National Air Pollution Research Articles

Air Quality Legislation in Australia and Canada—A Review

Air pollution is a pervasive global issue affecting human health, ecosystems, and the environment. This paper reviews the evolution and implementation of air quality legislation in Australia and Canada, providing a comparative analysis of their approaches to managing air pollution. Both countries have established robust legal frameworks to address air quality issues, involving governmental policies, regulatory mechanisms, and collaborative efforts among stakeholders. Australia began its air quality regulation at the state level in the 1950s, evolving into a national framework with the National Environment Protection Measure for Ambient Air Quality in 1998. In contrast, Canada centralized its efforts with the Clean Air Act in 1971, complemented by the National Air Pollution Surveillance program. Key findings reveal that, while both nations have achieved significant improvements in air quality, challenges remain in addressing the broader impacts of air pollution, such as climate change and health-related economic burdens. Australia’s air quality standards are generally more stringent than Canada’s for particulate matter but more relaxed for sulfur dioxide, nitrogen dioxide, and ozone. Both countries employ advanced air quality monitoring and reporting systems, with Australia’s Air Quality Index and Canada’s Air Quality Health Index providing critical public health information. The study highlights the need for continuous improvement and a more integrated approach to air quality management. By examining the legislative and regulatory landscapes of Australia and Canada, this paper offers valuable insights for other countries striving to enhance their air quality governance and mitigate the adverse effects of air pollution on a global scale.

Assessing long-term effects of gaseous air pollution exposure on mortality in the United States using a variant of difference-in-differences analysis

Long-term mortality effects of particulate air pollution have been investigated in a causal analytic frame, while causal evidence for associations with gaseous air pollutants remains extensively lacking, especially for carbon monoxide (CO) and sulfur dioxide (SO2). In this study, we estimated the causal relationship of long-term exposure to nitrogen dioxide (NO2), CO, SO2, and ozone (O3) with mortality. Utilizing the data from National Morbidity, Mortality, and Air Pollution Study, we applied a variant of difference-in-differences (DID) method with conditional Poisson regression and generalized weighted quantile sum regression (gWQS) to investigate the independent and joint effects. Independent exposures to NO2, CO, and SO2 were causally associated with increased risks of total, nonaccidental, and cardiovascular mortality, while no evident associations with O3 were identified in the entire population. In gWQS analyses, an interquartile range-equivalent increase in mixture exposure was associated with a relative risk of 1.067 (95% confidence interval: 1.010–1.126) for total mortality, 1.067 (1.009–1.128) for nonaccidental mortality, and 1.125 (1.060–1.193) for cardiovascular mortality, where NO2 was identified as the most significant contributor to the overall effect. This nationwide DID analysis provided causal evidence for independent and combined effects of NO2, CO, SO2, and O3 on increased mortality risks among the US general population.

Exposure to air pollution and cardiovascular risk in young children - a pilot project.

To examine relationships between traffic-related air pollution (TRAP) and markers of pre-clinical cardiovascular risk in young children. We studied a cohort of healthy children ages 2-5 recruited from pediatric primary care sites (n = 122). We obtained child weight, height, blood pressure and hair nicotine levels. A blood sample was obtained for biomarkers of systemic inflammation, oxidation, and prevalence of circulating endothelial progenitor cells. This manuscript represents a secondary analysis. TRAP exposure (particulate levels, nitrogen dioxide, nitrogen oxides, and proximity to major roadways) was assessed using national air pollution data based on child's census tract of residence. TRAP exposure had significant positive associations with prevalence of two of the three EPC subtypes (CD34 + /CD133 + /CD45- and CD133 + /CD45-) in unadjusted correlations. In a linear regression model, adjusting for sex, age, race, ethnicity, body mass index, parental education, child insurance, and secondhand smoke exposure, one EPC subtype (CD133 + /CD45-) had a positive significant correlation to every TRAP measure. No significant relationships between air pollution and measures of inflammation and oxidation was found. Our findings of the upregulation of EPCs may signal a response to early vascular damage during early childhood due to air pollution exposure. Traffic-related air pollution (TRAP) - known cardiovascular risk factor during adulthood Current pilot study in very young children shows upregulation of cells which protect the endothelial lining of blood vessels (endothelial progenitor cells, EPCs) Upregulation of EPCs aligns with other cardiovascular risks during childhood (obesity, prematurity, type 1 diabetes) Demonstrated with TRAP exposure lower than EPA threshold Response to air pollution may be protective of cardiovascular damage during early childhood.

