Annual Mean NO2 Concentrations Research Articles

How do emission reductions of individual national and local measures impact street-level air quality in a neighbourhood of Madrid, Spain?

AbstractThis paper aims to assess the impact of individual measures for NOx emission reduction on NO2 concentrations at very high spatial resolution in an urban district of Madrid City (Spain). A methodology based on a set of Computational Fluid Dynamics simulations for 16 meteorological scenarios combined with the CHIMERE model for background pollution is used to obtain annual NO2 concentration maps. Two scenarios included in the Spanish National Air Pollution Control Programme are investigated: NOx emission reductions from the installation of more efficient boilers for domestic heating (ECOBOIL) and from the partly substitution of passenger cars with combustion engines by electric cars (EC). This analysis is extended to 9 additional scenarios of more ambitious implementation of electric vehicles in order to determine what the NOx emission reduction required for the annual mean NO2 concentration EU limit value not being exceeded is. The ECOBOIL scenario has a very weak impact on the NO2 concentrations. However, the EC scenario implies a more significant reduction of the NO2 concentrations, but not enough to fully remove NO2 limit value exceedances in the study area. A small additional (compared with the EC scenario) implementation of electric vehicles seems to fulfil that the spatially averaged NO2 concentration be lower than the EU limit value, but the area with exceedances is still very large. However, stronger traffic emission reductions (80%) corresponding to the most ambitious scenarios are needed in order to reach that at least 95% of the domain is free of EU limit value exceedances.

Incident risk and burden of cardiovascular diseases attributable to long-term NO2 exposure in Chinese adults

BackgroundA number of studies suggested a nexus between long-term exposure to nitrogen dioxide (NO2) and the incidence of cardiovascular disease (CVD), while population-based cohort evidence in low- and middle-income countries was extensively sparse. MethodsWe carried out an 8-year longitudinal study (2010–2018) in a nationwide dynamic cohort of 36,948 Chinese adult participants, who were free of CVD at baseline. Annual average estimates of NO2 exposure were predicted using a well-validated spatiotemporal model and assigned to study participants based on their residential counties. Considering death as a competing risk event, Fine-Gray competing risk models with time-varying exposures at an annual scale were used to quantify incident risks of overall CVD, hypertension, and stroke associated with a 10-μg/m3 rise in NO2 exposure. Using the meta-analysis approach, we performed a pooled analysis of hazard ratio (HR) drawn from this and prior multinational cohort studies for the assessment of attributable burden. NO2-attributable overall CVD incidents in China were evaluated by city and province for years 2010 and 2018, referring to a counterfactual exposure level of 10 μg/m3 (2021 World Health Organization [WHO] air quality guidelines). A decomposition method was used to decompose net change in NO2-attributable CVD incidents during 2010 and 2018 into 3 primary contributions of driving factors (i.e., changes in NO2 exposure, population size, and incidence rate). ResultsA total of 4428 overall CVD events (hypertension 2448, stroke 1044) occurred during a median follow-up period of 6.1 years. Annual mean NO2 concentration from 2010 to 2018 was 20.0 μg/m3 (range: 6.9–57.4 μg/m3). An increase of 10-µg/m3 in NO2 was associated with an HR of 1.558 (95% confidence interval [CI]: 1.477, 1.642) for overall CVD, 1.521 (95% CI: 1.419, 1.631) for hypertension, and 1.664 (95% CI: 1.485, 1.865) for stroke. Longitudinal associations of NO2 exposure with incident CVD were nearly linear over the exposure range, suggesting no discernible thresholds. Subgroup analyses indicated significantly higher NO2-associated risks of incident CVD among urban residents and overweight/obese individuals. According to pooled HR of NO2-CVD association (1.108, 95% CI: [1.007, 1.219]) from 10 multinational cohort studies, we estimated totally 1.44 million incident CVD cases attributable to NO2 exposure in 2018, representing a substantial decrease of 0.41 million compared to the estimate in 2010 (1.85 million) in mainland of China. Nationally, from 2010 to 2018, the attributable incident cases greatly dropped by 22.4%, which was dominantly driven by declined NO2 concentration (−47.1%) that had offset far from the rise of CVD incidence rate (+19.6%) and population growth (+5.1%). ConclusionsThis study provided nationwide cohort evidence for elevated risks of CVD incidence associated with long-term ambient NO2 exposure among Chinese adults, particularly in urban areas and among overweight/obese individuals. Our findings highlighted that reducing NO2 exposure below 2021 WHO guideline could help prevent a substantial portion of incident CVD cases in China.

