基于调查的中国秸秆露天焚烧污染物排放清单

基于2010年初农村能源消费情况的问卷调查,获得全国分省秸秆露天焚烧比例,在此基础上确定秸秆露天焚烧的活动水平,采用排放因子法建立中国秸秆露天焚烧的污染物排放清单. 结果表明,中国农村秸秆露天焚烧平均比例为20.8%. 2009年全国28个省区(不包括西藏自治区、天津市、上海市、港澳台地区,下同)秸秆露天焚烧的PM_2.5、BC、OC、SO₂、NO_x、CO、NMVOC、NH₃、CH₄和CO₂排放量分别138.1×104、6.4×104、41.1×104、8.7×104、41.8×104、594.6×104、94.4×104、8.0×104、44.2×104和14 355.4×104 t. 稻谷、玉米和小麦是露天焚烧的三大作物秸秆,其对污染物排放的贡献合计约为87%. 秸秆露天焚烧排放量最高的前3位分别为湖南省、河南省和安徽省, 秸秆露天焚烧比例分别43.1%、20.8%和39.7%. 污染排放的高值区主要集中在华北和华中地区. 95%置信区间下的不确定性分析结果显示,PM_2.5、BC、OC、SO₂、NO_x、CO和NMVOC排放的不确定性范围分别为-60%~83%、-78%~147%、-73%~135%、-48%~75%、-49%~78%、-91%~155%和-67%~94%. 2015年初对六省(湖南省、广东省、江苏省、河南省、黑龙江省和辽宁省)农村能源消费调查的结果显示,2014年江苏省、湖南省和广东省的秸秆露天焚烧比例较2009年均有下降,而辽宁省、黑龙江省和河南省则相对上升. 研究显示,秸秆禁烧政策已取得初步成效,建议国家有关部门进一步加大秸秆禁烧政策的推行力度,完善相关政策措施.      

长江三角洲地区秸秆露天焚烧大气污染物排放清单及其在空气质量模式中的应用

基于长江三角洲江苏、安徽、浙江和上海地区2008年粮食产量的统计年鉴,结合作物谷草比、排放因子等估算了上述地区2008年秸秆焚烧排放污染物清单,重点完善了各县级市污染物排放.结果表明2008年江苏、安徽、浙江和上海地区SO2、NOx、CO、CO2、PM2.5、BC、OC、NH3、CH4、NMVOC的排放总量分别为14.28、86.01、1 744.56、36 893.03、517.54、11.74、114.63、19.93、89.37和208.57 kt.江苏中部和北部、安徽北部地区秸秆露天焚烧污染物排放较多,而江苏南部和浙江地区污染物排放量较少.将建立的秸秆露天焚烧排放污染物清单应用于WRF-CMAQ空气质量模式,结果表明,考虑秸秆焚烧排放源后,对PM10、CO等大气污染物的模拟能力大幅提高,模拟浓度比使用原始排放源分别提高42%和28%,模拟浓度与实测浓度的相关系数分别提高0.25和0.17,模拟值较使用原始排放源更加贴近实测值.     

广东省秸秆燃烧大气污染物及VOCs物种排放清单

基于广东省粮食产量的统计年鉴,建立了广东省2008~2016年秸秆燃烧污染物排放清单和2016年广东省秸秆燃烧VOCs物种清单,并对VOCs臭氧生成潜势进行评估.结果表明,2013~2016年广东省秸秆燃烧各大气污染物排放量较2008~2012年有所降低.这主要是由于禁止秸秆露天燃烧政策的出台及农村生活水平的提高降低了秸秆燃烧比例.2016年各类大气污染物SO_2、NO_x、NH_3、CH_4、EC、OC、NMVOC、CO和PM_(2.5)的排放量依次为2 443.7、16 187.9、6 943.8、29 174.4、3 625.5、14 830.7、65 612.6、591 613.9和49 463.0 t.稻谷秸秆燃烧是最主要的秸秆燃烧污染物来源,占据了污染物总排放量的约68.55%.污染物贡献最大的5个市分别为湛江、茂名、梅州、肇庆和韶关,约占总排放量的58.63%.2016年广东省秸秆燃烧VOCs物种排放清单中,排放量贡献前10的物种分别为:乙烯、乙醛、甲醛、苯、乙炔、丙烯、乙烷、甲苯、正丙烷和丙醛,占总VOCs量的67.91%.在VOCs物种清单的基础上估算了其臭氧生成潜势(OFP),OFP贡献前10 VOCs物种分别为:乙烯、甲醛、乙醛、丙烯、1-丁烯、丙醛、甲苯、丙烯醛、异戊二烯和丁烯醛,占总OFP量的80.83%.     

