Concentrations Of Major Pollutants Research Articles

Application of photocatalytic and Fenton processes for the degradation of toxic pollutants from pulp and paper industry effluents

Pulp and paper mill effluents contain a range of toxic organic and inorganic pollutants, with the potential for adverse environmental effects even at low concentrations. Currently, the paper production process requires approximately 200 tons of water per ton of paper, and the effluents generated at various stages of manufacturing contain around 250 different chemicals. The pulp and paper (PP) industry is frequently associated with pollution issues, characterized by elevated levels of chemical oxygen demand (COD), total organic carbon (TOC), total suspended solids (TSS), biochemical oxygen demand (BOD), adsorbable organic halides (AOX), toxic dyes, dark liquor, lignin, and chlorinated compounds. Several treatment methods have been proposed to address these pollutants and mitigate the environmental impact of the PP industry. This study aims to evaluate the efficacy of both heterogeneous and homogeneous photocatalytic treatments for PP industry-derived effluents, targeting reductions in major pollutant concentrations (i.e., COD, BOD, lignin, and color) to levels below environmental standards. A review of the literature on the efficiency of pollutant removal from PP effluents using photocatalytic treatment, particularly employing UV/TiO2 and UV/ZnO photocatalysts, revealed substantial removal rates. Specifically, removal rates of 97%, 90%, 96%, and 86% were observed for BOD, COD, color, and lignin, respectively. The use of doped photocatalysts demonstrated enhanced performance, achieving removal percentages of 98% for BOD and COD, and 99% for color and lignin. Furthermore, the application of Fenton and photo-Fenton treatment techniques yielded maximum removal percentages of 87%, 90%, 96%, and 99% for BOD, COD, color, and lignin, respectively.

ESTABLISHMENT OF THE LAWS OF FORMATION AND CHEMICAL COMPOSITION OF WASTEWATER OF A DAIRY PROCESSING PLANT IN THE WESTERN REGION OF UKRAINE

The dairy industry has a wide range of processing end products, which can be conventionally divided into liquid, solid and dry products. The first group includes pasteurized milk, cream and fermented milk drinks (kefir, yoghurt, desserts), the second group includes butter and cheese, the third group includes dry milk (whole or skim), proteins of various composition and purity, casein and whey. The wastewater of a dairy factory is the result of various technological and production processes, which vary in time and, accordingly, their products are not discharged simultaneously, which determines the formation of effluents of different compositions and volumes. Industrial wastewater generated at dairy factories is divided into two types: polluted and partly polluted wastewater. Polluted wastewater is produced after cleaning equipment, industrial pipelines, automobile tanks, floors, industrial premise panels, etc. Partly polluted wastewater is produced as a result of the cooling processes of milk and equipment. Both types of wastewater form a common flow that is subject to cleaning, disinfection and discharge into drainage systems or surface water bodies (depending on the chemical composition).
 The study of the wastewater composition of a dairy processing plant was divided into two stages. At the first stage, the analysis of mixed phases formed during the production process in each section of the factory was carried out.
 The analysis was carried out for one day of production at a dairy factory that processed 496 tons of whole milk, of which 170 tons were used to make whole milk products and cottage cheese, and the rest were used to make butter and casein. At the same time, 1200 m3 of water was used for all production processes, and additional water consumption for auxiliary processes and services amounted to 643 m3, so the total discharge per day was 2000.47 m3.
 The next step was to directly analyse the wastewater indicators of the dairy processing plant. To offset the impact of the production process on the composition of dairy wastewater and the volume of manufactured products, we organized sampling every two hours for four days. As a result, 48 points of analysis were obtained, which allowed us to form an objective assessment of the factory’s discharge.
 As a result of the research, the regularities and sources of formation of wastewater were established, and the chemical composition of wastewater from a dairy processing plant in the Western region of Ukraine was experimentally determined. The results obtained allowed us to draw the following conclusions. The formation of the total runoff is caused by both technological and related processes, which include sudden emissions of highly polluted wastewater with a high concentration of major pollutants, the use of different volumes of water for technological processes, and different volumes and composition of wastewater during the day. Therefore, to correctly assess the composition of a dairy factory's discharge, a systematic and long-term study is required, rather than a spot analysis.
 The chemical composition of wastewater was experimentally studied according to the main indicators regulated by the legislation of Ukraine regarding the discharge of wastewater into the sewage system and municipal biological treatment facilities. The data obtained indicates that the chemical composition of the total wastewater from the dairy processing plant does not meet the requirements. The main pollutants are: organic components, which are expressed in exceeding the chemical oxygen demand on average by three times, and at the peak load - by 10 times; phosphates in terms of total phosphorus - by 8-22 times and chlorides - by 2-7 times.
 A comparative characterization of individual technological stages shows that the most polluted wastewater is generated in the process of acid casein production. These waters are characterized by high values of COD, chlorides and phosphates, and their contribution to the overall value of these indicators is determinant. The production of whole milk products is characterized by a slight excess of COD.
 As a result, in order to prevent the death of activated sludge in municipal biological treatment facilities, pretreatment of wastewater is necessary to bring the above indicators to the norms.
 Key words: dairy industry, dairy processing plant, wastewater, wastewater chemical composition, the Western region of Ukraine.

