x monitoring campaign carried out at this road and specific efforts have been devoted to evaluate the reduction in ambient NO x levels with NOxOFF™-treated asphalt. Several methods were used to evaluate the photocatalytic effect, taking into account analysis limitations such as the short reference period prior to application and the highly uncertain measurement period during which SARS-CoV-2 lockdown measures impacted air quality. There was no statistically significant difference in NO x concentrations between the reference period and the photocatalytic active period and NO removal efficiency resulted in - 0.17 (± 1.27). An upper limit removal of 17.5% NO x was estimated using a kinetic tunnel model. While NO 2 comparison with COPERT V street traffic model projection was roughly estimated to decrease by 39% (± 38%), although this estimate is subject to high uncertainty. The observed annual mean NO 2 concentration complies with Frederiksberg clean-air Agenda 2030 and air quality standards.

GRAPHICAL ABSTRACT

A graphical abstract illustrating the air cleaning properties of TiO 2 -based photocatalytic-treated asphalt.

Hyperlocal variation of nitrogen dioxide, black carbon, and ultrafine particles measured with Google Street View cars in Amsterdam and Copenhagen

Hyperlocal air quality maps are becoming increasingly common, as they provide useful insights into the spatial variation and sources of air pollutants. In this study, we produced several high-resolution concentration maps to assess the spatial differences of three traffic-related pollutants, Nitrogen dioxide (NO₂), Black Carbon (BC) and Ultrafine Particles (UFP), in Amsterdam, the Netherlands, and Copenhagen, Denmark. All maps were based on a mixed-effect model approach by using state-of-the-art mobile measurements conducted by Google Street View (GSV) cars, during October 2018 - March 2020, and Land-use Regression (LUR) models based on several land-use and traffic predictor variables. We then explored the concentration ratio between the different normalised pollutants to understand possible contributing sources to the observed hyperlocal variations. The maps developed in this work reflect, (i) expected elevated pollution concentrations along busy roads, and (ii) similar concentration patterns on specific road types, e.g., motorways, for both cities. In the ratio maps, we observed a clear pattern of elevated concentrations of UFP near the airport in both cities, compared to BC and NO₂. This is the first study to produce hyperlocal maps for BC and UFP using high-quality mobile measurements. These maps are important for policymakers and health-effect studies, trying to disentangle individual effects of key air pollutants of interest (e.g., UFP).

Characterization of winter air pollutant gradients near a major highway

Traffic-related air pollutants (TRAP) including nitric oxide (NO), nitrogen oxide (NO_x), carbon monoxide (CO), ultrafine particles (UFP), black carbon (BC), and fine particulate matter (PM_2.5) were simultaneously measured at near-road sites located at 10 m (NR10) and 150 m (NR150) from the same side of a busy highway to provide insights into the influence of winter time meteorology on exposure to TRAP near major roads. The spatial variabilities of TRAP were examined for ambient temperatures ranging from -11 °C to +19 °C under downwind, upwind, and stagnant air conditions. The downwind TRAP concentrations at NR10 were higher than the upwind concentrations by a factor of 1.4 for CO to 13 for NO. Despite steep downwind reductions of 38 % to 75 % within 150 m, the downwind concentrations at NR150 were still well above upwind concentrations. Near-road concentrations of NO_x and UFP increased as ambient temperatures decreased due to elevated emissions of NO_x and UFP from vehicles under colder temperatures. Traffic-related PM_2.5 sources were identified using hourly PM_2.5 chemical components including organic/inorganic aerosol and trace metals at both sites. The downwind concentrations of primary PM_2.5 species related to tailpipe and non-tailpipe emissions at NR10 were substantially higher than the upwind concentrations by a factor of 4 and 32, respectively. Traffic-related PM_2.5 sources accounted for almost half of total PM_2.5 mass under downwind conditions, leading to a rapid change of PM_2.5 chemical composition. Under stagnant air conditions, the concentrations of most TRAP and related PM_2.5 including tailpipe emissions, secondary nitrate, and organic aerosol were comparable to, or even greater than, the downwind concentrations under windy conditions, especially at NR150. This study demonstrates that stagnant air conditions further widen the traffic-influenced area and people living near major roadways may experience increased risks from elevated exposure to traffic emissions during cold and stagnant winter conditions.

