Ambient Pollutant Concentrations Research Articles

Rapid detection of high-emitting vehicles by on-road remote sensing technology improves urban air quality.

Vehicle emissions are the most important source of air pollution in the urban environment worldwide, and their detection and control are critical for protecting public health. Here, we report the use of on-road remote sensing (RS) technology for fast, accurate, and cost-effective identification of high-emitting vehicles as an enforcement program for improving urban air quality. Using large emission datasets from chassis dynamometer testing, RS, and air quality monitoring, we found that significant percentages of in-use petrol and LPG vehicles failed the emission standards, particularly the high-mileage fleets. The RS enforcement program greatly cleaned these fleets, in terms of high-emitter percentages, fleet average emissions, roadside and ambient pollutant concentrations, and emission inventory. The challenges of the current enforcement program are conservative setting of cut points, single-lane measurement sites, and lack of application experience in diesel vehicles. Developing more accurate and vertical RS systems will improve and extend their applications.

Evaluating the Utility of High-Resolution Spatiotemporal Air Pollution Data in Estimating Local PM2.5 Exposures in California from 2015–2018

Air quality management is increasingly focused not only on across-the-board reductions in ambient pollution concentrations but also on identifying and remediating elevated exposures that often occur in traditionally disadvantaged communities. Remote sensing of ambient air pollution using data derived from satellites has the potential to better inform management decisions that address environmental disparities by providing increased spatial coverage, at high-spatial resolutions, compared to air pollution exposure estimates based on ground-based monitors alone. Daily PM2.5 estimates for 2015–2018 were estimated at a 1 km2 resolution, derived from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in order to assess the utility of highly refined spatiotemporal air pollution data in 92 California cities and in the 13 communities included in the California Community Air Protection Program. The identification of pollution hot-spots within a city is typically not possible relying solely on the regulatory monitoring networks; however, day-to-day temporal variability was shown to be generally well represented by nearby ground-based monitoring data even in communities with strong spatial gradients in pollutant concentrations. An assessment of within-ZIP Code variability in pollution estimates indicates that high-resolution pollution estimates (i.e., 1 km2) are not always needed to identify spatial differences in exposure but become increasingly important for larger geographic areas (approximately 50 km2). Taken together, these findings can help inform strategies for use of remote sensing data for air quality management including the screening of locations with air pollution exposures that are not well represented by existing ground-based air pollution monitors.

Impact of Corona Virus Stay-at-Home Policies on Traffic Emissions and Ambient Pollutant Concentrations in Ghana, West Africa

Impact of Corona Virus Stay-at-Home Policies on Traffic Emissions and Ambient Pollutant Concentrations in Ghana, West Africa

Effects of short-term increases in personal and ambient pollutant concentrations on pulmonary and cardiovascular function: A panel study analysis of the Multicenter Ozone Study in oldEr subjects (MOSES 2)

BackgroundThe cardiovascular effects of ozone exposure are unclear. Using measurements from the 87 participants in the Multicenter Ozone Study of oldEr Subjects (MOSES), we examined whether personal and ambient pollutant exposures before the controlled exposure sessions would be associated with adverse changes in pulmonary and cardiovascular function. MethodsWe used mixed effects linear regression to evaluate associations between increased personal exposures and ambient pollutant concentrations in the 96 h before the pre-exposure visit, and 1) biomarkers measured at pre-exposure, and 2) changes in biomarkers from pre-to post-exposure. ResultsDecreases in pre-exposure forced expiratory volume in 1 s (FEV1) were associated with interquartile-range increases in concentrations of particulate matter ≤2.5 μm (PM2.5) 1 h before the pre-exposure visit (−0.022 L; 95% CI -0.037 to −0.006; p = 0.007), carbon monoxide (CO) in the prior 3 h (−0.046 L; 95% CI -0.076 to −0.016; p = 0.003), and nitrogen dioxide (NO2) in the prior 72 h (−0.030 L; 95% CI -0.052 to −0.008; p = 0.007). From pre-to post-exposure, increases in FEV1 were marginally significantly associated with increases in personal ozone exposure (0.010 L; 95% CI 0.004 to 0.026; p = 0.010), and ambient PM2.5 and CO at all lag times. Ambient ozone concentrations in the prior 96 h were associated with both decreased pre-exposure high frequency (HF) heart rate variability (HRV) and increases in HF HRV from pre-to post-exposure. ConclusionsWe observed associations between increased ambient PM2.5, NO2, and CO levels and reduced pulmonary function, and increased ambient ozone concentrations and reduced HRV. Pulmonary function and HRV increased across the exposure sessions in association with these same pollutant increases, suggesting a “recovery” during the exposure sessions. These findings support an association between short term increases in ambient PM2.5, NO2, and CO and decreased pulmonary function, and increased ambient ozone and decreased HRV.