Causal links between long-term exposure to NO2 and the risk of cardiovascular hospitalization

Objective: To determine the causal association between long-term Nitrogen dioxide (NO2) exposure and the risk of cardiovascular hospitalization. Methods: Based on a sub-cohort of a community-based prospective cohort study, a total of 36 271 participants were recruited from 35 communities randomly selected in Guangzhou in 2015. The annual average exposure of NO2, demographic characteristics, lifestyle factors, and information on the causes of hospitalization was collected. We applied marginal structural Cox models to investigate the effect of NO2 on cardiovascular hospitalization. Demographic and behavioral factors also stratified results. Results: The mean age of participants in the present study was (50.9±17.8) years, and the cardiovascular admission rate was 8.7%, with 203 822 person-years of follow-up. The annual mean NO2 concentration was 48.7 μg/m3 during 2015-2020. For each 10 μg/m3 increase in NO2 concentrations, the HRs (95%CIs) of total cardiovascular hospitalization, cardiovascular hospitalization, and cerebrovascular hospitalization were 1.33 (1.16-1.52), 1.36 (1.16-1.60) and 1.25 (1.00-1.55), respectively. Participants who were never married/married, with secondary education, high exercise frequency, or non-smokers/current smokers may be more susceptible than their counterparts. Conclusion: Long-term exposure to NO2 significantly increased hospitalization risk for cardiovascular disease.

Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire

Abstract. Air pollution exhibits hyper-local variation, especially near emissions sources. In addition to people's time-activity patterns, this variation is the most critical element determining exposure. Pollution exposure is time-activity- and path-dependent, with specific behaviours such as mode of commuting and time spent near a roadway or in a park playing a decisive role. Compared to conventional air pollution monitoring stations, nodes containing low-cost air pollution sensors can be deployed with very high density. In this study, a network of 18 nodes using low-cost air pollution sensors was deployed in Newcastle-under-Lyme, Staffordshire, UK, in June 2020. Each node measured a range of species including nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5 and PM10); this study focuses on NO2 and PM2.5 over a 1-year period from 1 August 2020 to 1 October 2021. A simple and effective temperature, scale, and offset correction was able to overcome data quality issues associated with temperature bias in the NO2 readings. In its recent update, the World Health Organization (WHO) dramatically reduced annual exposure limit values from 40 to 10 µg m−3 for NO2 and from 10 to 5 µg m−3 for PM2.5. We found that the average annual mean NO2 concentration for the network was 17.5 µg m−3 and 8.1 µg m−3 for PM2.5. While in exceedance of the WHO guideline levels, these average concentrations do not exceed legally binding UK/EU standards. The network average NO2 concentration was 12.5 µg m−3 higher than values reported by a nearby regional air quality monitoring station, showing the critical importance of monitoring close to sources before pollution is diluted. We demonstrate how data from a low-cost air pollution sensor network can reveal insights into patterns of air pollution and help determine whether sources are local or non-local. With spectral analysis, we investigate the variation of the pollution levels and identify typical periodicities. Both NO2 and PM2.5 have contributions from high-frequency sources; however, the low-frequency sources are significantly different. Using spectral analysis, we determine that at least 54.3±4.3 % of NO2 is from local sources, whereas, in contrast, only 37.9±3.5 % of PM2.5 is local.

High Spatial Resolution Assessment of the Effect of the Spanish National Air Pollution Control Programme on Street-Level NO2 Concentrations in Three Neighborhoods of Madrid (Spain) Using Mesoscale and CFD Modelling

Current European legislation aims to reduce the air pollutants emitted by European countries in the coming years. In this context, this article studies the effects on air quality of the measures considered for 2030 in the Spanish National Air Pollution Control Programme (NAPCP). Three different emission scenarios are investigated: a scenario with the emissions in 2016 and two other scenarios, one with existing measures in the current legislation (WEM2030) and another one considering the additional measures of NAPCP (WAM2030). Previous studies have addressed this issue at a national level, but this study assesses the impact at the street scale in three neighborhoods in Madrid, Spain. NO2 concentrations are modelled at high spatial resolution by means of a methodology based on computational fluid dynamic (CFD) simulations driven by mesoscale meteorological and air quality modelling. Spatial averages of annual mean NO2 concentrations are only estimated to be below 40 µg/m3 in all three neighborhoods for the WAM2030 emission scenarios. However, for two of the three neighborhoods, there are still zones (4–12% of the study areas) where the annual concentration is higher than 40 µg/m3. This highlights the importance of considering microscale simulations to assess the impacts of emission reduction measures on urban air quality.

