Active Amplification of the Terrestrial Albedo to Mitigate Climate Change: An Exploratory Study

This study explores the potential to enhance the reflectance of solar insolation by the human settlement and grassland components of the Earth's terrestrial surface as a climate change mitigation measure. Preliminary estimates derived using a static radiative transfer model indicate that such efforts could amplify the planetary albedo enough to offset the current global annual average level of radiative forcing caused by anthropogenic greenhouse gases by as much as 30 percent or 0.76 W/m2. Terrestrial albedo amplification may thus extend, by about 25 years, the time available to advance the development and use of low-emission energy conversion technologies which ultimately remain essential to mitigate long-term climate change. However, additional study is needed to confirm the estimates reported here and to assess the economic and environmental impacts of active land-surface albedo amplification as a climate change mitigation measure.Comment: 21 pages, 3 figures. In press with Mitigation and Adaptation Strategies for Global Change, Springer, N

Global and regional trends in particulate air pollution and attributable health burden over the past 50 years

Long-term exposure to ambient particulate matter (PM2.5, mass of particles with an aerodynamic dry diameter of < 2.5 μm) is a major risk factor to the global burden of disease. Previous studies have focussed on present day or future health burdens attributed to ambient PM2.5. Few studies have estimated changes in PM2.5 and attributable health burdens over the last few decades, a period where air quality has changed rapidly. Here we used the HadGEM3-UKCA coupled chemistry-climate model, integrated exposure-response relationships, demographic and background disease data to provide the first estimate of the changes in global and regional ambient PM2.5 concentrations and attributable health burdens over the period 1960 to 2009. Over this period, global mean population-weighted PM2.5 concentrations increased by 38%, dominated by increases in China and India. Global attributable deaths increased by 89% to 124% over the period 1960 to 2009, dominated by large increases in China and India. Population growth and ageing contributed mostly to the increases in attributable deaths in China and India, highlighting the importance of demographic trends. In contrast, decreasing PM2.5 concentrations and background disease dominated the reduction in attributable health burden in Europe and the United States. Our results shed light on how future projected trends in demographics and uncertainty in the exposure–response relationship may provide challenges for future air quality policy in Asia

Global Health and Economic Impacts of Future Ozone Pollution

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).We assess the human health and economic impacts of projected 2000-2050 changes in ozone pollution using the MIT Emissions Prediction and Policy Analysis-Health Effects (EPPA-HE) model, in combination with results from the GEOS-Chem global tropospheric chemistry model that simulated climate and chemistry effects of IPCC SRES emissions. We use EPPA to assess the human health damages (including acute mortality and morbidity outcomes) caused by ozone pollution and quantify their economic impacts in sixteen world regions. We compare the costs of ozone pollution under scenarios with 2000 and 2050 ozone precursor and greenhouse gas emissions (SRES A1B scenario). We estimate that health costs due to global ozone pollution above pre-industrial levels by 2050 will be $580 billion (year 2000$) and that acute mortalities will exceed 2 million. We find that previous methodologies underestimate costs of air pollution by more than a third because they do not take into account the long-term, compounding effects of health costs. The economic effects of emissions changes far exceed the influence of climate alone.United States Department of Energy, Office of Science (BER) grants DE-FG02-94ER61937 and DE-FG02-93ER61677, the United States Environmental Protection Agency grant EPA-XA-83344601-0, and the industrial and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change

Assessing Africa-wide pangolin exploitation by scaling local data

Overexploitation is one of the main pressures driving wildlife closer to extinction, yet broad-scale data to evaluate species’ declines are limited. Using African pangolins (Family: Pholidota) as a case study, we demonstrate that collating local-scale data can provide crucial information on regional trends in exploitation of threatened species to inform conservation actions and policy. We estimate that 0.4-2.7 million pangolins are hunted annually in Central African forests. The number of pangolins hunted has increased by ∼150% and the proportion of pangolins of all vertebrates hunted increased from 0.04% to 1.83% over the past four decades. However, there were no trends in pangolins observed at markets, suggesting use of alternative supply chains. The price of giant (Smutsia gigantea) and arboreal (Phataginus sp.) pangolins in urban markets has increased 5.8 and 2.3 times respectively, mirroring trends in Asian pangolins. Efforts and resources are needed to increase law enforcement and population monitoring, and investigate linkages between subsistence hunting and illegal wildlife trade

Global distribution maps of the leishmaniases

The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa, and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives, and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases. These high-resolution evidence-based maps can help direct future surveillance activities, identify areas to target for disease control and inform future burden estimation efforts. DOI: http://dx.doi.org/10.7554/eLife.02851.00

Shifting baseline in macroecology? Unraveling the influence of human impact on mammalian body mass

