As a country with the highest CO2 emissions and at the turning point of socio-economic transition, China's effort to reduce CO2 emissions will be crucial for climate change mitigation. Yet, due to geospatial variations of CO2 emissions in different cities, it is important to develop city-specific policies and tools to help control and reduce CO2 emissions. The key question is how to identify and quantify these variations so as to provide reference for the formulation of the corresponding mitigation policies. This paper attempts to answer this question through a case study of 26 cities in the Yangtze River Delta. The CO2 emissions pattern of each city is measured by two statistics: Gini coefficient to describe its quantitative pattern and Global Moran's I index to capture its spatial pattern. It is found that Gini coefficients in all these cities are all greater than 0.94, implying a highly polarized pattern in terms of quantity; and the maximum value for Global Moran's I index is 0.071 with a standard deviation of 0.021, indicating a weak spatial clustering trend but strong difference among these cities. So, it would be more efficient for these cities at current stage to reduce CO2 emissions by focusing on the large emission sources at certain small localities, particularly the very built-up areas rather than covering all the emission sources on every plot of the urban prefectures. And by a combination of these two metrics, the 26 cities are regrouped into nine types with most of them are subject to type HL and ML. These reclassification results then can serve as reference for customizing mitigation policies accordingly and positioning these policies in a more accurate way in each city.

Adverse effect studies of gasoline exhaust are scarce, even though gasoline direct injection (GDI) vehicles can emit a high number of particles.The aim of this study was to conduct an in vitro hazard assessment of different GDI exhausts using two different cell culture models mimicking the human airway. In addition to gasoline particle filters (GPF), the effects of two lubrication oils with low and high ash content were assessed, since it is known that oils are important contributors to exhaust emissions.Complete exhausts from two gasoline driven cars (GDI1 and GDI2) were applied for 6 h (acute exposure) to a multi-cellular human lung model (16HBE14o-cell line, macrophages, and dendritic cells) and a primary human airway model (MucilAir™). GDI1 vehicle was driven unfiltered and filtered with an uncoated and a coated GPF. GDI2 vehicle was driven under four settings with different fuels: normal unleaded gasoline, 2% high and low ash oil in gasoline, and 2% high ash oil in gasoline with a GPF. GDI1 unfiltered was also used for a repeated exposure (3 times 6 h) to assess possible adverse effects.After 6 h exposure, no genes or proteins for oxidative stress or pro-inflammation were upregulated compared to the filtered air control in both cell systems, neither in GDI1 with GPFs nor in GDI2 with the different fuels. However, the repeated exposure led to a significant increase in HMOX1 and TNFa gene expression in the multi-cellular model, showing the responsiveness of the system towards gasoline engine exhaust upon prolonged exposure.The reduction of particles by GPFs is significant and no adverse effects were observed in vitro during a short-term exposure. On the other hand, more data comparing different lubrication oils and their possible adverse effects are needed. Future experiments also should, as shown here, focus on repeated exposures.

The unintended influence of exhaust plumes emitted from a vehicle ahead to on-road air quality surveying data measured with a mobile laboratory (ML) at 20–40 km h−1 in dense traffic areas was investigated by experiment and life-sized computational fluidic dynamics (CFD) simulation. The ML equipped with variable sampling inlets of five columns by four rows was used to measure the spatial distribution of CO2 and NOx concentrations when following 5–20 m behind a sport utility vehicle (SUV) as an emitter vehicle equipped with a portable emission monitoring system (PEMS). The PEMS measured exhaust gases at the tailpipe for input data of the CFD simulations. After the CFD method was verified with experimental results of the SUV, dispersion of exhaust plumes emitted from a bus and a sedan was numerically analyzed.More dilution of the exhaust plume was observed at higher vehicle speeds, probably because of eddy diffusion that was proportional to turbulent kinetic energy and vehicle speed. The CO2 and NOx concentrations behind the emitter vehicle showed less overestimation as both the distance between the two vehicles and their background concentrations increased. If the height of the ML inlet is lower than 2 m and the ML travels within 20 m behind a SUV and a sedan ahead at 20 km h−1, the overestimation should be considered by as much as 200 ppb in NOx and 80 ppm in CO2. Following a bus should be avoided if possible, because effect of exhaust plumes from a bus ahead could not be negligible even when the distance between the bus and the ML with the inlet height of 2 m, was more than 40 m. Recommendations are provided to avoid the unintended influence of exhaust plumes from vehicles ahead of the ML during on-road measurement in urban dense traffic conditions.

