The relationships between PM2.5 and meteorological factors in China: Seasonal and regional variations

The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the relationships between PM2.5 concentration and meteorological conditions have been mainly confined to a certain city or district, and the correlation over the whole of China remains unclear. Whether or not spatial and seasonal variations exit deserves further research. In this study, the relationships between PM2.5 concentration and meteorological factors were investigated in 74 major cities in China for a continuous period of 22 months from February 2013 to November 2014, at season, year, city, and regional scales, and the spatial and seasonal variations were analyzed. The meteorological factors were relative humidity (RH), temperature (TEM), wind speed (WS), and surface pressure (PS). We found that spatial and seasonal variations of their relationships with PM2.5 do exist. Spatially, RH is positively correlated with PM2.5 concentration in North China and Urumqi, but the relationship turns to negative in other areas of China. WS is negatively correlated with PM2.5 everywhere expect for Hainan Island. PS has a strong positive relationship with PM2.5 concentration in Northeast China and Mid-south China, and in other areas the correlation is weak. Seasonally, the positive correlation between PM2.5 concentration and RH is stronger in winter and spring. TEM has a negative relationship with PM2.5 in autumn and the opposite in winter. PS is more positively correlated with PM2.5 in autumn than in other seasons. Our study investigated the relationships between PM2.5 and meteorological factors in terms of spatial and seasonal variations, and the conclusions about the relationships between PM2.5 and meteorological factors are more comprehensive and precise than before.Comment: 3 tables, 13 figure

Land-Use Regression Modelling of Intra-Urban Air Pollution Variation in China: Current Status and Future Needs

Rapid urbanization in China is leading to substantial adverse air quality issues, particularly for NO2 and particulate matter (PM). Land-use regression (LUR) models are now being applied to simulate pollutant concentrations with high spatial resolution in Chinese urban areas. However, Chinese urban areas differ from those in Europe and North America, for example in respect of population density, urban morphology and pollutant emissions densities, so it is timely to assess current LUR studies in China to highlight current challenges and identify future needs. Details of twenty-four recent LUR models for NO2 and PM2.5/PM10 (particles with aerodynamic diameters <2.5 µm and <10 µm) are tabulated and reviewed as the basis for discussion in this paper. We highlight that LUR modelling in China is currently constrained by a scarcity of input data, especially air pollution monitoring data. There is an urgent need for accessible archives of quality-assured measurement data and for higher spatial resolution proxy data for urban emissions, particularly in respect of traffic-related variables. The rapidly evolving nature of the Chinese urban landscape makes maintaining up-to-date land-use and urban morphology datasets a challenge. We also highlight the importance for Chinese LUR models to be subject to appropriate validation statistics. Integration of LUR with portable monitor data, remote sensing, and dispersion modelling has the potential to enhance derivation of urban pollution maps

Analysis of Chengdu air quality pollution based on logistic sequential multi-classification of distance between classes

Air quality is closely related to people’s health. It is very important to analyze the pollutants affecting air quality. The sequential Logistic multi-classification method of inter class distance was used to analyze the air quality data of Chengdu from May 2019 to April 2020. Based on the inter class distance, the multi classification problem was transformed into multiple binary classification problems, and then the binary classification Logistic was used based on the sequential principle. Finally, the correct rate after stepwise regression was used to analyze the pollutants affecting air quality. Experimental results show that the four types of pollutants PM2.5, PM10, NO2 and O3 have the greatest comprehensive impact on air quality of Chengdu. The government should strengthen joint monitoring of these types of pollutants and formulate corresponding policies to reduce pollutants

Clean heating and heating poverty: A perspective based on cost-benefit analysis

To improve the air quality in winter, clean heating policy was implemented in “2 + 26” cities of China in 2016, which mainly included replacing coal with gas or electricity. Tremendous financial subsidies have been provided by city and central governments. This new heating mode changed the heating fee-cost to residents. This paper estimates the economic costs to both governments and residents, and evaluates the environmental and public health benefits by combining a difference-in-differences model with an exposure-response function. Results show that the total costs of clean heating were up to 43.1 billion yuan. Governments and residents account for 44% and 56% of the total costs, respectively. In terms of benefits, the clean heating project is effective for air pollution control and brings health economic benefits of about 109.85 billion yuan (95% CI: 22.40–159.83). The clean heating policy was identified as a net-positive benefit program with environmental and public health improvements. However, the inequality in subsidies from different cities governments increases the heating burden on low-income households and leads to heating poverty for households in the less developed regions. We provide suggestions for implementation in future clean heating campaigns and in subsidy mechanism design in China and for other developing countries

Measurement Report: Investigation on the sources and formation processes of dicarboxylic acids and related species in urban aerosols before and during the COVID-19 lockdown in Jinan, East China

