Ammonia emissions from swine houses in the southeastern United States

Ammonia (NH3) from confined animal feeding operations is emitted from several sources including lagoons, field applications, and houses. This paper presents studies that were conducted to evaluate NH3 emissions from swine finisher and sow animal houses in the southeastern USA. Management and climate variables including animal weight, feed consumption, housing gutter water temperature, total time fans operated per day, house air temperature, house ambient NH3 concentration, and animal numbers were measured to determine their individual and combined effect on NH3 emissions. Ammonia emissions varied on daily and seasonal bases with higher emissions during warmer periods. For finishers, the summertime housing emissions on a per-animal basis were 2.4 times higher than wintertime (7.0 vs. 3.3 g NH3 animal(-1) d(-1)) or 3.2 times higher when compared on an animal unit (AU) basis (1 AU = 500 kg) because of climate and animal size differences between measurement periods. For summertime, the emission factor for the finishing pigs was 7.8 times higher than for sows on an animal basis and 25.6 times higher on an AU basis. Simple models were developed for housing emissions based on (i) all measured factors that were independent of each other and (ii) on three commonly measured management factors. The two models explained 97 and 64%, respectively, of variations in emissions. Ammonia emissions were found to be somewhat less than other studies on the same type housing due to more representative housing concentration measurements and calibration of exhaust fans; thus, emission factors for these type houses will be less than previously thought.     

广元市房建施工扬尘排放清单研究

为了研究广元市房建施工扬尘排放特征,通过调研获取了广元市2010 ～2019年间的房建工地施工面积、抑尘措施及控制效率,按照自下而上的方法建立了房建施工扬尘排放清单,分析了2019年广元市房建施工扬尘的时空分布特征,并采用CALPUFF对广元市利州区某房建工地的排放进行了模拟.结果 表明:(1) 2010 ～2019年...     

Laboratory evaluation of dust-control effectiveness of pen surface treatments for cattle feedlots

Emission of particulate matter (PM) is one of the major air quality concerns for large beef cattle feedlots. Effective treatments on the uncompacted soil and manure mixture of the pen surface may help in reducing PM emission from feedlots. A laboratory apparatus was developed for measuring dust-emission potential of cattle feedlot surfaces as affected by pen surface treatments. The apparatus was equipped with a simulated pen surface, four mock cattle hooves, and samplers for PM with equivalent aerodynamic diam. ≤ 10 μm (PM(10)). The simulated pen surface had a layer of dry, loose feedlot manure with a compacted soil layer underneath. Mock hooves were moved horizontally on the manure layer to simulate horizontal action of cattle hooves on the pen surface. High-volume PM samplers were used to collect emitted dust. Effects of hoof speed, depth of penetration, and surface treatments with independent candidate materials (i.e., sawdust, wheat straw, hay, rubber mulch, and surface water application) on PM(10) emission potential of the manure layer were investigated. Our laboratory study showed PM(10) emission potential increased with increasing depth of penetration and hoof speed. Of the surface treatments evaluated, application of water (6.4 mm) and hay (723 g m(-2)) exhibited the greatest percentage reduction in PM(10) emission potential (69 and 77%, respectively) compared with the untreated manure layer. This study indicated application of hay or other mulch materials on the pen surface might be good alternative methods to control dust emission from cattle feedlots.     

Nitrogen cycling through swine production systems: ammonia, dinitrogen, and nitrous oxide emissions