Local PM10 and PM2.5 emission inventories from agricultural tillage and harvest in northeastern China

Mineral particles or particulate matters(PMs) emitted during agricultural activities are major recurring sources of atmospheric aerosol loading.However,precise PM inventory from agricultural tillage and harvest in agricultural regions is challenged by infrequent local emission factor(EF) measurements.To understand PM emissions from these practices in northeastern China,we measured EFs of PM_(10) and PM_(2.5) from three field operations(i.e.,tilling,planting and harvesting) in major crop production(i.e.,corn and soybean),using portable real-time PM analyzers and weather station data.County-level PM_(10) and PM_(2.5) emissions from agricultural tillage and harvest were estimated,based on local EFs,crop areas and crop calendars.The EFs averaged(107 ± 27),(17 ± 5) and 26 mg/m~2 for field tilling,planting and harvesting under relatively dry conditions(i.e.,soil moisture 15%),respectively.The EFs of PM from field tillage and planting operations were negatively affected by topsoil moisture.The magnitude of PM_(10) and PM_(2.5) emissions from these three activities were estimated to be 35.1 and 9.8 kilotons/yr in northeastern China,respectively,of which Heilongjiang Province accounted for approximately45%.Spatiotemporal distribution showed that most PM_(10) emission occurred in April,May and October and were concentrated in the central regions of the northeastern plain,which is dominated by dryland crops.Further work is needed to estimate the contribution of agricultural dust emissions to regional air quality in northeastern China.     

长三角地区秸秆焚烧污染物排放清单及其在重霾污染天气模拟中的应用

根据2008年长三角地区江苏、安徽、浙江3省各地级市及上海市水稻、小麦、玉米、油菜4种农作物的年产量,结合谷草比、秸秆焚烧比例及排放因子建立了长三角地区秸秆焚烧大气污染物排放清单.结果表明：长三角地区秸秆焚烧产生的PM10、PM2.5、SO2、NOx、CO、EC、OC分别为36.8×104、14.4×104、1.5×104、9.2×104、20.8×104、2.6×104、12.2×104t.秸秆焚烧污染物排放量较大的区域主要集中在江苏中北部和安徽北部.在区域大气环境模拟系统RegAEMS中考虑秸秆焚烧源的影响,针对2008年10月底江苏一次重霾污染天气事件进行模拟,发现考虑秸秆焚烧源后模拟结果有较大的改善.秸秆焚烧可以导致区域PM10、CO浓度上升30%以上,黑碳和有机物的消光贡献明显增强.区域输送研究表明,苏中地区、外省秸秆焚烧排放源对此次重霾污染的贡献分别达到32.4%、33.3%.     

四川省秸秆露天焚烧污染物排放清单及时空分布特征

根据收集的活动水平数据,采用排放因子法建立了四川省2012年秸秆露天焚烧污染物排放清单,并分析了污染排放的时空分布特征.结果表明,2012年四川省秸秆露天焚烧共排放SO2、NOx、NH3、CH4、NMVOC、CO、PM2.5、EC以及OC分别为1 210、12 185、2 827、20 659、40 463、292 671、39 277、1 984以及10 215 t;水稻、小麦、玉米、油菜是四大主要的焚烧作物秸秆,对污染物的总贡献率约为88%~94%;秸秆露天焚烧受农作收获的影响,全年的排放主要集中在7~8月,而5月是上半年的一个排放小高峰;秸秆焚烧排放的高值地区主要分布在成都平原、川北地区以及川南地区,川西地区排放分布相对较少;本清单的不确定性主要来自排放因子及秸秆焚烧量.     