Remotely sensed BC columns over rapidly changing Western China show significant decreases in mass and inconsistent changes in number, size, and mixing properties due to policy actions

Rapid economic and energy growth in Asia has led to change in the loadings of black carbon (BC) in the last two decades. This work uses remotely sensed column absorbing aerosol optical depth to quantify BC loading day-by-day and grid-to-grid. Variance maximization is used to uniquely compute an unbiased set of observations of remotely sensed NO2 in space and time of urban and suburban sources, including regions with changing energy and industry. An inversely applied probabilistic MIE algorithm constrains the size, mixing state, and number of BC using four spectral observations. Significant differences in the particle size and mixing state are identified and attributed including: a drop around 2012 when China’s national air pollution policies were adopted, a drop ahead of the 2008 Olympics, and flattening from 2015 onward. A case of simultaneous reduction in BC mass and increase in BC number demonstrates PM2.5 controls may not fully control BC.

Long term variation of microphysical properties of black carbon in Beijing derived from observation and machine learning

The microphysical attributes of black carbon (BC) can determine its absorption and hygroscopic properties. However, long-term information is difficult to obtain from the field. In this study, the BC properties including mass concentration, the coating volume ratio (VR) relative to the refractory BC (rBC), the rBC diameter and the fraction of cloud condensation nuclei (CCN), are derived from a number of field experiments using a random forest model. This model effectively derives the long-term BC microphysical properties in the Beijing region from 2013 to 2020 using continuous measurements of particulate matter, gas, BC mass concentration and meteorological parameters. The results reveal notably higher BC coatings (mean VR = 7.2) and a greater fraction of CCN-like BC (51%) in the winter compared to other seasons. Following the implementation of national air pollution control measures in 2017, BC mass exhibited a substantial reduction of 60% (29%) in the winter (summer), and VR decreased by 45% (24%). Apart from the influence of meteorological variations, these can be attributed to the declined primary emissions and the gas precursors which are associated with secondary formation of BC coatings. The reduction of both BC mass loading and coatings leads to its solar absorption decreasing by 50%, and the fraction of CCN-like BC (likely in clouds) decreasing by 23%. Environmental regulation will therefore continue to reduce both direct and indirect radiative impacts of BC in this region.

Long-term trends in British Columbia lower mainland air quality: Criteria air pollutants and VOC

ABSTRACT The lower mainland of British Columbia is a geographic region that comprises the districts of Metro Vancouver and the Lower Fraser Valley. It is situated in a complex topographical and coastal location in southwestern British Columbia. Metro Vancouver is Canada’s third largest population center. Accessing the Canadian National Air Pollution Surveillance Program (NAPS) database we calculated air pollutant statistics using the Canadian Ambient Air Quality Standards (CAAQS) averaging times, numerical forms, and numerical levels for the years 2001to 2020. Man Kendall and Sen statistical methods were used to test for the presence of trends and the slope of those trends in fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and volatile organic compound (VOC) ambient air concentrations. We did not determine a significant trend in 98th percentile of the daily 24-hr average PM2.5 concentrations. We did determine significant negative trends in the annual average of the daily 24-hr average PM2.5 concentrations at 6 of the 9 locations. Episodic, multi-day duration elevated PM2.5 concentrations related to forest fires were a significant influence on PM2.5 ambient concentrations. Annual 4th highest daily maximum 8-hr average O3 concentrations showed no trend at 14 of 18 locations, declined at 3 locations, and increased at one location. We determined statistically significant declines in peak and average NO2 and SO2 concentrations, and in time-integrated annual VOC concentrations.

