Unexpected Benefits of Reducing Aerosol Cooling Effects

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Unexpected benefits of reducing aerosol cooling effects jia xing, Jiandong Wang, Rohit Mathur, Jonathan Pleim, Shuxiao Wang, Christian Hogrefe, Chuen-Meei Gan, David wong, and Jiming Hao Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b00767 • Publication Date (Web): 16 Jun 2016 Downloaded from http://pubs.acs.org on June 17, 2016

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Environmental Science & Technology

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Unexpected benefits of reducing aerosol cooling effects

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Jia Xing1, 2, Jiandong Wang1, 2, Rohit Mathur2,*, Jonathan Pleim2, Shuxiao Wang1,*, Christian Hogrefe2, Chuen-

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Meei Gan2, David C. Wong2, Jiming Hao1

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1

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Tsinghua University, Beijing 100084, China

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2

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These authors contributed equally to this work: Jia Xing & Jiandong Wang

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*

State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment,

The U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA

Corresponding Author: Rohit Mathur (email: [email protected]; phone: 919-541-1483; fax: 919-541-

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1379); Shuxiao Wang (email: [email protected]; phone: +86-10-62771466; fax: +86-10-62773650)

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Abstract

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Impacts of aerosol cooling are not limited to changes in surface temperature since

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modulation of atmospheric dynamics resulting from the increased stability can deteriorate local

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air quality and impact human health. Health impacts from two manifestations of the aerosol

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direct effects (ADE) are estimated in this study: (1) the effect on surface temperature and (2) the

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effect on air quality through atmospheric dynamics. Average mortalities arising from the

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enhancement of surface PM2.5 concentration due to ADE in East Asia, North America and

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Europe are estimated to be 3-6 times higher than reduced mortality from decreases of

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temperature due to ADE. Our results suggest that mitigating aerosol pollution is beneficial in

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decreasing the impacts of climate change arising from these two manifestations of ADE health

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impacts. Thus, decreasing aerosol pollution gets direct benefits on health, and indirect benefits

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on health through changes in local climate and not offsetting changes associated only with

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temperature modulations as traditionally thought. The modulation of air pollution due to ADE

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also translates into an additional human health dividend in regions (e.g., U.S. Europe) with air

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pollution control measures but a penalty for regions (e.g., Asia) witnessing rapid deterioration in 1 ACS Paragon Plus Environment


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air quality.

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Introduction

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Aerosols can potentially compensate for the global warming effects of greenhouse gasses

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through light scattering and absorption, as well as by enhancing the optical thickness and lifetime

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of clouds, which is noted as the cooling effect1-3. Certain aerosol constituents (e.g., black and

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brown carbon) contribute to warming and are also detrimental to human health4-5. The radiative

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forcing due to aerosols including cloud adjustments due to aerosols, is currently estimated1 as –

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0.9 [–1.9 to −0.1] W m−2, which is comparable in magnitude to the total anthropogenic radiative

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forcing (i.e., 2.29 [1.13 to 3.33] W m−2). Thus, there is debate that aerosol mitigation efforts

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might be counterproductive since a reduction of aerosols could escalate warming, resulting in

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loss in human health6-8 due to rising global temperatures. Climate mitigation strategies that also

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benefit air quality and human health are desirable9. In the IPCC-2014 report (AR5) 1, reduction in

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aerosol air pollution is considered beneficial for protecting human health but in some instances

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suggested as detrimental to climate change mitigation. A recent study10 suggested that China’s

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eventual goal of improving air quality will result in changes in radiative forcing in the coming

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years, as a reduction of sulfur dioxide emissions would drive a faster future warming. However,

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it might not be true if the objective of climate change mitigation is changed to focus on

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mitigating the adverse impacts of climate change including adverse impacts on health. Studies4, 11

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suggest that the aerosol direct effects (ADE) associated modulation of atmospheric stability can

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effect air pollution through modification of atmospheric ventilation, changes in rainfall, thermal

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reactions, and temperature and wind-speed dependent emission rates of primary species. More

