Key Emission Sources Research Articles

Discussion on key issues of carbon footprint quantification of silk products

In this study, to accurately calculate the carbon footprint of silk products, key issues were analysed and discussed, including accounting boundary, accounting data, sequestration of greenhouse gases (GHG) and calculation of results. The results support the feasibility of "cradle to gate" or "gate to gate" as the accounting boundary for the carbon footprint of silk products. Accordingly, the quality of accounting data may be improved by determining the key emission sources of GHG within the accounting boundary, selecting the appropriate data allocation methods and maintaining the consistency of the allocation methods within the accounting boundary when necessary. The GHG sequestration of silk is explained separately in the results, which report on the carbon footprint of silk products. The carbon-neutral actions taken by silk enterprises are also discussed and quantified in the results of the carbon footprint calculation. Ultimately, it is found that a consistent accounting boundary and emission factors constitute two key prerequisites for the feasibility of carbon footprint quantification of various silk products.

Linking PAHs concentration, risk to PAHs source shift in soil and water in epikarst spring systems, Southwest China

A systematic assessment of the variations in the ecological risk of PAHs and the key emission sources controlling the variations is of great importance to human health and aquatic organisms. PAH concentrations, composition, source, and ecological risk in soils and water in two different periods (2010–2011 and 2019) of three typical epikarst springs in Southwest China were investigated. Results showed that PAH concentrations in soil and water have an overall downward trend (a reduction of 57 % and 93 %, respectively) in the past 10 years, which is consistent with the downward trend in the relative contribution rate of raw coal production (a 66 % reduction). In terms of composition, the proportion of low-ring PAHs decreased, medium-ring and high-ring PAHs increased in the soil profile. The proportion of low-ring PAHs did not change obviously, the proportion of medium-ring PAHs increased, and the proportion of high-ring PAHs decreased in epikarst springs. The source of PAHs changed remarkably over time, the relative contribution of coal combustion to PAHs decreased from 38 % to 20 %, and the vehicle contribution of PAHs increased from 31 % to 44 % in soils. The relative contribution rate of unburned oil and coke oven and biomass combustion change is less. Furthermore, the ecological risk of PAHs in the soils was reduced from moderate risk 2 to moderate risk 1, the risk in epikarst spring was reduced from high risk to moderate risk 2 after 10 years. This study demonstrates that substituting petroleum and coal with green energies can reduce PAH concentrations and risk.

Modern AAC additive—A ready tool helping with decarbonization of AAC production by reduction of water, cement, lime and energy consumption

AbstractEuropean Association of AAC producers (EAACA) has set the goal for the AAC industry to become carbon‐neutral by 2050, so it is now more important than ever to explore ways to achieve it. One of the readily available solutions is a dedicated additive for AAC production, production, the effects of which positively affect the reduction of CO2e emissions. The additive is a tool helping the chemical reaction and offers improvements in two key emission sources for AAC. The first one is cement and lime usage, responsible for 74% of CO2e emissions in AAC production. A few percent cutbacks of binders consumption generate direct results in this area. The second one is the production process itself, being accountable for 13% of CO2e emissions. Lowering water content in the mix directly results in a lower requirement for steam during autoclaving, therefore impacting energy usage. Reductions in these two areas can be calculated in terms of CO2e emissions, as well as economical savings. The financial advantages generated by the additive are always higher than the cost of it. The chemical and process background presented in this paper is supported with examples from AAC plants worldwide, and complemented by GHG methodology calculation where 3,6% of CO2e emissions reductions can be achieved solely by using modern additive for production.

