Importance Of Climate Change Research Articles

TEACHERS' ATTITUDES & BARRIERS TO IMPLEMENTING CLIMATE CHANGE EDUCATION IN SECONDARY SCHOOLS

This study aimed to investigate the teachers’ attitudes toward incorporating climate change education in secondary schools. It was a descriptive study with quantitative research design. Two hundred secondary school teachers were selected through a stratified sampling technique. For data collection, a five-point self-developed Likert scale was used. Data was analyzed over SPSS 20. Descriptive and inferential statistics were used. It was found that most of the participants agreed about the importance of climate change in education, but they face barriers to implementation. The main challenges found were insufficient resources, training, and a crowded curriculum. The professional development participation particularly anticipated positive attitudes towards the climate change education. There was no significant difference in attitude towards the climate change based upon gender. A significant association was found between the subject taught and attitude towards climate change education. Findings highlight the need for targeted support, including improved resources, training, and curriculum integration, to enhance teachers' capacity and confidence in delivering climate change education.

Print Media Coverage of Climate Change Crisis in Pakistan: A Comparative Study of Two Newspapers Dawn and Daily Times

The coverage of the climate change crisis in two elite Pakistani English print media outlets, Dawn and Daily Times, is examined in this study. Considering the importance of climate change as a worldwide concern, understanding how it is depicted in the media is critical for raising awareness and affecting public opinion. The study looks at the frequency, themes, and framing of climate change-related articles in these newspapers using content analysis. The study compares the two newspapers to shed light on the variations and similarities in their reporting as well as to analyse the degree of coverage of this critical issue. Political and economic stories received prominent coverage, signifying the media’s acknowledgement of the role played by policymaking, politics, and the economic implications associated with climate change. Moreover, in terms of geographical focus, both newspapers demonstrated a prioritization of reporting on national climate change issues. The implementation of the NDCs long-term plan has exerted a discernible influence on the coverage of climate change-related stories in both newspapers. Notably, after the adoption of the NDCs plan, both Dawn and Daily Times have increased their coverage of climate change issues, thereby indicating the plan’s substantial impact on media attention and reporting.

Variables controlling growing season carbon dynamics in desert shrub ecosystem

Arid and semi-arid lands (drylands) are under the influence of extreme environmental conditions and cover large areas on Earth’s land surface. Determining temporal and spatial variations of the greenhouse gas and energy exchange in these ecosystems will provide a better understanding of both, the dynamics between the drylands’s surface and the atmosphere and the importance in climate change. In this study, CO2 exchanges over a shrub steppe ecosystem were determined using the Eddy Covariance method during both dry and wet growing seasons in the Gobi Desert, Mongolia. The net ecosystem exchange (NEE) was modeled using the extreme gradient boosting method (XGBOOST). Variables influencing NEE were estimated employing the SHapley Additive exPlanations algorithm (SHAP). The XGBOOST predictions demonstrated impressive results across all growing seasons, with high performance metrics (R2 = 0.821; NSE = 0.817), particularly notable during the wet season (R2 = 0.932; NSE = 0.929). The total NEE changed between 79.7 and -110.4 gC m−2 throughout the growing seasons. Especially the precipitation before the growing period has a positive impact on carbon sequestration in the shrub ecosystem in the following dry season. A high similarity was found in the patterns of daily NEE of all growing seasons and normalized difference vegetation index (NDVI), albedo, soil water content, temperature, sensible heat flux, the difference between air and soil temperature in desert shrub ecosystem. Although NDVI was the dominant factor during the wet season, there was a weaker relationship between these factors and NEE in the dry season than in the wet season.

Evaluating the relative influence of climate and human activities on recent vegetation dynamics in West Bengal, India

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70–85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.

Patterns and drivers of soil carbon change (1980s-2010s) in the northeastern Qinghai-Tibet Plateau

