Analysis of influential factors for the relationship between PM_(2.5) and AOD in Beijing

The relationship between aerosol optical depth (AOD) and PM_(2.5) is often investigated in order to obtain surface PM_(2.5) from satellite observation of AOD with a broad area coverage. However, various factors could affect the AOD–PM_(2.5) regressions. Using both ground and satellite observations in Beijing from 2011 to 2015, this study analyzes the influential factors including the aerosol type, relative humidity (RH), planetary boundary layer height (PBLH), wind speed and direction, and the vertical structure of aerosol distribution. The ratio of PM_(2.5) to AOD, which is defined as η, and the square of their correlation coefficient (R^2) have been examined. It shows that η varies from 54.32 to 183.14, 87.32 to 104.79, 95.13 to 163.52, and 1.23 to 235.08 µg m^(−3) with aerosol type in spring, summer, fall, and winter, respectively. η is smaller for scattering-dominant aerosols than for absorbing-dominant aerosols, and smaller for coarse-mode aerosols than for fine-mode aerosols. Both RH and PBLH affect the η value significantly. The higher the RH, the smaller the η, and the higher the PBLH, the smaller the η. For AOD and PM2.5 data with the correction of RH and PBLH compared to those without, R^2 of monthly averaged PM_(2.5) and AOD at 14:00 LT increases from 0.63 to 0.76, and R^2 of multi-year averaged PM_(2.5) and AOD by time of day increases from 0.01 to 0.93, 0.24 to 0.84, 0.85 to 0.91, and 0.84 to 0.93 in four seasons respectively. Wind direction is a key factor for the transport and spatial–temporal distribution of aerosols originated from different sources with distinctive physicochemical characteristics. Similar to the variation in AOD and PM_(2.5), η also decreases with the increasing surface wind speed, indicating that the contribution of surface PM_(2.5) concentrations to AOD decreases with surface wind speed. The vertical structure of aerosol exhibits a remarkable change with seasons, with most particles concentrated within about 500 m in summer and within 150 m in winter. Compared to the AOD of the whole atmosphere, AOD below 500 m has a better correlation with PM_(2.5), for which R^2 is 0.77. This study suggests that all the above influential factors should be considered when we investigate the AOD–PM_(2.5) relationships

Long-term effects of mitigation measures and meteorological conditions on aerosol characteristics in Beijing, China

The aim of this dissertation was to study the characteristics and development of Beijing aerosol pollution and to evaluate the effects of governmental mitigation measures thereon, while considering meteorological conditions. Based on a decade of aerosol measurements, chemical elements, black carbon (BC), particulate mercury (HgP) and size distribution of aerosol particles were studied to quantify the effects of these measures. Gallium was recommended as a tracer for coal combustion

Interprovincial reliance for improving air quality in China:A case study on black carbon aerosol

Black carbon (BC) is of global concern because of its adverse effects on climate and human health. It can travel long distances via atmospheric movement and can be geographically relocated through trade. Here, we explored the integrated patterns of BC transport within 30 provinces in China from the perspective of meteorology and interprovincial trade using the Weather Research and Forecasting with Chemistry (WRF/Chem) model and multiregional input-output analysis. In general, cross-border BC transport, which accounts for more than 30% of the surface concentration, occurs mainly between neighboring provinces. Specifically, Hebei contributes 1.2 μg·m(-3) BC concentration in Tianjin. By contrast, trade typically drives virtual BC flows from developed provinces to heavily industrial provinces, with the largest net flow from Beijing to Hebei (4.2 Gg). Shanghai is most vulnerable to domestic consumption with an average interprovincial consumption influence efficiency of 1.5 × 10(-4) (μg·m(-3))/(billion Yuan·yr(-1)). High efficiencies (∼8 × 10(-5) (μg·m(-3))/(billion Yuan·yr(-1))) are also found from regions including Beijing, Jiangsu, and Shanghai to regions including Hebei, Shandong, and Henan. The above source-receptor relationship indicates two control zones: Huabei and Huadong. Both mitigating end-of-pipe emissions and rationalizing the demand for pollution-intense products are important within the two control zones to reduce BC and other pollutants

Assessing Atmospheric Pollution and Its Impacts on the Human Health

This reprint contains articles published in the Special Issue entitled "Assessing Atmospheric Pollution and Its Impacts on the Human Health" in the journal Atmosphere. The research focuses on the evaluation of atmospheric pollution by statistical methods on the one hand, and on the other hand, on the evaluation of the relationship between the level of pollution and the extent of its effect on the population's health, especially on pulmonary diseases

Ground-level ozone pollution in China: A synthesis of recent findings on influencing factors and impacts