REDUCING THE POLLUTION OF THE AIRSPACE OF THE CITY'S MAIN HIGHWAY AREAS

The article deals with problems of air pollution in large cities and how to solve them. In Europe, road transport produces nearly half of NOx emissions, which ensures urban air quality. Analysis of reference data has revealed scientists' active interest in reducing air pollution in large cities. However, since the objects of territorial planning continue to develop dangerously, one can speak of the absence of a sufficiently compelling concept of architectural and urban planning to ensure the environmental safety of the air basin of urban areas. Therefore, we propose to consider the object of the research and protection as systemic integrity of three entities: areas near trunk roads, air basins, and population. The paper presents an ER model of the research object and determines the main parameters of each entity, their interrelationships, and the action area. We propose an engineering and planning solution for installing special units to remove the most dangerous admixtures of nitrogen oxides and dust from the air basin near the city trunk roads through ozonation and absorption. The basis of the proposed treatment plant is a scrubber with combined processes of wet dust collection and ozonation characterized by high efficiency in removing fine dust and nitrogen oxides. The work presents a process flow diagram of purification and determines the operating conditions of the equipment. To substantiate the unit's operational safety in an emergency with ozone emission, we have simulated the process of ozone dispersion in the surrounding areas.

Characterizing Determinants of Near-Road Ambient Air Quality for an Urban Intersection and a Freeway Site

INTRODUCTION

Near-road ambient air pollution concentrations that are affected by vehicle emissions are typically characterized by substantial spatial variability with respect to distance from the roadway and temporal variability based on the time of day, day of week, and season. The goal of this work is to identify variables that explain either temporal or spatial variability based on case studies for a freeway site and an urban intersection site. The key hypothesis is that dispersion modeling of near-road pollutant concentrations could be improved by adding estimates or indices for site-specific explanatory variables, particularly related to traffic. Based on case studies for a freeway site and an urban intersection site, the specific aims of this project are to (1) develop and test regression models that explain variability in traffic-related air pollutant (TRAP) ambient concentration at two near-roadway locations; (2) develop and test refined proxies for land use, traffic, emissions and dispersion; and (3) prioritize inputs according to their ability to explain variability in ambient concentrations to help focus efforts for future data collection and model development.

The key pollutants that are the key focus of this work include nitrogen oxides (NOx), carbon monoxide (CO), black carbon (BC), fine particulate matter (PM2.5; PM ≤ 2.5 μm in aerodynamic diameter), ultrafine particles (UFPs; PM ≤ 0.1 μm in aerodynamic diameter), and ozone (O3). NOx, CO, and BC are tracers of vehicle emissions and dispersion. PM2.5 is influenced by vehicle table emissions and regional sources. UFPs are sensitive to primary vehicle emissions. Secondary particles can form near roadways and on regional scales, influencing both PM2.5 and UFP concentrations. O3 concentrations are influenced by interaction with NOx near the roadway. Nitrogen dioxide (NO2), CO, PM2.5, and O3 are regulated under the National Ambient Air Quality Standards (NAAQS) because of demonstrated health effects. BC and UFPs are of concern for their potential health effects. Therefore, these pollutants are the focus of this work.

METHODS

The methodological approach includes case studies for which variables are identified and assesses their ability to explain either temporal or spatial variability in pollutant ambient concentrations. The case studies include one freeway location and one urban intersection. The case studies address (1) temporal variability at a fixed monitor 10 meters from a freeway; (2) downwind concentrations perpendicular to the same location; (3) variability in 24-hour average pollutant concentrations at five sites near an urban intersection; and (4) spatiotemporal variability along a walking path near that same intersection.

The study boundary encompasses key factors in the continuum from vehicle emissions to near-road exposure concentrations. These factors include land use, transportation infrastructure and traffic control, vehicle mix, vehicle (traffic) flow, on-road emissions, meteorology, transport and evolution (transformation) of primary emissions, and production of secondary pollutants, and their resulting impact on measured concentrations in the near-road environment. We conducted field measurements of land use, traffic, vehicle emissions, and near-road ambient concentrations in the vicinity of two newly installed fixed-site monitors. One is a monitoring station jointly operated by the U.S. Environmental Protection Agency (U.S. EPA) and the North Carolina Department of Environmental Quality (NC DEQ) on I-40 between Airport Boulevard and I-540 in Wake County, North Carolina. The other is a fixed-site monitor for measuring PM2.5 at the North Carolina Central University (NCCU) campus on E. Lawson Street in Durham, North Carolina. We refer to these two locations as the freeway site and the urban site, respectively. We developed statistical models for the freeway and urban sites.

RESULTS

We quantified land use metrics at each site, such as distances to the nearest bus stop. For the freeway site, we quantified lane-by-lane total vehicle count, heavy vehicle (HV) count, and several vehicle-activity indices that account for distance from each lane to the roadside monitor. For the urban site, we quantified vehicle counts for all 12 turning movements through the intersection. At each site, we measured microscale vehicle tailpipe emissions using a portable emission measurement system.