Key factors for abating particulate matter in a highly industrialized area in N Spain: Fugitive emissions and secondary aerosol precursors

In highly industrialized areas, abating particulate matter (PM) is complex owing to the variety of emission sources with different chemical profiles that may mix in the atmosphere. Gijón—an industrial city in northern Spain—was selected as a case study to better understand the key emission sources and improve air quality in highly industrialized areas. Accordingly, the trends of various air quality indicators (PM10, PM2.5, SO2, NO2, and O3) during the past decade (2010–2019) were analyzed. Additionally, the inorganic and organic PM10 compositions were analyzed for source apportionment studies and to assess the impact of COVID-19 restrictions on PM10 levels.The results revealed that over the past decade, PM10 concentrations decreased, whereas PM2.5 concentrations dominated by secondary inorganic aerosols (SIA) remained relatively constant. Notably, during the COVID-19 lockdown, the PM10 concentration increased by 9.1%, primarily owing to an increase in regional SIA (>65%) due to specific meteorological conditions that favor the formation of secondary PM from gaseous precursors. Overall, eight key PM10 sources were identified: “industrial fugitive PM resuspension” (FPM, 28% of mean PM10 concentration), “aged sea spray” (SSp, 16%), “secondary nitrate” (SN, 15%), “local diffuse source” (LPM, 12%), “solid fuel combustion” (SFC, 7.8%), “biomass burning” (BB, 7.4%), “secondary sulphate” (SSu, 6.0%), and “sinter” (SIN, 4.5%). The PM10 concentration in Gijón is significantly influenced by the integrated steel industry (FPM, SFC, and SIN; 41% of PM10) and fugitive primary PM emissions were the main source (FPM and LPM; 40%). To reduce PM10 and PM2.5 concentrations, industrial fugitive emissions, which are currently poorly regulated, and SIA precursors must be abated.This study provides a methodological approach that combines trend analysis, chemical speciation, and source apportionment for assessing pollution abatement strategies in industrialized areas with a complex mix of emission sources.

Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US

Emerging evidence indicates that exposure to fine particulate matter (PM2.5) air pollution may increase dementia risk in older adults. Although this evidence suggests opportunities for intervention, little is known about the relative importance of PM2.5 from different emission sources. To examine associations of long-term exposure of total and source-specific PM2.5 with incident dementia in older adults. The Environmental Predictors of Cognitive Health and Aging study used biennial survey data from January 1, 1998, to December 31, 2016, for participants in the Health and Retirement Study, which is a nationally representative, population-based cohort study in the US. The present cohort study included all participants older than 50 years who were without dementia at baseline and had available exposure, outcome, and demographic data between 1998 and 2016 (N = 27 857). Analyses were performed from January 31 to May 1, 2022. The 10-year mean total PM2.5 and PM2.5 from 9 emission sources at participant residences for each month during follow-up using spatiotemporal and chemical transport models. The main outcome was incident dementia as classified by a validated algorithm incorporating respondent-based cognitive testing and proxy respondent reports. Adjusted hazard ratios (HRs) were estimated for incident dementia per IQR of residential PM2.5 concentrations using time-varying, weighted Cox proportional hazards regression models with adjustment for the individual- and area-level risk factors. Among 27 857 participants (mean [SD] age, 61 [10] years; 15 747 [56.5%] female), 4105 (15%) developed dementia during a mean (SD) follow-up of 10.2 [5.6] years. Higher concentrations of total PM2.5 were associated with greater rates of incident dementia (HR, 1.08 per IQR; 95% CI, 1.01-1.17). In single pollutant models, PM2.5 from all sources, except dust, were associated with increased rates of dementia, with the strongest associations for agriculture, traffic, coal combustion, and wildfires. After control for PM2.5 from all other sources and copollutants, only PM2.5 from agriculture (HR, 1.13; 95% CI, 1.01-1.27) and wildfires (HR, 1.05; 95% CI, 1.02-1.08) were robustly associated with greater rates of dementia. In this cohort study, higher residential PM2.5 levels, especially from agriculture and wildfires, were associated with higher rates of incident dementia, providing further evidence supporting PM2.5 reduction as a population-based approach to promote healthy cognitive aging. These findings also indicate that intervening on key emission sources might have value, although more research is needed to confirm these findings.

