Identifying the evolution of primary oxidation mechanisms and pollutant degradation routes in the electro-cocatalytic Fenton-like systems.

Herein, electro-catalysis (EC) as the electron donor to accelerate the continuable Fe(III)/Fe(II) cycles in different inorganic peroxides (i.e., peroxymonosulfate (PMS), peroxydisulfate (PDS) and hydrogen peroxide (HP)) activation systems were established. These electro-cocatalytic Fenton-like systems exhibited an excellent degradation efficiency of sulfamethoxazole (SMX). A series of analytical and characterization methods including quenching experiments, probe experiments, and electron paramagnetic resonance spectrometry (EPR) were implemented to systematically sort out the source and yield of reactive oxygen species (ROS). A wide kind of ROS including hydroxyl radical (•OH), singlet oxygen (1O2), and sulfate radical (SO4•-), which contributed 38%, 37%, and 24% were produced in EC/Fe(III)/PMS system, respectively. •OH was the dominant ROS in both EC/Fe(III)/PDS and EC/Fe(III)/HP processes. According to the analysis of SMX degradation routes and biotoxicity, abundant degradation pathways were identified in EC/Fe(III)/PMS process and lower environmental impact was achieved in EC/Fe(III)/HP process. The diversiform ROS of EC/Fe(III)/PMS system makes it exhibit greater environmental adaptability in complex water matrixes and excellent low-energy consumption performance in many organic pollutants degradation. Continuous flow treatment experiments proved that the three systems have great sustainability and practical application prospect. This work provides a strong basis for constructing suitable systems to achieve different treatment requirements.

Water quality assessment and pollution source apportionment using multivariate statistical techniques: a case study of the Laixi River Basin, China.

Identifying potential sources of pollution in tributaries and determining their contribution rates are critical to the treatment of water pollution in main streams. In this paper, we conducted a multivariate statistical analysis on the water quality data of 12 parameters for 3 years (2018-2020) at six sampling sites in the Laixi River to qualitatively identify potential pollution sources and quantitatively calculate the contribution rates to reveal the tributaries' pollution status. Spatio-temporal cluster analysis (CA) divided 12 months into two parts, corresponding to the lightly polluted season (LPS) and highly polluted season (HPS), and six sampling sites were divided into two regions, corresponding to the lightly polluted region (LPR) and highly polluted region (HPR). Principal component analysis (PCA) was used to determine the potential sources of contamination, identifying four and three potential factors in the LPS and HPS, respectively. The absolute principal component score-multiple linear regression (APCS-MLR) receptor model quantitatively analyzed the contribution rates of identified pollution sources, and the importance of the different pollution sources in LPS can be ranked as domestic sewage and industrial wastewater and breeding pollution (33.80%) > soil weathering (29.02%) > agricultural activities (20.95%) > natural influence (13.03%). HPS can be classified as agricultural cultivation (41.23%), domestic sewage and industrial wastewater and animal waste (33.19%), and natural variations (21.43%). Four potential sources were identified in LPR ranked as rural domestic sewage (31.01%) > agricultural pollution (26.82%) > industrial effluents and free-range livestock and poultry pollution (25.13%) > natural influence (14.82%). Three identified latent pollution sources in HPR were municipal sewage and industrial effluents (37.96%) > agricultural nonpoint sources and livestock and poultry wastewater (33.55%) > natural sources (25.23%). Using multivariate statistical tools to identify and quantify potential pollution sources, managers may be able to enhance water quality in tributary watersheds and develop future management plans.

Study on Emission Characteristics and Emission Reduction Effect for Construction Machinery under Actual Operating Conditions Using a Portable Emission Measurement System (Pems).

With the acceleration of urban construction, the pollutant emission of non-road mobile machinery such as construction machinery is becoming more and more prominent. In this paper, a portable emissions measurement system (PEMS) tested the emissions of eight different types of construction machinery under actual operating conditions and was used for idling, walking, and working under the different emission reduction techniques. The results showed that the pollutant emission of construction machinery is affected by the pollutant contribution of working conditions. According to different emission reduction techniques, the diesel oxidation catalyst (DOC) can reduce carbon monoxide (CO) by 41.6-94.8% and hydrocarbon (HC) by 92.7-95.1%, catalytic diesel particulate filter (CDPF) can reduce particulate matter (PM) by 87.1-99.5%, and selective catalytic reduction (SCR) using urea as a reducing agent can reduce nitrogen oxides (NOx) by 60.3% to 80.5%. Copper-based SCR is better than vanadium-based SCR in NOx reduction. In addition, the study found that when the enhanced 3DOC + CDPF emission reduction technique is used on forklifts, DOC has a "low-temperature saturation effect", which will reduce the emission reduction effect of CO and THC. The use of Burner + DOC + CDPF emission reduction techniques and fuel injection heating process will increase CO's emission factors by 3.2-3.5 and 4.4-6.7 times compared with the actual operating conditions.