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importantly, ADE associated modulation of atmospheric stability can enhance air pollution12-14

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and the magnitude of such enhancements have been shown to grow with increasing atmospheric

2 ACS Paragon Plus Environment

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aerosol loading15. The “enhanced” air pollution level arising from the ADE brings extra threats to

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human health that have not yet been adequately quantified and remain uncertain in the debate on

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optimal climate-air quality mitigation strategies. Better understanding of impacts from aerosol

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cooling effects requires a comprehensive assessment with consideration of multiple

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manifestations of aerosol cooling effects. Recent multi-decadal and contrasting changes in

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aerosol burden across the globe enable a comprehensive assessment of health impacts from

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aerosol cooling wherein uncertainty in estimates can be constrained using long-term air pollution

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records from observations and model estimates based on carefully constructed emission trends.

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In this study, two effects from ADE, i.e., (1) the effect on surface temperature and (2) the effect

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on air quality through atmospheric dynamics are assessed separately by using a coupled regional

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climate-chemistry model and a community health assessment tool.

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Though the potential influence from future climate change has been extensively examined

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in recent studies2, uncertainties associated with future projections of population, emission, and

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climate limit the confidence in these assessments. To address this gap, this study estimates the

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ADE impacts from its constrained historical evolution rather than projected changes in the

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future. During the past two decades, developed countries have implemented extensive aerosol

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controls which have significantly improved their air quality. During the same period, developing

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countries have witnessed rapid economic and industrial growth, leading to significant changes in

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their local environment and climate. Such striking contrasts in air quality trends between

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developed and developing countries across the northern hemisphere have become more obvious

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in recent years, providing a unique opportunity to quantify the ADE impact from a historical and

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verifiable perspective. In this study, we estimate the ADE and its impacts on summertime

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mortality on a hemispheric scale from 1990 to 2010. We focus on summertime when the heat



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related health effects are the largest.

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Method

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The ADE and its impacts on air quality and temperature are estimated from numerical

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simulations with a coupled regional climate-chemistry model, i.e., Weather Research and

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Forecast (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model,

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developed by U.S. Environmental Protection Agency13,

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WRF-CMAQ system is detailed in our previous papers17, 19. Simulated aerosol composition and

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size distribution are used to estimate their optical properties which are then fed back to the

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RRTMG radiation module in WRF, thereby impacting the simulated atmospheric dynamics

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which in turn then impact emission rates, transport and dispersion, deposition, and temperature

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and actinic flux dependent chemical rate constants; in the current simulations these feedbacks

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occur at 20 minute intervals. Additionally, these direct effects on atmospheric dynamics can

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impact simulated resolved and sub-grid scale clouds in WRF which may then impact the

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simulated cloud mixing and removal of pollutants. However, the indirect radiative effects of

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aerosols, i.e., on cloud droplets and optical thickness are not included in the current calculations,

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due to associated large uncertainties in their representation; a parameterization of aerosol indirect

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effects on resolved scale clouds has recently been implemented in WRF-CMAQ20 and will be

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evaluated in more detail in subsequent studies. Multiple pollutants including gaseous species and

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primary and secondary aerosols are simulated in WRF-CMAQ model, by using the Carbon Bond

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05 gas-phase chemistry21 and AERO6 aerosol module22 in which the primary and secondary

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organic and inorganic (including elemental carbon and dust) aerosols are simulated. Aerosol size

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distribution is represented as a superposition of three lognormal modes, nominally representing

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the Aitken, accumulation, and coarse modes. Aerosol optical properties were calculated by using

16-18

. The description of the coupled


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the BHCOAT coated-sphere module approach23, i.e., particles in the Aitken and accumulation

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model are assumed to have a core composed of elemental carbon with a shell coating of other

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species. Assessment of the aerosol optics calculations in the WRF-CMAQ model are detailed in

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Gan et al24. Simulations were conducted for a 21-year period (1990-2010) over a northern

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hemispheric domain discretized with a horizontal grid spacing of 108 km. These simulations

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have previously been thoroughly evaluated against measurements to establish the model’s

