Pollution Control Strategies Research Articles

Abundant oxygenated volatile organic compounds and their contribution to photochemical pollution in subtropical Hong Kong

Volatile organic compounds (VOCs), which are ubiquitous pollutants in the urban and regional atmosphere, promote the formation of ozone (O3) and secondary organic aerosols, thereby significantly affecting the air quality and human health. The ambient VOCs at a coastal suburban site in Hong Kong were continuously measured using proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) from November 2020 to December 2020. 83 VOC species, including 23 CxHy, 53 CxHyO1-3, and 7 nitrogen-containing species, were measured during the campaign, with a mean concentration of 36.75 ppb. Oxygenated VOCs (OVOCs) accounted for most (77.4%) of the measured species, including CxHyO1 (50.7%) and CxHyO2 (25.1%). The measured VOC species exhibited distinct temporal and diurnal variations. High concentrations of isoprene and OVOCs were measured in autumn with more active photochemistry, whereas large evening peaks of aromatics from local and regional primary emissions were prominent in winter. The OH reactivity and O3 formation potential (OFP) of key precursors were quantified. OVOCs contributed about half of the total OH reactivity and OFP, followed by alkenes and aromatics, and the contribution of aromatics increased significantly in winter. The potential source contribution function was used to investigate the potential source regions associated with high VOC concentrations. Through positive matrix factorization analysis, six major sources were identified based on fingerprint molecules. The contributions of biogenic sources and secondary formation to the observed species were notable in late autumn, whereas vehicle emissions and solid fuel combustion had higher contributions in winter. The findings highlight the important role of OVOCs in photochemical pollution and provide valuable insights for the development of effective pollution control strategies.

System Dynamics Modeling for Effective Strategies in Water Pollution Control: Insights and Applications

Water pollution is a significant environmental challenge with implications for both the natural world and human well-being. To better understand and manage the complex interactions within water pollution systems, such as waste dumping in the sea, system dynamics modeling has emerged as a valuable tool. This simulation-based approach employs feedback loops and cause-and-effect relationships to capture the dynamic behavior of such systems over time. By simulating various waste disposal scenarios and assessing their impacts on the environment and human health, system dynamics modeling aids policymakers and waste managers in devising effective strategies for the sustainable management of dumping sites into the sea. In this manuscript, we present a system dynamics approach to model water pollution control. Our study entails the development of a conceptual model that encompasses pollution sources, pollutant transport and fate, and their effects on water quality and human health. By calibrating and validating the model using data from a case study in Charleston Harbor, South Carolina, United States, we ensure its accuracy and reliability. The results highlight the model’s versatility in simulating different pollution control scenarios, particularly those involving dredging discharge and powerhouse effluent. Through these simulations, we gain valuable insights into the potential impacts of various pollution control measures on water pollution dynamics. Our research underscores the significance of system dynamics modeling in comprehending intricate water pollution systems, including those associated with waste dumping in the sea. By identifying effective strategies for water pollution control, this approach offers invaluable support in safeguarding marine ecosystems and human communities. In conclusion, system dynamics modeling proves to be a powerful tool for sustainable water pollution management. This research demonstrates its utility in analyzing dumping sites in the sea and provides essential findings to inform effective pollution control strategies. Emphasizing the broader context of water pollution, this study contributes to advancing knowledge and fostering sustainable practices to protect our precious water resources.

Prevalence of antibiotic-resistant Gram-negative bacteria having extended-spectrum β-lactamase phenotypes in polluted irrigation-purpose wastewaters from Indian agro-ecosystems.