Ammonia (NH(3)) emissions from animal systems have become a primary concern for all of livestock production. The purpose of this research was to establish the relationship of nitrogen (N) emissions to specific components of swine production systems and to determine accurate NH(3) emission factors appropriate for the regional climate, geography, and production systems. Micrometeorological instrumentation and gas sensors were placed over two lagoons in North Carolina during 1997-1999 to obtain information for determining ammonia emissions over extended periods and without interfering with the surrounding climate. Ammonia emissions varied diurnally and seasonally and were related to lagoon ammonium concentration, acidity, temperature, and wind turbulence. Conversion of significant quantities of ammonium NH(4)(+) to dinitrogen gas (N(2)) were measured in all lagoons with the emission rate largely dependent on NH(4)(+) concentration. Lagoon NH(4)(+) conversion to N(2) accounted for the largest loss component of the N entering the farm (43% as N(2)); however, small amounts of N(2)O were emitted from the lagoon (0.1%) and from field applications (0.05%) when effluent was applied nearby. In disagreement with previous and current estimates of NH(3) emissions from confined animal feeding operation (CAFO) systems, and invalidating current assumptions that most or all emissions are in the form of NH(3), we found much smaller NH(3) emissions from animal housing (7%), lagoons (8%), and fields (2%) using independent measurements of N transformation and transport. Nitrogen input and output in the production system were evaluated, and 95% of input N was accounted for as output N from the system.     

Simple estimates of vehicle-induced resuspension rates

Road dust emissions are considered to be a major source of airborne particulate matter (PM). This is particularly true for industrial environments, where there are high resuspension rates of deposited dust. The calculation of roads as PM emission sources has mostly focused on the consequences of this emission, viz. the increase in PM concentrations. That approach addresses the atmospheric transport of the emitted dust, and not its primary origin. In contrast, this paper examines the causes of the emission. The study is based on mass conservation of the dust deposited on the road surface. On the basis of this premise, estimates of emission rates were calculated from experimental data obtained in a road in a ceramic industrial area.     

Comparison of DAYCENT-simulated and measured nitrous oxide emissions from a corn field

Accurate assessment of N(2)O emission from soil requires continuous year-round and spatially extensive monitoring or the use of simulation that accurately and precisely predict N(2)O fluxes based on climatic, soil, and agricultural system input data. DAYCENT is an ecosystem model that simulates, among other processes, N(2)O emissions from soils. The purpose of the study was to compare N(2)O fluxes predicted by the DAYCENT model to measured N(2)O fluxes from an experimental corn field in central Iowa. Soil water content temperature and inorganic N, simulated by DAYCENT were compared to measured values of these variables. Field N(2)O emissions were measured using four replicated automated chambers at 6-h intervals, from day of year (DOY) 42 through DOY 254 of 2006. We observed that DAYCENT generally accurately predicted soil temperature, with the exception of winter when predicted temperatures tended to be lower than measured values. Volumetric water contents predicted by DAYCENT were generally lower than measured values during most of the experimental period. Daily N(2)O emissions simulated by DAYCENT were significantly correlated to field measured fluxes; however, time series analyses indicate that the simulated fluxes were out of phase with the measured fluxes. Cumulative N(2)O emission calculated from the simulations (3.29 kg N(2)O-N ha(-1)) was in range of the measured cumulative N(2)O emission (4.26 +/- 1.09 kg N(2)O-N ha(-1)).     

泸州市主城区2019年3月至2020年2月大气颗粒物污染特征及防治对策研究

为了解泸州市主城区颗粒物污染变化特征及成因,选取2019年3月至2020年2月空气自动监测数据,运用Origin 2017等技术手段对PM2.5与PM10的时间变化特征、污染来源方向以及污染物之间的相关性进行了分析.结果表明:PM2.5与PM10在不同季节的变化趋势均具有较好的一致性,不同站点污染物相关性特征明显.分析...     

