In this study, a geographically weighted regression (GWR) approach was adopted to forecast regional concentration of particulate matter 2.5 (PM2.5) for the southern Ontario based on both in situ meteorological measurement and Satellite retrievals of aerosol optical depth (AOD). The correlation between monitored concentration of PM2.5 and Satellite-retrieved AOD would be quantified. The ground-level PM2.5 for South Ontario area was then predicted using GWR with AOD and meteorological variables considered as inputs. The results indicated that performance of GWR was slightly better than the ordinary least squares (OLS) model, indicating spatial variations between independent and dependent variables. Consequently, the GWR model can help us to predict the PM2.5 concentration in terms of time or region with satellite data, and also help improve satellite data inversion.
{"title":"Regional PM2.5 Estimation for Southern Ontario through Geographically Weighted Regression","authors":"K. Huang","doi":"10.3808/jeil.202300100","DOIUrl":"https://doi.org/10.3808/jeil.202300100","url":null,"abstract":"In this study, a geographically weighted regression (GWR) approach was adopted to forecast regional concentration of particulate matter 2.5 (PM2.5) for the southern Ontario based on both in situ meteorological measurement and Satellite retrievals of aerosol optical depth (AOD). The correlation between monitored concentration of PM2.5 and Satellite-retrieved AOD would be quantified. The ground-level PM2.5 for South Ontario area was then predicted using GWR with AOD and meteorological variables considered as inputs. The results indicated that performance of GWR was slightly better than the ordinary least squares (OLS) model, indicating spatial variations between independent and dependent variables. Consequently, the GWR model can help us to predict the PM2.5 concentration in terms of time or region with satellite data, and also help improve satellite data inversion.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115302521","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}
Y. Liu, Xiujuan Chen, H. Wang, Winnipeg Manitoba R P Y Canada Hsbc Bank Canada
. Being the third most significant anthropogenic greenhouse gas, nitrous gas (N 2 O) has 300-fold stronger effect than carbon dioxide (CO 2 ) and 4 ~ 30-fold stronger effect than methane (CH 4 ). In this study, the main sources and mechanisms of N 2 O emission from biological wastewater treatment were reviewed, and the possible mitigation strategies were discussed. Parameters including dissolved oxygen, temperature, pH, organic carbon, and nitrite concentration have influences on the emission of N 2 O. The possible mitigation strategies were put forward by controlling these parameters in biological wastewater treatment and inducing modified technologies such as simultaneous nitrification-denitrification, denitrifying phosphorus removal, and aerobic granular sludge. In order to obtain a near-zero N 2 O emission, applying typical catalysts in the nitrification or denitrification tank to decompose N 2 O into harmless gas is recommended. Moreover, a method of developing photochemical processes to transform N 2 O could also be suggested.
{"title":"Perspective for Emission and Control of Nitrous Gas in Biological Wastewater Treatment","authors":"Y. Liu, Xiujuan Chen, H. Wang, Winnipeg Manitoba R P Y Canada Hsbc Bank Canada","doi":"10.3808/jeil.201900020","DOIUrl":"https://doi.org/10.3808/jeil.201900020","url":null,"abstract":". Being the third most significant anthropogenic greenhouse gas, nitrous gas (N 2 O) has 300-fold stronger effect than carbon dioxide (CO 2 ) and 4 ~ 30-fold stronger effect than methane (CH 4 ). In this study, the main sources and mechanisms of N 2 O emission from biological wastewater treatment were reviewed, and the possible mitigation strategies were discussed. Parameters including dissolved oxygen, temperature, pH, organic carbon, and nitrite concentration have influences on the emission of N 2 O. The possible mitigation strategies were put forward by controlling these parameters in biological wastewater treatment and inducing modified technologies such as simultaneous nitrification-denitrification, denitrifying phosphorus removal, and aerobic granular sludge. In order to obtain a near-zero N 2 O emission, applying typical catalysts in the nitrification or denitrification tank to decompose N 2 O into harmless gas is recommended. Moreover, a method of developing photochemical processes to transform N 2 O could also be suggested.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126034213","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}
{"title":"Research Progress on the Land Application of Tannery Sludge","authors":"K. Xu, C. Wu","doi":"10.3808/jeil.202100076","DOIUrl":"https://doi.org/10.3808/jeil.202100076","url":null,"abstract":"","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125890387","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}
Scarcity of water resource recommended developing innovative technology to reclaim wastewater. Greywater is an appropriate source to reuse through advanced treatment. Meanwhile, MBRs are novel techniques to reclaim wastewater, which are composed of activated sludge processes and membrane filtration. Characteristic and application of Hybrid MBR, MBMBR and OMBR were reviewed in this article. And sources, analysis methods and controlling methods of biofouling resulted from extracellular polymeric substances and soluble microbial products were also discussed. According to a detailed analysis of research publications, MBRs are promising techniques to reclaim wastewater.