Ozone (O3) in the troposphere is an air pollutant and a greenhouse gas. In mainland China, after the Air Pollution Prevention and Action Plan was implemented in 2013 - and despite substantial decreases in the concentrations of other air pollutants - ambient O3 concentrations paradoxically increased in many urban areas. The worsening urban O3 pollution has fuelled numerous studies in recent years, which have enriched knowledge about O3-related processes and their impacts. In this article, we synthesise the key findings of over 500 articles on O3 over mainland China that were published in the past six years in English-language journals. We focus on recent changes in O3 concentrations, their meteorological and chemical drivers, complex O3 responses to the drastic decrease in human activities during coronavirus disease 2019 lockdowns, several emerging chemical processes, impacts on crops and trees, and the latest government interventions. © 2022 The Author(s). Published by IOP Publishing Ltd

Estimating PM 2.5 concentrations in Xi'an City using a generalized additive model with multi-source monitoring data

© 2015 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5

우리나라 주요 대도시(서울, 대전, 광주, 울산)의 PM2.5 구성성분 및 오염원 기여도에 의한 건강영향 분석

학위논문(박사) -- 서울대학교대학원 : 보건대학원 환경보건학과, 2023. 2. 이승묵.PM2.5에 대한 노출은 전 세계적으로 사람의 건강에 심각한 위협이 되고 있으며, 사망과 장애에 영향을 미치는 대표적인 위험 인자(risk factor)이다. 우리나라 역시 급속한 산업화 및 도시화에 따라 PM2.5에 의한 심각한 대기질 문제를 겪고 있으며, 대기 중 PM2.5 농도 저감을 위해 다양한 정책이 추진되고 있다. PM2.5는 불균일 혼합물(heterogeneous mixture)로 황산염, 질산염, 유기탄소, 원소탄소 및 비소, 크롬과 같은 중금속 등의 매우 다양한 화학물질로 구성되는데, PM2.5의 화학적 조성은 지역에 따라 다른 (region- specific) 특성이 있다. 이는 PM2.5가 배출원에서의 직접 배출(primary emission) 보다 황산화물(SOx), 질소산화물(NOx), 휘발성 유기화합물(VOCs) 등 가스상 전구물질의 대기 중 화학반응에 의한 2차 생성(secondary formation)을 통해 주로 대기 중에 존재하기 때문이다. 즉, 대상지역 및 인근지역의 전구물질 배출량, 대기 중 전구물질의 농도, 기상조건, 오염원의 위치, 지리적 특성 등 매우 다양한 인자들에 의해 PM2.5 조성이 결정된다. PM2.5 화학적 조성은 대상 지역의 PM2.5에 영향을 나타내는 주요 오염원을 규명하고, 각 오염원의 기여도를 산정함에 있어 매우 중요한 요소이다. 또한, 화학적 조성은 궁극적으로 PM2.5 노출이 인체에 유발하는 건강영향과도 밀접하게 연관되어 있기 때문에 보건학적 측면에서의 PM2.5 관리를 위해서는 대상 지역에서의 PM2.5의 구성성분 및 오염원에 의한 건강영향을 정량적으로 산정할 필요가 있다.본 연구에서는대기관리권역의 대기환경개선에 관한 특별법에 따라 지정된 4개 대기관리권역을 대표하는 대도시인 서울, 대전, 광주, 울산에서 2014년부터 5년간 분석된 일별 PM2.5 질량농도 및 구성성분 농도를 이용하여 도시별 오염원을 규명하고, 각 오염원의 기여도를 산정하였다. 또한, 같은 기간 PM2.5 구성성분 농도 및 오염원 기여도와 일별 사망자 수 및 응급실 내원환자 수의 연관성을 분석함으로써 PM2.5 노출이 사망과 질병에 미치는 건강영향을 산정하여 건강영향 측면에서 도시별 오염원 관리의 우선순위 선정을 위한 기초자료를 구축하였다.PMF 모델링을 통해 확인된 오염원은 서울, 광주, 울산의 경우 총 10개로 이차 질산염, 이차 황산염, 자동차, 생물성 연소, 소각시설, 토양, 산업, 석탄 연소, 석유 연소, 노후 해염입자 오염원으로 나타났다. 대전의 경우 지리적 위치로 인해 노후 해염입자 오염원은 확인되지 않았고, 나머지 9개 오염원은 다른 도시들과 동일한 것으로 확인되었다. 오염원 기여도에 있어서는 4개 도시 모두에서 공통적으로 이차 질산염, 이차 황산염 및 자동차 오염원에 의한 기여도가 60% 이상으로 나타나 PM2.5가 주로 대기 중 이차생성 및 자동차에 기인하는 것을 확인하였다. 하지만 다른 오염원의 기여도는 도시별 특성에 따라 다르게 나타났는데 특히, 대규모 화력발전소에 인접한 서울, 광주의 경우 석탄 연소 오염원의 기여도가 10% 내외로 높게 나타나 해당 도시에서 네번째로 높은 기여도를 보였다. 반면, 가장 동쪽에 위치한 울산에서는 석탄 연소 오염원의 기여율은 상대적으로 낮았으나 대규모 중화학 공업 도시의 특성이 반영되어 산업 오염원의 기여도가 다른 도시에 비해 월등히 높게 나타났다.PM2.5 구성성분 및 오염원 기여도와 건강영향의 연관성을 분석한 결과는 PM2.5 구성성분 농도 및 오염원 기여도의 단위(IQR) 증가가 전반적으로 사망 및 질병의 상대위험도 증가로 이어짐을 보여주었다. 그러나 구성성분 및 오염원 기여도와 건강영향 사이 연관성의 유의성 및 정도는 지역마다 다르게 나타났다. 먼저 구성성분이 사망에 미치는 영향의 경우 서울, 대전에서는 주로 심혈관계 사망에서 중금속, 유기탄소 등의 구성성분과의 유의한 연관성이 확인되었으나 광주에서는 주로 호흡기계 사망의 상대위험도가 중금속, 이온성분과 밀접한 관계가 있는 것으로 나타났다. 오염원-사망의 연관성에 있어서는 사망의 상대위험도를 증가시킨 구성성분과 밀접한 오염원의 기여도 증가가 사망과 밀접한 것으로 확인되었다. 따라서 PM2.5 노출로 인한 사망 영향을 줄이기 위해서는 도시별 건강영향 분석에 따라 오염원 관리의 우선순위를 마련하고, 각 오염원별 배출량 저감을 위한 정책이 수반될 필요성이 있다. 사망과 다르게 PM2.5 노출에 따른 질병 영향은 주로 호흡기계 질병을 중심으로 구성성분 및 오염원 기여도와 유의한 연관성이 확인되었다. 이 같은 결과는 PM2.5의 주 노출경로가 호흡(inhalation)이고, PM2.5가 매우 미세한 크기로 인해 매질인 공기와 유사하게 거동함에 따라 상기도 뿐만 아니라 하기도인 기관, 기관지, 폐포 등에도 쉽게 도달한 후 염증 반응, 산화스트레스 등의 메커니즘을 통해 호흡기계에 급성 영향을 나타내기 때문으로 판단된다. 상기 메커니즘에 의해 호흡기계 기관에서 생성된 염증성 사이토카인, 활성산소종 등은 다시 전신순환을 통해 심혈관계에 도달해 질병을 유발할 수 있고, 궁극적으로 사망의 위험도를 증가시킬 수 있다. 본 연구의 결과는 대기 중 질량농도 저감에 초점이 맞추어져 있는 현재의 PM2.5 관리정책이 지역별 조성, 오염원 기여도 및 건강영향 특성을 고려한 정책으로 확대될 필요성이 있음을 시사한다. 