资阳市大气污染源排放清单研究

采用实地调研、资料收集等方式获得了2017年资阳市典型污染源的活动水平数据,参照城市大气污染物排放清单编制技术手册建立了基于排放因子法和物料衡算法的资阳市大气污染源排放清单,分析了主要污染物的行业排放特征和空间分布特征。结果表明,2017年资阳市SO₂、NO_X、CO、PM₁₀、PM_2.5、VOCs、NH₃总排放量分别为3.58kt、13.91kt、94.91kt、25.51kt、8.67kt、23.84kt和46.44kt。SO₂排放主要来自工业源;NOX排放主要来自移动源;CO排放主要来自工业过程及移动源;PM₁₀和PM_2.5、排放来自扬尘源和露天秸秆焚烧;VOCs主要来自溶剂使用源;NH₃主要来自农业活动。资阳市主要污染物排放分布在工业点源较为集中的雁江区和安岳县,乐至县污染物排放量相对较小。     

基于LMDI模型的乌鲁木齐工业废气排放影响因素研究

本文运用对数平均的LMDI 分解模型,选取工业SO₂、工业烟(粉)尘排放量作为污染物指标,将2006—2013 年,乌鲁木齐工业废气排放量影响因素分解为规模效应、结构效应、技术效应,考虑到技术效应机制的复杂性,进一步将技术效应细化为污染治理效应和清洁技术效应。研究结果表明:规模效应和结构效应增加乌鲁木齐工业废气排放,其中规模效应对工业废气排放量贡献率由2007 年的119.10%增加到2013 年的263.03%,结构效应对工业废气排放量的增加也起到一定的促进作用,但影响效果远低于规模效应,年贡献率均低于10%,技术效应阻碍工业废气排放的增加,贡献率由2007 年的-19.86%增加到2013 年的-172.50%。制造业和电力、燃气及水的生产和供应业废气排放量占工业废气排放总量的70% 左右,是乌鲁木齐工业废气污染的主要行业。清洁技术效应对SO₂ 的减排起促进作用,是阻碍工业SO₂ 排放量增加的主要因素。污染治理效应是工业烟(粉)尘的减排主要因素,说明目前乌鲁木齐工业烟(粉)尘的减排依赖于排放后的治理。     

Policy evaluation of vehicle exhaust standards in Japan from 1995 to 2005 based on two human health risk indices for air pollution and global warming

Measures for vehicle exhaust emissions aimed at reducing either air pollution or global warming could have counterproductive effects on one another. Increasing diesel passenger vehicles, which generally have lower CO₂ emissions than gasoline counterparts, leads to increasing particulate matter (PM) emissions, while gasoline has lower PM emissions than diesel. It is said that stringent limits on PM emission factors discourages improved CO₂ emission factors. Without including both effects in a risk evaluation, one cannot evaluate whether the total risk is reduced or not. Hence, we evaluated representative exhaust emission measures based on risk evaluation for both air pollution and global warming. Considering consumer choice between diesel and gasoline passenger vehicles and emissions standards adopted in Japan from 1995 to 2005, we built five cases for vehicle policy evaluation. For each case, we estimated disability-adjusted life years (DALY) as an index of human health risk caused by lung cancer linked to inhalation exposure of elemental carbon in PM as well as due to global warming linked to CO₂. The results of our risk evaluation reveal that the case adopting the 2005 new long-term Japanese emission standard reduces the human health risk caused by lung cancer due to air pollution by 0.6 × 10³ DALY, but would increase the risk due to global warming by 31.9 × 10³ DALY compared with the case of adopting EURO 4, for the same conditions of passenger vehicle choice from 1995. These results suggest that the characteristics of Japanese emissions standards are mainly designed to reduce air pollution.     

燃煤电厂PM_(2.5)减排技术与装备探讨

燃煤电厂在我国电力工业中占有很大的比重,其烟尘排放污染问题也尤其突出。大量燃煤烟尘的排放造成了严重的环境污染,特别是其中的细颗粒物PM2.5,能长期悬浮于大气中,对人类的健康造成了长期持续的危害,因此燃煤电厂PM2.5减排技术对于环境保护事业具有重要的意义和深远的影响,大力发展PM2.5减排技术与装备是电力行业大势所趋。     