OMI-based emission source classification in East China and its spatial redistribution in view of pollution control measures

This study aims to generate a satellite-based qualitative emission source characterization for the heavily polluted eastern part of China in the 2010–2016 time period. The applied source identification technique relies on satellite-based NOx and SO2 emission estimates by OMI, their SO2:NOx ratio, and the MIX anthropogenic emission inventory to distinguish emissions from different emission categories (urban, industrial, natural) and characterize the dominant source per 0.25° × 0.25° grid cell in East China. Overall, we find good agreement between the satellite- and emission inventory–based spatiotemporal distribution and characterization of the dominant emission sources in East China in 2010–2016. In 2010, the satellite measurements suggest an emission distribution less dominated by industrial areas, a somewhat larger role for urban/transportation areas and agricultural activities, and more natural emissions in the southern part compared to the bottom-up emission categorization. In 2016, more than half of the classified emission categories over East China have remained the same. At the same time, there is a notable increase of agricultural lands and decrease of areas dominated by industry/transportation in 2016, suggestive of an overall decrease in heavy air pollution in East China over the course of 7 years. This is likely attributed to the sustained efforts of the Chinese government to drastically improve the air quality, especially since 2013 when the National Air Pollution Prevention and Control Action Plan was enacted. However, signs of urban expansion (urbanization) and rural–urban migration (“Go West” motion) stemmed from China’s rapid economic growth and labour demand are evident; escalating industrialization (even with cleaner means) and the urban population growth in East China resulted in stronger emissions from sources representing consumption and transportation which are strongly related to NO2 and PM10 pollution (rather than SO2) and are directly influenced by the population size. This resulted to a shift of the emissions from the east mainly to the north and northwest of East China. Overall, although the effectiveness of the Chinese environmental control policies has been successful, the air pollution problem remains an important concern.

A261 INVESTIGATING THE RELATIONSHIP BETWEEN AIR POLLUTION AND BIOMARKERS OF CROHN’S DISEASE IN CANADA

Abstract Background The cause of Crohn's disease (CD) remains unclear. Studies suggest a potential connection between CD and air pollution, with a higher occurrence of CD found in areas with higher pollution levels. Aims Our study sought to explore this potential connection by investigating the relationship between components of air pollution and biomarkers indicative of CD risk. Methods In total, 2,256 healthy first-degree relatives of patients with CD were recruited as part of the CCC-GEM Project. We assessed baseline samples of gut permeability using the urinary fractional excretion ratio of lactulose-to-mannitol (LMR), subclinical inflammation via fecal calprotectin (FCP), and stool microbiome using 16S-rRNA sequencing. Air pollutant (n=8) concentrations were obtained from the National Air Pollution Surveillance Database. We used postal code to estimate air pollutant exposure via inverse distance weighting, averaging data for one (pollutant1-month), three (pollutant3-months), and twelve months (pollutant12-months) prior to recruitment. We used generalized estimating equation models to find associations between pollutant exposure and LMR, FCP, and microbiome composition, adjusting for age, sex, air pollutant seasonality, familial income, and familial relationships. Significance was set at pampersand:003C0.05, and false discovery rate (q) correction was applied to microbiome analysis. Results We observed a negative association between particulate matter (PMµg/m3), PM101-month, and PM103-months and LMR (β=-0.06[-0.09, -0.01], p=6.0×10-3 and β=-0.05[-0.07, -0.01], p=7.6×10-4), and a positive association between PM103-months and FCP (β=0.05[0.001, 0.10], p=0.04). 12-month pollutant exposure was associated with seven microbial taxa in a logit model. Notably, Carbon monoxide (CO)12-months was associated with Oscillospiraceae UCG_003 (β=3.49[1.53, 5.46], q=0.03). PM2512-months was associated with Marvinbryantia (β=0.12[0.06, 0.18], q=0.02). PM1012-months was associated with Moryella (β=0.07[0.03, 0.10], q=0.02). Nitrogen dioxide (NO)12-months was associated with Coprobacter and Ruminococcaceae UBA1819 (β=0.05[0.02, 0.07], q=0.03 and β=0.05[0.02, 0.08], q=0.04). NOX12-months was also associated with Ruminococcaceae_UBA1819 as well as Intestinimonas (β=0.03[0.01, 0.04], q=0.04 and β=0.03[0.01, 0.04], q=0.02). Conclusions Air pollutant exposure was associated with biomarkers of gut inflammation, barrier function, and microbiome composition. A shorter exposure (1/3 months) primarily affected FCP and LMR, while longer-term exposure (12 months) exerted a discernible impact on the microbiome. These findings suggest that exposure to air pollution may modulate the gut barrier function, inflammation, and the gut microbiome, biomarkers that are associated with the development of CD. Funding Agencies Crohn’s and Colitis Canada Genetics Environment Microbial (CCC-GEM) III, Leona M. and Harry B. Helmsley Charitable Trust, Dr. Croitoru is the recipient of the Canada Research Chair in Inflammatory Bowel Diseases