Identify the key emission sources for mitigating ozone pollution: A case study of urban area in the Yangtze River Delta region, China

Ozone (O3) has become the most critical air pollutant in the Yangtze River Delta (YRD) region of China. Research on the O3 formation mechanism and its precursor sources (including nitrogen oxides (NOX) and volatile organic compounds (VOCs)) could provide a theoretical basis for mitigating O3 pollution in this region. In this study, simultaneous field experiments were conducted for air pollutants in a typical urban area (Suzhou) in the YRD region in 2022. The capacity of in-situ O3 formation, O3-NOX-VOCs sensitivities and sources of O3 precursors were analyzed. The results showed that in-situ formation contributed 20.8 % of the O3 concentration in the warm season (April to October) of the Suzhou urban area. Compared with the warm season average, the concentrations of various O3 precursors increased on pollution days. The O3-NOX-VOCs sensitivity was the VOCs-limited regime based on the average concentrations during the warm season. O3 formation was most sensitive to anthropogenic VOCs, of which oxygenated VOCs, alkenes and aromatics were the key species. There was a VOCs-limited regime in spring and autumn, while a transitional regime in summer due to the changes in NOX concentrations. This study considered NOX emission from VOCs sources and calculated the contribution of various sources to O3 formation. The results of VOCs source apportionment showed that diesel engine exhaust and fossil fuel combustion had a dominant proportion, but O3 formation presented significant negative sensitivities to the above two sources because of their high NOX emissions. There were significant sensitivities of O3 formation to gasoline vehicle exhaust and VOCs evaporative emissions (gasoline evaporation and solvent usage). The contribution of VOCs evaporative emissions during the O3 pollution episode was significantly higher than the average; therefore, controlling VOCs evaporative emissions during the O3 pollution episode is critical. These results provide feasible strategies to mitigate O3 pollution.

Common Driving Forces of Provincial-Level Greenhouse Gas and Air Pollutant Emissions in China.

By developing a filtering framework and a sector-level multi-regional input-output structural decomposition model, this study identifies key common emission sources, motivation sources, and inter-provincial emission flows of both GHGs and air pollutants and reveals the key driving forces of changes in different emissions from 2012 to 2017. Results show that key common emission sources are electricity sector, non-metallic mineral products, and smelting and processing of metals in Shandong and Hebei. However, key common motivation sources are the construction sectors in Guangdong, Henan, Jiangsu, Zhejiang, and Shandong. The key inflow regions include Guangdong and Zhejiang and key outflow regions include Jiangsu and Hebei. The emission reductions are attributed to the emission intensity effect of the construction sector; contrastingly, the emission increase is from the investment scale of the construction sector. Here, Jiangsu could be a key target for future emission reduction because of its high absolute emissions and low past reduction. The scale of investment in construction might be a significant factor in reducing emissions in Shandong and Guangdong. Henan and Zhejiang could concentrate on sound new building planning and resource recycling.

Source Contributions to PM2.5-Related Mortality and Costs: Evidence for Emission Allocation and Compensation Strategies in China

The emissions from various pollution sources were not proportional to their contributions to ambient PM2.5 concentrations and associated health burdens. That means even with the same total abatement targets, different abatement allocation strategies across emission sources can have distinct health benefits. Insufficient knowledge of various sources' contributions to health burdens in China, the country suffering substantial PM2.5-related deaths, hindered the government from seeking optimized abatement allocation strategies. In this context, we separated the contributions of 155 emission sources (31 provinces × 5 sectors) to PM2.5-related mortality across China in 2017 by coupling the Comprehensive Air Quality Model with Extensions (CAMx), Weather Research and Forecasting model (WRF), and health impact assessment model. We further identified the priority-control emission sources and quantified interprovincial ecological compensation volumes to alleviate inequality induced by emission allocation strategies. Results showed that PM2.5 pollution caused 899,443 excess deaths and around 127 billion USD costs in 2017. Approximately half of the deaths and costs were attributable to emissions from sources outside the boundary of the regions where the deaths occurred. Twenty-five out of 155 emission sources that contributed to the top 60% mortality burdens and had high marginal abatement efficiencies in China shall be the priority-control emission sources. A 1 μg/m3 decrease of PM2.5 concentration in regions where these key emission sources occur shall be compensated by 76-153 million USD in their receptor regions. Our study sheds light on the sources' contributions to mortality burdens and costs and provides scientific evidence for optimizing the emission allocation and compensation strategies in China. It also has wide implications for other countries suffering similar problems.

