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Much research has been conducted to find evidence of the environmental Kuznets curve (EKC) in the relationship between air-pollutant concentration and economic development. A major focus of EKC-related research has so far been to identify the turning point illustrated by EKC theory or to predict the moment when the turning point will occur. In our research, via analyzing the relationship between an aggregate social-development-representative variable (the Socio-demographic Index or SDI) and the population-weighted concentration of PM2.5, we propose that the overall relationship takes the form of a tilted-S shape with two types of turning points rather than one. Additionally, our research shows that the EKC is highly country-specific, making it extremely difficult to predict the positions of both turning points based on the historical development or trajectories of other countries. Therefore, we conclude that EKC theory is not a useful tool to predict the location of the turning points. However, for short-term prediction of the relationship, we advocate the use of support vector regression, which can forecast the evolution, unless rapid changes are occurring. We suggest that policy makers should not anchor their hopes on predicting turning points from previous studies, but should put more effort into dealing with present particulate matter pollution.

Severe episodic air pollution blankets entire cities and regions and have a profound impact on humans and their activities. We compiled daily fine particle (PM2.5) data from 100 cities in five continents, investigated the trends of number, frequency, and duration of pollution episodes, and compared these with the baseline trend in air pollution. We showed that the factors contributing to these events are complex; however, long-term measures to abate emissions from all anthropogenic sources at all times is also the most efficient way to reduce the occurrence of severe air pollution events. In the short term, accurate forecasting systems of such events based on the meteorological conditions favouring their occurrence, together with effective emergency mitigation of anthropogenic sources, may lessen their magnitude and/or duration. However, there is no clear way of preventing events caused by natural sources affected by climate change, such as wildfires and desert dust outbreaks., The authors would like to acknowledge the support of the: Australia-China Centre on Air Quality Science and Management (ACC-AQSM) to undertake and conduct this study; Department of Water and Environmental Regulation (DWER) in Western Australia for access to the data; Spanish Ministry of Science and Innovation and FEDER funds under the project HOUSE (CGL2016-78594-R), and by the Generalitat de Catalunya (AGAUR 2017 SGR41); Climate and Resilient Research (FONDAP 15110009), and the PAPILA (Prediction of Air Pollution in Latin America and the Caribbean) project (ID: 777544, H2020-EU.1.3.3.); ASAP-Delhi project (An Integrated Study of Air Pollutant Sources in the Delhi National Capital Region) funded by the Natural Environmental Research Council under the grant number NE/P016510/1; Stockholm Air and Noise Analysis at Stockholm City Environmental Department for the provision of the data; National Key R&D Program of China via grant No. 2017YFC0212001; National Air Pollution Surveillance (NAPS) program in Canada for data on PM2.5.

This research focuses on treatment model of diesel leakage accident near the Weihe River at the beginning of 2010. A technical option is proposed for determination of diesel content in soil by the method of ultrasonic-ultraviolet spectrophotometry, so as to evaluate the soil pollution and reasonably select the remediation scheme according to the pollution degree and the migration and transformation regularity of diesel contaminants in the loess soil. Results show the diesel-soil separation effect comes to the maximal degree during the deposition process using petroleum ether as extraction solvent, and ultrasonic irradiation at 200W for 10min, and then using ultraviolet spectrophotometry to determine the diesel content in soil. The diesel content in soil at each sampling point exceeds the maximum allowable concentration (3g/kg). If physical remediation is applied at the occurrence of the accident and bioremediation is selected later, the migration and transformation efficiency of diesel contaminants can be improved and the diesel content in soil can be reduced. The objective of this paper is to establish a model of the determination and remediation of diesel contaminants in soil, which can be used for reference in the treatment of petroleum leakage accident.