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credibility in simulating trends in concentrations of a variety of gas and aerosol phase species25,

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associated impacts on trends in clear-sky shortwave radiation19,, and assessing relationships

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between trends in aerosol burden, radiation, and other climate relevant metrics15. Feedback and

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no-feedback cases were simulated by the same model configuration except that ADE were only

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considered in the feedback case19. In the no-feedback case, the aerosol effects on the radiation

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calculations were turned off13, 15. The baseline situation was estimated from the year-round no-

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feedback simulation. Additional feedback case was conducted for summertime (June, July and

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August) of this 21-year period. Changes in surface PM2.5 concentrations and surface temperature

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due to ADE are estimated from the difference between feedback and no-feedback simulations for

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summertime.

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To estimate the health impacts from aerosol pollution and temperature change, we used a

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modified version of the BenMAP- Community Edition, released by the U.S. EPA. In particular,

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the concentration-response function was modified based on the integrated exposure–response

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(IER) model from global burden of disease (GBD) study26-28. The long-term exposure to airborne

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aerosols has been associated with increased mortality from all-cause and cause-specific

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diseases29-30. The concentration-response functions used to assess PM2.5-related mortality were

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obtained from the GBD-IER model study31-33. The method that is used for heat-mortality



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estimation in this study uses prior relationships describing the health effect due to temperature

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change6,

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Naghavi et al.35. Gridded population data for 1990, 1995, 2000, 2005, 2010 was obtained from

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Gridded Population of the World, Version 3 (GPWv3) developed by Columbia University36. The

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population data for 1991-1994,1996-1999, 2001-2004, 2006-2009 was interpolated based on

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1990/1995, 1995/2000, 2000/2005 and 2005/2010 pairs respectively. The population age

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structures were obtained from Ahmad et al.37

28, 34

. The cause-specific mortality and all-cause mortality data were obtained from

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The PM2.5-related mortality estimated in this study includes five causes of mortality:

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ischemic heart disease (IHD), cerebrovascular disease (stroke), chronic obstructive pulmonary

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disease (COPD), lung cancer (LC) for adults over 25, and acute respiratory lung infection

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(ALRI) for children under 5. The method is based on Burnett et al.31, as summarized below: . =

,!"#$%&,'( ,)'

, × ×

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in which, incidence0,i is the baseline incidence rate of the cause-specific mortality of i. The value

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of incidence0,i refers to Naghavi et al.35. PAFi is population attributable fraction of the cause-

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specific mortality of i. The value of PAF is defined by the following function: = *++ − 1.⁄++

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in which, RRi is the relative risk for the cause-specific mortality of i, for 4 < 4 ,

++ *4. = 1

for 4 ≥ 4 ,

++ *4. = 1 + 8 × 91 − :;−< × *4 − 4 .= >?

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where, C is the ambient PM2.5 concentration and C0 is the threshold value (5.8-8.0 µg m-3) of

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PM2.5 concentration below which there is no additional risk assumed in this study. The parameter

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values of α, γ, and δ were given by distributions rather than fixed numbers32. For

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computational efficiency, a lookup table developed by Apte et al.32 was used for the estimates of 6 ACS Paragon Plus Environment

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RRi. The estimated range of relative risk for PM2.5 (ranging from 1 µg/m3 to 410 µg/m3 with the

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resolution of 0.1 µg/m3) is from 1 to 4.8 which varies with different endpoints and ages.

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The estimation of heat-mortality is based on previous studies on the health effects due to

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temperature change6,

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premature death due to heat waves and hot weather. These are estimated based on the case-

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crossover approach, which analyze heat-mortality data using conditional logistic regression to

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estimate the increased risk associated with elevated temperatures28. The summertime

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temperature-related mortality estimated in this study is calculated by the following function:

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28, 34

. The physical cause of reduction in mortality is the prevention of

@&AB&#C"D#& = × E:*F × ∆HI. − 1J ×

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where, incidence0 is the baseline incidence rate of

all-cause mortality. To simplify the

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estimation, the parameter β is derived from an epidemiological study conducted in California34.