A recent high-resolution PM2.5 and VOCs speciated emission inventory from anthropogenic sources: A case study of central China

Aiming to provide basic data support for the improvement of air quality in the study region, this study established the emission inventory and speciated emission inventory of PM2.5 and VOCs in Henan Province, and further estimated the ozone formation potential (OFP) and secondary organic aerosols formation potential (SOAFP) of VOCs to identify key species, priority sources and typical cities. The 2017-based emissions of PM2.5 and VOCs were 598 and 1079 kt, respectively. Industrial process, fugitive dust and biomass burning were the three major contributors to PM2.5, with a combined contribution of 79%, while industrial process, on-road mobile, solvent utilization and biomass burning were the four major contributors to VOCs emissions, with a combined contribution of 90%. Other unidentified species had the highest emissions, followed by carbonaceous components and inorganic elements and water-soluble ions. The total amount of OFP and SOAFP were 3482 and 81 kt. The species categories of VOCs that contributed large fractions to the emissions were alkanes, aromatic hydrocarbons and oxygenated VOCs, to the OFP were aromatic hydrocarbons, olefins, and oxygenated VOCs, and to the SOAFP were aromatic hydrocarbons and alkanes. Considering OFP and SOAFP together, industrial process, solvent utilization, on-road mobile and biomass burning are the key emission sources to control. The overall spatial distribution showed that PM2.5 and VOCs emissions were relatively low in the southwest and southeast of Henan province, while emissions were high in densely populated, industrial, agricultural and transportation developed areas, and the spatial distribution characteristics of OFP and SOAFP were similar to those of VOCs emissions.

Evaluation of Air Quality in Sudanese Gold Mining Fields

This study intended to provide a base line and describe the current air quality in Sudanese Gold mining fields. It covers 21 gold marketing centers in 5 states; namely Northern, River Nile, Gadaref, Red Sea and Kurdofan state. The main objectives of the survey is the detection of any significant concentrations that exceed Occupational Safety and Health norms and specifying the key emission sources, and also identification and assessing of the health hazards and environmental impacts. The tests were carried out by using electronic portable devices to measure the concentrations of pollutants in air. The measured pollutants were: Dust or Particulate Matter (PM), Nitrogen Dioxide (NO2), Volatile Organic Components (VOCs), Sulphur Dioxide (SO2), Ammonia (NH3), Carbon Monoxide (CO) and Ozone (O3). National Ambient Air Quality Standards (NAAQSs) and Sudanese Standards for Ambient Air Pollutants were used for comparison purposes. In addition to that, Air Quality Index (AQI) was applied for the average concentrations of each pollutant. It was found that, all gold marketing centers suffered from very high concentration of PM2.5 and PM10. 90.5% of those centers had higher NO2 concentration than the standards, 37% of it was increased by 200% and 42% of it was increased by 150%. In addition to that, 48% of gold marketing centers had higher SO2 concentration than the standards. On the other hand, concentrations of other pollutants obtained were found within the allowable limits. Finally, it was concluded that all those centers are contaminated with one or more air pollutants. Therefore, it was recommended to improve the environmental conditions by mitigating emissions from point sources. Supervisors have been advised to assume their responsibilities in controlling the use of Personal Protective Equipment (PPE) in addition to the dissemination of safety culture through psychological approach.