Spatiotemporal Variation Characteristics of Main Pollutant Fluxes in the Yangtze River Basin from 2017 to 2020

Based on the monitoring data of various pollutants at important water system points in the Yangtze River Basin from 2017 to 2020, research on the flux change law of the main and tributary water systems in the Yangtze River Basin was carried out at the spatiotemporal scale, and the spatial change response, interannual change trend, and flux correlation analysis were analyzed from the aspects of water quantity, quality, and flux so as to reveal the spatial-temporal contribution characteristics of pollutant flux in the upper, middle, and lower reaches of the Yangtze River Basin. The results showed that over the past four years, the concentration of major pollutants in the Yangtze River Basin showed an overall downward trend. The concentration of total phosphorus (TP) and ammonia (NH+4-N) decreased significantly. The concentration of total nitrogen (TN) and total phosphorus (TP) in the main stream gradually increased from west to east. The annual concentration of permanganate index in the upper, middle, and lower reaches decreased by 18.5%, 16.0%, and 14.0%, respectively, from 2017 to 2020, with the highest decline in the upper reaches. The four-year average value of the spatial distribution of runoff significantly increased from 466×108 m3 to 9923×108 m3. The two lake basins in the tributary river lake water system had the largest contribution to the water volume. The fluxes of permanganate index, total phosphorus (TP), and total nitrogen (TN) among the main pollutants showed an annual increase and then decrease trend. The pollutant fluxes in the Minjiang River, Tuojiang River, Jialing River, and the middle reaches of the two lakes contributed greatly to the river inflow. There were differences in fluxes in different regional water environments. The results of correlation and hierarchical cluster analysis showed that the permanganate index and TP fluxes were highly significantly correlated with water volume, and there was a significant correlation between biochemical oxygen demand (BOD5) and total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD). The main pollutants showed strong differences in the flood and non-flood periods and had a significant response in the flood season from July to September. The research results can provide scientific basis and theoretical support for the integrated management and precise prevention and control of the aquatic environment in the Yangtze River Basin.

Environmental consequences of fuel price shocks in China

This study investigates the environmental consequences of fuel price shocks, using a rich dataset from the Chinese megacity of Hangzhou. Our identification strategy is mainly aided by instrumenting fuel price using exogenous global oil prices. We find that a 10% increase in fuel price leads to a 10.29%–11.45% decrease in driving demand, reflected by road congestion index, and a 17.6%–20.27% decrease in industrial activities, measured by electricity consumption. The decreases in driving demand and industrial activities are indeed correlated with air quality improvement and decline in major pollutant concentrations. While the findings shed light on the short-term environmental outcomes of price-based measures, the negative effects of fuel price increases on industrial activities may generate undesirable impacts on macroeconomy in the long-term perspective. Despite ample evidence demonstrating that drivers respond to fuel price changes, considerably fewer studies investigate their environmental and economic consequences. This study addresses this gap in the literature and contributes to a better understanding of the effects of fuel price shocks on air pollution and economic activities.