Vehicular emissions in China in 2006 and 2010

Vehicular emissions in China in 2006 and 2010 were calculated at a high spatial resolution based on the data released by the National Bureau of Statistics, by taking the emission standards into consideration. China's vehicular emissions of carbon monoxide(CO),nitrogen oxides(NO_x), volatile organic compounds(VOCs), ammonia(NH_3), fine particulate matters(PM_(2.5)), inhalable particulate matters(PM_(10)), black carbon(BC), and organic carbon(OC) were 30,113.9, 4593.7, 6838.0, 20.9, 400.2, 430.5, 285.6, and 105.1 Gg, respectively, in 2006 and 34,175.2, 5167.5, 7029.4, 74.0, 386.4, 417.1, 270.9, and 106.2 Gg, respectively, in 2010. CO,VOCs, and NH_3 emissions were mainly from motorcycles and light-duty gasoline vehicles,whereas NO_X, PM_(2.5), PM_(10), and BC emissions were mainly from rural vehicles and heavyduty diesel trucks. OC emissions were mainly from motorcycles and heavy-duty diesel trucks. Vehicles of pre-China Ⅰ(vehicular emission standard of China before phase Ⅰ) and China Ⅰ(vehicular emission standard of China in phase Ⅰ) were the primary contributors to all of the pollutant emissions except NH_3, which was mainly from China Ⅲ and China Ⅳ gasoline vehicles. The total emissions of all the pollutants except NH_3 changed little from2006 to 2010. This finding can be attributed to the implementation of strict emission standards and to improvements in oil quality.     

Effect of elevated tropospheric ozone on methane and nitrous oxide emission from rice soil in north India

Physiological changes in crop plants in response to the elevated tropospheric ozone (O₃) may alter N and C cycles in soil. This may also affect the atmosphere-biosphere exchange of radiatively important greenhouse gases (GHGs), e.g. methane (CH₄) and nitrous oxide (N₂O) from soil. A study was carried out during July to November of 2007 and 2008 in the experimental farm of Indian Agricultural Research Institute, New Delhi to assess the effects of elevated tropospheric ozone on methane and nitrous oxide emissions from rice (Oryza sativa L.) soil. Rice crop was grown in open top chambers (OTC) under elevated ozone (EO), non-filtered air (NF), charcoal filtered air (CF) and ambient air (AA). Seasonal mean concentrations of O₃ were 4.3 ± 0.9, 26.2 ± 1.9, 59.1 ± 4.2 and 27.5 ± 2.3 ppb during year 2007 and 5.9 ± 1.1, 37.2 ± 2.5, 69.7 ± 3.9 and 39.2 ± 1.8 ppb during year 2008 for treatments CF, NF, EO and AA, respectively. Cumulative seasonal CH₄ emission reduced by 29.7% and 40.4% under the elevated ozone (EO) compared to the non-filtered air (NF), whereas the emission increased by 21.5% and 16.7% in the charcoal filtered air (CF) in 2007 and 2008, respectively. Cumulative seasonal emission of N₂O ranged from 47.8 mg m⁻² in elevated ozone to 54.6 mg m⁻² in charcoal filtered air in 2007 and from 46.4 to 62.1 mg m⁻² in 2008. Elevated ozone reduced grain yield by 11.3% and 12.4% in 2007 and 2008, respectively. Global warming potential (GWP) per unit of rice yield was the least under elevated ozone levels. Dissolved organic C content of soil was lowest under the elevated ozone treatment. Decrease in availability of substrate i.e., dissolved organic C under elevated ozone resulted in a decline in GHG emissions. Filtration of ozone from ambient air increased grain yield and growth parameters of rice and emission of GHGs.     