Characteristics of Industrial Volatile Organic Compounds(VOCs) Emission in China from 2011 to 2019

In order to better understand the industrial volatile organic compounds(VOCs) emissions in China in recent years, an industrial VOCs emission inventory was developed from 2011 to 2019, based on the dynamic emission factors method and the comprehensive source classification system. The results showed that VOCs emissions increased first from 11122.7 kt in 2011 to 13397.9 kt in 2017, and then decreased to 13247.0 kt in 2019. The emission structure of the four source categories changed. The contribution from basic organic chemical industries, gasoline storage and transportation, manufacturing(i.e., coatings, inks, pigments, and similar products), and industrial protective coatings continued to increase. On the contrary, the contributions of oil and natural gas processing, automobile, and container manufacturing industries declined over the study period. Among the industrial emissions in China in 2019, industrial coating, printing, and basic organic chemical industries emitted large amounts of VOCs(accounting for 39.2% of the total emission), and because their contribution became increasingly prominent since 2011, these sectors will be the key emission sources in the future. With respect to the spatial distribution in 2019, East China and South China had the largest VOCs emissions. Shandong, Guangdong, Jiangsu, and Zhejiang were the four provinces that contributed the most, accounting for 40.6% of the total VOCs emissions.

Variability in real-world emissions and fuel consumption by diesel construction vehicles and policy implications

Strategically reducing the emission of non-road mobile source especially diesel construction vehicle (DCV) has a large potential in improving air quality and has attracted much scientific and public attention in recent years around the world. In this study, we explored real-world fuel consumption rate and gaseous emissions factors for multiple pollutants of three typical DCVs in China. The sampling campaign considered the operation mode, cumulative operation hour, emission standard stage and engine power. Results show that the accumulated fuel consumption per hour of vehicle weight for working, load-free moving and idling modes was 0.3, 0.2 and 0.1 kg/h·tons, respectively. The fuel-based NOx emission factor exhibited a bimodal distribution at 27 and 41 g/kg. The fuel-based emission factors for volatile organic compounds (VOCs) were in the range of 0.8 to 2.6 g/kg, where alkene and alkane were the dominant components (>80%), i.e., ethylene, acetylene, propylene, and isobutane. We observed that the ratio of toluene and benzene concentration (T/B) (1.4 ± 1.3) differed from other key emission sources and may be used as the specific indicator of DCV emission exhaust. Our estimates suggest that in 2017 the fuel consumption and NOx emissions of DCV emission accounted for 22–28% of non-road mobile sources in China; NOX emissions were 2.7 times higher than those in 2006, and it is forecasted that NOx emissions would reduce by 23% between 2017 and 2025 with the implementation of stage IV and the strict supervision policy. The comprehensive dataset on DCV emissions will either guide the government to establish precise and effective policies to regulate the non-road mobile source or significantly improve our understanding of source apportionment of atmospheric NOx and VOCs, both of which are key precursors of haze and ozone pollution.

Trends and Source Contribution Characteristics of SO2, NOX, PM10 and PM2.5 Emissions in Sichuan Province from 2013 to 2017

As one of the most populated regions in China, Sichuan province had been suffering from deteriorated air quality due to the dramatic growth of economy and vehicles in recent years. To deal with the increasingly serious air quality problem, Sichuan government agencies had made great efforts to formulate various control measures and policies during the past decade. In order to better understand the emission control progress in recent years and to guide further control policy formulation, the emission trends and source contribution characteristics of SO2, NOX, PM10 and PM2.5 from 2013 to 2017 were characterized by using emission factor approach in this study. The results indicated that SO2 emission decreased rapidly during 2013–2017 with total emission decreased by 52%. NOX emission decreased during 2013–2015 but started to increase slightly afterward. PM10 and PM2.5 emissions went down consistently during the study period, decreased by 26% and 25%, respectively. In summary, the contribution of power plants kept decreasing, while contribution of industrial combustion remained steady in the past 5 years. The contribution of industrial processes increased for SO2 emission, and decreased slightly for NOX, PM10 and PM2.5 emissions. The on-road mobile sources were the largest emission contributor for NOX, accounting for about 32–40%, and its contribution increased during 2013–2015 and then decreased. It was worth mentioning that nonroad mobile sources and natural gas fired boilers were becoming important NOX contributors in Sichuan. Fugitive dust were the key emission sources for PM10 and PM2.5, and the contribution kept increasing in the study period. Comparison results with other inventories, satellite data and ground observations indicated that emission trends developed in this research were relatively credible.

