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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.

As the environmental awareness of urban citizens increases, traditional air quality monitoring stations cannot satisfy the need for air quality data at high temporal and spatial resolution due to their high construction and maintenance costs. Low-cost air quality monitors are being increasingly used for this purpose because of their portability and affordable price. However, low-cost monitors are usually beset by data quality issues, and the number of mounted air pollutant sensors is limited by the restriction of the cost and size of monitors. Therefore, we propose to extend the use of air quality monitor data via a deep learning technique called long short-term memory (LSTM). The extension is embodied in two aspects: first, calibration of air pollutant concentration data; and second, provision of indicative information about air pollutants where no corresponding sensors are available. A low-cost air quality monitor called KOALA (Knowing Our Ambient Local Air Quality), which was deployed in Sydney (Australia), was used as an example to prove this method's feasibility. Data from a 90-day period were used for model training, and data from a 30-day period were used for model validation. Random forest models were used for selecting the most useful LSTM model input variables. Historical 24-h information was incorporated to improve the performance of the LSTM models. The results showed that: first, LSTM models can be used to calibrate KOALA carbon monoxide (CO) data with the optimum input being raw CO measurements and the corresponding standard deviation information; and second, LSTM models can be used to estimate ozone concentration with the optimum input being CO concentration and three meteorological parameters [i.e. top soil layer temperature, 10 m U wind (earth-relative), and net shortwave radiation flux at the ground] generated through a deterministic model known as WRF (Weather Research and Forecasting). In addition, the LSTM ozone estimation model showed good performance at both the training location and a location 11 km away, indicating that the proposed method can be used to provide indicative information about air pollutants around the training location.

There are currently more than 400 cities that are subject to the urban heat island (UHI) effect, whose summer temperature can be over 15 °C above the human thermal comfort zone. As the scope of urbanization expands, more people will feel the influence of the UHI effect. Since cool coatings can serve as a mitigation measure against the UHI effect, this research proposes a method that can estimate its mitigation effect in any given region. The main idea of this method is to simulate the function of cool coatings via increasing the albedo values in the Weather Research and Forecasting (WRF) model. The main novelty of this method is that it incorporates detailed land categorization data to simulate realistic urban morphology for the purpose of improving model performance. To demonstrate the feasibility of the proposed method, the UHI mitigation effect of cool coatings was estimated in the city of Sydney during two consecutive sweltering days (7–8 January 2018) via the WRF model. The results showed that the proposed method fulfilled its purpose. To be specific, as the consequence of a 0.35 albedo increase in urban Sydney, the whole urban area will be subject to an average temperature decrease of 0.76 °C, while some regions will experience a temperature decrease as great as 5.71 °C during the hottest hour. However, this value for a given zone, such as the downtown coast area, was closely related to the local wind directions. The results also showed that the values of different urban canopy parameters could be treated as auxiliary information of WRF modeling results and used to identify the locations that suffered the most from the UHI effect. Therefore, the proposed method can help decision-makers and stakeholders to better analyze the UHI mitigation potential of cool coatings. Additionally, it indicates incorporating detailed land categorization data is an effective way of improving UHI numerical simulations.

Iron oxides are widely used as adsorbents to remove pollutants because of their excellent surface activities and resultant significant adsorption capabilities. In an effort to study the adsorption and desorption behavior of arsenic in aqueous solutions containing magnetism iron oxide (MIO), solid-liquid separations were conducted in the laboratory using synthetically-prepared solutions. Results indicate that arsenic can be easily adsorbed and the adsorption can be described using Langmuir and Freundlich equation. It was determined that the capability of MIO for arsenic adsorption depended primarily on the surface activity of the adsorbent, pH of the solution, and arsenic speciation. Optimization adsorption was found to occur between pH 6.0 and 9.4 for arsenic (III) and pH less than 5.0 for arsenic (V). Adsorbed arsenic (V) could be easily desorbed from using a 10 percent solution of sodium hydroxide whereas arsenic (III) was found to be recalcitrant.

The research object of our study is oil sludge produced in petrochemical wastewater treatment. A technical option is proposed in conditioning and dewatering of oil sludge, recycling of gas condensate and malysite so as to minimize the oil containing sludge, fully utilize resources and to protect environment. Results show that the structure of oil sludge is improved and the dewatering effect of oil sludge by flocculants conditioning. The sludge dewatering rate can increase about 22% and the gas condensate content is reduced to 0.086g/g after ultrasonic treatment. The malysite recovery and the total solid reduction are improved to 72.15% and 46.41% under the synergistic effect of acidification and ultrasonic wave. Finally, the excess sludge solidification by using solar drying method can reach landfill atandard. The objective of this paper is to establish a technique of the oil sludge treatment, which can be used for reference in the recycling utilization of oil sludge resource.

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.

The extensive application of malysite flocculants inevitably brings about the massive production of malysite-containing sludge. The recycle of malysite flocculants can not only make the sludge reduced in volume and reused as resource, but also solve the problems of environment protection. The research object of our study is malysite-containing sludge. The technology of recycling malysite under the synergistic effect of acidification and ultrasonic is also discussed in our study. Experimental results show that the recovery rate of malysite raises accordingly with the concentration of [H]+ increasing. Under the influence of ultrasound, the average particle diameter of the sludge is decreased, the reaction rate is increased, the recovery rate of malysite and the reduction of total solid are enhanced. The malysite recovery rate and the total solid reduction is in a linear relationship under the effect of acidification, the effect of ultiasonic, the synergistic effect of acidification and ultrasonic.

Mg3Al Layered Double Hydroxides (Mg3Al-LDH) and calcined Mg3Al layered double hydroxides (Mg3Al-CLDH) are prepared. According to the gas field in northern Shaanxi water quality analysis results, this kind of wastewater is simulated in the laboratory, this paper studies on removal rate of easily scaling carbonate anion by Mg3Al-CLDH. For carbonate anion solution with concentration of 100 mg/L, the removal rate of carbonate anion could be over 59% by addition of 1.0g/L Mg3Al-CLDH after 4h reaction at 20°C, and pH=10~12, but the removal rate of 100 mg/L carbonate anion by Mg3Al-CLDH after four times recycling may still be 57.79%, so the removal rate may reach up to 90% after multiple times recycling use of Mg3Al-CLDH. Mg3Al-CLDH has the characteristics of eco-friendliness, reusability, low cost and so on, so calcined hydrotalcite is an ideal material that is used in wastewater scale inhibition in the oil and gas fields.

Collection, treatment, operation and management of municipal solid waste (MSW) at home and abroad are presented in the paper, expounding the development trends of disposing MSW, which are to classify and collect garbage, promote recycling benefits, make resource and harmless disposal of non-recycle. It is recommended that each city choose reasonable waste disposal methods, learn from foreign advanced technology and experience, according to the characteristics of geography, economy and MSW in local areas. Some specific suggestions are also provided in the paper.

This paper focuses on the color reaction of chromotrope and formaldehyde, an oxidation product of methanol, with sulfuric acid as the medium, under the existence of phosphoric acid. The generated purple complexes have characteristic absorption peak at wavelength of 570 nm. This reaction principle is applicable to measurement of methanol content in gas field wastewater. It is found there is a linear relationship between methanol content and absorbance while methanol content is within the range of 1~99.0 mg/L. This method has added recovery rate of 97.8~104.5%, detection limit of 1.0 mg/L and relative standard deviation less than 2.9%. The match rate of test results, obtained by this method and gas chromatography respectively, is higher than 95.0%. It is a simple, rapid and accurate method for supervision and management of methanol-containing wastewater in gas fields.