Estimation and Spatiotemporal Analysis of NO2 Pollution in East Asia During 2001–2016

AbstractAmbient nitrogen dioxide (NO2) not only has adverse health effects on humans but also contributes to the production of two major secondary atmospheric pollutants, ozone (O3) and fine particulate matter (PM2.5). In this study, surface NO2 concentrations in East Asia from 2001 to 2016 were estimated by combining an ensemble backpropagation neural network method, satellite NO2 column data, and reanalysis data. The estimated monthly and annual mean NO2 concentrations were well‐correlated with the observations, with R (correlation coefficient) values of 0.89 and 0.91, respectively. Our results indicate that the NO2 concentrations in most areas of East Asia peaked during 2011–2013. The NO2 concentrations in autumn and winter, especially in the eastern and northern parts of China, were much higher than those in summer. In terms of population NO2 exposure, over 25 million South Korea residents (∼45% of the population) were exposed to NO2 concentrations higher than the 2005 World Health Organization's annual standard (40 μg/m3, ∼22 ppbv at 25°C) in 2015. In contrast, the entire populations of some developing countries, such as Vietnam, Cambodia, Myanmar, the Philippines, and Lao PDR, were exposed to NO2 concentrations less than 14 ppbv. Based on the estimation, NO2‐related asthma cases in East Asia increased by 1.37% annually from 2001 to 2015, reaching 139,000 cases (95% confidence interval: 37,400–263,400) in 2015. NOx emission inventories vary from country to country in East Asia; thus, more targeted NOx emission‐control policies are urgently required.

First satellite-based regional hourly NO2 estimations using a space-time ensemble learning model: A case study for Beijing-Tianjin-Hebei Region, China

Surface Nitrogen dioxide (NO2) concentrations have been generated with satellite retrievals using multiple statistical algorithms. However, they are often given at coarse frequencies (“snapshot”, daily or even longer), limiting their applications in epidemiological studies and assessing the evolution of NO2 pollution. This study investigated the potential applicability of Himawari-8 derived hourly fine particulate matter concentrations in producing hourly NO2 concentrations by constructing a space-time ensemble model. The Beijing-Tianjin-Hebei (BTH) region, one of the serious pollution regions in China, is the study region chosen. The proposed model performs well in estimating hourly NO2 concentration with a high cross-validation (CV) coefficient of determination (R2 = 0.81) and low CV root-mean-square (RMSE = 9.71 μg/m3), mean prediction errors (MPE = 6.33 μg/m3), and relative prediction errors (RPE = 22.5%). On daily, monthly, seasonal, and annual time scales, CV R2 increases to 0.89, 0.93, 0.97, and 0.99, respectively. The annual mean model estimated NO2 concentration over BTH region is 28.2 ± 6.5 μg/m3, with relatively higher NO2 concentrations are seen in southern and southeastern BTH. Winter experiences the most severe NO2 concentrations, followed by autumn, spring, and summer. Surface NO2 concentrations are higher (lower) in the morning (afternoon) and tend to decrease gradually with time. The model generally captures the hourly evolution of NO2 concentrations for the severe pollution episode but shows some underestimations. The annual mean NO2 concentrations were 2.8% lower on the weekend than on weekdays. In addition, the weekend effects of NO2 concentrations are larger at rush hour and lower in the noon. The hourly NO2 products derived from proposed approach are potentially useful for improving our understanding of the source, evolution, and transportation behavior of NO2 pollution episodes and for exposure- and health-related research. The proposed approach also enriches the potential applications of geostationary satellites (e.g., Himawari-8).

Downscaling of air pollutants in Europe using uEMEP_v6

Abstract. The air quality downscaling model uEMEP and its combination with the EMEP MSC-W chemical transport model are used here to achieve high-resolution air quality modelling at street level in Europe. By using publicly available proxy data, this uEMEP–EMEP modelling system is applied to calculate annual mean NO2, PM2.5, PM10, and O3 concentrations for all of Europe down to 100 m resolution and is validated against all available AIRBASE monitoring stations in Europe at 25 m resolution. Downscaling is carried out on annual mean concentrations, requiring special attention to non-linear processes, such as NO2 chemistry for which frequency distributions are applied to better represent the non-linear NO2 chemistry. The downscaling shows significant improvement in NO2 concentrations for which the spatial correlation has been doubled for most countries and bias reduced from −46 % to −18 % for all stations in Europe. The downscaling of PM2.5 and PM10 does not show improvement in spatial correlation but does reduce the overall bias in the European calculations from −21 % to −11 % and from −39 % to −30 % for PM2.5 and PM10, respectively. There is improved spatial correlation in most countries after downscaling of O3 and a reduced positive bias of O3 concentrations from +16 % to +11 %. Sensitivity tests in Norway show that improvements in the emission and emission proxy data used for the downscaling can significantly improve both the NO2 and PM results. The downscaling development opens the way for improved exposure estimates, improved assessment of emissions, and detailed calculations of source contributions to exceedances in a consistent way for all of Europe at high resolution.