Antibiotic resistance in bacteria has emerged as a serious public health threat worldwide. Aquatic environments including irrigation-purpose wastewaters facilitate the emergence and transmission of antibiotic-resistant bacteria and antibiotic resistance genes leading to detrimental effects on human health and environment sustainability. Considering the paramount threat of ever-increasing antibiotic resistance to human health, there is an urgent need for continuous environmental monitoring of antibiotic-resistant bacteria and antibiotic resistance genes in wastewater being used for irrigation in Indian agro-ecosystems. In this study, the prevalence of antibiotic resistance in Gram-negative bacteria isolated from irrigation-purpose wastewater samples from Sirmaur and Solan districts of Himachal Pradesh was determined. Bacterial isolates of genera Escherichia, Enterobacter, Hafnia, Shigella, Citrobacter, and Klebsiella obtained from 11 different geographical locations were found to exhibit resistance against ampicillin, amoxyclav, cefotaxime, co-trimoxazole, tobramycin, cefpodoxime and ceftazidime. However, all the isolates were sensitive to aminoglycoside antibiotic gentamicin. Enterobacter spp. and Escherichia coli showed predominance among all the isolates. Multidrug-resistance phenotype was observed with isolate AUK-06 (Enterobacter sp.) which exhibited resistant to five antibiotics. Isolate AUK-02 and AUK-09, both E. coli strains showed resistant phenotypes to four antibiotics each. Phenotypic detection revealed that six isolates were positive for extended-spectrum β-lactamases which includes two isolates from Enterobacter spp. and E. coli each and one each from Shigella sp. and Citrobacter sp. Overall, the findings revealed the occurrence of antibiotic resistant and ESBL-positive bacterial isolates in wastewaters utilized for irrigation purpose in the study area and necessitate continuous monitoring and precautionary interventions. The outcomes of the study would be of significant clinical, epidemiological, and agro-environmental importance in designing effective wastewater management and environmental pollution control strategies.

Seasonal Variation and Source Identification of PM10 in an Industrialized City

AbstractA 1‐year PM10 sampling campaign from January 2019 to December 2019 is conducted in an urban industrial area Raipur, India. For the development of effective pollution control strategies, quantitative assessment of potentially toxic metals and accurate identification of pollutant sources are essential. The annual average PM10 aerosol mass concentration during the study period is recorded as 187.89 ± 91 µg m−3. PM10 concentrations are found to vary with meteorological parameters such as wind speed, temperature, rainfall, and humidity. Heavy metals including Fe, Mn, Ni, Pb, Zn, Al, Ba, Cr, Sr, Ga, Mg, and V are studied using atomic absorption spectroscopy (AAS). Seasonally, average winter time PM10 concentration (234.86 ± 104.3 µg m−3) is accounted higher as compared to summer (169.02 ± 27.1 µg m−3) and rainy season (106.28 ± 32.6 µg m−3) during the study period. The aerosol sources identified by positive matrix factorization (PMF) model are: iron and steel production (34.7%), vehicular emissions (29.3%), road dust (14.6%), heavy oil/petroleum (14.6%), and coal combustion (6.9%). Among these sources, iron and steel production contributes maximum in PM10 concentrations. The probable source locations are recognized through concentration weighted trajectory (CWT) analysis. The AirQ+ model is used to assess the health effects of regional PM10 concentrations.

Effects of Dissolved Organic Matter on the Release of Soluble Phosphorus and Fluoride Ion from Phosphate Ore

Unreasonable storage of phosphate ore is becoming an important pathway causing phosphate pollution in the surrounding aquatic environment. However, there is little research on the influence of dissolved organic matter (DOM) in water on the fate of phosphate ore. Here, we collected phosphate ores from two phosphate mines along the coast of Tanglang River and studied the effects of DOM concentrations and pH on the release of soluble active phosphorus (SRP) and fluoride ion (F−) from phosphate ores using humic acid (HA) as the representative of DOM. Based on the analysis of ZP, FTIR, XPS, and SEM, the influence mechanism of HA was revealed. The results showed that HA efficiently promoted the release of SRP and F− from phosphate ore. With decreasing pH, the P release increased in both water and HA solutions in general. The beneficial influence of HA on the release of SRP and F− from phosphate ore was ascribed to the introduction of oxygen-containing functional groups by HA, which altered the surface properties and enhanced the dispersion stability of phosphate ore. These findings provided new insights into the dispersion behavior of phosphate ore, which is helpful in promoting the pollution control and management strategy of phosphate ore.

