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Fire is an integral ecosystem process and a major natural source of vegetation disturbance globally. Yet at the same time, humans use and manage fire in diverse ways and for a huge range of purposes. Therefore, it is perhaps unsurprising that a central finding of the first Fire Model Intercomparison Project was simplistic representation of humans is a substantial shortcoming in the fire modules of dynamic global vegetation models (DGVMs). In response to this challenge, we present a novel, global geospatial model that seeks to capture the diversity of human–fire interactions. Empirically grounded with a global database of anthropogenic fire impacts, WHAM! (the Wildfire Human Agency Model) represents the underlying behavioural and land system drivers of human approaches to fire management and their impact on fire regimes. WHAM! is designed to be coupled with DGVMs (JULES-INFERNO in the current instance), such that human and biophysical drivers of fire on Earth, and their interactions, can be captured in process-based models for the first time. Initial outputs from WHAM! presented here are in line with previous evidence suggesting managed anthropogenic fire use is decreasing globally and point to land use intensification as the underlying reason for this phenomenon.

Peat fires in the northern high latitudes have the potential to burn vast amounts of carbon-rich organic soil, releasing large quantities of long-term stored carbon to the atmosphere. Due to anthropogenic activities and climate change, peat fires are increasing in frequency and intensity across the high latitudes. However, at present they are not explicitly included in most fire models. Here we detail the development of INFERNO-peat, the first parameterization of peat fires in the JULES-INFERNO (Joint UK Land Environment Simulator INteractive Fire and Emission algoRithm for Natural envirOnments) fire model. INFERNO-peat utilizes knowledge from lab and field-based studies on peat fire ignition and spread to be able to model peat burnt area, burn depth, and carbon emissions, based on data of the moisture content, inorganic content, bulk density, soil temperature, and water table depth of peat. INFERNO-peat improves the representation of burnt area in the high latitudes, with peat fires simulating on average an additional 0.305×106 km2 of burn area each year, emitting 224.10 Tg of carbon. Compared to Global Fire Emissions Database version 5 (GFED5), INFERNO-peat captures ∼ 20 % more burnt area, whereas INFERNO underestimated burning by 50 %. Additionally, INFERNO-peat substantially improves the representation of interannual variability in burnt area and subsequent carbon emissions across the high latitudes. The coefficient of variation in carbon emissions is increased from 0.071 in INFERNO to 0.127 in INFERNO-peat, an almost 80 % increase. Therefore, explicitly modelling peat fires shows a substantial improvement in the fire modelling capabilities of JULES-INFERNO, highlighting the importance of representing peatland systems in fire models.

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.

Future African aerosol emissions, and therefore air pollution levels and health outcomes, are uncertain and understudied. Understanding the future health impacts of pollutant emissions from this region is crucial. Here, this research gap is addressed by studying the range in the future health impacts of aerosol emissions from Africa in the Shared Socioeconomic Pathway (SSP) scenarios, using the UK Earth System Model version 1 (UKESM1), along with human health concentration–response functions. The effects of Africa following a high-pollution aerosol pathway are studied relative to a low-pollution control, with experiments varying aerosol emissions from industry and biomass burning. Using present-day demographics, annual deaths within Africa attributable to ambient particulate matter are estimated to be lower by 150 000 (5th–95th confidence interval of 67 000–234 000) under stronger African aerosol mitigation by 2090, while those attributable to O3 are lower by 15 000 (5th–95th confidence interval of 9000–21 000). The particulate matter health benefits are realised predominantly within Africa, with the O3-driven benefits being more widespread – though still concentrated in Africa – due to the longer atmospheric lifetime of O3. These results demonstrate the important health co-benefits from future emission mitigation in Africa.

The occurrence of forest fires can impact vegetation in the ecosystem, property, and human health but also indirectly affect the climate. The Joint UK Land Environment Simulator – INteractive Fire and Emissions algorithm for Natural envirOnments (JULES-INFERNO) is a global land surface model, which simulates vegetation, soils, and fire occurrence driven by environmental factors. However, this model incurs substantial computational costs due to the high data dimensionality and the complexity of differential equations. Deep-learning-based digital twins have an advantage in handling large amounts of data. They can reduce the computational cost of subsequent predictive models by extracting data features through reduced-order modelling (ROM) and then compressing the data to a low-dimensional latent space. This study proposes a JULES-INFERNO-based digital twin fire model using ROM techniques and deep learning prediction networks to improve the efficiency of global wildfire predictions. The iterative prediction implemented in the proposed model can use current-year data to predict fires in subsequent years. To avoid the accumulation of errors from the iterative prediction, latent data assimilation (LA) is applied to the prediction process. LA manages to efficiently adjust the prediction results to ensure the stability and sustainability of the prediction. Numerical results show that the proposed model can effectively encode the original data and achieve accurate surrogate predictions. Furthermore, the application of LA can also effectively adjust the bias of the prediction results. The proposed digital twin also runs 500 times faster for online predictions than the original JULES-INFERNO model without requiring high-performance computing (HPC) clusters.