High-resolution modeling of the distribution of surface air pollutants and their intercontinental transport by a global tropospheric atmospheric chemistry source–receptor model (GNAQPMS-SM)

Abstract. Many efforts have been devoted to quantifying the impact of intercontinental transport on global air quality by using global chemical transport models with horizontal resolutions of hundreds of kilometers in recent decades. In this study, a global online air quality source–receptor model (GNAQPMS-SM) is designed to effectively compute the contributions of various regions to ambient pollutant concentrations. The newly developed model is able to quantify source–receptor (S-R) relationships in one simulation without introducing errors by nonlinear chemistry. We calculate the surface and planetary boundary layer (PBL) S-R relationships in 19 regions over the whole globe for ozone (O3), black carbon (BC), and non-sea-salt sulfate (nss-sulfate) by conducting a high-resolution (0.5∘ × 0.5∘) simulation for the year 2018. The model exhibits a realistic capacity in reproducing the spatial distributions and seasonal variations of tropospheric O3, carbon monoxide, and aerosols at global and regional scales – Europe (EUR), North America (NAM), and East Asia (EA). The correlation coefficient (R) and normalized mean bias (NMB) for seasonal O3 at global background and urban–rural sites ranged from 0.49 to 0.87 and −2 % to 14.97 %, respectively. For aerosols, the R and NMB in EUR, NAM, and EA mostly exceed 0.6 and are within ±15 %. These statistical parameters based on this global simulation can match those of regional models in key regions. The simulated tropospheric nitrogen dioxide and aerosol optical depths are generally in agreement with satellite observations. The model overestimates ozone concentrations in the upper troposphere and stratosphere in the tropics, midlatitude, and polar regions of the Southern Hemisphere due to the use of a simplified stratospheric ozone scheme and/or biases in estimated stratosphere–troposphere exchange dynamics. We find that surface O3 can travel a long distance and contributes a non-negligible fraction to downwind regions. Non-local source transport explains approximately 35 %–60 % of surface O3 in EA, South Asia (SAS), EUR, and NAM. The O3 exported from EUR can also be transported across the Arctic Ocean to the North Pacific and contributes nearly 5 %–7.5 % to the North Pacific. BC is directly linked to local emissions, and each BC source region mainly contributes to itself and surrounding regions. For nss-sulfate, contributions of long-range transport account for 15 %–30 % within the PBL in EA, SAS, EUR, and NAM. Our estimated international transport of BC and nss-sulfate is lower than that from the Hemispheric Transport of Air Pollution (HTAP) assessment report in 2010, but most surface O3 results are within the range. This difference may be related to the different simulation years, emission inventories, vertical and horizontal resolutions, and S-R revealing methods. Additional emission sensitivity simulation shows a negative O3 response in receptor region EA in January from EA. The difference between two methods in estimated S-R relationships of nss-sulfate and O3 are mainly due to ignoring the nonlinearity of pollutants during chemical processes. The S-R relationship of aerosols within EA subcontinent is also assessed. The model that we developed creates a link between the scientific community and policymakers. Finally, the results are discussed in the context of future model development and analysis opportunities.