Impact of the emergency response to COVID-19 on air quality and its policy implications: Evidence from 290 cities in China

The emergency response to the COVID-19 pandemic had an extreme exogenous impact on society and the economy. This paper aims to explore the impacts of the national emergency response and the subsequent emergency response termination on air quality and its policy implications through regression discontinuity design (RDD) estimation by employing panel data on daily air quality from January 1, 2019, to July 31, 2020, for 290 cities in China. The empirical results showed that the emergency response resulted in a significant decrease in most of the major pollutant concentrations within a short time frame, and the average air quality index (AQI) decreased by approximately 11.0%. The concentrations of PM2.5, PM10, SO2, NO2, and CO decreased by approximately 18.8%, 13.1%, 13.5%, 11.1% and 6.7%, respectively, while the O3 concentration did not change significantly. Further causal analysis found that mandatory traffic restrictions and the shutdown of industries were two important factors that contributed greatly to air quality improvement. Moreover, since the process of returning to normal daily activities and promoting the economy were gradual, the results showed that air pollution did not rebound immediately after the government called for the “resumption of production and work” and announced the “termination of the emergency response”. Our findings suggest that to achieve a substantial and sustainable improvement in air quality, it is necessary to continuously implement strict emission control routines and take co-control measures for various VOCs precursors of ozone.

Spatial–Temporal Characteristics and Influencing Mechanisms of Air Quality Index by Considering COVID-19 in Yunnan, Southeastern Tibetan Plateau

Based on the analysis of air quality data in Yunnan Province from 2015 to 2020, combined with spatial interpolation analysis and geographic detector factor analysis, the spatial–temporal evolution characteristics of air quality in Yunnan Province have been studied, and the main driving factors, the mechanisms, and the impact of regional COVID-19 control measures affecting air quality have been discussed. The results show that the air quality in Yunnan Province was generally good (superior rate > 98%) from 2015 to 2020, that the Air Quality Index (AQI) value is better in the wet season than in the dry season, and that the concentration of major pollutants shows a decreasing trend. AQI values are spatially high in the east and low in the west. The relative humidity, precipitation, population density, building construction area, and civil vehicles have a greater degree of explanation for the spatial differentiation of AQI, whereas the synergistic influence (maximum value 0.92) of socio-economic factors and meteorological factors is significantly greater than that of a single factor (maximum value 0.80) by the geographic detector model. The control measures for COVID-19 in 2020 reduced the concentration of major pollutants in the atmosphere to a certain extent. Controlling regional air pollution in urban agglomerations in low-latitude plateau areas can improve their air quality by reducing human activities. However, the control of O3 concentration is more complex, and more restrictive factors need to be considered. The results will provide a scientific basis for the prevention and control of air pollution in plateau cities.

Gaseous and Particulate Pollution in the Wu-Chang-Shi Urban Agglomeration on the Northern Slope of Tianshan Mountains from 2017 to 2021

Rapid social development has led to serious air pollution problems in cities, and air pollutants, including gaseous pollutants and particulate matter, have an important impact on climate, the environment, and human health. This study analyzed the characteristics, potential sources, and causes of air pollution in the Wu-Chang-Shi urban cluster. The results showed that NO2, CO, SO2, PM10, and PM2.5 had a tendency to decrease, while O3 showed an increasing trend. The concentrations of SO2, NO2, CO, PM2.5, and PM10 showed the highest values in winter and the lowest values in summer, with similar seasonal variations. However, the concentration of O3 was highest in the summer and lowest in the winter. Compared with the pollutant concentrations in other Chinese cities, PM2.5, PM10, and NO2 are more polluted in the Wu-Chang-Shi urban. Meteorological factors have a greater impact on pollutant concentrations, with higher concentrations of major pollutants observed when wind speeds are low and specific wind directions are observed, and higher secondary pollutant O3 concentrations observed when wind speeds are low and specific wind directions are observed. The backward trajectory and concentration weighting analysis show that the particulate pollutants in the Wu-Chang-Shi urban in winter mainly come from Central Asia and surrounding cities. O3 showed an increasing trend before and after the novel coronavirus outbreak, which may be related to changes in NOX, volatile organic compounds, and solar radiation intensity, and the concentrations of SO2, NO2, CO, PM10, and PM2.5 showed an overall decreasing trend after the outbreak and was smaller than before the outbreak, which is related to the reduction of industrial and anthropogenic source emissions during the outbreak.