A multi-step machine learning approach to assess the impact of COVID-19 lockdown on NO2 attributable deaths in Milan and Rome, Italy

BackgroundAir pollution is one of the main concerns for the health of European citizens, and cities are currently striving to accomplish EU air pollution regulation. The 2020 COVID-19 lockdown measures can be seen as an unintended but effective experiment to assess the impact of traffic restriction policies on air pollution. Our objective was to estimate the impact of the lockdown measures on NO2 concentrations and health in the two largest Italian cities.MethodsNO2 concentration datasets were built using data deriving from a 1-month citizen science monitoring campaign that took place in Milan and Rome just before the Italian lockdown period. Annual mean NO2 concentrations were estimated for a lockdown scenario (Scenario 1) and a scenario without lockdown (Scenario 2), by applying city-specific annual adjustment factors to the 1-month data. The latter were estimated deriving data from Air Quality Network stations and by applying a machine learning approach. NO2 spatial distribution was estimated at a neighbourhood scale by applying Land Use Random Forest models for the two scenarios. Finally, the impact of lockdown on health was estimated by subtracting attributable deaths for Scenario 1 and those for Scenario 2, both estimated by applying literature-based dose–response function on the counterfactual concentrations of 10 μg/m3.ResultsThe Land Use Random Forest models were able to capture 41–42% of the total NO2 variability. Passing from Scenario 2 (annual NO2 without lockdown) to Scenario 1 (annual NO2 with lockdown), the population-weighted exposure to NO2 for Milan and Rome decreased by 15.1% and 15.3% on an annual basis. Considering the 10 μg/m3 counterfactual, prevented deaths were respectively 213 and 604.ConclusionsOur results show that the lockdown had a beneficial impact on air quality and human health. However, compliance with the current EU legal limit is not enough to avoid a high number of NO2 attributable deaths. This contribution reaffirms the potentiality of the citizen science approach and calls for more ambitious traffic calming policies and a re-evaluation of the legal annual limit value for NO2 for the protection of human health.

Mapping high resolution national daily NO2 exposure across mainland China using an ensemble algorithm.

Nitrogen dioxide (NO2) is an important air pollutant and highly related to air quality, short- and long-term health effects, and even climate. A national model was developed using the extreme gradient boosting algorithm with high-resolution tropospheric vertical column NO2 densities from the Sentinel-5 Precursor/Tropospheric Monitoring Instrument and general meteorological variables as input to generate daily mean surface NO2 concentrations across mainland China. Model-derived daily NO2 estimates were high accuracy with sample-based cross-validation coefficient of determination of 0.83, a root-mean-square error of 7.58μg/m3, a mean prediction error of 5.56μg/m3, and a mean relative prediction error of 18.08%. It has good performance in NO2 estimations at both regional and individual site scale. The model also performed well in terms of estimating monthly, seasonal, and annual mean NO2 concentrations across China. The model performance appears to better than or comparable to most previous related studies. The seasonal and annual spatial distributions of surface NO2 across China and several regional NO2 hotspots in 2019 were derived from the model and analyzed. Also evaluated were the population exposure levels of NO2 for cities in and provinces of China. At the national scale, about 12% of the population experienced annual mean NO2 concentrations exceeding the Chinese national air quality standard. The nationwide model with conventional predictors developed here can derive high-resolution surface NO2 concentrations across China routinely, benefitting air epidemiological and environmental related studies.

