Air assimilative capacity-based environment friendly siting of new industries--a case study of Kochi region, India

Air pollution has become a matter of grave concern, particularly in mega-cities and urban areas, where the situation is alarming and becoming more and more severe day-by-day and warrants, therefore, careful planning to facilitate future industrial development. Site selection, with the objective of minimizing adverse environmental impacts based on environmental criteria is a vital prerequisite, particularly for air polluting industries. In order to locate any air polluting industry, the assimilative capacity of the region needs to be assessed carefully and planned accordingly, so that the receiving environment is not adversely affected. Assimilative capacity of a region/airshed, widely represented through the ventilation coefficient by many researchers in the past, does not give a clear picture about the amount of emission load that can be assimilated in a given region. The ventilation coefficient, at best, can only present a broad picture about the air pollution dispersion potential (low, medium or high) of the region. A modified approach, which utilizes air quality modelling as a tool to estimate the maximum allowable emission load that a region can assimilate without violating the stipulated standards, has been used for estimating the assimilative capacity of the air environment. Details of this approach have been presented in this paper through a case study carried out for the Kochi region, located in the Kerala State of India. A variety of emission and meteorological scenarios have been considered and critical emission loads have been estimated. This approach shall provide necessary technical guidance to the environmental regulatory authorities as well as to the industries in planning environment friendly industrial development.     

A framework for assessing the impact of land use policy on community exposure to air toxics

Our research focuses on the linkage between land use planning policy and the spatial pattern of exposure to air toxics emissions. Our objective is to develop a modeling framework for assessment of the community health risk implications of land use policy. The modeling framework is not intended to be a regulatory tool for small-scale land use decisions, but a long-range planning tool to assess the community health risk implications of alternative land use scenarios at a regional or subregional scale. This paper describes the development and application of an air toxic source model for generating aggregate emission factors for industrial and commercial zoning districts as a function of permitted uses. To address the uncertainty of estimating air toxics emission rates for planned general land use or zoning districts, the source model uses an emissions probability mass function that weights each incremental permitted land use activity by the likelihood of occurrence. We thus reduce the uncertainty involved in planning for development with no prior knowledge of the specific industries that may locate within the land use district. These air toxics emission factors can then be used to estimate pollutant atmospheric mass flux from land use zoning districts, which can then be input to air dispersion and human health risk assessment models to simulate the spatial pattern of air toxics exposure risk. The model database was constructed using the California Air Toxics Inventory, 1997 US Economic Census, and land assessment records from several California counties. The database contains information on more than 200 air toxics at the 2-digit Standard Industrial Classification (SIC) level. We present a case study to illustrate application of the model. LUAIRTOX, the interactive spreadsheet model that applies our methodology to the California data, is available at http://www2.bren.ucsb.edu/~mwillis/LUAIRTOX.htm.     

Developing the interaction matrix technique as a tool assessing the impact of traffic on air quality

This paper develops a technique which can be used as a preliminary tool for assessing air quality related to urban traffic. It combines a Geographic Information System (GIS) with an interaction matrix-type methodology based on a system analysis approach. The matrix identifies and quantifies interactions between all selected variables involved in a system as well as their interaction with the system as a whole. This matrix is used to determine the weightings to apply to spatial datasets within a GIS to develop a pollution vulnerability map. The focus of the paper is to introduce and assess a more versatile coding of the interaction matrix with respect to previously used coding. A case study is presented in which the modified interaction methodology is applied to data for a busy urban location. The resulting vulnerability map, in terms of pollution vulnerable hot spots, was compared to a pollution map derived from an advanced dispersion model. The interaction matrix technique with GIS can be used as a tool complementary to sophisticated numerical modelling and has potential as an analytical tool to evaluate multidisciplinary systems.     