Accurate particulate matter emission measurements from biomass combustion: A holistic evaluation of full and partial flow dilution systems

Accurately measuring particulate matter emissions from biomass combustion is crucial for evaluating the performance of fuels, combustion appliances and flue gas cleaning methods. These measurements are essential for refining emission inventories for health risk assessments and environmental models and for defining pollution control strategies. However, as air quality standards become increasingly stringent and emission levels decrease, it is important to develop reliable, accurate measurement methods. This study presents a comprehensive evaluation of two particulate dilution systems, namely a full flow dilution (FFD) tunnel and a two-stage partial flow dilution system (porous tube diluter combined with ejector diluter, PTD + ED), for characterising the particle number size distribution from a wood pellet boiler. The maximum relative sampling errors due to not sampling isokinetically increase with particle size and dilution ratio (DR), but are less than 1% for particles smaller than 1 μm for both systems. The total particle number concentration with FFD is on average 35% lower than with PTD + ED, which suggests substantial particle loss during FFD. In addition with FFD, a strong negative correlation is observed between DR and the average particle size. On the other hand with PTD + ED, both the dilution air temperature and DR have no substantial influence on the particle number emissions. However, it is observed with both systems that the particle distribution is affected by coagulation, and this effect becomes more pronounced as dilution decreases. Overall, this work provides insights into the strengths and limitations of particulate dilution systems for accurately measuring emissions from biomass combustion, which can support the development of more reliable measurement methods and assist in implementing effective pollution control strategies.

Seasonal and regional variations of atmospheric ammonia across the South Korean Peninsula

This study aimed to identify the factors causing NH3 emissions in the South Korean Peninsula and West Sea region. To analyze the trends of NH3 and other air pollutants, such as NOx, CO, and NR-PM1, we collected samples from six supersites across the peninsula, a roadside in Seoul, and the West Sea over different sampling periods, ranging from 1 month to 1 year. The highest NH3 concentrations were found at rural areas, ascribed to agricultural activities, particularly NH4NO3 decomposition at high summer temperatures. Areas with low population densities recorded the lowest NH3 concentrations, attributed to the lack of anthropogenic activities. A roadside field experiment confirmed the close link between ambient NH3 and vehicle emissions in urban regions by showing a strong correlation between CO and NOx concentrations and that of NH3. Moreover, we examined oceanic emissions near the eastern coast of South Korea in the West Sea. Long-range transportation studies confirmed that most of the pollutants (NH3, CO, and PM1) were transported by wind from the northeastern region of China. A maritime origin study showed that oceanic emissions and NH4NO3 decomposition in the atmosphere owing to high temperatures were the causing NH3 pollution. These findings provided valuable insights into the emission sources of NH3 in primary air pollutants in South Korea, highlighting the contributions of land-based and oceanic sources. Our study can help inform policymakers and stakeholders for developing effective regional air pollution control strategies.

Estrogens and xenoestrogen residues in manure-based fertilizers and their potential ecological risks

Optimal manure treatment aimed at usage as agricultural soil fertilizers is a prerequisite ecological pollution control strategy. In this work, livestock manure-based fertilizers were collected from 71 animal farms across 14 provinces in China. The contamination levels and potential ecotoxicological risks of residual steroid estrogens (SEs): estrone (E1), estriol (E3), 17α-estradiol (17α-E2), 17β-estradiol (17β-E2) and xenoestrogen (XE) bisphenol A (BPA), were investigated. The results showed that the occurrence frequencies for SEs and XE ranged from 66.67% to 100%, and the mean concentration varied considerably across the study locations. The total content of SEs and XE in Hebei province was the highest, and swine manure-based fertilizers concentrations were higher than the levels reported in other animal fertilizers. Compared with farm level manure, manure-based fertilizers are processed by composting, and the micropollutants quantities are significantly reduced (mean: 87.65 – 534.02 μg/kg). The total estradiol equivalent quantity (EEQ) that might migrate to the soil was estimated to be 1.23 μg/kg. Based on the estimated application rate of manure, 38% of the fertilizers risk quotients exceeded 0.1, indicating medium to high risks pressure on terrestrial organisms. Nonetheless, the estrogenic risk was lower in manure-based fertilizers than in manure. This study highlights the significance of proper treatment of livestock manure and designing an optimal manure fertilization strategy to mitigate the risks posed by SEs and XEs to the agroecosystems.