At the freeway site, we measured the spatial gradient of NOx, BC, UFPs, and PM, quantified particle size distributions at selected distances from the roadway and assessed partitioning of particles as a function of evolving volatility. We also quantified fleet-average emission factors for several pollutants.

At the urban site, we measured daily average concentrations of nitric oxide (NO), NOx, O3, and PM2.5 at five sites surrounding the intersection of interest; we also measured high resolution (1-second to 10-second averages) concentrations of O3, PM2.5, and UFPs along a pedestrian transect. At both sites, the Research LINE-source (R-LINE) dispersion model was applied to predict concentration gradients based on the physical dispersion of pollution.

Statistical models were developed for each site for selected pollutants. With variables for local wind direction, heavy-vehicle index, temperature, and day type, the multiple coefficient of determination (R2) was 0.61 for hourly NOx concentrations at the freeway site. An interaction effect of the dispersion model and a real-time traffic index contributed only 24% of the response variance for NOx at the freeway site. Local wind direction, measured near the road, was typically more important than wind direction measured some distance away, and vehicle-activity metrics directly related to actual real-time traffic were important. At the urban site, variability in pollutant concentrations measured for a pedestrian walk-along route was explained primarily by real-time traffic metrics, meteorology, time of day, season, and real-world vehicle tailpipe emissions, depending on the pollutant. The regression models explained most of the variance in measured concentrations for BC, PM, UFPs, NO, and NOx at the freeway site and for UFPs and O3 at the urban site pedestrian transect.

CONCLUSIONS

Among the set of candidate explanatory variables, typically only a few were needed to explain most of the variability in observed ambient concentrations. At the freeway site, the concentration gradients perpendicular to the road were influenced by dilution, season, time of day, and whether the pollutant underwent chemical or physical transformations. The explanatory variables that were useful in explaining temporal variability in measured ambient concentrations, as well as spatial variability at the urban site, were typically localized real-time traffic-volume indices and local wind direction. However, the specific set of useful explanatory variables was site, context (e.g., next to road, quadrants around an intersection, pedestrian transects), and pollutant specific. Among the most novel of the indicators, variability in real-time measured tailpipe exhaust emissions was found to help explain variability in pedestrian transect UFP concentrations. UFP particle counts were very sensitive to real-time traffic indicators at both the freeway and urban sites. Localized site-specific data on traffic and meteorology contributed to explaining variability in ambient concentrations. HV traffic influenced near-road air quality at the freeway site more so than at the urban site. The statistical models typically explained most of the observed variability but were relatively simple. The results here are site-specific and not generalizable, but they are illustrative that near-road air quality can be highly sensitive to localized real-time indicators of traffic and meteorology.

Mixed-Effects Modeling Framework for Amsterdam and Copenhagen for Outdoor NO2 Concentrations Using Measurements Sampled with Google Street View Cars

High-resolution air quality (AQ) maps based on street-by-street measurements have become possible through large-scale mobile measurement campaigns. Such campaigns have produced data-only maps and have been used to produce empirical models [i.e., land use regression (LUR) models]. Assuming that all road segments are measured, we developed a mixed model framework that predicts concentrations by an LUR model, while allowing road segments to deviate from the LUR prediction based on between-segment variation as a random effect. We used Google Street View cars, equipped with high-quality AQ instruments, and measured the concentration of NO₂ on every street in Amsterdam (n = 46.664) and Copenhagen (n = 28.499) on average seven times over the course of 9 and 16 months, respectively. We compared the data-only mapping, LUR, and mixed model estimates with measurements from passive samplers (n = 82) and predictions from dispersion models in the same time window as mobile monitoring. In Amsterdam, mixed model estimates correlated r_s (Spearman correlation) = 0.85 with external measurements, whereas the data-only approach and LUR model estimates correlated r_s = 0.74 and 0.75, respectively. Mixed model estimates also correlated higher r_s = 0.65 with the deterministic model predictions compared to the data-only (r_s = 0.50) and LUR model (r_s = 0.61). In Copenhagen, mixed model estimates correlated r_s = 0.51 with external model predictions compared to r_s = 0.45 and r_s = 0.50 for data-only and LUR model, respectively. Correlation increased for 97 locations (r_s = 0.65) with more detailed traffic information. This means that the mixed model approach is able to combine the strength of data-only mapping (to show hyperlocal variation) and LUR models by shrinking uncertain concentrations toward the model output.