A hybrid air pollution / land use regression model for predicting air pollution concentrations in Durban, South Africa.

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R2 annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R2 for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables.

Progress of the stable carbon and radiocarbon isotopes of black carbon aerosol

Black carbon (BC) aerosol derived from incomplete combustion of fossil fuel (e.g., coal and liquid petroleum) and biomass (e.g., agricultural residue, biofuel, and forest) is an important atmospheric pollutant globally. Besides presenting potential risks to public health, BC strongly absorbs solar radiation, decreases atmospheric visibility, heats the air, and is thought to be a key driver of climate warming. However, there is a large discrepancy between observations and models of the source apportionment and climate forcing of atmospheric BC globally, due to uncertain emission estimates. Stable carbon (13C) and radiocarbon (14C) isotope measurements are some of the most objective and accurate tools for apportioning atmospheric BC into key emission sources due to their unique fingerprint features. This review focuses on the principle of source apportionment for BC using 13C and 14C measurements, and the recent important progress in China, one of the largest emitters of BC. As expected, fossil fuel combustion is the largest contributor (70%−90%) of BC in many Chinese cities, mainly due to the huge consumption of coal and petroleum. However, the impact of biomass burning on BC can reach ~50% in some cities and even higher (~70%) in some remote sites, strongly reflecting the regional features of BC emission sources in China. Moreover, the largest and smallest contributions of fossil fuel combustion to BC are generally in summer and winter, respectively, highlighting the important influence of biomass burning on atmospheric BC during the cold season. The combined 13C and 14C measurements show that atmospheric BC in Northern China is mainly associated with coal combustion, followed by the burning of petroleum and biomass, which is very different from other regions where BC is typically dominated by petroleum burning. This implies that coal combustion is much more common and intensive in Northern China than in other regions. A strong correlation ( R 2 = 0.81) is observed between the 14C signal and atmospheric levoglucosan concentration in winter, while the correlation is very weak ( R 2 = 0.19) in summer. These results indicate that levoglucosan is chemically stable in the cold, but is degraded to a large extent in the atmosphere in summer. Compared with the levoglucosan concentration in winter, we roughly estimate that ~24% and ~70% of levoglucosan would be chemically degraded in spring and summer, respectively, which is consistent with chamber-based results (30%–75%). Therefore, we confirm that levoglucosan cannot quantify the impact of biomass burning on atmospheric BC in hot seasons. The source apportionment of BC based on emission-inventory technology is variable. In China, the contribution of biomass burning to BC could be as low as ~20% or as high as ~50%, depending on the emission inventory. Given the excellent ability of 13C and 14C isotopes to quantify atmospheric BC, this review notes that a combined 13C and 14C measurement technique can serve as a good “referee” to guide the improvement of the BC emission inventory and deepen our understanding of the environmental and climatic effects of BC aerosols. Future research should (1) establish a 13C-BC database for different combustion-related emission sources and regions, (2) bridge the emission inventory of BC and isotope-based observations using atmospheric chemistry models, (3) comprehensively explore the atmospheric stability of levoglucosan using carbon isotopes, and (4) build an atmospheric observation network for BC carbon isotopes covering urban, rural, and remote areas in China.