Rapid climate warming, permafrost degradation and widespread vegetation improvement on the Qinghai-Tibet Plateau (QTP) have caused carbon input via photosynthesis and carbon output through soil respiration to significantly increase in recent decades; thus, its role as a carbon sink/source is unclear and highly disputed, especially at different soil depths. In this study, we took the Qinghai Plateau (northeastern QTP), with an area of 7.2 × 105 km2 (permafrost accounts for 52% of the land) and an elevation ranging from 1669 m to 6548 m, as the study region and estimated its spatial pattern of soil organic carbon (SOC) stock changes at different soil depths from the 1980s to 2010s. The paired site observations of the SOC stocks in the 1980s from the second national soil survey and in the 2010s from a field survey and the literature were compiled and then combined with 77 related environmental factors to drive multiple machine learning models (random forest, gradient-boosting machine, and Cubist), from which the spatial patterns of SOC stock changes at different soil depths (0–30, 30–50, and 50–100 cm) were revealed. The results indicated that the SOC stock increased in the soil at 0–100 cm over the past three decades, with a mean net accumulation rate of 7.36 g C m−2 yr−1 or a total of 0.153 Pg C. Compared with seasonally frozen soil, more significant increases in the SOC stock were observed in permafrost at the 0–100 cm depth (9.71 vs. 4.81 g C m−2 yr−1). However, the SOC stock changes in different soil layers showed significant differences. Specifically, the SOC stock substantially increased in the topsoil layer (0–30 cm), with a carbon increase of 7.82 g C m−2 yr−1; the SOC stock in the middle layer (30–50 cm) had a slight increase, with a carbon increase of 1.69 g C m−2 yr−1; and the SOC stock decreased in the bottom layer (50–100 cm), with a net carbon loss rate of 2.15 g C m−2 yr−1. We found that vegetation change was the key driver of SOC stock change in the topsoil layer. With the increase in soil depth, the importance of climate change on SOC stock change increased. We concluded that climate-driven carbon losses in the deep soil layer were offset by an increase in vegetation-driven carbon inputs at the top and middle soil layers, triggering plant-dominated negative soil carbon feedback to climate warming. With the temperature continuing to increase, however, we must pay more attention to the risk of carbon release in the middle and bottom soil layers.

CO2 impact on convolutional network model training for autonomous driving through behavioral cloning

Autonomous driving and the machine learning (ML) models developed to achieve it have grown rapidly in importance and complexity respectively, and with them has also grown their carbon footprint due to long training times. Given the importance of climate change, it should be necessary to include the CO2 impact of ML models explicitly to encourage competition on more than just model quality. This work presents the implementation of two different Convolutional Neural Network (CNN) training approaches, used for autonomous driving by behavioral cloning in a simulated environment and compares their impact on the CO2 footprint. Using a cloud execution environment and driving data, previously obtained by applying an end-to-end deep learning technique, the first implemented training approach is a classical approach that uses an image generator that carries out the pre-processing and data augmentation during training. The contribution proposed in this paper is a second approach that improves the training by decreasing the training time, carrying out the data augmentation and pre-processing tasks before training the model, storing the result in RAM and then starting the training.The new approach to training presented in this article finishes the training approximately 38 times faster and reduces the carbon footprint impact by approximately 96%. In absolute values, this is a reduction from an average value of approximately 0.1643 CO2eq (kg) to 0.007 CO2eq (kg). To estimate the impact of CO2, the hardware used for the project, the training time and the cloud service provider were all taken into account.

Effect of Future Climate Change on Stratosphere-to-Troposphere-Exchange Driven Ozone in the Northern Hemisphere.

Future estimates of atmospheric pollutant concentrations serve as critical information for policy makers to formulate current policy indicators to achieve future targets. Tropospheric burden of O3 is modulated not only by anthropogenic and natural precursor emissions, but also by the downward transport of O3 associated with stratosphere to troposphere exchange (STE). Hence changes in the estimates of STE and its contributions are key to understand the nature and intensity of future ground level O3 concentrations. The difference in simulated O3 mixing ratios with and without the O3-Potential Vorticity (PV) parameterization scheme is used to represent the model estimated influence of STE on tropospheric O3 distributions. Though STE contributions remain constant in Northern hemisphere as a whole, regional differences exist with Europe (EUR) registering increased STE contribution in both spring and winter while Eastern China (ECH) reporting increased contribution in spring in 2050 (RCP8.5) as compared to 2015. Importance of climate change can be deduced from the fact that ECH and EUR recorded increased STE contribution to O3 in RCP8.5 compared to RCP4.5. Comparison of STE and non-STE meteorological process contributions to O3 due to climate change revealed that contributions of non-STE processes were highest in summer while STE contributions were highest in winter. EUR reported highest STE contribution while ECH reported highest non-STE contribution. None of the 3 regions show consistent low STE contribution due to future climate change (< 50%) in all seasons indicating the significance of STE to ground level O3.