The urban dispersion model EPISODE v10.0 – Part 1: An Eulerian and sub-grid-scale air quality model and its application in Nordic winter conditions

Abstract. This paper describes the Eulerian urban dispersion model EPISODE. EPISODE was developed to address a need for an urban air quality model in support of policy, planning, and air quality management in the Nordic, specifically Norwegian, setting. It can be used for the calculation of a variety of airborne pollutant concentrations, but we focus here on the implementation and application of the model for NO2 pollution. EPISODE consists of an Eulerian 3D grid model with embedded sub-grid dispersion models (e.g. a Gaussian plume model) for dispersion of pollution from line (i.e. roads) and point sources (e.g. chimney stacks). It considers the atmospheric processes advection, diffusion, and an NO2 photochemistry represented using the photostationary steady-state approximation for NO2. EPISODE calculates hourly air concentrations representative of the grids and at receptor points. The latter allow EPISODE to estimate concentrations representative of the levels experienced by the population and to estimate their exposure. This methodological framework makes it suitable for simulating NO2 concentrations at fine-scale resolution (<100 m) in Nordic environments. The model can be run in an offline nested mode using output concentrations from a global or regional chemical transport model and forced by meteorology from an external numerical weather prediction model; it also can be driven by meteorological observations. We give a full description of the overall model function and its individual components. We then present a case study for six Norwegian cities whereby we simulate NO2 pollution for the entire year of 2015. The model is evaluated against in situ observations for the entire year and for specific episodes of enhanced pollution during winter. We evaluate the model performance using the FAIRMODE DELTA Tool that utilises traditional statistical metrics, e.g. root mean square error (RMSE), Pearson correlation R, and bias, along with some specialised tests for air quality model evaluation. We find that EPISODE attains the DELTA Tool model quality objective in all of the stations we evaluate against. Further, the other statistical evaluations show adequate model performance but that the model scores greatly improved correlations during winter and autumn compared to the summer. We attribute this to the use of the photostationary steady-state scheme for NO2, which should perform best in the absence of local ozone photochemical production. Oslo does not comply with the NO2 annual limit set in the 2008/50/EC directive (AQD). NO2 pollution episodes with the highest NO2 concentrations, which lead to the occurrence of exceedances of the AQD hourly limit for NO2, occur primarily in the winter and autumn in Oslo, so this strongly supports the use of EPISODE for application to these wintertime events. Overall, we conclude that the model is suitable for an assessment of annual mean NO2 concentrations and also for the study of hourly NO2 concentrations in the Nordic winter and autumn environment. Further, in this work we conclude that it is suitable for a range of policy applications specific to NO2 that include pollution episode analysis, evaluation of seasonal statistics, policy and planning support, and air quality management. Lastly, we identify a series of model developments specifically designed to address the limitations of the current model assumptions. Part 2 of this two-part paper discusses the CityChem extension to EPISODE, which includes a number of implementations such as a more comprehensive photochemical scheme suitable for describing more chemical species and a more diverse range of photochemical environments, as well as a more advanced treatment of the sub-grid dispersion.

The impact of ship emissions on air quality and human health in the Gothenburg area – Part 1: 2012 emissions

Abstract. Ship emissions in and around ports are of interest for urban air quality management in many harbour cities. We investigated the impact of regional and local ship emissions on urban air quality for 2012 conditions in the city of Gothenburg, Sweden, the largest cargo port in Scandinavia. In order to assess the effects of ship emissions, a coupled regional- and local-scale model system has been set up using ship emissions in the Baltic Sea and the North Sea as well as in and around the port of Gothenburg. Ship emissions were calculated with the Ship Traffic Emission Assessment Model (STEAM), taking into account individual vessel characteristics and vessel activity data. The calculated contributions from local and regional shipping to local air pollution in Gothenburg were found to be substantial, especially in areas around the city ports. The relative contribution from local shipping to annual mean NO2 concentrations was 14 % as the model domain average, while the relative contribution from regional shipping in the North Sea and the Baltic Sea was 26 %. In an area close to the city terminals, the contribution of NO2 from local shipping (33 %) was higher than that of road traffic (28 %), which indicates the importance of controlling local shipping emissions. Local shipping emissions of NOx led to a decrease in the summer mean O3 levels in the city by 0.5 ppb (∼2 %) on average. Regional shipping led to a slight increase in O3 concentrations; however, the overall effect of regional and the local shipping together was a small decrease in the summer mean O3 concentrations in the city. In addition, volatile organic compound (VOC) emissions from local shipping compensate up to 4 ppb of the decrease in summer O3 concentrations due to the NO titration effect. For particulate matter with a median aerodynamic diameter less than or equal to 2.5 µm (PM2.5), local ship emissions contributed only 3 % to the annual mean in the model domain, while regional shipping under 2012 conditions was a larger contributor, with an annual mean contribution of 11 % of the city domain average. Based on the modelled local and regional shipping contributions, the health effects of PM2.5, NO2 and ozone were assessed using the ALPHA-RiskPoll (ARP) model. An effect of the shipping-associated PM2.5 exposure in the modelled area was a mean decrease in the life expectancy by 0.015 years per person. The relative contribution of local shipping to the impact of total PM2.5 was 2.2 %, which can be compared to the 5.3 % contribution from local road traffic. The relative contribution of the regional shipping was 10.3 %. The mortalities due to the exposure to NO2 associated with shipping were calculated to be 2.6 premature deaths yr−1. The relative contribution of local and regional shipping to the total exposure to NO2 in the reference simulation was 14 % and 21 %, respectively. The shipping-related ozone exposures were due to the NO titration effect leading to a negative number of premature deaths. Our study shows that overall health impacts of regional shipping can be more significant than those of local shipping, emphasizing that abatement policy options on city-scale air pollution require close cooperation across governance levels. Our findings indicate that the strengthened Sulphur Emission Control Areas (SECAs) fuel sulphur limit from 1 % to 0.1 % in 2015, leading to a strong decrease in the formation of secondary particulate matter on a regional scale was an important step in improving the air quality in the city.