{"title":"Review on Membrane Biofouling Occurring in MBR and Its Related Technologies for Greywater or Wastewater Treatment","authors":"P. Zhang, S. Young, W. Huang","doi":"10.3808/jeil.202300101","DOIUrl":"https://doi.org/10.3808/jeil.202300101","url":null,"abstract":"Scarcity of water resource recommended developing innovative technology to reclaim wastewater. Greywater is an appropriate source to reuse through advanced treatment. Meanwhile, MBRs are novel techniques to reclaim wastewater, which are composed of activated sludge processes and membrane filtration. Characteristic and application of Hybrid MBR, MBMBR and OMBR were reviewed in this article. And sources, analysis methods and controlling methods of biofouling resulted from extracellular polymeric substances and soluble microbial products were also discussed. According to a detailed analysis of research publications, MBRs are promising techniques to reclaim wastewater.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130717834","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}
W. D. Kirkey, C. B. Fuller, P. O’Brien, P. J. Kirkey, A. Mahmoud, A. N. Ernest, J. Guerrero
. A system comprised of software and on-site measurements is presented for accurately obtaining water stage data from vented or non-vented submersible pressure sensors installed at autonomous stream gauging stations. The system accounts for pressure sensor offset errors, water density, and local gravitational acceleration to produce a stage height reading which is accurate to either ±0.01 ft (±3 mm) or to the accuracy limit of the sensor, whichever is greater. A 2 nd order polynomial expression for determination of water density from temperature and salinity is developed and found to be sufficiently accurate for this purpose. Simulated stage measurements performed in the laboratory with a commercially produced sensor showed errors of up to ±0.04 ft in reported stage when the sensor’s default conversion from pressure to depth was used; the maximum error limit was reduced to ±0.02 ft when the sensor output was instead processed using the new system. A custom-designed, low-cost, versatile submersible pressure sensor is introduced and tested under the same conditions and found to exhibit a maximum error of ±0.04 ft without any sensor calibration. These new developments, integrated into previously developed inexpensive base stations, enable accurate monitoring of stage height at remote locations with low installation and operating costs.
{"title":"River & Estuary Observation Network: Refinement of Stage Height Sensor Subsystem for Low Cost and High Reliability","authors":"W. D. Kirkey, C. B. Fuller, P. O’Brien, P. J. Kirkey, A. Mahmoud, A. N. Ernest, J. Guerrero","doi":"10.3808/JEIL.202000045","DOIUrl":"https://doi.org/10.3808/JEIL.202000045","url":null,"abstract":". A system comprised of software and on-site measurements is presented for accurately obtaining water stage data from vented or non-vented submersible pressure sensors installed at autonomous stream gauging stations. The system accounts for pressure sensor offset errors, water density, and local gravitational acceleration to produce a stage height reading which is accurate to either ±0.01 ft (±3 mm) or to the accuracy limit of the sensor, whichever is greater. A 2 nd order polynomial expression for determination of water density from temperature and salinity is developed and found to be sufficiently accurate for this purpose. Simulated stage measurements performed in the laboratory with a commercially produced sensor showed errors of up to ±0.04 ft in reported stage when the sensor’s default conversion from pressure to depth was used; the maximum error limit was reduced to ±0.02 ft when the sensor output was instead processed using the new system. A custom-designed, low-cost, versatile submersible pressure sensor is introduced and tested under the same conditions and found to exhibit a maximum error of ±0.04 ft without any sensor calibration. These new developments, integrated into previously developed inexpensive base stations, enable accurate monitoring of stage height at remote locations with low installation and operating costs.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129576631","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}
{"title":"Response of Surface Water Quality in Urban and Non-urban Areas to Heavy Rainfall: Implications for the Impacts of Climate Change","authors":"Q. Wu, X. Xia","doi":"10.3808/JEIL.201900004","DOIUrl":"https://doi.org/10.3808/JEIL.201900004","url":null,"abstract":"","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127881376","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}
