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Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change.Current and future climate change is expected to impact human health, both indirectly and directly, through increasing temperatures. Climate change has already had an impact and is responsible for 37% of warm-season heat-related deaths between 1991 and 2018, with increases in mortality observed globally.

Internal variability in the climate system confounds assessment of human-induced climate change and imposes irreducible limits on the accuracy of climate change projections, especially at regional and decadal scales. A new collection of initial-condition large ensembles (LEs) generated with seven Earth system models under historical and future radiative forcing scenarios provides new insights into uncertainties due to internal variability versus model differences. These data enhance the assessment of climate change risks, including extreme events, and offer a powerful testbed for new methodologies aimed at separating forced signals from internal variability in the observational record. Opportunities and challenges confronting the design and dissemination of future LEs, including increased spatial resolution and model complexity alongside emerging Earth system applications, are discussed.Climate change detection is confounded by internal variability, but recent initial-condition large ensembles (LEs) have begun addressing this issue. This Perspective discusses the value of multi-model LEs, the challenges of providing them and their role in future climate change research.

Climate-induced sea-level rise and vertical land movements, including natural and human-induced subsidence in sedimentary coastal lowlands, combine to change relative sea levels around the world’s coasts. Although this affects local rates of sea-level rise, assessments of the coastal impacts of subsidence are lacking on a global scale. Here, we quantify global-mean relative sea-level rise to be 2.6 mm yr−1 over the past two decades. However, as coastal inhabitants are preferentially located in subsiding locations, they experience an average relative sea-level rise up to four times faster at 7.8 to 9.9 mm yr−1. These results indicate that the impacts and adaptation needs are much higher than reported global sea-level rise measurements suggest. In particular, human-induced subsidence in and surrounding coastal cities can be rapidly reduced with appropriate policy for groundwater utilization and drainage. Such policy would offer substantial and rapid benefits to reduce growth of coastal flood exposure due to relative sea-level rise.Land subsidence and uplift influence the rate of sea-level rise. Most coastal populations live in subsiding areas and experience average rates of relative sea-level rise three to four times faster than due to climate change alone, indicating the need for policy to address subsidence.

Many studies have investigated the energy-environment nexus for Indonesia using carbon emissions to proxy environmental quality, while totally ignoring ecological footprint which is a more reliable measure of environmental quality. Factors like urbanization and energy consumption may increase the ecological footprint since ecological distortions are mainly human-induced. This study explores the effect of energy use, urbanization, trade, and economic growth on the environment which is captured by ecological footprint. The findings indicate that urbanization, economic growth, and energy consumption increase environmental degradation, while trade deteriorates it in the long run. Trade reduces environmental quality in the short run, while economic growth, energy use, and urbanization show consistent result with their long-run outcomes. Further findings reveal a unidirectional causality from economic growth to ecological footprint, and from urbanization to energy use. Therefore, policies to abate emissions, curtail urban anomaly and uphold a sustainable environment are extensively discussed.

Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1 °C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.Regional changes in dry-season water availability over recent decades can be attributed to human-induced climate change, according to analyses of global reconstructions.

Parties to the Paris Agreement agreed to holding global average temperature increases “well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels”. Monitoring the contributions of human-induced climate forcings to warming so far is key to understanding progress towards these goals. Here we use climate model simulations from the Detection and Attribution Model Intercomparison Project, as well as regularized optimal fingerprinting, to show that anthropogenic forcings caused 0.9 to 1.3 °C of warming in global mean near-surface air temperature in 2010–2019 relative to 1850–1900, compared with an observed warming of 1.1 °C. Greenhouse gases and aerosols contributed changes of 1.2 to 1.9 °C and −0.7 to −0.1 °C, respectively, and natural forcings contributed negligibly. These results demonstrate the substantial human influence on climate so far and the urgency of action needed to meet the Paris Agreement goals.Quantifying the temperature impacts of anthropogenic emissions helps monitor proximity to the Paris Agreement goals. Human activities warmed global mean temperature during the past decade by 0.9 to 1.3 °C above 1850–1900 values, with 1.2 to 1.9 °C from greenhouse gases and −0.7 to −0.1 °C from aerosols.