즉, 환경 오염물질 관리의 궁극적인 목적은 오염물질에 대한 노출이 인체에 유발하는 부정적인 영향을 최소화함으로써 국민의 건강과 안녕을 유지하는 것이기 때문에 지역 특이적인 PM2.5의 조성과 그로 인해 다르게 나타나는 건강영향을 평가함으로써 최적의 대기관리 정책 및 계획 등을 수립하여 실행할 필요가 있다.Exposure to fine particulate matter (PM2.5) has been revealed as severe threats to human health and one of the major risk factors driving both death and disability. South Korea is one of the countries have been suffering from serious air pollution, especially problems related to PM2.5. PM2.5 is a heterogeneous mixture of numerous components such as sulfate, nitrate, organic carbon, elemental carbon, arsenic, lead. The chemical compositional characteristics are highly region-specific because most of the PM2.5 mass concentration is attributable to secondary particles, formed by the reactions among gaseous precursors in the atmosphere. In general, the factors affecting secondary formation are meteorological conditions, source locations, geographical features of the region well as the ambient concentration of gaseous pollutants including sulfur oxides, nitrogen oxides. Therefore, understanding the chemical composition and source profiles in the region of interest is crucial for controlling PM2.5. Moreover, the assessment of health risk caused by PM2.5 exposure needs to conducted to mitigate the adverse health effects from a public health perspective. In this study, the associations of cause-specific mortality and morbidity with both PM2.5 constituents and source contributions were investigated in four metropolitan cities, namely Seoul, Daejeon, Gwangju, and Ulsan. Each city represents the air control zone in the country designated by a special act as of April 2020 to mitigate and control the air pollution on a regional basis. For the analyses, generalized linear model (GLM) was applied to the data including daily health outcomes, the average concentrations of PM2.5 constituents and the results of PMF modelling. The findings show that short-term exposure to PM2.5 constituents largely increased the relative risk (RR) of mortality and morbidity. However, the significance and strength of associations were different among the cities. In addition, source contributions also increased the RR of mortality and morbidity with different strength. In summary, the results of the study imply the importance of approaches based on compositional characteristics and health risk in making proper policies in the region of interest to mitigate the negative health effects of PM2.5 exposure more efficiently.Chapter 1. Background 1 1. Introduction 2 2. Potential mechanisms of health effects of PM2.5 exposure 4 2.1 Respiratory system 4 2.2 Cardiovascular system 6 3. Objectives of the study 7 References 10 Chapter 2. Compositional characteristics of ambient PM2.5 in Seoul, Daejeon, Gwangju, and Ulsan during 2014–2018 16 Abstract 17 1. Introduction 18 2. Materials and methods 19 2.1 Study area and period 19 2.2 Data 22 3. Results and discussion 23 3.1 PM2.5 mass and gaseous precursors 23 3.2 PM2.5 chemical constituents 31 4. Conclusions 50 References 52 Chapter 3. Source apportionment of PM2.5 in Seoul, Daejeon, Gwangju, and Ulsan during 2014-2018 56 Abstract 57 1. Introduction 58 2. Materials and methods 59 2.1 Input data 59 2.2 PMF modelling 59 2.3 Conditional probability function 61 2.4 Potential source contribution function 62 3. Results and discussion 64 3.1 Source apportionment 64 3.2 Seasonal source contributions 78 3.3 Possible source locations 86 4. Conclusions 108 References 110 Chapter 4. Associations of PM2.5 chemical constituents and source contributions with mortality 122 Abstract 123 1. Introduction 124 2. Materials and methods 125 2.1 Data 125 2.2 Statistical model 126 3. Results and discussion 129 4. Conclusions 150 References 152 Chapter 5. Associations of PM2.5 chemical constituents and source contributions with morbidity 158 Abstract 159 1. Introduction 160 2. Materials and methods 161 2.1 Data 161 2.2 Statistical model 163 3. Results and discussion 165 4. Conclusions 181 References 183 Chapter 6. Summary, significance, and conclusions 192 1. Summary 193 1.1 Compositional characteristics and source apportionment of ambient PM2.5 in Seoul, Daejeon, Gwangju, and Ulsan during 2014-2018 193 1.2 Associations of PM2.5 chemical constituents and source contributions with mortality 195 1.3 Associations of PM2.5 chemical constituents and source contributions with morbidity 196 2. Significance 197 2.1 Region-specific characteristics of the health effects of PM2.5 exposure on mortality 197 2.2 Impacts of government policy interventions on PM2.5 composition, source contribution, and health effects 198 3. Conclusions 207 References 210 국문초록 213박