Dynamics of sediment transport in the Yangtze River and their key drivers

Understanding the dynamics of sediment transport and their underlying driving mechanisms is critical to developing strategic plans for sustainable river basin management. However, the quantification of various drivers (e.g., dam construction, soil and water conservation measures) of sediment load change remains scarce, and the projections of sediment transport under the 1.5 °C and 2.0 °C global warming scenarios are not well understood. Here we quantify the sediment load dynamics in the Yangtze River and also estimate the relative contributions of climate change and human activities to these changes using the Soil and Water Assessment Tool (SWAT) hydrologic model and statistical methods. Results show that the sediment load exhibited a significant decreasing trend at most stations in the Yangtze River, with breakpoints occurring around 1993 and 2003. The study period of 1972–2016 can be split into three sub-periods: 1972–1992 (P1), 1993–2003 (P2), and 2004–2016 (P3). From P1 to P3, 95.6 % of the decline can be attributed to climate change, the remainder resulting from the construction of dams and reservoirs (3.6 %) and improved soil and water conservation (0.8 %). Specifically, human activities contributed ∼67.96 % to sediment changes during the period P1–P2, whereas climatic change contributed ∼81.76 % during the period P2–P3. The sediment load significantly increased in the RCP 2.6 (slope = 0.87 Mt·yr−1, P < 0.01) and RCP 4.5 (slope = 0.84 Mt·yr−1, P < 0.05) under the global warming of 1.5 °C and 2.0 °C towards the entire Yangtze River. Compared with the 2.0 °C (2040–2059) global warming scenario, the mean annual sediment load in the 1.5 °C (2020–2039) global warming scenario is smaller by 17.88 Mt. Our investigation found that climate variations will provide a more remarkable contribution to sediment load dynamics in the Yangtze River in the future than the historical average due to the effectiveness of reservoirs decreases and the saturation of the capacity of the soil and water conservation measures to capture sediment. Although these findings indicate the importance of climate change's impact on sediment load changes, it is necessary to apply them to appropriate management to adapt to climate changes in future river basin management policies.

Green Bonds: Quick Insight into One of the Most Implemented Sustainable Debt Instrument to Tackle Climate Change

The importance of climate change and its impacts on different areas has helped to increase the implementation of financial instruments that seek to mitigate or adapt future events. After Paris Agreement in 2015 a particular instrument started to gain momentum: Green Bonds are debt instruments which focus on financing only green projects and even when the need financial flows are higher than actual contributions, green bonds issuance has been breaking major milestones since 2007. Until June 2021, cumulative volume of green bonds was 1.6 trillion dollars, mostly coming from United States, China, and Europe. Countries are exposed to climate change risks despite its contribution to it however efforts from some regions such as Latin America or Africa are still very low. Also, an unorganized transition to a greener future could increase instability within prices, people, and natural resources.

Eco-anxiety: A Q method analysis towards eco-anxiety attitudes in the United Arab Emirates

ABSTRACT Humans are witnessing extreme events such as droughts, floods, heat waves, wildfires, and emergence of novel diseases causing unprecedented changes to our planet. These rapid changes coupled with a transparent world that enjoys access to information mean that today’s population is more aware and attentive about the progress of climate change. The purpose of this study is to discover attitudes towards new gained consciousness and the term Eco-anxiety. The American Psychological Association (APA) defines eco-anxiety as a ‘chronic fear of environmental doom’. To investigate this phenomenon, we use Q-methodology to analyse discourses on the topic. Thirty-nine people from four different stakeholder groups were surveyed. Five distinct discourses were generated covering the connection between environmental awareness and psychological well-being, coming to terms with emotional response to climate change, importance of climate change, awareness about eco-anxiety leading to a more positive outlook, and disbelief that eco-anxiety and climate change can affect mental well-being.

ASTROPARAMO. SCIENCE CLUB OF PLANETARY HABITABILITY AND CLIMATE CHANGE

We introduce Astropáramo: an initiative of science clubs in rural educational institutions in very remote regions of the Santurbán páramo. This initiative uses a mobile laboratory of didactic experiments initially developed by the University of Munich within the project "Climate change: understanding and acting". Taking advantage of the innate charisma for stars in the inhabitants of the mountainous areas of Colombia, we use the teaching of astronomy as a bridge to recognize our planet as the only home and understand the science and importance of climate change. The first version was developed with three educational institutions in the paramo area. The students had synchronous encounters with an instructor via WhatsApp: the only means that the pandemic allowed the connection of students in remote areas of the country. Thanks to this medium, the young people could share their experiences and doubts they encountered in the development of the experiments. Thus, despite the adverse conditions of the pandemic, favorable spaces were generated for debate and the construction of knowledge, demonstrating that science is inclusive, fun, and can be available to everyone.

