International Journal of Big Data Mining for Global Warming

One aspect of the psychology of weather and climate concerns the multiple meanings that may be associated with weather and climate as event. Atmospheric scientists and journalists have increasingly described both weather and climate as event. In this paper, the authors documented the increasing use of weather and climate as events in the scholarly literature of the American Meteorological Society and in newspaper articles over time. The authors also conducted pathfinder network scaling analyses with event-related terms to assess the meanings of events in academic and journalistic writing. The analyses suggested four contexts of event meanings: (1) study of ordinary weather or climate occurrences, (2) the study and attribution of severe and extreme weather, (3) societal impacts of weather, and (4) the public lexicon. Communicating about weather and climates as event contributes to the development and evolution of the public idea of climate change. The burgeoning of event in discourse contributes to the public idea of climate change in at least three ways: (1) events contribute specificity to the more general idea of climate change; (2) events contribute experientiality of climate change, and (3) events contribute exemplification to the public idea of climate change to the extent that weather events can be attributed to climate change.

Pakistan is ranked in the 7th position among the affected countries by climate changes. Although many studies have been done on the impacts of climate change in Pakistan, little attention has been given to the need for an energy transition and reduction of greenhouse gas emissions in this country. This study highlights the needs of the national energy transition in Pakistan to reduce the greenhouse gas emissions. Considering the fact that natural gas has lower greenhouse gas emission than coal or oil, Pakistan needs to shift its energy system towards natural gas in the near future. Meanwhile, Pakistan government should take key measures and revise energy policies to support such energy transition by making large gas discoveries, increasing energy conversion systems, and implementing renewable and sustainable energies.

The influence of solar activity on climate system at regional or global scales cannot be neglected. In this study, we will stimulate full-length sunspot time series (1932–2014) and all four Hale cycles by fractional auto regressive integrated moving average (FARIMA ($p$, $d$, $q$)) model. By minimizing Akaike information criterion (AIC), Bayesian–Schwarz information criterion (BIC) and Hannan–Quinn information criterion (HIC), the best FARIMA model for full-length sunspot time series is

The treatment of large-scale air pollution models is not only important for modern society, but also an extremely difficult task. Five important physical and chemical processes: (1) horizontal advection, (2) horizontal diffusion, (3) vertical exchange, (4) emission of different pollutants and (5) dry and wet deposition have to be united and handled together. This leads to huge computational problems which have to be treated on modern high-speed parallel architectures by using advanced numerical methods. The computational difficulties are vastly increased when such models are used in the investigation of the impact of climatic changes on high pollution levels that are often exceeding certain critical concentrations and, therefore, are becoming harmful for plants, animals and human beings. There are two major reasons for the great increase in computational difficulties: (a) it is necessary to run the discretized data on fine spatial grid models over very long time-periods consisting of many consecutive years and (b) different scenarios are to be used in order to investigate the sensitivity of the pollution levels to systematic variations of several carefully selected key parameters. How the major difficulties can be resolved is explained here. Furthermore, many results are presented in order to demonstrate the ability of the model to handle successfully the huge computational tasks by using fine space and time discretization and by applying a chemical scheme with many chemical species participating in several hundred chemical reactions. Our results indicate that the climatic changes will often lead to some increases in the pollution levels.

In May 2017, Department of Science, Technology and Standards, MEP, China held the first training conference of “2017 CCUS environmental risk assessment technology”. After the conference, specially designed questionnaires were sent to the participants so as to collect the professional opinions to improve the guideline in the next revision. Basic information of participants, knowledge of capture, utilization and geological storage (CCUS), and attitude to the CCUS environmental risk are contained in the questionnaires. The 82 questionnaires were issued to the participants, and 77 valid questionnaires were collected with the response rate of 93.9%. According to the data mining, (a) nearly one third of the participants had not heard of the CCUS before the training; (b) the attitude to CCUS environmental impact and risk is influenced by the knowledge of CCUS; (c) the severities of the three aspects of capture component are medium; (d) for onshore CCUS projects, underground water, atmosphere, soil, and human health were considered the highest sensitivity receptors; (e) the enterprises were very concerned of the CCUS environmental management policies, three most important policies were conducting environmental monitoring across the whole chain, clarifying the environmental management responsibilities, and establishing emergency plans for environmental accidents. The result of this survey would provide the guidance for the improvement of the technical guideline which planned to be released during the official version in 2020.