The deleterious effects induced by an acute exposure of human skin to common air pollutants are prevented by extracts of Deschampsia antarctica

The homeostatic and regenerative potential of the skin is critically impaired by an increasing accumulation of air pollutants in human ecosystems. These toxic compounds are frequently implicated in pathological processes such as premature cutaneous ageing, altered pigmentation and cancer. In this scenario, innovative strategies are required to tackle the effects of severe air pollution on skin function. Here we have used a Human Skin Organotypic Culture (HSOC) model to characterize the deleterious effects of an acute topic exposure of human skin to moderately high concentrations of common ambient pollutants, including As, Cd, Cr, dioxins and tobacco smoke. All these toxic compunds inflict severe damage in the tissue, activating the AHR-mediated response to xenobiotics. We have further evaluated the potential of an aqueous leaf extract of the polyextremophile plant Deschampsia antarctica (Edafence) to protect human skin against the acute exposure to toxic pollutants. Our results indicate that pre-treatment of HSOC samples with this aqueous extract conuterbalances the deleterious effects of the exposure to toxic comunds and triggers the activation of key genes invoved in the redox system and in the pro-inflammatory/wound healing response in the skin, suggesting that this natural compound might be effectively used in vivo to protect human skin routinely in different daily conditions.

Multi-pollutant urban study on acute respiratory hospitalization and mortality attributable to ambient air pollution in Canada for 2001–2012

Humans inhale a mixture of various air pollutants, and there is ambiguity whether these pollutants act independently or in an additive, synergistic, or antagonistic manner. We aimed to examine differences in adverse health effects of short-term exposure to air pollution through single-versus multi-pollutant models. We collected daily ambient air pollutants (O3, NO2 and PM2.5) concentrations from 24 Canadian urban centers from 2001 to 2012. We examined between-pollutant correlations and estimated their associations with respiratory hospitalization and mortality. We applied a generalized quasi-Poisson model to each city adjusting for one and/or two pollutants. Then we employed a Bayesian hierarchical model to pool the city-specific estimates for national estimates. We also examined 0- to 6-day air pollutant lagged effects by season. Overall, we found more frequently significant effects from single-pollutant models (vs. multi-pollutant models), for hospitalization (vs. mortality), for O3 (vs. NO2, PM2.5), for warm (vs. cold) season, and for lags ≤2 days (vs. 3–6 days). The most consistent effects appeared on respiratory hospitalization for 1-day lagged O3 and PM2.5, but not NO2. This study found little additive or antagonistic risk of respiratory health outcomes from multi-pollutant models due to low-to-medium correlations among the specified air pollutants.

Using Satellite Data for Environmental Justice Efforts in California

BACKGROUND AND AIM: Air quality management is increasingly focused not only on across-the-board reductions in ambient pollution concentrations, but also on identifying and remediating elevated exposures that often occur in traditionally disadvantaged communities. Remote sensing of ambient air pollution using data derived from satellites has the potential to better inform management decisions that address environmental disparities by providing increased spatial coverage, at high spatial resolutions, compared to air pollution exposure estimates based on ground monitors alone. METHODS: Daily PM₂.₅ estimates for 2015-2018 were estimated at a 1 km² resolution, derived from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, and compared to federal ground monitors in order to assess the utility of highly-refined spatiotemporal air pollution data in the 13 communities included in the California Community Air Protection Program. RESULTS:Results suggest that regulatory monitoring networks are unable to identify pollution hotspots within these communities without the addition of high-resolution satellite data. However, day-to-day temporal variability is generally well represented by nearby ground-based monitoring data even in communities with strong spatial gradients in pollutant concentrations. CONCLUSIONS:These findings can help inform strategies for use of remote sensing data in environmental justice efforts including the screening of locations with air pollution exposures that are not well-represented by existing ground-based air pollution monitors. KEYWORDS: Air Pollution, Environmental Disparities, Environmental Justice, Exposure Assessment, Particulate Matter