Impact of Cement Industry on Water Quality in the Athi River, Machakos County, Kenya

Cement is one of the most often used building materials and its production is increasing globally. Simultaneously, cement production is energy intensive and produces harmful emissions such as gases, noise, and wastewater. The aim of the study was to determine the impact of the cement industry on water quality in Athi River, Kenya. The cement industry had significant impacts on water physicochemical variables such as temperature (p = 0.0003), conductivity (p = <0.001), total suspended solids (p = <0.001), ammonium (p = 0.04), pH (p = 0.02), and turbidity (p = 0.0001). Mean values for physicochemical variables such as conductivity, total suspended solids, total dissolved solids, turbidity, and lead exceeded the limits set by World Health Organization (WHO) for drinking water quality. Water pollution control strategies need to be implemented to improve water quality in the Athi River and prevent further deterioration of the environment. Future studies should evaluate the effect of the cement industry on other water resources (e.g., groundwater) and air quality

An integrated approach using multi-source data for effective pollution risk monitoring of urban rivers: a case study of Hangzhou.

With the rapid urbanization of cities, water pollution has emerged as a major challenge to their sustainable development. To tackle this problem, we developed a river pollution risk management system that integrates multi-source data and includes risk identification, early warning, and control. We applied this system to a case study of urban rivers in Hangzhou, China. The results indicated that the measured and effect values of urban river water quality in Hangzhou were 1.01 and 1.14, respectively, indicating mild pollution levels. NH3-N is the main risk factor, with poor supervision and land use being the main risk sources. River pollution risk in different drainage zones demonstrated stratification. Since 2012, the measured risk of water quality in Hangzhou has been decreasing, mainly concentrated in the built-up area; however, the effect risk has been increasing, especially in the new center and sub-center of the city. Based on these findings, three strategies for urban river pollution control are suggested: water ecology source rehabilitation, water environment process supervision, and water pollution end management. The results of this study extend the understanding of urban water environment risk and provide implications for sustainable urban planning.

Modelling optimal control of air pollution to reduce respiratory diseases

Respiratory diseases caused by inhalation of air pollutants are affected by seasonal changes and mitigated by air pollution control, resulting in complex dynamics. In order to investigate the effects of various factors such as random noise and air pollution control on respiratory diseases, we developed deterministic and stochastic two-dimensional coupled SIS models with multiple control measures. The proposed models and parameter estimation methods, including determinations of unknown parameter values, were used to fit the Air Quality Index (AQI) data for Xi’an city in recent 10 years. The existence of the optimal solutions for the deterministic and stochastic models were analyzed theoretically and provided to compare the parameter fitting solutions with the optimal solutions, and give theoretical support for seeking a more reasonable air pollution optimization prevention and control scheme. To show this, we conducted numerical simulations of the optimal control solution and state evolution trajectories under different weight coefficient ratios and control objectives. The results show that the stochastic optimal control problem is more consistent with the practical scenario. We also formulate the optimal control problem assuming that the control variable depends on the concentration of air pollutants. The optimal control solution reflected the periodic variation of the air pollution control strategy well. A comparison of cost values for different combinations of the three control measures illustrated that air pollution reduction is the most effective control measure.

Geochemical factors controlling the mobilization of geogenic cadmium in soils developed on carbonate bedrocks in Southwest China

Soils developed on carbonate bedrocks commonly contain high contents of geogenic cadmium (Cd). The bioavailability of Cd greatly varies among such soils and tends to be elevated in paddy soils compared to upland soils. However, the factors controlling the mobilization of geogenic Cd in paddy soils remain unclear. Therefore, this study aimed to reveal the processes and influencing factors of Cd mobilization in soils, by collecting upland soils and paddy soils from a carbonate region in Southwest China and analyzing the integrated soil properties and content, speciation and bioavailability of Cd. The results showed that the in-situ weathering of Cd-rich limestone (average of 0.66 mg/kg) resulted in the enrichment of Cd in overlying soils (4.75 to 13.2 mg/kg). Based on sequential extraction, ∼43%, 18% and 17% of Cd in paddy soils was retained by Mn oxides, Fe oxides and the residual fraction, respectively. Hence, the transformation of Mn oxides drove the redistribution of Cd. In the upper layers, Cd released from Mn oxides was sequestered by soil organic matter and carbonate. Based on extraction using diethylene triamine pentaacetic acid (DTPA), paddy soils presented a higher Cd bioavailability (27%) than upland soils (18%). Furthermore, both the bioavailability and mobility of Cd gradually increased toward the surface in the profiles. The bioavailability of Cd was significantly correlated with the content of soil organic matter in these soils, indicating that soil organic matter was another crucial factor controlling Cd mobilization in paddy soils. The outcomes of this study provided new evidence for understanding the mobilization of Cd in soils and are helpful for developing pollution-control strategies to combat geogenic Cd in paddy soils in carbonate regions.