Anthropogenic air pollutants reduce insect-mediated pollination services

Common air pollutants, such as nitrogen oxides (NO_x), emitted in diesel exhaust, and ozone (O₃), have been implicated in the decline of pollinating insects. Reductionist laboratory assays, focused upon interactions between a narrow range of flowering plant and pollinator species, in combination with atmospheric chemistry models, indicate that such pollutants can chemically alter floral odors, disrupting the cues that foraging insects use to find and pollinate flowers. However, odor environments in nature are highly complex and pollination services are commonly provided by suites of insect species, each exhibiting different sensitivities to different floral odors. Therefore, the potential impacts of pollution-induced foraging disruption on both insect ecology, and the pollination services that insects provide, are currently unknown. We conducted in-situ field studies to investigate whether such pollutants could reduce pollinator foraging and as a result the pollination ecosystem service that those insects provide. Using free-air fumigation, we show that elevating diesel exhaust and O₃, individually and in combination, to levels lower than is considered safe under current air quality standards, significantly reduced counts of locally-occurring wild and managed insect pollinators by 62-70% and their flower visits by 83-90%. These reductions were driven by changes in specific pollinator groups, including bees, flies, moths and butterflies, and coincided with significant reductions (14-31%) in three different metrics of pollination and yield of a self-fertile test plant. Quantifying such effects provides new insights into the impacts of human-induced air pollution on the natural ecosystem services upon which we depend.

Air quality and photochemical reactions: analysis of NOx and NO2 concentrations in the urban area of Turin, Italy

In this work, based on the existing studies on photochemical reactions in the lower atmosphere, an analysis of the historical series of NO_x, NO₂, and O₃ concentrations measured in the period 2015-2019 by two monitoring stations located in the urban area of Turin, Italy, was elaborated. The objective was to investigate the concentration trends of the contaminants and evaluate possible simplified relationships based on the observed values. Concentration trends of these pollutants were compared in different time bands (diurnal or seasonal cycles), highlighting some differences in the dispersion of the validated data. Calculated [NO₂]/[NO_x] ratios were in agreement with the values observed in other urban areas worldwide. The influence of temperature on the [NO₂]/[NO_x] ratio was investigated. An increase of [NO₂]/[NO_x] concentration ratio was found with increasing temperature. Finally, a set of empirical relationships for the preliminary determination of NO₂ concentration values as a function of the NO_x was elaborated and compared with existing formulations. Polynomial functions were adapted to the average concentration values returned by the division into classes of 10 μg/m³ of NO_x. The choice of an empirical function to estimate the trend of NO₂ concentrations is potentially useful for the preliminary data analysis, especially in case of data scarcity. The scatter plots showed differences between the two monitoring stations, which may be attributable to a different urban context in which the stations are located. The dissonance between a purely residential context (Rubino station) and another characterised by the co-presence of residential buildings and industries of various kinds (Lingotto station) leads to the need to consider a greater contribution to the calculation of the concentrations emitted in an industrial/residential context due to a greater presence of industrial chimneys but also to more intense motorised vehicle transport. The analysis of the ratio between nitrogen oxides and tropospheric ozone confirmed that, as O₃ concentration increases, there is a consequent reduction of NO_x concentration, due to the chemical reactions of the photo-stationary cycle that takes place between the two species. This work highlighted that the use of an empirical formulation for the estimation of [NO_x] to [NO₂] conversion rate could in principle be adopted. However, the application of empirical models for the preliminary estimation of [NO_x] conversion to [NO₂] cannot replace advanced models and should be, in principle, restricted to a limited area and a limited range of NO_x concentrations.

Nitrogen oxides (NO and NO2) pollution in the Accra metropolis: Spatiotemporal patterns and the role of meteorology

Economic and urban development in sub-Saharan Africa (SSA) may be shifting the dominant air pollution sources in cities from biomass to road traffic. Considered as a marker for traffic-related air pollution in cities, we conducted a city-wide measurement of NO_x levels in the Accra Metropolis and examined their spatiotemporal patterns in relation to land use and meteorological factors. Between April 2019 to June 2020, we collected weekly integrated NO_x (n = 428) and NO₂ (n = 472) samples at 10 fixed (year-long) and 124 rotating (week-long) sites. Data from the same time of year were compared to a previous study (2006) to assess changes in NO₂ concentrations. NO and NO₂ concentrations were highest in commercial/business/industrial (66 and 76 μg/m³, respectively) and high-density residential areas (47 and 59 μg/m³, respectively), compared with peri-urban locations. We observed annual means of 68 and 70 μg/m³ for NO and NO₂, and a clear seasonal variation, with the mean NO₂ of 63 μg/m³ (non-Harmattan) increased by 25-56% to 87 μg/m³ (Harmattan) across different site types. The NO₂/NO_x ratio was also elevated by 19-28%. Both NO and NO₂ levels were associated with indicators of road traffic emissions (e.g. distance to major roads), but not with community biomass use (e.g. wood and charcoal). We found strong correlations between both NO₂ and NO₂/NO_x and mixing layer depth, incident solar radiation and water vapor mixing ratio. These findings represent an increase of 25-180% when compared to a small study conducted in two high-density residential neighborhoods in Accra in 2006. Road traffic may be replacing community biomass use (major source of fine particulate matter) as the prominent source of air pollution in Accra, with policy implication for growing cities in SSA.