Modelling public health benefits of various emission control options to reduce NO2 concentrations in Guangzhou

The local government of the megacity of Guangzhou, China, has established an annual average NO2 concentration target of 40 μg m−3 to achieve by 2020. However, the Guangzhou Ambient Air Quality Compliance Plan does not specify what constitutes compliance with this target. We investigated a range of ambition levels for emissions reductions required to meet different possible interpretations of compliance using a hybrid dispersion and land-use regression model approach. We found that to reduce average annual-mean NO2 concentration across all current monitoring sites to below 40 μg m−3 (i.e. a compliance assessment approach that does not use modelling) would require emissions reductions from all source sectors within Guangzhou of 60%, whilst to attain 40 μg m−3 everywhere in Guangzhou (based on model results) would require all-source emissions reduction of 90%. Reducing emissions only from the traffic sector would not achieve either interpretation of the target. We calculated the impacts of the emissions reductions on NO2-atttributable premature mortality to illustrate that policy assessment based only on assessment against a fixed concentration target does not account for the full public health improvements attained. Our approach and findings are relevant for NO2 air pollution control policy making in other megacities.

Atmospheric reactive nitrogen concentration and deposition trends from 2011 to 2018 at an urban site in north China

Atmospheric reactive nitrogen (Nr) emissions and deposition have caused much damage to the global environment and also impacted human health. Determining long-term trends in atmospheric Nr concentrations and deposition is important for evaluating air quality and ecosystem effects and formulating control measures to reduce negative impacts. We measured monthly concentrations of NH3, pNH4+, HNO3, pNO3-, and NO2 and calculated their dry deposition rates using an inferential method from 2011 to 2018 at an urban site in Zhengzhou in the North China Plain. Inorganic N (NH4+ and NO3−) concentrations in precipitation and wet/bulk N deposition were also quantified in 2011, 2016, 2017 and 2018. The results showed high concentrations of atmospheric Nr species, with considerable variation in some species over the monitoring period. Annual mean NH3 concentrations significantly increased from 2011 to 2018 (p < 0.001) with that in 2018 being twice that in 2011. However, pNO3- and pNH4+ concentrations decreased after 2013. The annual mean NO2 concentration in 2018 had decreased by 33.4% compared to the peak in 2011. Highest NH3 concentrations were measured in spring or summer, and lowest concentrations in winter. pNH4+ and pNO3- concentrations peaked mainly in winter. Total annual dry N deposition ranged from 21.9 to 41.2 kg N ha−1. Bulk NH4+ and NO3− deposition was lower in 2016–2018 than in 2011. However, atmospheric Nr concentrations and N deposition remained high in this urban ecosystem. NH3 emissions urgently need control measures, and Nr impacts on the surrounding ecosystems and human health should be considered. Continuous long-term measurements of atmospheric Nr concentrations and deposition at a regional scale are necessary to help formulate emission control measures and protect human and ecosystem health.