The Statistical Analysis of Anomalous Anticyclone in Ocean Atmosphere and Economy Based on Target Tracking Algorithm

Based on the importance of climate change in the environmental and economic fields, this study analyzes the impact of climate change on the economy based on the current situation, including the impact on sensitive industries and the impact on each district, in order to study the impact of abnormal atmospheric anticyclones on the economy. Furthermore, this study enhances the image-tracking algorithm, fuses the registered radar picture using the wavelet multiresolution analysis approach, and decomposes the registered radar image using the Mallat algorithm to retrieve the low- and high-frequency components of the image. Because the information included in the frequency components after wavelet decomposition differs, this study uses appropriate fusion algorithms for the decomposed low-frequency and high-frequency components, respectively, to produce panoramic photographs with acceptable visual effects. Through experimental research, it can be seen that the statistical analysis model of anomalous anticyclone in ocean atmosphere and economy based on the target tracking algorithm proposed in this study has a good simulation operation effect, and it also verifies that there is a certain correlation between the atmospheric anomalous anticyclone and the economy.

Quantifying the Contributions of Climate Change and Human Activities to Maize Yield Dynamics at Multiple Timescales

Under a changing environment, the effect of climate change and human activities on maize yield is vital for ensuring food security and efficient socio-economic development. The time series of maize yield is generally non-stationary and contains different frequency components, such as long- and short-term oscillations. Nevertheless, there is no adequate understanding of the relative importance of climate change. In addition, human activities on maize yield at multiple timescales remain unclear, which help in further improving maize yield prediction. Based on the ensemble empirical mode decomposition method (EEMD), the method of dependent variable variance decomposition (DVVD) and the Sen-slope method, the effect of climate change including growing-season precipitation and temperature (i.e., GSP, GEP, CDD, GST, GSMAT, and GSMT) and human activities including effective irrigation area (EIA) and the consumption of chemical fertilizers (CCF) on maize yield were explored at multiple timescales during 1979–2015. The Heilongjiang Province, a highly important maize production area in China, was selected as a case study. The results of this work indicate the following: (1) The original maize yield series was divided into 3.1-, 7.4-, 18.5-, and 37-year timescale oscillations and a residual series with an increasing trend, where the 3.1-year timescale (IMF1), the 18.5-year timescale (IMF3), and the increasing trend (R) were dominant; (2) the original sequence was mainly affected by human activities; (3) climate change and human activities had different effects on maize yield at different timescales: The short-term oscillation (IMF1) of maize yield was primarily affected by climate change. However, human activities dominated the mid- and long-term oscillations (IMF3 and R) of maize yield. This study sheds new insight into multiple timescale analysis of the role of climate and human activities on maize yield dynamics.

Significant Increase in Population Exposure to Extreme Precipitation in South China and Indochina in the Future

Extreme precipitation events cause severe economic losses and can seriously impact human health. Therefore, it is essential to project possible future changes in the population’s exposure to precipitation extremes against the background of global warming. On the basis of model outputs from phase 6 of the Coupled Model Intercomparison Project, our study shows that both the frequency and intensity of extreme precipitation are likely to increase in the South China and Indochina region in the coming century, especially under the business-as-usual Shared Socioeconomic Pathway (SSP) scenario, SSP5-8.5. The largest population exposure can be expected under the SSP2-4.5 scenario, both in South China and Indochina. If early adoption of mitigation measures via the SSP1-2.6 scenario can be achieved, it may be possible to limit the average population exposure in South China to a relatively low level, while Indochina’s may even be smaller than it is currently. In terms of spatial distribution, the maximum population exposure is most likely to be centered in southern South China. This study also reveals that the contribution of the population–climate interaction to population exposure is likely to increase in the future, and different contributions from the factors of climate and population correspond to different emission policies. Under SSP2-4.5, the importance of climate change and the population–climate interaction is more likely to increase.