Source apportionment of PM2.5 in Montréal, Canada, and health risk assessment for potentially toxic elements

Abstract. Source apportionment of PM2.5 was performed using positive matrix factorization (PMF) based on detailed chemical composition data from 24 h filter samples collected over a 3-month period (August–November 2020) at an urban site in Montréal, a Canadian city with a population of approximately 4×106 people. This source apportionment study, which examined the main contributing sources to PM2.5 using a larger suite of organic molecular markers than other Canadian studies, is the first of its sort in Canada. A focus of this study was on quantifying previously unresolved sources of PM2.5 through the inclusion in the PMF analysis of additional organic molecular markers beyond those measured typically by the Canadian government's National Air Pollution Surveillance Program (NAPS). The organic species included in the PMF model were comprised of six n-alkanes, two fatty acids, one dicarboxylic acid, two biogenic secondary organic aerosol (SOA) tracers, and hopane. Secondary inorganic aerosols (SIAs) and SOAs were the dominant components and constituted 39 % of the measured PM2.5 mass, while the local primary anthropogenic sources, namely traffic exhaust, road dust, industrial, and cooking emissions, contributed 23 %. The chemical transport model GEOS-Chem revealed that ammonium sulfate concentrations in Montréal are strongly influenced by both local sources in Quebec and transboundary input from the United States, with the transboundary input exceeding the local emissions for SOA. Co and Cr(VI) presented an elevated cancer risk, highlighting that more attention should be given to these trace metals, which were associated with industrial emissions by the PMF analysis. Furthermore, the results showed that industrial emissions were minor contributors to the total PM2.5 mass concentration but were the largest contributors to Co and Cr(VI) concentrations. Thus, the health hazards associated with this source cannot be entirely established by the PM2.5 mass concentration alone. This study highlights that, when evaluating air quality in Montréal and other urban regions, the prioritization of sources for mitigation strategies will diverge if one considers total PM2.5 mass concentration or the concentration of individual particulate-bound contaminants. Furthermore, the large transboundary contribution from the United States to total PM2.5 levels suggests that future municipal, provincial, and federal monitoring and regulations would be more effective if they focus on specific high-risk contaminants (e.g., Co and Cr(VI) rather than total PM2.5).

Predicting Asthma Exacerbation Risk in the Adult South Korean Population Using Integrated Health Data and Machine Learning Models.

Asthma is a chronic inflammatory airway disease with significant burden; exacerbations can severely affect quality of life and healthcare costs. Advances in big data analysis and artificial intelligence have made it easier to predict future exacerbations more accurately. This study used an integrated dataset of Korean National Health Insurance, meteorological, air pollution, and viral data from national public databases to develop a model to predict asthma exacerbations on a daily basis in South Korea. We merged these sources and applied random forest, AdaBoost, XGBoost, and LightGBM machine learning models to compare their performances at predicting future exacerbations. Of the models, XGBoost (AUROC of 0.68 and accuracy of 0.96) and LightGBM (AUROC of 0.67 and accuracy of 0.96) were the most promising. Common important variables were the number of visits and exacerbations per year, and medical resource utilization, including the prescription of asthma medications. Comorbid diabetes, hypertension, gastroesophageal reflux, arthritis, metabolic syndrome, osteoporosis, and ischemic heart disease were also associated with elevated exacerbation risk. The models examined in this study highlight the importance of previous exacerbations, use of medical resources, and comorbidities in the prediction of future exacerbations in patients with asthma.