Assessment of mean annual NO2 concentration based on a partial dataset

NO2 is a pollutant harmful to both health and the environment. The European Union and the World Health Organization have developed guidelines in terms of pollutant. The value of 40 μg/m3 is set by both entities as the annual mean NO2 concentration not to be exceeded to prevent risks for human health. To assess this given value, yearlong in situ measurements are required. However, sometimes only partial data are available, such as having only NOx (NO + NO2) information, on the one hand, and, on the other hand, brief NO2 measurements performed over few months. To overcome the first hurdle, several methods exist in the literature to transform NOx data into NO2 data. The method of Derwent and Middleton is the most appropriate for France with less than 8% of deviation and even less deviation when considering rural and urban sites. For all values, NOx concentrations behave as expected with higher concentrations in autumn and winter than in spring and summer. However, for NO2 this trend changes around 80 μg/m³ for which the spring and summer values are higher. Therefore, to maximize measurements to assess an upper limit on annual NO2 concentration over a short period of time, those measurements should be done in winter if an annual concentration of less than 80 μg/m3 is expected, otherwise they should carry out in summer. To tackle the second issue, a second order polynomial approach is built on a Paris dataset covering years between 2013 and 2017 to determine annual mean concentrations with monthly mean concentrations and gives an overall error of 10%. The law built on Paris was then tested on several regions in France for the same period and resulted in predicted values with a mean error of about 15% compared to the measured ones. In the end, the presented methodology allows covering twelve times more ground with a single NO2 or NOx sensor with an acceptable error.

Spatial and temporal variations of air quality and six air pollutants in China during 2015\u20132017

Air pollution has aroused significant public concern in China, therefore, long-term air-quality data with high temporal and spatial resolution are needed to understand the variations of air pollution in China. However, the yearly variations with high spatial resolution of air quality and six air pollutants are still unknown for China until now. Therefore, in this paper, we analyze the spatial and temporal variations of air quality and six air pollutants in 366 cities across mainland China during 2015–2017 for the first time to the best of our knowledge. The results indicate that the annual mean mass concentrations of PM2.5, PM10, SO2, and CO all decreased year by year during 2015–2017. However, the annual mean NO2 concentrations were almost unchanged, while the annual mean O3 concentrations increased year by year. Anthropogenic factors were mainly responsible for the variations of air quality. Further analysis suggested that PM2.5 and PM10 were the main factors influencing air quality, while NO2 played an important role in the formation of PM2.5 and O3. These findings can provide a theoretical basis for the formulation of future air-pollution control policy in China.

Assessment of impact of traffic-related air pollution on morbidity and mortality in Copenhagen Municipality and the health gain of reduced exposure

BackgroundHealth impact assessment (HIA) of exposure to air pollution is commonly based on city level (fine) particle concentration and may underestimate health consequences of changing local traffic. Exposure to traffic-related air pollution can be assessed at a high resolution by modelling levels of nitrogen dioxide (NO2), which together with ultrafine particles mainly originate from diesel-powered vehicles in urban areas. The purpose of this study was to estimate the health benefits of reduced exposure to vehicle emissions assessed as NO2 at the residence among the citizens of Copenhagen Municipality, Denmark. MethodsWe utilized residential NO2 concentrations modelled by use of chemistry transport models to calculate contributions from emission sources to air pollution. The DYNAMO-HIA model was applied to the population of Copenhagen Municipality by using NO2 concentration estimates combined with demographic data and data from nationwide registers on incidence and prevalence of selected diseases, cause specific mortality, and total mortality of the population of Copenhagen. We used exposure-response functions linking NO2 concentration estimates at the residential address with the risk of diabetes, cardiovascular diseases, and respiratory diseases derived from a large Danish cohort study with the majority of subjects residing in Copenhagen between 1971 and 2010. Different scenarios were modelled to estimate the dynamic impact of NO2 exposure on related diseases and the potential health benefits of lowering the NO2 level in the Copenhagen Municipality. ResultsThe annual mean NO2 concentration was 19.6 μg/m3 and for 70% of the population the range of exposure was between 15 and 21 μg/m3. If NO2 exposure was reduced to the annual mean rural level of 6 μg/m3, life expectancy in 2040 would increase by one year. The greatest gain in disease-free life expectancy would be lifetime without ischemic heart disease (1.4 years), chronic obstructive pulmonary disease (1.5 years for men and 1.6 years for women), and asthma (1.3 years for men and 1.5 years for women). Lowering NO2 exposure by 20% would increase disease-free life expectancy for the different diseases by 0.3–0.5 years. Using gender specific relative risks affected the results. ConclusionsReducing the NO2 exposure by controlling traffic-related air pollution reduces the occurrence of some of the most prevalent chronic diseases and increases life expectancy. Such health benefits can be quantified by DYNAMO-HIA in a high resolution exposure modelling. This paper demonstrates how traffic planners can assess health benefits from reduced levels of traffic-related air pollution.