Potential ammonia emission from flag leaves of paddy rice (Oryza sativa L. cv. Koshihikari)

The present study aimed to investigate the potential ammonia (NH₃) emission from flag leaves of paddy rice (Oryza sativa L. cv. Koshihikari). The study was conducted at a paddy field in central Japan that was designed as a free-air CO₂ enrichment (FACE) facility for paddy rice. A dynamic chamber method was used to measure the potential NH₃ emissions. The air concentrations of NH₃ at two heights (2 and 6 m from the ground surface) were measured using a filter-pack method, and the exchange fluxes of NH₃ of the whole paddy field were calculated using a gradient method. The flag leaves showed potential NH₃ emissions of 25-38 ng N cm⁻² h⁻¹ in the daytime from the heading to the maturity stages, and they showed potentials of approximately 22 ng N cm⁻² h⁻¹, even in the nighttime, at the heading and mid-ripening stages. The exchange fluxes of NH₃ of the whole paddy field in the daytime were net emissions of 0.9-3.9 g N ha⁻¹ h⁻¹ whereas the exchange fluxes of NH₃ in the nighttime were approximately zero.     

城市生活垃圾露天焚烧PM2.5及其组分排放特征

利用稀释采样系统,针对桶内燃烧和自然堆积两种常见露天焚烧方式,分别对橡塑类、纸类和木竹类这3种组分生活垃圾露天焚烧PM_(2.5)排放特征进行实测,计算PM_(2.5)、OC、EC、水溶性离子和无机元素排放因子.结果表明,木竹类生活垃圾PM_(2.5)排放因子(7.44±0.76)g·kg~(-1)最高,纸类PM_(2.5)排放因子(2.72±0.52)g·kg~(-1)最低.桶内燃烧的条件会造成更多污染物排放.在不同的燃烧方式下,橡塑类和纸类生活垃圾在桶内燃烧的条件下PM_(2.5)排放因子是自然堆积燃烧的2.5~3.5倍.PM_(2.5)中OC和EC为主要组成成分,PM_(2.5)组分构成占比约为46.6%~67.2%.不同垃圾组分OC/EC比率差异较大,但该比率受焚烧条件影响较小,有助于解析不同组分垃圾焚烧排放贡献.水溶性离子中NH+4离子、Cl-离子含量最高,在PM_(2.5)中所占比例范围分别为2.28%~6.35%和1.04%~14.31%.无机元素中Ca、K、Fe和Ba元素排放因子较高.重金属元素中Zn元素排放因子最高,Cu、Cr、Sb和Pb等元素也有一定富集.Zn元素含量主要由燃烧方式决定,桶内燃烧大约是自然堆积燃烧的20倍左右.     

Characteristics and anthropogenic sources of carbonyl sulfide in Beijing

Atmospheric mixing ratios of carbonyl sulfide (COS) in Beijing were intensively measured from March 2011 to June 2013. COS mixing ratios exhibited distinct seasonal variation, with a maximum average value of 849 ± 477 pptv in winter and a minimal value of 372 ± 115 pptv in summer. The seasonal variation of COS was mainly ascribed to the combined effects of vegetation uptake and anthropogenic emissions. Two types of significant linear correlations (R² > 0.66) were found between COS and CO during the periods from May to June and from October to March, with slopes (ΔCOS/ΔCO) of 0.72 and 0.14 pptv/ppbv, respectively. Based on the emission ratios of COS/CO from various sources, the dominant anthropogenic sources of COS in Beijing were found to be vehicle tire wear in summer and coal burning in winter. The total anthropogenic emission of COS in Beijing was roughly estimated as 0.53 ± 0.02 Gg/year based on the local CO emission inventory and the ΔCOS/ΔCO ratios.     

Direct N2O emissions following transition from conventional till to no-till in a cover cropped Mediterranean vineyard (Vitis vinifera)