Controllable synthesis of a nanoparticle-modified thin-layer 3D flower-like CuZnAl-LDHs material with high NO2 gas sensing performance at room temperature

Three-dimensional flower-like CuZnAl-LDHs attached to nanoparticles were prepared by a one-step hydrothermal method with a detection limit of 30 ppb for NO2.

Development and Validation of a Sub-National, Satellite-Based Land-Use Regression Model for Annual Nitrogen Dioxide Concentrations in North-Western China

Existing national- or continental-scale models of nitrogen dioxide (NO₂) exposure have a limited capacity to capture subnational spatial variability in sparsely-populated parts of the world where NO₂ sources may vary. To test and validate our approach, we developed a land-use regression (LUR) model for NO₂ for Ningxia Hui Autonomous Region (NHAR) and surrounding areas, a small rural province in north-western China. Using hourly NO₂ measurements from 105 continuous monitoring sites in 2019, a supervised, forward addition, linear regression approach was adopted to develop the model, assessing 270 potential predictor variables, including tropospheric NO₂, optically measured by the Aura satellite. The final model was cross-validated (5-fold cross validation), and its historical performance (back to 2014) assessed using 41 independent monitoring sites not used for model development. The final model captured 63% of annual NO₂ in NHAR (RMSE: 6 ppb (21% of the mean of all monitoring sites)) and contiguous parts of Inner Mongolia, Gansu, and Shaanxi Provinces. Cross-validation and independent evaluation against historical data yielded adjusted R² values that were 1% and 10% lower than the model development values, respectively, with comparable RMSE. The findings suggest that a parsimonious, satellite-based LUR model is robust and can be used to capture spatial contrasts in annual NO₂ in the relatively sparsely-populated areas in NHAR and neighbouring provinces.

Stable isotopic characterization of nitrate wet deposition in the tropical urban atmosphere of Costa Rica

Increasing energy consumption and food production worldwide results in anthropogenic emissions of reactive nitrogen into the atmosphere. To date, however, little information is available on tropical urban environments where inorganic nitrogen is vastly transported and deposited through precipitation on terrestrial and aquatic ecosystems. To fill this gap, we present compositions of water stable isotopes in precipitation and atmospheric nitrate (δ¹⁸O-H₂O, δ²H-H₂O, δ¹⁵N-NO₃^-, and δ¹⁸O-NO₃^-) collected daily between August 2018 and November 2019 in a tropical urban atmosphere of central Costa Rica. Rainfall generation processes (convective and stratiform rainfall fractions) were identified using stable isotopes in precipitation coupled with air mass back trajectory analysis. A Bayesian isotope mixing model using δ¹⁵N-NO₃^- compositions and corrected for potential ¹⁵N fractionation effects revealed the contribution of lightning (25.9 ± 7.1%), biomass burning (21.8 ± 6.6%), gasoline (19.1 ± 6.4%), diesel (18.4 ± 6.0%), and soil biogenic emissions (15.0 ± 2.6%) to nitrate wet deposition. δ¹⁸O-NO₃^- values reflect the oxidation of NO_x sources via the ·OH + RO₂ pathways. These findings provide necessary baseline information about the combination of water and nitrogen stable isotopes with atmospheric chemistry and hydrometeorological techniques to better understand wet deposition processes and to characterize the origin and magnitude of inorganic nitrogen loadings in tropical regions.

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM_2.5) and nitrogen dioxide (NO₂). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Environmental and Health Impacts of Air Pollution: A Review

One of our era's greatest scourges is air pollution, on account not only of its impact on climate change but also its impact on public and individual health due to increasing morbidity and mortality. There are many pollutants that are major factors in disease in humans. Among them, Particulate Matter (PM), particles of variable but very small diameter, penetrate the respiratory system via inhalation, causing respiratory and cardiovascular diseases, reproductive and central nervous system dysfunctions, and cancer. Despite the fact that ozone in the stratosphere plays a protective role against ultraviolet irradiation, it is harmful when in high concentration at ground level, also affecting the respiratory and cardiovascular system. Furthermore, nitrogen oxide, sulfur dioxide, Volatile Organic Compounds (VOCs), dioxins, and polycyclic aromatic hydrocarbons (PAHs) are all considered air pollutants that are harmful to humans. Carbon monoxide can even provoke direct poisoning when breathed in at high levels. Heavy metals such as lead, when absorbed into the human body, can lead to direct poisoning or chronic intoxication, depending on exposure. Diseases occurring from the aforementioned substances include principally respiratory problems such as Chronic Obstructive Pulmonary Disease (COPD), asthma, bronchiolitis, and also lung cancer, cardiovascular events, central nervous system dysfunctions, and cutaneous diseases. Last but not least, climate change resulting from environmental pollution affects the geographical distribution of many infectious diseases, as do natural disasters. The only way to tackle this problem is through public awareness coupled with a multidisciplinary approach by scientific experts; national and international organizations must address the emergence of this threat and propose sustainable solutions.

Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory

Fine-scale nitrogen oxide (NOx) concentrations over South Korea are examined using surface observations, satellite data and high-resolution model simulations based on the latest emission inventory. While accurate information on NOx emissions in South Korea is crucial to understanding regional air quality in the region, consensus on the validation of NOx emissions is lacking. We investigate the spatial and temporal variation in fine-scale NOx emission sources over South Korea. Surface observations and newly available fine-scale satellite data (TROPOspheric Monitoring Instrument; TROPOMI; 3.5 × 7 km2) are compared with the community multiscale air quality (CMAQ) model based on the clean air policy support system (CAPSS) 2016 emission inventory. The results show that the TROPOMI NO2 column densities agree well with the CMAQ simulations based on CAPSS emissions (e.g., R = 0.96 for June 2018). The surface observations, satellite data and model are consistent in terms of their spatial distribution, the overestimation over the Seoul Metropolitan Area and major point sources; however, the model tends to underestimate the surface concentrations during the cold season.

Vertical and horizontal fall-off of black carbon and NO2 within urban blocks

While exposure to traffic pollutants significantly decreases with distance from the curb, very dense urban architectures hamper such dispersion. Moreover, the building height reduces significantly the dispersion of pollutants. We have investigated the horizontal variability of Black Carbon (BC) and the vertical variability of NO₂ and BC within the urban blocks. Increasing the distance from road BC concentrations decreased following an exponential curve reaching halving distances at 25 m (median), although with a wide variability among sites. Street canyons showed sharper fall-offs than open roads or roads next to a park. Urban background concentrations were achieved at 67 m distance on average, with higher distances found for more trafficked roads. Vertical fall-off of BC was less pronounced than the horizontal one since pollutants homogenize quickly vertically after rush traffic hours. Even shallower vertical fall-offs were found for NO₂. For both pollutants, background concentrations were never reached within the building height. A street canyon effect was also found exacerbating concentrations at the lowest floors of the leeward side of the road. These inputs can be useful for assessing population exposure, air quality policies, urban planning and for models validation.

Hazardous Air Pollutants and Adverse Birth Outcomes in Portland, OR

Supplemental Digital Content is available in the text.

The impact of multiple hazardous air pollutant (HAP) exposures during pregnancy on adverse birth outcomes is unknown. We examined associations between cumulative and individual HAP exposures and adverse birth outcomes in Portland, OR, a region that has exceeded HAP air quality guidelines for decades.

On-Road Chemical Transformation as an Important Mechanism of NO2 Formation

Nitrogen dioxide (NO₂) not only is linked to adverse effects on the respiratory system but also contributes to the formation of ground-level ozone (O₃) and fine particulate matter (PM_2.5). Our curbside monitoring data analysis in Detroit, MI, and Atlanta, GA, strongly suggests that a large fraction of NO₂ is produced during the "tailpipe-to-road" stage. To substantiate this finding, we designed and carried out a field campaign to measure the same exhaust plumes at the tailpipe-level by a portable emissions measurement system (PEMS) and at the on-road level by an electric vehicle-based mobile platform. Furthermore, we employed a turbulent reacting flow model, CTAG, to simulate the on-road chemistry behind a single vehicle. We found that a three-reaction (NO-NO₂-O₃) system can largely capture the rapid NO to NO₂ conversion (with time scale ≈ seconds) observed in the field studies. To distinguish the contributions from different mechanisms to near-road NO₂, we clearly defined a set of NO₂/NO _x ratios at different plume evolution stages, namely tailpipe, on-road, curbside, near-road, and ambient background. Our findings from curbside monitoring, on-road experiments, and simulations imply the on-road oxidation of NO by ambient O₃ is a significant, but so far ignored, contributor to curbside and near-road NO₂.