Aim Human activities have led to hundreds of species extinctions and have narrowed the distribution of many of the remaining species. These changes influence our understanding of global macroecological patterns, but their effects have been rarely explored. One of these patterns, the Bergmann’s rule, has been largely investigated in macroecology, but often under the assumption that observed patterns reflect “natural” processes. We assessed the extent to which humans have re-shaped the observable patterns of body mass distribution in terrestrial mammals, and how this has altered the macroecological baseline. Location Global Methods Using a comprehensive set of ecological, climatic, and anthropogenic variables we tested several alternative hypotheses to explain the body mass pattern observed in terrestrial mammals assemblages at a 1-degree resolution. We then explored how model predictions and the Bergmann’s latitudinal pattern are affected by the inclusion of human impact variables, and identified areas where predicted body mass differs from the expected due to human impact. Results Our model suggests that median and maximum body mass predicted in grid cells would be higher, and skewness in local mass distributions reduced, if human impacts were minimal, especially in areas that are highly accessible to humans and where natural land cover has been converted for human activities. Main conclusions Our study provides evidence of the pervasive effects of anthropogenic impact on nature, and shows human-induced distortion of global macroecological patterns. This extends the notion of “shifting baseline”, suggesting that when the first macroecological investigations started, our understanding of global geographic patterns was based on a situation which was already compromised. While in the short term human impact is causing species decline and extinction, in the long term it is causing a broad re-shaping of animal communities with yet unpredicted ecological implications

Environmental-mechanistic modelling of the impact of global change on human zoonotic disease emergence: A case study of Lassa fever

1. Human infectious diseases are a significant threat to global human health and economies (e.g., Ebola, SARs), with the majority of infectious diseases having an animal source (zoonotic). Despite their importance, the lack of a quantitative predictive framework hampers our understanding of how spill-overs of zoonotic infectious diseases into the human population will be impacted by global environmental stressors. 2. Here, we create an environmental-mechanistic model for understanding the impact of global change on the probability of zoonotic disease reservoir host-human spill-over events. As a case study, we focus on Lassa fever virus (LAS). We firstly quantify the spatial determinants of LAS outbreaks, including the phylogeographic distribution of its reservoir host Natal multimammate rat (Mastomys natalensis) (LAS host). Secondly, we use these determinants to inform our environmental-mechanistic model to estimate present day LAS spill-over events and the predicted impact of climate change, human population growth, and land use by 2070. 3. We find phylogeographic evidence to suggest that LAS is confined to only one clade of LAS host (Western clade Mastomys natalensis), and that the probability of its occurrence was a major determinant of the spatial variation in LAS historical outbreaks (69.8%), along with human population density (20.4%). Our estimates for present day LAS spill-over events from our environmental-mechanistic model were consistent with observed patterns, and we predict an increase in events per year by 2070 from 195,125 to 406,725 within the LAS endemic western African region. Of the component drivers, climate change and human population growth are predicted to have the largest effects by increasing landscape suitability for the host and human-host contact rates, while land use change has only a weak impact on the number of future events. 4. LAS spill-over events did not respond uniformly to global environmental stressors, and we suggest that understanding the impact of global change on zoonotic infectious disease emergence requires an understanding of how reservoir host species respond to environmental change. Our environmental-mechanistic modelling methodology provides a novel generalizable framework to understand the impact of global change on the spill-over of zoonotic diseases

Preterm birth associated with maternal fine particulate matter exposure : A global, regional and national assessment

Reduction of preterm births (< 37 completed weeks of gestation) would substantially reduce neonatal and infant mortality, and deleterious health effects in survivors. Maternal fine particulate matter (PM2.5) exposure has been identified as a possible risk factor contributing to preterm birth. The aim of this study was to produce the first estimates of ambient PM2.5-associated preterm births for 183 individual countries and globally. To do this, national, population-weighted, annual average ambient PM2.5 concentration, preterm birth rate and number of livebirths were combined to calculate the number of PM2.5-associated preterm births in 2010 for 183 countries. Uncertainty was quantified using Monte-Carlo simulations, and analyses were undertaken to investigate the sensitivity of PM2.5-associated preterm birth estimates to assumptions about the shape of the concentration-response function at low and high PM2.5 exposures, inclusion of provider-initiated preterm births, and exposure to indoor air pollution. Globally, in 2010, the number of PM2.5-associated preterm births was estimated as 2.7 million (1.8–3.5 million, 18% (12–24%) of total preterm births globally) with a low concentration cut-off (LCC) set at 10 μg m− 3, and 3.4 million (2.4–4.2 million, 23% (16–28%)) with a LCC of 4.3 μg m− 3. South and East Asia, North Africa/Middle East and West sub-Saharan Africa had the largest contribution to the global total, and the largest percentage of preterm births associated with PM2.5. Sensitivity analyses showed that PM2.5-associated preterm birth estimates were 24% lower when provider-initiated preterm births were excluded, 38–51% lower when risk was confined to the PM2.5 exposure range in the studies used to derive the effect estimate, and 56% lower when mothers who live in households that cook with solid fuels (and whose personal PM2.5 exposure is likely dominated by indoor air pollution) were excluded. The concentration-response function applied here derives from a meta-analysis of studies, most of which were conducted in the US and Europe, and its application to the areas of the world where we estimate the greatest effects on preterm births remains uncertain. Nevertheless, the substantial percentage of preterm births estimated to be associated with anthropogenic PM2.5 (18% (13%–24%) of total preterm births globally) indicates that reduction of maternal PM2.5 exposure through emission reduction strategies should be considered alongside mitigation of other risk factors associated with preterm births

