Evaluation of Health Loss Caused by Haze Pollution in Beijing: Historical Changes and Current Situation

Haze pollution’s harm to residents’ health has become a public topic arousing the national, social and public concerns. This paper, taking Beijing as an example, quantitatively evaluated the current situation and historical changes of health-related economic loss caused by haze pollution across Beijing’s districts, based on the data from 2009 to 2016 on air pollutant concentration, pathology and health statistics. The results show that health-related economic loss caused by haze pollution of Beijing in 2016 was about RMB 67.925 billion. The most severe health loss was seen in Chaoyang, Haidian and Fengtai districts, while less health loss was found in Yanqing, Mentougou and Huairou districts. This is mainly attributed to the differences in pollutants emission, local population and geographic location. Judging from the trend, the health loss caused by air pollution across Beijing saw a wavelike rise first, followed by a decrease year by year, from 2009 to 2016; but the loss in 2016 was at least 1.1 times that in 2009. The control over air pollution faces severe challenges. Therefore, it is urgently needed to address haze pollution in line with the local conditions of Beijing and take gradual steps to incorporate health loss caused by air pollution into the balance sheet accounting system of natural resources.

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Effects of Ambient Air Quality Improvement on Mortality From Acute Air Pollution Exposure in Beijing

10.21203/rs.3.rs-386816/v1 ◽

2021 ◽

Author(s):

Jingxiu Han ◽

Han Jingxiu ◽

Meng Congshen ◽

Liu Jingyi ◽

Xu Chunyu ◽

...

Keyword(s):

Air Pollution ◽

Quality Improvement ◽

Air Quality ◽

Respiratory Disease ◽

Local Population ◽

Random Effect ◽

Random Effect Model ◽

Ambient Air ◽

Air Pollutant ◽

Air Quality Improvement

Abstract Exposure to air pollutants increase the mortality of population. Developing countries have taken measures to control air pollution. To explore the effects of air quality improvement on mortality, air quality and acute exposure-response coefficients of excess death in Beijing since the 1990’s were analyzed. It was divided into five stages according to the concentration level of pollutants. Coefficients for period 1990 – 2013 were obtained by retrieving literatures published before December 31, 2019. The coefficients for period 2015 – 2017 were obtained by analyzing the daily data of air pollutant concentration, meteorological and human mortality conducting Poisson Generalized Additive Model (GAM). Meta-analysis of random effect model was used to estimate the integrated coefficient of multiple studies at each stages. Comparative analysis was used to analyze the variation of air quality and coefficients in different stages. The results showed that the concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with aerodynamic diameter ≤10μm (PM10) and ≤2.5μm (PM2.5) decreased by up to 50%, 21%, 22% and 15% in different stages. The coefficient of SO2 on death from respiratory diseases decreased by up to 63.79%. The coefficients of NO2 on mortality from non-accidental causes, cardiovascular disease, and respiratory disease decreased by up to 0.95%, 1.34% and 0.54%. The coefficients of PM10, PM2.5 on mortality from cardiovascular diseases and respiratory disease were decreased by up to 0.19%, 0.31%, 0.65% and 0.36%. Continued improvements in air quality have reduced the acute impact on the health of the local population.

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Quantifying air quality co-benefits of climate policy across sectors and regions

Climatic Change ◽

10.1007/s10584-020-02685-7 ◽

2020 ◽

Vol 163 (3) ◽

pp. 1501-1517 ◽

Cited By ~ 3

Author(s):

Toon Vandyck ◽

Kimon Keramidas ◽

Stéphane Tchung-Ming ◽

Matthias Weitzel ◽

Rita Van Dingenen

Keyword(s):

Air Pollution ◽

Air Quality ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Climate Policy ◽

Ambient Air ◽

Air Pollutant ◽

Pollutant Emissions ◽

Gas Emissions ◽

Health Related

AbstractThe overlap in sources of greenhouse gas and local air pollutant emissions creates scope for policy measures to limit global warming and improve air quality simultaneously. In a first step, we derive estimates for the air pollution mortality-related component of the social cost of atmospheric release for 6 pollutants and 56 regions in the world. Combining these estimates with emission inventory data highlights that sector contributions to greenhouse gas emissions and air pollution health impacts differ widely across regions. Next, simulations of future emission pathways consistent with the 2 °C and 1.5 °C targets illustrate that strengthening climate policy ambition raises the total value of air quality co-benefits despite lower marginal co-benefits per tonne of greenhouse gas emissions abated. Finally, we use results from a multi-model ensemble to quantify and compare the value of health-related ambient air quality co-benefits of climate policy across sectors and regions. On the global level, overall air quality co-benefits range from $8 to $40 per tonne of greenhouse gases abated in 2030, with median across models and scenarios of $18/tCO2e. These results mask strong differentiation across regions and sectors, with median co-benefits from mitigation in the residential and service sectors in India exceeding $500/tCO2e. By taking a sector- and region-specific perspective, the results presented here reveal promising channels to improve human health outcomes and to ratchet up greenhouse gas reduction efforts to bridge the gap between countries’ pledges and the global targets of the Paris Agreement.