京津冀地区重点耗煤行业大气污染物排放清单研究

本研究通过京津冀地区各行业的年度煤炭消费量确定火电行业、钢铁行业和焦化行业为重点耗煤行业,以在线监测数据、污染源调查(现场调研、环评、验收)数据、排放因子数据为基础,自下而上建立了2013年京津冀地区重点耗煤行业大气污染物排放清单,分析研究了SO_2、NO_x和PM_(10)的排放量与污染贡献分布情况,掌握了京津冀地区重点耗煤行业大气污染物排放现状,为大气污染物减排提供数据基础。研究表明,2013年京津冀火电、钢铁焦化行业共排放SO_2 72.35万t、NO_x 131.99万t、PM_(10) 30.36万t。     

A comparative study of US EPA 1996 and 1999 emission inventories in the west Gulf of Mexico coast region, USA

Emission inventory is one of the required inputs to air quality models. To assist in the urban and regional modeling efforts, United States Environmental Protection Agency (EPA) has compiled a National Emission Inventory (NEI) for criterion pollutants, and the precursors of ozone and particulate matter (PM). In December 2002, EPA released the 1999 NEI estimates (NEI99), which represent the most recent national emission data. However, the data sets are not in model-ready format for air quality simulations. This present work converts the NEI99 Final Version 2 data sets into Inventory Data Analyzer (IDA) format and processes the data using the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system to generate a gridded emission inventory in a domain covering the west Gulf Coast Region, USA. The spatial and diurnal emission characteristics of the gridded emission inventories are then assessed and compared with those of the National Emission Trend 1996 (NET96). The NEI99 database contains more complete emission records in both area and point sources. It is also found that NEI99 data exhibit greater emissions with respect to point and mobile sources but smaller emissions with respect to area sources when compared to the corresponding gridded NET96 data in the same study domain. The most distinct differences between the NEI99 and NET96 databases are CO emission of mobile sources, SO2 emissions of point sources, and VOC/PM/NH3/NOx emissions of area and non-road sources. The gridded NEI99 data show low VOC/NOx ratios (<2-5) in the urban areas of the study domain.     

Dust dynamics in off-road vehicle trails: Measurements on 16 arid soil types, Nevada, USA

Soil analyses and measurements with the Portable In Situ Wind Erosion Laboratory (PI-SWERL) were conducted on 16 soil types in an area heavily affected by off-road vehicle (ORV) driving. Measurements were performed in ORV trails as well as on undisturbed terrain to investigate how ORV driving affects the vulnerability of a soil to emit PM10 (particles < 10 μm), during the driving as well as during episodes of wind erosion. Particular attention is paid to how the creation of a new trail affects those properties of the topsoil that determine its capability to emit PM10. Also, recommendations are given for adequate management of ORV-designed areas. The type of surface (sand, silt, gravel, drainage) is a key factor with respect to dust emission in an ORV trail. Trails in sand, defined in this study as the grain size fraction 63–2000 μm, show higher deflation thresholds (the critical wind condition at which wind erosion starts) than the surrounding undisturbed soil. Trails in silt (2–63 μm) and in drainages, on the other hand, have lower deflation thresholds than undisturbed soil. The increase in PM10 emission resulting from the creation of a new ORV trail is much higher for surfaces with silt than for surfaces with sand. Also, the creation of a new trail in silt decreases the supply limitation in the top layer: the capacity of the reservoir of emission-available PM10 increases. For sand the situation is reversed: the supply limitation increases, and the capacity of the PM10 reservoir decreases. Finally, ORV trails are characterized by a progressive coarsening of the top layer with time, but the speed of coarsening is much lower in trails in silt than in trails in sand or in drainages. The results of this study suggest that, to minimize emissions of PM10, new ORV fields should preferably be designed on sandy terrain rather than in silt areas or in drainages.     

