Extreme Pollution Events Research Articles

Effects of Aerosol Water Content on the formation of secondary inorganic aerosol during a Winter Heavy PM2.5 Pollution Episode in Xi'an, China

Sulfate, nitrate and ammonium are the most abundant secondary inorganic aerosols (SIA) in atmospheric fine particle matter (PM2.5). Meteorological conditions, gas-particle transportation process, and aerosol acidity (pH) can influence SIA formation. In this study, we conducted semi-continuous measurements of water-soluble inorganic ions during a winter extreme pollution event (from January 9th to January 17th, 2015, average PM2.5 concentrations of ~250 μg m−3 and peak concentrations of ~700 μg m−3) in Xi'an to elucidate on the SIA formation mechanism. The hourly mean level of the total water-soluble ion was 137.4 μg m−3, accounting for 55.3% of PM2.5 on average. The dominant ions concentrations of SO42−, NO3− and NH4+ accounted for 15.8%, 19.0% and 13.2% of PM2.5 mass, respectively. PM2.5 was moderately acidic, with an average pH of 4.8 ± 0.4. Compared to the clean periods, sulfate content decreased by 6.9% during the polluted periods, while those of nitrate and ammonium increased by 2.2% and 5.0%, respectively. The increase in nitrogen oxidation ratios (NOR) and ammonia conversion ratio (NHR) from normal days to haze days were greater when comparison to sulfur oxidation ratios (SOR). In the polluted periods, sulfate and nitrate formations were facilitated by water content increase. Strong linear correlation coefficients between SOR (R2 = 0.81) and NOR (R2 = 0.55) with aerosol water content indicated that the gas-liquid reaction of SO2 and NO2 is the major pathway of sulfate and nitrate formation during severe haze episodes. In contrast, the NHR and aerosol water content exhibited a logarithmic relationship, which reveals that when water content was greater than 100 μg m−3, the gas-particle partitioning ratio of ammonium was basically unchanged following an increase in water content.

Association of retreating monsoon and extreme air pollution in a megacity

The world's top ranked mega city Delhi is known for deteriorated air quality. However, the analysis of air pollution data of 5 years (2014–2018) reveals that years 2016 and 2017, which were marked by an unusual delayed withdrawal of monsoon, witnessed an unprecedented extreme levels of toxic PM2.5 particles (≤2.5 µm in diameter) touching a peak level of ∼760 µg/m3 (24 hr average), immediately after the monsoon retreat, surpassing WHO standards by ∼30 time and Indian national standards by ∼12 times, jeopardising lives of its citizens. However, the normal monsoon withdrawal years do not show such extreme levels of pollution. The high resolution WRF-Chem model along with meteorological data are used in this work to understand that how the delayed monsoon withdrawal and associated vagarious anti-cyclonic circulation resulted in trapping externally generated pollutants ceaselessly under colder conditions, leading to historic air quality crisis in landlocked mega city in these selected years. The sensitivity analysis confirmed that when WRF-chem model forced the climatology of normal monsoon year (2015) to simulate the pollution scenario of 2016 and 2017 for the above time period, the crisis subsided. Present findings suggest that such unusual monsoon patterns are on the hook to spur extreme pollution events in recent time.

Role of meteorological regime in mitigating biomass induced extreme air pollution events

India is an agriculture-based economy; a large fraction of crop residue is being burned directly on fields that are one of the major sources of air pollution. As the autumn edges towards the cooler winter in mega city Delhi, the fear of smog looms, frequently leading to extreme pollution events caused by burn paddy straw under the hostile weather. The Kharif crop stubble burning starts around the first week of October and lasts up to the end of November. We hereby propose that if the burning period is advanced backward by about a month then the severity of its impact in deteriorating the air quality of Delhi would be significantly reduced due to less hostile meteorological regime. The current work is based on 2018 and generalization of current findings would require a much more comprehensive simulation and protocols. In the present work, an interactive high resolution WRF-Chem model forced with newly developed synergized gridded stubble burning emission inventory of PM2.5 for 2018 is used along with normal emissions. Results indicate that emergency episodes significantly reduced from 12 to nil, under proposed scenario that may help minimizing adverse health impacts. Such effort, however, requires a feasibility study and policy level intervention.