{"title":"Gauging the Effects of Potential Chemical Transferal on High Flood-Risk Fenceline Communities","authors":"G. Newman, Z. Cai, R. Zhu, J. Horney, W. Chiu","doi":"10.3808/jeil.202100073","DOIUrl":"https://doi.org/10.3808/jeil.202100073","url":null,"abstract":"","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131235316","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}
With the rapid development of Central China, the temperature in this region is continuously increasing. Extreme weather events (e.g., high-temperature weather for many consecutive days) are becoming frequent. In order to provide future theoretical guidance on the direction of local development and the prevention of extreme natural disasters, the daily datasets of 12 meteorological stations in three provinces were collected. The corresponding predictors from 25 large-scale climatic factors were then screened using stepwise regression. A stepwise regression and statistical downscaling (SRSD) approach was developed to establish the statistical relationship. The future temperature results were projected by the weather generator, and the probability of extreme weather occurrence was analyzed by extreme values. The results indicate that future temperature in Central China shows an increasing trend from 2036 to 2065 and 2066 to 2095, with the representative concentration pathway 4.5 (RCP4.5) scenario showing a greater increase in temperature than the representative concentration pathway 8.5 (RCP8.5) scenario. Hunan Province has the largest temperature increase, followed by Hubei Province and Henan Province. The average annual duration of heat waves in Central China is 74.7 days.
{"title":"A Stepwise Regression and Statistical Downscaling Approach for Projecting Temperature Variations under Multiple RCP Scenarios","authors":"X. Huang, Xiaoping Zhou, G. Huang, Y. Li, Y. Li","doi":"10.3808/jeil.202300096","DOIUrl":"https://doi.org/10.3808/jeil.202300096","url":null,"abstract":"With the rapid development of Central China, the temperature in this region is continuously increasing. Extreme weather events (e.g., high-temperature weather for many consecutive days) are becoming frequent. In order to provide future theoretical guidance on the direction of local development and the prevention of extreme natural disasters, the daily datasets of 12 meteorological stations in three provinces were collected. The corresponding predictors from 25 large-scale climatic factors were then screened using stepwise regression. A stepwise regression and statistical downscaling (SRSD) approach was developed to establish the statistical relationship. The future temperature results were projected by the weather generator, and the probability of extreme weather occurrence was analyzed by extreme values. The results indicate that future temperature in Central China shows an increasing trend from 2036 to 2065 and 2066 to 2095, with the representative concentration pathway 4.5 (RCP4.5) scenario showing a greater increase in temperature than the representative concentration pathway 8.5 (RCP8.5) scenario. Hunan Province has the largest temperature increase, followed by Hubei Province and Henan Province. The average annual duration of heat waves in Central China is 74.7 days.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121196719","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}
Hydrodesulfurization (HDS) plays a vital role in the production of clean fuels when more stringent environmental legislation forces the sulfur content in fuels to an ultra-low level. There are two alternative approaches for producing ultra-low sulfur diesel (ULSD) in a cost-effective way, including the activity improvement of HDS catalysts and the optimization of the operating conditions in HDS reactions. In this study, the activity improvement of HDS catalysts was first examined, and then the optimization of operational conditions was further explored to gain the ULSD in a cost-effective way. In detail, the catalysts were improved through optimizing the ratio between active metal (Mo) and promoter (Co) based on the MgO-Al2O3 as support. Precursors of the improved oxide catalysts and sulfide catalysts were characterized by various techniques, and the catalytic performances were further evaluated in the hydrodesulfurization of dibenzothiophene. Catalysts with the best catalytic performance were chosen to optimize the reaction conditions. Results show that the optimal amounts of catalysts were 4 wt.% of MoO3 and combined with 2 wt.% of CoO. Moreover, the optimal reaction conditions were reaction temperature of 240 °C, total reaction pressure of 4.0 MPa, the hydrogen-to-oil volume ratio of 300, and LHSV of 2.0 h−1. Under the optimal reaction condition, the desulfurization rate could reach to 99.8%.