Environmental Equity and the Role of Public Policy: Experiences in the Rijnmond Region

This Φ Ψ study of environmental equity uses secondary quantitative data to analyze socioeconomic disparities in environmental conditions in the Rijnmond region of the Netherlands. The disparities of selected environmental indicators—exposure to traffic noise (road, rail, and air), NO₂, external safety risks, and the availability of public green space—are analyzed both separately and in combination. Not only exposures to environmental burdens (“bads”) were investigated, but also access to environmental benefits (“goods”). Additionally, we held interviews and reviewed documents to grasp the mechanisms underlying the environmental equity situation, with an emphasis on the role of public policy. Environmental equity is not a priority in public policy for the greater Rotterdam region known as the Rijnmond region, yet environmental standards have been established to provide a minimum environmental quality to all local residents. In general, environmental quality has improved in this region, and the accumulation of negative environmental outcomes (“bads”) has been limited. However, environmental standards for road traffic noise and NO₂ are being exceeded, probably because of the pressure on space and the traffic intensity. We found an association of environmental “bads” with income for rail traffic noise and availability of public green space. In the absence of regulation, positive environmental outcomes (“goods”) are mainly left up to market forces. Consequently, higher-income groups generally have more access to environmental “goods” than lower-income groups.     

通过屋顶暴露方法模拟聚碳酸酯微塑料在长江水样的长期老化行为

由于较低的自然老化速率,微塑料在实际水体长期户外暴露过程中老化行为的数据仍较缺乏.通过聚碳酸酯（Polycarbonate,PC）微塑料在长江表层水样的18个月户外暴露试验以揭示自然老化过程对微塑料表面特征及对金属离子(Cr⁶⁺和Co²⁺)吸附行为的重要影响.结果显示,户外暴露改变了PC微塑料的理化性质,包括表面开裂、粒径降低、亲水性和熔点增加以及表面氧化（产生羰基和羟基）.同时,户外老化过程明显影响微塑料对金属离子的吸附行为.原始和低老化程度PC对金属离子的吸附主要通过物理作用控制,而高老化程度微塑料由于产生含氧功能团对金属离子的吸附主要由化学过程如络合和共价键等作用控制.并且,不同老化程度PC微塑料对Cr⁶⁺和Co²⁺的吸附性能不同.对于Cr⁶⁺,PC的吸附性能随其老化程度增加呈先升高后降低的趋势,然而对于Co²⁺,平衡吸附性能随老化程度增加呈增加的趋势.户外老化过程产生含氧官能团、破碎和开裂以及生物膜可能是影响吸附性能的主要因素.本研究证实了长期户外...     

战斗部飞行可靠性评估方法研究

目的 解决高可靠、小子样战斗部飞行可靠性评估时样本量不满足标准要求的问题。方法 通过对战斗部结构功能分析,建立包含壳体强度、主装药安定性及主装药正常起爆等单元的可靠性框图,并利用L-M法对战斗部系统进行可靠性评估。首先利用基准设计许用值的安全系数法将应力强度干涉模型与安全系数进行结合,对壳体强度可靠性进行评估;然后结合战斗部试验数据,利用最大熵试验法,在小样本下评估战斗部主装药安定性及正常起爆的可靠性;最后,将各单元的可靠性数据转化为成败型数据进行分析,利用L-M法,结合战斗部整机试验数据,开展战斗部飞行可靠度评估。结果 分别计算了小子样下战斗部壳体和装药安定性及正常起爆的可靠度,并将其转换为等效成功数和等效失败数,结合战斗部试验打靶等可靠性信息,综合评估了战斗部飞行可靠度。结论 充分利用战斗部在研制阶段的试验信息进行评估,减少了样本量,解决了战斗部可靠性高、样本量小的评估难题。     

