In recent years, research on normatively positive social tipping dynamics in response to the climate crisis has produced invaluable insights. In contrast, relatively little attention has been given to the potentially negative social tipping processes that might unfold due to an increasingly destabilized Earth system and to how they might in turn reinforce social and ecological destabilization dynamics and/or impede positive social change. In this paper, we discuss selected potential negative social tipping processes (anomie, radicalization and polarization, displacement, conflict, and financial destabilization) linked to Earth system destabilization. We draw on related research to understand the drivers and likelihood of these negative tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions (e.g. food insecurity and displacement) contributing to systemic risks. This first attempt to provide an explorative conceptualization and empirical account of potential negative social tipping dynamics linked to Earth system destabilization is intended to motivate further research into an under-studied area that is nonetheless crucial for our ability to respond to the climate crisis and for ensuring that positive social tipping dynamics are not averted by negative ones.

Globally, mangrove forests are substantially declining, and a globally synthesized database containing the drivers of deforestation and drivers' interactions is scarce. Here, we synthesized the key social-ecological drivers of global mangrove deforestation by reviewing about two hundred published scientific studies over the last four decades (from 1980 to 2021). Our focus was on both natural and anthropogenic drivers with their gradual and abrupt impacts and on their geographic coverage of effects, and how these drivers interact. We also summarized the patterns of global mangrove coverage decline between 1990 and 2020 and identified the threatened mangrove species. Our consolidated studies reported an 8600 km(2) decline in the global mangrove coverage between 1990 and 2020, with the highest decline occurring in South and Southeast Asia (3870 km(2)). We could identify 11 threatened mangrove species, two of which are critically endangered (Sonneratia griffithii and Bruguiera hainseii). Our reviewed studies pointed to aquaculture and agriculture as the predominant driver of global mangrove deforestation though their impacts varied across global regions. Gradual climate variations, i.e., sea-level rise, long-term precipitation, and temperature changes and driven coastline erosion, salinity intrusion and acidity at coasts, constitute the second major group of drivers. Our findings underline a strong interaction across natural and anthropogenic drivers, with the strongest interaction between the driver groups aquaculture and agriculture and industrialization and pollution. Our results suggest prioritizing globally coordinated empirical studies linking drivers and mangrove deforestation and global development of policies for mangrove conservation.

Achieving the goals of the Paris Agreement and related sustainability initiatives will require halving of global greenhouse gas emissions each decade from now on through to 2050, when net zero emissions should be achieved. To reach such significant reductions requires a rapid and strategic scaling of existing and emerging technologies and practices, coupled with economic and social transformations and novel governance solutions. Here we present a new ‘Powers of 10’ (P10) logarithmic framework and demonstrate its potential as a practical tool for decision makers and change agents at multiple scales to inform and catalyze engagement and actions, complementing and adding nuance to existing frameworks. P10 assists in identifying the suitable cohorts and cohort ranges for rapidly deploying climate and sustainability actions between a single individual and the globally projected ∌ 10 billion persons by 2050. Applying a robust dataset of climate solutions from Project Drawdown’s Plausible scenario that could cumulatively reduce greenhouse gas emissions by 1051 gigatons (Gt) against a reference scenario (2190 Gt) between 2020 and 2050, we seek to identify a ‘sweet spot’ where these climate and sustainability actions are suitably scaled. We suggest that prioritizing the analyzed climate actions between community and urban scales, where global and local converge, can help catalyze and enhance individual, household and local practices, and support national and international policies and finances for rapid sustainability transformations.

Safely achieving the goals of the Paris Climate Agreement requires a worldwide transformation to carbon-neutral societies within the next 30 y. Accelerated technological progress and policy implementations are required to deliver emissions reductions at rates sufficiently fast to avoid crossing dangerous tipping points in the Earth's climate system. Here, we discuss and evaluate the potential of social tipping interventions (STIs) that can activate contagious processes of rapidly spreading technologies, behaviors, social norms, and structural reorganization within their functional domains that we refer to as social tipping elements (STE5). STE5 are subdomains of the planetary socioeconomic system where the required disruptive change may take place and lead to a sufficiently fast reduction in anthropogenic greenhouse gas emissions. The results are based on online expert elicitation, a subsequent expert workshop, and a literature review. The STIs that could trigger the tipping of STE subsystems include 1) removing fossil-fuel subsidies and incentivizing decentralized energy generation (STE1, energy production and storage systems), 2) building carbon-neutral cities (STE2, human settlements), 3) divesting from assets linked to fossil fuels (STE3, financial markets), 4) revealing the moral implications of fossil fuels (STE4, norms and value systems), 5) strengthening climate education and engagement (STE5, education system), and 6) disclosing information on greenhouse gas emissions (STE6, information feedbacks). Our research reveals important areas of focus for larger-scale empirical and modeling efforts to better understand the potentials of harnessing social tipping dynamics for climate change mitigation.