A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification

Due to the complexity of land cover and aerosol types, the high-precision retrieval of land aerosol properties is challenging. A land general aerosol (LaGA) algorithm called the High-Precision Aerosol Retrieval Algorithm (HiPARA) is proposed for the Advanced Himawari Imager (AHI) sensor over East Asia. In this algorithm, a monthly spectral base reflectance ratio library was constructed to obtain a pixel-by-pixel spectral reflectance relationship model. Statistical methods were used to obtain aerosol types in China, and a linearization scheme for the aerosol types was proposed based on sensitivity analysis. Based on these techniques, HiPARA achieved a completely dynamic determination of the surface reflectance and aerosol types. The new multiband aerosol characteristic retrieval strategy can return two parameters, aerosol optical depth (AOD) and single scattering albedo (SSA). The AOD retrieved from HiPARA showed high consistency with AERONET AOD measurements, with correlation coefficients (R) of 0.939, a mean absolute error (MAE) of 0.082, a root mean square error (RMSE) of 0.113, ratios that meet an expected error (EE) of 0.825, and ratios that meet a Global Climate Observing System (GCOS) error of 0.339. Comparison of the HiPARA retrieved AOD with other operational aerosol products revealed that the accuracy of the HiPARA product was better than those of the Japan Aerospace Exploration Agency (JAXA) product (R < 0.9, RMSE > 0.175), Moderate-resolution Imaging Spectro-radiometer (MODIS) products (Dark Target (DT) algorithm, R = 0.907, RMSE = 0.203; Deep Blue (DB) algorithm, R = 0.909, RMSE = 0.139) and Visible/Infrared Imager Radiometer Suite (VIIRS) AERDB product (R = 0.932, RMSE = 0.117). The HiPARA fitting line was close to 1:1 (i.e., y = x). The aerosol products were further evaluated for four extreme aerosol events: a smoke aerosol event, a haze aerosol event, a dust aerosol event, and a continuous aerosol variation event. Observation of the true-color images and AOD retrievals showed that the HiPARA AOD distribution matched the true-color images very well. The JAXA product had abnormal values and spatial discontinuities. The MODIS and VIIRS products were not as good as the HiPARA product in terms of spatial coverage. In the application to continuous monitoring of a dust event, the HiPARA AOD captured the variations in and intensity of the dust aerosols very well. These results suggested the robustness of HiPARA and its potential for monitoring extreme pollution events with high precision and high temporal resolution.

ATMOSPHERIC POLLUTION AND HUMAN HEALTH (APHH): INDO-UK PROGRAM FOR INDIAN MEGA CITY

Majority of mega cities in India are reeling under air quality crisis in terms of health impacts and compliance with regulatory standards, particularly, the WHO guidelines which are usually more stringent. Atmospheric Pollution and Human Health in an Indian Megacity (APHH) is a research programme jointly launched by the Ministry of Earth Sciences (MoES, India), Department of Biotechnology (DBT, India), Natural Environment Research Council (NERC, UK), Medical Research Council (MRC, UK), and Newton-Bhabha Fund. This programme, which has been organised into four interrelated themes, will support research on the sources and emissions of urban air pollution in New Delhi, India, the processes underlying and impacting on these, and how air pollution then impacts on health. Existing and new findings will be combined to understand the cost-effectiveness of potential interventions and thus identify appropriate solutions for the benefit of the economy and population. These APHH themes are highly interrelated and, therefore, there is considerable benefit in the projects working together and integrating activities. The present paper will focus on new results emerging from 4 SAFAR cities of India to contrast the scientific challenges which are not only driven by different emission contributions but also by differences in the prevailing meteorology, orography and air quality management capacity. The major air quality issue in Urban India is largely PM2.5. The ultra high-resolution emission inventory for some India mega cities (400m resolution) and its implication in terms of improving forecasting capability and policy framing will be disused. SAFAR-WRF-Chem model results will be focussed on extreme pollution events whose intensity and longevity has increased in recent time and likely to be related to climate change and erratic weather.