Factors associated with NO2 and NOX concentration gradients near a highway

The objective of this research is to learn how the near-road gradient, in which NO2 and NOX (NO + NO2) concentrations are elevated, varies with changes in meteorological and traffic variables. Measurements of NO2 and NOX were obtained east of I-15 in Las Vegas and fit to functions whose slopes (dCNO2 /dx and dCNOX /dx, respectively) characterize the size of the near-road zone where NO2 and NOX concentrations from mobile sources on the highway are elevated. These metrics were used to learn about the near-road gradient by modeling dCNO2 /dx and dCNOX /dx as functions of meteorological variables (e.g., wind direction, wind speed), traffic (vehicle count), NOX concentration upwind of the road, and O3 concentration at two fixed-site ambient monitors. Generalized additive models (GAM) were used to model dCNO2 /dx and dCNOX /dx versus the independent variables because they allowed for nonlinearity of the variables being compared. When data from all wind directions were included in the analysis, variability in O3 concentration comprised the largest proportion of variability in dCNO2 /dx, followed by variability in wind direction. In a second analysis constrained to winds from the west, variability in O3 concentration remained the largest contributor to variability in dCNO2 /dx, but the relative contribution of variability in wind speed to variability in dCNO2 /dx increased relative to its contribution for the all-wind analysis. When data from all wind directions were analyzed, variability in wind direction was by far the largest contributor to variability in dCNOX /dx, with smaller contributions from hour of day and upwind NOX concentration. When only winds from the west were analyzed, variability in upwind NOX concentration, wind speed, hour of day, and traffic count all were associated with variability in dCNOX /dx. Increases in O3 concentration were associated with increased magnitude near-road dCNO2 /dx, possibly shrinking the zone of elevated concentrations occurring near roads. Wind direction parallel to the highway was also related to an increased magnitude of both dCNO2 /dx and dCNOX /dx, again likely shrinking the zone of elevated concentrations occurring near roads. Wind direction perpendicular to the road decreased the magnitude of dCNO2 /dx and dCNOX /dx and likely contributed to growth of the zone of elevated concentrations occurring near roads. Thus, variability in near-road concentrations is influenced by local meteorology and ambient O3 concentration.

NO to NO2 Conversion Rate Analysis and Implications for Dispersion Model Chemistry Methods using Las Vegas, Nevada Near-Road Field Measurements

The nitrogen dioxide/oxides of nitrogen (NO₂/NO_X) ratio is an important surrogate for NO to NO₂ chemistry in dispersion models when estimating NO_X impacts in a near-road environment. Existing dispersion models use different techniques and assumptions to represent NO to NO₂ conversion and do not fully characterize all of the important atmospheric chemical and mechanical processes. Thus, "real-world" ambient measurements must be analyzed to assess the behavior of NO₂/NO_X ratios near roadways. An examination of NO₂/NO_X ratio data from a field study conducted in Las Vegas, Nevada (NV), from mid-December, 2008 through mid-December, 2009 provides insights into the appropriateness of assumptions about the NO₂/NO_X ratio included in dispersion models. Data analysis indicates multiple factors affect the downwind NO₂/NO_X ratio. These include spatial gradient, background ozone (O₃), source emissions of NO and NO₂, and background NO₂/NO_X ratio. Analysis of the NO₂/NO_X ratio spatial gradient indicates that under high O₃ conditions, the change in the ratio is fairly constant once a certain O₃ threshold (≥ 30 ppb) is reached. However, under low O₃ conditions (< 30 ppb), there are differences between weekdays and weekends, most likely due to a decline in O₃ concentrations during the weekday morning hours, reducing the O₃ available to titrate the emitted NO, allowing lower NO₂/NO_X ratios. These results suggest that under high O₃ conditions, NO_X chemistry is driving the NO₂/NO_X ratios whereas under low O₃ conditions, atmospheric mixing is the driving factor.

Part 1. Assessment of carcinogenicity and biologic responses in rats after lifetime inhalation of new-technology diesel exhaust in the ACES bioassay

