A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of \(\text {NO}_{x}\) in the Los Angeles area during a 10 year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated \(R^2\) of approximately \(0.7\) at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.     

沙尘与大雾天气对京津石空气质量影响

采用北京、天津、石家庄2001-2010年沙尘与大雾天气的统计数据以及城市空气污染指数（API）,分析北京、天津、石家庄3市空气污染指数变化特征及大雾和沙尘天气下北京、天津、石家庄3市空气质量情况,进而得出沙尘大雾天气对京津石空气质量的影响。结果表明：2001-2010年间北京、天津、石家庄3市API总体呈下降趋势,天津、石家庄相对于北京空气质量改善较为明显,且空气质量夏季〉秋季〉春冬季。沙尘天气条件下,北京、天津、石家庄3市API平均值分别为255、179和167,空气质量出现良的比率天津为24%,北京、石家庄为10%左右,出现重污染的比率北京高达50%以上,天津和石家庄均在20%左右;3市沙尘天气高频次均出现在3-5月份,但北京沙尘天气发生次数远大于天津和石家庄。大雾天气条件下,北京、天津、石家庄3市API平均值为185、130和167,空气质量出现优或良的比率：天津〉石家庄〉北京,北京和石家庄出现重污染的比率均接近30%,天津不到10%,所以大雾天气对3市空气质量影响较小,大雾天气频次的变化波动并未对该地区空气质量的年际变化造成显著影响,3市高频次大雾天气集中在10-12月份,对该时段内空气污染呈现加重趋势有一定的贡献。所以沙尘和大雾天气均对北京、天津和石家庄空气质量存在不利影响,其中对北京影响最为严重,对天津影响最轻。整体上沙尘对3市的空气质量影响较大,大雾天气影响较小。     

北京城市温室气体排放清单基础研究

回顾中国城市,主要是北京温室气体排放研究和排放状况,结合目前国际上主要采用的城市清单方法,梳理北京温室气体排放清单,并利用收集的北京市基本资料进行相关分析,作为北京和洛杉矶温室气体清单比较研究的基础.通过分析可以看出,中国城市温室气体清单的编制需要大量精确的数据作为支撑,但目前由于在统计口径上与国际上通用的排放清单有差...     

Air pollution and its control in China

The rapid growth of China’s economy has led to severe air pollution characterized by acid rain, severe pollution in cities, and regional air pollution. High concentrations are found for various pollutants such as sulfur dioxides (SO₂), nitrogen oxides (NO_x), and fine particulates. Great efforts have thus been undertaken for the control of air pollution in the country. This paper discusses the development and application of appropriate technologies for reducing the major pollutants produced by coal and vehicles, and investigates air quality modeling as an important support for policy-making.     

Impact of energy structure adjustment on air quality: a case study in Beijing, China

Energy consumption is a major cause of air pollution in Beijing, and the adjustment of the energy structure is of strategic importance to the reduction of carbon intensity and the improvement of air quality. In this paper, we explored the future trend of energy structure adjustment in Beijing till 2020, designed five energy scenarios focusing on the fuel substitution in power plants and heating sectors, established emission inventories, and utilized the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality Model (CMAQ) to evaluate the impact of these measures on air quality. By implementing this systematic energy structure adjustment, the emissions of PM₁₀, PM_2.5, SO₂, NO _x , and non-methane volatile organic compounds (NMVOCs) will decrease distinctly by 34.0%, 53.2%, 78.3%, 47.0%, and 30.6% respectively in the most coalintensive scenario of 2020 compared with 2005. Correspondingly, MM5-Models-3/CMAQ simulations indicate significant reduction in the concentrations of major pollutants, implying that energy structure adjustment can play an important role in improving Beijing??s air quality. By fuel substitution for power plants and heating boilers, PM₁₀, PM_2.5, SO₂, NO _x , and NMVOCs will be reduced further, but slightly by 1.7%, 4.5%, 11.4%, 13.5%, and 8.8% respectively in the least coal-intensive scenario. The air quality impacts of different scenarios in 2020 resemble each other, indicating that the potential of air quality improvement due to structure adjustment in power plants and heating sectors is limited. However, the CO₂ emission is 10.0% lower in the least coal-intensive scenario than in the most coal-intensive one, contributing to Beijing??s ambition to build a low carbon city. Except for energy structure adjustment, it is necessary to take further measures to ensure the attainment of air quality standards.     