Shell Growth of Large Benthic Foraminifera under Heavy Metals Pollution: Implications for Geochemical Monitoring of Coastal Environments.

This study was promoted by the recent efforts using larger benthic foraminiferal (LBF) shells geochemistry for the monitoring of heavy metals (HMs) pollution in the marine environment. The shell itself acts as a recorder of the ambient water chemistry in low to extreme HMs-polluted environments, allowing the monitoring of recent-past pollution events. This concept, known as sclerochronology, requires the addition of new parts (i.e., new shell) even in extreme pollution events. We evaluated the physiological resilience of three LBF species with different shell types and symbionts to enriched concentrations of Cd, Cu, and Pb at levels several folds higher than the ecological criteria maximum concentration (CMC) (165–166, 33–43, 1001–1206 µg L−1, respectively), which is derived from aquatic organisms’ toxicity tests. The physiological response of the holobiont was expressed by growth rates quantified by the addition of new chambers (new shell parts), and by the chlorophyll a of the algal symbionts. The growth rate decrease varied between 0% and 30% compared to the unamended control for all HMs tested, whereas the algal symbionts exhibited a general non-fatal but significant response to Pb and Cu. Our results highlight that shell growth inhibition of LBF is predicted in extreme concentrations of 57 × CMC of Cu and 523 × CMC of Cd, providing a proof of concept for shell geochemistry monitoring, which is currently not used in the regulatory sectors.

Intensity–duration–frequency approach for risk assessment of air pollution events

Intensity–duration–frequency (IDF) curves can serve as useful tools in risk assessment of extreme environmental events. Thus, this study proposes an IDF approach for evaluating the risk of expected occurrences of extreme air pollution as measured by an air pollution index (API). Hourly data of Klang city in Malaysia from 1997 to 2016 are analyzed. For each year, a block maxima size is determined based on four different monsoon seasons. Generalized extreme value (GEV) distribution is used as a model to represent the probabilistic behavior of maximum intensity of the API, which is derived from each block. Based on the GEV model, the IDF curves are developed to estimate the extreme pollution intensities that correspond to various duration hours and return periods. Considering the IDF curves, we found that for any duration hour, the magnitude of pollution intensity tends to be high in parallel with increasing return periods. In fact, a high-intensity pollution event that poses a high risk of affecting the environment is less frequent than low-intensity pollution. In conclusion, the IDF curves provide a good basis for decision makers to assess the expected risk of extreme pollution events in the future.

Risk assessment of extreme air pollution based on partial duration series: IDF approach

The occurrences of extreme pollution events have serious effects on human health, environmental ecosystems, and the national economy. To gain a better understanding of this issue, risk assessments on the behavior of these events must be effectively designed to anticipate the likelihood of their occurrence. In this study, we propose using the intensity–duration–frequency (IDF) technique to describe the relationship of pollution intensity (i) to its duration (d) and return period (T). As a case study, we used data from the city of Klang, Malaysia. The construction of IDF curves involves a process of determining a partial duration series of an extreme pollution event. Based on PDS data, a generalized Pareto distribution (GPD) is used to represent its probabilistic behaviors. The estimated return period and IDF curves for pollution intensities corresponding to various return periods are determined based on the fitted GPD model. The results reveal that pollution intensities in Klang tend to increase with increases in the length of time between return periods. Although the IDF curves show different magnitudes for different return periods, all the curves show similar increasing trends. In fact, longer return periods are associated with higher estimates of pollution intensity. Based on the study results, we can conclude that the IDF approach provides a good basis for decision-makers to evaluate the expected risk of future extreme pollution events.