The impact of restriction measures implementation due to COVID-19 on particulate atmospheric pollution in Greek urban areas

In this work, the variation on the levels of suspended particulates, in Greek urban areas, was examined, for the period of the restrictive measures implementation (period 1: March to May 2020 and period 2: November 2020 to January 2021) due to the pandemic caused by the COVID-19 virus. The PM10 and PM2.5 concentrations are measured by the National Air Pollution Monitoring Network of Greece monitored by the Energy/Environment Ministry. In particular, a comparison of the PM10 and PM2.5 concentration levels was made, concerning the above time periods, with the corresponding atmospheric pollution levels during the periods 2001-2009 (period before the Greek economic crisis), 2010-2019 (period during the Greek economic crisis), as well as with the entire time period 2001-2019. The assessment showed a significant reduction in the levels of both PM10 concentrations, which ranged from 8% to 45%, and PM2.5 concentrations, which ranged from 13% to 48%, thus demonstrating the effectiveness of the control measures in improving air quality in Greek urban areas. The above findings show that with appropriate emission control strategies, vital improvements in the air environment of urban areas can be achieved.

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.

Environmental exposure and sensitization patterns in a Swiss alpine pediatric cohort

BackgroundThe level of environmental exposure throughout life may contribute to the prevalence of allergic sensitization and allergic disease. The alpine climate has been considered a healthy climate with little allergen exposure and pollution. We conducted a cross-sectional study to investigate local environmental exposure and concomitant prevalence of allergic sensitization among local school children born and raised in an alpine environment. MethodsClinical and demographic data were collected with a questionnaire. Allergen content was assessed in residential settled dust samples, lifetime exposure to pollen and air pollution was calculated using data from national pollen and air pollution monitoring stations, and the allergic sensitization profile was determined with component resolved diagnostics (ISAC®). Univariate and multivariate regression models were used to estimate the relation between exposure and sensitization. ResultsIn a cohort of children born and raised in an alpine environment, sensitization to aeroallergens is quite common (38%), especially to grass (33%) and cat (16%). House dust mite allergen was detected in up to 38% of residential dust samples, but sensitization to HDM was low (2.5%). Pollutant levels were low, but an increasing trend was observed in the amount of ozone and PM10. Living close to a busy road was associated with increased odds OR (95% CI) for being sensitized to any allergen 2.7 (1.0–7.2), to outdoor allergens 2.8 (1.1–7.1) and being sensitized plus reporting symptoms of rhinoconjunctivitis 4.4 (1.3–14.8) and asthma 5.5 (1.4–21). Indoor living conditions, including the presence of visible mold, increased the odds of being sensitized to indoor allergens (1.9 (1.1–3.2) and being sensitized plus reporting symptoms of rhinoconjunctivitis 1.9 (1.0–3.6) and asthma 2.1 (1.0–4.1). ConclusionIn a healthy alpine environment, pollution might still be an important factor contributing to allergic sensitization.

Quantifying national household air pollution (HAP) exposure to PM2.5 in rural and urban areas

According to WHO (World Health Organization), in 2020, 14% of people in global urban areas relied on polluting solid fuels and technologies, compared with 52% of the rural population. The health impacts of such inequality are massive. It was estimated that 3.2 million premature deaths per year (2020), particularly in low-income and middle-income countries due to household air pollution (HAP). Several studies provide estimates of the exposure to fine particulate matter (PM2.5) from household air pollution (HAP-PM2.5) for users of different fuel/cookstove types in rural and urban areas. However, hardly any studies estimate the population-weighted exposure to HAP-PM2.5 at the global scale. A Bayesian hierarchical model was developed to estimate PM2.5 exposure coefficients and their uncertainties for an annual average of HAP-PM2.5 personal exposure. The predicted HAP-PM2.5 exposure at the user level was used to estimate the national-level exposure for the population living in urban and rural areas. The results suggest that switching from polluting solid fuels (biomass, charcoal, coal) to cleaner fuels (gas and electricity) for heating and cooking can potentially reduce the national-level HAP-PM2.5 personal exposure on average by 53%. However, there exists a significant disparity between rural and urban areas, partly reflecting inequality in energy access. More specifically, switching from polluting solid fuels for heating and cooking to cleaner fuels can reduce the personal exposure to HAP-PM2.5 in rural areas by 54% and in urban areas by 38%. The study indicates that increased access to clean fuels and improved stove interventions are needed to achieve the goals of universal energy access and equality between urban and rural areas.