Estimation of Cropland Nitrogen Runoff Loss Loads in the Yangtze River Basin Based on the Machine Learning Approaches

A quantitative understanding of cropland nitrogen (N) runoff loss is critical for developing efficient N pollution control strategies. Using correlation analysis, a structural equation model, variance decomposition, and machine learning methods, this study identified the primary influencing factors of total N (TN) runoff loss from uplands (n=570) and paddy (n=434) fields in the Yangtze River Basin (YRB) and then developed a machine learning-based prediction model to quantify cropland N runoff loss load. The results indicated that runoff depth, soil N content, and fertilizer addition rate were the major influencing factors of TN runoff loss from uplands, whereas TN runoff loss rate from paddy fields was mainly regulated by runoff depth and fertilizer addition rate. Among the four used machine learning methods, the prediction models based on the random forest algorithm presented the highest accuracy (R2=0.65-0.94) for predicting upland and paddy field TN runoff loss rates. The random forest algorithm based model estimated a total cropland TN loss load in the YRB of 0.47 Tg·a-1 (upland:0.25 Tg·a-1; paddy field:0.22 Tg·a-1) in 2013, with 58% of TN runoff loss load derived from the midstream and downstream regions. The models predicted that TN runoff loss loads from croplands in YRB would decrease by 2.4%-9.3% for five scenarios, with higher TN load reductions occurring from scenarios with decreased runoff amounts. To mitigate cropland N nonpoint source pollution in YRB, it is essential to integrate efficient water, fertilizer, and soil nutrient managements as well as to consider the midstream and downstream regions as the high priority area. The machine learning-based modeling method developed in this study overcame the difficulty of identifying the functional relationships between cropland TN loss rate and multiple influencing factors in developing relevant prediction models, providing a reliable method for estimating regional and watershed cropland TN loss load.

Simulation of Pollution Apportionment and Optimization of Control Methods in Watershed Scale: A Case Study of the Shun'an Watershed in Tongling City

The protection of the Yangtze River is an important national strategy in China, but it faces many problems such as difficult water environment protection, unclear pollution sources, and low integration of measures. Aimed at addressing watershed scale multi-source pollution together with facing the bottleneck method, by combining research data analysis, mechanism model, and intelligent algorithm optimization, this study built the framework for accurate pollution apportionment, measures evaluation, and overall measure optimization. Shun'an watershed in Tongling City of Anhui Province was set as an example for the application. The results showed that the new method could accurately quantify the impacts of planting industry, rural life, livestock and poultry breeding, aquaculture, industrial sewage, and domestic sewage in the watershed and evaluate the overall effects of various measures. The multi-objective optimization algorithm provided a cooperative multi-source pollution control scheme with higher cost performance and better environmental benefit by comparing the cost effectiveness of various schemes systematically. The optimization scheme showed that total nitrogen could be reduced by 1274.24 t·a-1 in wet years, 855.24 t·a-1 in normal years, and 381.96 t·a-1 in dry years. Total phosphorus was reduced by 321.42 t·a-1 in wet years, 159.80 t·a-1 in normal years, and 42.93 t·a-1 in dry years, such that the water quality reached the surface class Ⅲ water quality standard. These research results can be extended to other watersheds and provide a method reference for water environment protection under the background of the high-quality development of watersheds.

Source apportionment of heavy metal(loid)s in sediments of a typical karst mountain drinking-water reservoir and the associated risk assessment based on chemical speciations.

