Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand

Annual and monthly-based emission inventories in northern, central and north-eastern provinces in Thailand, where agriculture and related agro-industries are very intensive, were estimated to evaluate the contribution of agricultural activity, including crop residue burning, forest fires and related agro-industries on air quality monitored in corresponding provinces. The monthly-based emission inventories of air pollutants, or, particulate matter (PM), NOx and SO₂, for various agricultural crops were estimated based on information on the level of production of typical crops: rice, corn, sugarcane, cassava, soybeans and potatoes using emission factors and other parameters related to country-specific values taking into account crop type and the local residue burning period. The estimated monthly emission inventory was compared with air monitoring data obtained at monitoring stations operated by the Pollution Control Department, Thailand (PCD) for validating the estimated emission inventory. The agro-industry that has the greatest impact on the regions being evaluated, is the sugar processing industry, which uses sugarcane as a raw material and its residue as fuel for the boiler. The backward trajectory analysis of the air mass arriving at the PCD station was calculated to confirm this influence. For the provinces being evaluated which are located in the upper northern, lower northern and northeast in Thailand, agricultural activities and forest fires were shown to be closely correlated to the ambient PM concentration while their contribution to the production of gaseous pollutants is much less.     

北京冬奥会同期空气污染数值模拟

第24届冬季奥运会将于2022年2月4—20日在我国北京市和河北省张家口市联合举办,主要会场有北京奥体中心、北京延庆县和张家口市崇礼县.为了模拟分析冬奥会空气质量情况,利用冬奥会同期(2006—2016年2月)北京市和张家口市空气质量资料及韩国气象厅天气图资料(2013—2016年2月),分析该时段重污染发生的频次,统计不利于污染物扩散的天气形势出现概率及污染传输路径,并结合嵌套网格空气质量预报模式(NAPQMS),评估不同减排方案对ρ(PM_2.5)的影响.结果表明:① 2006—2016年冬奥会同期,北京奥体中心和延庆县发生重污染天气的概率分别为17%和9%,污染发生的风险频率为北京奥体中心>延庆县>张家口市,并且北京奥体中心和延庆县在2月13—16日易出现持续的重污染天气过程;② 2013—2016年2月不利于污染扩散的天气形势出现概率较为频繁,尤其在850 hPa高度和地面,不利天气形势出现的概率分别为35%和41%;地面偏南风易将在北京西南方滞留较长时间的污染气团沿太行山输送至北京;③ 冬奥会期间,若于2月2—12日及17—20日将京津冀及周边城市污染物排放量在当前的基础上减排50%、2月13—16日减排75%,将可能不出现重污染日.严格控制北京及周边地区的大气污染物排放是保障冬奥会期间空气质量的必要措施.      

Determination of 15 phthalate esters in air by gas-phase and particle-phase simultaneous sampling

Based on previous research, the sampling and analysis methods for phthalate esters (PAEs) were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 hr. Meanwhile, through the optimization of chromatographic conditions, the concentrations of 9 additional PAE pollutants in indoor air were measured. The optimized chromatographic conditions required a similar amount of time for analysis as before, but gave high responsivity, the capability of simultaneously distinguishing 15 kinds of PAEs, and a high level of discrimination between individual sample peaks, as well as stable peak generation. The recovery rate of all gas-phase and particle-phase samples of the 15 kinds of PAEs ranged from 91.26% to 109.42%, meeting the quantitative analysis requirements for indoor and outdoor air sampling and analysis. For the first time, investigation of the concentration levels as well as characteristics of 15 kinds of PAEs in the indoor air from four different traffic micro-environments (private vehicles, busses, taxis and subways) was carried out, along with validation of the optimized sampling and analytical method. The results show that all the 9 additional PAEs could be detected at relatively high pollution levels in the indoor air from the four traffic micro-environments. As none of the pollution levels of the 15 kinds of PAEs in the indoor air from the 4 traffic micro-environments should be neglected, it is of great significance to increase the types of PAEs able to be detected in indoor air.     