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∆Temperature represents the temperature changes associated with ADE.

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One should note that, the Integrated exposure–response (IER) model from global burden of

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disease (GBD) is based on annual averages. Since few studies on seasonal differences are

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available, in this study we used summer (JJA) averaged PM2.5 concentrations and a quarter of

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annual cause-specific mortality for the estimation of summer-based mortality responses to ADE.

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However, considering that during winter the ADE effect should be larger and also that its

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importance relative to the T-effect will be higher, the summer-based estimates of ADE health

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impacts estimated in this study are likely on the conservative side.

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The PM2.5 related mortalities for each individual year was estimated using the PM2.5

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concentrations from the corresponding annual simulation without ADE. One should note that in

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the two heavily populated regions with poor air quality, i.e., East and South Asia, significant

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increases in mortality risks due to PM2.5, have occurred during the past two decades. Mortalities



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in East Asia and South Asia increased by 21% and 85% respectively, from 866 and 578 thousand

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in 1990, to 1048 and 1068 thousand in 2010 respectively. However, in developed regions

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including high-income North America and Europe, mortalities have been significantly reduced,

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with a reduction by 58% and 67% respectively, from 122 thousand and 418 thousand in 1990, to

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51 thousand and 137 thousand in 2010. Our estimates of mortality are comparable in magnitude

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with those reported in GBD33. For example, the PM2.5-related mortalities in East Asia, high-

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income North America and Europe in GBD are estimated as 1270, 110 and 420 thousand in

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2010. Populations in North Africa and the Middle East, Eastern and Western Sub-Saharan Africa

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were also confronted with a substantial growth of mortality risk due to PM2.5 over the past two

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decades, with estimated mortality increase of 38% and 53%, respectively.

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Results and discussion

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The ADE has a sequence of influences on the dynamics of the near-surface atmosphere

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(TOC/Abstract Art). Both aerosol scattering and absorption of incoming solar radiation result in

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reduced solar radiation impinging the ground (noted as ∆T-fb) causing reduced ground

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temperatures. Light-absorbing carbon aloft increases the temperature in the upper boundary

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layer12,

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atmosphere, leading to lower PBL height and ventilation14,

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concentrated locally resulting in more polluted conditions. For PM2.5, as an indicator for health

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risk assessment40, its concentration was estimated to be increased by 2.2-3.2% on summer

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average basis due to the ADE, though increases as high as 10% can occur during more polluted

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days15. Figure 1 displays the simulated average change in surface PM2.5 concentrations due to

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ADE during 1990-2010 (denoted as ∆PM2.5-fb, recreated from the Figure 9 in Xing et al. 15).

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Large ∆PM2.5-fb values are particularly prevalent in populated areas, e.g., East Asia, Eastern US

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. The change in the vertical profile of temperature results in a more stabilized 39


causing pollutants to be more

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and Europe. As displayed in Figure 2, ∆PM2.5-fb increases with increasing population densities

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in all three regions. Particularly in East Asia, the ∆PM2.5-fb increases from 0 (i.e., no effects from

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ADE) to more than 1.5 µg m-3. The ∆PM2.5-fb in Europe also exhibits a continual increase with

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increasing population density within the region. Some negative ∆PM2.5-fb values are noted in

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North America, which are associated with the dust region in mid-west U.S. where surface PM2.5

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concentrations is reduced due to the reduction of wind-blown dust emissions from lower wind

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speed stemming from ADE. However, larger positive ∆PM2.5-fb are present in more populated

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locations in North America. Such strong positive correlations between the ∆PM2.5-fb with

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distributions of population might be explained by the fact that emission sources, e.g., on-road

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vehicles, industries and domestic usage, are usually located in areas of high population density.

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Higher aerosol loading causes stronger ADE, resulting in more serious pollution conditions in

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higher population areas, indicating that more significant impacts on mortality can be expected

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due to the ADE’s enhancement effect on air pollution concentrations.