Knowing underlying practices for current greenhouse gas (GHG) emissions is a necessary precursor for developing best management practices aimed at reducing N₂O emissions. The effect of no-till management on nitrous oxide (N₂O), a potent greenhouse gas, remains largely unclear, especially in perennial agroecosystems. The objective of this study was to compare direct N₂O emissions associated with management events in a cover-cropped Mediterranean vineyard under conventional tillage (CT) versus no-till (NT) practices. This study took place in a wine grape vineyard over one full growing season, with a focus on the seven to ten days following vineyard floor management and precipitation events. Cumulative N₂O emissions in the NT system were greater under both the vine and the tractor row compared to CT, with 0.15 ± 0.026 kg N₂O-N ha⁻¹ growing season⁻¹ emitted from the CT vine compared to 0.22 ± 0.032 kg N₂O-N ha⁻¹ growing season⁻¹ emitted from the NT vine and 0.13 ± 0.048 kg N₂O-N ha⁻¹growing season⁻¹ emitted from the CT row compared to 0.19 ± 0.019 kg N₂O-N ha⁻¹ growing season⁻¹ from the NT row. Yet these variations were not significant, indicating no differences in seasonal N₂O emissions following conversion from CT to NT compared to long-term CT management. Individual management events such as fertilization and cover cropping, however, had a major impact on seasonal emissions, indicating that management events play a critical role in N₂O emission patterns.     

Composition and source apportionment of dust fall around a natural lake

The aim of this study was to determine the source apportionment of dust fall around Lake Chini, Malaysia. Samples were collected monthly between December 2012 and March2013 at seven sampling stations located around Lake Chini. The samples were filtered to separate the dissolved and undissolved solids. The ionic compositions(NO-3, SO2-4, Cl-and NH+4) were determined using ion chromatography(IC) while major elements(K, Na, Ca and Mg) and trace metals(Zn, Fe, Al, Ni, Mn, Cr, Pb and Cd) were determined using inductively coupled plasma mass spectrometry(ICP-MS). The results showed that the average concentration of total solids around Lake Chini was 93.49 ± 16.16 mg/(m2·day). SO2-4, Na and Zn dominated the dissolved portion of the dust fall. The enrichment factors(EF) revealed that the source of the trace metals and major elements in the rain water was anthropogenic, except for Fe. Hierarchical agglomerative cluster analysis(HACA) classified the seven monitoring stations and 16 variables into five groups and three groups respectively. A coupled receptor model, principal component analysis multiple linear regression(PCA-MLR), revealed that the sources of dust fall in Lake Chini were dominated by agricultural and biomass burning(42%),followed by the earth's crust(28%), sea spray(16%) and a mixture of soil dust and vehicle emissions(14%).     

基于遥感数据的秸秆焚烧源排放清单及时空分布特征

分析秸秆焚烧事件引起的空气污染状况,常使用CMAQ、NAQPMS、WRF-CHEM等模型进行空气质量模拟,而污染源排放清单是模拟模型的关键输入.为满足模型清单输入要求,以2014年5月7日四川盆地内发生的一次由油菜秸秆焚烧引起的重污染事件为例,采用排放因子法进行污染物年排放量估算,结合卫星火点数据、土地利用数据对其进行空间特征分析,并使用Bluesky CONSUME模型估算了污染物的烟羽抬升,结合激光雷达获取了气溶胶消光系数以分析其时间特征.结果表明:以2013年为基准年,全年区域内CO、NO_x、SO₂、PM_2.5、PM₁₀及NMVOC（非甲烷挥发性有机化合物）的年排放量分别为5 791.022、193.842、43.268、574.602、1 495.350和1 495.350 t,成都市、德阳市、绵阳市、眉山市、资阳市各污染物排放量占比分别为13.90%、22.39%、31.81%、12.11%、19.79%.各污染物排放量均在地面层呈3个大值中心、2个空值带的分布趋势.采用环境1B卫星和MODIS火点数据结合提取焚烧火点分析发现,5月7日四川盆地内5个城市均存在不同程度的秸秆焚烧情况.经空间分配后发现,此次排放的重点在德阳市及绵阳市南部,污染物排放量最大值出现在德阳市中部,成都市秸秆焚烧火点最少,污染物排放量也最小.受当天大气边界层高度的影响,污染物垂直分布主要集中在35 m以下,并在30 m左右形成污染物极大层.另外,受秸秆焚烧管制影响,在16:00-翌日04:00排放量呈逐渐上升趋势,09:00-16:00排放量较少.研究显示,秸秆焚烧源排放清单与前人研究结果较为一致,排放清单的烟羽抬升结果与气溶胶消光系数的垂直分布较为吻合.      