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing–Tianjin–Hebei region, China

In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km~2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m~3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively.     

基于T-S模糊神经网络的大沽河水质变化特征分析研究

基于T-S模糊神经网络,利用大沽河2010年-2015年水质监测数据,选取溶解氧、化学需氧量、高锰酸盐指数、氨氮、总氮、总磷对水质具有重要影响的6项指标,建立适用的水质评价模型,对大沽河水质变化特征进行分析.结果显示:上游水质评价结果明显优于中游、下游水质评价结果,网络评价水质等级变化趋势同真实指标数据变化趋势一致.验证结果充分表明了T-S模糊神经网络用于水质变化特征分析是可行、有效的.     

关中地区城市空气质量特征及影响因素分析

本文对陕西省关中地区33个城市环境空气质量自动监测站点2015年全年的监测数据进行统计和研究,讨论了关中城市空气质量特征和主要影响因素。结果表明,关中地区城市间空气质量具有密切的相关性和整体性,影响关中城市群全年空气质量最主要的污染因子是可吸入颗粒物(PM10)和细颗粒物(PM2.5),首要污染物呈现出显著的季节变化规律。人类活动、气象因素以及地形特征是造成关中地区空气质量现状的主要原因。     

哈尔滨市环境空气质量评价与经济增长关系研究

以PM10、SO2和NO2作为空气质量的评价对象,采用空气综合污染指数法研究了哈尔滨市2001年到2015年的环境空气质量变化趋势.以空气综合污染指数作为因变量,哈尔滨市人均GDP作为自变量,来探讨哈尔滨环境空气质量与经济增长之间的关系.得出2001年到2015年期间,哈尔滨环境空气质量呈现先变好又变差再变好的趋势,哈尔滨环境空气质量与经济增长之间呈现近似三次方函数关系,且部分呈现到"U"型曲线关系.     

遂宁市主城区环境空气质量现状及原因分析研究

利用遂宁市2017年1月份4个国控环境空气自动监测数据,分析了遂宁市主城区环境空气质量现状,与整个成渝地区和周边城市的空气质量进行了横向比较,并阐述了遂宁市空气质量变化的原因.结果发现遂宁市主城区2017年1月份空气质量指数的范围为32～203,优良率为54.8％,首要污染物为PM2.5,空气质量同比下降了22.8％,环比下降了26.1％,但均显著优于成渝地区和周边城市的平均水平,并从4个方面阐述了空气质量下降的原因.最后,根据遂宁市大气污染现状,提出了4条针对性的防治措施.     

层次分析模型在室内空气质量评价中的应用研究

当前评价方法没有考虑室内空气质量界线的模糊性,不能真实反映室内空气品质,导致评价结果不准确.提出基于层次分析模型的室内空气质量评价方法,建立室内空气质量评价目标层、准则层和措施层三层递阶的层次结构模型,构造判断矩阵,计算特征向量,得到各自的层次总排序结果,结合室内空气质量评价各指标权重,计算空气各污染物的隶属函数,求导室内空气质量最终评价值.实验结果表明,所提方法获得的室内空气质量评价值与实际调查监测值一致,能够真实反映室内空气质量状况,具有较高的可靠性.     

基于微信公众平台的空气质量显示系统的设计与实现研究

空气质量的好坏直接影响着人类的出行和健康,创建便于查询的空气质量显示系统,可以使人们简单直观的了解当日的空气质量指数(AQI).随着互联网的迅猛发展,"微信"逐渐成了人们日常通信的重要工具.本系统利用物联网技术与微信公众平台相结合,提出了空气质量显示系统的设计与实现方案,来建设空气质量显示系统.该系统可从各个区内监测点得到空气质量指数数据,进而将每日各个时段的空气质量指数(AQI)以动态图的方式直观清晰的展示给用户,为人们的出行带来了方便.