Ammonia emissions from Swine waste lagoons in the Utah great basin

In animal production systems (poultry, beef, and swine), current production, storage, and disposal techniques present a challenge to manage wastes to minimize the emissions of trace gases within relatively small geographical areas. Physical and chemical parameters were measured on primary and secondary lagoons on three different swine farming systems, three replicates each, in the Central Great Basin of the United States to determine ammonia (NH3) emissions. Nutrient concentrations, lagoon water temperature, and micrometeorological data from these measurements were used with a published process model to calculate emissions. Annual cycling of emissions was determined in relation to climatic factors and wind speed was found the predominating factor when the lagoon temperatures were above about 3 degrees C. Total NH3 emissions increased in the order of smallest to largest: nursery, sow, and finisher farms. However, emissions on an animal basis increased from nursery animals being lowest to sow animals being highest. When emissions were compared to the amount of nitrogen (N) fed to the animals, NH3 emissions from sows were lowest with emissions from finisher animals highest. Ammonia emissions were compared to similar farm production systems in the humid East of the United States and found to be similar for finisher animals but had much lower emissions than comparable humid East sow production. Published estimates of NH3 emissions from lagoons ranged from 36 to 70% of feed input (no error range) compared to our emissions determined from a process model of 9.8% with an estimated range of +/-4%.     

考虑“水—土—能—碳”关联的我国工农业碳排放效率及减排潜力研究

考虑“水—土—能—碳”关联,本文将水土资源要素纳入投入变量,构建了我国工农业碳排放效率投入产出测度指标,运用考虑非期望产出的SBM-undesirable模型计算我国29个省份2004—2017年农业、工业部门碳排放效率,利用乘法逆转法计算碳减排潜力并对影响碳排放的投入产出因素进行分析。结果表明：研究期内我国整体农业、工业碳排放效率均呈波动下降趋势,各年的农业碳排放效率均高于工业碳排放效率,江苏、山东等7省份农业碳排放效率以及北京、天津工业碳排放效率最优;各省份农业、工业减排潜力和规模具有显著差异,山西、甘肃的农业、工业碳减排均具有较大潜力;我国绝大多数省份均存在农业、工业的资源能源投入冗余和非期望产出冗余,土地资源投入过剩是影响农业碳排放效率的最重要因素,水资源投入过剩是影响工业碳排放效率的最重要因素。碳排放效率较低省份应积极开展技术创新,发展低碳技术,提高水土资源和能源利用效率,减少碳排放。     

我国大气细颗粒物污染防治目标和控制措施研究

我国面临着严重的细颗粒物(PM2.5)污染问题,PM2.5对人体健康、能见度、气候变化、生态系统等均产生了不良影响。本文旨在提出我国PM2.5污染防治目标和控制措施,为从根本上改善空气质量提供科学依据。首先,本文提出了2020年和2030年我国PM2.5污染防治目标。其次,采用能源和污染排放技术模型,分情景预测了我国未来一次大气污染物排放量的变化趋势。基于情景预测结果和此前研究建立的一次污染物排放与PM2.5浓度间的非线性关系,确定了2020年—2030年与PM2.5浓度改善相适应的全国和重点区域大气污染物减排目标。最后,利用能源和污染排放技术模型,提出了实现大气污染物减排的技术措施和对策建议。研究表明,2030年全国二氧化硫、氮氧化物、一次PM2.5和挥发性有机物的排放量应分别比2012年至少削减51%、64%、53%和36%,氨排放量也要略有下降。对于污染严重的重点区域,必须采取更严格的控制力度。要实现上述减排,应加快能源结构调整,推进煤炭清洁高效集中可持续利用,建立"车-油-路"一体的移动源控制体系,并强化多源多污染物的末端控制。     