Integrated human exposure to air pollution

The book “Integrated human exposure to air pollution” aimed to increase knowledge about human exposure in different micro-environments, or when citizens are performing specific tasks, to demonstrate methodologies for the understanding of pollution sources and their impact on indoor and ambient air quality, and, ultimately, to identify the most effective mitigation measures to decrease human exposure and protect public health. Taking advantage of the latest available tools, such as internet of things (IoT), low-cost sensors and a wide access to online platforms and apps by the citizens, new methodologies and approaches can be implemented to understand which factors can influence human exposure to air pollution. This knowledge, when made available to the citizens, along with the awareness of the impact of air pollution on human life and earth systems, can empower them to act, individually or collectively, to promote behavioral changes aiming to reduce pollutants’ emissions. Overall, this book gathers fourteen innovative studies that provide new insights regarding these important topics within the scope of human exposure to air pollution. A total of five main areas were discussed and explored within this book and, hopefully, can contribute to the advance of knowledge in this field

Introduction to Special Issue - In-depth study of air pollution sources and processes within Beijing and its surrounding region (APHH-2 Beijing)

Abstract. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1-3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme, and (ii) the measurement and modelling activities performed as part of it. In addition, this paper introduces the meteorology and air quality conditions during two joint intensive field campaigns - a core integration activity in APHH-Beijing. The coordinated campaigns provided observations of the atmospheric chemistry and physics at two sites: (i) the Institute of Atmospheric Physics in central Beijing, and (ii) Pinggu in rural Beijing during 10 November – 10 December 2016 (winter) and 21 May- 22 June 2017 (summer). The campaigns were complemented by numerical modelling and automatic air quality and low-cost sensor observations in the Beijing megacity. In summary, the paper provides background information on the APHH-Beijing programme, and sets the scene for more focussed papers addressing specific aspects, processes and effects of air pollution in Beijing