Spatial-temporal prediction of air quality based on recurrent neural networks

To predict air quality (PM2.5 concentrations, et al), many parametric regression models have been developed, while deep learning algorithms are used less often. And few of them takes the air pollution emission or spatial information into consideration or predict them in hour scale. In this paper, we proposed a spatial-temporal GRU-based prediction framework incorporating ground pollution monitoring (GPM), factory emissions (FE), surface meteorology monitoring (SMM) variables to predict hourly PM2.5 concentrations. The dataset for empirical experiments was built based on air quality monitoring in Shenyang, China. Experimental results indicate that our method enables more accurate predictions than all baseline models and by applying the convolutional processing to the GPM and FE variables notable improvement can be achieved in prediction accuracy

Aircraft Observations of Dust and Pollutants over NE China: Insight into the Meteorological Mechanisms of Long-Range Transport

Substantial concentrations of trace gases and aerosols are lofted and carried from Asia over the Pacific producing an inter-hemispheric impact on atmospheric chemistry and climate. The meteorological mechanism leading to this large-scale transport of dust and pollutants remains a major uncertainty in quantifying the global effects of emissions from the developing world. Models and downwind measurements have identified isentropic advection associated with wave cyclones (warm conveyor belt circulation) as an important mechanism. We present data from a case study conducted over Shenyang in NE China as part of EAST-AIRE in April 2005 in which upstream convection, rather than WCB lofting appears to dominate. Observations from instrumented aircraft flights, back trajectories, and satellite images of clouds (GOES) and aerosols (MODIS) are analyzed. In this heavily industrialized and populated region, the warm-sector PBL air ahead of a cold front was highly polluted. In the free troposphere, between ~1000 and 4000 m altitude, concentrations of trace gases and aerosols were lower, but well above background; we measured ~70 ppb O3, ~300 ppb CO, ~2 ppb SO2, and ~ 8x10-5 m-1 aerosol scattering. These observations show that dry (non-precipitating) convection can be an important mechanism for converting local air pollution problems into regional or global atmospheric chemistry problems. Climatological data indicate that spring (MAM) precipitation over NE China is low, about 90 mm compared to 290 mm over the NE US. Cloud cover, however, is similar with cumulus clouds reported about 7% of the time over NE China and about 9% of the time over the NE US suggesting that lofting in dry convective events may be common over NE Asia. Evaluation of models’ convective schemes and further observations near the source regions are called for.NS

Behavior analysis and risk assessment of atmospheric polycyclic aromatic hydrocarbons in cities under the East Asian monsoon climate

13301甲第5386号博士（創薬科学）金沢大学博士論文本文Full 以下に掲載：Environmental Pollution 287(15) Article No.117360 9p. 2021. Elsevier B.V.. 共著者：Lu Yang, Lulu Zhang, Lijiang Chen, Chong Han, Tomoko Akutagawa, Osamu Endo, Masahito Yamauchi, Andrey Neroda, Akira Toriba, Ning Tan

Air Quality Prediction in Smart Cities Using Machine Learning Technologies Based on Sensor Data: A Review

The influence of machine learning technologies is rapidly increasing and penetrating almost in every field, and air pollution prediction is not being excluded from those fields. This paper covers the revision of the studies related to air pollution prediction using machine learning algorithms based on sensor data in the context of smart cities. Using the most popular databases and executing the corresponding filtration, the most relevant papers were selected. After thorough reviewing those papers, the main features were extracted, which served as a base to link and compare them to each other. As a result, we can conclude that: (1) instead of using simple machine learning techniques, currently, the authors apply advanced and sophisticated techniques, (2) China was the leading country in terms of a case study, (3) Particulate matter with diameter equal to 2.5 micrometers was the main prediction target, (4) in 41% of the publications the authors carried out the prediction for the next day, (5) 66% of the studies used data had an hourly rate, (6) 49% of the papers used open data and since 2016 it had a tendency to increase, and (7) for efficient air quality prediction it is important to consider the external factors such as weather conditions, spatial characteristics, and temporal features

Emissions, Transport, and Evolution of Atmospheric Pollutants from China: An Observational Study

