Estimating the contribution of industrial facilities to annual PM10 concentrations at industrially influenced sites

If measures to reduce the industrial discharge of PM10 shall be planned with high accuracy, a first step must be to estimate the contribution of single industrial facilities to the overall PM10 burden as accurately as possible. In northern Duisburg as an example, an area where iron and steel producing industry is concentrated, PM10 was measured at 4 sampling sites very close to an industrial complex of blast furnaces, a sinter plant, oxygen steel works and a coke oven plant for 9 months in 2006. At two sites metals in PM10 were determined. The results, together with analytical data of urban background sites in the region and data of wind direction and wind speed were used for an estimation of the contribution of single plants to the PM10 burden. A careful analysis of the data showed, that the data of PM10, calcium, iron and zinc measured at two sites close to the industrial area and information about the urban background aerosol were sufficient to calculate the PM10 contribution of the main single plants. The data could be compared with those of modelling.     

屠宰与肉类加工废水可持续处理工艺探讨

文章对屠宰与肉类加工废水废水中的主要污染物来源、特点及对常见的两种屠宰与肉类加工废水处理工艺特点进行了阐述,通过对某大型屠宰与肉类加工企业污水处理工艺的两个不同方案进行对比分析。指出了在结合废水特征与出水指标的情况下,更为合理的屠宰与肉类加工废水处理工艺,并通过相关技术指标,论证了最佳的废水处理工艺,同时提出了屠宰与肉类加工废水可持续处理技术的观点。     

绍兴部分河道水中重金属的检测及污染评估

为探索绍兴部分河道水中重金属元素的含量,采用电感耦合等离子体发射光谱(ICP-AES)方法测定绍兴河道水中铬、锰、铁、汞、铅、镍、锡、镉、砷、铜、锌和钴12种重金属元素含量。参照国家有关标准,对重金属检测结果进行与国标标准限值进行比较而达到对重金属的污染评价。结果表明:绍兴部分河流不存在重金属污染情况,但个别元素接近标准限值。     

Emission of particulate and gaseous pollutants from household laser processing machine

Indoor air quality (IAQ) directly affects the health of occupants. Household manufacturing equipment (HME) used for hobbies or educational purposes is a new and unexplored source of air pollution. In this study, we evaluated the characteristics of particulate and gaseous pollutants produced by a household laser processing equipment (HLPE). Various target materials were tested using a commercial HLPE under various operating conditions of laser power and sheath air flow rate. The mode diameters of the emitted particles gradually decreased as laser power increased, while the particle number concentration (PNC) and particle emission rate (PER) increased. In addition, as the sheath air flow rate quadrupled from 10 to 40 L/min, the mode diameter of the emitted particles decreased by nearly 25%, but the effect on the PNC was insignificant. When the laser induced the target materials at 53 mW, the mode diameters of particles were <150 nm, and PNCs were >2.0 × 10⁴ particles/cm³. Particularly, analyses of sampled aerosols indicated that harmful substances such as sulfur and barium were present in particles emitted from leather. The carcinogenic gaseous pollutants such as acrylonitrile, acetaldehyde, 1,3-butadiene, benzene, and C₈ aromatics (ethylbenzene) were emitted from all target materials. In an actual indoor environment, the PNC of inhalable ultrafine particles (UFPs) was >5 × 10⁴ particles/cm³ during 30 min of HLPE operation. Our results suggest that more meticulous control methods are needed, including the use of less harmful target materials along with filters or adsorbents that prevent emission of pollutants.     

A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China

The conventional Ensemble Kalman filter (EnKF), which is now widely used to calibrate emission inventories and to improve air quality simulations, is susceptible to simulation errors of meteorological inputs, making accurate updates of high temporal-resolution emission inventories challenging. In this study, we developed a novel meteorologically adjusted inversion method (MAEInv) based on the EnKF to improve daily emission estimations. The new method combines sensitivity analysis and bias correction to alleviate the inversion biases caused by errors of meteorological inputs. For demonstration, we used the MAEInv to inverse daily carbon monoxide (CO) emissions in the Pearl River Delta (PRD) region, China. In the case study, 60% of the total CO simulation biases were associated with sensitive meteorological inputs, which would lead to the overestimation of daily variations of posterior emissions. Using the new inversion method, daily variations of emissions shrank dramatically, with the percentage change decreased by 30%. Also, the total amount of posterior CO emissions estimated by the MAEInv decreased by 14%, indicating that posterior CO emissions might be overestimated using the conventional EnKF. Model evaluations using independent observations revealed that daily CO emissions estimated by MAEInv better reproduce the magnitude and temporal patterns of ambient CO concentration, with a higher correlation coefficient (R, +37.0%) and lower normalized mean bias (NMB, -17.9%). Since errors of meteorological inputs are major sources of simulation biases for both low-reactive and reactive pollutants, the MAEInv is also applicable to improve the daily emission inversions of reactive pollutants.     