Antibiotic resistance in water environment: Frontiers of fundamental research, risk assessment and control strategies

<p indent=0mm>Antibiotic resistance has been considered as a major health security challenge of the 21st century in the 2013 G8 Science Minsters Statement. UN Environment ranked “Antimicrobial Resistance: Investigating the Environmental Dimension” as No.1 emerging issue among the six emerging issues of environmental concern in 2017. It should be pointed out that antibiotic resistance is not just a regional or national phenomenon but also a global problem, indicated by the famously typical cases of the rapid dissemination of <italic>Klebsiella pneumonia</italic> carbapenemase-positive bacteria and New Delhi metallo-β-lactamase-positive bacteria in Asia, Europe and North America. Animal waste, antibiotic production wastewater, hospital wastewater, sewage, sludge, soil, sediment, surface water and even air have been considered as important reservoirs for antibiotic resistance genes (ARGs) because abundant ARGs have been frequently detected in these environments. Among the different environment types, the water environment is a key node for the dissemination of antibiotic resistance. A large number of previous studies mainly focused on the abundance and diversity of ARGs in the water environments. However, the systematic and in-depth studies on the source, spread and fate of ARGs in the water environment are still limited. The basic framework and sophisticated models for risk assessment are still lacking for environments even possessing data of antibiotic concentration and exposure levels of ARGs. In addition, there is also no strategic thinking in the formulation and implementation of antibiotic resistance control strategies. Considering the above issues, this review will focus on the frontiers of fundamental research, risk assessment, and control strategies of antibiotic resistance in water environment and other environments, including: (1) The establishment of standardized detection approach and public database for antibiotics, i.e., the major selection pressure of antibiotic resistance; (2) the migration, transformation and bioavailability of antibiotics; (3) the transfer and dissemination of ARGs in the wastewater treatment plants; (4) exploring the standardized methods for investigating exposure levels of ARGs: metagenomic approach & high-throughput qPCR approach; (5) the key mobile genetic elements responsible for horizontal gene transfer and environmental transmission of ARGs; (6) deep mining and machine learning of ARGs using metagenomic/genomic big data. Several case studies were selected respectively to demonstrate current research status of the above six frontiers of fundamental research, risk assessment, and control strategies of antibiotic resistance. For the risk assessment, two types of risks including the risk of antibiotic treatment failure and the risk of ARGs dissemination in the environment should be distinguished. The prevention and control strategy of antibiotic resistance involves multi-disciplinary linkage and combination together, which requires the joint efforts of clinical medicine, ecology, agriculture, pharmacy, environmental science and engineering, as well as the cooperation of education, etc. Currently, following the integrative strategy of One Health, we should give the first priority to the investment on prevention and control measures at the key emission sources and other nodes to effectively reduce and ultimately stop the emissions of antibiotics and ARGs. The key emission sources mainly include antibiotic manufacturing factory, livestock farm, aquaculture farms, slaughter house, hospital and municipal wastewater treatment plants etc.

Carbon Footprint as Climate Change Disclosure – Opportunities for Performance Improvement

Carbon Footprint refers to the potential climate impact (Global Warming) due to Greenhouse Gases (GHG) emitted directly or indirectly owing to an organization’s activities. A climate change disclosure of any educational institution must be studied so that its key emission sources can be identified and necessary mitigation measures be adopted for carbon reduction. An assessment based on the same was carried out at Maitreyi College, a constituent of the University of Delhi. The emissions were reported from college-owned facilities, indirect energy emissions from electricity, travel and solid waste generation. Consequently, some measures for efficient power consumption and management of waste were suggested to the college management in order for them to set a target for carbon reduction in the upcoming years. The benefits of the project will manifest in substantial utility cost reduction across the campus in the coming years, and will lead to both financial as well as environmental sustainability of the institution.