The potential future trend in African aerosol emissions is uncertain, with a large range found in future scenarios used to drive climate projections. The future climate impact of these emissions is therefore uncertain. Using the Shared Socioeconomic Pathway (SSP) scenarios, transient future experiments were performed with the UK Earth System Model (UKESM1) to investigate the effect of African emissions following the high emission SSP370 scenario as the rest of the world follows the more sustainable SSP119, relative to a global SSP119 control. This isolates the effect of Africa following a relatively more polluted future emissions pathway. Compared to SSP119, SSP370 projects higher non-biomass-burning (non-BB) aerosol emissions, but lower biomass burning emissions, over Africa. Increased shortwave (SW) absorption by black carbon aerosol leads to a global warming, but the reduction in the local incident surface radiation close to the emissions is larger, causing a local cooling effect. The local cooling persists even when including the higher African CO2 emissions under SSP370 than SSP119. The global warming is significantly higher by 0.07 K when including the non-BB aerosol increases and higher still (0.22 K) when including all aerosols and CO2. Precipitation also exhibits complex changes. Northward shifts in the Inter-tropical Convergence Zone (ITCZ) occur under relatively warm Northern Hemisphere land, and local rainfall is enhanced due to mid-tropospheric instability from black carbon absorption. These results highlight the importance of future African aerosol emissions for regional and global climate and the spatial complexity of this climate influence.

Interactions between aerosols and gases in the atmosphere have been the focus of an increasing number of studies in recent years. Here, we focus on aerosol effects on tropospheric ozone that involve meteorological feedbacks induced by aerosol–radiation interactions. Specifically, we study the effects that involve aerosol influences on the transport of gaseous pollutants and on atmospheric moisture, both of which can impact ozone chemistry. For this purpose, we use the UK Earth System Model (UKESM1), with which we performed sensitivity simulations including and excluding the aerosol direct radiative effect (ADE) on atmospheric chemistry, and focused our analysis on an area with a high aerosol presence, namely China. By comparing the simulations, we found that ADE reduced shortwave radiation by 11 % in China and consequently led to lower turbulent kinetic energy, weaker horizontal winds and a shallower boundary layer (with a maximum of 102.28 m reduction in north China). On the one hand, the suppressed boundary layer limited the export and diffusion of pollutants and increased the concentration of CO, SO2, NO, NO2, PM2.5 and PM10 in the aerosol-rich regions. The NO/NO2 ratio generally increased and led to more ozone depletion. On the other hand, the boundary layer top acted as a barrier that trapped moisture at lower altitudes and reduced the moisture at higher altitudes (the specific humidity was reduced by 1.69 % at 1493 m on average in China). Due to reduced water vapour, fewer clouds were formed and more sunlight reached the surface, so the photolytical production of ozone increased. Under the combined effect of the two meteorology feedback methods, the annual average ozone concentration in China declined by 2.01 ppb (6.2 %), which was found to bring the model into closer agreement with surface ozone measurements from different parts of China.

Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by ∼7 % per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.4±0.9 % K−1 for sulfate to 9.8±2 % K−1 for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.2±0.5 to 9.9±0.7 d between 1986–2005 and 2081–2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.