Air of Uncertainty from Pollution Profiteers: Status of Ambient Air Quality of Sawmill Industry in Ilorin Metropolis, Kwara State, Nigeria

We can’t stop breathing, but we can do something about the quality of air that we breathe. Clean fresh air is indispensable ingredient for a good life quality. Individuals poses the right towards expecting that the breathed air will not harm people. Thus, fighting air pollution will not only improve health outcomes, productivity, and well-being, it’s also essential toward reducing the emissions of greenhouse gas as well as fighting climate change. For examples, a third of the global population is at risk from unhealthy of ambient air pollutants concentrations, with the loss of approximately 6.4 million healthy-life-years attributed specifically to chronic exposure to ambient particulate matter. Expert panels have consistently rated air pollution as a greater health hazard than water pollution. Pollution of air is the leading source of unexplained and undiagnosed diseases, besides have remained associated with a variety of serious human health risks, and in fact, a threshold has not been established under which these pollutants exert no adverse effects. This study evaluates ambient air quality at major sawmill sites in Ilorin Metropolis, Kwara State, Nigeria. “Measurements of Air pollution were accurately carried out using direct reading, automatic in situ gas monitors; Hand held mobile multi-gas monitor with model AS8900 [Combustible (LEL), and Oxygen (O2)], BLATN with model BR – Smart Series air quality monitor (PM10, Formaldehyde) and air quality multimeter with model B SIDE EET100 (Dust (PM2.5), VOC, Temperature and Relative Humidity)”. The outcomes disclosed among others, the average concentrations of CO, O2 as well as other measured parameters for instance formaldehyde (HcHo) etc., they are also consistently low as well as within acceptable range in terms of National as well as Global monitoring standards for air quality indices. However, there are few exceptions for instance the average volatile organic compounds (VOCs) concentrations, PM2.5, PM10 as well as Combustible (LEL) respectively, which are higher when compared to National and Global standards. This high figure is due to pollutant amount existing in the sawmills air environment resulting from input of influents from activities of the sawmill. However, as a result, air pollution in the city of Ilorin is found to be increasingly polluted and are of major health concern because of their synergistic action. Due to the high evidences and values, it can lead to a remarkable rise in over-all figure of hospital visits/ patients’ admissions with acute respiratory illnesses as soon as air pollutants level remained high. Hence, there is the need for an aggressive control of ambient air pollution.

Assessment of air pollution status during COVID-19 lockdown (March-May 2020) over Bangalore City in India.

The coronavirus disease 2019 (COVID-19), which became a global pandemic by March 2020, forced almost all countries over the world to impose the lockdown as a measure of social distancing to control the spread of infection. India also strictly implemented a countrywide lockdown, starting from 24 March to 12 May 2020. This measure resulted in the reduction of the sources of air pollution in general: industrial, commercial, and vehicular pollution in particular, with visible improvement in ambient air quality. In this study, the impact of COVID-19 lockdown on the ambient concentration of air pollutants over the city of Bangalore (India) is assessed using Continuous Ambient Air Quality Measurement (CAAQM) data from 10 monitoring stations spread across the city. The data was obtained from Central Pollution Control Board (CPCB) and Karnataka State Pollution Control Board (KSPCB). The analysis of the relative changes in the ambient concentration of six major air pollutants (NO, NO2, NOX, PM2.5, O3, and SO2) has been carried out for two periods: March–May 2020 (COVID-19 lockdown) and the corresponding period of 2019 during when there was no lockdown. The analysis revealed significant reduction in the concentration of ambient air pollutants at both daily and monthly intervals. This can be attributed to the reduction in sources of emission; vehicular traffic, industrial, and other activities. The average reduction in the concentration of NO, NO2, NOX, PM2.5, and O3 between 01 March and 12 May 2020 was found to be 63%, 48%, 48%, 18%, and 23% respectively when compared to the same period in 2019. Similarly, the comparative analysis of pollutant concentrations between pre-lockdown (01–23 March 2020) and lockdown (24 March–12 May 2020) periods has shown a huge reduction in the ambient concentration of air pollutants, 47.3% (NO), 49% (NO2), 49% (NOX), 10% (SO2), 37.7% (PM2.5), and 15.6% (O3), resulting in improved air quality over Bangalore during the COVID-19 lockdown period. It is shown that the strict lockdown resulted in a significant reduction in the pollution levels. Such lockdowns may be useful as emergency intervention strategies to control air pollution in megacities when ambient air quality deteriorates dangerously.

