At present, there is relatively little research on the impact of climate change on regional air quality, and statistical downscaling methods are often used to process global climate model results. The WRF mesoscale meteorological model is used to dynamically downscale the CMIP5 RCP8.5 scenario estimation results of the CCSM4 climate model, and to provide a meteorological field for the CMAQ air quality model; Based on the 2012 Tsinghua University MEIC atmospheric pollutant emission inventory, 2005 was selected as the representative year for climate status and 2049-2051 as the future climate representative year. The meteorological and air quality numerical simulation results of typical months (January, April, July, and October) in the Beijing Tianjin Hebei region were compared to estimate the potential changes in air quality in the Beijing Tianjin Hebei region under the background of climate change. The results showed that under the unchanged emission situation and the RCP8.5 scenario, Compared with the current representative year, the average annual meteorological factors in the Beijing Tianjin Hebei region, represented by typical months, show an overall trend of temperature increase, while wind speed, relative humidity, and atmospheric boundary layer height all decrease; The annual average concentration of atmospheric pollutants shows an overall upward trend, with temperatures increasing by about 0.8 ℃, wind speeds decreasing by about 0.11 m/s, relative humidity decreasing by about 2%, and atmospheric boundary layer height decreasing by about 8 m, ρ (PM2.5) increase by approximately 2.4 μ G/m3, ρ (SO2) increases by approximately 1.8 μ G/m3, ρ (NOx) increases by approximately 1.0 μ G/m3; In addition, among the main meteorological conditions (temperature, wind speed, relative humidity, atmospheric boundary layer height), the decrease in wind speed and atmospheric boundary layer height may be the main meteorological factors causing changes in the concentration of these atmospheric pollutants, and the decrease in wind speed and atmospheric boundary layer height is related to ρ The correlation coefficients of (PM2.5) reduction are approximately -0.44 and -0.26, respectively. Studies have shown that climate change poses a potential risk of increasing pollutant concentrations in the Beijing Tianjin Hebei region. At the same time, due to the lack of future emission scenario data for air quality models and the increasing improvement of online coupling models, deeper research is urgently needed in the field of climate air quality research in China
{"title":"Preparation of Porous Pellets Based on Nano-Zero Valent Iron-Enhanced Fly Ash and Their Application for Crystal Violet Removal","authors":"Xiaolin Zhang, Teza Mwamulima, Yongmei Wang, S. Hu, Q. Gu, Changsheng Peng","doi":"10.13198/J.ISSN.1001-6929.2017.02.48","DOIUrl":"https://doi.org/10.13198/J.ISSN.1001-6929.2017.02.48","url":null,"abstract":"","PeriodicalId":21108,"journal":{"name":"环境科学研究","volume":"30 1","pages":"1295-1302"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49436817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.13198/J.ISSN.1001-6929.2017.02.20
Qucheng Deng, Xiaofei Wang, Juan Yin, C. Deng
This study aimed to investigate how the development of the non-ferrous metals industry impacted sediment deposition in the upstream Xijiang Basin. Twelve sampling sites were selected on four tributaries in the upstream Xijiang Basin, namely, Diaojiang River, Longjiang River, Rongjiang River, and Liujiang River. Contents of Cu, Zn, Pb, Cd, As, Cr, Ni, Tl, Sb and Hg in sediments were measured in the twelve sampling sites, then correlation, clustering, and lead isotope tracing analyses were used to evaluate the distribution and sources of the measured heavy metals in sediments. The results showed that: (1) the average contents of As, Pb, Cd, Ni, Zn, Cu, Tl, Hg, Sb and Cr in sediments were 95.42, 113.09, 4.92, 28.03, 416.51, 27.07, 0.75, 0.31, 34.02 and 57.58 mg/kg, respectively. The river sediments have been seriously polluted by Cd, As, Zn and Pb, moderately polluted by Hg and Sb, and slightly polluted by Cr, Ni, Cu and Tl. (2) From a spatial perspective, the order of pollution degrees of sediments in the four tributaries was Diaojiang, Longjiang, Rongjinag, and Liujiang. (3) Regarding the source of contamination, As, Pb, Cd, Zn, Cu and Sb in the sediments were related to the mineral exploitation of nonferrous metal accumulation areas in the upstream Xijiang Basin. Ni, Tl, Hg and Cr in sediments mainly came from the natural geological background. The range of Pb/Pb ratio was 1.08 to 1.19 in the sediments. The order of similarity between lead isotope ratio in the sediments of the four tributaries and ore of Dachang and Chehe was Diaojiang, Longjiang, Rongjiang, and Liujiang. Lead isotope tracing analysis further revealed that heavy metals in the sediments of Diaojiang and Longjiang Rivers originated from non-ferrous mining and smelting activities, and those in Rongjiang and Liujiang Rivers were mainly contributed by the geological background in the sites.