The literature on atmospheric particulate matter (PM), or atmospheric aerosol, has increased enormously over the last 2 decades and amounts now to some 1500–2000 papers per year in the refereed literature. This is in part due to the enormous advances in measurement technologies, which have allowed for an increasingly accurate understanding of the chemical composition and of the physical properties of atmospheric particles and of their processes in the atmosphere. The growing scientific interest in atmospheric aerosol particles is due to their high importance for environmental policy. In fact, particulate matter constitutes one of the most challenging problems both for air quality and for climate change policies. In this context, this paper reviews the most recent results within the atmospheric aerosol sciences and the policy needs, which have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate–aerosol interactions and effects of PM on human health and the environment. However, while airborne particulate matter is responsible for globally important influences on premature human mortality, we still do not know the relative importance of the different chemical components of PM for these effects. Likewise, the magnitude of the overall effects of PM on climate remains highly uncertain. Despite the uncertainty there are many things that could be done to mitigate local and global problems of atmospheric PM. Recent analyses have shown that reducing black carbon (BC) emissions, using known control measures, would reduce global warming and delay the time when anthropogenic effects on global temperature would exceed 2 °C. Likewise, cost-effective control measures on ammonia, an important agricultural precursor gas for secondary inorganic aerosols (SIA), would reduce regional eutrophication and PM concentrations in large areas of Europe, China and the USA. Thus, there is much that could be done to reduce the effects of atmospheric PM on the climate and the health of the environment and the human population. A prioritized list of actions to mitigate the full range of effects of PM is currently undeliverable due to shortcomings in the knowledge of aerosol science; among the shortcomings, the roles of PM in global climate and the relative roles of different PM precursor sources and their response to climate and land use change over the remaining decades of this century are prominent. In any case, the evidence from this paper strongly advocates for an integrated approach to air quality and climate policies.

The Southern Ocean has, on average, warmed and freshened over the past several decades. As a primary global sink for anthropogenic heat and carbon, to understand changes in the Southern Ocean is directly relevant to predicting the future evolution of the global climate system. However, the drivers of these changes are poorly understood, owing to sparse observational sampling, large amplitude internal variability, modelling uncertainties and the competing influence of multiple forcing agents. Here we construct an observational synthesis to quantify the temperature and salinity changes over the Southern Ocean and combine this with an ensemble of co-sampled climate model simulations. Using a detection and attribution analysis, we show that the observed changes are inconsistent with the internal variability or the response to natural forcing alone. Rather, the observed changes are primarily attributable to human-induced greenhouse gas increases, with a secondary role for stratospheric ozone depletion. Physically, the simulated changes are primarily driven by surface fluxes of heat and freshwater. The consistency between the observed changes and our simulations provides increased confidence in the ability of climate models to simulate large-scale thermohaline change in the Southern Ocean.

The Emissions Database for Global Atmospheric Research (EDGAR) estimates the human-induced emission rates on Earth. EDGAR collaborates with atmospheric modelling activities and aids policy in the design of mitigation strategies and in evaluating their effectiveness. In these applications, the uncertainty estimate is an essential component, as it quantifies the accuracy and qualifies the level of confidence in the emission. This study complements the EDGAR emissions inventory by providing an estimation of the structural uncertainty stemming from its base components (activity data, AD, statistics and emission factors, EFs) by (i) associating uncertainty to each AD and EF characterizing the emissions of the three main greenhouse gases (GHGs), namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O); (ii) combining them; and (iii) making assumptions regarding the cross-country uncertainty aggregation of source categories. It was deemed a natural choice to obtain the uncertainties in EFs and AD statistics from the Intergovernmental Panel on Climate Change (IPCC) guidelines issued in 2006 (with a few exceptions), as the EF and AD sources and methodological aspects used by EDGAR have been built over the years based on the IPCC recommendations, which assured consistency in time and comparability across countries. On the one hand, the homogeneity of the method is one of the key strengths of EDGAR, on the other hand, it facilitates the propagation of uncertainties when similar emission sources are aggregated. For this reason, this study aims primarily at addressing the aggregation of uncertainties' sectorial emissions across GHGs and countries. Globally, we find that the anthropogenic emissions covered by EDGAR for the combined three main GHGs for the year 2015 are accurate within an interval of −15 % to +20 % (defining the 95 % confidence of a log-normal distribution). The most uncertain emissions are those related to N2O from waste and agriculture, while CO2 emissions, although responsible for 74 % of the total GHG emissions, account for approximately 11 % of global uncertainty share. The sensitivity to methodological choices is also discussed.

A potential glacial lake outburst flood from Lake Palcacocha (Cordillera Blanca, Peru) threatens Huaraz, a city of 120,000 people. In 1941, an outburst flood destroyed one-third of the city and caused at least 1,800 fatalities. Since pre-industrial times, Lake Palcacocha has expanded due to the retreat of Palcaraju glacier. Here we used observations and numerical models to evaluate the anthropogenic contribution to the glacier’s retreat and glacial lake outburst flood hazard. We found that the magnitude of human-induced warming equals between 85 and 105% (5–95% confidence interval) of the observed 1 °C warming since 1880 in this region. We conclude that it is virtually certain (>99% probability) that the retreat of Palcaraju glacier to the present day cannot be explained by natural variability alone, and that the retreat by 1941 represented an early impact of anthropogenic greenhouse gas emissions. Our central estimate is that the overall retreat is entirely attributable to the observed temperature trend, and that the resulting change in the geometry of the lake and valley has substantially increased the outburst flood hazard. Human-induced warming is responsible for the retreat of Palcaraju glacier and the associated increase in glacial lake outburst flood hazard, according to an analysis of observations and numerical models.