25 research outputs found
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Megacities and climate change: a brief overview
Cities have developed into the hotspots of human economic activity. From the appearance of the first cities in the Neolithic to 21st century metropolis their impact on the environment has always been apparent. With more people living in cities than in rural environments now it becomes crucial to understand these environmental impacts. With the immergence of megacities in the 20th century and their continued growth in both, population and economic power, the environmental impact has reached the global scale. In this paper we examine megacity impacts on atmospheric composition and climate. We present basic concepts, discuss various definitions of footprints, summarize research on megacity impacts and assess the impact of megacity emissions on air quality and on the climate at the regional to global scale. The intention and ambition of this paper is to give a comprehensive but brief overview of the science with regard to megacities and the environment
The ozoneâclimate penalty over South America and Africa by 2100
Climate change has the potential to increase surface ozone (O3) concentrations, known as the âozoneâclimate penaltyâ, through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozoneâclimate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15âppb (model range 12 to 18âppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozoneâclimate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx-limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low-NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozoneâclimate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario
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Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations
We document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 (GC3.1) and UKESM1, which are contributing to the 6th Coupled Model Intercomparison Project (CMIP6). The simulation of aerosols in the present-day period of the historical ensemble of these models is evaluated against a range of observations. Updates to the aerosol microphysics scheme are documented as well as differences in the aerosol representation between the physical and Earth system configurations. The additional Earth-system interactions included in UKESM1 leads to differences in the emissions of natural aerosol sources such as dimethyl sulfide, mineral dust and organic aerosol and subsequent evolution of these species in the model. UKESM1 also includes a stratospheric-tropospheric chemistry scheme which is fully coupled to the aerosol scheme, while GC3.1 employs a simplified aerosol chemistry mechanism driven by prescribed monthly climatologies of the relevant oxidants. Overall, the simulated speciated aerosol mass concentrations compare reasonably well with observations. Both models capture the negative trend in sulfate aerosol concentrations over Europe and the eastern United States of America (US) although the models tend to underestimate the sulfate concentrations in both regions. Interactive emissions of biogenic volatile organic compounds in UKESM1 lead to an improved agreement of organic aerosol over the US. Simulated dust burdens are similar in both models despite a 2-fold difference in dust emissions. Aerosol optical depth is biased low in dust source and outflow regions but performs well in other regions compared to a number of satellite and ground-based retrievals of aerosol optical depth. Simulated aerosol number concentrations are generally within a factor of 2
of the observations with both models tending to overestimate number concentrations over remote ocean regions, apart from at high latitudes, and underestimate over Northern Hemisphere continents. Finally, a new primary marine organic aerosol source is implemented in UKESM1 for the first time. The impact of this new aerosol source is evaluated. Over the pristine Southern Ocean, it is found to improve the seasonal cycle of organic aerosol mass and cloud droplet number concentrations relative to GC3.1 although underestimations in cloud droplet number concentrations remain. This paper provides a useful characterization of the aerosol climatology in both models facilitating the understanding of the numerous aerosol-climate interaction studies that will be conducted as part of CMIP6 and beyond
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UKESM1: description and evaluation of the UK Earth System Model
We document the development of the first version of the United Kingdom Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2âES, with enhancements to all component models and new feedback mechanisms. These include: a new core physical model with a wellâresolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; troposphericâstratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane and nitrous oxide; twoâmoment, fiveâspecies, modal aerosol; and ocean biogeochemistry with twoâway coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities, and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall the model performs well, with a stable preâindustrial state, and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits strongerâthanâobserved cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealised simulations show a high climate sensitivity relative to previous generations of models: equilibrium climate sensitivity (ECS) is 5.4 K, transient climate response (TCR) ranges from 2.68 K to 2.85 K, and transient climate response to cumulative emissions (TCRE) is 2.49 K/TtC to 2.66 K/TtC
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Changes in extreme events over Asia for present and future climate conditions based on a modelling analysis of atmospheric circulation anomalies