Near-field dust exposure from cotton field tilling and harvesting

The frequency and intensities of dust exposures in and near farm fields, which potentially contribute to high intensity human exposure events, are undocumented due to the transient nature of local dust plumes and the difficulties of making accurate concentration measurements. The objective of this study is to measure near-field spatial concentrations of the dust plumes emitted during tilling and harvesting of an irrigated cotton field outside of Las Cruces, NM (soil class: fine-loamy, mixed, superactive, thermic Typic Calciargid). A comparison of remote lidar measurements of plumes emitted from cotton field operations with in situ samplers shows a strong agreement between the two techniques: r2 = 0.79 for total suspended particulates (TSP) and r2 = 0.61 for particulate matter with diameter less than or equal to 10 microm (PM10). Plume movement was dependent on the short-term wind field and atmospheric stability. Horizontal spread rate of the plumes, determined from lidar measured Gaussian dispersion parameters, was less than expected by a factor of 7. Thus, in-plume downwind concentrations were higher than expected. Vertical dispersion was dependent on the rise of "cells" of warm air convecting off the soil surface. On a windy day, discing the field showed TSP and PM10 concentrations at the source itself of up to 176 microg m(-3) and 120 microg m(-3), respectively. These resulted in in-plume peak TSP concentrations of about 1.22 microg m(-3) at 10 m downwind and 0.33 microg m(-3) at 100 m downwind. The measured concentrations highlight a potential exposure risk to people in and around farming operations.     

Dairy farm methane emissions using a dispersion model

There is a need to know whole-farm methane (CH(4)) emissions since confined animal facilities such as beef cattle feedlots and dairy farms are emission "hot spots" in the landscape. However, measurements of whole-farm CH(4) emissions can differ between farms because of differences in contributing sources such as manure handling, number of lactating and nonlactating cows, and diet. Such differences may limit the usefulness of whole-farm emissions for national inventories and mitigation purposes unless the variance between farms is taken into account or a large number of farms can be examined. Our study describes the application of a dispersion model used in conjunction with field measurements of CH(4) concentration and stability of the air to calculate whole-farm emissions of CH(4) from three dairy farms in Alberta, Canada, during three sequential campaigns conducted in November 2004 and May and July 2005. The dairy farms ranged in herd size from 208 to 351 cows (102 to 196 lactating cows) and had different manure handling operations. The results indicate that the average CH(4) emission per cow (mixture of lactating and nonlactating) from the three dairy farms was 336 g d(-1), which was reduced to 271 g d(-1) when the emission (estimated) from the manure storage was removed. Further separation of source strength yielded an average CH(4) (enteric) emission of 363 g d(-1) for a lactating cow. The estimated CH(4) emission intensities were approximately 15 g CH(4) kg(-1) dry matter intake and 16.7 L CH(4) L(-1) of milk produced. The approach of understanding the farm-to-farm differences in CH(4) emissions as affected by diet, animal type, and manure management is essential when utilizing whole-farm emission measurements for mitigation and inventory applications.     

Iron Ore Industry Emissions as a Potential Ecological Risk Factor for Tropical Coastal Vegetation

In the coastal zone of the Espírito Santo state, Brazil, fragments of restinga, which form a natural ecosystem, share their space with an increasing number of iron ore industries. The iron ore dust and SO(2) originating from the industry processing activities can interfere with the vegetation of the adjacent ecosystems at various levels. This study was undertaken in order to evaluate the effects of industry emissions on representative members of the restinga flora, by measuring physiological and phenological parameters. Foliar samples of Ipomoea pes caprae, Canavalia rosea, Sophora tomentosa, and Schinus terebinthifolius were collected at three increasing distances from an ore industry (1.0, 5.0, and 15.0 km), and were assessed for their dust deposition, chlorophyll, and Fe content. Phenological monitoring was focused on the formation of shoots, flowers, and fruits and was also performed throughout the course of a year. The results showed that the edaphic characteristics and the mineral constitutions of the plants were affected by industry emissions. In addition, the chlorophyll content of the four species increased with proximity to the industry. Phenological data revealed that the reproductive effort, as measured by fruit production, was affected by emissions and S. tomentosa was the most affected species. The use of an integrative approach that combines biochemical and ecological data indicates that the restinga flora is under stress due to industry emissions, which on a long-term basis may put the ecosystem at risk.