On-board measurements of gaseous pollutant emission characteristics under real driving conditions from light-duty diesel vehicles in Chinese cities

A total of 15 light-duty diesel vehicles(LDDVs) were tested with the goal of understanding the emission factors of real-world vehicles by conducting on-board emission measurements. The emission characteristics of hydrocarbons(HC) and nitrogen oxides(NOx) at different speeds, chemical species profiles and ozone formation potential(OFP) of volatile organic compounds(VOCs) emitted from diesel vehicles with different emission standards were analyzed. The results demonstrated that emission reductions of HC and NOxhad been achieved as the control technology became more rigorous from Stage I to Stage IV. It was also found that the HC and NOxemissions and percentage of O2 dropped with the increase of speed, while the percentage of CO2 increased. The abundance of alkanes was significantly higher in diesel vehicle emissions, approximately accounting for 41.1%–45.2%, followed by aromatics and alkenes. The most abundant species were propene,ethane, n-decane, n-undecane, and n-dodecane. The maximum incremental reactivity(MIR)method was adopted to evaluate the contributions of individual VOCs to OFP. The results indicated that the largest contributors to O3 production were alkenes and aromatics, which accounted for 87.7%–91.5%. Propene, ethene, 1,2,4-trimethylbenzene, 1-butene, and1,2,3-trimethylbenzene were the top five VOC species based on their OFP, and accounted for 54.0%-64.8% of the total OFP. The threshold dilution factor was applied to analyze the possibility of VOC stench pollution. The majority of stench components emitted from vehicle exhaust were aromatics, especially p-diethylbenzene, propylbenzene, m-ethyltoluene, and p-ethyltoluene.     

对排污申报内部审计中存在问题的探讨

主要论述了排污申报登记、排污申报登记核定、内部审计的内容和依据,以便将环境保护部门内部审计工作更好地开展起来。     

Atmospheric isoprene and monoterpenes in a typical urban area of Beijing: Pollution characterization, chemical reactivity and source identification

Continuous observation of isoprene, α-pinene and β-pinene was carried out in a typical urban area of Beijing from March 2014 to February 2015, using an AirmoV OC online analyzer. Based on the analysis of the ambient level and variation characteristics of isoprene, α-pinene and β-pinene, the chemical reactivity was studied, and their sources were identified. Results showed that the concentrations of isoprene, α-pinene and β-pinene in the urban area of Beijing were lower than those in richly vegetated areas; the concentrations of isoprene were at a moderate level compared with those of previous studies of Beijing. Concentrations of isoprene, α-pinene and β-pinene showed different seasonal, monthly, daily and diurnal variations, and all of the three species showed higher level at night than those in the daytime as a whole, the variations of isoprene, α-pinene and β-pinene mainly influenced by emission of sources, photochemical reaction, and meteorological parameters. Isoprene was the largest contributor to the total OFP values than α-pinene and β-pinene. α-Pinene was the largest contributor to the total SOAFP values than isoprene and β-pinene in autumn, while isoprene was the largest one in other seasons. Isoprene, α-pinene and β-pinene were derived mainly from biological sources; and α-pinene level were also affected by industrial sources. To reduce the concentrations of isoprene, α-pinene and β-pinene, it is necessary to scientifically select urban green plant species, and more strict control measures should be taken to reduce the emission of α-pinene from industrial sources, such as artificial flavors and resins synthesis processes.     

常州市人为源挥发性有机物排放清单

对常州市VOCs人为源进行系统划分,运用国内外排放因子研究成果及常州市各排放源调研结果,采用排放因子法建立了2017年常州市分类型、分辖区(市)的人为源VOCs排放清单。结果表明,2017年常州市人为源VOCs排放总量约为9. 662×10~4t,其中化石燃料燃烧源、工业过程源、移动源、非工业溶剂使用源、油品储运源、生物质燃烧源、固废污水处理源和餐饮源排放分别占排放总量的1. 9%,47. 2%,9. 0%,27. 6%,9. 4%,2. 6%,0. 4%和1. 9%。工业过程源中黑色(有色)金属冶炼及压延加工业、非金属矿物制品业、化学原料和化学品制造业、机械装备制造业、交通设备制造业、纺织业是重点行业;武进区、溧阳市、新北区3个工业发达的区域VOCs排放量明显高于常州其他几个辖区,占全市总排放量的71%;各辖区(市)的重点排放源存在差异,其中武进区、溧阳市、新北区以工业过程源为主,金坛区、天宁区、钟楼区以非工业溶剂使用源为主。     

抚顺市大气颗粒物主要排放源的成分谱研究

抚顺市的5种大气颗粒物主要排放源中土壤风沙尘的特征元素为K,钢铁尘的特征元素为Fe,建筑水泥尘的特征元素为Ca,煤烟尘的特征元素为Ti。土壤风沙尘和扬尘中含量最高的元素为Al,煤烟尘中含量最高的元素为EC,钢铁尘中含量最高的元素为Fe,建筑水泥尘中含量最高的元素为Ca。