Synoptic weather and larger scale circulation patterns are closely coupled and have a major influence on regional weather and extreme events. This study examines the role of regional circulations on meteorology and extreme events for the present and future years over Asia with the WRF model driven by HadGEM2 global model boundary conditions that includes RCP4.5 scenarios based bicentennial transient simulation. The regional scale analysis was based on boundary conditions derived from 40 years of global model outputs spanning periods of 1995-2005, 2015-2025, 2025-2035 and 2045-2055. For brevity these periods are labelled as 2000, 2020, 2030, 2050 and 'represent' decadal periods centered around the named years. Model results were compared and validated (using a number of skill metrics) against observations for the present period showing that the model is able to delineate the observed features within 95% confidence level compared to the annual mean. To characterise and quantify the changes in the circulation patterns, an Empirical Orthogonal Function (EOF) based analysis was conducted. Results indicate that wintertime minimum temperatures are projected to increase by 3 - 4 0C over Asia by 2050 compared to reference period of 2000. Furthermore, anti-cyclonic activity associated with low PV anomalies and high positive temperature anomalies may be a key driver that influence the increase in frequency and duration of heat waves and droughts over SA, SEA, EA and NA regions of Asia. Overall, the modelling results suggest that regional meteorology and circulation patterns may significantly influence extremes over Asia in the future. Such impacts will have major implications for weather patterns as well as for air pollution over the region both of which will require policy responses to adjust to a changing regional climate
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The role of future anthropogenic methane emissions in air quality and climate
Funder: National Centre for Atmospheric Science (NCAS); doi: https://doi.org/10.13039/501100000662Funder: Met Office Hadley Centre Climate ProgrammeAbstractMitigation of greenhouse gas emissions is crucial for achieving the goals of the Paris climate agreement. One key gas is methane, whose representation in most climate models is limited by using prescribed surface concentrations. Here we use a new, methane emissions-driven version of the UK Earth System Model (UKESM1) and simulate a zero anthropogenic methane emissions scenario (ZAME) in order to (i) attribute the role of anthropogenic methane emissions on the Earth system and (ii) bracket the potential for theoretical maximum mitigation. We find profound, rapid and sustained impacts on atmospheric composition and climate, compared to a counterfactual projection (SSP3-7.0, the âworst caseâ scenario for methane). In ZAME, methane declines to below pre-industrial levels within 12 years and global surface ozone decreases to levels seen in the 1970s. By 2050, 690,000 premature deaths per year and 1° of warming can be attributed to anthropogenic methane in SSP3-7.0. This work demonstrates the significant maximum potential of methane emissions reductions, and their air-quality co-benefits, but also reiterates the need for action on carbon dioxide (CO2) emissions. We show that a methane emissions-driven treatment is essential for simulating the full Earth system impacts and feedbacks of methane emissions changes.</jats:p
Representing socio-economic factors in the INFERNO global fire model using the Human Development Index
Humans can act as fire starters or suppressors, changing ïŹre regimes by increasing the number of ignitions, changing their timing, and altering fuel structure and abundance, which can be considered a humanâenvironmental coupling. Considering the human influences on fire activity, representing socio-economic impacts on fires in global fire models is crucial to underpin the confidence in these modelling frameworks. In this work we implement a socio-economic factor in the fire ignition and suppression parametrisation in INFERNO based on a Human Development Index (HDI). HDI captures human development's income, health, and education dimensions leading to a representation where if there is more effort to improve human development, the population also invests in higher fire suppression. Including this representation of socio-economic factors in INFERNO reduces the annual mean burnt area (between 1997â2016) positive biases found in Temperate North America, Central America, Europe and Southern Hemisphere South America, by more than 100 % without statistically significant impact to other areas. In addition, it improves the representation of the burnt area trends, especially in Africa. Central Asia and Australia where observations show negative trends. Including socio-economic impacts on fire based on HDI in INFERNO provides a simple and linear representation of these effects on fire ignition and suppression, leading to an improvement of the model performance, especially in developed regions, These impacts are especially relevant to understand future climate regimes and inform policymakers on effects of fire policy in a changing climate
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The role of future anthropogenic methane emissions in air quality and climate
Mitigation of greenhouse gas emissions is crucial for achieving the goals of the Paris climate agreement. One key gas is methane, whose representation in most climate models is limited by using prescribed surface concentrations. Here we use a new, methane emissions-driven version of the UK Earth System Model (UKESM1) and simulate a zero anthropogenic methane emissions scenario (ZAME) in order to (i) attribute the role of anthropogenic methane emissions on the Earth system and (ii) bracket the potential for theoretical maximum mitigation. We find profound, rapid and sustained impacts on atmospheric composition and climate, compared to a counterfactual projection (SSP3-7.0, the 'worst case' scenario for methane). In ZAME, methane declines to below pre-industrial levels within 12 years and global surface ozone decreases to levels seen in the 1970s. By 2050, 690,000 premature deaths per year and 1 degree of warming can be attributed to anthropogenic methane in SSP3-7.0. This work demonstrates the significant maximum potential of methane emissions reductions, and their air-quality co-benefits, but also reiterates the need for action on carbon dioxide (CO2) emissions. We show that a methane emissions-driven treatment is essential for simulating the full Earth system impacts and feedbacks of methane emissions changes.Met Office Hadley Centre Climate Programme funded by BEIS and Defra (grant no. GA1101