Objective evaluation of stubble emission of North India and quantifying its impact on air quality of Delhi

Crop residue burning during post monsoon season in the neighboring provinces leads to frequent episodes of extreme pollution events, associated with premature morbidity and mortality. A synergistic use of multiple satellite measurements in conjunction with actual field incidences data at the ground led us to develop the realistic high-resolution emission inventory of the hazardous pollutant PM2.5 due to stubble burning. We quantify the share of biomass burning in deteriorating Delhi's air quality during 2018 using the SAFAR chemical transport model that has been validated with dense observational network of Delhi. The impact of biomass burning on Delhi's PM2.5 is found to vary on day-to day basis (peaking at 58%) as it is highly dependent on transportation pathway of air mass, controlled by meteorological parameters from source to target region. Comprehending the multi-scale nature of such events is crucial to plan air quality improvement strategies.

A Clean Air Plan for Sydney: An Overview of the Special Issue on Air Quality in New South Wales

This paper presents a summary of the key findings of the special issue of Atmosphere on Air Quality in New South Wales and discusses the implications of the work for policy makers and individuals. This special edition presents new air quality research in Australia undertaken by (or in association with) the Clean Air and Urban Landscapes hub, which is funded by the National Environmental Science Program on behalf of the Australian Government’s Department of the Environment and Energy. Air pollution in Australian cities is generally low, with typical concentrations of key pollutants at much lower levels than experienced in comparable cities in many other parts of the world. Australian cities do experience occasional exceedances in ozone and PM2.5 (above air pollution guidelines), as well as extreme pollution events, often as a result of bushfires, dust storms, or heatwaves. Even in the absence of extreme events, natural emissions play a significant role in influencing the Australian urban environment, due to the remoteness from large regional anthropogenic emission sources. By studying air quality in Australia, we can gain a greater understanding of the underlying atmospheric chemistry and health risks in less polluted atmospheric environments, and the health benefits of continued reduction in air pollution. These conditions may be representative of future air quality scenarios for parts of the Northern Hemisphere, as legislation and cleaner technologies reduce anthropogenic air pollution in European, American, and Asian cities. However, in many instances, current legislation regarding emissions in Australia is significantly more lax than in other developed countries, making Australia vulnerable to worsening air pollution in association with future population growth. The need to avoid complacency is highlighted by recent epidemiological research, reporting associations between air pollution and adverse health outcomes even at air pollutant concentrations that are lower than Australia’s national air quality standards. Improving air quality is expected to improve health outcomes at any pollution level, with specific benefits projected for reductions in long-term exposure to average PM2.5 concentrations.

Sensitivity of Ozone Dry Deposition to Ecosystem‐Atmosphere Interactions: A Critical Appraisal of Observations and Simulations

AbstractThe response of ozone (O3) dry deposition to ecosystem‐atmosphere interactions is poorly understood but is central to determining the potential for extreme pollution events under current and future climate conditions. Using observations and an interactive dry deposition scheme within two dynamic vegetation land models (Geophysical Fluid Dynamics Laboratory LM3.0/LM4.0) driven by observation‐based meteorological forcings over 1948–2014, we investigate the factors controlling seasonal and interannual variability (IAV) in O3 deposition velocities (Vd,O3). Stomatal activity in this scheme is determined mechanistically, depending on phenology, soil moisture, vapor pressure deficit, and CO2 concentration. Soil moisture plays a key role in modulating the observed and simulated Vd,O3 seasonal changes over evergreen forests in Mediterranean Europe, South Asia, and the Amazon. Analysis of multiyear observations at forest sites in Europe and North America reveals drought stress to reduce Vd,O3 by ~50%. Both LM3.0 and LM4.0 capture the observed Vd,O3 decreases due to drought; however, IAV is weaker by a factor of 2 in LM3.0 coupled to atmospheric models, particularly in regions with large precipitation biases. IAV in summertime Vd,O3 to forests, driven primarily by the stomatal pathway, is largest (15–35%) in semiarid regions of western Europe, eastern North America, and northeastern China. Monthly mean Vd,O3 for the highest year is 2 to 4 times that of the lowest, with significant implications for surface O3 variability and extreme events. Using Vd,O3 from LM4.0 in an atmospheric chemistry model improves the simulation of surface O3 abundance and spatial variability (reduces mean biases by ~10 ppb) relative to the widely used Wesely scheme.