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Estimated annual mortalities due to PM2.5 in 7 regions (definition in Table 1) across the

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northern hemisphere from 1990 to 2010 are summarized in Table 2. Analysis of trends and

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sensitivity of the baseline mortalities41 suggests that the increased health risk from the

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deterioration of air quality in East Asia and South Asia offset the benefits of PM2.5-mortality

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reduction from the improvement in living conditions and the quality of medical care. In contrast,

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in Europe and high-income North America, the decrease in PM2.5 concentrations is the major

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reason for the PM2.5-mortality reduction. The ADE impacts mortality in two different ways but

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with opposite effects. The reduction effect from the decrease of surface temperature due to the

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ADE (∆T-fb) is displayed in Figure 3a. Large reductions in mortality are evident in populated

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regions such as East Asia, India, US, Europe, west sub-Sahara area. However, mortalities in all



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those regions except southwest India (downwind of dust area) were also significantly increased

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by the ADE enhancement effect through the increase of surface PM2.5 concentration (∆PM2.5-fb)

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(Figure 3b). In addition, the reduction of mortality by ∆T-fb is overwhelmed by the mortality

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increase due to ∆PM2.5-fb in most non-dust regions (Figure 3c). The 21-yr averaged summertime

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mortality reductions by ∆T-fb in East Asia, North America, Europe are estimated to be 1320,

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225, 442, respectively, while mortality increases arising from ∆PM2.5-fb in the three regions are

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estimated to be 4855, 695, 2459, respectively, the magnitude of which are 3-6 times higher than

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the reduction due to ∆T-fb, indicating that the ADE has an overall enhancement effect on

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mortality in non-dust regions. The simulated PM2.5 burden across India is comprised of both an

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anthropogenic and wind-blown dust (local and transported) component. The net negative ADE

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impact in the region primarily arises because of the disproportionately larger contribution of

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dust, due to reasons explained earlier for regions influenced by windblown dust. Nevertheless, it

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should be noted that in isolation ∆PM2.5-fb due to anthropogenic emissions in the region do

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translate to a net increased mortality.

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From the historical trend of mortality changes due to the ADE in East Asia, North America

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and Europe displayed in Figure 4, it is evident that all three regions exhibited excess mortality

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due to the ADE in the past two decades. Associated with the increase in population-weighted

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PM2.5 from 1990-2010, a continual increasing trend of this excess mortality is noted in East Asia.

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The excess mortality caused by ADE in this region increased by 11.3%, from +3187 in 1990 to

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+3548 in 2010, suggesting that ADE resulted in an additional penalty to human health from the

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continuous deterioration in air quality since 1990. In contrast, in Europe and North America, a

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declining trend of excess mortality is attributable to the decrease in PM2.5 stemming from strict

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controls on particulate matter and precursor emissions. The excess mortality due to ADE in


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Europe and North America was reduced by 64.4%, 46.9%, respectively, from 3338 and 599 in

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1990, to 1189 and 318 in 2010. This implies that the air pollution control actions in these regions

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aimed at reducing pollution-related mortality (such as the U.S. Clean Air Act) had the additional

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benefit of reducing the mortality arising from the ADE, making the controls even more effective

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in improving human well-being than originally projected. The importance of measures to control

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ambient aerosols is emphasized. For East Asia, the continuing deterioration of air quality leads to

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serious health damages which can be even significantly worse due to the ADE.

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The increase of aerosol loading is not uniformly distributed across space but rather is

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strongly related to the spatial distribution of population, indicating more significant impacts on

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human health. In addition, rapid urbanization and rising population densities in developing

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countries lead to even worse living conditions for their people. Estimates of health impacts

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depend on the product of aerosol concentration and population density. More serious health

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impacts from aerosols have been found in this study due to these two highly correlated factors.