Ambient air quality data reported at Sasol Secunda monitoring stations during COVID-19 lockdown – Mpumalanga, South Africa

Various local and international research has been published on the effects of COVID-19 lockdown on ambient air quality. In most cases, a reduction in ambient NOx and PM concentrations have been observed with varying changes in ambient SO2 levels. Secunda, located in the Highveld Priority Area in Mpumalanga, South Africa is known for its large industrial facilities utilising coal as primary feedstock. The towns of Secunda and eMbalenhle provide the majority of the workforce to Sasol and has therefore been the focus of this study. The ambient air quality in the Secunda region was assessed due to the changes in human behaviour during lockdown, familiarity with the Sasol facility and the strategic locations of ambient air quality stations.Results show a clear decrease in ambient CO, NO2 and PM concentrations, especially during the first two weeks of lockdown. Only subtle changes were observed for ambient H2S and SO2 pollutant concentrations at the ambient monitoring stations. An increasing trend in all ambient species was observed towards the end and post lockdown, in contrast to declining ambient temperatures with the onset of winter. This is also contrary to the reduction in emissions from the factory that conducted annual maintenance in the month following lockdown (phase shutdown). This article concludes that human behaviour has a material local ambient impact on CO, NO2 and PM pollutant species, while H2S concentration profiles are more directly related to the industrial complex’s levels of activity. Ambient SO2 trends did not show a similar correlation with the facility’s activities (as H2S), but a stronger correlation was observed with the diverse local and regional sources in close proximity to Secunda and eMbalenhle. The influence of better dispersion especially on a local scale, brought about by more effective emission heights, is considered material. Moreover, meteorological factors, on local air quality, has been shown to be a material contributor to observed ambient air quality levels in the study domain

Comparison of air pollutants and their health effects in two developed regions in China during the COVID-19 pandemic

Air pollution attributed to substantial anthropogenic emissions and significant secondary formation processes have been reported frequently in China, especially in Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD). In order to investigate the aerosol evolution processes before, in, and after the novel coronavirus (COVID-19) lockdown period of 2020, ambient monitoring data of six air pollutants were analyzed from Jan 1 to Apr 11 in both 2020 and 2019. Our results showed that the six ambient pollutants concentrations were much lower during the COVID-19 lockdown due to a great reduction of anthropogenic emissions. BTH suffered from air pollution more seriously in comparison of YRD, suggesting the differences in the industrial structures of these two regions. The significant difference between the normalized ratios of CO and NO2 during COVID-19 lockdown, along with the increasing PM2.5, indicated the oxidation of NO2 to form nitrate and the dominant contribution of secondary processes on PM2.5. In addition, the most health risk factor was PM2.5 and health-risked based air quality index (HAQI) values during the COVID-19 pandemic in YRD in 2020 were all lower than those in 2019. Our findings suggest that the reduction of anthropogenic emissions is essential to mitigate PM2.5 pollution, while O3 control may be more complicated.

Mass dose rates of particle-bound organic pollutants in the human respiratory tract: Implications for inhalation exposure and risk estimations.