As important place for water storage and supply, drinking-water reservoirs in karst mountain areas play a key role in ensuring human well-being, and its water quality safety has attracted much attention. Source apportionment and ecological risks of heavy metal(loid)s in sediments of drinking-water reservoir are important for water security, public health, and regional water resources management, especially in karst mountain areas where water resources are scarce. To expound the accumulation, potential ecological risks, and sources of heavy metal(loid)s in a drinking-water reservoir in Northwest Guizhou, China, the surface sediments were collected and analyzed based on the combined use of the geo-accumulation index (Igeo), sequential extraction (BCR), ratios of secondary phase and primary phase (RSP), risk assessment code (RAC), modified potential ecological risk index (MRI), as well as the positive matrix factorization methods. The results indicated that the accumulation of Cd in sediments was obvious, with approximately 61.9% of the samples showing moderate to high accumulation levels, followed by Pb, Cu, Ni, and Zn, whereas the As and Cr were at low levels. A large proportion of BCR-extracted acid extractable and reducible fraction were found in Cd (72.5%) and Pb (40.3%), suggesting high bioavailability. The combined results of RSP, RAC, and MRI showed that Cd was the major pollutant in sediments with high potential ecological risk, while the risk of other elements was low. Source apportionment results of heavy metal(loid)s indicated that Cd (75.76%) and Zn (23.1%) mainly originated from agricultural activities; As (69.82%), Cr (50.05%), Cu (33.47%), and Ni (31.87%) were associated with domestic sources related to residents' lives; Cu (52.36%), Ni (44.57%), Cr (34.33%), As (26.51%), Pb (24.77%), and Zn (23.80%) primarily came from natural geological sources; and Pb (47.56%), Zn (22.46%) and Cr (13.92%) might be introduced by mixed sources of traffic and domestic. The contribution ratios of the four sources were 18.41%, 36.67%, 29.48%, and 15.44%, respectively. Overall, priority control factors for pollution in relation to agricultural sources included Cd, while domestic sources are primarily associated with As. It is crucial to place special emphasis on the impacts of human activities when formulating pollution prevention and control measures. The results of this study can provide valuable reference and insights for water resources management and pollution prevention and control strategies in karst mountainous areas.

ADVANCE POLLUTION MONITORING SYSTEM WITH HEALTH CRITICAL GAS INDEXING USING IOT

The rise of urbanization and industrialization has led to an increase in pollution, posing serious risks to human health and the environment. Consequently, the development of advanced pollution monitoring systems has become crucial for efficient pollution control and management. This abstract introduces a cutting-edge pollution monitoring system based on the Internet of Things (IoT), which incorporates health critical gas indexing to provide real-time and precise information about air quality. The proposed system utilizes IoT technology to create a network of interconnected sensors installed in various locations within cities or industrial areas. These sensors are designed to measure the concentration of pollutants such as carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM2.5 and PM10), and ozone (O3) in the surrounding air. The collected data is wirelessly transmitted to a central monitoring station for analysis and visualization. To assess the health risks associated with measured pollutant levels, a health critical gas indexing algorithm is employed. This algorithm considers pollutant concentrations and their corresponding health effects based on established air quality guidelines and standards, calculating an index value that indicates the overall health impact on the exposed population. The monitoring system provides real-time updates and alerts to relevant stakeholders, including government authorities, environmental agencies, and the public. Accessible through a userfriendly web or mobile application, the data and index values empower users to make informed decisions regarding outdoor activities, pollution mitigation measures, and health precautions. Compared to traditional monitoring approaches, the IoT-based advance pollution monitoring system with health critical gas indexing offers several advantages. It provides a comprehensive and accurate assessment of air quality by considering the specific health risks posed by different pollutants. Its real-time nature enables prompt actions and interventions to mitigate pollution levels, safeguarding public health and the environment. Furthermore, the availability of data empowers policymakers and researchers to analyze trends, identify pollution sources, and develop targeted pollution control strategies. In conclusion, the proposed IoT-based advance pollution monitoring system with health critical gas indexing represents a significant advancement in pollution monitoring and management. By leveraging IoT technology and incorporating health-related considerations, the system enables effective and proactive pollution control measures, leading to improved air quality and overall well-being of the population.

Analisis Kualitas Air di Sungai Marbau

This study aims to analyze the quality of river water and the water quality status of the Marbau watershed in North Labuhanbatu Regency based on water quality criteria and to formulate a pollution control strategy that needs to be implemented. The method used is a quantitative descriptive method by analyzing the status of river water quality based on the pollution index. The results showed that the P1 value of Marbau river water ranged from 0.94 to 1.82. The recommended pollution control strategies are: 1) maintaining river protection zones involving environmental cadres and green communities in monitoring; 2) monitoring and controlling water pollution along the river; 3) improve river water quality monitoring; 5) supervision of the discharge of waste water into rivers; 4) granting permits for disposal of wastewater (IPLC) into rivers must pay attention to the condition of the capacity to accommodate river pollution loads and enforce environmental law against business actors who violate established environmental quality standards. In conclusion, the quality of the Marbau river has decreased with the water quality status being slightly polluted. The recommendations for water pollution control strategies that need to be implemented are progressive strategies.
 Keywords: Water Quality, North Labuhanbatu, Marbau

Sorption of organic contaminants by biochars with multiple porous structures: Experiments and molecular dynamics simulations mediated by three-dimensional models

Interactions between organic pollutants and carbon-based particles are critical for understanding and predicting the fate of organic contaminants in the environment. However, traditional modeling concepts did not consider three-dimensional (3-D) structures of carbon-based materials. This prevents a deep understanding of the sequestration of organic pollutants. Therefore, this study revealed interactions between organics and biochars by combining experimental measurements and molecular dynamics simulations. Biochars displayed the best and worst sorption performances for naphthalene (NAP) and benzoic acid (BA), respectively, among the five adsorbates. The kinetic model fitting suggested that biochar pores played a vital role during sorption and led to the fast and slow sorption of organics on the biochar surface and in pores, respectively. Active sites on the biochar surface predominantly sorbed organics. Organics were only sorbed in pores when the surface’s active sites were fully occupied. These results can guide the development of efficient organic pollution control strategies to protect human health and improve ecological security.

Comparison of PM spatiotemporal variations and exposure at adjacent signalized intersection and roundabout

As urban traffic nodes, signalized intersections and roundabouts gather a large number of vehicles, forming traffic particulate matter (PM) hotspots. However, related studies have focused only on signalized intersections, and knowledge of PM characteristics on roundabouts are still scarce. For this reason, we carried out mobile and fixed-site monitoring of PM mass and number concentrations and comparative analysis, at an adjacent roundabout and intersection. The attenuation curves of PM2.5 concentrations down the departure roads from the roundabout and intersection centers showed an exponential decay, but their distribution profiles were obviously different. Particle number concentration (PNC) first increased and then decreased at the roundabout, while it was similar to PM2.5 with exponential decay at the intersection. The temporal variation of PNC in different particle sizes differed between the roundabout and intersection. A Generalized Additive Model (GAM) quantified the contribution of background concentration, Meteorological conditions, and traffic volume to PM2.5 at the roundabout and the intersection, respectively, identifying their different influential levels. Lastly, using field data of this case study, the average respiratory deposition dose (RDD) rates were estimated for adults and children. The study can help formulate effective urban traffic pollution control strategies.

Chemical speciation of organic compounds and elemental compositions of PM2.5 in Mexico City: Spatial-seasonal distribution, emission sources, and formation processes

The simultaneous study of n-alkanes, polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs, and metals in particles ≤2.5 μm (PM2.5) provided helpful information to identify pollutant emission sources in the Metropolitan Zone of Mexico Valley (MZMV). PM2.5 samples were obtained during three seasons of a year from five sampling sites simultaneously collected. The dominant sources of the species were the incomplete combustion of fossil fuel by vehicles, followed by the resuspension of geogenic material, evaporation from petrogenic sources, and emissions from the oil refining industry. The northeast (NE) of the MZMV, hosting the industrial area, exhibited the highest contribution of ΣPAHs<228 due to the high presence of diesel vehicles. The NE also showed the highest metal concentrations of geogenic origin due to its proximity to agricultural lands and the dominant wind direction from the north to the south, introducing pollutants into the Valley. Among the pollutants, 1-nitropyrene emitted from diesel combustion sources and 2-nitrofluoranthene formed in the atmosphere were found. Particles enriched with Mn + Fe + Co + Cu and Rb were emitted from agricultural lands and volcanic soil, respectively, and originated from local/peripherical soils, while particles enriched with Cr + Cs + Th were originated from geogenic sources further away from the MZMV. Cd + Pb and n-alkanes C16-C22 were emitted outside the Valley, while PAHs, nitro-PAHs, and heavier n-alkanes (C23-C33) were emitted inside the Valley. Decision-makers could use our results to develop control strategies for air pollutants from specific sources. Comparisons of hydrocarbon and metal concentrations in other cities were also made.