The Health Effects Institute and its partners conceived and funded a program to characterize the emissions from heavy-duty diesel engines compliant with the 2007 and 2010 on-road emissions standards in the United States and to evaluate indicators of lung toxicity in rats and mice exposed repeatedly to 2007-compliant new-technology diesel exhaust (NTDE*). The a priori hypothesis of this Advanced Collaborative Emissions Study (ACES) was that 2007-compliant on-road diesel emissions "... will not cause an increase in tumor formation or substantial toxic effects in rats and mice at the highest concentration of exhaust that can be used ... although some biological effects may occur." This hypothesis was tested at the Lovelace Respiratory Research Institute (LRRI) by exposing rats by chronic inhalation as a carcinogenicity bioassay. Indicators of pulmonary toxicity in rats were measured after 1, 3, 12, 24, and 28-30 months of exposure. Similar indicators of pulmonary toxicity were measured in mice, as an interspecies comparison of the effects of subchronic exposure, after 1 and 3 months of exposure. A previous HEI report (Mauderly and McDonald 2012) described the operation of the engine and exposure systems and the characteristics of the exposure atmospheres during system commissioning. Another HEI report described the biologic responses in mice and rats after subchronic exposure to NTDE (McDonald et al. 2012). The primary motivation for the present chronic study was to evaluate the effects of NTDE in rats in the context of previous studies that had shown neoplastic lung lesions in rats exposed chronically to traditional technology diesel exhaust (TDE) (i.e., exhaust from diesel engines built before the 2007 U.S. requirements went into effect). The hypothesis was largely based on the marked reduction of diesel particulate matter (DPM) in NTDE compared with emissions from older diesel engine and fuel technologies, although other emissions were also reduced. The DPM component of TDE was considered the primary driver of lung tumorigenesis in rats exposed chronically to historical diesel emissions. Emissions from a 2007-compliant, 500-horsepower-class engine and after treatment system operated on a variable-duty cycle were used to generate the animal inhalation test atmospheres. Four groups were exposed to one of three concentrations (dilutions) of exhaust combined with crankcase emissions, or to clean air as a negative control. Dilutions of exhaust were set to yield average integrated concentrations of 4.2, 0.8, and 0.1 ppm nitrogen dioxide (NO2). Exposure atmospheres were analyzed by daily measurements of key effects of NTDE in the present study were generally consistent with those observed previously in rats exposed chronically to NO2 alone. This suggests that NO2 may have been the primary driver of the biologic responses to NTDE in the present study. There was little evidence of effects characteristic of rats exposed chronically to high concentrations of DPM in TDE, such as an extensive accumulation of DPM within alveolar macrophages and inflammation leading to neoplastic transformation of epithelia and lung tumors. components and periodic detailed physical-chemical characterizations. Exposures were conducted 16 hours/day (overnight, during the rats' most active period), 5 days/week. Responses to exposure were evaluated via hematology, serum chemistry, bronchoalveolar lavage (BAL), lung cell proliferation, histopathology, and pulmonary function. The exposures were accomplished as planned, with average integrated exposure concentrations within 20% of the target dilutions. The major components from exhaust were the gaseous inorganic compounds, nitrogen monoxide (NO), NO2, and carbon monoxide (CO). Minor components included low concentrations of DPM and volatile and semi-volatile organic compounds (VOCs and SVOCs). Among the more than 100 biologic response variables evaluated, the majority showed no significant difference from control as a result of exposure to NTDE. The major outcome of this study was the absence of pre-neoplastic lung lesions, primary lung neoplasia, or neoplasia of any type attributable to NTDE exposure. The lung lesions that did occur were minimal to mild, occurred only at the highest exposure level, and were characterized by an increased number and prominence of basophilic epithelial cells (considered reactive or regenerative) lining distal terminal bronchioles, alveolar ducts, and adjacent alveoli (termed in this report "Hyperplasia; Epithelial; Periacinar"), which often had a minimal increase in subjacent fibrous stroma (termed "Fibrosis; Interstitial; Periacinar"). Slight epithelial metaplastic change to a cuboidal morphology, often demonstrating cilia, was also noted in some animals (termed "Bronchiolization"). In addition to the epithelial proliferation, there was occasionally a subtle accumulation of pulmonary alveolar macrophages (termed "Accumulation; Macrophage") in affected areas. The findings in the lung progressed slightly from 3 to 12 months, without further progression between 12 months and the final sacrifice at 28 or 30 months. In addition to the histologic findings, there were biochemical changes in the lung tissue and lavage fluid that indicated mild inflammation and oxidative stress. Generally, these findings were observed only at the highest exposure level. There was also a mild progressive decrease in pulmonary function, which was more consistent in females than males. Limited nasal epithelial changes resulted from NTDE exposure, including increases in minor olfactory epithelial degeneration, hyperplasia, and/or metaplasia. Increases in these findings were present primarily at the highest exposure level, and their minor and variable nature renders their biologic significance uncertain. Overall, the findings of this study demonstrated markedly less severe biologic responses to NTDE than observed previously in rats exposed similarly to TDE. Further, the effects of NTDE in the present study were generally consistent with those observed previously in rats exposed chronically to NO2 alone. This suggests that NO2 may have been the primary driver of the biologic responses to NTDE in the present study. There was little evidence of effects characteristic of rats exposed chronically to high concentrations of DPM in TDE, such as an extensive accumulation of DPM within alveolar macrophages and inflammation leading to neoplastic transformation of epithelia and lung tumors.