Atmospheric aerosols and greenhouse gases affect cloud properties, radiative balance and, thus, the hydrological cycle. Observations show that precipitation has decreased in the Mediterranean since the beginning of the 20th century, and many studies have investigated possible mechanisms. So far, however, the effects of aerosol forcing on Mediterranean precipitation remain largely unknown. Here we compare the modeled dynamical response of Mediterranean precipitation to individual forcing agents in a set of global climate models (GCMs). Our analyses show that both greenhouse gases and aerosols can cause drying in the Mediterranean and that precipitation is more sensitive to black carbon (BC) forcing than to well-mixed greenhouse gases (WMGHGs) or sulfate aerosol. In addition to local heating, BC appears to reduce precipitation by causing an enhanced positive sea level pressure (SLP) pattern similar to the North Atlantic Oscillation–Arctic Oscillation, characterized by higher SLP at midlatitudes and lower SLP at high latitudes. WMGHGs cause a similar SLP change, and both are associated with a northward diversion of the jet stream and storm tracks, reducing precipitation in the Mediterranean while increasing precipitation in northern Europe. Though the applied forcings were much larger, if forcings are scaled to those of the historical period of 1901–2010, roughly one-third (31±17 %) of the precipitation decrease would be attributable to global BC forcing with the remainder largely attributable to WMGHGs, whereas global scattering sulfate aerosols would have negligible impacts. Aerosol–cloud interactions appear to have minimal impacts on Mediterranean precipitation in these models, at least in part because many simulations did not fully include such processes; these merit further study. The findings from this study suggest that future BC and WMGHG emissions may significantly affect regional water resources, agricultural practices, ecosystems and the economy in the Mediterranean region.

Precipitation changes are strongly linked to the Earth’s energy budget. Here the authors show that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since pre-industrial time.

Abstract Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyze the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature‐driven circulation changes, but the magnitude is uncertain. CO2 drives reductions in precipitation concentrated in the east, mainly due to a robustly negative, but highly variable in magnitude, fast response. We find that the physiological effect of CO2 on plant stomata is the dominant driver of the fast response due to reduced latent heating and also contributes to the large model spread. Using a simple model, we show that CO2 physiological effects dominate future multimodel mean precipitation projections over the Amazon. However, in individual models temperature‐driven changes can be large, but due to little agreement, they largely cancel out in the model mean.

We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against observations.

Science, in our case the climate and geosciences, is increasingly interdisciplinary. Scientists must therefore communicate across disciplinary boundaries. For this communication to be successful, scientists must write clearly and concisely, yet the historically poor standard of scientific writing does not seem to be improving. Scientific writing must improve, and the key to long-term improvement lies with the early-career scientist (ECS). Many interventions exist for an ECS to improve their writing, like style guides and courses. However, momentum is often difficult to maintain after these interventions are completed. Continuity is key to improving writing. This paper introduces the ClimateSnack project, which aims to motivate ECSs to develop and continue to improve their writing and communication skills. The project adopts a peer-learning framework where ECSs voluntarily form writing groups at different institutes around the world. The group members learn, discuss, and improve their writing skills together. Several ClimateSnack writing groups have formed. This paper examines why some of the groups have flourished and others have dissolved. We identify the challenges involved in making a writing group successful and effective, notably the leadership of self-organized groups, and both individual and institutional time management. Within some of the groups, peer learning clearly offers a powerful tool to improve writing as well as bringing other benefits, including improved general communication skills and increased confidence.

Future African aerosol emissions, and therefore air pollution levels and health outcomes, are uncertain and understudied. Understanding the future health impacts of pollutant emissions from this region is crucial. Here, this research gap is addressed by studying the range in the future health impacts of aerosol emissions from Africa in the Shared Socioeconomic Pathway (SSP) scenarios, using the UK Earth System Model version 1 (UKESM1), along with human health concentration-response functions. The effects of Africa following a high-pollution aerosol pathway are studied relative to a low-pollution control, with experiments varying aerosol emissions from industry and biomass burning. Using present-day demographics, annual deaths within Africa attributable to ambient particulate matter are estimated to be lower by 150 000 (5th-95th confidence interval of 67 000-234 000) under stronger African aerosol mitigation by 2090, while those attributable to O 3 are lower by 15 000 (5th-95th confidence interval of 9000-21 000). The particulate matter health benefits are realised predominantly within Africa, with the O 3 -driven benefits being more widespread - though still concentrated in Africa - due to the longer atmospheric lifetime of O 3 . These results demonstrate the important health co-benefits from future emission mitigation in Africa., Competing Interests: Competing interests. The contact author has declared that none of the authors has any competing interests.

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth's radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project., (© 2022. The Author(s).)

Quantifying the efficacy of different climate forcings is important for understanding the real-world climate sensitivity. This study presents a systematic multimodel analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near-surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multimodel mean efficacies based on ERF are close to one for global perturbations of methane, sulfate, black carbon, and insolation, but there is notable intermodel spread. We do not find robust evidence that the geographic location of sulfate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO 2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy-induced bias of ±0.4 K in equilibrium climate sensitivity to CO 2 doubling when estimated using the historical GSAT trend., (©2019. The Authors.)

Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail. It is shown that rapid adjustments reduce the effective radiative forcing (ERF) of black carbon by half of the instantaneous forcing, but for CO 2 forcing, rapid adjustments increase ERF. Competing tropospheric adjustments for CO 2 forcing are individually significant but sum to zero, such that the ERF equals the stratospherically adjusted radiative forcing, but this is not true for other forcing agents. Additional experiments of increase in the solar constant and increase in CH 4 are used to show that a key factor of the rapid adjustment for an individual climate driver is changes in temperature in the upper troposphere and lower stratosphere.

Different climate drivers influence precipitation in different ways. Here we use radiative kernels to understand the influence of rapid adjustment processes on precipitation in climate models. Rapid adjustments are generally triggered by the initial heating or cooling of the atmosphere from an external climate driver. For precipitation changes, rapid adjustments due to changes in temperature, water vapor, and clouds are most important. In this study we have investigated five climate drivers (CO 2 , CH 4 , solar irradiance, black carbon, and sulfate aerosols). The fast precipitation responses to a doubling of CO 2 and a 10-fold increase in black carbon are found to be similar, despite very different instantaneous changes in the radiative cooling, individual rapid adjustments, and sensible heating. The model diversity in rapid adjustments is smaller for the experiment involving an increase in the solar irradiance compared to the other climate driver perturbations, and this is also seen in the precipitation changes.

Atmospheric aerosols such as sulfate and black carbon (BC) generate inhomogeneous radiative forcing and can affect precipitation in distinct ways compared to greenhouse gases (GHGs). Their regional effects on the atmospheric energy budget and circulation can be important for understanding and predicting global and regional precipitation changes, which act on top of the background GHG-induced hydrological changes. Under the framework of the Precipitation Driver Response Model Inter-comparison Project (PDRMIP), multiple models were used for the first time to simulate the influence of regional (Asian and European) sulfate and BC forcing on global and regional precipitation. The results show that, as in the case of global aerosol forcing, the global fast precipitation response to regional aerosol forcing scales with global atmospheric absorption, and the slow precipitation response scales with global surface temperature response. Asian sulphate aerosols appear to be a stronger driver of global temperature and precipitation change compared to European aerosols, but when the responses are normalised by unit radiative forcing or by aerosol burden change, the picture reverses, with European aerosols being more efficient in driving global change. The global apparent hydrological sensitivities of these regional forcing experiments are again consistent with those for corresponding global aerosol forcings found in the literature. However, the regional responses and regional apparent hydrological sensitivities do not align with the corresponding global values. Through a holistic approach involving analysis of the energy budget combined with exploring changes in atmospheric dynamics, we provide a framework for explaining the global and regional precipitation responses to regional aerosol forcing.

Globally, latent heating associated with a change in precipitation is balanced by changes to atmospheric radiative cooling and sensible heat fluxes. Both components can be altered by climate forcing mechanisms and through climate feedbacks, but the impacts of climate forcing and feedbacks on sensible heat fluxes have received much less attention. Here we show, using a range of climate modelling results, that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since preindustrial time, because the radiative impact of forcings and feedbacks approximately compensate. The model results show a dissimilar influence on sensible heat and precipitation from various drivers of climate change. Due to its strong atmospheric absorption, black carbon is found to influence the sensible heat very differently compared to other aerosols and greenhouse gases. Our results indicate that this is likely caused by differences in the impact on the lower tropospheric stability.

Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyse the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature-driven circulation changes, but the magnitude is uncertain. CO 2 drives reductions in precipitation concentrated in the east, mainly due to a robustly negative, but highly variable in magnitude, fast response. We find that the physiological effect of CO 2 on plant stomata is the dominant driver of the fast response due to reduced latent heating, and also contributes to the large model spread. Using a simple model we show that CO 2 physiological effects dominate future multi-model mean precipitation projections over the Amazon. However, in individual models temperature-driven changes can be large, but due to little agreement, they largely cancel out in the model-mean.

We investigate the climate response to increased concentrations of black carbon (BC), as part of the Precipitation Driver Response Model Intercomparison Project (PDRMIP). A tenfold increase in BC is simulated by 9 global coupled-climate models, producing a model-median effective radiative forcing (ERF) of 0.82 (ranging from 0.41 to 2.91) Wm -2 , and a warming of 0.67 (0.16 to 1.66) K globally and 1.24 (0.26 to 4.31) K in the Arctic. A strong positive instantaneous radiative forcing (median of 2.10 Wm -2 based on five of the models) is countered by negative rapid adjustments (-0.64 Wm -2 for the same five models), which dampen the total surface temperature signal. Unlike other drivers of climate change, the response of temperature and cloud profiles to the BC forcing is dominated by rapid adjustments. Low-level cloud amounts increase for all models, while higher-level clouds are diminished. The rapid temperature response is particularly strong above 400 hPa, where increased atmospheric stabilization and reduced cloud cover contrast the response pattern of the other drivers. In conclusion, we find that this substantial increase in BC concentrations does have considerable impacts on important aspects of the climate system. However, some of these effects tend to offset one another, leaving a relatively small global warming of 0.47 K per Wm -2 - about 20 % lower than the response to a doubling of CO 2 . Translating the tenfold increase in BC to the present-day impact of anthropogenic BC (given the emissions used in this work) would leave a warming of merely 0.07 K.