Air travel accounts for a major share of individual greenhouse gas emissions, particularly for people in high-income countries. Until recently, few have reduced flying because of climate concerns, but currently, a movement for staying on the ground is rising. Sweden has been a focal point for this movement, particularly during 2018–2019, when a flight tax was introduced, and air travel reduction was intensely discussed in the media. We performed semi-structured interviews with Swedish residents, focusing primarily on individuals who have reduced flying because of its climate impact. We explore how such individual transformation of air travel behavior comes about, and the phases and components of this process. Applying a framework of sustainability transformation, we identify incentives and barriers in personal and political spheres. We show that internalized knowledge about climate change and the impact of air travel is crucial for instigating behavioral change. Awareness evokes negative emotions leading to a personal tipping point where a decision to reduce or quit flying is made. However, the process is often counteracted by both personal values and political structures promoting air travel. Even individuals with a strong drive to reduce flying feel trapped in social practices, norms and infrastructures. Hence, we argue that personal and political spheres interact complexly and to reduce flying at larger scales, interventions are needed across spheres, e.g., change of norms, effective policy instruments and better alternatives to air travel. 

The present study aims to assess the arsenic (As) levels into dust samples and its implications for human health, of four ecological zones of Pakistan, which included northern frozen mountains (FMZ), lower Himalyian wet mountains (WMZ), alluvial riverine plains (ARZ), and low lying agricultural areas (LIZ). Human nail samples (N=180) of general population were also collected from the similar areas and all the samples were analysed by using ICP-MS. In general the higher levels (p < 0.05) in paired dust and human nail samples were observed from ARZ and LIZ than those of other mountainous areas (i.e., WMZ and FMZ), respectively. Current results suggested that elevated As concentrations were associated to both natural, (e.g. geogenic influences) and anthropogenic sources. Linear regression model values indicated that As levels into dust samples were associated with altitude (r(2)=0.23), soil carbonate carbon density (SCC; r(2)=033), and population density (PD; r(2)=0.25). The relationship of paired dust and nail samples was also investigated and associations were found for As-nail and soil organic carbon density (SOC; r(2)=0.49) and SCC (r(2)=0.19) in each studied zone, evidencing the dust exposure as an important source of arsenic contamination in Pakistan. Risk estimation reflected higher hazard index (HI) values of non carcinogenic risk (HI > 1) for children populations in all areas (except FMZ), and for adults in LIZ (0.74) and ARZ (0.55), suggesting that caution should be paid about the dust exposure. Similarly, carcinogenic risk assessment also highlighted potential threats to the residents of LLZ and ARZ, as in few cases (5-10%) the values exceeded the range of US -EPA threshold limits (10'6-10-4).

Data scarcity is a major scientific challenge for accuracy and precision of the spatial interpolation of climatic fields, especially in climate-stressed developing countries. Methodologies have been suggested for coping with data scarcity but data have rarely been checked for their representativeness of corresponding climatic fields. This study proved that satisfactory accuracy and precision can be ensured in spatial interpolation if data are satisfactorily representative of corresponding climatic fields despite their scarcity. The influence of number and representativeness of climate data on accuracy and precision of their spatial interpolation has been investigated and compared. Two precipitation and temperature indices were computed for a long time series in Bangladesh, which is a data-scarce region. The representativeness was quantified by dispersion in the data and the accuracy and precision of spatial interpolation were computed by four commonly used error statistics derived through cross-validation. The precipitation data showed very little and sometimes null representativeness whereas the temperature data showed very high representativeness of the corresponding fields. Consequently, precipitation data denoted scarcity but the temperature data denoted sufficiency regarding the required number of data for ensuring satisfactory accuracy and precision for spatial interpolation. It was also found that with the available data, accurate and precise precipitation surfaces can be produced only for representative synoptic spatial scales whereas such temperature surfaces can be generated for the regional scale of Bangladesh. It is highly recommended that the rain-gauge network of Bangladesh be increased or redistributed for computing representative regional precipitation surfaces.

The Sundarbans - the world’s largest single block of tidal halophytic mangrove forest situated at the southwest of Bangladesh, plays a vital role in maintaining environmental sustainability of the country and the world in general. This study identified and quantified the extent and degree of damage caused to the floristic diversity of the Sundarbans by the tropical cyclone Sidr in 15 November 2007. It also quantified the extent and rate of the post-cyclone regeneration in the damaged flora. Unsupervised classification - ISODATA and the normalized difference vegetation index (NDVI) were carried out over a temporal series of 2007-2010 on four Landsat 7 Enhanced Thematic Mapper Plus (ETM +) images for the months of February. Land change analysis from the classification results show that three important floristic taxa - Heritiera fomes (Sundari), Excoecaria agallocha (Gewa) and Sonneratia apetala (Kewra) have been significantly affected by the cyclone. NDVI analysis indicates that 45% area of the Bangladesh’s part of the Sundarbans (approximately 2500 sq.km) was affected due to the cyclone action. Results further indicated that the average rate of post-cyclone floristic growth in 2009-2010 is four times higher than the average rate in 2008-2009. Thus the study identified a temporary loss of the diversity (in terms of relative abundance) in the affected three floristic taxa of the Sundarbans after that severe exogenous perturbation; which took three years to regenerate. Moreover, it showed the higher efficiency and promptness of remote sensing techniques in similar cases than the ground data based studies.