Response of a low elevation carbonate lake in the Yucatan Peninsula (Mexico) to climatic and human forcings

The importance of climate change, specifically drought, across the Maya region in the northern Neotropics, remains a topic of lively debate. Part of this discussion hinges on the coherency of response to climatic variability across different archives and proxies. In this paper we present a 6600-year palaeolimnological record from Yaal Chac, a carbonate lake (known locally as a cenote) in the northern lowlands of the Yucatan Peninsula, < 2 km from the location of the previously published Aguada X'Caamal record. The Yaal Chac sequence has been analysed for loss-on-ignition (LOI), stable isotopes (δ18O, δ13C) and elemental analysis using μXRF, complemented by some mineralogical, charcoal and pigment data. Mid Holocene sediments, predating evidence of human impact, are carbonate dominated and finely laminated. δ18O values are positive (>2‰), but show no covariation with δ13C. A major transition occurs at ca. 4360 cal yr BP, with a change to generally more organic sediments and increased variability in all proxies. Although direct evidence for anthropogenic activity in the Yaal Chac catchment is limited, it seems feasible that human impact was affecting the system. Comparison with other records from the Northern Maya lowlands and the wider region shows little coherence in the mid Holocene, when Yaal Chac seems to have been quite stable, but possibly responsive to increased climatic seasonality, driving the production of seasonal laminae. In the late Holocene, when the climate was generally more variable, there is more coherence between Yaal Chac and other regional records, including the so called Pan Caribbean Dry Period (3500–2500 cal yr BP) and the droughts of the late Pre-Classic period (1800–1600 cal yr BP). The Yaal Chac record shows no evidence of drought at the time of either the Maya ‘hiatus’ or the Maya ‘collapse’ of the Terminal Classic, but does record drying from the 14th to 19th centuries CE, in keeping with other proxy and historical records. This new record from Yaal Chac highlights the spatial variability of responses to climate forcings and the importance of recognising individual system sensitivity.

Monetize the Urban Multiplier: A Study of India’s National Infrastructure Pipeline and National Monetization Plan

India’s infrastructure requirements are fuelled by increasing urbanization, a more significant contribution of urban areas to employment generation, a shift to the services-based economy, and the rising importance of climate change and disaster resilience. The National Infrastructure Pipeline (NIP) is seen as a foundation for achieving India’s economic goal of becoming a 5 trillion economy by 2024–2025. The National Monetization Plan (NMP) is a vital component to financing the NIP. This research uses content analysis to understand how responsive these two documents are to key factors that drive the growth of India’s infrastructure: urbanization, land availability, incorporating sustainability principles, and involvement of the private sector. It is found that the importance given to these factors in the NIP is not sustained in the NMP, with the consequence that the insights obtained while developing the NIP will not inform a significant effort in its financing. It is useful to set out integrated, risk-informed thinking about the life-cycle of monetization. Strengthening the PPP models of NMP with the appropriate valuation of location in cities, land values, and the risks and constraints represented by sustainability would leverage the urban multiplier.

Renewable Energy Sources as the Future of the Energy Sector and Climate in Poland—Truth or Myth in the Opinion of the Society

The electricity sector in the 21st century should be associated with renewable energy sources (RES), which the majority of society currently equates with solar photovoltaics, wind power, and hydroelectricity, with this energy being used mainly in households. Households consume only 20% of energy, with the remainder used in various sectors of the national economy. In these sectors, the possibilities of using renewable energy sources should be sought. Many experts express the opinion that myths about renewable energy sources exist only “in our minds and opinions, that we formed years ago”, mainly under pressure from the decreasing number of supporters of conventional energy sources. Currently, we observe much greater possibilities of using renewable energy sources globally, and all forecasts suggest that—by 2050—the economy, transport, and industry may become almost emission-free and rely on RES. Of course, we cannot present renewable energy sources only in terms of superlatives, because they also involve many unknowns and myths which we will present in the article. Considering the complexity of factors influencing the involvement of young people in shaping the socio-economic reality, a group of people aged between 18 and 40 was selected for the study. The aim of this study was to identify the attitudes of young inhabitants of south-eastern Poland regarding the issues of climate change and renewable energy, and to identify the level of acceptance for changes in Poland’s energy mix. The conducted research shows that the studied group of people appreciated the importance of climate change and considered the anthropogenic impact on this phenomenon to be of key importance. The perception of renewable energy was positive, and respondents saw the solution to the problems of the energy deficit in increasing the use of renewable energy sources. Respondents also showed significant support for nuclear energy and expected government support programs for activities related to energy conservation. The survey shall be repeated on a random sample at the time when the energy price changes caused by the transformation of the energy mix occur—i.e., around 2025.