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Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in China's Jing-Jin-Ji area

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-2971-2017 ◽

2017 ◽

Vol 17 (4) ◽

pp. 2971-2980 ◽

Cited By ~ 65

Author(s):

Tingting Liu ◽

Sunling Gong ◽

Jianjun He ◽

Meng Yu ◽

Qifeng Wang ◽

...

Keyword(s):

Air Pollution ◽

Emission Control ◽

Northern China ◽

Air Pollutant ◽

Control Measures ◽

Air Pollution Control ◽

Emission Data ◽

Haze Pollution ◽

Stable Conditions ◽

Emission Control Measures

Abstract. In the 2015 winter month of December, northern China witnessed the most severe air pollution phenomena since the 2013 winter haze events occurred. This triggered the first-ever red alert in the air pollution control history of Beijing, with an instantaneous fine particulate matter (PM2. 5) concentration over 1 mg m−3. Air quality observations reveal large temporal–spatial variations in PM2. 5 concentrations over the Beijing–Tianjin–Hebei (Jing-Jin-Ji) area between 2014 and 2015. Compared to 2014, the PM2. 5 concentrations over the area decreased significantly in all months except November and December of 2015, with an increase of 36 % in December. Analysis shows that the PM2. 5 concentrations are significantly correlated with the local meteorological parameters in the Jing-Jin-Ji area such as the stable conditions, relative humidity (RH), and wind field. A comparison of two month simulations (December 2014 and 2015) with the same emission data was performed to explore and quantify the meteorological impacts on the PM2. 5 over the Jing-Jin-Ji area. Observation and modeling results show that the worsening meteorological conditions are the main reasons behind this unusual increase of air pollutant concentrations and that the emission control measures taken during this period of time have contributed to mitigate the air pollution ( ∼  9 %) in the region. This work provides a scientific insight into the emission control measures vs. the meteorology impacts for the period.

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Contributions of meteorology and emission to the 2015 winter severe haze pollution episodes in Northern China

10.5194/acp-2016-204 ◽

2016 ◽

Author(s):

Ting Ting Liu ◽

Sunling Gong ◽

Meng Yu ◽

Qi Chao Zhao ◽

Huai Rui Li ◽

...

Keyword(s):

Air Pollution ◽

Emission Control ◽

Northern China ◽

Air Pollutant ◽

Control Measures ◽

Air Pollution Control ◽

Pollutant Concentrations ◽

Haze Pollution ◽

Air Pollutant Concentrations ◽

Emission Control Measures

Abstract. Northern China in the 2015 winter months of November and December has witnessed the most severe air pollution phenomena since the 2013 winter haze events occurred, which triggered the first ever Red Alert in the air pollution control history of Beijing, with an instantaneous PM2.5 concentration over 1 mg m−3. Analysis and modeling results show that the worsening meteorology conditions are the main reason behind this unusual increase of air pollutant concentrations and the emission control measures taken during this period of time have contributed to mitigate the air pollution in the region. This work provides a scientific insight of the emission control measures vs. meteorology impacts for the period.

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“Warm cover”: precursory strong signals for haze pollution hidden in the middle troposphere

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-14131-2021 ◽

2021 ◽

Vol 21 (18) ◽

pp. 14131-14139

Author(s):

Xiangde Xu ◽

Wenyue Cai ◽

Tianliang Zhao ◽

Xinfa Qiu ◽

Wenhui Zhu ◽

...

Keyword(s):

Air Pollution ◽

Eastern China ◽

Air Pollutant ◽

Pollutant Emissions ◽

Ambient Atmosphere ◽

The Tibetan Plateau ◽

Vertical Diffusion ◽

Middle Troposphere ◽

Strong Signal ◽

Haze Pollution

Abstract. Eastern China (EC), located in the downstream region of the Tibetan Plateau (TP), is a large area with frequent haze pollution. In addition to air pollutant emissions, meteorological conditions are a key inducement for air pollution episodes. Based on the study of the Great Smog of London in 1952 and haze pollution in EC over recent decades, it is found that the abnormal “warm cover” (air–temperature anomalies) in the middle troposphere, as a precursory strong signal, could be connected to severe air pollution events. The convection and vertical diffusion in the atmospheric boundary layer (ABL) were suppressed by a relatively stable structure of warm cover in the middle troposphere leading to ABL height decreases, which were favorable for the accumulation of air pollutants in the ambient atmosphere. The anomalous structure of the troposphere's warm cover not only exist in heavy haze pollution on the daily scale, but also provide seasonal, interannual and interdecadal strong signals for frequently occurring regional haze pollution. It is revealed that a close relationship existed between interannual variations of the TP's heat source and the warm cover strong signal in the middle troposphere over EC. The warming TP could lead to anomalous warm cover in the middle troposphere from the plateau to the downstream EC region and even the entire East Asian region, thus causing frequent winter haze pollution in EC region.

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Warm Cover – Precursory Strong Signals hidden in the Middle Troposphere for Haze Pollution

10.5194/acp-2020-1140 ◽

2021 ◽

Author(s):

Xiangde Xu ◽

Wenyue Cai ◽

Tianliang Zhao ◽

Xinfa Qiu ◽

Wenhui Zhu ◽

...