Analysis of exposure to fine particulate matter using passive data from public transport

The city of Santiago experiences extreme pollution events during winter due to particulate matter and the associated health impact depends on the exposure to this pollutant, particularly to PM2.5. We present and apply a method that estimates the exposure of users of the public transport system of Santiago by combining smart card mobility data with measured surface concentrations from the monitoring network of Santiago and simulated concentrations by the CHIMERE model. The method was applied between July 20th and 24th of 2015 to 105,588 users corresponding to 12% of the frequent users of the public transport system and approximately 2% of the total population of Santiago. During those five days, estimated exposure based on measured concentrations varied between 44 and 75 μg/m3 while exposure based on simulated concentrations varied between 45 and 89 μg/m3. Furthermore, including socioeconomic conditions suggests an inverse relationship between exposure and income when measured concentrations are used, i.e. the lower the income the higher the exposure, whereas no such relationship is observed when using simulated concentrations. Although only exposure to PM2.5 was considered in this study, the method can also be applied to estimate exposure to other urban pollutant such as ozone.

Characteristics of the factors influencing transportation and accumulation processes during a persistent pollution event in the middle reaches of the Yangtze River, China

Extreme pollution event is a major environmental concern in the middle reaches of the Yangtze River, which located at the position of a transportation hub connecting the four major air pollution areas in China. In this study, we focused on a continuous heavy air pollution event that affected Hubei from 12 to 24 January 2018, and examined the meteorological conditions, regional transport features, boundary-layer characteristics, and the evolution of PM and gaseous pollutants in Xiangyang (XY), Jingmen (JM), Jingzhou (JZ), Yichang (YC), Xiaogan (XG), and Wuhan (WH). The results showed that this pollution event was the result of joint action of fog, haze, and fog-haze transformation weather. The pure haze was mainly concentrated at the pollution-transport channel (XY and JM) of Hubei. The explosive growth of PM concentrations was more obvious in XY, JM, and JZ than that in YC, XG, and WH, with the growth and reduction rates of PM2.5 at XY station, at 20.11 and 19.50 μg/(m3·h), respectively. During the explosive growth period, northerly winds were dominant at XY, JM, JZ, XG, and WH stations, with large and weak wind speed (WS) resulted in significantly increased PM2.5 concentrations in XY and JM (transport), and in JM, JZ, and YC (accumulation), respectively. The height of northward airflow reached 2000 m in the main pollutant transport channel of Hubei. The upper and lower inversion layers would be enhanced before the explosive growth of PM concentration significantly, then be weakened by continuous transport of the northerly airflow. The concentrations of SO2, NO2, and CO decreased with the increase in WS during the explosive growth period, and O3 concentration reached maximum value at a WS of 3.5–5 m/s. The correlation analysis indicated significant differences in the effects of transport and accumulation.

Responses of PM2.5 and O3 concentrations to changes of meteorology and emissions in China

Tremendous efforts have been made to reduce the severe air pollution in China since 2013. However, the annual and peak fine particulate matter (PM2.5) concentrations during severe events in winter did not always reduce as expected. This is partially due to the inter-annual variation of meteorology, which affects the emission, transport, transformation, and deposition processes of air pollutants. In this study, the responses of PM2.5 and ozone (O3) concentrations to changes in emission and meteorology from 2013 to 2015 were investigated based on ambient measurements and the Community Multi-Scale Air Quality (CMAQ) model simulations with anthropogenic emissions. It is found that emission reductions in 2014 and 2015 effectively reduced PM2.5 concentrations by 23.9 and 43.5 μg/m3, respectively, but was partially counteracted by unfavorable meteorology. The negative effects from unfavorable meteorology were significant in extreme pollution events. For example, in December 2015, unfavorable meteorology caused a great increase (90 μg/m3) of PM2.5 in Beijing. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of O3-8 h daily concentrations in the summertime in 2014 and 2015 in comparison of 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. In addition, reduction of nitrogen oxides (NOx) emissions in areas with negative NOx-O3 sensitivity could lead to an increase of O3 formation when the reduction of volatile organic compounds (VOCs) was not sufficient. This unintended enhanced O3 formation could also lead to higher O3 in downwind areas. This study emphasizes the role of meteorology in pollution control, validates the effectiveness of PM2.5 control measures in China, and highlights the importance of appropriate joint reduction of NOx and VOCs to simultaneously decrease O3 and PM2.5 for higher air quality.