Freshwater ecosystems play a key role in global greenhouse gas estimations and carbon budgets, and algal blooms are widespread owing to intensified anthropological activities. However, little is known about greenhouse gas dynamics in freshwater experiencing frequent algal blooms. Therefore, to explore the spatial and temporal variations in methane (CH₄) and carbon dioxide (CO₂), seasonal field investigations were performed in the Northwest Bay of Lake Chaohu (China), where there are frequent algal blooms. From the highest site in the nearshore to the pelagic zones, the CH₄ concentration in water decreased by at least 80%, and this dynamic was most obvious in warm seasons when algal blooms occurred. CH₄ was 2–3 orders of magnitude higher than the saturated concentration, with the highest in spring, which makes this bay a constant source of CH₄. However, unlike CH₄, CO₂ did not change substantially, and river mouths acted as hotspots for CO₂ in most situations. The highest CO₂ concentration appeared in winter and was saturated, whereas at other times, CO₂ was unsaturated and acted as a sink. The intensive photosynthesis of rich algae decreased the CO₂ in the water and increased dissolved oxygen and pH. The increase in CH₄ in the bay was attributed to the mineralization of autochthonous organic carbon. These findings suggest that frequent algal blooms will greatly absorb more CO₂ from atmosphere and increasingly release CH₄, therefore, the contribution of the bay to the lake's CH₄ emissions and carbon budget will be major even though it is small. The results of this study will be the same to other shallow lakes with frequent algal bloom, making lakes a more important part of the carbon budget and greenhouse gases emission.

Surface and water bodies in many parts of the world are affected due to eutrophication, contamination and depletion. The approach of wastewater treatment using algae for eliminating nutrients and other pollutants from domestic wastewater is growing interest among the researchers. However, sustainable treatment of the wastewater is considered to be important in establishing more effective nutrient and pollutant reduction using algal systems. In comparison to the conventional method of remediation, there are opportunities to commercially viable businesses interest with phycoremediation, thus by achieving cost reductions and renewable bioenergy options. Phycoremediation is an intriguing stage for treating wastewater since it provides tertiary bio-treatment while producing potentially valuable biomass that may be used for a variety of applications. Furthermore, the phycoremediation provides the ability to remove heavy metals as well as harmful organic substances, without producing secondary contamination. In this review, the role of microalgae in treating different wastewaters and the process parameters affecting the treatment and future scope of research have been discussed. Though several algae are employed for wastewater treatment, species of the genera Chlamydomonas, Chlorella, and Scenedesmus are extensively utilized. Interestingly, there is a vast scope for employing algal species with high flocculation capacity and adsorption mechanisms for the elimination of microplastics. In addition, the algal biomass generated during phycoremediation has been found to possess high protein and lipid contents, promising their exploitation in biofuel, food and animal feed industries.

Due to the increase of the human population and the rapid industrial growth in the past few decades, air quality monitoring is essential to assess the pollutant levels of an area. However, monitoring air quality in a high-density area like Sunway City, Selangor, Malaysia is challenging due to the limitation of the local monitoring network. To establish a comprehensive data for air pollution in Sunway City, a mobile monitoring campaign was employed around the city area with a duration of approximately 6 months, from September 2018 to March 2019. Measurements of air pollutants such as carbon dioxide (CO₂) and nitrogen dioxide (NO₂) were performed by using mobile air pollution sensors facilitated with a GPS device. In order to acquire a more in-depth understanding on traffic-related air pollution, the measurement period was divided into two different time blocks, which were morning hours (8 a.m.–12 p.m.) and afternoon hours (3 p.m.–7 p.m.). The data set was analysed by splitting Sunway City into different zones and routes to differentiate the conditions of each region. Meteorological variables such as ambient temperature, relative humidity, and wind speed were studied in line with the pollutant concentrations. The air quality in Sunway City was then compared with various air quality standards such as Malaysian Air Quality Standards and World Health Organisation (WHO) guidelines to understand the risk of exposure to air pollution by the residence in Sunway City.

The increase of CO₂ concentration in the atmosphere, water and soil environment can lead to the changes in microbial activities. However, the transformation of antibiotic resistance genes has not been investigated in the presence of higher levels of CO₂. This study demonstrated that CO₂ facilitated the transformation of pUC19 plasmid, carrying ampicillin resistance genes, into Escherichia coli. Mechanism studies revealed that the type Ⅱ secretion system, type Ⅳ pilus and some other secretion systems were enhanced by CO₂, leading to DNA capture by pilus, larger cell pore sizes and more cell membrane channels. CO₂ also increased reactive oxygen species production, leading to SOS response and cell membrane damage. Besides, changes in intracellular Fe²⁺ and Mg²⁺ concentrations induced by CO₂ caused greater damage to the cell membrane and enhanced secretion systems, respectively. Overall, increased CO₂ provided more cell membrane channels for plasmid uptake and led to higher transformation efficiencies. The potential risk of a natural factor on the transformation of ARGs was first studied in this study, which helps us understand the fate of ARGs in ecosystems. As the carbon emission will continue to grow and enhance the enrichment of CO₂ in water and soil, the findings revealed a more severe public health issue under the background of carbon emission and CO₂ leakage.