Samples of size-fractionated particles were collected from local natural and anthropogenic sources in two industrial cities in the Yangtze River Delta, using either grab/resuspension sampling or ambient air sampling. The chemical characterizations of twenty one source profiles were obtained, based on elements (Al, As, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Pb and Zn), soluble ions (Cl - , NO 3 - , SO 4 2- , NH 4 + , K + , Na + and Ca 2+ ) and carbonaceous material such as organic carbon (OC) and elemental carbon (EC). The profiles vary between sources from different areas, as well as between different particulate sizes. Results show that particulate matter that originated as soil dust, construction dust and fugitive dust is typically rich in crustal elements, especially Al, Ca, Fe and Mg, while the presence of calcium is found to be a hallmark of the cement industry and ceramic industry. Dominant compositions of particles from coal-fired power plants are variable, with OC ranging from 2.2%-27%. Garbage-fired power plant and cooking smoke particulate emissions are enriched in Na, Cl - , OC and K due to the presence of salty and organic matter. The element Fe, ranging from 6.1% to 26.0%, is found to be an important marker for steel production dust. Vehicle exhaust profiles are characterized by high abundances of OC (12.1%-53.6%) and EC (3.9%-20.0%). Burning of straw results in K (1.6%-7.2%) and OC (12.4%-25.9%) being the dominant composition. Preliminary work has also been done on establishing local industrial profiles such as textile, ceramic and electroplating industries. This work could be used in receptor model studies to estimate the contributions of different sources to the size-fractionated particulate matter in the Yangtze River Delta., (Copyright © 2017 Elsevier B.V. All rights reserved.)

As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and needs better quantifications to improve precipitation predictions. Here, we introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve our understanding of the causes of the present diversity in future climate projections.

In this study, samples of size-fractionated particulate matter were collected continuously using a 9-size interval cascade impactor at an urban site in Nanjing, before, during and after the Asian Youth Games (AYG), from July to September of 2013, and the Youth Olympic Games (YOG), from July to September of 2014. First, elemental concentrations, water-soluble ions including Cl - , NO 3 - , SO 4 2- , NH 4 + , K + concentrations were 90.4±20.0μg/m + during the 2013 AYG and 70.6±25.3μg/m 2+ , organic carbon (OC) and elemental carbon (EC) were analysed. Then, the source apportionment of the fine and coarse particulate matter was carried out using the chemical mass balance (CMB) model. The average PM 10 the average concentrations were 50.0±12.8μg/m 3 in 2013 and 34.6±17.0μg/m 3 during the 2014 YOG. For PM 2.1, the average concentrations were 50.0±12.8μg/m 3 in 2013 and 34.6±17.0μg/m 3 in 2014. Investigations showed that the average concentrations of particles declined significantly from 2013 to 2014, and concentrations were at the lowest levels during the events. Results indicated that OC, EC, sulfate and crustal elements have significant monthly and size-based variations. The major components, including crustal elements, water-soluble ions and carbonaceous aerosol accounted for 75.3-91.9% of the total particulate mass concentrations during the sampling periods. Fugitive dust, coal combustion dust, iron dust, construction dust, soil dust, vehicle exhaust, secondary aerosols and sea salt have been classified as the main emissions in Nanjing. The source apportionment results indicate that the emissions from fugitive dust, which was the most abundance emission source during the 2013 AYG, contributed to 23.0% of the total particle mass. However, fugitive dust decreased to 6.2% of the total particle mass during the 2014 YOG. Construction dust (14.7% versus 7.8% for the AYG and the YOG, respectively) and secondary sulfate aerosol (9.3% versus 8.0% for the AYG and the YOG, respectively) showed the same trend as fugitive dust, suggesting that the mitigation measures of controlling particles from the paved roads, construction and industry worked more efficiently during the YOG., (Copyright © 2016 Elsevier B.V. All rights reserved.)