Extensible Database of Validated Biomass Smoke Events for Health Research

The extensible Biomass Smoke Validated Events Database is an ongoing, community driven, collection of air pollution events which are known to be caused by vegetation fires such as bushfires (also known as wildfire and wildland fires), or prescribed fuel reduction burns, and wood heaters. This is useful for researchers of health impacts who need to distinguish smoke from vegetation versus other sources. The overarching aim is to study statistical associations between biomass smoke pollution and health. Extreme pollution events may also be caused by dust storms or fossil fuel smog events and so validation is necessary to ensure the events being studied are from biomass. This database can be extended by contribution from other researchers outside the original team. There are several available protocols for adding validated smoke events to the database, to ensure standardization across datasets. Air pollution data can be included, and free software was created for identification of extreme values. Protocols are described for reference material needed as supporting evidence for event days. The utility of this database has previously been demonstrated in analyses of hospitalization and mortality. The database was created using open source software that works across operating systems. The prospect for future extensions to the database is enhanced by the description in this paper, and the availability of these data on the open access Github repository enables easy addition to the database with new data by the research community.

Extreme air pollution from residential solid fuel burning

Atmospheric aerosol particles (also known as particulate matter) are central to the cause of the two greatest threats to human security: air pollution (~5 million premature deaths per year) and climate change (~0.5 million per year). Addressing these threats requires an understanding of particulate matter sources responsible for both extreme air pollution immediately affecting human health and less extreme levels affecting climate over longer timescales. Here, extraordinary levels of air pollution, with submicrometre aerosol (PM1) mass concentration surpassing 300 µg m−3, were observed in a moderately sized European city and are attributed to emissions from residential solid fuel—specifically peat and wood, often promoted as ‘slow-renewable’, ‘low-carbon’ or ‘carbon-neutral’ biomass. Using sophisticated fingerprinting techniques, we find that consumption of peat and wood in up to 12% and 1% of households, respectively, contributed up to 70% of PM1. The results from this approach can better inform emissions reduction policies and help to ensure the most appropriate air pollution sources are targeted. Given the far greater abundance of solid fuels and concomitant emissions required to match the calorific benefit of liquid fuels, even modest increases in the consumption of ‘green’-marketed solid fuels will disproportionally increase the frequency of extreme pollution events. Understanding the sources of particulate matter responsible for extreme air pollution and climate change is critical for designing adequate policies to protect the wellbeing of citizens. This study shows that extraordinary levels of particulate matter with diameter smaller than 1 µm were observed in Dublin in November 2016 and January 2017 and can be attributed to emissions from residential burning of peat and wood, often promoted as ‘slow renewables’.

Connections between summer air pollution and stagnation

The body of literature on ambient air pollution suggests that atmospheric stagnation events trigger high levels of air pollution. In this paper we use fifteen years (2000–2014) of summertime in situ air quality measurements together with meteorological reanalysis data to examine the temporal correlation of pollutants with the Air Stagnation Index (ASI) on daily timescales. We find that while the direction of the relationship between the ASI and summertime PM2.5 and O3 ranges from near-zero to positive throughout regions comprising the contiguous United States (US), the strength of the relationship is very weak (e.g. in the Northeast the correlation coefficient between the ASI and PM2.5 is 0.09). Moreover, similar to our analysis of the correlation of day-to-day variations of the ASI and pollutants, the percentage of co-occurring extreme pollution and stagnation events is small (e.g. days with a high coverage of stagnation only co-occur with extreme pollution events about one-third of the time in the Northeast). The southern US is an exception to our overall findings as the strength of the relationship between the ASI and pollution is stronger and the percentage of co-occurring events is higher compared with other regions. The results of this study suggest a reevaluation of the ASI as an index to assess meteorological and climatic impacts to air quality.