To date, little is known about the effective doses of airborne particulate matter (PM) and PM-bound hazardous organic components to the human respiratory tract (HRT). In the light of this, here we provide particle mass dose rates (dose per hour of exposure) of PM and a suite of PM-bound hazardous organic compounds in the HRT for two population age groups (adults & children). More specifically, the mass dose rates of PM and PM-bound polycyclic aromatic hydrocarbons (PAHs), nitrated-PAH (NPAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polybrominated diphenyl ethers (PBDEs) were estimated at two urban sites using a multiple path particle dosimetry model. We find that, in most cases, the total mass doses are following similar variations across sites and seasons as their ambient total concentrations, however their distribution in the HRT is a function of the particle size distributions and the physiological parameters of each age group. More specifically, the majority of the deposited mass of PM and all the chemical components investigated was accumulated in the upper airways instead of the lungs. We further show that children, due to their different physiology, are more susceptible and receive larger fraction of the total mass doses in the deepest parts of the lungs compared to the adults' group. Comparing the traditional method for estimating the inhalation risk, which is based on the ambient concentration of pollutants, and a modified version using the mass dose in the HRT, we find that the former may overestimate the reported risks. The results presented here provide a novel dataset composed by previously undetermined doses of hazardous airborne particulate organic components in the HRT and demonstrate that alternative health risk estimation approaches may capture some variabilities that are traditionally overlooked.

Ambient air pollution and emergency department visits in Toronto, Canada

To investigate the acute impact of various air pollutants on various disease groups in the urban area of the city of Toronto, Canada. Statistical models were developed to estimate the relative risk of an emergency department visit associated with ambient air pollution concentration levels. These models were generated for 8 air pollutants (lagged from 0 to 14 days) and for 18 strata (based on sex, age group, and season). Twelve disease groups extracted from the International Classification of Diseases 10th Revision (ICD-10) were used as health classifications in the models. The qualitative results were collected in matrices composed of 18 rows (strata) and 15 columns (lags) for each air pollutant and the 12 health classifications. The matrix cells were assigned a value of 1 if the association was positively statistically significant; otherwise, they were assigned to a value of 0. The constructed matrices were totalized separately for each air pollutant. The resulting matrices show qualitative associations for grouped diseases, air pollutants, and their corresponding lagged concentrations and indicate the frequency of statistically significant positive associations. The results are presented in colour-gradient matrices with the number of associations for every combination of patient strata, pollutant, and lag in corresponding cells. The highest number of the associations was 8 (of 12 possible) obtained for the same day exposure to carbon monoxide, nitrogen dioxide, and days with elevated air quality health index (AQHI) values. For carbon monoxide, the number of the associations decreases with the increasing lags. For this air pollutant, there were almost no associations after 8 days of lag. In the case of nitrogen dioxide, the associations persist even for longer lags. The numerical values obtained from the models are provided for every pollutant. The constructed matrices are a useful tool to analyze the impact of ambient air pollution concentrations on public health.

The Association between Air Pollution and COVID-19 Related Mortality in Santiago, Chile: A Daily Time Series Analysis

Background: Exposure to ambient air pollution is a risk factor for morbidity and mortality from lung and heart disease.Research Question: Does short term exposure to ambient air pollution concentration influence COVID-19 related mortality? Study Design and Methodology: Using time series analyses we tested the association between daily changes in air pollution measured by stationary monitors in and around Santiago, Chile and deaths from laboratory confirmed or suspected COVID-19 between March 16 and August 31, 2020. Results were adjusted for temporal trends, temperature and humidity, and stratified by age and sex.Results: There were 10,069 COVID-19 related deaths of which 7,659 were laboratory confirmed. For an unlagged interquartile range (IQR) increase in CO, NO2 and PM2.5 the relative mortality risk (RR) estimates (95% CI) were 1.058 (1.031, 1.085), 1.063 (1.029, 1.098) and 1.061 (1.036, 1.085), respectively. There were no significant differences in RR by sex, but RR generally increased with age. In those at least 85 years old, an IQR increase in NO2 was associated with a 12.7% (95% CI 4.2, 22.2) increase in daily mortality.Interpretation: This study provides evidence that daily increases in air pollution increase the risk of dying from COVID-19, especially in the elderly.Funding Statement: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectorsDeclaration of Interests: All authors have no competing financial interests.Ethics Approval Statement: The data were collected for administrative purposes, and were provided with no personal identifiers; hence, the present study was exempt from review by the Health Canada Research Ethics Board.