DEFINITION OF NEW ASPECTS OF CHANGING THE ECOLOGICAL STATE OF A SURFACE WATER OBJECT

The article analyzes the qualitative composition of the surface water body, namely the Seym River in Chernihiv and Sumy regions, to determine changes in its ecological status. Possible causes of its pollution have been identified. Statistical and systematic analysis of environmental change was conducted on the basis of the interactive map «Monitoring and Environmental Assessment of Water Resources of Ukraine» of the State Agency of Water Resources of Ukraine in the period from January 2012 to December 2020 based on data from four observation posts of the Seym. The purpose of the study is to identify new temporal and spatial trends in the concentration of major pollutants along the Seym River within Sumy and Chernihiv regions to ensure the possibility of using the results as baseline data in subsequent stages of the study to apply the basin principle of water management. The content of the main indicators was analyzed: polyphosphates, ammonium, nitrates and nitrites, phosphates and sulfates. Data on water intake control from four posts within the Seym River were studied. The increase in the content of ammonium ions every year indicates a deterioration in the sanitary condition of the water in the Seym River. According to the data on biological oxygen consumption in the Seym River, there is a constant deterioration of the oxygen regime at four posts. The increase in nitrate content is associated with an increase in the area of nitrate washout. The decrease in the content of phosphates and sulphates in the Seym River at the observation posts may be due to the fact that the population in the settlements is decreasing every year. From the point of view of basin management, it is expedient to establish an additional point of quality control of water discharges. In the future, the results of the study can be used in the development and implementation of a reliable and effective model for forecasting the ecological status of the Seym River. The results obtained during the study make it possible to state that the ecological condition of the Seyjm River, one of the important tributaries of the Dnieper River, is deteriorating today due to man-made impact. This leads to a deterioration of water quality and the regime of its river runoff.

Restricted Anthropogenic Activities and Improved Urban Air Quality in China: Evidence from Real-Time and Remotely Sensed Datasets Using Air Quality Zonal Modeling

The study aims to examine the major atmospheric air pollutants such as NO2, CO, O3, PM2.5, PM10, and SO2 to assess the overall air quality using air quality zonal modeling of 15 major cities of China before and after the COVID-19 pandemic period. The spatio-temporal changes in NO2 and other atmospheric pollutants exhibited enormous reduction due to the imposition of a nationwide lockdown. The present study used a 10-day as well as 60-day tropospheric column time-average map of NO2 with spatial resolution 0.25 × 0.25° obtained from the Global Modeling and Assimilation Office, NASA. The air quality zonal model was employed to assess the total NO2 load and its change during the pandemic period for each specific region. Ground surface monitoring data for CO, NO2, O3, PM10, PM2.5, and SO2 including Air Quality Index (AQI) were collected from the Ministry of Environmental Protection of China (MEPC). The results from both datasets demonstrated that NO2 has drastically dropped in all the major cities across China. The concentration of CO, PM10, PM2.5, and SO2 demonstrated a decreasing trend whereas the concentration of O3 increased substantially in all cities after the lockdown effect as observed from real-time monitoring data. Because of the complete shutdown of all industrial activities and vehicular movements, the atmosphere experienced a lower concentration of major pollutants that improves the overall air quality. The regulation of anthropogenic activities due to the COVID-19 pandemic has not only contained the spread of the virus but also facilitated the improvement of the overall air quality. Guangzhou (43%), Harbin (42%), Jinan (33%), and Chengdu (32%) have experienced maximum air quality improving rates, whereas Anshan (7%), Lanzhou (17%), and Xian (25%) exhibited less improved AQI among 15 cities of China during the study period. The government needs to establish an environmental policy framework involving central, provincial, and local governments with stringent laws for environmental protection.