西宁市生物质燃烧源大气污染物排放清单

本研究根据调查的西宁市生物质燃烧源活动水平数据,采用排放因子方法,建立了 2018年西宁市生物质燃烧源9种大气污染物的排放清单,并分析了清单的时空分布特征和不确定性.结果表明,西宁市2018年生物质燃烧源CO、NOx、SO2、NH3、VOCs、PM2.5、PM10、BC 和OC 的排放量分别为 11 718.34、604.41、167.80、209.72、1 617.97、2 054.04、2 135.04、281.07和 1 224.78 t.秸秆露天焚烧 CO、NOx、VOCs、PM2.5、PM10、BC 和OC 的排放对生物质燃烧源的排放贡献率最高;其中,秸秆露天焚烧NOx、VOCs和CO的贡献率分别为72.35％、63.94％和53.18％.户用生物质炉NH3和SO2的排放对生物质燃烧源的贡献率最大,分别为41.49％和42.05％.生物质燃烧源大气污染物排放地区分布不均衡,主要集中于大通县和湟中区.生物质燃烧源9项污染物的排放量在1、2、3、10、11和12月较大,占比在5％～33％.蒙特卡罗模拟结果表明,在95％置信区间下,不确定度最高的是森林和草原火灾的PM2.5排放,不确定度为-26.71％～29.78％.     

长沙市人为源大气污染物排放清单及特征研究

根据收集的长沙市人为源活动水平数据,建立了该地区2014年1 km×1 km人为源大气污染物排放清单.结果显示,2014年长沙市SO_2、NO_x、CO、PM_(10)、PM_(2.5)、BC、OC、VOCs和NH_3排放总量分别为53.5×10~3、78.3×10~3、284.6×10~3、102.3×10~3、42.1×10~3、4.0×10~3、7.2×10~3、64.2×10~3、27.1×10~3t.化石燃料固定燃烧源为最大的SO_2排放贡献源,道路移动源是主要的NO_x贡献源,CO排放主要来自化石燃料固定燃烧源和道路移动源,长沙市VOCs的最大贡献源是溶剂使用源,PM_(10)、PM_(2.5)最主要的排放源是扬尘源,BC最大的排放贡献源为化石燃料固定燃烧源,生物质燃烧源是最大的OC贡献源,NH_3排放主要来源于畜禽养殖和农业施肥.空间分布结果显示,长沙市NH_3的排放在宁乡县、望城区、长沙县、浏阳市分布较多,主要呈现片状分布.其他污染物排放高值区则主要分布在中心城区、工业区及道路分布区域.     

Gaseous emissions from compressed natural gas buses in urban road and highway tests in China

The natural gas vehicle market is rapidly developing throughout the world, and the majority of such vehicles operate on compressed natural gas(CNG). However, most studies on the emission characteristics of CNG vehicles rely on laboratory chassis dynamometer measurements, which do not accurately represent actual road driving conditions. To further investigate the emission characteristics of CNG vehicles, two CNG city buses and two CNG coaches were tested on public urban roads and highway sections. Our results show that when speeds of 0–10 km/hr were increased to 10–20 km/hr, the CO_2, CO, nitrogen oxide(NO_x), and total hydrocarbon(THC) emission factors decreased by(71.6 ± 4.3)%,(65.6 ± 9.5)%,(64.9 ± 9.2)% and(67.8 ± 0.3)%, respectively. In this study, The Beijing city buses with stricter emission standards(Euro Ⅳ) did not have lower emission factors than the Chongqing coaches with Euro Ⅱ emission standards. Both the higher emission factors at 0–10 km/hr speeds and the higher percentage of driving in the low-speed regime during the entire road cycle may have contributed to the higher CO_2 and CO emission factors of these city buses. Additionally, compared with the emission factors produced in the urban road tests, the CO emission factors of the CNG buses in highway tests decreased the most(by 83.2%), followed by the THC emission factors, which decreased by 67.1%.     

