A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China

Zhou, Ying; Xing, Xiaofan; Lang, Jianlei; Chen, Dongsheng; Cheng, Shuiyuan; Wei, Lin; Wei, Xiao; Liu, Chao

doi:https://doi.org/10.5194/acp-17-2839-2017

Articles | Volume 17, issue 4

https://doi.org/10.5194/acp-17-2839-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

East Asia emissions assessment (EA2)

https://doi.org/10.5194/acp-17-2839-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 4

Research article

|

23 Feb 2017

Research article |

| 23 Feb 2017

A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China

Ying Zhou, Xiaofan Xing, Jianlei Lang, Dongsheng Chen, Shuiyuan Cheng, Lin Wei, Xiao Wei, and Chao Liu

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Final revised paper (published on 23 Feb 2017)
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Preprint (discussion started on 19 Jul 2016)
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China', Anonymous Referee #1, 15 Aug 2016
- AC1: 'Interactive comment on "A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China" by Y.Zhou et al.', Ying Zhou, 02 Nov 2016
RC2: 'Review of “A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China”', Anonymous Referee #2, 30 Aug 2016
- AC2: 'Interactive comment on "A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China" by Y.Zhou et al.', Ying Zhou, 02 Nov 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Ying Zhou on behalf of the Authors (21 Nov 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (05 Dec 2016) by Gregory Frost

RR by Anonymous Referee #2 (22 Dec 2016)

Suggestions for revision or reasons for rejection

In this revised manuscript the authors have thoroughly addressed all my comments and concerns with the original manuscript. I believe the manuscript is suitable for publication following minor revisions described below.

In many places I found myself a bit confused by the usage of crop straw, unsure if the authors were referring to in-field burning of crop residue or domestic burning. I suggest the authors consistently use “in-field straw” to describe in-field burning of crop straw and consistently use “domestic straw” when referring to domestic burning of crop straw. I imagine the authors use “crop residue” since not all crop residue is straw, e.g. residue from potatoes, beets, peanuts, and cotton. This should be clarified early on for the readers. Where the author are referring to all in-field burning of crop residue types they should consistently use “in-field crop residue” not “in-field straw”.

In the manuscript text the authors need to define all chemical formulas upon their first use, e.g. at
P2, L13 “Active trace gases (e.g., SO2, NOx, NMVOCs, NH3) released from biomass burning are the major precursors of…” and other places in the Introduction.

Frequent use of “higher” when authors should use “largest” or “highest” or need an explicit comparison, for example:
P1 L25 “…wheat straw burning has higher contribution to CO and Hg emissions.” – “higher” compared to what?
P1 L26: “Heilongjiang, Shandong, and Henan provinces located in northeast and central-south region of China have higher emissions.”
And similar misuse n many other places. These instances need to be corrected.

P1 L21-22: Based on Figure 2, perhaps state that: “Domestic straw burning is the largest source of biomass burning emissions for all the pollutants considered except for NH3, EC (firewood), and NOx (in-field crop residue)”

P1 L 24: “As for the straw burning emission of various crops, corn straw burning has the largest contribution to EC, NOx and SO2 emissions”
Here any EVERYWHERE else specify “in-field” or “domestic” straw burning.

P2, L2: “The temporal distribution shows that April, May, June and October are the top four months with higher emissions, due to the in-field crop residue burning.”
This statement is a bit confusing as written and not too useful once deciphered. Change to something like: “The months of April, May, June and October account for X% of emissions from in-field crop residue burning”.

P2, L3: “While as for EC, the emission in February, January, October and December are relatively higher due to the biomass domestic burning in heating season.”
See previous comment.

P2, L4: “There’s regional difference in monthly variation due to the diversity of main planted crop and the climate conditions.”
“Variation” of what? Please clarify.

P2, 13: Biomass burning emission have an important role in climate system, independent of anthropogenic forcing / change. Suggest delete “change”
P5, L25: Since E and A are in units of Mg/yr and EF is in units of g/kg, the equation should multiplied by 0.001 (.001 kg per g). This must be a typo as the emission estimates in this study are similar to other inventories (Fig 10) and not high by a factor 100,000.