Environmental pollution analysis during the lockdown imposed due to COVID-19: A case study

ABSTRACT The Corona Virus Disease of 2019 (COVID-19) pandemic in the year 2020 has become a curse for mankind and their livelihood, and India has not been exempted from it. India currently (August 2020) is among the top five countries in terms of the number of cases and is being reported on a daily basis. This also stems due to India having the world’s second-largest population. The country is being largely run by the informal sector, which has brought the economic sector to a standstill. Essential service sectors such as pharmaceutical, food industry, and logistics are up and running. However, these barely contribute to the country’s economy but have replenished the environment. This manuscript analyzes the environmental effects of enforced lockdown in India on air quality, water quality, and noise levels. In comparison to 2019, levels, air quality, and water quality show positive trends with a reduction in the concentration of major pollutants, such as particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). Parts of the India have witnessed up to 44% reduction in the Air Quality Index. Dissolved oxygen (DO) has increased and biochemical oxygen demand (BOD) has decreased in most of the rivers in the country, enhancing the water quality. The noise levels in different parts of the country have declined during this lockdown period. However, the stockpiling of COVID-19 related biomedical waste and lack of proper handling has raised concerns over the spread of the disease. Thus, the study shows that the nature itself is capable enough to reduce the environmental pollution within a span of months.

Haze Grading Using the Convolutional Neural Networks

As an air pollution phenomenon, haze has become one of the focuses of social discussion. Research into the causes and concentration prediction of haze is significant, forming the basis of haze prevention. The inversion of Aerosol Optical Depth (AOD) based on remote sensing satellite imagery can provide a reference for the concentration of major pollutants in a haze, such as PM2.5 concentration and PM10 concentration. This paper used satellite imagery to study haze problems and chose PM2.5, one of the primary haze pollutants, as the research object. First, we used conventional methods to perform the inversion of AOD on remote sensing images, verifying the correlation between AOD and PM2.5. Subsequently, to simplify the parameter complexity of the traditional inversion method, we proposed using the convolutional neural network instead of the traditional inversion method and constructing a haze level prediction model. Compared with traditional aerosol depth inversion, we found that convolutional neural networks can provide a higher correlation between PM2.5 concentration and satellite imagery through a more simplified satellite image processing process. Thus, it offers the possibility of researching and managing haze problems based on neural networks.

ВЛИЯНИЕ МЕР ПО СДЕРЖИВАНИЮ ПАНДЕМИИ COVID-19 И МЕТЕОРОЛОГИЧЕСКИХ УСЛОВИЙ НА СОСТАВ АТМОСФЕРНОГО ВОЗДУХА В МОСКВЕ В 2020 Г

Changes in the atmospheric composition during different periods of 2020 in Moscow which were associated with the COVID-19 pandemic preventing measures as well as corresponding pollutant emission reduction, are investigated. Surface concentrations of nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), aerosol fraction (PM10), and meteorological parameters during different periods of 2020 were compared with similar data for the previous five years. The analysis of ground-based measurements, as well as of high-resolution satellite distributions of CO and NO2 indicated that the concentration of major pollutants and its spatial distribution in the Moscow region were significantly affected by both restrictive measures and abnormal meteorological conditions in 2020

Impact of COVID-19 Pandemic Preventing Measures and Meteorological Conditions on the Atmospheric Air Composition in Moscow in 2020

Changes in the atmospheric composition during different periods of 2020 in Moscow which were associated with the COVID-19 pandemic preventing measures as well as corresponding pollutant emission reduction, are investigated. Surface concentrations of nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), aerosol fraction (PM10), and meteorological parameters during different periods of 2020 were compared with similar data for the previous five years. The analysis of ground-based measurements, as well as of high-resolution satellite distributions of CO and NO2 indicated that the concentration of major pollutants and its spatial distribution in the Moscow region were significantly affected by both restrictive measures and abnormal meteorological conditions in 2020.