The Influence of Soil Physical Properties on the Load Factor for Agricultural Tractors in Different Paddy Fields

The load factor (LF) of a tractor represents the ratio of actual engine power and rated engine power, and is an important indicator directly used in calculating national air pollutant emissions. Currently, in the Republic of Korea, a fixed value of 0.48 is used for the LF regardless of the working conditions, making it difficult to establish a reliable national air pollutant inventory. Since tractors perform work under soil conditions, soil physical properties directly affect the tractor LF. Therefore, it is expected that more accurate LF estimation will be possible by utilizing soil physical properties. This study was conducted to assess the impact of soil physical properties on the LF. Experimental data were collected in ten different soil conditions. Correlation analysis revealed that the LF exhibited strong correlations with SMC, soil texture, and CI, in that order. The coefficient of determination for the regression model developed using soil variables ranged from 0.678 to 0.926. The developed regression models generally showed higher accuracy when utilizing multiple soil variables, as compared to using a single soil variable. Therefore, an effective estimation of the LF through non-experimental methods can be achieved by measuring various soil properties.

Influence of aerosol acidity and organic ligands on transition metal solubility and oxidative potential of fine particulate matter in urban environments

The adverse health effects of air pollution around the world have been associated with the inhalation of fine particulate matter (PM2.5). Such outcomes are thought to be related to the induction of oxidative stress due to the excess formation of reactive oxygen species (ROS) in the respiratory and cardiovascular systems. The ability of airborne chemicals to deplete antioxidants and to form ROS is known as oxidative potential (OP). Here we studied the influence of aerosol acidity and organic ligands on the solubility of transition metals, in particular iron (Fe) and copper (Cu), and on the OP of PM2.5 from Canadian National Air Pollution Surveillance urban sites in Toronto, Vancouver, and Hamilton. Using chemical assays and model simulations of the lung redox chemistry, we quantified ROS formation in the lung lining fluid, targeting superoxide anion (O2•-), hydrogen peroxide (H2O2), and hydroxyl radical (•OH), as well as the PM2.5 redox potential (RP). Experimental •OH formation (OPOH) showed high correlations with RP and model-predicted ROS metrics. Both aerosol acidity and oxalate content enhanced the solubility of transition metals, with oxalate showing a stronger association. While experimental OP metrics were primarily associated with species of primary origin such as elemental carbon, Fe, and Cu, model-predicted ROS were associated with secondary processes including proton- and ligand-mediated dissolution of Fe. Model simulations showed that water-soluble Cu was the main contributor to O2•- formation, while water-soluble Fe dominated the formation of highly reactive •OH radical, particularly at study sites with highly acidic aerosol and elevated levels of oxalate. This study underscores the importance of reducing transition metal emissions in urban environments to improve population health.

Nitrogen dioxide spatiotemporal variations in the complex urban environment of Athens, Greece