Kinetics and reaction mechanism of photochemical degradation of diclofenac by UV-activated peroxymonosulfate.

Diclofenac (DCF) is a common non-steroidal anti-inflammatory drug, which is frequently detected in different environmental media such as surface water, groundwater, domestic sewage, and sediment. In this study, UV-activated peroxymonosulfate (PMS) was used to degrade DCF by generating active radicals (i.e., SO4˙- and HO˙) with strong oxidizing properties. The effects of PMS dosage, pH, initial DCF concentration and common water constituents on the removal of DCF as well as its degradation mechanism in UV/PMS system were investigated. Compared to UV alone and PMS alone systems, DCF was removed more efficiently in the UV/PMS system at pH 7.0 due to the contribution of SO4˙- and HO˙, and its degradation followed the pseudo-first order kinetic model. As the dosage of PMS or solution pH increased, the degradation efficiency of DCF was gradually enhanced. The highest DCF degradation was obtained at pH 11.0 in this study, because the molar absorption coefficient of PMS increased with increasing pH at 254 nm resulting in generation of more reactive radicals at high pH. Removal efficiency of DCF was decreased significantly with the increase in its initial concentration due to the insufficient concentration of radicals. The presence of HCO3 - and NO3 - could promote the degradation of DCF because of the role of carbonate radicals and extra HO˙ formed, respectively, while NOM inhibited DCF degradation due to its competition with DCF for reactive radicals. No obvious influence on DCF degradation was observed in the UV/PMS system with the addition of Cl- and SO4 2-. The degradation of DCF by UV/PMS in real waters was slightly suppressed compared with its removal in ultrapure water. Seven transformation products were detected using UPLC-QTOF/MS, and the potential degradation mechanism of DCF was thus proposed showing six reaction pathways including hydroxylation, decarboxylation, dechlorination-cyclization, formylation, dehydrogenation and dechlorination-hydrogenation.

Degradation of diclofenac by Fe(II)-activated peracetic acid.

In this study, peracetic acid (PAA) activated by Fe(II) was proposed to remove diclofenac (DCF) in polluted water. It was found that Fe(II)/PAA system could effectively remove DCF at neutral condition, which has a significant advantage over classical Fenton process. According to the result of scavenging experiment, both hydroxyl radical and peroxy radical were considered to be responsible for the degradation of DCF. The influence of several operational parameters including initial pH, Fe(II) dosage, PAA concentration and common water matrix on DCF removal were investigated. 80% DCF was removed at mild condition (pH 6-7) within 60 s, and its removal rate could be enhanced with the increase in Fe(II) dosage and PAA concentration. Presence of HCO3- and natural organic matter (NOM) was proved to have a significantly negative impact on DCF degradation. Four probable degradation pathways of DCF were proposed based on the detected reaction products, including hydroxylation, C-N bond cleavage, decarboxylation and dehydrogenation.

Kinetics and pathways of diclofenac degradation by heat-activated persulfate.

In this study, the degradation of diclofenac (DCF) by heat-activated persulfate (HAP) was investigated. It was found that DCF could be degraded efficiently by HAP. The degradation of DCF followed the pseudo-first-order kinetic model, and the highest observed degradation rate constant (k obs) was obtained at pH 3. The sulfate radical was mainly responsible for DCF removal at pH < 7, whereas it was the hydroxyl radical at high pH. The elimination of DCF was enhanced with the increase in temperature or initial dosage of persulfate. Presence of Cu2+ and CO3 2- could improve DCF degradation, while an inhibition effect was observed in the presence of natural organic matter. According to the identified nine transformation products, the potential DCF degradation mechanism was proposed revealing five different reaction pathways, including hydroxylation, decarboxylation, formylation, dehydrogenation and C-N bond cleavage. This study indicates that HAP can effectively oxidize and degrade DCF, especially under acidic conditions.