Role of secondary aerosols in haze formation in summer in the Megacity Beijing

A field experiment from 18 August to 8 September 2006 in Beijing, China, was carried out. A hazy day was defined as visibility < l0 km and RH (relative humidity) < 90%. Four haze episodes, which accounted for ~ 60% of the time during the whole campaign, were characterized by increases of SNA (sulfate, nitrate, and ammonium) and SOA (secondary organic aerosol) concentrations. The average values with standard deviation of SO₄^2 −, NO₃⁻, NH₄⁺ and SOA were 49.8 (± 31.6), 31.4 (± 22.3), 25.8 (± 16.6) and 8.9 (± 4.1) μg/m³, respectively, during the haze episodes, which were 4.3, 3.4, 4.1, and 1.7 times those in the non-haze days. The SO₄^2 −, NO₃⁻, NH₄⁺, and SOA accounted for 15.8%, 8.8%, 7.3%, and 6.0% of the total mass concentration of PM₁₀ during the non-haze days. The respective contributions of SNA species to PM₁₀ rose to about 27.2%, 15.9%, and 13.9% during the haze days, while the contributions of SOA maintained the same level with a slight decrease to about 4.9%. The observed mass concentrations of SNA and SOA increased with the increase of PM₁₀ mass concentration, however, the rate of increase of SNA was much faster than that of the SOA. The SOR (sulfur oxidation ratio) and NOR (nitrogen oxidation ratio) increased from non-haze days to hazy days, and increased with the increase of RH. High concentrations of aerosols and water vapor favored the conversion of SO₂ to SO₄^2 − and NO₂ to NO₃⁻, which accelerated the accumulation of the aerosols and resulted in the formation of haze in Beijing.     

海峡西岸地区人为源大气污染物排放特征研究

采用以"自下而上"为主的方法建立了2007年海峡西岸地区的人为源大气污染物排放清单.计算结果显示,海西地区人为源SO2、NOx、CO、PM10、PM2.5、VOCs和NH3排放总量分别为69.5×104、96.1×104、413.1×104、93.9×104、40.6×104、85.0×104和28.5×104t.电厂和工业燃烧设施分别占SO2排放的48%和39%,以及NOx排放的51%和25%.水泥、砖瓦等制造过程贡献了约51%的PM10排放和36%的PM2.5排放.秸秆燃烧、加油站和涂料等VOCs面源分别占到其排放总量的27%、15%和4%.NH3的主要排放源为畜禽养殖和氮肥施用等农业部门,占到总排放量的89%.海西地区的单位面积大气污染物排放量仅相当于长三角地区的25%左右,略高于全国平均水平.该地区人为源和天然源VOCs排放比重分别占56%和44%,人为源VOCs排放比重低于全国大部分地区.海西大气污染高排放地区主要集中在沿海一带,以泉州、潮汕、福州和温州等地区为主,建议"十二五"发展过程中,重点关注上述高排放地区,限制重点排放源的发展,开发低耗能、低污染的发展模式.     

The potential to increase soil carbon stocks through reduced tillage or organic material additions in England and Wales: A case study

Results from the UK were reviewed to quantify the impact on climate change mitigation of soil organic carbon (SOC) stocks as a result of (1) a change from conventional to less intensive tillage and (2) addition of organic materials including farm manures, digested biosolids, cereal straw, green manure and paper crumble. The average annual increase in SOC deriving from reduced tillage was 310 kg C ± 180 kg C ha⁻¹ yr⁻¹. Even this accumulation of C is unlikely to be achieved in the UK and northwest Europe because farmers practice rotational tillage. N₂O emissions may increase under reduced tillage, counteracting increases in SOC. Addition of biosolids increased SOC (in kg C ha⁻¹ yr⁻¹ t⁻¹ dry solids added) by on average 60 ± 20 (farm manures), 180 ± 24 (digested biosolids), 50 ± 15 (cereal straw), 60 ± 10 (green compost) and an estimated 60 (paper crumble). SOC accumulation declines in long-term experiments (>50 yr) with farm manure applications as a new equilibrium is approached. Biosolids are typically already applied to soil, so increases in SOC cannot be regarded as mitigation. Large increases in SOC were deduced for paper crumble (>6 t C ha⁻¹ yr⁻¹) but outweighed by N₂O emissions deriving from additional fertiliser. Compost offers genuine potential for mitigation because application replaces disposal to landfill; it also decreases N₂O emission.