Predicting the deforestation-trend under different carbon-prices

BACKGROUND: Global carbon stocks in forest biomass are decreasing by 1.1 Gt of carbon annually, owing to continued deforestation and forest degradation. Deforestation emissions are partly offset by forest expansion and increases in growing stock primarily in the extra-tropical north. Innovative financial mechanisms would be required to help reducing deforestation. Using a spatially explicit integrated biophysical and socio-economic land use model we estimated the impact of carbon price incentive schemes and payment modalities on deforestation. One payment modality is adding costs for carbon emission, the other is to pay incentives for keeping the forest carbon stock intact. RESULTS: Baseline scenario calculations show that close to 200 mil ha or around 5% of todays forest area will be lost between 2006 and 2025, resulting in a release of additional 17.5 GtC. Today's forest cover will shrink by around 500 million hectares, which is 1/8 of the current forest cover, within the next 100 years. The accumulated carbon release during the next 100 years amounts to 45 GtC, which is 15% of the total carbon stored in forests today. Incentives of 6 US$/tC for vulnerable standing biomass payed every 5 year will bring deforestation down by 50$/year. On the other hand a carbon tax of 12 $/tC harvested forest biomass will also cut deforestation by half. The tax income will, if enforced, decrease from 6 billion US$ in 2005 to 4.3 billion US$in 2025 and 0.7 billion US$ in 2100 due to decreasing deforestation speed. CONCLUSION: Avoiding deforestation requires financial mechanisms that make retention of forests economically competitive with the currently often preferred option to seek profits from other land uses. Incentive payments need to be at a very high level to be effective against deforestation. Taxes on the other hand will extract budgetary revenues from the regions which are already poor. A combination of incentives and taxes could turn out to be a viable solution for this problem. Increasing the value of forest land and thereby make it less easily prone to deforestation would act as a strong incentive to increase productivity of agricultural and fuelwood production, which could be supported by revenues generated by the deforestation tax

Invasion of freshwater ecosystems is promoted by network connectivity to hotspots of human activity

Aim: Hotspots of human activity are focal points for ecosystem disturbance and non‐native introduction, from which invading populations disperse and spread. As such, connectivity to locations used by humans may influence the likelihood of invasion. Moreover, connectivity in freshwater ecosystems may follow the hydrological network. Here we tested whether multiple forms of connectivity to human recreational activities promotes biological invasion of freshwater ecosystems. Location: England, UK. Time period: 1990–2018. Major taxa studied: One hundred and twenty‐six non‐native freshwater birds, crustaceans, fish, molluscs and plants. Methods: Machine learning was used to predict spatial gradients in human recreation and two high risk activities for invasion (fishing and water sports). Connectivity indices were developed for each activity, in which human influence decayed from activity hotspots according to Euclidean distance (spatial connectivity) or hydrological network distance (downstream, upstream and along‐channel connectivity). Generalized linear mixed models identified the connectivity type most associated to invasive species richness of each group, while controlling for other anthropogenic and environmental drivers. Results: Connectivity to humans generally had stronger positive effects on invasion than all other drivers except recording effort. Recreation had stronger influence than urban land cover, and for most groups high risk activities had stronger effects than general recreation. Downstream human connectivity was most important for invasion by most of the groups, potentially reflecting predominantly hydrological dispersal. An exception was birds, for which spatial connectivity was most important, possibly because of overland dispersal capacity. Main conclusions: These findings support the hypothesis that freshwater invasion is partly determined by an interaction between human activity and species dispersal in the hydrological network. By comparing alternative connectivity types for different human activities, our approach could enable robust inference of specific pathways and spread mechanisms associated with particular taxa. This would provide evidence to support better prioritization of surveillance and management for invasive non‐native species