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Mortality arising from ADE is estimated to be 3548 in East Asia for 2010 summer time. A simple

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extrapolation of this to an annual basis (i.e., multiply by 4; about 10 thousand) suggests that this

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increase is comparable to the annual increase of PM2.5-related mortality due to increased

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emissions witnessed during the 1990-2010 time period (Table 2). These results emphasize that

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health risks arising from the ADE are large enough to be considered in future health assessments

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of aerosols and in deliberations related to the role of anthropogenic influences on climate. Our

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results confirm the notion that if anthropogenic influences on climate are only measured in terms

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of temperature change, then controlling aerosol pollution though beneficial to protecting human

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health may be viewed as detrimental to climate change mitigation. However, they also show that

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mitigating aerosol pollution is beneficial in decreasing the impacts of climate change. Thus,



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decreasing aerosol pollution gets direct benefits on health, and indirect benefits on health through

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changes in local climate (not offsetting changes).

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Fine particles in the air are injurious to human health, reduce visibility, but cool surface-

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temperatures thereby partially offsetting the warming from greenhouse gases. The induced

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cooling (ADE) also impacts the ventilation, especially in polluted and populated regions, which

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in turn exacerbate air pollution and associated human exposure. A combined assessment of these

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effects for historical and documented changes in the state of our atmosphere performed in this

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study, show that mitigating aerosol pollution is beneficial in decreasing the impacts of climate

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change. Air pollution changes due to ADE translate to additional health benefits in regions with

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control measures, but a penalty in regions witnessing air quality deterioration. The health

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assessment in this study was conducted based on summer conditions. The seasonal variability of

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PM2.5 concentration might cause uncertainties in the estimation of ADE associated mortalities

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since the health function is based on annual estimates. The mortality reduced by the cooling

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effect of ADE is likely smaller in other seasons compared to that in summer. One the other hand,

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the enhancement of PM2.5 due to the ADE could be even larger in winter39. Thus these summer-

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based estimates can be considered to be on the conservative side of the annual ADE.

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This study has attempted to systematically assess two manifestations of aerosol direct

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effects through careful examination of their past trends in response to changes in emissions.

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However, aerosol indirect effects related to clouds42 can also alter meteorology and resulting air

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pollution and thus might have additional contributions to the PM2.5-mortalities as assessed here.

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Recent measurements and modeling efforts are improving the characterization of aerosol indirect

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effects. A comprehensive assessment of health impacts from both aerosol direct and indirect

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effects is thus suggested for future studies. Though this study only focused on the surface PM2.5


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concentrations, the ADE related pollution enhancement due to reduced atmospheric ventilation

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also applies to other pollutants15, such as CO, SO2, NO2 and O3. Consequently the combined

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multi-pollutant health risks could be even larger than those previously estimated without

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consideration of ADE and those presented here.

279 280

Acknowledgements

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Although this work has been reviewed and approved for publication by the U.S.

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Environmental Protection Agency (EPA), it does not reflect the views and policies of the agency.

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Mention of trade names or commercial products does not constitute endorsement. We thank

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Terry Keating, Bryan Hubbell, Chris Nolte, Jason Sachs, Neal Fann (EPA) and the two

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anonymous reviewers for helpful suggestions on initial versions of this manuscript. This work

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was supported in part by an inter-agency agreement between the Department of energy project

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(IA number is DE-SC000378) and EPA (IA number is RW-89-9233260 1), also the MEP’s

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Special Funds for Research on Public Welfare (201409002) and Strategic Priority Research

289

Program of the Chinese Academy of Sciences (XDB05020300). This research was performed

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while Jia Xing and Chuen-Meei Gan held a National Research Council Research Associateship

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Award at US EPA, and Jiandong Wang held a China Scholar Council Award at US EPA. The

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authors gratefully acknowledge the availability of population data from GPW and cause of death

293

data from HEI.