Did the COVID-19 lockdown in Delhi and Kolkata improve the ambient air quality of the two cities?

To control the spread of COVID-19, the government of India imposed a nationwide lockdown on all nonessential activities from 22 Mar. to 3 May 2020. Daily ambient particulate matter ≤10 μm in diameter (PM10 ), particulate matter ≤2.5 μm in diameter (PM2.5 ), NO, NO2 , and O3 concentrations in Delhi and Kolkata from 1 March to 3 May in both 2019 and 2020 were collected from different monitoring stations along with meteorological data to study the impact of the COVID-19 lockdown on ambient pollutant concentrations. In 2020, average ambient concentrations of PM10 and PM2.5 were significantly decreased (Delhi: 59 and 43%, respectively; Kolkata: 49 and 50%, respectively) during the lockdown period compared with the same period during 2019 in both cities. Average ambient O3 concentration in Delhi was significantly lower in 2020 (38.5μg m-3 ) compared with 2019 (44.7μg m-3 ) during the study period. However, average ambient O3 concentration was significantly higher during 2020 (46.9μg m-3 ) compared with 2019 (31.4μg m-3 ) in Kolkata. Effect size analysis of different predictive variables reveals that the lockdown period explains maximum variation in ambient concentrations of PM10 and PM2.5 during 2020 in both cities. However, maximum variation in ambient O3 concentrations in both cities was explained primarily by spatial variation rather than by the lockdown period. This study suggests that major policy implementation related to the transport and industrial sectors that aims to address the ambient air pollution problem in India may reduce the ambient particulate matter concentrations, although it may not have a significant effect on other ambient air pollutants such as O3 in major Indian cities.

Ambient marine shipping emissions determined by vessel operation mode along the East China Sea

Marine shipping emissions exert important air quality and climate impacts. This study characterized the ambient pollutants predominant by emissions from a variety of marine vessel types near the mid-latitude East China Sea. Two discernible primary shipping emissions were identified by factorization analysis on detailed mass spectra of organic aerosol (OA), as emissions in maneuvering and cruise, highly linked with NOx (and less oxidized OA, black carbon, BC) or CO (and more oxidized OA), respectively. Using radio-recorded quantities and activities of 3566 vessels mixed with slow and high-speed diesel engines, we found emission of NOx or BC per vessel was positively correlated with vessel speed, while CO emission peaked at moderate speed. The approach here based on vessel operation mode directly linked the vessel activities to ambient concentrations of pollutants from marine shipping emission, and may synthesize the complex vessel types in shipping emission inventory.

Effects of short-term exposure to ambient airborne pollutants on COPD-related mortality among the elderly residents of Chengdu city in Southwest China