基于多元随机效应Wiener过程的某弹用弹簧可靠性评估

目的 解决某弹用弹簧可靠性评估中存在的不确定性问题。方法 对某弹用弹簧进行加速退化试验,试验过程中发现其具有多个性能退化参数,并且其退化过程具有非线性、随机性及样本差异性的特征。为了对其退化过程进行数学表征,提出一种基于多元随机效应Wiener过程的退化模型。采用基于时间尺度变换的非线性Wiener过程,描述弹簧退化过程中的非线性与随机性。基于随机效应模型,对样本的差异性进行表征,利用Copula函数描述多元性能参数之间的相互作用关系。最后推导弹簧失效寿命的概率密度函数、可靠度函数。结果 在贮存条件为25 ℃、可靠度为0.9时,基于构建的多元随机效应Wiener过程模型,当考虑性能间的相关性时,得到某弹用弹簧的贮存寿命为12 a;不考虑性能间的相关性时,得到其贮存寿命为11.5 a。结论 构建的多元随机退化模型为该弹药健康状态管理提供了相应的理论依据。     

Modelling individual preferences for environmental policy drivers: Empirical evidence of Italian lifestyle changes using a latent class approach

Degraded air quality severely affects the health of citizens worldwide. The design of effective policies requires exploring public preferences for environmental and air quality policy instruments. Within the EC-FP7 SEFIRA project, using a choice experiment that stresses the trade-offs between attributes, this study investigates public preferences for environmental policy drivers in Italy. The main objective is to investigate the role played by selected policy drivers in determining policy preferences, complemented by elasticity and willingness to pay estimations. Preference heterogeneity and the role of socio-economic and attitudinal variables are explored with a latent class model over 2400 respondents sampled across Italy. The results allow identifying the different role played by the policy drivers across the classes. It emerged that most of the respondents (43%) are particularly sensitive to the cost components (cost sensitive respondents). The remaining respondents instead show an important sensitivity towards personal engagement in term of changes in the mobility and eating habits (lifestyle-change sensitive respondents). However, while 29% of them perceive these habits’ changes as negatively impacting on the personal utility, the other 28% of respondents translate the potential changes in the habitual behaviour of driving and eating as environmental and health benefits. Based on the modelling results, potential policies are simulated reporting respondents’ reaction to selected scenarios. It shows the crucial role played by reduction of premature deaths due to atmospheric pollution and measure cost.     

Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O_3,decreased. Spatially, the PM_(2.5), PM_(10), SO_2, and CO concentrations were higher in the northern YRD region, and NO_2 and O_3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM_(2.5) was the largest contributor to air pollution in the YRD region, followed by O_3, PM_(10), and NO_2.However, particulate matter pollution has declined gradually, while O_3 pollution worsened.Meteorological conditions mainly influenced day-to-day variations in pollutant concentrations. PM_(2.5) concentration was inversely related to wind speed, while O_3 concentration was positively correlated with temperature and negatively correlated with relative humidity.The air quality improvement in recent years was mainly attributed to emission reductions.During 2014–2016, PM_(2.5), PM_(10), SO_2, NO_x, CO, NH_3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.     

Effect of air masses motion on the rapid change of aerosols in marine atmosphere

The impact of air masses motion on marine aerosol properties was investigated using an on-board single particle mass spectrometer(SPAMS) deployed for the determination of single particle size resolved chemical composition over Southeast China Sea. Two aerosol blooms(E1 and E2) were observed during the cruise. High average particle number count occurred in E1(7320), followed by E2(5850), which was more than 100–150 times of the average particle number count during normal periods. Particles were classified as four major sources, including continental source, shipping source, marine source, and transport source based on the mass spectral similarity. Transport source was identified as those particles with high particle number count occurred only during aerosol bloom period. Three sub-types of EC-Ca, OC-Ca, and Al-rich were classified as transport source.EC-Ca was the dominant particles of the transport source, accounting for more than 70%of the total particles in aerosol bloom events. A uni-modal size distribution in the size range of 0.1–2.0 μm was observed during normal period, while a bimodal distribution with a tiny mode(0.3 μm) and a coarse mode between 0.4 and 0.6 μm was present during aerosol bloom. The variation of aerosol source is consistent with air masses back trajectories, for the reason that most of the long-range air trajectories are from the ocean,while short air trajectories originate in the continental regions, which means that air masses have a significant impact on the aerosol physical–chemical properties along their tracks.