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Table 1 Regions defined in this study

418 419

Region East Asia High-income North America

Europe

South Asia High-income Asia Pacific North Africa and Middle East Eastern and Western SubSaharan Africa

Country China, North Korea U.S.A, Canada Albania, Andorra, Armenia, Austria, Azerbaijan, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Macedonia, Malta, Moldova, Monaco, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Russia, San Marino, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom, Vatican City, Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka, Brunei, Japan, South Korea, Singapore Algeria, Bahrain, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Yemen, United Arab Emirates, Libya, Morocco, Oman, Palestine, Israel, Qatar, Saudi Arabia, Sudan, Syria, Tunisia Burundi, Comoros, Djibouti, Eritrea, Ethiopia, Kenya, Madagascar, Mauritius, Rwanda, Seychelles, Somalia, Tanzania, Uganda, South Sudan, Benin, Burkina Faso, Cameroon, Cape Verde, Chad, Cote d’Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Sao Tome and Principe, Senegal, Sierra Leone, Togo



420 421 422 423

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Table 2 Annual PM2.5 related mortalities (thousand. The PM2.5 related mortalities were estimated by using the PM2.5 concentrations from the year-round no feedback simulations)

Year

East Asia

South Asia

High-income Asia Pacific

High-income North America

Europe

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Annual incr.

866 901 936 909 934 940 976 955 963 927 920 958 948 983 1034 1019 1076 1089 1109 1087 1048 +10

578 669 708 656 696 710 776 809 819 880 924 921 967 983 975 948 989 1077 1107 1141 1068 +26

108 100 104 102 100 93 99 99 96 91 93 91 85 86 85 82 90 90 89 89 80 -1

122 104 94 91 97 92 91 84 88 87 84 82 74 77 71 73 63 65 62 55 51 -3

418 442 393 412 373 331 352 277 248 232 234 226 209 248 194 203 182 155 139 139 137 -16

424 425 426 427


North Africa and Middle East 124 145 139 121 130 112 130 123 130 128 137 149 146 163 172 155 163 174 174 168 171 +3

Eastern and Western SubSaharan Africa 96 103 119 103 117 116 107 111 133 115 137 126 135 124 142 138 134 161 166 142 147 +3

Page 19 of 23


428 429

430 431 432

TOC/Abstract Art: ADE impacts on atmospheric dynamics, air pollution and human health

433



434 435 436 437 438

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Figure 1 Enhancement of surface PM2.5 concentration due to ADE (∆PM2.5-fb) through atmospheric dynamics: estimates of surface PM2.5 concentration changes (1990-2010 summer averages, values in sparsely populated areas are set to zero). Map used in this figure was created using ArcGIS software by Esri (www.esri.com).


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439 440 (a) East Asia

441 442 443 444

(b) North America

(c) Europe

Figure 2 Distribution of surface PM2.5 concentration changes due to ADE (∆PM2.5-fb) across grid cells grouped by populations (19902010 summer averages).



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445 446 (a) Due to ∆T-fb

447 448 449 450 451

(b) Due to ∆PM2.5-fb

(b) Due to (∆PM2.5-fb + ∆T-fb)

Figure 3 Mortality changes due to ADE from PM2.5 changes and Temperature changes (1990-2010 summer averages, values indicate the number in each 108×108km2 grid cell and values in sparsely populated areas are set to zero). Maps used in this figure were created using ArcGIS software by Esri (www.esri.com).



6000

∆Excess mortality due to ADE

Excess mortality due to ADE

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5000 4000 3000 2000 1000 0 1990

1000 0 mitigation

1995

2000

2005

-2000 -3000

2010

East Aisa

deterioration

-1000

-10

Europe 452 453 454 455 456 457 458 459 460 461

penalty

2000

dividend -5 0 5 10 15 ∆population-weighted PM2.5

20

North America

Figure 4 Historical trend in excess mortality due to ADE. Left: dash-line represents the response to enhanced PM2.5 concentration, solid-line represents the response to overall effects of enhanced PM2.5 concentration and decreased temperature; Right: Relationship between changes in excess mortality due to ADE and population-weighted PM2.5 relative to 1990. Each point represents a year in the 1991-2010 analysis period and measures the change relative to the 1990 value for both the ADE excess mortality and the regional population weighted PM2.5 Reductions in PM2.5 values have thus reduced the ADE related mortality and can be viewed as a dividend from the air pollution control measures. Increase in emissions of PM2.5 and precursors in conjunction with population growth as currently being witnessed across large parts of Asia will further exacerbate air pollution in these regions resulting in an additional penalty from uncontrolled growth.


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