Modeling the quality of sewage during the leaking of stormwater surface runoff to the sanitary sewer system using SWMM: a case study

Abstract This paper describes the application of the storm water management model (SWMM) for predicting the sewage quality in the sanitary sewer system of the study area resulting from the leaking of stormwater surface runoff to the system during rainfall events at different return periods. The concentrations of major pollutants were assessed in the sanitary sewer system at different rainfall intensities. Then, a solution to mitigate the problem was proposed using low impact development (LID) technology. The results of sensitivity analysis indicated that maximum build-up possible was the most sensitive parameter for model calibration. The model was calibrated using actual rainfall events, and statistical validation coefficients of R (0.81–0.82) and NMSE (0.0173–0.022) proved that the model is valid. The sewage quality assessment results showed that pollutants concentration increased to its maximum level at 20 min and gradually decreased to a slightly constant minimum value after 2 h. The proposed solution of LID reduced the pollutants concentrations by 82–88, 75–77, 52–55, and 7–10% for all pollutants at return periods of 2, 5, 10, and 25 years, respectively. To conclude, SWMM simulation successfully predicted the concentration of the pollutants, and leaking of stormwater surface runoff has changed the sewage quality.

Haze-day Trends from 2013 to 2020 and Analysis of Spatiotemporal Characteristics of a Haze Process in Ningbo, China

Air quality in Ningbo continues to improve with a constant decrease in the PM2.5 concentration. However, pollution levels occasionally increase during autumn and winter. To understand the regional and seasonal distributions and the interannual variation during haze days, we analyzed the haze monitoring data from 2013 to 2020 and the haze weather process during January 18–19, 2016. Our results showed a downward trend in the major pollutant concentrations. High PM2.5 concentrations persist in certain areas of Ningbo during winter owing to seasonal haze conditions. However, the annual number of haze days has decreased between 2013 and 2020. Regional variations in pollutant concentrations appear mainly in winter, especially in December and January. The observed concentrations were higher in the north and west, and lower in the south and east. The haze process during January 18–19, 2016, occurred within a height of 0–1.5 km, with high PM2.5 concentrations mainly occurring as small and spherical particles. A higher relative humidity, temperature drop, and stable weather assist in accumulating and sinking pollutants, which cause long-term effects and render diffusion difficult. Although recent national initiatives have been effective, the air quality in northern Ningbo requires further improvement during autumn and winter.

Valuation of Local Demand for Improved Air Quality: The Case of the Mae Moh Coal Mine Site in Thailand

While the district of Mae Moh, Thailand has been well known for its atmospheric pollution associated with coal power production, economic assessment of demand for improved air quality has not been conducted to date. This study estimated local residents’ individual and aggregate willingness to pay (WTP) for mitigation of atmospheric pollution in Mae Moh using the contingent valuation method (CVM), and analyzed the factors associated with the individual WTP using the bivariate tobit and double-hurdle regression techniques. Primary data were collected through face-to-face interviews with a stratified sample of 200 residents. The hypothetical scenarios used in the CVM module were 50% and 80% mitigation of atmospheric concentrations of major pollutants. The weighted average WTP was found to be THB 251.3 and 307.9 per annum (USD 8.4 and 10.3) for the 50% and 80% reduction scenarios, respectively. The aggregate WTP for the entire population of Mae Moh was THB 10,008,733 and 12,264,761 per annum (USD 336,294 and 412,096), respectively. Education, occupation type, income, expenses, satisfaction with ambient quality, and perceived sources of pollution had significant associations with the individual WTP. The paper concludes by discussing policy implications for atmospheric pollution management and avenues for future research.