In this study, five years of total, tropospheric and near-surface nitrogen dioxide, ΝΟ2, observations from a Pandora spectrometer system routinely operating in the city center of Athens, Greece, are presented and compared with space-borne observations from the S5P/TROPOMI sensor and in-situ air quality monitoring station measurements from the Greek National Air Pollution Monitoring Network. Each of the three different systems exhibits its own monitoring capabilities and restrictions, based on the spatial representativeness and temporal resolution of its measurements. However, they all reveal a clear weekly pattern with low NO2 concentrations on Sundays while a diurnal cycle with higher levels of NO2 in the morning is observed from the ground due to the high NOx emissions from heavy traffic in the urban environment. A seasonal pattern is further demonstrated by both space- and ground-based remote sensing instruments with enhanced NO2 loadings in wintertime and decreased levels in summertime. Even though, as expected, S5P/TROPOMI appears to underestimate the tropospheric NO2 load, the correlation between the ground-based and space-borne data is relatively high, with corresponding correlation coefficients ranging between 0.73 in spring and 0.80 in winter. High correlations are also found between the relatively new near-surface NO2 product of Pandora and the in situ observations, ranging from 0.91 to 0.99. However, an underestimation is observed by the Pandora instrument compared to those in situ monitoring stations which are highly affected by the increased NOx emissions in the city center. For the Pandora near-surface NO2 at 0° (north) azimuthal viewing angle, the best agreement is found with the urban background in situ stations, with a negative bias at 0.99 ± 1.60 × 1011 molecules cm−3, whereas the Pandora retrievals at 39° (north-east) are closer to the urban in situ NO2 levels, with a bias of −1.10 ± 2.02 × 1011 molecules cm−3 on average.

Emissions leakage embodied in inter-provincial trade brings unexpected air quality and health benefits

Inter-provincial trade can bring “emission leakage”, and consequently influence the air quality and public health. However, there has been a lack of systematic research on air pollution and public health related to emission leakage embodied in inter-provincial trade of China. Here, we systematically evaluated for the first time the influence of emission leakage on national air pollution and related premature deaths in 2012 of China. Unexpected opposite influences of emission leakage on emission and air quality/public health were discovered. Emission leakage embodied in inter-provincial trade in 2012 of China led to an increase of 1.4 % to 4.8 % in national air pollutant emissions, but a decrease of 1.5 % (−0.8 μg·m−3) in population-weighted concentration of PM2.5, while avoiding 1.1 % (−1.4 × 104 people) of premature deaths. Therefore, to reveal the intrinsic mechanism of this opposite influences, we proposed two coefficients, the Concentration per unit primary PM2.5 emission (CPE, unit: μg·m−3/t) and the Death per unit primary PM2.5 emission (DPE, unit: people/t), to characterize the response of air quality and health to emission leakage embodied in inter-provincial trade. Statistical analysis indicated that both the above coefficients showed significant negative correlation (P < 0.05) with provincial PM2.5 emissions changes. The findings offer a means of adjustment and its related evaluation parameters for the emission transfer caused by inter-provincial trade, thereby contributing to further improvement environmental and health benefits through inter-provincial trade.

A Study on the Comparison of Areas Near Gunsan according to the Revision of the National Air Pollutant Emissions (CAPSS) in 2020

A Study on the Comparison of Areas Near Gunsan according to the Revision of the National Air Pollutant Emissions (CAPSS) in 2020

A baseline characterization of fine particulate matter (PM2.5) concentration and releases in Nova Scotia, Canada

Three industrial facilities (a kraft pulp mill, a tire manufacturing, and a coal-fired power generation plant), have operated in Pictou County, Nova Scotia, Canada for more than 50 years. The local population, including an Indigenous community, has raised concerns for several decades about the environmental and human health impacts of local air and effluent pollution. Numerous studies have reported negative air, water, sediment, and ecological and human health impacts in the region. However, previous studies mainly focused on wastewater effluent discharge from the kraft pulp mill, with only a few studies focused on air pollution. These limited air pollution studies pointed out the pulp mill as the primarily responsible for local emissions of fine particulate matter (PM2.5), but with high levels of uncertainty. This study analyzed hourly and daily PM2.5 concentrations measured at an air quality monitoring station in Pictou (part of the National Air Pollution Surveillance [NAPS] network) between 2004 and 2021. For events of high PM2.5 concentrations (which occurred predominantly in April and May in 2014 and 2015), air masses were tracked using the HYSPLIT model to evaluate if long-range transboundary pollution could have contributed to PM2.5 concentration. Results suggest that the pulp mill was likely the primary source of high PM2.5 concentrations recorded at the Pictou NAPS station. Measured PM2.5 concentrations only met the desirable air quality management concentrations after the pulp mill installed a recovery boiler electrostatic precipitator in October 2015 to reduce PM2.5 emissions.