P10, L2-4: This first two sentences are awkward and bit confusing. I believe the authors intend something like: “Detailed speciation of NMVOC and PM2.5 emissions in necessary to model gas and aerosol chemistry and simulate the impact of biomass burning on atmospheric composition and it has received extensive attention by domestic scholars in recent years (refs…)”

P10 L18-19: Based on Figure 2, perhaps rephrase to stress that domestic straw burning is the largest source of biomass burning emissions for all the pollutants considered except for NH3, EC (firewood), and NOx (in-field crop residue).

P11, L15-17: “Among the various crops, corn straw burning has large contribution to all of the chemical species except for CH4. Rice straw has the largest contribution to CO2, NMVOC, CH4 and NH3 emissions, accounting for 32.90%, 32.43%, 31.61% and 30.12%, respectively;..”
These statements are contradictory. Which has the larger contribution corn or rice? Should this read “corn straw burning has the largest contribution to all of the chemical species…” and “Rice straw has the second largest contribution to…”?

P1, L21-22: “In addition, Fig. 3a and Fig. 3b indicate that for most of the chemical species, the contribution of in-field corn residue burning is larger than that of domestic burning, except for SO2, EC and CO2.”
This statement is incorrect. Figure 3a and Figure 3b show percentages within groups (in-field and domestic). The magnitudes of emissions from in-field and domestic cannot be inferred from Fig 3a and Fig 3b. This statement must be supported by a different figure or table.

P11, L22-24: “Contrary to that for corn straw, emissions of all chemical species (except for SO2, NOx and EC) from wheat straw domestic burning is greater than those from in-field crop residue burning. For rice straw, the contribution of in-field crop residue burning to NOx, PM10, PM2.5, NMVOC, EC and OC emissions is larger than domestic burning.”
These statements are cannot be supported by Figure 3. Please refer the reader to figures or tables that support these statements.

Technical
The manuscript has may instances where English usage needs to be improved. Here is a list of some, but not all instances.
P3, L1: insert “frequently” between “more” and “burned”
P3, L10: insert “associated” between “the” and “environmental”
P3, L12: change “inventory” to “inventories”
P3, L24: spelling, change “in-filed’ to “in-field”
P6, L22: Maybe change “investigation” to “review”
P6, L22: change “collect” to “estimate” or “derive”
P9, L3: change “research” to “review”
P9, L6: insert “burning” between “biomass” and “emission” and change “emission” to “emissions”
P10, L5: new paragraph not needed.
P10, L16: delete “the” before “domestic straw…”
P11, L10: delete “change” it is not needed, see earlier comment for P2, L13.
P12, L8: change “shown” to “provided”
P14, L 7: Change “The most of high values” to “Most of the high values”
P15, L6: Change “Figure 8 shows the 12 species emissions in each month…” to “Figure 8 shows the monthly emissions of all 12 species considered”
P15, L7-8: “Besides, the in-field burning of crop residue mainly in the harvest season and thus shows the obvious monthly variation features.”
This statement is unclear and needs to be rewritten. Do the authors mean to say that “the monthly variability in in-field emissions reflects the timing of the harvest seasons”?
P16, L16: change “The total PM2.5 emission of biomass burning emission …” to “Total PM2.5 emissions from biomass burning…”
P18, L11: change “The emission involves…” to “The emission inventory includes…”

Figure 2 caption: add “s” “source” and delete “the”
Figure 6d caption is awkward change to something like: “The distribution of county level annual PM2.5 emissions”

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RR by Anonymous Referee #1 (10 Jan 2017)

Suggestions for revision or reasons for rejection

Page 8 Line 23-26: As for CF, it has usually been set as a constant in previous literature. In our paper, CF values were collected for each vegetation type, and the CF in each pixel was determined by the MODIS Land Cover product and the CF of typical vegetation. The CF of the forest, closed shrublands, open shrublands, woody savannas, and grassland were set as 0.25, 0.5, 0.85, 0.4, and 0.95, respectively (Michel et al., 2005; Kasischke et al., 2000; Hurst et al., 1994).
The constant CF can not reflect the spatial variation on the fraction of burned aboveground biomass when a fire happens. CF was controlled by both land cover type and moisture condition. Land cover type decides the maximum and minimum of the combustion efficiency. But the moisture condition determines how much the fuel can be burned during fires. If the fuel is too dry, almost 90% can be combusted, but when it is too wet, only 5% can be burned (van der Werf et al., 2006; 2010). This condition (ranging from 5 to 90%) significantly affects the final emission estimation. Many existing studies dealed with the problem by using vegetation fraction, leaf area index or NDVI to reflect the real condition of CF pixel by pixel since they vary greatly (Zhang et al., 2008, Atmos Environ).