Coupling interactive fire with atmospheric composition and climate in the UK Earth System Model
Summarization: Fire constitutes a key process in the Earth system (ES), being driven by climate as well as affecting the climate by changing atmospheric composition and impacting the terrestrial carbon cycle. However, studies on the effects of fires on atmospheric composition, radiative forcing and climate have been limited to date, as the current generation of ES models (ESMs) does not include fully atmosphereâcompositionâvegetation coupled fires feedbacks. The aim of this work is to develop and evaluate a fully coupled fireâcompositionâclimate ES model. For this, the INteractive Fires and Emissions algoRithm for Natural envirOnments (INFERNO) fire model is coupled to the atmosphere-only configuration of the UK's Earth System Model (UKESM1). This fireâatmosphere interaction through atmospheric chemistry and aerosols allows for fire emissions to influence radiation, clouds and generally weather, which can consequently influence the meteorological drivers of fire. Additionally, INFERNO is updated based on recent developments in the literature to improve the representation of human and/or economic factors in the anthropogenic ignition and suppression of fire. This work presents an assessment of the effects of interactive fire coupling on atmospheric composition and climate compared to the standard UKESM1 configuration that uses prescribed fire emissions. Results show a similar performance when using the fireâatmosphere coupling (the âonlineâ version of the model) when compared to the offline UKESM1 that uses prescribed fire. The model can reproduce observed present-day global fire emissions of carbon monoxide (CO) and aerosols, despite underestimating the global average burnt area. However, at a regional scale, there is an overestimation of fire emissions over Africa due to the misrepresentation of the underlying vegetation types and an underestimation over equatorial Asia due to a lack of representation of peat fires. Despite this, comparing model results with observations of CO column mixing ratio and aerosol optical depth (AOD) show that the fireâatmosphere coupled configuration has a similar performance when compared to UKESM1. In fact, including the interactive biomass burning emissions improves the interannual CO atmospheric column variability and consequently its seasonality over the main biomass burning regions â Africa and South America. Similarly, for aerosols, the AOD results broadly agree with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations.Presented on: Geoscientific Model Developmen
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Evaluation of tropospheric ozone and ozone precursors in simulations from the HTAPII and CCMI model intercomparisons â a focus on the Indian Subcontinent
Abstract. Here we present results from an evaluation of model simulations from the International Hemispheric Transport of Air Pollution Phase II (HTAPII) and Chemistry Climate Model Initiative (CCMI) model inter-comparison projects against a comprehensive series of ground based, aircraft and satellite observations of ozone mixing ratios made at various locations across India. The study focuses on the recent past (observations from 2008â2013, models from 2008â2010) as this is most pertinent to understanding the health impacts of ozone. To our understanding this is the most comprehensive evaluation of these models' simulations of ozone across the Indian sub-continent to date. This study highlights some significant successes and challenges that the models face in representing the oxidative chemistry of the region. The multi-model range in area weighted surface ozone over the Indian subcontinent is 37.26â56.11âppb, whilst the population weighted range is 41.38â57.5âppb. When compared against surface observations from the Modelling Atmospheric Pollution and Networking (MAPAN) network of eight semi-urban monitoring sites spread across India, we find that the models tend to simulate higher ozone than that which is observed. However, observations of NOx and CO tend to be much higher than modelled mixing-ratios, suggesting that the underlying emissions used in the models do not characterise these regions accurately and/or that the resolution of the models is not adequate to simulate the photo-chemical environment about these surface observations. Empirical Orthogonal Function (EOF) analysis is used in order to identify the extent to which the models agree with regards to the spatio-temporal distribution of the tropospheric ozone column, derived using OMI-MLS observations. We show that whilst the models agree with the spatial pattern of the first EOF of observed tropospheric ozone column, most of the models simulate a peak in the first EOF seasonal cycle represented by principle component 1, which is later than the observed peak . This suggest a widespread systematic bias in the timing of emissions or some other unknown seasonal process. In addition to evaluating modelled ozone mixing ratios, we explore modelled emissions of NOx, CO, VOCs, and the ozone response to the emissions. We find a high degree of variation in emissions from non-anthropogenic sources (e.g. lightning NOx and biomass burning CO) between models. Total emissions of NOx and CO over India vary more between different models in the same MIP than the same model used in different MIPs, making it impossible to diagnose whether differences in modelled ozone are due to emissions or model processes. We therefore recommend targeted experiments to pinpoint the exact causes of discrepancies between modelled and observed ozone and ozone precursors for this region. To this end, a higher density of long term monitoring sites measuring not only ozone but also ozone precursors including speciated VOCs, located in more rural regions of the Indian sub-continent, would enable improvements in assessing the biases in models run at the resolution found in HTAPII and CCMI.
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