Analysing urban ventilation in building arrays with the age spectrum and mean age of pollutants

This study investigates the applicability and relevance of the Green's function and age spectrum to urban ventilation. Ventilation in an idealised urban environment is examined by characterising pollutant dispersion from the urban canopy layer. Air flow over regular uniform and non-uniform building arrays is computed using large-eddy simulation and pollutant removal is analysed via the age spectrum for localised sources. The age spectrum represents the probability distribution function of pollutant or tracer ages. Since the age spectrum is obtained directly from the evolution equation for the passive scalar, it is more effective for flows with high intermittency. This should be beneficial for studies of extreme pollution events in the urban environment such as accidental release of toxic gases and dust storms. It is demonstrated that the age spectrum is sensitive to the source release location, implying that pollutant removal depends on the initial conditions. Mean ages calculated using the homogeneous emission method and the age spectrum show qualitative similarities; however, there are quantitative differences in regions where the flow is highly unsteady and intermittent. The age spectrum indicates that ventilation decreases by ∼70% when the aspect ratio (building height/street width) is increased from 1 to 4. Furthermore, the effect of fresh air entrainment increases by ∼80% when the building heights are non-uniform.

Influences of socioeconomic vulnerability and intra-urban air pollution exposure on short-term mortality during extreme dust events.

Air pollution has been shown to be significantly associated with morbidity and mortality in urban areas, but there is lack of studies focused on extreme pollution events such as extreme dust episodes in high-density Asian cities. However, such cities have had extreme climate episodes that could have adverse health implications for downwind areas. More importantly, few studies have comprehensively investigated the mortality risks of extreme dust events for socioeconomically vulnerable populations. This paper examined the association between air pollutants and mortality risk in Hong Kong from 2006 to 2010, with a case-crossover analysis, to determine the elevated risk after an extreme dust event in a high-density city. The results indicate that PM10-2.5 dominated the all-cause mortality effect at the lag 0 day (OR: 1.074 [1.051, 1.098]). This study also found that people who were aged≥65, economically inactive, or non-married had higher risks of all-cause mortality and cardiorespiratory mortality during days with extreme dust events. In addition, people who were in areas with higher air pollution had significantly higher risks of all-cause mortality and cardiorespiratory mortality. In conclusion, the results of this study can be used to target the vulnerable among a population or an area and the day(s) at risk to assist in health protocol development and emergency planning, as well as to develop early warnings for the general public in order to mitigate potential mortality risk for vulnerable population groups caused by extreme dust events.

Extreme value analysis of air pollution data and their comparison between two large urban regions of South America

Sixteen years of hourly atmospheric pollutant data (1996–2011) in the Metropolitan Area of São Paulo (MASP), and seven years (2005–2011) of data measured in the Metropolitan Area of Rio de Janeiro (MARJ), were analyzed in order to study the extreme pollution events and their return period. In addition, the objective was to compare the air quality between the two largest Brazilian urban areas and provide information for decision makers, government agencies and civil society. Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) were applied to investigate the behavior of pollutants in these two regions. Although GEV and GPD are different approaches, they presented similar results. The probability of higher concentrations for CO, NO, NO2, PM10 and PM2.5 was more frequent during the winter, and O3 episodes occur most frequently during summer in the MASP. On the other hand, there is no seasonally defined behavior in MARJ for pollutants, with O3 presenting the shortest return period for high concentrations. In general, Ibirapuera and Campos Elísios stations present the highest probabilities of extreme events with high concentrations in MASP and MARJ, respectively. When the regions are compared, MASP presented higher probabilities of extreme events for all analyzed pollutants, except for NO; while O3 and PM2.5 are those with most frequent probabilities of presenting extreme episodes, in comparison other pollutants.