China's air pollution issue, a byproduct of recent phenomenal economic growth, has received increasing attention in light of its local and large-scale impacts. I investigated the emissions, transport, and evolution of pollutants from China using measurements near some source regions in northern China in 2005. Surface pollution near Beijing in March was overall heavy but changed dramatically, as passing mid-latitude cyclones led to fast transitions between polluted prefrontal and clean postfrontal conditions. Large differences found between measurements and inventories suggest substantial uncertainties in emission estimates. Small, coal-fired boilers are shown unlikely to be the major source of inventory error; experiments measuring traffic emissions are called for. Ground-level aerosols absorb light and are from both wind-blown dust and anthropogenic emissions. Their effects on climate are to be further studied. Pollutants at higher altitudes are more likely to have large-scale impact than pollutants that remain near the surface. The aircraft campaign in April was among the first efforts to measure the vertical distribution of pollutants over inland China. The largest pollutant levels observed in the free troposphere during the campaign were related to dry convective lofting over an industrial region. This differs from earlier experiments over the Pacific, which recognized the warm conveyor belt (WCB) as the main lofting mechanism. Dry convection over the continent may be followed by WCB lifting as the systems move out over the ocean. Their relative roles are yet to be determined. Analyses of meteorological and satellite cloud data reveal the importance of in-cloud processing in oxidizing SO2 transported behind cold fronts. Through integration of satellite sensors, in-situ measurements, trajectory and chemical transport models, I tracked a pollution plume as it traveled away from source region. The decay of SO2 in the plume over three days was quantified, suggesting an SO2 lifetime of 1-4 d. Formation of sulfate and loss of dust together changed the aerosol loading of the plume. This analysis showcases the potential for employing satellites to trace transport events and pollutant evolution, and highlights the main uncertainties in quantitative application of satellite data

Sustainability in China: Bridging Global Knowledge with Local Action

China’s road to sustainability has attracted global attention. Since the “Reform & Opening Up” policy, China’s rapid pace of both urbanization and industrialization has made its being the second largest economy but meantime a heavy environmental price has been paid over the past few decades for addressing the economic developmental target. Today, as the biggest developing country, China needs to take more responsibilities for constructing its local ecological-civilization society as well as for addressing the global challenges such as climate change, resources scary and human beings well-fare; therefore, we need to have deeper understandings into China’s way to sustainability at very different levels, both spatially and structurally, concerns ranging from generating sustainable household livelihoods to global climate change, from developing technological applications to generate institutional changes. In this spirit, this publication, “Sustainability in China: Bridging Global Knowledge with Local Action” aims to investigate the intended and spontaneous issues concerning China’s road to sustainability in a combined top-down and bottom-up manner, linking international knowledge to local-based studies

Quantifying and modeling ecosystem services provided by urban greening in cities of the Southern Alps, N Italy

Population growth in urban areas is a world-wide phenomenon. According to a recent United Nations report, over half of the world now lives in cities. Numerous health and environmental issues arise from this unprecedented urbanization. Recent studies have demonstrated the effectiveness of urban green spaces and the role they play in improving both the aesthetics and the quality of life of its residents. In particular, urban green spaces provide ecosystem services such as: urban air quality improvement by removing pollutants that can cause serious health problems, carbon storage, carbon sequestration and climate regulation through shading and evapotranspiration. Furthermore, epidemiological studies with controlled age, sex, marital and socio-economic status, have provided evidence of a positive relationship between green space and the life expectancy of senior citizens. However, there is little information on the role of public green spaces in mid-sized cities in northern Italy. To address this need, a study was conducted to assess the ecosystem services of urban green spaces in the city of Bolzano, South Tyrol, Italy. In particular, we quantified the cooling effect of urban trees and the hourly amount of pollution removed by the urban forest. The information was gathered using field data collected through local hourly air pollution readings, tree inventory and simulation models. During the study we quantified pollution removal for ozone, nitrogen dioxide, carbon monoxide and particulate matter (<10 microns). We estimated the above ground carbon stored and annually sequestered by the urban forest. Results have been compared to transportation CO2 emissions to determine the CO2 offset potential of urban streetscapes. Furthermore, we assessed commonly used methods for estimating carbon stored and sequestered by urban trees in the city of Bolzano. We also quantified ecosystem disservices such as hourly urban forest volatile organic compound emissions

First Assessment of NOx Sources at a Regional Background Site in North China Using Isotopic Analysis Linked with Modeling

important role in the formation of atmospheric particles. Thus, NOx emission reduction is critical for improving air quality, especially in severely air-polluted regions (e.g., North China). In this study, the source of NOx was investigated by the isotopic composition (delta N-15) of particulate nitrate (p-NO3-) at Beihuangcheng Island (BH), a regional background site in North China. It was found that the delta N-15-NO3- (n = 120) values varied between -1.7 parts per thousand and +24.0 parts per thousand and the delta O-18-NO3- values ranged from 49.4 parts per thousand to 103.9 parts per thousand. On the basis of the Bayesian mixing model, 27.78 +/- 8.89%, 36.53 +/- 6.66%, 22.01 +/- 6.92%, and 13.68 +/- 3.16% of annual NOx could be attributed to biomass burning, coal combustion, mobile sources, and biogenic soil emissions, respectively. Seasonally, the four sources were similar in spring and fall. Biogenic soil emissions were augmented in summer in association with the hot and rainy weather. Coal combustion increased significantly in winter with other sources showing an obvious decline. This study confirmed that isotope-modeling by delta N-15-NO3- is a promising tool for partitioning NOx sources and provides guidance to policymakers with regard to options for NOx reduction in North China