城市大气污染综合治理规划方法

以北京市2008年三种主要大气污染物PM10、SO2及NOx环境空气质量达标方案的设计为案例，从城市大气污染综合治理规划方法学角度，提出并发展了一套包括环境空气质量的模拟、城市背景浓度的确定、优化模型、传输矩阵、分区规划、等效排放、措施信息库等方法在内的城市大气污染综合治理规划问题的整体解决的技术方案，为全国其它类似城市进行大气污染综合治理规划提供一种实例与参考，同时，研究的结果对北京市2008年大气污染控制对策的制定提供了科学的依据。     

Air quality analysis and indexing of Kolkata city with respect to vertical floor heights and seasonal variation

Air pollution is one of the most important global environmental issues. Urban air quality is generally becoming vulnerable especially in the developing countries due to various developmental activities. Several national and international studies prove that air pollution is harmful to human health and its long term exposure contributes to even mortality. Current study has been designed to determine the vertical floor wise air quality status of the city of Kolkata and the seasonal variation of the pollutants during two consecutive years. Particulate matter (PM₁₀ and suspended particulate matter), oxides of nitrogen, sulfur dioxide and carbon monoxide were analyzed for a total number of 135 air quality samples throughout the study area and period. Pollutants were found positively correlated with each other and with the floor heights. According to the air quality indexing, all the places were found affected from moderate to severe air pollution irrespective of the vertical floor heights, seasons and places. Although, no such seasonal trend has been emerged from the study but the number of samples beyond standard is found highest during the winter season followed by pre-monsoon.     

China’s carbon neutrality: an extensive and profound systemic reform

● China has pledged ambitious carbon peak and neutrality goals for mitigating global climate change. ● Major challenges to achieve carbon neutrality in China are summarized. ● The new opportunities along the pathway of China’s carbon neutrality are discussed from four aspects. ● Five policy suggestions for China are provided. China is the largest developing economy and carbon dioxide emitter in the world, the carbon neutrality goal of which will have a profound influence on the mitigation pathway of global climate change. The transition towards a carbon-neutral society is integrated into the construction of ecological civilization in China, and brings profound implications for China’s socioeconomic development. Here, we not only summarize the major challenges in achieving carbon neutrality in China, but also identify the four potential new opportunities: namely, the acceleration of technology innovations, narrowing regional disparity by reshaping the value of resources, transforming the industrial structure, and co-benefits of pollution and carbon mitigation. Finally, we provide five policy suggestions and highlight the importance of balancing economic growth and carbon mitigation, and the joint efforts among the government, the enterprises, and the residents.     

Does subway expansion improve air quality?

Major cities in China and many other fast-growing economies are expanding their subway systems in order to address worsening air pollution and traffic congestion. This paper quantifies the impact of subway expansion on air quality by leveraging fine-scale air quality data and the rapid build-out of 14 new subway lines and 252 stations in Beijing from 2008 to 2016. Our main empirical framework examines how the density of the subway network affects air quality across different locations in the city during this period. To address the potential endogenous location of subway stations, we construct an instrument based on historical subway planning, long before air pollution and traffic congestion were of concern. Our analysis shows that an increase in subway density by one standard deviation improves air quality by two percent and the result is robust to a variety of alternative specifications including the distance-based difference-in-differences method. The total discounted health benefit during a 20-year period from reduced mortality and morbidity as a result of 14 new subway lines amounts to $1.0–3.1 billion, or only 1.4–4.4 percent of the total construction and operating cost.     

EU air pollution regulation: A breath of fresh air for Eastern European polluting industries?

Does air quality regulation in the European Union (EU) foster polluting activity in emerging and developing countries? In this paper, we propose an original variable that evaluates regulation stringency, based on the EU Air Quality Framework Directive. Focusing on the underlying mechanism and controlling for endogeneity in the relation between regulation and trade, we provide robust evidence that EU countries implementing more stringent air pollution regulations import relatively more in pollution-intensive sectors from developing and emerging countries in Europe and Central Asia.