The increasing adoption of intelligent transportation system (ITS) data in smart-city initiatives worldwide has offered unprecedented opportunities for improving transportation air quality management. In this paper, we demonstrate the effective use of ITS and other traffic data to develop a link-level and hourly-based dynamic vehicle emission inventory. Our work takes advantage of the extensive ITS infrastructure deployed in Nanjing, China (6600 km2) that offers high-resolution, multi-source traffic data of the road network. Improved than conventional emission inventories, the ITS data empower the strength of revealing significantly temporal and spatial heterogeneity of traffic dynamics that pronouncedly impacts traffic emission patterns. Four urban districts account for only 4% of the area but approximately 30%–40% of vehicular emissions (e.g., CO2 and air pollutants). Owing to the detailed resolution of road network traffic, two types of emission hotspots are captured by the dynamic emission inventory: those in the urban area dominated by urban passenger traffic, and those along outlying highway corridors reflecting inter-city freight transportation (especially in terms of NOX). Fine-grained quantification of emissions reductions from traffic restriction scenarios is explored. ITS data-driven emission management systems coupled with atmospheric models offer the potential for dynamic air quality management in the future.

Indoor air quality ((IAQ) in classrooms was associated with the daily exposure of school-age children who are particularly vulnerable to air pollutants exposure, while few data exist to evaluate classroom indoor air quality nationwide in China. The subsample of the CIEHS 2018 study was performed in 66 classrooms of 22 primary schools nationwide in China. Temperature, relative humidity, PM₂.₅, PM₁₀, CO₂, CO, formaldehyde concentrations, bacteria and fungi were detected in all classrooms by using the instruments that meet the specified accuracy. The ratios of indoor to outdoor (I/O) of PM₂.₅ were calculated in each classroom to identify whether the indoor environment the pollutants comes from outdoors. The indoor PM₂.₅, PM₁₀, CO, HCHO, bacteria and fungi GM concentration are 47.40 μg/m³, 72.91 μg/m³, 0.37 mg/m³, 0.02 mg/m³, 347.51 CFU/m³ and 362.76 CFU/m³, respectively. We observed that there were 66.5%, 52.6%, 22.4%, 1.8%, and 9.6% of the classrooms that exceeded the guideline values of PM₂.₅, PM₁₀, CO₂, HCHO, and bacteria, respectively. It should be attention that all of the classroom's PM₂.₅ concentrations in Shijiazhuang and Nanning, PM₁₀ concentrations in Nanning, CO₂ concentration in Lanzhou were exceeded the suggested values. Bacteria contamination in Shijiazhuang's classrooms is also serious. All classroom CO concentrations meet the requirement. The results indicated that classroom indoor PM₂.₅ was significantly positively correlated with indoor PM₁₀ and CO₂, while was negative correlated with temperature, CO, and fungi. Our results suggest that indoor air pollution in classrooms was a severe problem in Chinese primary schools. It is necessary to strengthen ventilation in the classroom to improve indoor air quality. What's more, a healthy learning environment should be created for primary school students.

The challenge to mitigate real-world emissions from vehicles calls for powerful in-use compliance supervision. The remote on-board diagnostic (OBD) approach, with wireless data communications, is one of the promising next-generation monitoring methods. We collected second-by-second profiles of carbon dioxide (CO2) and nitrogen oxides (NOX) emissions, driving conditions and engine performance for three conventional diesel and three hybrid diesel buses participating in a remote OBD pilot program in Nanjing, China. Our results showed that the average CO2 emissions for conventional diesel and hybrid diesel buses were 816 ± 83 g km−1 and 627 ± 54 g km−1, respectively, under a typical driving pattern. An operating mode binning analysis indicated that CO2 emissions reduction by series-parallel hybrid technology was largely because of the significant benefits of the technology under the modes of low speed and low power demand. However, significantly higher CO2 emissions were observed for conventional diesel buses during rush hours, higher than 1200 g km−1. The OBD data suggested no improvement in NOX emission reduction for hybrid buses compared with conventional buses; both were approximately 12 g km−1 because of poor performance of the selective catalyst reduction (SCR) systems in the real world. Speed-dependent functions for real-world CO2 and NOX emissions were also constructed. The CO2 emissions of hybrid buses were much less sensitive to the average speed than conventional buses. If the average speed decreased from 20 km h−1 to 10 km h−1, the estimated CO2 emission factor for conventional buses would be increased by 34%. Such a change in speed would increase NOX emissions for conventional and hybrid buses by 38% and 56%, respectively. This paper demonstrates the useful features of the remote OBD system and can inform policy makers how to take advantage of these features in monitoring in-use vehicles.