{"title":"Spatial Distribution and Source Analysis of Heavy Metals in Sediments of the Upstream Xijiang Basin within Nonferrous Metal Accumulation Areas","authors":"Qucheng Deng, Xiaofei Wang, Juan Yin, C. Deng","doi":"10.13198/J.ISSN.1001-6929.2017.02.20","DOIUrl":"https://doi.org/10.13198/J.ISSN.1001-6929.2017.02.20","url":null,"abstract":"This study aimed to investigate how the development of the non-ferrous metals industry impacted sediment deposition in the upstream Xijiang Basin. Twelve sampling sites were selected on four tributaries in the upstream Xijiang Basin, namely, Diaojiang River, Longjiang River, Rongjiang River, and Liujiang River. Contents of Cu, Zn, Pb, Cd, As, Cr, Ni, Tl, Sb and Hg in sediments were measured in the twelve sampling sites, then correlation, clustering, and lead isotope tracing analyses were used to evaluate the distribution and sources of the measured heavy metals in sediments. The results showed that: (1) the average contents of As, Pb, Cd, Ni, Zn, Cu, Tl, Hg, Sb and Cr in sediments were 95.42, 113.09, 4.92, 28.03, 416.51, 27.07, 0.75, 0.31, 34.02 and 57.58 mg/kg, respectively. The river sediments have been seriously polluted by Cd, As, Zn and Pb, moderately polluted by Hg and Sb, and slightly polluted by Cr, Ni, Cu and Tl. (2) From a spatial perspective, the order of pollution degrees of sediments in the four tributaries was Diaojiang, Longjiang, Rongjinag, and Liujiang. (3) Regarding the source of contamination, As, Pb, Cd, Zn, Cu and Sb in the sediments were related to the mineral exploitation of nonferrous metal accumulation areas in the upstream Xijiang Basin. Ni, Tl, Hg and Cr in sediments mainly came from the natural geological background. The range of Pb/Pb ratio was 1.08 to 1.19 in the sediments. The order of similarity between lead isotope ratio in the sediments of the four tributaries and ore of Dachang and Chehe was Diaojiang, Longjiang, Rongjiang, and Liujiang. Lead isotope tracing analysis further revealed that heavy metals in the sediments of Diaojiang and Longjiang Rivers originated from non-ferrous mining and smelting activities, and those in Rongjiang and Liujiang Rivers were mainly contributed by the geological background in the sites.","PeriodicalId":21108,"journal":{"name":"环境科学研究","volume":"30 1","pages":"1221-1229"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49163954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to understand the toxic effects of Sb (antimony) on soil invertebrates and compare the differences in Sb toxicity in different types of soil, three groups of individual level evaluation indicators, namely mortality rate, escape rate, and reproduction number, were selected to study the acute and chronic toxic effects of exogenous Sb addition on the model organism, Folsomia candida, in three typical soils (Helen black soil, Qiyang red soil, and Beijing tidal soil). The results showed that:, Based on the measured w (Sb total), the 2d-EC50 (EC50 is the half effective concentration) of Sb affecting the escape of fleas in the above three soils were 298,>431 [higher than the highest w (Sb total) in the soil] and 132 mg/kg, respectively; The 7 d-LC50 (LC50 is the median lethal concentration) that affects the death of jumping insects are 3352, 4007, and 2105 mg/kg, respectively; The 28 d-LC50 that affects the death of fleas were 2271, 1865, and 703 mg/kg, respectively, and the 28 d-EC50 that affects the reproduction of fleas was 1799, 1323, and 307 mg/kg, respectively. From the above toxicity thresholds, it can be seen that the sensitivity of flea escape rate is higher than that of mortality rate and reproduction number. There is a significant difference in the toxicity of Sb to fleas in different soils. The toxicity of Sb to fleas in Beijing Chao soil is close to six times higher than that in Helen black soil and Qiyang red soil, It indicates that different soil physicochemical properties have a significant impact on the ecotoxicity effect of Sb. However, the difference in toxicity thresholds of Sb in the above three soils obtained based on w (Sb water extraction) decreases, indicating a significant correlation between water extracted Sb and its toxicity, which can better explain the differences in Sb toxicity among different soils. The research results can provide a basis for establishing a toxicity prediction model for Sb in soil in China and formulating quality standard values for Sb
In order to explore the degradation ability of sulfate radical on azo dyes, direct acid resistant red 4BS (hereinafter referred to as red 4BS) was used as a simulated pollutant. The effects of initial c (PDS), Fe (II)/EDTA (molar ratio), and inorganic salt anions on the degradation of red 4BS were investigated through a UV/Fe (II) - EDTA/PDS (PDS is sodium persulfate) system. The results showed that the decolorization rate of red 4BS increased with the increase of initial c (PDS), When c (PDS) exceeds 15 mmol/L, there is no significant change. The best effect is achieved when the Fe (II)/EDTA ratio is 5:1, and the decolorization rate of 0.0380 mmol/L bright red 4BS reaches 93.6% at 5 minutes. The reaction follows a second-order kinetic model. Inorganic salt anions such as HCO3-, Cl -, NO3-, SO42- exhibit significant inhibitory effects on production. Under 100 mmol/L conditions, the decolorization rate of c (inorganic salt anions) decreases by 66.9%, 13.2%, 12.1%, and 9.43%, respectively. By using UV visible spectroscopy, Based on the relationship between its structure and characteristic absorption, it is preliminarily speculated that the pathway of free radical ions in the degradation of bright red 4BS is the first destruction of the benzene ring, followed by the cleavage of the azo bond and the cracking of the naphthalene ring. Studies have shown that UV light can effectively strengthen the activation of perovsulfate by Fe (II) - EDTA to form SO4- · radicals, which has good decolorization ability for azo dyes. The optimal reaction conditions are [PDS: Fe (II): EDTA (molar ratio 15:5:1)], The decolorization rate of Dahong 4BS is as high as 98.1% at 10 minutes