Perspectives for Greening European Fossil-Fuel Infrastructures Through Use of Biomass: The Case of Liquid Biofuels Based on Lignocellulosic Resources

Given the importance of climate change it is vital to find a transition away from fossil fuels. The transition will include electrification of several sectors, for example road transport, but considering the strong dependency on carbon-based fuels and associated infrastructures, it is reasonable to assume that biomass-based hydrocarbon will play a key role to smoothen the transition away from fossil fuels. This study provides an analysis of direct and indirect technological options for liquid biofuels based on lignocellulosic resources in the context of greening European fossil-fuel infrastructures. Direct options are those which result in integration of biogenic feedstock in a fossil-based process and then co-processing in a downstream conventional unit or substituting a conventional part of the production chain of a liquid fuel by a bio-based one. Indirect options are those which pave the way for ramping-up biomass supply chain in the form of infrastructure and market. Examples of direct options in the focus of this study are biomass gasification for production of intermediates and biomass pyrolysis substituting fossil feedstock. Examples of indirect options are co-firing biomass in coal-fired power plants and integrating biomass gasification plants with district heating (DH) networks. Such options are important for establishing biomass supply chains and markets. This study also assesses the potential of biomass use in other industrial sectors not directly related with fossil-based fuel or energy production, such as the pulp and paper industry and the iron and steel industry. In this context, opportunities and barriers for both direct and indirect greening options are discussed, focusing mainly on technological and logistic aspects. It is highlighted that fossil-fuel infrastructures can act as drivers for the development of advanced biofuels production as they can reduce the initial risks, in terms of cost and technological maturity, offering the opportunity to increase gradually the demand for biomass, and develop the logistic infrastructure. It is, however, important to make sure that such biofuel production processes are part of a long-term strategy, which needs incentives to overcome current barriers and eventually phase out fossil infrastructures.

Bots and online climate discourses: Twitter discourse on President Trump’s announcement of U.S. withdrawal from the Paris Agreement

ABSTRACT In the early days of social media, social scientists speculated that it could support democracy because large media conglomerates could not dominate it. Regarding climate change, research documents the influence of the fossil fuel industry in climate denial discourses in the traditional media. Therefore, a similar hope emerged that a more democratized platform would see less polarization in belief about climate change's scientific basis. However, online public opinion about climate change continues to be extremely polarized, and the social forces behind it are not well understood. Here, we examine the role of one proposed mechanism for the systemic polarization and spread of disinformation in online discourses - the automated social media bot. This article pioneers the use of bot detection software on climate change discussion on Twitter, using automated monitoring of 6.8 million tweets. We examine the period around the time of U.S. President Donald Trump's announcement of U.S. withdrawal from the Paris Agreement on June 1, 2017. We find that the announcement generated an immediate online social movement response with very low suspected bot presence. Prior to and afterwards, however, suspected bots were responsible for approximately 25% of original tweets. Additionally, we find that suspected bots were more frequent in some topic areas than others, including denialist discourses focused on research questioning the reality or importance of climate change. Key policy insights On an average day during our study period, automated bots produced an estimated one-quarter of all original tweets referencing climate change and global warming. Bots were more active in some discussion areas than others - including climate denialist messages. President Trump's announcement of the U.S.'s planned withdrawal from the Paris Agreement generated an immediate online social movement response with very low suspected bot presence. For social media to deliver on its promise of a decentralized and democratic forum, automated accounts need to be identified, marginalized, and removed.

Aerosols in an urban cold climate: Physical and chemical characteristics of nanoparticles

Atmospheric aerosols are of significant importance in climate change and health research. This study provides a 2-years meta dataset of real-time aerosol number and size distribution measurements in a model cold-climate city of Montreal (Canada). We provide selected information on the chemical composition and morphology of aerosols (~10 nm to 10 μm). We deployed a suite of complementary techniques such as aerosol particle sizers, MOUDI, S/TEM imaging, EDS, QQQ-ICP-MS/MS, IC, and TOC analyzers. The highest geomean nanoparticles (<100 nm) number density (9260 ± 1.6 number/cm3) was observed in the winter. A broad range of metals, including emerging contaminants, was quantified in all aerosol sizes include Pb, Cd, Ni, Zn, As, Al, Mn, Co, and Se, with concentrations ranging from 0.01 to 67.64 ng/m3. Nanosize particles included Ni, Cd, Pb, Zn. Iron exhibited the highest concentrations consistently in two modes (<180 nm and > 1 μm). S/TEM-EDS confirmed the abundance of nanoparticles, single and clusters, with multifaceted morphologies and compositions. We identified (a) emerging nanoparticles, (b) secondary organic aerosols, (c) bioaerosols, and (d) combustion particles. Diurnal, weekly, monthly, seasonal, and yearly variations of aerosols are provided. We herein discuss the implications of these results on air quality and climate modelling.