Quantifying the reductions in mortality from air-pollution by cancelling new coal power plants

Deep decarbonization paths to the 1.5 °C or 2 °C temperature stabilization futures require a rapid reduction in coal-fired power plants, but many countries are continuing to build new ones. Coal-fired plants are also a major contributor to air pollution related health impacts. Here, we couple an integrated human-earth system model (GCAM) with an air quality model (TM5-FASST) to examine regional health co-benefits from cancelling new coal-fired plants worldwide. Our analysis considers the evolution of pollutants control based on coal plants vintage and regional policies. We find that cancelling all new proposed projects would decrease air pollution related premature mortality between 101,388–213,205 deaths (2–5%) in 2030, and 213,414–373,054 (5–8%) in 2050, globally, but heavily concentrated in developing Asia. These health co-benefits are comparable in magnitude to the values obtained by implementing the Nationally Determined Contributions (NDCs). Furthermore, we estimate that strengthening the climate target from 2 °C to 1.5 °C would avoid 326,351 additional mortalities in 2030, of which 251,011 (75%) are attributable to the incremental coal plant shutdown.The authors acknowledge funding support from Bloomberg Philanthropies. This research is also supported by Basque Government through the BERC 2018-2021 and the Spanish Government through María de Maeztu excellence accreditation MDM-2017-0714. Jon Sampedro and Ignacio Cazcarro acknowledge financial support from the Ministry of the Economy and Competitiveness of Spain (RTI2018-099858-A-100 and RTI2018-093352-B-I00). Jon Sampedro acknowledge financial support from the Basque Government (PRE_2017_2_0139). The authors thank Patrick O’Rourke and Brinda Yarlagadda for their support with data processing. The authors declare no competing interests

Nonlinear impacts of future anthropogenic aerosol emissions on Arctic warming

Past reductions of anthropogenic aerosol concentrations in Europe and North America could have amplified Arctic warming. In the future the impact of air pollution policies may differ, because the major anthropogenic sources of atmospheric aerosols are increasingly located in Asia. In this study numerical experiments evaluating only direct aerosol effects on atmospheric temperatures indicate that, while reduced carbon dioxide (CO2) emissions weaken Arctic warming, direct radiative forcing effects by reductions of anthropogenic aerosol concentrations, additional to those obtained by lower CO2 emissions, can either amplify or diminish it. Interactions between regionally modified radiation in Asia and internal climate variability may differently initiate and sustain atmospheric planetary waves propagating into the Arctic. In a nonlinear manner planetary waves may redistribute atmospheric and oceanic meridional heat fluxes at the high latitudes and either amplify or diminish Arctic warming in 2050. Lower CO2 concentrations might apparently contribute to reduce the interactions between the Arctic system and the lower latitudes, thus reducing the influence of strong air quality measures in Asia on the Arctic amplification of global warming. While past and present air pollution policies could have amplified Arctic warming, in the future the effects from atmospheric pollution reductions are less certain, depending on the future CO2 concentrations, and requiring improved simulations of changing aerosol concentrations and their interactions with clouds in Asia and the Arctic

Organic aerosol and global climate modelling: a review

The present paper reviews existing knowledge with regard to Organic Aerosol (OA) of importance for global climate modelling and defines critical gaps needed to reduce the involved uncertainties. All pieces required for the representation of OA in a global climate model are sketched out with special attention to Secondary Organic Aerosol (SOA): The emission estimates of primary carbonaceous particles and SOA precursor gases are summarized. The up-to-date understanding of the chemical formation and transformation of condensable organic material is outlined. Knowledge on the hygroscopicity of OA and measurements of optical properties of the organic aerosol constituents are summarized. The mechanisms of interactions of OA with clouds and dry and wet removal processes parameterisations in global models are outlined. This information is synthesized to provide a continuous analysis of the flow from the emitted material to the atmosphere up to the point of the climate impact of the produced organic aerosol. The sources of uncertainties at each step of this process are highlighted as areas that require further studies

Future air pollution in the Shared Socio-economic Pathways

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high, central, and low pollution control ambitions over the 21st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. The resulting pollutant emission trajectories under the SSP scenarios cover a wider range than the scenarios used in previous international climate model comparisons. In the SSP3 and SSP4 scenarios, where economic, institutional and technological limitations slow air quality improvements, global pollutant emissions over the 21st century can be comparable to current levels. Pollutant emissions in the SSP1 scenarios fall to low levels due to the assumption of technological advances and successful global action to control emissions

TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants

This paper describes, documents, and validates the TM5-FAst Scenario Screening Tool (TM5-FASST), a global reduced-form air quality source–receptor model that has been designed to compute ambient pollutant concentrations as well as a broad range of pollutant-related impacts on human health, agricultural crop production, and short-lived pollutant climate metrics, taking as input annual pollutant emission data aggregated at the national or regional level. The TM5-FASST tool, providing a trade-off between accuracy and applicability, is based on linearized emission-concentration sensitivities derived with the full chemistry-transport model TM5. The tool has been extensively applied in various recent critical studies. Although informal and fragmented validation has already been performed in various publications, this paper provides a comprehensive documentation of all components of the model and a validation against the full TM5 model. We find that the simplifications introduced in order to generate immediate results from emission scenarios do not compromise the validity of the output and as such TM5-FASST is proven to be a useful tool in science-policy analysis. Furthermore, it constitutes a suitable architecture for implementing the ensemble of source–receptor relations obtained in the frame of the HTAP modelling exercises, thus creating a link between the scientific community and policy-oriented users.</p