A sixteen-year reduction in the concentrations of aquatic PAHs corresponding to source shifts in the Elbe River, Germany

Polycyclic aromatic hydro-carbons (PAHs) are carcinogenic, mutagenic, and teratogenic persistent organic molecules. To protect human health and aquatic organisms, a systematic assessment of the trends in PAH exposure risk and the key emission sources governing such trends is essential. Therefore, the long-term trends in PAH concentrations were assessed for the Elbe River, Germany, which represents a dynamic environment in which anthropogenic activities and nature exhibit complicated interactions. A Mann-Kendall trend test identified a general decreasing trend (a 38% reduction) in PAH concentrations over the last 16 years (2001–2016), which was consistent with a decline in the relative contribution from coke oven use (a 26–14% reduction). According to the source apportionment, an increasing number of source contributors were identified over time. Furthermore, PAH exposure risks for aquatic organisms and human health were calculated as risk quotient (RQ) and chronic daily intake (CDI). For most PAHs, the risk quotient of negligible concentrations (RQNCs) exceeded 1 and the risk quotient of maximum permissible concentrations (RQMPCs) was less than 1, indicating a middle-level ecological risk. In addition, the CDI-based hazard quotients suggested that the risk of human exposure to PAHs remained within acceptable limits during the study period. However, vehicular-associated benzo(a)pyrene (BaP) emissions contributed the most to human health risk. The data presented here suggest that substituting petroleum and coal with green energies will reduce PAH concentrations in aquatic environments.

Ecotoxicity risk of presence of two cytostatic drugs: Bleomycin and vincristine and their binary mixture in aquatic environment

Cytostatic drugs have become one of the greatest environmental threats. They occur in surface, ground and even drinking water. Their key emission sources are hospital effluents, municipal wastewater, as well as drug manufacturers and their effluents. These compounds are extremely stable in natural waters and they are not significantly removed during wastewater treatment, because they are resistant to biodegradation. The aim of this work was to establish possible negative effects of chosen cytostatics: bleomycin and vincristine on the three trophic levels of surface waters. A single agent acute toxicity test was conducted on representatives of the producer – an aquatic freshwater plant Lemna minor, the consumer - crustaceans Daphnia magna, and the decomposer - bacteria Pseudomonas putida. Binary mixture tests were performed according to the Concentration Addition, Response Additivity, and Independent Action models. Both substances had a different effect on the tested organisms; bleomycin could be classified as a very toxic, while vincristine as a toxic water pollutant. Half maximal effective concentration (EC50) values designed in the presented single agent acute toxicity studies are < 10 mg/L in all the tests with bleomycin as well as vincristine conducted on L. minor. In tests with vincristine performed on D. magna and P. putida EC50 > 100 mg/L. The highest toxicity is demonstrated by bleomycin towards the aquatic freshwater plant (EC50 = 0.2 mg/L). The binary mixture of the tested chemicals showed antagonistic effects of environmental concern.

Characterisation and variability of greenhouse gas emissions from biomethane production via anaerobic digestion of maize

Biomethane is a renewable gas that can be used in existing infrastructure to reduce dependency on natural gas and lower greenhouse gas (GHG) emissions. Policy incentives have promoted a rapid implementation of biomethane production facilities using anaerobic digestion (AD). A range of feedstocks are used in AD including crops which have a higher GHG burden than most wastes and residues. The purpose of this research is to characterise and assess GHG emissions from typical operational biomethane facilities. It is imperative that GHG savings are obtained therefore quantifying emissions using a robust methodology is paramount. This study uses maize as a case study utilising data from several farms and AD facilities. Results show that calculated emissions for biomethane production from maize are 33.8 gCO2e/MJ of biomethane using the Renewable Energy Directive (RED) methodology. Key emission sources include N-fertiliser production, soil N2O emissions, imported electricity use, and fugitive methane. Sensitivity analysis performed assessed key data inputs and demonstrates how input inventory parameters affect the GHG balance and highlights variability in results. For the desired GHG savings to be achieved it is important that operators minimise fertiliser use, use nitrogen inhibitors, minimise imported electricity, and undertake close management of methane loss. This paper shows that although biomethane is considered a renewable, low carbon fuel, the inputs need to be carefully managed in order to achieve this.