BackgroundChronic obstructive pulmonary disease (COPD) has become a severe global burden in terms of both health and the economy. Few studies, however, have thoroughly assessed the influence of air pollution on COPD-related mortality among elderly people in developing areas in the hinterland of southwestern China. This study is the first to examine the association between short-term exposure to ambient airborne pollutants and COPD-related mortality among elderly people in the central Sichuan Basin of southwestern China.MethodsData on COPD-related mortality among elderly people aged 60 and older were obtained from the Population Death Information Registration and Management System (PDIRMS). Data on airborne pollutants comprised of particulate matter < 2.5 μm in aerodynamic diameter (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were derived from 23 municipal environmental monitoring sites. Data on weather conditions, including daily mean temperature and relative humidity, were obtained from the Chengdu Meteorological Bureau. All data were collected from January 1, 2015, to December 31, 2018. A quasi-Poisson general additive model (GAM) was utilized to assess the effects of short-term exposure to airborne pollutants on COPD-related mortality among elderly people.ResultsA total of 61,058 COPD-related deaths of people aged 60 and older were obtained. Controlling the influences of daily temperature and relative humidity, interquartile range (IQR) concentration increases of PM2.5 (43 μg/m3), SO2 (8 μg/m3), NO2 (18 μg/m3), CO (0.4 mg/m3), and O3 (78 μg/m3) were associated with 2.7% (95% CI 1.0–4.4%), 4.3% (95% CI 2.1–6.4%), 3.6% (95% CI 1.7–5.6%), 2.7% (95% CI 0.6–4.8%), and 7.4% (95% CI 3.6–11.3%) increases in COPD-related mortality in people aged 60 and older, respectively. The exposure-response curves between each pollutant and the log-relative risk of COPD-related mortality exhibited linear relationships. Statistically significant differences in the associations between pollutants and COPD-related mortality were not observed among sociodemographic factors including age, gender, and marital status. The effects of O3 remained steady after adjusting for PM2.5, SO2, NO2, and CO each time in the two-pollutant models.ConclusionsIncreased concentrations of ambient airborne pollutants composed of PM2.5, SO2, NO2, O3, and CO were significantly and positively associated with COPD-related mortality in the central Sichuan Basin, which is located in the hinterland of southwestern China. The adverse effects of O3 were stable, a finding that should receive more attention.

Impact of reduction of CO2 emissions in the households and tertiary sector on PM2.5 concentration and human health

Significant efforts are being made in the world to reduce greenhouse gas emissions. In the households and tertiary sectors, where energy is mainly used for heating, one should also expect a shift away from fossil fuels (including natural gas) to renewables. In the REFLEX project the energy and emission scenarios were developed for various sectors with the use of ASTRA, ELTRAMOD, TIMES-HEAT-EU and FORECAST models for analysing the longterm situation up to 2050. The paper presents the results of the evaluation of air quality and health impacts associated with direct emissions of air pollutants from households and tertiary sector based on the Driver-Pressure-State-Impact-Response framework. Ambient concentration of air pollutants in Europe was calculated with the use of Polyphemus Air Quality System. Health impacts were estimated based on the concentration-response functions for PM2.5, which is responsible for the most significant impacts to human health. The study shows that according to analysed scenarios, particulate matter (PM2.5 and PM10) emissions from residential and tertiary sectors in Europe will decrease by 30 times untill 2050 compared to 2015. These emission reductions lead to improvement of the air quality. The largest reduction in PM2.5 ambient concentrations is observed over Poland. Consequently, it is expected that in 2050 the negative impact of air pollution on human health as well the associated external costs will be reduced in EU-28.

Integrated Multiple Directed Attention-Based Deep Learning for Improved Air Pollution Forecasting

In recent years, human health across the world is becoming concerned by a constant threat of air pollution, which causes many chronic diseases and premature mortalities. Poor air quality does not have only serious adverse effects on human health and vegetation but also some major negative political, societal, and economic impacts. Hence, it is essential to invest more effort on accurate forecasting of ambient air pollution to provide practical and relevant solutions, achieve acceptable air quality, and plan for prevention. In this work, we propose a flexible and efficient deep learning-driven model to forecast concentrations of ambient pollutants. This article introduces first the traditional variational autoencoder (VAE) and the attention mechanism to develop the forecasting modeling strategy based on the innovative integrated multiple directed attention (IMDA) deep learning architecture. To assess the performance of the proposed forecasting methodology, experimental validation is then performed using air pollution data from four US states. Six statistical indicators have been used to evaluate the forecasting accuracy. A discussion of the results obtained finally demonstrates the satisfying performance of integrated multiple directed attention variational autoencoder (IMDA-VAE) methods to forecast different pollutants in different locations. Furthermore, results indicate that the proposed IMDA-VAE model can effectively improve air pollution forecasting performance and outperforms the deep learning models, namely VAE, long short-term memory (LSTM), gated recurrent units (GRU), bidirectional LSTM, bidirectional GRU, and ConvLSTM. We also showed that the forecasting results of the proposed model surpass the performance of LSTM and GRU with the attention mechanism.