Processing of cloud condensation nuclei by collision-coalescence in a mesoscale model

This is the publisher's version, also available electronically from http://onlinelibrary.wiley.com/doi/10.1029/2006JD007183/abstract.The Naval Research Laboratory's Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS) is employed to explore the relative importance of source, sink, and transport processes in producing an accurate forecast of the aerosol-cloud-drizzle system. Cloud processing, defined to be the reduction of cloud condensation nuclei (CCN) via collision-coalescence, is not uniquely related to total particle concentration, a behavior which stems from the roughly inverse dependence on cloud droplet concentration between autoconversion and accretion depletion terms. Instead, the behavior of cloud processing in COAMPS suggests relationships (scalings) based on cloud base drizzle rate (R) and cloud droplet concentration (Nc). Cloud processing is found to be correlated with drizzle, a relationship that can be represented as a power law for drizzle rates less than 0.6 mm d−1. A scaling for cloud processing based on the product of Nc and R is accurate over a wider range of drizzle rates. Results from large eddy simulation with size-resolved microphysical processes demonstrate reasonable agreement with COAMPS and the two parameter scaling. Entrainment plays an important role in strongly modulating the mean marine boundary layer (MBL) concentration, both increasing and decreasing CCN, depending upon the entrainment velocity we and the difference between MBL and free tropospheric CCN concentrations. The importance of entrainment suggests that transport processes, especially in the vertical, play a fundamental role in the overall MBL CCN balance. In situ sources rates of CCN, taken to represent heterogeneous chemical processes and sea salt flux of submicron size particles from the ocean surface, must be unrealistically large in order to be of the same magnitude as cloud processing. Because of the prevailing importance of cloud processing and entrainment over timescales of a typical mesoscale forecast, we argue that incorporating accurate vertical aerosol profiles into the model update cycles, either from remote sensing or from global chemistry models, is more important than highly constrained local CCN source rates

LC‐IMPACT: A regionalized life cycle damage assessment method

Life cycle impact assessment (LCIA) is a lively field of research, and data and models are continuously improved in terms of impact pathways covered, reliability, and spatial detail. However, many of these advancements are scattered throughout the scientific literature, making it difficult for practitioners to apply the new models. Here, we present the LC‐IMPACT method that provides characterization factors at the damage level for 11 impact categories related to three areas of protection (human health, ecosystem quality, natural resources). Human health damage is quantified as disability adjusted life years, damage to ecosystem quality as global species extinction equivalents (based on potentially disappeared fraction of species), and damage to mineral resources as kilogram of extra ore extracted. Seven of the impact categories include spatial differentiation at various levels of spatial scale. The influence of value choices related to the time horizon and the level of scientific evidence of the impacts considered is quantified with four distinct sets of characterization factors. We demonstrate the applicability of the proposed method with an illustrative life cycle assessment example of different fuel options in Europe (petrol or biofuel). Differences between generic and regionalized impacts vary up to two orders of magnitude for some of the selected impact categories, highlighting the importance of spatial detail in LCIA. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges.info:eu-repo/semantics/publishedVersio

Global ozone and air quality: a multi-model assessment of risks to human health and crops

Within ACCENT, a European Network of Excellence, eighteen atmospheric models from the U.S., Europe, and Japan calculated present (2000) and future (2030) concentrations of ozone at the Earth's surface with hourly temporal resolution. Comparison of model results with surface ozone measurements in 14 world regions indicates that levels and seasonality of surface ozone in North America and Europe are characterized well by global models, with annual average biases typically within 5–10 nmol/mol. However, comparison with rather sparse observations over some regions suggest that most models overestimate annual ozone by 15–20 nmol/mol in some locations. Two scenarios from the International Institute for Applied Systems Analysis (IIASA) and one from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) have been implemented in the models. This study focuses on changes in near-surface ozone and their effects on human health and vegetation. Different indices and air quality standards are used to characterise air quality. We show that often the calculated changes in the different indices are closely inter-related. Indices using lower thresholds are more consistent between the models, and are recommended for global model analysis. Our analysis indicates that currently about two-thirds of the regions considered do not meet health air quality standards, whereas only 2–4 regions remain below the threshold. Calculated air quality exceedances show moderate deterioration by 2030 if current emissions legislation is followed and slight improvements if current emissions reduction technology is used optimally. For the "business as usual" scenario severe air quality problems are predicted. We show that model simulations of air quality indices are particularly sensitive to how well ozone is represented, and improved accuracy is needed for future projections. Additional measurements are needed to allow a more quantitative assessment of the risks to human health and vegetation from changing levels of surface ozone

Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015

Background Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels. Methods We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure–response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure–response functions spanning the global range of exposure. Findings Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000–422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015. Interpretation Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction