Chinese emissions reductions deliver reduced PM2.5-caused mortality across China during 2015-2017

Silver, Ben; Conibear, Luke; Reddington, Carly L.; Knote, C.; Arnold, S.; Spracklen, Dominick V.

doi:10.5194/egusphere-egu2020-19729

Cited by 6 publications

(22 citation statements)

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“…Air pollution exposure is a leading public health problem in China (GBD 2017 Risk Factor Collaborators, 2018; Yin et al., 2020). Despite recent improvements in the air quality of China, air pollution exposure remains high, requiring further emission reductions to improve public health (Silver et al., 2020; Zhao et al., 2018). The impacts of potential emission changes on air quality can be determined through chemical transport model simulations.…”

Section: Introductionmentioning

confidence: 99%

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

et al. 2021

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Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China.The emulators were optimised based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51−94% of first−order sensitivity index), industrial (7−31%), and agricultural emissions (0−24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68−81% down to 15.3−25.9 g m −3 , remaining above the World Health Organization annual guideline of 10 g m −3 . The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasising the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 g m −3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors.

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Section: Introductionmentioning

confidence: 99%

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

et al. 2021

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“…Simulations were conducted using the Weather Research and Forecasting model online‐coupled with Chemistry (WRFChem) version 3.7.1 (Grell et al., 2005; Skamarock et al., 2008). Detailed information on the model setup is provided in Table and in our previous work (Reddington et al., 2019; Silver et al., 2020a). The model domain covered China at 30 km (∼0.3°) horizontal resolution with a 10 km (∼0.1°) nest over the GBA (Figure S1).…”

Section: Methodsmentioning

confidence: 99%

“…(2018). The same model setup was evaluated in our previous work (Reddington et al., 2019; Silver et al., 2020a). For the first set of simulations in 2014, we evaluated PM 2.5 concentrations from the nested domain over the GBA.…”

Section: Methodsmentioning

confidence: 99%

“…There was a 5% reduction in the loss of healthy life associated with air pollution exposure from 2013 to 2017 (8.0%, 95UI: 6.9 to 9.0, GBD 2017 Risk Factor Collaborators, 2018). This improvement in public health was primarily attributed to reduced PM 2.5 exposure, resulting from emission reductions of the 2013–2017 Air Pollution Prevention and Control Action Plan (APPCAP, Cheng et al., 2019; Ding et al., 2019; Guo et al., 2018; J. Huang et al., 2018; X. Jiang et al., 2015; Li et al., 2019a Ministry of Environmental Protection of China, 2013; Silver et al., 2020a; B. Zheng et al., 2018; Y. Zheng et al., 2017b). For example, a key region targeted by the APPCAP was the PRD which achieved a 28% reduction in ambient PM 2.5 concentrations (from 47 μg m −3 to 34 μg m −3 ), exceeding the targeted 15% reduction (China Ministry of Ecological Environment, 2013, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…This highlights the difficulty in simultaneously reducing local PM 2.5 and O 3 concentrations (H. Liu et al., 2013). Indeed, long−term monitoring studies show PM 2.5 concentrations across the PRD and GBA have declined in recent years, whereas O 3 concentrations have increased (Silver et al., 2020a; Silver et al., 2018). Despite improvements, PM 2.5 concentrations across the GBA are still damaging to public health.…”

Section: Introductionmentioning

confidence: 99%

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Regional Policies Targeting Residential Solid Fuel and Agricultural Emissions Can Improve Air Quality and Public Health in the Greater Bay Area and Across China

et al. 2021

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Air pollution exposure is a leading public health problem in China. The majority of the total air pollution disease burden is from fine particulate matter (PM2.5) exposure, with smaller contributions from ozone (O3) exposure. Recent emission reductions have reduced PM2.5 exposure. However, levels of exposure and the associated risk remain high, some pollutant emissions have increased, and some sectors lack effective emission control measures. We quantified the potential impacts of relevant policy scenarios on ambient air quality and public health across China. We show that PM2.5 exposure inside the Greater Bay Area (GBA) is strongly controlled by emissions outside the GBA. We find that reductions in residential solid fuel use and agricultural fertilizer emissions result in the greatest reductions in PM2.5 exposure and the largest health benefits. A 50% transition from residential solid fuel use to liquefied petroleum gas outside the GBA reduced PM2.5 exposure by 15% in China and 3% within the GBA, and avoided 191,400 premature deaths each year across China. Reducing agricultural fertilizer emissions of ammonia by 30% outside the GBA reduced PM2.5 exposure by 4% in China and 3% in the GBA, avoiding 56,500 annual premature deaths across China. Our simulations suggest that reducing residential solid fuel or industrial emissions will reduce both PM2.5 and O3 exposure, whereas other policies may increase O3 exposure. Improving particulate air quality inside the GBA will require consideration of residential solid fuel and agricultural sectors, which currently lack targeted policies, and regional cooperation both inside and outside the GBA.

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Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong‐Hong Kong‐Macau Greater Bay Area of China Using a Regional‐To‐Local Coupling Model

et al. 2022

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Ultrahigh‐resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM2.5) concentrations over the past decade has triggered ozone (O3) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh‐resolution perspective. We propose a regional‐to‐local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NOx) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NOx, PM2.5, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO2 and PM2.5 but increased O3 concentrations in urban areas. Guangzhou is located in a VOC‐limited O3 formation regime, and traffic is a key factor in controlling NOx and O3. The reduced industrial VOC scenario leads to reduced O3 concentrations throughout the mitigation domain. The maximum decrease in median hourly NO2 is >11 μg/m³, and the maximum increase in the median daily maximum 8‐hr rolling O3 is >10 μg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O3 increase reduces to <7 μg/m³. The daily averaged PM2.5 decreases by <2 μg/m³ for the reduced traffic scenario and varies little for the reduced industrial VOC scenario. An O3 episode analysis of the dual‐control scenario leads to O3 decreases of up to 15 μg/m³ (8‐hr metric) and 25 μg/m³ (1‐hr metric) in rural areas.

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Chinese emissions reductions deliver reduced PM2.5-caused mortality across China during 2015-2017

Cited by 6 publications

References 0 publications

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Regional Policies Targeting Residential Solid Fuel and Agricultural Emissions Can Improve Air Quality and Public Health in the Greater Bay Area and Across China

Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong‐Hong Kong‐Macau Greater Bay Area of China Using a Regional‐To‐Local Coupling Model

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