The effects of COVID-19 pandemic on the air pollutants concentration during the lockdown in Tehran, Iran

In this study, 24-h average concentration of major pollutants, including PM2.5, PM10, NO2, SO2, O3 and CO in the period 1 January to 30 July 2016 to 2020 were investigated to show how partial lockdown affects the behavior of pollutants' concentrations in an urban region. For this purpose, three sites of Aghdasieh, Setad-e Bohran and Shahr-e-Rey, which are located in various parts of Tehran considered. Results showed that PM10 had maximum reduction especially for Aghdasieh and Setad-e Bohran stations (20–30%) compared to the 5-year monthly average. Furthermore, the highest reduction in the Shahr-e-Rey station was related to NO2 (−17.99%). The trend of AQI decreased considerably in 2020 compared to its pre-lockdown values. The relative reduction of AQI in March compared to February was about −12.8%, −27.6%, and −2.27% for Shahr-e-Rey, Aghdasieh, and Setad-e Bohran, respectively. The concentration of pollutants was expected to fall after the lockdown, but it was noted that compared to their average during the 5-year period, the concentrations of all pollutants especially O3 increased to some extent. A major reason for this trend is the removal of the traffic control plan and the increasing use of private vehicles in an effort to implement social distancing.

Estimation of Pollutants’ Emission Rates and Associated Impact on Local Air Quality: A Case Study of Cottage Industry in Ibadan Metropolis

Major urban cities in the developing countries are faced with the peculiar problem of poor air quality, which has resulted into millions of untimely death as well as other adverse environmental impacts including climate change. To combat this negative trend, regular documentation of the emission rates and concentrations of the various air pollutants has been identified as a suitable means of designing a sound mitigation approach. Here, we estimated the emission rates of criteria air pollutants (CAPs) and greenhouse gases (GHGs) generated from an industrial setting; as well as the associated environmental impact on local air quality, using emission inventory methodology and air dispersion model. In the study area, the energy consumption pattern was reported and the emission rates of associated gaseous pollutants were observed to range from 0.22 to 85500 kg/day. Similarly, the concentrations of major pollutants were observed to be within the thresholds stipulated by the World Health Organization.

Co-benefits of carbon and pollution control policies on air quality and health till 2030 in China

Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration–response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM2.5- and O3-related mortality was expected to decline 23% or 289 (95% confidence interval: 220–360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM2.5 exposure under the national air quality standard (35 μg/m3) and WHO guideline (10 μg/m3) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O3 (100 μg/m3). Increased health impact of O3 suggested a great significance of joint control of PM2.5 and O3 in future policy-making.

Municipal wastewater treatment by combining in series microalgae Chlorella sorokiniana and macrophyte Lemna minor: Preliminary results

Conventional treatment of municipal wastewater requires large inputs of energy, and high operation and maintenance costs. On the other hand, the use of microalgae and macrophytes on wastewater treatment offers an alternative approach that combines removal of pollutants with production of valuable biomass. An integrated sequencing batch reactor system that combines in series microalgae Chlorella sorokiniana UTEX 1230 and macrophyte Lemna minor was tested for municipal wastewater treatment in the current study. The average removal of COD, TKN, NH4–N and PO4–P was 99%, 88%, 90% and 91%, respectively, while the concentrations of major pollutants in the effluents complied with European Directive 91/271 for wastewater discharge to the aquatic environment as well as with national legislation for wastewater reuse for limited irrigation. The microalgae reactor was capable of fully removing COD and partially removing N and P nutrients, while Lemna minor reactor contributed mainly to nitrogen removal. Batch experiments with Chlorella sorokiniana and different types of municipal wastewater (raw sewage, anaerobically treated wastewater and aerobically treated wastewater) with no pH adjustment and CO2 addition showed that the optimal microalgae growth and the highest pollutants removal were achieved when raw sewage were used. Comparison of mixotrophic and heterotrophic conditions showed highest biomass growth under mixotrophic conditions. Except for nitrates, the higher removal of other pollutants was also achieved under mixotrophic conditions. Further experiments should be conducted to examine the characteristics of produced microalgae and macrophyte biomass and the alternative ways of their valorization under the frame of circular economy.