Temporal distribution, influencing factors and pollution sources of urban ambient air quality in Nanchong, China

The PM10, SO₂ and NO₂ mass concentrations were obtained over five years from monitoring stations across Nanchong, a southwest city in China. Changes in urban air quality over time, as well as the factors influencing that change, were evaluated based on air pollutant concentrations, the Air Pollution Index (API), and the Comprehensive Pollution Index (P). The results showed that the total annual mean PM10, SO₂ and NO₂ concentrations over the five years studied were 61.1±1.1, 45.0±3.9 and 34.9±4.9 μg·m-3, respectively. The annual mean concentrations displayed a generally decreasing trend; lower than the annual mean second-level air quality limit. Meanwhile, the annual mean API values were in a small range of 52-53, the air quality levels were gradeⅡ, and P values were 1.06-1.21 less than the slight level (P ≤ 1.31). Total monthly mean PM10, SO₂, NO₂ concentrations, and API and P values were consistently higher in winter and spring than during autumn and summer. The results of a correlation analysis showed that temperature and pressure were the major meteorological factors influencing pollution levels. Pollution sources included industrial coal and straw burning, automobiles exhaust and road dust, fireworks, and dust storms.

Temporal and spatial distribution of tropospheric NO2 over Northeast Asia using OMI data during the years 2005–2010

This study aimed to examine the main characteristics of tropospheric nitrogen dioxide (NO2) concentrations over the Northeast Asia, using the Ozone Monitoring Instrument (OMI) data from 2005 to 2010. The annual mean NO2 concentrations (AMNC) had an increasing trend mainly due to increasing NO2 emissions in China except during the 2008 Beijing Olympic Games period, while the reduction policies of South Korea and Japan have led it to be stagnant or decreased. To investigate further regional characteristics of NO2 increasing trends in China, we divided our study area into 6 geographical regions (sectors 1–6) and then considering 4 different socio–economic levels (groups 1–4) among main cities in Eastern regions (sector 2 and 4) where the concentrations level is the highest in China and NO2 concentrations show continued increasing trend. Especially OMI NO2 and emissions consistently showed that metropolitan/big—sized and developed cities (group 1), such as Beijing and Shanghai, had an increasing trend of NO2 concentrations until 2007 and decreasing thereafter, while small/mid–sized and developing cities (groups 2 and 3) kept a continuous increasing trend over all periods. The seasonal change in NO2 concentrations showed the apparent increasing trend in winter and no significant trend in summer in all groups except for group 1. These results indicate that an increase in AMNC in Northeast Asia was mainly attributed to the increasing NO2 concentrations in winter in groups 2 and 3. Therefore, it strongly suggests the importance of the NO2 management for groups 2 and 3 to improve air quality in the Northeast Asia.

Long-Term Trends Worldwide in Ambient NO2 Concentrations Inferred from Satellite Observations.

BackgroundAir pollution is associated with morbidity and premature mortality. Satellite remote sensing provides globally consistent decadal-scale observations of ambient nitrogen dioxide (NO2) pollution.ObjectiveWe determined global population-weighted annual mean NO2 concentrations from 1996 through 2012.MethodsWe used observations of NO2 tropospheric column densities from three satellite instruments in combination with chemical transport modeling to produce a global 17-year record of ground-level NO2 at 0.1° × 0.1° resolution. We calculated linear trends in population-weighted annual mean NO2 (PWMNO2) concentrations in different regions around the world.ResultsWe found that PWMNO2 in high-income North America (Canada and the United States) decreased more steeply than in any other region, having declined at a rate of –4.7%/year [95% confidence interval (CI): –5.3, –4.1]. PWMNO2 decreased in western Europe at a rate of –2.5%/year (95% CI: –3.0, –2.1). The highest PWMNO2 occurred in high-income Asia Pacific (predominantly Japan and South Korea) in 1996, with a subsequent decrease of –2.1%/year (95% CI: –2.7, –1.5). In contrast, PWMNO2 almost tripled in East Asia (China, North Korea, and Taiwan) at a rate of 6.7%/year (95% CI: 6.0, 7.3). The satellite-derived estimates of trends in ground-level NO2 were consistent with regional trends inferred from data obtained from ground-station monitoring networks in North America (within 0.7%/year) and Europe (within 0.3%/year). Our rankings of regional average NO2 and long-term trends differed from the satellite-derived estimates of fine particulate matter reported elsewhere, demonstrating the utility of both indicators to describe changing pollutant mixtures.ConclusionsLong-term trends in satellite-derived ambient NO2 provide new information about changing global exposure to ambient air pollution. Our estimates are publicly available at http://fizz.phys.dal.ca/~atmos/martin/?page_id=232.CitationGeddes JA, Martin RV, Boys BL, van Donkelaar A. 2016. Long-term trends worldwide in ambient NO2 concentrations inferred from satellite observations. Environ Health Perspect 124:281–289; http://dx.doi.org/10.1289/ehp.1409567