In recent years, with the continuous growth of China's economy, anthropogenic nitrogen oxide emissions have remained high, leading to increasingly serious regional air pollution in China The NOx emission inventory is of great significance for the study of atmospheric composite pollution. In order to reduce the uncertainty of the NOx emission inventory, based on the concentration data of NO2 column in the troposphere observed by OMI satellite and combined with the WRF-CMAQ model system, the 2014 Yangtze River Delta region NOx emission inventory was verified, and the uncertainty of the inventory was preliminarily evaluated. The results show that based on the 2014 Yangtze River Delta region atmospheric pollutant emission inventory, Using the WRF-CMAQ system to simulate the average concentration of NO2 column in the region (4.66 × 1015-10.58 × 1015 mole/cm2) and OMI satellite data (3.49 × 1015-11.47 × 1015 moles/cm2 is relatively close and has a good correlation (average R=0.65). The normalized mean deviation (NMB) is between -7.71% and 33.52%, and the average deviation (Bias) is between 0.06 and 0.28. This can to some extent indicate that the total NOx emissions in the Yangtze River Delta region in 2014 can basically reflect the regional NO2 pollution situation. A comparative analysis of OMI satellite remote sensing data and CMAQ model simulation results shows that the spatial distribution of NO2 column concentration is generally consistent. However, The NO2 column concentration of OMI satellites in industrial developed areas such as southern Jiangsu, Shanghai, and northern Zhejiang is lower than the simulated value of the CMAQ model, while the OMI satellite data in surrounding economically underdeveloped areas is higher than the simulated value of the CMAQ model, indicating that there is still room for further optimization of spatial distribution. By comparing near-surface satellite observation data with the simulated results of the CMAQ model, near-surface observations can be obtained ρ (NO2) is higher than the simulation results, indicating that there is a certain deviation in verifying the model simulation results solely using ground observation data. Research shows that the simulation results of the NOx emission inventory model are consistent with the OMI satellite data in terms of total amount and time changes, and there is a certain deviation in spatial allocation
Since the first nationwide ground level monitoring of PM2.5 in China in 2013, there have been few studies analyzing the overall spatiotemporal changes of PM2.5 pollution in the past three years at the national spatial scale, identifying the spatial range of PM2.5 pollution exacerbation or mitigation, and lacking direct comparative evaluation of the differences in PM2.5 pollution characteristics changes inside and outside the national key air pollution prevention and control areas. Based on PM2.5 monitoring data from 2013 to 2015, Comprehensively utilizing spatiotemporal statistical analysis and spatial interpolation mapping methods, revealing the past 3 years ρ (PM2.5) and the spatiotemporal variation pattern of pollution days at different levels, with a focus on comparing and analyzing the inside and outside of the "three zones and ten groups" region ρ The difference in changes in (PM2.5). The results show that from 2013 to 2015, there were 335 monitoring stations out of 413 continuously monitored nationwide ρ The average annual concentration of (PM2.5) has decreased, with 218 stations achieving two consecutive years of annual concentration reduction and 74 stations ρ The average annual value of (PM2.5) has been reduced to meet the national second level standard; Most parts of the country ρ The annual exceeding standard rate of (PM2.5) has decreased from over 50% to below 30%, the proportion of heavily polluted sites has decreased from 88.38% to 73.77%, and the proportion of severely polluted sites has decreased from 65.86% to 36.35%; The PM2.5 pollution in the Yangtze River Delta urban agglomeration, Changzhutan urban agglomeration, Wuhan and surrounding urban agglomeration, and Shaanxi Guanzhong urban agglomeration shows a significant improvement trend; Xizang, the Yunnan-Guizhou Plateau, urban agglomeration on the west side of the Straits, Pearl River Delta urban agglomeration and other coastal areas ρ (PM2.5) has been consistently low, with relatively good air quality; However, at the same time, the Beijing Tianjin Hebei urban agglomeration, the Shandong Peninsula urban agglomeration, and the central and northern regions of Henan Province are still areas of heavy PM2.5 pollution in China. New PM2.5 heavy pollution patterns are gradually forming in southwestern Xinjiang, Hefei, Nanchang, and other regions
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