Keyword(s):

Air Pollution ◽

Eastern China ◽

Air Pollutant ◽

Pollutant Emissions ◽

Ambient Atmosphere ◽

Large Area ◽

Middle Troposphere ◽

Haze Pollution ◽

Close Relationship ◽

Pollution Events

Abstract. Eastern China (EC), located on the downstream region of Tibetan Plateau (TP), is a large area that has become vulnerable to frequent haze. In addition of air pollutant emissions, meteorological conditions were a key inducement for air pollution episodes. Based on the study of the Great Smog of London in 1952 and haze pollution in EC over recent decades, it is found that the abnormal warm cover in the middle troposphere, as a precursory strong signal hidden, could connect to severe air pollution events. The convection and diffusion in the atmospheric boundary layer (ABL) were suppressed by a relatively stable structure of warm cover in the middle troposphere, leading to the ABL height decreases, which were favourable for the accumulation of air pollutants in the ambient atmosphere. The warming TP built the warm cover in the middle troposphere from the plateau to the downstream EC region and even the entire East Asian region. The frequent haze events in EC is connected with a significantly strong warm cover in the interdecadal variability. It is also revealed that a close relationship existed between interannual variations of the TP's heat source and the warm cover hidden in the middle troposphere over EC.

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Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in Northern China

10.5194/acp-2016-798 ◽

2016 ◽

Cited By ~ 1

Author(s):

Tingting Liu ◽

Sunling Gong ◽

Meng Yu ◽

Qichao Zhao ◽

Huairui Li ◽

...

Keyword(s):

Air Pollution ◽

Emission Control ◽

Northern China ◽

Air Pollutant ◽

Control Measures ◽

Air Pollution Control ◽

Pollutant Concentrations ◽

Haze Pollution ◽

Air Pollutant Concentrations ◽

Emission Control Measures

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Vicious Cycle of Economic Growth, Pm2.5 and COVID-19 Case of G7 Countries

10.31124/advance.12937019.v1 ◽

2020 ◽

Author(s):

Rıdvan Karacan

Keyword(s):

Economic Growth ◽

Air Pollution ◽

Particulate Matter ◽

Fossil Fuels ◽

Fine Particulate Matter ◽

Panel Cointegration ◽

Air Pollutant ◽

Population Exposure ◽

Causality Analysis ◽

G7 Countries

Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases. [1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).

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An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

Revista de Chimie ◽

10.37358/rc.17.4.5566 ◽

2017 ◽

Vol 68 (4) ◽

pp. 858-863

Author(s):

Mihaela Oprea ◽

Marius Olteanu ◽

Radu Teodor Ianache

Keyword(s):

Air Pollution ◽

Early Warning ◽

Urban Areas ◽

Early Warning System ◽

Urban Air Pollution ◽

Warning System ◽

Air Pollutant ◽

Pollution Level ◽

Urban Air ◽

Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

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Multiple air pollutant exposure and lung cancer in Tehran, Iran

Scientific Reports ◽

10.1038/s41598-021-88643-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zahra Khorrami ◽

Mohsen Pourkhosravani ◽

Maysam Rezapour ◽

Koorosh Etemad ◽

Seyed Mahmood Taghavi-Shahri ◽

...

Keyword(s):

Lung Cancer ◽

Air Pollution ◽

Cancer Incidence ◽

Latent Profile Analysis ◽

Negative Binomial ◽

Profile Analysis ◽

Positive Association ◽

Air Pollutant ◽

World Health ◽

Lung Cancer Incidence

AbstractLung cancer is the most rapidly increasing malignancy worldwide with an estimated 2.1 million cancer cases in the latest, 2018 World Health Organization (WHO) report. The objective of this study was to investigate the association of air pollution and lung cancer, in Tehran, Iran. Residential area information of the latest registered lung cancer cases that were diagnosed between 2014 and 2016 (N = 1,850) were inquired from the population-based cancer registry of Tehran. Long-term average exposure to PM10, SO2, NO, NO2, NOX, benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene (BTEX), and BTEX in 22 districts of Tehran were estimated using land use regression models. Latent profile analysis (LPA) was used to generate multi-pollutant exposure profiles. Negative binomial regression analysis was used to examine the association between air pollutants and lung cancer incidence. The districts with higher concentrations for all pollutants were mostly in downtown and around the railway station. Districts with a higher concentration for NOx (IRR = 1.05, for each 10 unit increase in air pollutant), benzene (IRR = 3.86), toluene (IRR = 1.50), ethylbenzene (IRR = 5.16), p-xylene (IRR = 9.41), o-xylene (IRR = 7.93), m-xylene (IRR = 2.63) and TBTEX (IRR = 1.21) were significantly associated with higher lung cancer incidence. Districts with a higher multiple air-pollution profile were also associated with more lung cancer incidence (IRR = 1.01). Our study shows a positive association between air pollution and lung cancer incidence. This association was stronger for, respectively, p-xylene, o-xylene, ethylbenzene, benzene, m-xylene and toluene.

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