Dicarboxylic acid (diacid) homologs are essential indicators of secondary organic aerosols (SOA) that exert a considerable influence on climate changes and atmospheric chemistry. However, their sources and formation processes are poorly understood, leading to uncertainty in predicting the climate effect of SOA. A substantial drop in anthropogenic emissions during the COVID-19 lockdown (LCD) provides a “controlled experiment” to explore the effects of LCD measures and meteorological conditions on SOA. Here we investigated the difference in molecular distributions and stable carbon isotopic compositions (δ13C) of diacid homologs in PM2.5 before and during the LCD. We found that the concentration and contribution of diacid homologs during the LCD were higher than before the LCD, indicating that the enhanced secondary oxidation could offset the reduction in anthropogenic emissions during the LCD. A higher oxalic acid (C2) / diacid ratio and more positive δ13C values of major diacids during the LCD suggested more aged organic aerosols. The enhanced C2 and related species during the LCD were mainly derived from the promoted gaseous photochemical oxidation by the higher oxidants and stronger solar radiation. However, C2 and related species before the LCD were dominantly derived from the aqueous oxidation of α-dicarbonyls depending on relative humidity and liquid water content. The increased δ13C values of C2 and other major diacids along with the high ratios of C2 / glyoxal, C2 / methylglyoxal, and C2 / diacid confirmed an isotopic fractionation effect during the oxidation process of precursors. Our results indicate that atmospheric pollution treatment depends on a balanced strategy and a coordinated effort to control multiple pollutants.</p

Influence of Cloud/Fog on Atmospheric VOCs in the Free Troposphere: A Case Study at Mount Tai in Eastern China

International audienceField measurements of volatile organic compounds (VOCs) were conducted in July of 2015 at Mount Tai, where 63 species of VOCs were measured using GC-MS. In this study, air samples were collected in two different weather conditions: cloud/fog and non-cloud/fog respectively and influences of the cloud/fog on VOCs species were analyzed. The sources of air masses were calculated by back trajectories with HYSPLIT model. Five main kinds of VOCs were analyzed and oxy-VOCs (OVOCs) had the largest contribution (67% on the cloudy/foggy days and 72% on the non-cloudy/foggy days) to total measured VOCs among all of the samples collected at Mount Tai. Acetone was the most abundant compound (18 ppb on the cloudy/foggy days and 15 ppb on the non-cloudy/foggy days) among the VOCs. The concentrations of VOCs collected in cloudy/foggy days were higher than those measured in non-cloudy/foggy days and indicated that cloudy/foggy days favoured the accumulation of atmospheric VOCs. However, the concentrations of most OVOCs in non-cloud/fog conditions were higher than those in cloud/fog conditions. Atmospheric photochemical reactions may partly account for this result. Air mass trajectory analysis shows that most air masses from heavily polluted areas results in the increase of atmospheric VOCs. OVOCs and aromatics provided the main contribution to ozone formation potential. Besides cloud and fog, VOC concentration is concerned with integrated factors including temperature, relative humidity, wind speed and direction

Levels of PM2.5-bound species in Beijing, China: Spatio-temporal distributions and human health risks

High concentrations of PM2.5 and the corresponding health effect in Beijing, China have drawn attention worldwide. This study aims to assess the lifetime health risk of ambient PM2.5 bound elements and polycyclic aromatic hydrocarbons (PAHs) from 2013 to 2015 in Beijing. Risk assessment methods of US Environment Protection Agency (USEPA) were applied to the following PM2.5 components: six elemental components (Cr, Co, Ni, As, Cd, Pb) and sixteen EPA priority PAHs for cancer risks, and thirteen non- elemental components (Al, Ba, Cr, Mn, Ni, As, Cd, Pb, Co, V, P, Cl, Se) for non-cancer risks. Spatial and temporal variations of health risks were examined across Beijing. Source apportionment was applied to apportion the risks. The estimated lifetime cancer risk due to exposure to ambient PM2.5 in Beijing is 2.30E-02. This cancer risk level is two magnitudes higher than EPA upper threshold of 1.00E-04. Thus, remediation is desirable. Lifetime non-cancer hazard quotient in Beijing is 13.7, higher than EPA upper threshold of non-cancer hazard quotient (1.0), indicating that some non-cancer health impacts may also occur. Seasonal cancer risks range 7.47E-03 to 4.78E-03. Summer and winter have higher percentages of 31% and 26% respectively to the total lifetime risk, while lower in spring (23%), and autumn (20%). Seasonal non-cancer hazard quotients in Beijing range 4.5 to 26.2. Winter contributed approximate 52% of total non-cancer hazard quotient, followed by spring (21%), autumn (18%), and summer (9%). Lifetime cancer risk is higher in suburban area (3.53E-02) than in urban area (1.82E-02), while hazard quotient is higher in urban area (14.3) than suburban area (2.6). Overall, both lifetime cancer and non-cancer risks in Beijing are higher than the corresponding USEPA threshold. The health risks in Beijing are all higher than other cities in China, Windsor, and Mexico