Human waste open burning accounted for a large proportion in developing countries due to without efficient burning facility, especially in rural area. China is a good example. The study from Wiedinmyer et al. (2014) estimated the global emissions of trace gases, particulate matter, and hazardous air pollutants from open burning of domestic waste, China is the largest contributor worldwide. Please refer to the large emissions from this part.

The Monta Carlo model was used to allocate the uncertainty. How did the author run this model? There is a strange phenomenon in this process since the input data for emission estimate are very with Street et al (2003) and van der Werf et al. (2006; 2010), Huang et al. (2011). And the uncertainties you defined in this study is the same with others, therefore, how the uncertainty ranges are so narrow than the others? That means why your estimation has more confidence than others. This is unbelievable.

The author stress the Emission Factors (EF) in their study. The emission factors indeed have spatial variations with geographical characteristics. I welcome the authors to employ the regional EF to reflect the real condition. All EF actually can only be derived from experiment, the authors just used the EF from literature. Your study China covers a large area with strong geographical characteristics, the EF in different ecosystem located in different climatic zones vary greatly. Only one EF value cannot reflect the real situation in China.
The authors contributed their originality to the other studies by highlighting the employed EF in China, but the EF you used actually has minor differences or we can say they are identical to many studies outside China (Andreae and Merlet, 2001; Akagi et al., 2011). therefore, you cannot conclude assertively at Page 20 Line 3-5 below.
Though the uncertainty exists in this study, compared with the limited research of national and comprehensive emission with uncertainty analysis (Table 8), our emission inventory is relatively reliable due to the selection of localized and specific crop EFs.

Besides, the emission is calculated by using activity data and emission factors. Before excluding the potential different activity data between this study and others, it is irresponsible to judge a conclusion that localized EF is the only reason that contributes your emissions comparable to others.

Figure 7 has a fundamental serious problem. Based on the reply from the authors, we think that . But please refer to the urban center of Beijing, the PM2.5 annual emissions is very low, there was scarce open burning, firewood burning. But comparing to other counties in North China Plain, their amounts are similar to Beijing. If you attribute the low emission in Beijing center to its urban area. That means the counties with low emissions in Shangdong, Jiangsu and Anhui provinces are all urban areas, which are larger than Beijing. This is a paradox. The strange results appeared many polygons with obvious administrative boundaries, where the emissions were significantly lower than its surrounding areas. The authors failed in improving this figures and understanding the real meaning.
Please refer to Huang et al. (2011) on biomass burning emissions in China.

The author stressed the updated biomass burning emissions in China. The study period was selected to be 2012. There is no sign to show the reason for 2012 selection. A comprehensive biomass burning emissions inventory lasting for only one year has little implications. China released strict controls and restrictions on its open biomass burning recently with the decreasing amount of crop residue burning from year to year, therefore, only one-year emission inventory has no meaning.

In Figure 9, the largest monthly variations of the PM2.5 were found in in-field straw. Actually the in-field straw has strong seasonal variations peaking during field crop rotation twice or three times within a year. The farmer burns the residue for land clearing for next plantation. That means at least two peaks can be found on emissions. And then the emissions will be very low. But we cannot find the monthly variations in the South.

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ED: Reconsider after minor revisions (Editor review) (10 Jan 2017) by Gregory Frost

AR by Ying Zhou on behalf of the Authors (20 Jan 2017) Author's response Manuscript

ED: Publish subject to technical corrections (23 Jan 2017) by Gregory Frost

AR by Ying Zhou on behalf of the Authors (30 Jan 2017) Manuscript

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Short summary

A 1 km gridded and comprehensive biomass burning emission inventory including domestic and in-field straw burning, firewood burning, livestock excrement burning, and forest and grassland fires is developed for mainland China in 2012 based on county-level activity data, satellite data, and updated source-specific emission factors. The detailed emission inventory could provide useful information for air-quality modelling and supports the development of appropriate pollution-control strategies.