{"title":"CoMo/Al2O3-MgO Supported Catalysts: Improvement of Hydrodesulfurization Activity and Optimization of Operational Processing","authors":"X. Zheng, Y. Yue","doi":"10.3808/jeil.202200085","DOIUrl":"https://doi.org/10.3808/jeil.202200085","url":null,"abstract":"Hydrodesulfurization (HDS) plays a vital role in the production of clean fuels when more stringent environmental legislation forces the sulfur content in fuels to an ultra-low level. There are two alternative approaches for producing ultra-low sulfur diesel (ULSD) in a cost-effective way, including the activity improvement of HDS catalysts and the optimization of the operating conditions in HDS reactions. In this study, the activity improvement of HDS catalysts was first examined, and then the optimization of operational conditions was further explored to gain the ULSD in a cost-effective way. In detail, the catalysts were improved through optimizing the ratio between active metal (Mo) and promoter (Co) based on the MgO-Al2O3 as support. Precursors of the improved oxide catalysts and sulfide catalysts were characterized by various techniques, and the catalytic performances were further evaluated in the hydrodesulfurization of dibenzothiophene. Catalysts with the best catalytic performance were chosen to optimize the reaction conditions. Results show that the optimal amounts of catalysts were 4 wt.% of MoO3 and combined with 2 wt.% of CoO. Moreover, the optimal reaction conditions were reaction temperature of 240 °C, total reaction pressure of 4.0 MPa, the hydrogen-to-oil volume ratio of 300, and LHSV of 2.0 h−1. Under the optimal reaction condition, the desulfurization rate could reach to 99.8%.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115927412","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}
Evaluation of water pollution is a priority work nowadays. The signature of the waterbody reveals its excellence or mediocrity and reflectance that can measure by a sensor used to analyse the health status of the waterbody. The remote sensing analysis has become the latest state of art technologies for monitoring large-scale waterbodies. High-resolution satellite data are now available to estimate water pollution through various water quality parameters like clarity, chlorophyll, suspended solids, turbidity, temperature, salinity, organic matter, etc. In this review study, a special emphasise has been given to the various satellites like Landsat, sentinel, satellite pourl’Observation de la terre (SPOT), moderate resolution imaging spectroradiometer (MODIS), medium resolution imaging spectrometer (MERIS), Indian remote sensing satellites (IRS) and its application on water pollution. Availability of satellite data, algorithms, and models to assess water quality has also been reviewed in detailed. The review suggests development and innovation in satellites, sensors and techniques to assess the non-optically active constituents of water quality for better understanding and management of water pollution.
{"title":"Application of Satellite Data on Water Pollution: An Intensive Review","authors":"J. Dey, R. Vijay","doi":"10.3808/jeil.202200084","DOIUrl":"https://doi.org/10.3808/jeil.202200084","url":null,"abstract":"Evaluation of water pollution is a priority work nowadays. The signature of the waterbody reveals its excellence or mediocrity and reflectance that can measure by a sensor used to analyse the health status of the waterbody. The remote sensing analysis has become the latest state of art technologies for monitoring large-scale waterbodies. High-resolution satellite data are now available to estimate water pollution through various water quality parameters like clarity, chlorophyll, suspended solids, turbidity, temperature, salinity, organic matter, etc. In this review study, a special emphasise has been given to the various satellites like Landsat, sentinel, satellite pourl’Observation de la terre (SPOT), moderate resolution imaging spectroradiometer (MODIS), medium resolution imaging spectrometer (MERIS), Indian remote sensing satellites (IRS) and its application on water pollution. Availability of satellite data, algorithms, and models to assess water quality has also been reviewed in detailed. The review suggests development and innovation in satellites, sensors and techniques to assess the non-optically active constituents of water quality for better understanding and management of water pollution.","PeriodicalId":143718,"journal":{"name":"Journal of Environmental Informatics Letters","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115192448","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}
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